Download Brain regions involved in heading estimation and steering control in

Brain regions involved in heading estimation and
steering control in a virtual environment
Anita Liu, MSc candidate
Faculty of Medicine
Department of Neurology & Neurosurgery
McGill University, Montréal
December 2012
A thesis submitted to McGill University
in partial fulfillment of the requirements of the degree of
Master of Science (Neurological Sciences)
© Anita Liu 2012
Table of Contents
TABLE OF CONTENTS……………………………………………………………….. ii
Index of Figures………………………………………………………………...……….. iv
Index of Tables………………………………………………………………………...... v
Abstract….………………………………………………………………………………. vi
Abrégé…………………………………………………………………………………… vii
Acknowledgements…………………………………………………………………...….. ix
PREFACE………………………………………………………………………………. x
Structure of thesis…………………………………………………………….……...…... x
Contribution of authors……………………………………………………………...…... x
CHAPTER 1: INTRODUCTION & OBJECTIVES………….…………………………. 1
1.1 Background…………………...…...…………………………………………….…….. 2
1.2 Visuomotor control of locomotion…..………………………………………….…….. 3
1.3 Brain Regions used in Optic Flow Perception: Primate Studies………………..….….... 7
1.4 Human Brain Regions used in Optic Flow Perception: imaging studies………….….... 10
1.5 Steering Strategies………………………………………………………………....….. 14
1.6 Human Brain Regions required for Heading and Steering……………………......…… 15
1.7 Summary & Rationale for the present project…………….…………………………... 18
1.8 Study Purposes & Hypotheses……………………………………………………….. 19
CHAPTER 2: Manuscript..…..….…………….…………….…………....…….………… 20
Brain regions involved in heading estimation and
control of steering in a virtual environment…..……………………………………...…… 21
Abstract & Keywords……………………………....…………………………………….. 22
1: Background & Objectives……………………………………………………………... 23
2: Methods & Procedures…...…………..………………………………………………... 26
2.1 Participants……......……..……………………………………..…………..…. 26
2.2 Apparatus……………...………………………………..……………………. 26
2.2.1 Virtual environment……………....……………….….……………………….. 26
2.2.2 fMRI scanner & acquisition………………………………………….................. 27
2.3 Procedure……………………………………...……..………………………. 28
2.3.1 Training session……………………………………….……………………..... 28
2.3.2 Experimental design……….………………..…………………………….......... 29
2.3.3 Heading Discrimination task.….…………………………………...………........ 29
2.3.4 Steering task..…………...……………………………………………………. 29
2.3.5 Motor & Visual Perceptual ………………….………………………...……… 29
2.3.6 Passive viewing task………….………….…………………………...……….... 30
2.3.7 Rest/Perceptual task……….…….…………………………………………… 30
2.3.8 fMRI analysis…………………………….…...……………………………… 30
ii
3: Results………………………………………………………………………………… 32
3.1 Behavioral results…………………………………………...………………... 32
3.2 Imaging results…………………………………….………………..………... 32
3.2.1 Passive Viewing………………………………….………………..………....... 32
3.2.2 Heading discrimination……………………………………………………….... 33
3.2.3 Steering……………………………………………………………………… 33
4: Discussion……………………………………………………………………...…….... 35
4.1 Passive Viewing of optic flow………………………………………...…..…... 36
4.2 Heading discrimination………………………………………………………. 36
4.3 Steering………………………………………………………………………. 38
4.4 Design limitations……………………………………………………….…… 41
4.5 Conclusion & Future Directions………………………………………………42
Acknowledgements……………………………………………………………………… 43
References……………………………………………………………………………..… 43
Figure captions…………………………………………………………………………... 52
Table captions…………………………………………………………………………… 53
Figures………………………………………………………………………………….... 54
Tables……………………………………………………………………………………. 58
CHAPTER 3: CONCLUSIONS………………………………………………………… 61
REFERENCES……………………………………………………………..………...…. 63
APPENCIDES…………………………………………………………………..…......... 78
Appendix I : Consent form (English)………………….………………………...…....…... 79
Appendix II: MRI Screening form…….…………………………………………………. 86
Appendix III : Experimental design…………..…………………………………...…...…. 88
Appendix III : Varying virtual scenes………………………………………………........... 89
iii
Index of Figures
Introduction
Figure 1. Optic flow and focus of expansion during locomotion…………….….....……... 4
Figure 2. A simplified schematic overview of how motion is processed in our central
nervous system………………………………………….....................................…9
Figure 3. A simplified schematic overview of how optic flow perception is transformed
into motor execution…………………..……………………….……….………10
Manuscript
Figure 1. Virtual environment……………………………………………………………. 54
Figure 2. Activations for contrast
“Heading discrimination – Motor/Perceptual” ………………………………… 55
Figure 3. Activations for contrast
“Steering – Motor/Perceptual” vs. “Heading discrimination – Motor/Perceptual”
……………………………………………………………………………...…. 56
Figure 4. Key activations in all three contrasts…………………………………………… 57
iv
Index of Tables
Introduction
Table 1. Summary of activated human brain regions elicited by optic flow stimuli……..13
Table 2. Summary of activated human brain regions elicited by a heading task…...…….16
Table 3. Summary of activated human brain regions elicited by a steering task.…….…..17
Manuscript
Table 1. Peak activations for contrast
“Heading discrimination – Motor/Perceptual”………………………..……… 58
Table 2. Peak activations for contrast
“Steering – Motor/Perceptual”…………………………………….………...... 59
Table 3. Peak activations for contrast “Steering – Heading discrimination”……………. 60
v
Abstract
The brain regions required for judging heading direction and actively steering towards a goal
could be damaged by stroke. Identifying the neural correlates responsible for goal-directed
locomotion is important for the understanding of the mechanism underlying neuroplasticity
and functional recovery. Past research shows that when we are walking through a texturerich environment, we primarily use optic flow, a radially expanding pattern of motion, to
accurately discriminate our heading direction and steer towards a goal. The purpose of this
study was to investigate the different brain regions involved in heading discrimination and
steering using an ecological virtual environment, mimicking most environments we walk
through in everyday life. Fourteen participants (7 males, 7 females) took part in an fMRI
study where their BOLD responses were measured while they completed a heading
discrimination and active steering tasks using a joystick. A cluster level inference was
conducted and clusters that were statistically significant above a threshold of Z=4 (p<0.01)
were identified. This study investigated which brain regions display higher BOLD responses
in the heading discrimination and steering task, independent of motor movements from
joystick input. Consistent with previous studies, the bilateral intraparietal sulcus is involved
in heading discrimination and bilateral posterior cerebellum was observed in the steering
task. Further analysis revealed that the hMT+ and V2, the bilateral cerebellum,
supplementary eye fields, premotor cortex, and supplementary motor area, displayed higher
BOLD responses in the steering task than in the heading discrimination task. These results
suggest that although heading discrimination involves a certain degree of sensorimotor
integration and optic flow processing, steering is a more demanding task, requiring more
brain regions to transform dynamic optic flow information into context-adapted motor
responses.
vi
Abrégé
L’indentification des régions du cerveau humain, requises pour juger la direction
choisie et s’orienter activement vers notre but, pourrait aider à comprendre le fait que ceux
qui ont eu un AVC ont des difficultés avec la locomotion orientée vers un but. Des études
antérieures ont démontré que lorsque nous marchons dans un environnement avec des
textures riches, nous utilisons principalement le flux optique, un modèle de mouvement
d’expansion radiale, pour discerner avec précision la direction choisie et de se diriger vers
une cible. Le but de cette étude était d’investiguer quelles régions du cerveau sont impliquées
dans la discrimination et dans le contrôle de la direction (pilotage) en utilisant un
environnement virtuel écologique qui ressemble à la plupart des environnements dans
lesquels nous évoluons dans la vie quotidienne. Quatorze personnes (7 hommes, 7 femmes)
ont participé à une étude de IRMf où leurs réponses BOLD ont été mesurées pendant qu’ils
complétaient une tâche de discrimination et une tâche active de pilotage à l’aide d’une
manette de commande, en réponse à des flux optiques de différentes directions. Une
inférence de groupe a été réalisée et ceux statistiquement significatifs au-dessus d’un seuil de
Z=4 (p<0.01) ont été identifiés. Cette étude portait sur les régions du cerveau qui ont
affiché des réponses BOLD plus élevées dans les tâches de discrimination de la direction et
de pilotage, indépendamment des réponses motrices associées aux mouvements de la
manette de commande. Le sillon interpariétal (divisions antérieure et postérieure) a été
impliqué bilatéralement dans la tâche de discrimination et une activation bilatérale du
cervelet postérieur a été observée dans la tâche pilotage. D’autres analyses ont démontré que
le complexe hMT+ et V2, des régions impliquées dans le traitement du flux optique, des
régions bilatérales dans le cervelet, le cortex prémoteur et l’aire motrice supplémentaire
vii
présentaient des réponses BOLD plus élevées dans la tâche de pilotage que dans la tâche de
discrimination. Ces résultats suggèrent que même si la discrimination de la direction implique
un certain degré d’intégration sensorimotrice et de traitement du flux optique, le pilotage est
une tâche plus exigeante nécessitant davantage de régions du cerveau pour transformer les
informations dynamiques du flux optique en réponses motrices adaptées aux exigences
contextuelles.
viii
Acknowledgments
I would like to first and foremost thank my thesis supervisor, Dr. Anouk
Lamontagne, for her guidance and confidence in my potential as a researcher. Many thanks
to Mr. Rick Hoge, my co-supervisor, who had always encouraged me to ask questions, Dr.
Joyce Fung and Dr. Julien Doyon for their valuable feedback on the manuscript, and to Dr.
Kathy Mullen, my mentor, who has been a great source of wisdom on matters in and outside
of the ivory tower. Graduate studies can sometimes be a difficult endeavor due to the
intellectual and emotional demand on the student; but having supportive supervisors and a
great mentor has not facilitated the learning process, but has made the overall experience a
memorable one.
I would also like to thank Christian Beaudoin, André Cyr, Andrei Garcia-Popov,
Valeri Goussev, Carollyn Hurst, and Cécile Madjar for their patience, technical support, and
dedication to the project. I am grateful to not only have had the opportunity to work with
them, but to have also gained their friendship.
Last but most certainly not least, I would like to thank my friends and family. My
friends at the Montreal Neurological Institute have shown great compassion and support
during my leave of absence. They also welcomed me to the city, helped me settle in, and
showed me warmth in an environment that can sometimes be cold. Colleagues and friends at
the Jewish Rehabilitation Hospital have also enriched my graduate experience with their
insights, unique experiences, and friendship. Also, sincerest thanks and mention to my
friends from the Neuroscience program. I have learned a lot from their diverse experiences
and am grateful to have had the opportunity to meet such kind and talented individuals. My
three sisters, Wendy, Diana, and Karen has also been a great deal of support and most
importantly my mom and dad, who inspired and led me to become the person I am today.
ix
________________________________________________________________________
PREFACE
________________________________________________________________________
Structure of Thesis
This is a manuscript-based thesis and is to be submitted to NeuroImage. The
manuscript provides a concise overview of the purpose of the study, methods, results, and
conclusions. A detailed literature review precedes the manuscript in Chapter 1. Chapter 1
discusses how and why heading discrimination and steering are critical components to
achieve goal-direction locomotion, how vision aids in locomotion, and which brain regions
have been implicated in processing visual information associated with heading discrimination
and steering. The rationale is stated in light of past findings and the hypotheses are
highlighted in Chapter 1. Following the manuscript, conclusions and future directions are
summarized in Chapter 3.
Contribution of Authors
My thesis supervisor, Dr. Anouk Lamontagne, supervised the conductance of this
project and was responsible for its inception. Mr. Rick Hoge, Dr. Julien Doyon, and Dr.
Joyce Fung has contributed intellectually to the experimental design and provided valuable
insight on data analysis & interpretation, quality assurance, and manuscript drafting. I acted
as the principle investigator and have contributed intellectually in the experimental design,
participant recruitment, data collection and analysis, interpretation of the results, and
manuscript drafting.
x
Chapter 1
Introduction & Objectives
____________________________________________________________________
CHAPTER 1
Introduction & Objectives
____________________________________________________________________
1.1 Background
Steering refers to the ability to control one’s direction of movement by adjusting our
body orientation and it is a critical component of goal-directed locomotion. Steering enables
us to walk and arrive accurately to our intended goal in space by anticipating our future path
and avoiding obstacles along the way. Although steering may seem effortless and automatic
to healthy individuals, our brain carries out complex computations such as integrating sensory
information from our vestibular, visual, and proprioceptive sensory systems (Ivanenko,
Grasso, Israel, & Berthoz, 1997; Warren, Kay, Zosh, Duchon, & Sahuc 2001; Wilkie & Wann,
2005). This allows us to execute the appropriate motor response by providing us with
information about our relative body orientation in space.
Impairment in the ability to steer, as it is observed in people with central nervous
system (CNS) lesions (e.g. Lamontagne, Fung, McFadyen, Faubert, & Paquette, 2010), will
consequently alter the ability to modify the walking trajectory and arrive accurately at the
desired goal. It is also reasonable to assume that an alteration in heading discrimination, which
is the process of identifying which direction we perceive ourselves to be moving in, will also
lead to alter locomotor steering abilities. Despite the importance of steering in everyday life,
however, very few studies have investigated the neural correlates required for steering (Field,
Wilkie, & Wann, 2007), as well as brain areas involved in heading discrimination (Peuskens,
Sunaert, Dupont, Van Hecke, & Orban, 2001; Billington, Field, Wilkie, & Wann, 2010; Field
et al., 2007). In addition, the brain imaging studies that used heading discrimination or
2
steering tasks were done in non-ecological environments, which may not reflect most
environments we walk through in everyday life.
Heading discrimination and steering are two different components of goal-directed
locomotion. Heading discrimination does not involve any changes in walking trajectory
whereas steering is the behavioral component of goal-directed locomotion, which requires
constant context-adapted locomotive behavior. Thus, it is likely that steering activates a more
extensive neural network in addition to the brain regions required for heading discrimination.
Identifying which brain regions are involved in locomotive steering and heading
discrimination, using a texture-rich ecological environment, may help us understand why
those afflicted by CNS lesions have difficulty walking.
1.2 Visuomotor Control of Locomotion
Community ambulation requires us to adapt our locomotor strategy in response to
changing contextual demands. Beyond the different neural systems responsible for the
maintenance of upright posture (Duffy & Wurtz, 1996) and rhythmic activation of the limb
(Purves, Augustine, & Fitzpatrick, 2004), locomotor adjustments also involve an extended
neural network associated with cognitive, perceptual and sensorimotor processes (Knill,
Maloney, & Trommershäuser, 2007). For instance, judging changes in our locomotor
trajectory, also referred to as heading discrimination, and steering our body to avoid obstacles
along the path, is needed to arrive at our desired destination. Vision is a powerful source of
sensory information as it provides us with real-time information about the characteristics of
our environment; together with the proprioceptive and vestibular systems, it provides
information about self-motion.
Gibson (1958) is credited as the first researcher to address how we use visual motion
perception to guide self-motion. Gibson argued that the perception of self-motion is primarily
3
guided by optic flow, which is defined as the visual motion we perceive as we move through a
static environment. This visual motion is created by the surfaces, textures, and contours of
our environment; when we walk, these cues will create a radially expanding pattern of motion
on our retina and motion trajectories that expand from a focus of expansion (FOE) in the
direction the observer is moving in (Warren et al., 2001; Figure 1). The optic flow theory
stipulates that we steer toward a goal by aligning the FOE with our desired heading direction
(Gibson, 1950), which aids us in reaching our goal in space.
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Figure 1. As we walk forward, a radially expanding pattern of motion is created from the
contours, textures, and surfaces of our environment; this is known as optic flow. Optic flow
expands from a focus of expansion (FOE), which is normally located in the direction of
heading. The optic flow theory stipulates that one steers toward the desired direction by
aligning the FOE with the goal. Picture taken by A. Liu.
4
Not all studies on human locomotion (Rushton, Harris, Lloyd, & Wann, 1998; Harris
& Bonnas, 2002) support Gibson’s claim that optic flow guides human locomotion and
proposed instead an egocentric hypothesis, which hypothesizes that goal-directed locomotion
can be achieved when an observer aligns his or her body with the goal without optic flow
aiding the observer. These discrepant findings were later explained by a hallmark study
conducted by Warren and colleagues (2001), which demonstrates that optic flow is the
primary contributor to achieve goal-directed locomotion when an environment is texture-rich.
They found that when no optic flow is available, participants arrived at a goal by using the
egocentric strategy, although with a substantially higher degree of error when compared to
walking with optic flow available. Furthermore, participants displayed increased reliance on
optic flow to reach a target when optic flow was available, reaching heading errors below 2o
from the intended goal. Similarly, Turano and colleagues (2005) found that optic flow
decreases heading errors by 42% in those without any visual impairment compared to 16% in
those with center field vision lost that prevented them from using optic flow information to
aid in heading discrimination. Other studies have shown that healthy adults are able to
accurately discriminate heading direction within 1o accuracy using optic flow (Warren, Morris,
& Kalish, 1988; van der Berg, 1992). Collectively, these observations indicate that optic flow
can be used to discriminate heading direction and steer toward the desired direction as we
walk. In healthy young individuals, this task can be accomplished with high accuracy.
Although healthy young adults are able to discriminate heading with high accuracy,
aging and the presence of CNS pathologies has been shown to affect the ability to use optic
flow for accurate heading judgment and influence steering behavior. When compared to
young healthy adults, older healthy adults display larger errors in heading discrimination in the
presence of optic flow created from translational and curvilinear movements (Warren,
5
Blackwell, & Morris, 1989). The ability to accurately discriminate heading direction was also
shown to be further altered in persons with Alzheimer’s Disease (Kavcic, Vaughn, & Duffy,
2011), Parkinson’s Disease (Young et al., 2010), stroke (Billino, Braun, Böhm, Bremmer, &
Gegenfurtner, 2009) and children with mild traumatic injuries (Brosseau-Lachaine, Gagnon,
Forget, & Faubert, 2008) compared to age-matched controls, indicating that events or disease
that compromise the CNS integrity have high potential to alter such abilities.
Healthy aging also affects the ability to adapt to changes in optic flow direction while walking
(Berard, Fung, McFadyen, & Lamontagne, 2009; Huitema, Brouwer, Mulder, Dekker, &
Postema, 2005). The ability to steer accurately in response to changing optic flow directions is
also more severely affected in those afflicted by CNS lesion such as stroke (Lamontagne et al.,
2010).
The mechanisms by which older adults and persons with a CNS lesion present with
altered heading discrimination and steering accuracy in response to optic flow changes are not
fully understood. Those with CNS lesions may present damage in optic flow processing
centers, such as the human middle temporal complex (hMT+; Braun, Petersen, Schonle, &
Fahle, 1998; Vaina, Cowey, Eskew, LeMay, & Kemper, 2001), and the parietal lobe, which is
needed for multi-sensory integration (Macaluso & Driver, 2005; Meehan & Staines, 2009).
Difficulty in sensorimotor integration (Lamontagne, Paquette, & Fung, 2007; Lamontagne &
Fung, 2009) and an over reliance on visual cues (Lord & Webster, 1990; Lord et al. 2006) that
are misperceived to start with (Warren et al., 1989), may also play a role. Given that the exact
neural substrates involved in accurate heading discrimination and steering are still unknown,
the focus of this thesis is to investigate the brain regions that are selectively involved in
discrimination of heading from optic flow and the control of steering.
6
The following sections will review relevant primate work, brain imaging studies, and
brain lesion studies that inform us on the neural correlates of heading discrimination and the
control of steering while exposed to expanding optic flows of different directions, as
experienced during locomotion. Behavioral responses of participants when walking in virtual
environment describing optic flow expanding from different FOE locations will also be
presented.
1.3 Brain Regions used in Optic Flow Perception: Primate Studies
Previous research suggests that different brain regions respond optimally to different
types of motion. For example, although first order motion (motion perception created from
shifts in luminance distribution) and second order motion (motion perception created from
contours and textures) is processed in the same cortical structures in the early stages of
processing, some evidence suggest that there is distinct extrastriatal specialization for first and
second order motion processing (for review see Baker, 1999). This observation also extends
to optic flow, where research on primates has elucidated extrastriatal structures that respond
optimally to expanding radial motion and shifts to FOE.
The medial temporal (MT; also known as V5) area was one of the first extrastriatal
areas to be discovered and it is implicated in motion processing. Researchers found that when
primates passively viewed moving or flashing dots that simulated coherent motion, neurons in
the MT area can be directionally selective, such that they respond to a specific direction of
visual motion (Dubner & Zeki, 1971; Mikami, Newsome, & Wurtz, 1986). Lesions in MT/V5
area significantly decreases the monkeys’ ability to discriminate the direction of motion
(Pasternak & Merigan, 1994), suggesting this area is needed to judge heading direction.
Although motion perception was severely impaired in these monkeys, the ability to detect
motion was not completely lost, thus suggesting that other brain regions are involved in
7
motion perception. There is cumulating evidence suggesting that optic flow, a complex type
of visual motion information, requires the recruitment of higher order extrastriatal cortices
beyond area MT.
Recent findings suggest that two brain regions, found upstream in the dorsal pathway,
are implicated in optic flow perception: the medial superior temporal area (MST) and the
ventral intraparietal areas (VIP). Neurons in the MST area, adjacent to the MT area, and
neurons in the ventral intraparietal area (VIP) has been shown to aid in heading
discrimination in the presence of optic flow. The MST receive strong inputs from the MT
area and it contains neurons that respond optimally to expansion or contraction, movement
over a large visual field, and rotation (Tanaka, Fukada, & Saito, 1989), which are all
characteristics that describe optic flow. Neurons in both MST and VIP are sensitive to shifts
in FOE (Duffy & Wurtz, 1995; Bremmer, Duhamel, Ben Hamed, & Graf, 2002) as well as
varying optic flow speeds (Duffy & Wurtz, 1997; Zhang & Britten, 2004).
In addition to the evidence found in these electrophysiology studies, behavioral
studies have found that when optic flow is viewed, primates’ MST neurons are activated,
which in turn elicits an alteration in posture (Duffy & Wurtz, 1996). Primates’ heading
perception is also significantly biased when MST (Britten & van Wezel, 1998) and VIP
(Zhang & Britten, 2011) neurons were stimulated, which reinforces the idea that the neurons
in MST and VIP are highly involved in accurately judging heading direction. Thus, MST and
VIP neurons not only possess the appropriate anatomical and physiological properties to
process optic flow, but they may also function as heading estimators and influence the control
of posture needed for locomotion (see Figure 1 & 2 for a summary of how optic flow
perception is transformed into action).
8
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Behavioral changes in posture, in addition to optic flow processing, also relies on an
extended neural circuit that involves and integrates different sources of sensory information
(e.g. vestibular and proprioceptive), which is used to plan and execute contextually adapted
motor responses. Neurons in the ventral premotor cortex seem to act as a sensory integration
center as they receive neuronal projections from the parietal lobe, encoding somatosensory
and proprioceptive information (Jones & Powell, 1970; Kunzie, 1978; Cavada & GoldmanRakic, 1989), as well as visuospatial information (Graziano & Gross, 1994; Graziano, Hu, &
Gross, 1997; Fogassi et al., 1996). Ventral premotor neurons subsequently send projections to
the primary motor cortex (M1) and spinal cord to execute context-adapted motor responses
(Barbas & Pandya, 1987; Dum & Strick, 1991). It has been shown that different areas of the
parietal lobe may also be involved in beginning stages of somatosensory integration and
9
motor planning. Area 7a and the lateral intraparietal area (LIP) are suggested to integrate both
proprioceptive and visual information (Andersen, 1997) while area 7b and the ventral
intraparietal area (VIP) was shown to be involved in the integration of tactile and visual
information (Avillac, Deneve, Olivier, Pouget, & Duhamel, 2005; see Figure 3 for an
overview).
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Figure 3. A simplified schematic overview of how optic flow perception is transformed into
motor execution. Optic flow is first processed in area MST in the temporal cortex, then
information is further processed in the parietal and frontal cortex, and lastly, signals are sent
to the primary motor cortex to execute behavior. Adapted from Graziano & Gross, 1998.
1.4 The human homologue for area MT: imaging studies
Although primates and humans possess some anatomical and behavioral differences,
our visual systems have many similarities. Human imaging studies reveal that there is a human
homolog of the MT area in primates; this area is termed the human MT complex (hMT/V5+;
Zeki et al., 1991; Watson et al., 1993; Dupont, Orban, De Bruyn, Verbruggen, &
10
Mortelsmans, 1994). However, later research suggests that hMT+1 may have subregions that
specialize in the processing of different visual motion stimuli (Howard et al., 1996). Morrone
and colleagues (2000), for instance, found that only a subregion of hMT+ responds
specifically to radial and circular motion and that this region is separated by more than 1cm
from the area responding to translation. Ptito, Kupers, Faubert, and Gjedde (2001) also found
that the motion sensitive area hMT may not be specifically involved in optic flow analysis (i.e.
expanding and contracting motion).
Later studies supported this finding by delineating human MST area located in the
dorsal/posterior limb of the inferior temporal sulcus (Dukelow et al., 2001; Huk, Dougherty,
Heeger, 2002; Smith, Wall, Williams, & Singh, 2008). These studies aimed at elucidating the
receptive field size and retinotopic organization of hMT versus hMST neurons. The
cumulative results of these studies show that while neurons found in hMT respond to
contralateral translational motion stimuli, hMST neurons respond specifically to expanding
radial and circular motion in the ipsilateral and contralateral visual fields; thus, evidence
suggests that these areas possess large receptive fields. In addition to possessing the ideal
properties to process optic flow, hMST is also functionally involved in optic flow perception
when observers viewed rotating and expanding coherent motion (Becker, Erb, M., &
Haarmeier, 2008; Wall, Lingnau, Ashida, & Smith, 2008). Patients with damage to the
occipitoparietal and parietotemporal lobe, which contains the hMT+, display impairment in
discrimination direction from global motion (Vaina et al., 2001), which further suggest that
the hMT+ is needed for heading discrimination using optic flow. In summary, hMST is
located in the same brain region as primate MST neurons, its neurons contain large receptive
fields and this area seems to be necessary for heading discrimination using optic flow.
1
The hMT+ comprise of the hMT and hMST areas
11
In addition to the hMST, additional extrastriatal areas are reported to respond to optic
flow stimuli. Coherent radial motion that defines optic flow elicits activation in inferior
cuneous (human homologue of V3), insular cortex, and the posterior precuneous in the
occipitoparietal cortex (de Jong, Shipp, Skidmore, Frackowiak, & Zeki 1994). Other brain
regions include the lingual gyrus and lingual cuneous, ventral intraparietal sulcus (analogous to
primate VIP area; Orban et al., 2003), the lateral occipital sulcus (LOS, also formerly known
as the kinetic occipital [KO] region; Rutschmann, Schrauf, & Greenlee, 2000; Orban et al.,
2003), V2, and V3 (Ptito et al., 2001; Orban et al., 2003; Wall et al., 2008) and, to a lesser
extent, the dorsal intra-parietal sulcal area (DIPSM/L) and the inferotemporal gyrus (i.e. face
area; de Jong et al., 1994; Orban et al., 2003). Table 1 summarizes these brain regions and the
function associated with each area.
12
Table 1. Summary of activated human brain regions elicited by optic flow stimuli.
Brain region
Human V5/V5a complex
in occipitotemporal area
(i.e. human homologue of
MT/MST)62
Type of stimulus eliciting maximal response
low contrast stimulus55
Inferior cuneous (human
homologue of V3) 62
motion-defined borders62
Insular cortex62
coherent radial motion62
Posterior precuneous in
occipitoparietal cortex62
coherent radial motion62
Lingual gyrus16
direction and speed16
Lingual cuneous16
direction and speed16
Kinetic occipital (KO) cortex16
(i.e. V3b or
lateral occipital sulcus)
Ventral intraparietal sulcus24
dorsal intra-parietal sulcal area
(DIPSM/L)11, 45
Inferotemporal sulcus
Motion-defined borders within complex displays
& second-order motion16
somatosensory & visual integration24
n/a
complex pattern recognition
13
1.5 Steering strategies
It is likely that heading discrimination and steering require more brain regions than the
hMT+ and parietal lobe because steering requires constant context-adapted behavior. Steering
strategies also differ depending on which type of optic flow is present (Sarre, Berard, Fung,
and Lamontagne, 2008). When we are walking along a straight path, a translational optic flow
field is created and the FOE is used to guide heading direction by estimating the error
between the FOE and the intended goal. To maintain a straight trajectory, many studies
showed (e.g. Warren et al., 2001; Lamontagne et al., 2010) that the observer veers in the
opposite direction of a shifted FOE. However, walking along a curved path comprises of a
rotational optic flow created by horizontal eye, head, and body rotations. This distorts our
optic flow field that aids us is accurate heading discrimination (Grasso, Prevost, Ivanenko, &
Berthoz, 1998; Imai, Moore, Raphan, & Cohen, 2001; Hollands, Patla, & Vickers, 2002),
which is known as the “rotation problem”.
Sarre, Berard, Fung, and Lamontagne (2008) have shown that when only translational
flow is available, the observer would “crabwalk”, which is characterized by a mediolateral
(ML) shift in walking trajectory, towards his or her goal. When optic flow contains a
rotational component, the observer displays a ML displacement and head and body
reorientation. Thus, similar to previous studies (e.g. Warren et al. 2001; Lamontagne et al.,
2010), we have chosen to use a translational flow paradigm where only one steering strategy is
possible and intend to control for head and gaze orientation by ensuring gaze fixation on a
target throughout the experiment (to avoid the “rotation problem”).
14
1.6 Human Brain Regions required for Heading and Steering
Surprisingly, although there is a lot of research on the neural correlates of optic flow
processing in humans, there are few studies investigating the neural correlates for heading
estimation and active steering despite the fact that they are essential for human mobility.
Peuskens, Sunaert, Dupont, Van Hecke, and Orban (2001) conducted a study where
participants viewed various ground plane stimuli that simulated self-motion and were required
to actively indicate heading using button presses while in the PET or fMRI scanner. This
contrasts with previous studies (e.g. de Jong Shipp, Skidmore, Frackowiak, & Zeki, 1994) that
recorded functional brain activation while the participants passively viewed dots moving in a
specific direction. Active heading discrimination is more realistic and generalizable to
everyday life, as actively judge our heading direction from optic flow in order to accomplish
goal-directed locomotion. In this study, Peuskens and colleagues found a neural network and
that comprised of the hMT+/V5, an inferior satellite of the hMT+, DIPSM/L, as well as the
dorsal premotor area to display significantly higher activation than the visual motion control
condition. Activation of hMT/V5+ and DIPSM/L was attributed to motion processing by
the authors and when past literature is taken into consideration (in section 1.3 and 1.4), this
explanation is highly probable. The inferior satellite near the fusiform area is considered to be
the human MSTd homolog, which is sensitive to both optic flow and speed gradients. The
dorsal premotor was regarded as the ‘final stage’ in the parieto-premotor visuomotor pathway
and would help translate the heading information extracted hMT/V5+ and DIPSM/L into
motor schemes (Peuskens et al. 2001; see Figure 3).
In a more recent study, Billington, Field, Wilkie, and Wann (2010) found that when
information about the future path is available, in addition to optic flow information,
participants can discriminate heading direction faster and that this process is coupled with
15
activation in the superior parietal and the DIPSM/L. These results, which are consistent with
previous studies (Peuskens et al., 2001; Field, Wilkie, & Wann, 2007), suggest that these two
areas are needed to anticipate and assess the future path for accurate steering. Area MT+ is
activated when information about the future path was not available and thus, the authors
contributed this activation to optic flow perception. Table 2 summarizes these findings.
Table 2. Summary of activated human brain regions elicited by a heading
discrimination task.48
Brain region
hMT+/V5
inferior satellite hMT+
dorsal intra-parietal sulcal area
(DIPSM/L)
dorsal premotor
Type of stimulus eliciting maximal response
motion processing
optic flow & speed gradients
motion processing
translates visual information needed for heading into
motion
To date, only one research group has investigated the neural correlates involved in
active steering (see Table 3 for summary of brain regions used for steering). However, unlike
the focus of this thesis, Field and colleagues (2007) were interested in which brain regions
were activated when participants steer, while using button presses on a keypad, while viewing
a simple, ground plane virtual environment where future path information (defined by road
edges) is available. Although this study did not investigate the control of steering using optic
flow alone, it provides valuable insight into which brain regions may be involved in the
16
control of steering. Notably, it was found that the superior parietal region is activated when
the observer perceives what is ahead in our path and the anterior parietal region is needed to
detect motor error signals that aid the observer in arriving to a goal. In addition, the
cerebellum, supplementary eye fields, and the dorsal premotor cortex were shown to be
activated during the steering task. However, the authors acknowledged that the cerebellar and
dorsal premotor activation might have been due to the precise timing and fine finger
movements from the button presses used to control steering.
Table 3. Summary of activated human brain regions elicited by a steering task, while
using future path (road) information.18
Brain region
Type of stimulus eliciting maximal response
superior parietal region
anticipate future path
anterior parietal region
steering error signal processing
intraparietal sulcus
anticipate future path
parietal eye fields
processes spatial information for visuomotor
transformations
supplementary eye fields
planning of eye movements for visual information
needed for steering
dorsal premotor cortex
motor planning
17
1.7 Summary and Rationale for the present project
Optic flow provides us with information about our heading direction and allows us to
accurately steer our walking trajectory toward a desired point in space. Much research has
been conducted in both primates and humans to delineate brain regions that specialize in
optic flow processing. However, few studies have investigated the neural correlates involved
in active heading discrimination. Previous studies have investigated the brain regions that
respond to moving dots or a ground plane that simulates self-motion and did not require the
observer to actively indicate their heading direction. To date, only one group has investigated
the brain regions activated during a steering task (Field et al., 2007). The focus of the study,
however, was on the contribution of future path information and their experimental design
did not allow for the identification of brain areas used in the control of steering from optic
flow.
Therefore, there are no studies to date that have investigated the brain regions
involved in heading discrimination and steering from optic flow, which are two critical
components to achieve goal-directed locomotion, while using an ecological environment. In
this thesis, I am using a texture-rich virtual environment to investigate heading discrimination
and steering. It is a more realistic environment and it is assumed that the observed patterns of
brain activation will be more closely related to what is experienced in everyday life. Also,
studying the neural correlates associated with a heading discrimination task and a steering task
in the same individuals will allow me to make direct comparisons and determine which
additional brain regions, if any, are recruited to complete the steering task. A better
understanding of which brain regions are involved in these two processes is necessary to
understand why persons with CNS lesions, such as stroke, display altered steering behaviors
18
when exposed to changing optic flow direction while walking (Lamontagne et al., 2010;
Berard et al., 2011).
1.8 Study purposes and hypotheses
The main purpose of this thesis is to identify the brain regions involved in the control
of steering while immersed in a virtual environment describing optic flows expanding from
different locations. In addition, the brain areas that are involved in the discrimination of
heading under similar optic flow conditions will be examined. The hypotheses are as follow:
1) Heading discrimination will be associated with activations in the human MT complex
(hMT+/V5), DIPSM/L, and possibly additional regions due to visually rich and realistic
nature of the environment that participants will be viewing.
2) Steering will be associated with specific activation of the cerebellum, parietal lobule, and
dorsal premotor cortex, which may reflect, respectively, processes of error correction in
the trajectory, multi-sensory integration, and anticipation of future action.
19
Chapter 2
Manuscript:
Brain regions involved in
heading estimation and steering
control in a virtual environment
Formatted for NeuroImage
BRAIN REGIONS INVOLVED IN HEADING ESTIMATION AND
STEERING CONTROL IN A VIRTUAL ENVIRONMENT
Anita Liua,c, H.BSc
Rick Hogeb,f, PhD
Julien Doyonb,e, PhD
Joyce Funga,d, PhD, PT
Anouk Lamontagnea,d, PhD, PT
a. Jewish Rehabilitation Hospital Research Centre (site of CRIR),
3205 Place Alton Goldbloom, Laval (QC), H7V 1R2, Canada
b. Functional Neuroimaging Unit, University of Montreal Geriatric Institute,
4565 Queen-Mary, Montreal (QC), H3W 1W5, Canada
c. Department of Neurology & Neurosurgery, McGill University,
3801 University Street, Montreal (QC), H3A 2B4, Canada
d. School of Physical & Occupational Therapy, McGill University,
3654 Promenade Sir-William-Osler, Montreal (QC), H3G 1Y5Canada
e. Department of Psychology, University of Montreal,
90 Vincent d’Indy Avenue, Montreal (QC), H2V 2S9,Canada
f. Department of Physiology, University of Montreal,
C. P. 6128, Centre-ville, Montreal (QC), H3C 3J7, Canada
Send all correspondence to:
Anouk Lamontagne, PT, PhD
Associate Professor
School of Physical and Occupational Therapy
McGill University
3630 Promenade Sir William Osler
Montréal, Québec
H3G 1Y5
Tel: 514-398-8193
Email: [email protected]
Authors’ email addresses:
[email protected]
[email protected]
[email protected]
[email protected]
[email protected]
21
Abstract
The brain regions required for judging heading direction and actively steering towards
a goal could be damaged by stroke. Identifying the neural correlates responsible for goaldirected locomotion is important for the understanding of the mechanism underlying
neuroplasticity and functional recovery. Past research shows that when we are walking
through a texture-rich environment, we primarily use optic flow, a radially expanding pattern
of motion, to accurately discriminate our heading direction and steer towards a goal. The
purpose of this study was to investigate the different brain regions involved in heading
discrimination and steering using an ecological virtual environment, mimicking most
environments we walk through. Fourteen participants (7 males, 7 females) took part in an
fMRI study where their BOLD responses were measured while they completed a heading
discrimination and active steering task using a joystick. A cluster level inference was
conducted and clusters that were statistically significant above a threshold of Z=4 (p<0.01)
were identified. This study investigated which brain regions display higher BOLD responses
in the heading discrimination and steering task, independent of motor movements from
joystick input. Consistent with previous studies, the bilateral intraparietal sulcus is involved in
heading discrimination and bilateral posterior cerebellum was observed in the steering task.
Further analysis revealed that the hMT+ and V2, the bilateral cerebellum, supplementary eye
fields, premotor cortex, and supplementary motor area, displayed higher BOLD responses in
the steering task than in the heading discrimination task. These results suggest that although
heading discrimination involves a certain degree of sensorimotor integration and optic flow
processing, steering is a more demanding task, requiring more brain regions to transform
dynamic optic flow information into context-adapted motor responses. Keywords: Cerebellum,
Locomotion, Optic flow, Premotor, Visual motion
22
1. Background & Objectives
1.1 Background
Locomotor steering, which refers to the ability to control one’s trajectory by
reorienting our body position to walk towards our goal, is an essential component of
community ambulation. Although steering may seem effortless and automatic to healthy
individuals, it involves complex interactions between cognitive, sensory (e.g. vestibular, visual,
and proprioceptive) and motor systems. Researchers have previously demonstrated that optic
flow, as available in a texture-rich environment, is heavily relied upon to guide locomotion
(Warren et al., 2001; Wilkie & Wann, 2003).
Optic flow is a pattern of visual motion created when an observer moves through the
environment or when the visual pattern moves in relations to a fixed observer. The optic flow
in forward walking describes an expanding pattern of motion that radiates from a singular
point, known as the focus of expansion (FOE). Under normal circumstances, we are able to
judge which direction we are moving in, also known as heading discrimination, by localizing
the FOE from the optic flow field, such that accurate locomotor steering is achieved by
aligning the FOE with the desired goal (Gibson, 1950). Healthy young adults can perceive
their heading (Warren et al., 1988) and control their locomotor trajectories with high accuracy
when exposed to optic flow fields expanding from different directions (Warren et al., 2001).
Heading discrimination and steering abilities from optic flow, however, are both altered by
aging (Warren et al., 1989; Kavcic et al., 2011; Berard et al., 2009) and can further deteriorate
with the presence of CNS lesions (Kavcic et al., 2011; Young et al., 2010; Billino et al. 2009;
Lamontagne et al., 2010). To date, the mechanisms responsible for these perceptuo-motor
alterations are poorly understood. An identification of the neural substrates involved in the
23
discrimination of heading direction is needed to understand the brain structures and
mechanims used to guide locomotor steering.
It has been shown through previous research that the human medial temporal
complex (hMT+) containing the human medial temporal (hMT) human medial superior
temporal (hMST) areas, is involved in processing motion and optic flow (Morrone et al. 2000;
Dukelow et al., 2001; Huk et al., 2002; Smith et al., 2008). Both primate and human studies
have further identified the involvement of the intraparietal sulcus (IPS) in response to viewing
coherent moving dots that simulated different heading directions (Zhang & Britten, 2004;
Bremmer et al., 2002; Cornette et al., 1998) and global motion (Sunaert et al. 1999; Orban et
al, 1999). Other areas that were identified to be selectively responsive to direction created by
optic flow include areas V2, V3, and the lateral occipital sulcus (i.e. kinetic occipital [KO]
area) (Ptito et al., 2001; Orban et al., 2003; Wall et al., 2008).
While the above-mentioned studies have characterized optic flow processing in
humans passively viewing optic flow displays, only a few research groups have investigated
the brain regions associated with heading discrimination and steering using optic flow. In a
hallmark study by Peuskens and colleagues (2001), heading estimation was found to
selectively activate hMT+, including an inferior satellite, the dorsal intra-parietal sulcal area
(DIPSM/L) as well as dorsal premotor regions. It was suggested that the heading information
extracted from the human MT complex and DIPSM/L was translated into motor programs
in a parieto-premotor connection, where the dorsal premotor areas acted as a ‘final stage’.
Bilateral superior parietal lobe (SPL) activations was also observed when providing path
information, such as road edges, in addition to optic flow, suggesting that this area is
implicated in processing information regarding our future path (Field et al. 2007; Billington et
al., 2010).
24
To our knowledge, only Field and colleagues (2007) have investigated the neural
systems involved in the control of steering. Using button presses, participants were able to
control their steering direction when future path information was available. A network of
three main areas, including the dorsal premotor cortex, supplementary eye fields (SEF) and
cerebellum, was found to be involved in generating the trajectory adjustments. It was
suggested that the SEF activation was related to a planning component involving eye
movements in the future travel direction, while the cerebellum might have been processing
errors or deviations from an internal forward model prediction.
The study by Field and colleagues (2007) has provided information that is key to the
hypotheses examined in the present study. Its focus on the specific contribution of future
path information and experimental design, however, did not allow for the identification of
brain areas used in the control of steering from optic flow. Furthermore, past studies have
used moving dot patterns or a ground plane stimulus, which may have yielded results that do
not accurately reflect the neural processes involved while navigating in texture-rich, ecological
environments, as experienced in everyday life. Task-specific patterns of brain activation is
likely, given that some brain areas and neurons respond selectively to different types visual
motion (Ptito et al., 2001; Vaina & Soloviev, 2004) and that the richness and structure of the
visual flow have a profound influence on steering strategies while walking (Warren et al. 2001;
Sarre et al 2008).
In this study, we investigated the neural correlates of associated with a heading
discrimination task vs. a steering task using a texture-rich, meaningful environment. Both
tasks will be examined in the same environment across individuals, hence allowing direct
comparisons that will help determine which additional brain regions, beyond those involved
in the discrimination task, are involved in steering.
25
2. Methods & Procedures
2.1 Participants
Fourteen participants (7 males, 7 females) between ages 18-31 were recruited from
Montreal, Canada, using posters advertised at McGill University and Université de Montréal
(Mean± 1SD = 25.6± 4.51 years). Prior to this study, participants were prescreened and were
included if they scored above 25 on the Montreal Cognitive Assessment (MoCA; Nasreddine
et al., 2005), were right handed (according to the Edinburgh Handedness Inventory; Oldfield,
1971), had normal or corrected-to-normal visual acuity (Snellen Chart 20/20), were not
colorblind (Dvorine, 1953; Ishihara, 1983), and were MRI-compatible.12 Participants
presented with a past history of neurological, ophthalmological, or psychiatric disease were
excluded, as well as those who have had a concussion in the past. Informed consent was
obtained during the pre-training session and participants were compensated for traveling
expenses. All experimental procedures were conducted in accordance with the Health Canada
Research Ethics Guidelines and approved by the Centre de recherche Institut universitaire de
gériatrie de Montréal (CRIUGM) and Centre de recherche interdisciplinaire en réadaptation
du Montréal métropolitain (CRIR).
2.2 Apparatus
2.2.1 Virtual environment. For this study, we created a texture-rich virtual environment
(VE) representing a large room (100m x 30m) with a static isosceles triangle located in the
center and at eye level (1.7m) to aid in gaze fixation (Softimage XSITM, San Francisco, CA;
Figure 1). The VE was projected on a screen located behind the MRI scanner and participants
viewed the stimuli through a mirror embedded within the head coil 15cm away from their
eyes. During the experiment, participants held a multi-axial (i.e. x, y, z) MRI-compatible
1
Please see Appendix 2 for MRI screening form
26
joystick (Mag Design and Engineering (1024 points resolution along each axis, at a 150Hz
refresh rate) in their right hand. Depending on the experimental conditions, the joystick was
used to provide a response or to control the perceived mediolateral displacement within the
VE. In the steering task, every unit of joystick movement along the mediolateral axis (512
points in each direction) resulted in 0.2m of mediolateral displacement in the VE. The
participants’ perceived position in the VE was updated in real-time by the Caren-3TM system
based on the joystick input.
__________________________________
Insert Figure 1 here
__________________________________
2.2.2 fMRI scanner & acquisition. Images were acquired using a 3.0 Tesla TRIO TIM
MRI system (Siemens Medical Solutions) equipped with a 32-channel head coil. Participants
first underwent a 3D anatomical (MP-RAGE) and 2D scan, which lasted ~9min and ~5min,
respectively. Next, T2*-weighted blood oxygenation level dependent (BOLD) signals were
recorded during the experiment using echo-planar imaging with each functional volume
consisting of 43 slices to cover the whole brain (TR = 2000ms; TE = 30ms; flip angle = 90o;
FOV = 256 x 256mm2; matrix size = 64x64; voxel size = 4 x 4 x 4mm). Slices were acquired
in ascending order, and each functional scan lasted for ~8min per run. After functional
imaging, a DTI scan (3 directions; ~2min) was performed for the purpose of a future study in
which these DTI scans may be compared to healthy older adults or stroke patients. The
entire scanning session lasted approximately 1 hour.
27
2.3 Procedure
2.3.1 Training session. Participants were trained 24-48 hours before fMRI acquisition on
the different tasks in the experiment until they reached a performance of !80% correct
response on the heading direction discrimination task (Peuskens et al., 2001) and 8
consecutive good trials on the steering task.
Because higher amplitude of BOLD response has been reported in the primary motor
cortex (M1) during slow hand movements compared to fast hand movements (Lindberg et al.
2009), participants were trained to maintain the same joystick velocity throughout all the
tasks. This was achieved by providing the participants with a real-time visual feedback
representing the joystick movement velocity with Caren-3TM. A description of the different
tasks can be found below.
2.3.2 Experimental Design. A block design was used, in which each fMRI run included
distinct blocks corresponding to one the following tasks: 1) heading discrimination task; 2)
steering task; 3) motor & visual perceptual task; 4) passive viewing and 5) rest condition.
Tasks 1 to 4 were presented once in each run, in a random order, and were interspersed with
‘rest’ blocks, for a total of 8 blocks per run. Except for the rest blocks that included a static
VE, each block included 6 trials, that is two trials for each of the 3 optic flow directions tested
(+40º right, -40º left, or 0º straight ahead; 10s/trial), interspersed with a variable inter-stimulus
interval of 2-6s during which a static VE was displayed. In the virtual world coordinates, the
observer was displaced on a 10m absolute distance, resulting in a 10m forward displacement
when FOE was located at 0º and 8.4m when FOE was at ± 40º. Prior to the scan, instructions
for each block were repeated verbatim and concise instructions (1-2 words) were displayed
for 3s before each block began during the scan. Participants were scanned for ~7min per run
and performed 5 runs in total.2 They were instructed to fixate their eyes on the red triangle,
28
which remained centered throughout the experiment, regardless of the presence of visual
motion, to ensure eye fixation.3
Joystick movement and speed, as well as the participants’ performance on the heading
discrimination task and the motor & visual perceptual task described below, were recorded in
Caren-3.4 The Caren-3 system and MRI was synchronized to trigger the start of the
experiment when the MRI scanning session began. This was done via an interface box that
received a trigger from the scanner via a fiber optic link, which in turn sent a signal via a USB
connection to Caren-3.
2.3.3 Heading discrimination task. Participants perceived themselves to be moving in
either of three directions (+40º right, -40º left, or 0º straight ahead) at a fixed forward speed of
1m/s. They were instructed to actively discriminate the direction of perceived self-motion by
displacing the joystick right, left, or forward, respectively.
2.3.4 Steering task. Participants perceived themselves to be moving in one of the three
directions described in 2.3.3. They were instructed to maintain a straight trajectory so they
perceived themselves to be moving straight ahead in the VE. Real-time mediolateral trajectory
corrections within the VE were accomplished using joystick mediolateral displacements.
2.3.5 Motor & Visual Perceptual task. Participants were shown a static virtual
environment with the red triangle pointing in either of three directions (left, up, or right).
Participants were required to indicate which direction the triangle (vertex angle) was pointing
to by moving the joystick in the appropriate direction. The purpose of this condition was to
control for the hand motor responses and visual attention in the heading discrimination and
2
See Appendix 3 for a schematic overview of the experimental design
Note that although a monocular MRI compatible eye tracker (RK-826PCI Pupil/Corneal Reflection Tracking
System; ISCAN Inc., Woburn, MA; 60 Hz refresh rate) was available for us to collect eye movements during the
experiment, persistent technical difficulties prevented us from either recording and/or analysis of the eye data.
4
See Appendix 4 for the virtual scene the participants viewed for each of the conditions
3
29
steering conditions. In the results section, this condition will be referred to as
“Motor/Perceptual”.
2.3.6 Passive Viewing task. This block was identical to the heading discrimination block,
with the exception that participants were instructed to passively view the virtual environments
and not to move the joystick. This condition allowed us to identify and control for brain
regions involved in the processing of optic flow.
2.3.7 Rest/Perceptual task. Participants viewed the static VE and were instructed to ‘rest’
without performing any joystick movements. This condition served the purpose of recording
brain activity at rest while visually attending to the VE, in the absence of visual motion
information.
2.4 Data analysis
2.4.1 Behavioral data. Mean mediolateral velocity and range of motion of the joystick
was calculated and compared across the conditions that required joystick movements (heading
discrimination, steering and motor/perceptual conditions) and optic flow direction or triangle
orientation (right, left, centered or up) with 2-way analyses of variance (ANOVAs). In
addition, the participants’ performance on the discrimination and steering tasks were
analyzed, respectively, by examining the direction of the joystick displacement (right, left, or
down) as well as the mediolateral position of the participants within the VE coordinates
during the last 500ms of each trial. We have excluded three participants in our analysis of
joystick movements due to malfunction of the recording device during data collection.
2.4.2 fMRI analysis. Image processing and statistical analysis of all functional data was
performed using FSL (Analysis Group, FMRIB, Oxford, UK). The acquired DICOM files
were converted into NIFTI files and each brain was extracted using FSL’s brain extraction
tool (BET) where 0.3mm of the skull was removed and a bias field and neck cleanup was
30
performed. Preprocessing steps include slice timing correction (ascending order), motion
correction for small head movements, and the time series was high pass filtered at a cut off of
128s to remove low frequency signal drift. Images were then co-registered to anatomical
volume and normalized to standard Montreal Neurological Institute (MNI) space. Lastly,
images were spatially smoothed with a 6mm FWHM Gaussian kernel.
For all the conditions, with the exception of Rest, the 6 trials were modeled as a single
regressor (i.e. 2 in each of the three directions +40O right, -40O left, or 0O straight ahead); we
were mainly interested in the following three contrasts: a) Steering-Motor/Perceptual b)
Heading discrimination-Moto/Perceptual, and lastly, c) Steering-Heading discrimination. The
first two contrasts reveal which brain regions respond to a heading discrimination and
steering task, which is accomplished using optic flow information. However, to investigate
which activations are associated with a heading discrimination or steering task rather than
optic flow processing, we also conducted two additional contrasts. This was accomplished by
subtracting significant BOLD responses associated with the Passive Viewing condition from
the heading discrimination and steering tasks.
We convolved the time series of each participant with a double-gamma hemodynamic
response function and applied a temporal derivative with temporal filtering. We conducted a
cluster level inference and were interested in clusters that are statistically significant above a
threshold of Z=4 (p<0.01). For analyses, we first performed repeated measures ANOVA for
each participant, corrected for fixed effects, followed by a group analysis using a one-way
ANOVA, corrected for mixed effects. Peak activations for each cluster are reported in MNI
space and brain structures were identified using the Juelich Histological Atlas and the
Harvard-Oxford Cortical Structural Atlas.
31
Section 3: Results
3.1 Behavioural responses
Participants completed the Heading Discrimination task with a mean accuracy of 87%
(range: 73% to 100%) and the Motor/Perceptual task with 100% accuracy. On the steering
task, they displayed heading errors within 6 o to 8o, which is typical of a highly accurate
performance for healthy individuals on a similar task (Aburub & Lamontagne, submitted). A
2-way ANOVA across different tasks that required joystick movements (Steering, Heading
Discrimination, and Motor/Perceptual tasks) and the three directions (+40O right, -40O left, or
0O straight ahead) revealed an interaction effect between tasks and direction for joystick range
of motion F(4, 89)= 6.5192, p<0.0001 and velocity F(4, 89)= 9.29, p<0.0001. Post-hoc
comparisons revealed similar range of motion and speed values across tasks for the 0O
stimulus direction (i.e. straight ahead optic flow/upward triangle orientation). Smaller values,
however, were observed for the ±40O direction in the Steering task (speed= 0.05±0.01 m/s;
range of motion=5.19O±0.41O) compared to both the Heading Discrimination (0.10±0.01
m/s; 3.91O±0.41O) and Motor/Perceptual tasks (0.15±0.01 m/s; 3.46O±0.41O) (p=0.05).
3.2 Imaging results
3.2.1 Passive Viewing. When activations associated with Passive Viewing were
contrasted with that of Rest, we observed activation in areas associated with optic flow and
visual processing such as V2 (-18, -98, 12) and the lateral occipital lobe (48, -66, 0), which
corresponds closely to the coordinates for the hMT+ reported in other papers (Zeki, et al.
1991; Watson et al., 1993; Dupont, Orban, De Bruyn, Verbruggen, & Mortelsmans, 1994).
3.2.2 Heading discrimination. The heading discrimination task showed activation in the
bilateral superior parietal lobule in the contrast ‘Heading discrimination – Motor/Perceptual’
(Z > 4; see Figure 2 and Table 1), which has also been referred to as DIPSM/L (Sunaert, Van
32
Hecke, Marchal, & Orban, 1999). This contrast also revealed significant activation in the left
lateral occipital lobe (-50, -78, 2), which displays coordinated that are compatible with area
hMT+ (Zeki, et al. 1991; Watson et al., 1993; Dupont, Orban, De Bruyn, Verbruggen, &
Mortelsmans, 1994).
Other areas that displayed activation included the bilateral lateral occipital cortex
(hMT+), bilateral primary visual cortex (V1), and left secondary visual cortex (V2), which
were present in the contrast ‘Heading discrimination – Motor/Perceptual’, but were not
observed when Heading discrimination was contrasted with Passive Viewing. In the contrast
‘Heading discrimination – Passive Viewing’, bilateral activation of superior parietal lobule
(DIPSM/L) remained present.
__________________________________
Insert Figure 2 & Table 2 here
__________________________________
3.2.3 Steering. A widespread activation in all four lobes, as well as in the cerebellum,
was observed when activations from the Motor/Perceptual task were subtracted from
activations observed in the Steering task (Table 2). In addition to a number of temporal and
parietal brain regions that were activated, bilateral peaks of activation were observed in the
premotor cortex and the right middle frontal gyrus with coordinates (36, -2, 54) compatible
with the localization of the frontal eye field (Paus, 1996). The right hMT+ displayed the
highest peak activations among all the brain regions activated in this contrast.
Bilateral cerebellar (Crus I and VI) and hMT+ activity was observed for both
contrasts ‘Steering – Motor/Perceptual’ and ‘Steering – Passive Viewing’. A contrast of the
33
Steering condition with the Heading Discrimination condition (Steering-Heading
discrimination) was carried out to examine which regions were additionally recruited while
steering, above those recruited in the discrimination task (Table 3). A relatively extended
network of activation was observed after this subtraction, with bilateral peaks of activation
found in the premotor areas, supplementary motor areas and in the cerebellum (left Crus I,
left & right VI) (Figure 3). Our MNI coordinates for the supplementary motor cortex
corresponds closely to the Talairach coordinates reported for the supplementary eye fields in
Grosbras and colleagues’ (1999) study, where they delineated the landmarks for this region. In
addition, significant peaks of activation were observed in the left inferior parietal lobule (-60, 28, 38) and primary motor cortex (-34,-26, 60), as well as in left V2 and bilateral hMT+ (see
Table 3). Note that activations in the left V2, but not in hMT+ (Z = 4.16), remained when
contrasting ‘Steering-Passive viewing’, which is different from what was observed for the
‘Heading discrimination-Passive viewing’ contrast where both V2 and hMT+ activations were
no longer observed.
__________________________________
Insert Table 3 here
__________________________________
34
Section 4: Discussion
Our study reveals, for the first time, the different brain regions contributing to
heading discrimination and steering control when optic flow is provided via a texture-rich,
ecological environment. When available, optic flow information is used to determine heading
and guide steering toward the desired location (Warren et al., 2001). It can thus be inferred
that while both tasks may share some similarities in terms of the neural processes that are
involved, a larger network associated with the planning and implementation of steering
adjustments is necessary. Confirming earlier reports on heading discrimination (Billington et
al., 2010; Peuskens et al., 2001), we found that not only DIPSM/L and the human MT/V5
complex, but also visual processing areas V1 and V2, were involved in heading discrimination
using optic flow. As anticipated, the steering task recruited an extended neural network
involving all four lobes of the human brain. Compared to the heading discrimination task, it
further resulted in a higher BOLD response in brain regions associated with optic flow and
visual processing (V2 and hMT+), spatial orientation (cerebellum), and motor planning
(premotor cortex).
Identification of these structures suggests a more demanding nature of steering
compared to heading estimation. It has been observed in past studies that constant visual
feedback is needed to update the observer on the position of the FOE and consequently
adjust their position in space to reach their goal (Fajen & Warren, 2003; Warren et al., 2001;
Berard et al., 2010). Our findings agree with previous studies and have found DIPSM/L
activation in the Heading Discrimination task (Peuskens et al., 2001; Billington et al., 2010)
and the cerebellum, SEF, and premotor cortex activation in the Steering task (Field et al.,
2007). We have additionally found that activation in the anterior DIPSM/L and posterior lobe
35
of the cerebellum are specific to discriminating heading and steering, respectively, in a virtual
environment.
4.1 Passive viewing of optic flow
As anticipated, the Passive Viewing condition in this study showed activation in
hMT+ as well as V2, as previously reported in other studies investigating brain regions
involved in optic flow processing (Tootell et al., 1995; Morrone et al., 2000; Ptito et al, 2001).
This provides confirmation that this condition did provide typical activation observed when
exposed to visual motion information.
4.2 Heading Discrimination
Our results revealed bilateral BOLD responses in areas hMT+, V1, and DIPSM/L
and activation in the left V2 for the contrast ‘Heading Discrimination-Motor/Perceptual’.
Once contrasted with the Passive Viewing condition, however, the hMT+, V1, and V2
activations did not survive the subtraction, indicating these areas were not selectively involved
in the heading discrimination process. Past studies (Peuskens et al., 2001; Field et al., 2007;
Billington et al., 2010) have found contrary results where bilateral hMT+ activation remained
after their visual motion control condition was subtracted from the heading discrimination
condition. We attribute this discrepant finding to the difference in our control conditions.
Peuskens and colleagues’ (2001) two control conditions consisted of moving dots that
simulated forward movement and a static scene; however, the heading discrimination task
consisted of a lateral shift in FOE. Field and colleagues (2007) and Billington and colleagues
(2010) used a ground plane that simulated the perception of forward self-motion to control
for their heading discrimination task, which included additional visual information regarding
future path of a road. In contrast, our Passive Viewing condition provided changing flow
fields that were identical to those of the Heading Discrimination condition (+40O right, -40O
36
left, or 0O straight ahead), thus eliciting similar activation patterns in motion sensitive areas.
This suggests that although hMT+, V1, and V2 are needed for optic flow processing, they are
not specifically involved in the heading discrimination process.
The bilateral activation in the anterior and posterior DIPSM/L, however, was still
observed when we contrasted Heading Discrimination with Passive Viewing. This activation
is unlikely to be due to shifts in visuospatial attention (Corbetta et al., 1993; Shulman et al.,
2003), as this area would also be activated in the ‘Steering-Passive Viewing’. Similarly, it
cannot be explained by the presence of a motor response, as it was still present in the contrast
‘Heading Discrimination – Motor/Perceptual’. As in the present study, activation of DIPSM
posterior division was reported when estimating heading direction from ground plane moving
dots (Peuskens et al., 2001). It was proposed that this area might serve a similar role as area 7a
in the monkey, which is involved in the representation of extra-personal space and selfmotion (Read & Siegel, 1997; Andersen et al., 1987; Phinney & Siegel, 2000). This area might
be involved in a decision-related process (Peuskens et al., 2001). At variance with previous
work, however, is the observed activation in the anterior division of DIPSM/L. The texturerich 3D environment used in the present study may have additionally recruited the anterior
division, which is involved in the integration of sensorimotor and visual information for 3D
object recognition (Grefkes et al., 2002; Shikata et al., 2003), in addition to processing speed
and direction discrimination (Cornette et al., 1998; Büchel et al., 1998).
Furthermore, our coordinates for the anterior division (right: 12, -64, 62; left: -24, 60, 66) correspond closely to the coordinates reported by others for the parietal eye fields
(Koyama et al., 2004; Field et al., 2007). Our results thus agree with previous studies (Field et
al., 2007; Billington et al., 2010), where parietal eye field activation was observed in heading
discrimination tasks performed while both optic flow and path information was made
37
available to the participants. Present findings suggest that this parietal eye field involvement,
which is thought to be involved in processing visual information that aids in visuomotor
transformations (Andersen et al., 1997; DeSouza et al., 2000; Pouget & Sejnowski, 2001), is
largely contributed by optic flow. It cannot be excluded, however, that the participants used
other visual cues in the scene to create information in regards to future path.
4.3 Steering
We observed a larger network of activation for the contrast ‘SteeringMotor/Perceptual’ compared to all contrasts involving Heading Discrimination. The main
areas of activation include the bilateral hMT+, posterior cerebellum, supplementary and
frontal eye field (SEF; FEF), and premotor cortex. Unlike our contrast ‘Heading DirectionPassive Viewing’, hMT+ remained active in ‘Steering-Passive Viewing’ (right hMT+; 58, -62, 6) and additional visual processing areas (left V1, left V2) along with hMT+ displayed
activation in ‘Steering-Heading Discrimination’. Although visual processing areas, including
the hMT+, was not observed to be involved in the steering condition examined in Field and
colleagues’ (2007) study, a direct comparison between our results cannot be made due to the
difference in visual stimulus used. Past research has shown that the hMT+, along with other
basic visual processing regions (e.g. V2/V3), display strong activation when discriminating
speed and direction from optic flow (Orban et al., 1998; Sunaert et al., 2000; Wutte et al.,
2011) and the magnitude of activation is modulated by the degree of change in spatial and
featural attention in a visual stimulus (Beauchamp et al., 1997). Thus, our observation may be
genuinely due to higher demand in visual and optic flow processing created from constant
steering adjustments in response to shifts in FOE, which have yielded constantly changing
spatial and optic flow characteristics. Such changing characteristics of the flow field were not
present in the Passive Viewing and Heading Discrimination tasks, given that the participants
38
had no control over their perceived direction of movement. Our finding that V1 and V2
remained active in ‘Steering-Heading’ reinforces this idea that Steering can be more visually
demanding than Heading Discrimination. The need to continually adjust one’s trajectory in
the Steering task may require the observer to re-examine changing visual features of the
environment, judge the speed of their readjustments, and redirect their spatial attention to
accurately perform the task.
In the present study, activations in the posterior lobe of the cerebellum (bilateral Crus
I and VI lobule) were also found to be unique to steering. Bilateral activation in VI lobule
remained in ‘Steering-Heading Discrimination’, but Crus I was lateralized to the left side. The
anterior lobe has been associated with motor control whereas posterior lobe has been linked
with cognitive processes and higher-level tasks (Schmahmann & Sherman, 1998;
Schmahmann, 2007; Tavano et al., 2007). At variance with Field and colleagues (2007), we did
not observed activation in the anterior lobe of the cerebellum, which they attributed to the
processing of errors in the perceived trajectory compared to an internal prediction, and
possibly to the temporal coordination of eye and hand during the steering task. This is further
supported by the absence of a specific activation in the primary motor area in the steering
task. The lack of activation in the anterior lobe of the cerebellum further suggest that the
presence of a target for visual fixation most likely ensured similar eye movement behaviors
across the different tasks, although this cannot be confirmed experimentally due to the lack of
valid eye recordings.
Specific activity in the VI lobule has been associated with judgment of spatial
orientation (Lee et al., 2005) and spatial navigation through a virtual environment (Moffat et
al., 2006). Crus I was also shown to be involved in executive function and in using visual
information to plan movement direction (Blackwood et al., 2004; Harrington et al., 2004; Taig
39
et al., 2012). This suggests that the cerebellar posterior lobe activation observed in this study
might be due to high level spatial and executive functioning processes associated with the
planning and online monitoring of the observer’s perceived position in space during simulated
self-motion.
We also observed bilateral activation in the SEF and FEF. These two areas are
anatomically connected in the human brain showing more prominent connections in the right
hemisphere (Anderson et al., 2012). This may explain the lateralized FEF activation we
observed in Steering-Motor/Perceptual but not Steering-Heading, as activations associated
with heading may have ‘canceled out’ this lateralization effect. We propose that SEF may be
specifically involved in steering to monitor one’s motor performance using visual information
(Purcell et al., 2012). In monkeys, the SEF is shown to send projections to the striatum
(Parthasarathy et al., 1992), suggesting also the use of visual information to guide motor
performance (Schall & Boucher, 2007). Again, we cannot fully exclude the possibility that
activation in the SEF an FEF may be attributed to saccades. These regions have been shown
to display increase BOLD responses depending on saccade frequency (Kimmig et al., 2001).
However, fMRI preprocessing data reveal that head movement was minimal and in monkeys,
PEF and FEF may be activated independent of saccades (Gottlieb & Goldberg, 1999; Bisley
& Goldberg, 2003).
Lastly, similar to the IPS, bilateral activation in the premotor reflects sensorimotor
and crossmodal integration (Draganski et al., 2008). As Peusken and colleagues’ (2001)
suggested, the premotor cortex may act as the final stage of the parieto-premotor visuomotor
pathway where projections are sent from the premotor cortex to the striatum (Draganski et
al., 2008) to influence visually guided motor performance (Grafton et al., 1998).
4.3 Design Limitations
40
Our study used translational optic flow to simulate forward and sideways movement
in order to elucidate the brain regions involved in heading discrimination and locomotive
steering. In reality, however, we also walk along curved paths, which comprises of a rotational
optic flow created by horizontal eye, head, and body rotations (Grasso et al., 1998; Imai,
Moore et al., 2001; Hollands et al., 2002). Although our study design did not allow us to
reveal the brain regions involved in heading discrimination and steering using rotational flow,
it allowed us to attribute our findings to brain regions associated with mediolateral
displacement steering strategy (Warren et al., 2001; Sarre et al., 2008).
In addition, although we intended to use a texture-rich environment to create optic
flow, we cannot exclude the possibility that the participants used any cues from the scene to
aid in heading estimation and steering. However, our scene did not include any visual targets
or landmarks where the observer might use as a reference point (e.g. egocentric strategy). In
addition, we did not observe any significant BOLD responses in the medial parietal cortex,
which has been shown to be involved in navigation using allocentric heading information
(Baumann & Mattingley, 2010). Thus, it is not likely that allocentric heading was used to aid in
steering.
4.4 Conclusion & Future Directions
Although heading discrimination and steering are two critical components to goaldirected locomotion, few studies investigated the neural correlates for these two processes.
Using an ecological virtual environment, we were able to demonstrate that the posterior and
anterior division of DIPSM/L is specifically involved in heading discrimination from optic
flow and the posterior cerebellum is involved in steering, which has not been observed in
previous studies using moving dots or a ground plane. In the steering task, it is proposed that
hMT+ is involved in optic flow processing, which is needed when we move through our
41
environment, while the SEF helps monitor one’s motor performance using visual information
and subsequently sends projections to the striatum to influence motor commands. The
cerebellum and premotor cortex is involved in motor planning and aids in executing the
appropriate motor response. Thus, our observations reflect the pathway in which visual
information is transformed into goal-directed action. Our findings may help understand why
those with occipitoparietal and parietotemporal lobe lesions display difficulty in using optic
flow to discriminate heading (Billino et al., 2009; Young et al., 2010; Kavcic et al., 2011) and
locomotor steering is impaired post stroke (Lamontagne et al., 2010). A comparison between
brain lesion sites and the brain areas involved in heading discrimination and steering can
provide further insight into the neuroanatomical structures needed to achieve goal-directed
locomotion.
Acknowledgements
We would like to thank all our participants as well as Christian Beaudoin, André Cry, Andrei
Garcia-Popov, Valeri Goussev, and Carollyn Hurst for their technical assistance. This study
was funded by Canadian Institutes of Health Research (CIHR) (MOP 77548). A. Lamontagne
is the recipient of a CIHR New Investigator Award (2006-11) and FRQS Junior 2 Salary
Award (2011-13). R.H., J.D., J.F. and A.Lamontagne are researchers of the multidisciplinary
SensoriMotor Rehabilitation Research Team [http://www.errsm.ca/], an emerging research
team in Regenerative Medicine and Nanomedicine funded by the CIHR.
42
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Figure Captions
Figure 1. This figure represents the virtual environment (VE) used for all conditions. In
conditions where visual motion information was present, the VE would describe and
expanding optic flow with a focus of expansion located straight ahead (0º) or shifted
±40º to the side, while the triangle would remained centered to allow gaze fixation.
In the Motor/Perceptual task, the orientation of the triangle was changing and
pointing either up, right or left.
Figure 2. Areas activated in the contrast Heading discrimination – Motor/Perceptual:
a) right and left DIPSM/L b) sagittal view of the DIPSM/L
c) left hMT+ d) right and left V1 e) left V2
Figure 3. Activated brain regions associated with the contrast Steering – Motor/Perceptual
vs. Heading Discrimination – Motor/Perceptual. A generally more widespread
activation pattern is observed in Steering, especially in the occipital lobe region
containing area hMT+ and other brain structures involved in optic flow
processing.
Figure 4. Area activated in the contrast Steering – Heading discrimination (beige) vs.
Steering – Motor/Perceptual (blue) vs. overlapping activations observed in both
contrasts (purple): a) sagittal view of cerebellum (Curis I and VI) b) bilateral
activation in the posterior lobe of cerebellum c) premotor cortex d) supplementary
eye fields (SEF). Note: the premotor cortex and SEF are circled.
53
Table Captions
Table 1. Peak activations for contrast
“Heading discrimination – Motor/Perceptual”
Table 2. Peak activations for contrast “Steering – Motor/Perceptual”
Table 3. Peak activations for contrast “Steering – Heading discrimination”
53
!
!
Figure 1. This figure represents the virtual environment (VE) used for all conditions. In conditions where visual motion information was present, the VE would
describe and expanding optic flow with a focus of expansion located straight ahead (0º) or shifted ±40º to the side, while the triangle would remained
centered to allow gaze fixation. In the Motor/Perceptual task, the orientation of the triangle was changing and pointing either up, right or left.
!
!
!
54
!
!
!
!
!
!
!
!
Figure 2. Areas activated in the contrast Heading discrimination – Motor/Perceptual:
a) right and left DIPSM/L b) left hMT+ c) right and left V1 d) left V2
!
!
55
Figure 3. Activated brain regions associated with the contrast Steering – Motor/Perceptual vs. Heading
Discrimination – Motor/Perceptual. A generally more widespread activation pattern is observed in
Steering, especially in the occipital lobe region containing area hMT+ and other brain structures
involved in optic flow processing.
56
!
!
!
Figure 4. Areas activated in the contrast Steering – Heading discrimination (beige) vs. Steering – Motor/Perceptual (blue) vs. overlapping activations observed in both
contrasts (purple): a) sagittal view of cerebellum (Crus I and VI) b) bilateral activation in the posterior lobe of cerebellum c) premotor cortex
d) supplementary eye fields (SEF). Note: the premotor cortex and SEF are circled
! 57
!
Table 1. Peak activations for contrast “Heading discrimination – Motor/Perceptual”
Brain region
Parietal lobe
R Superior parietal lobule 7A
L Superior parietal lobule 7A
R Superior parietal lobule 7P
L Superior parietal lobule 7P
L Superior parietal lobule 5L
Occipital lobe
R Lateral Occipital cortex, inferior division
L Lateral Occipital cortex, inferior division
R Visual cortex (V1, BA17)
L Visual cortex (V1, BA17)
L Visual cortex (V2, BA18)
z
MNI Coordinates
x
y
z
DIPSM/L
DIPSM/L
DIPSM/L
DIPSM/L
4.83
5.06
4.32
4.6
4.58
12
-24
-10
-16
-8
-64
-60
-70
-78
-54
62
66
56
54
68
hMT+
hMT+
4.76
4.55
4.76
9
5.4
44
-50
16
-6
-16
-66
-78
-100
-100
-96
4
2
10
8
20
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
58
!
Table 2. Peak activations for contrast “Steering – Motor/Perceptual”
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
!
Brain region
Frontal lobe
R Middle frontal gyrus
R Premotor cortex
L Premotor cortex
Parietal lobe
L Secondary somatosensory cortex / Parietal
operculum OP1
L Inferior parietal lobule PFop
Occipital lobe
R Lateral Occipital Cortex, inferior division
L Lateral Occipital Cortex, inferior division
L Occipital Fusiform Gyrus
L Planum temporale
Temporal lobe
R Middle Temporal Gyrus, temporooccipital part
Cerebellum
R Crus I
L Crus I
R VI
L VI
z
frontal eye field
hMT+
hMT+
MNI Coordinates
x
y
z
5.87
6.64
5.21
4.7
36
52
48
-52
-2
8
2
8
54
20
50
32
5.04
-62
-24
22
4.87
-62
-38
20
7.62
7.5
5.43
4.75
42
-48
-40
-52
-64
-76
-74
-38
-4
2
-18
14
4.88
66
-50
-2
5.06
4.87
5.51
4.79
36
-18
34
-24
-74
-88
-64
-72
-22
-24
-22
-22
59
!
Table 3. Peak activations for contrast “Steering-Heading Discrimination”
Brain regions
Frontal lobe
R Premotor cortex BA6
z
6.15
4.88
4.93
4.76
4.65
4.92
4.84
5.28
5.25
44
-22
6
22
-4
-26
-52
52
-32
-8
-28
14
4
12
-26
6
18
14
52
62
56
62
48
64
8
-6
2
6.23
5.37
4.83
5.64
-60
-34
-52
-60
-28
-26
-38
-20
38
60
12
18
Supplementary eye fields
5.86
4
-2
54
hMT+
5.52
5.79
5.79
5.56
4.78
4.75
42
30
-44
-20
-14
-26
-64
-88
-70
-82
-106
-104
-20
0
0
22
4
0
L Premotor cortex BA6
L Precentral gyrus
R VLPFC BA47
Parietal lobe
L Inferior parietal lobule
L Primary motor cortex
L Planum temporale
L Secondary somatosensory cortex / Parietal
operculum
R/L Supplementary motor cortex
Occipital lobe
R lateral occipital cortex, inferior division
L lateral occipital cortex, inferior division
L lateral occipital cortex, superior division
L Visual cortex V1 BA17
L Visual cortex V2 BA17
Cerebellum
L Crus I
!
MNI Coordinates
x
y
z
hMT+
5.34
-26
-76
-20
R VI
5.54
36
-64
-20
L VI
5.35
-26
-72
-22
!
!
!
!
!
!
!
!
!
!
60
Chapter 3
Conclusions
Although heading discrimination and steering are two critical components to goaldirected locomotion, few studies investigated the neural correlates for these two processes.
Using an ecological virtual environment, we were able to demonstrate that the posterior and
anterior division of DIPSM/L is specifically involved in heading discrimination from optic
flow and the posterior cerebellum is involved in steering, which has not been observed in
previous studies using moving dots or a ground plane. In the steering task, it is proposed
that hMT+ is involved in optic flow processing, which is needed when we move through
our environment, while the SEF helps monitor one’s motor performance using visual
information and subsequently sends projections to the striatum to influence motor
commands. The cerebellum and premotor cortex is involved in motor planning and aids in
executing the appropriate motor response. Thus, our observations reflect the pathway in
which visual information is transformed into goal-directed action. Our findings may help
understand why those with occipitoparietal and parietotemporal lobe lesions display
difficulty in using optic flow to discriminate heading (Billino et al., 2009; Young et al., 2010;
Kavcic et al., 2011) and locomotor steering is impaired post stroke (Lamontagne et al., 2010).
A comparison between brain lesion sites and the brain areas involved in heading
discrimination and steering can provide further insight into the neuroanatomical structures
needed to achieve goal-directed locomotion.
62
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Appendices
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RNQ
COMITÉ MIXTE D’ÉTHIQUE DE LA RECHERCHE
INFORMED CONSENT FORM
Title of the research project :
Investigator :
Co-investigators :
Collaborators :
Funding organization :
Visuomotor control of locomotion: a functional Magnetic
Resonance Imaging study
Anouk Lamontagne, Ph.D., PT
Jewish Rehabilitation Hospital (JRH) and School of Physical and
Occupational Therapy, McGill University
Julien Doyon, Ph.D.
Department of Psychology, University of Montréal
Jocelyn Faubert, Ph.D.
School of Optometry, University of Montréal
Joyce Fung, Ph.D.
JRH and School of Physical and Occupational Therapy
Rick Hoge, Ph.D.
Department of Psychology, University of Montréal
Anita Liu, H.BSc, M.Sc Candidate
JRH and Department of Neurology and Neurosurgery, McGill
University
Canadian Institutes of Health Research
Preamble
We would like to invite you to participate in a neuroimaging research project. However, before
accepting to participate in this research project and sign this informed consent form, please take the
time to read, understand and consider carefully the following information.
The informed consent form may contain words that you do not understand. We invite you to ask any
questions that you deem useful to the researcher or members involved in the project, in order for them
to explain or clarify any words or information that does not seem clear.
Aim and objective of research project
You are invited to participate in this neuroimaging study that seeks to elucidate which brain regions
are used to discriminate and to actively control the direction of perceived self-motion using visual
information.
We are interested in this information because persons who suffered a brain lesion, such as a stroke,
are often faced with mobility problems. These mobility problems include a slow gait speed and
difficulties using visual information to steer in the desired direction. By identifying brain regions of
interest in healthy young adults, we can gain insight into which brain regions may be altered after
stroke that lead to mobility problems.
To do so, you will be viewing a virtual room moving in different directions. As a result, you will perceive
yourself as walking in different direction in this virtual room, as in a video game. You will be required to
identify your perceived direction of self-motion within this environment or to actively steer in a desired
destination with a joystick. The specific objectives are:
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1- To identify the brain regions used to discriminate and actively control the direction of visually
perceived self-motion
2- To investigate whether different speeds of perceived self-motion will affect the intensity of brain
activation when identifying the direction of perceived self-motion
We will be recruiting a total of 16 male and female participants, aged 18-29, for this project .
What is magnetic resonance imaging (MRI)
Magnetic resonance imaging is a medical technique that produces pictures of the brain and internal
organs. It can also perform functional assessments. It is based on a natural force present around us:
magnetism. It uses a strong magnetic field generated by a large magnet positioned around a sliding
bed.
MRI allows us to study not only the anatomy but also the function of the brain. In this case, the MRI
permits us to see how different regions of the brain work together, independently of the performance
of a task. When neuronal activity is increased in a region of the brain, there is a local increase in
oxygenated blood flow in the brain areas where this activity occurs. This local increase in oxygenated
blood flow in turn causes a local increase in MR signal over activated brain areas and this increase in
MR signal is detected by the MRI machine.
During the magnetic resonance imaging test, you will be lying on a mattress that will slowly move into
a large tube. This tube is open on both ends, with excellent ventilation and illumination. An intercom
system will allow you to communicate with the technician. For your comfort, we will ask you to wear
earplugs and a headset to decrease the significant noise emitted by the machine. While the machine
is operating, it is important to remain very still. For this purpose, a cushion will be placed around your
head to help you immobilize it. You will not be injected with any substances.
Outline of the research project
This research project will take place at the Unité de Neuroimagerie Fonctionnelle of the Institut
universitaire de gériatrie de Montréal.
The experiment takes place over one (1) session including a data collection block (~ 90min) that is
preceded by a pre-test screening (~ 20min) and a training block (~ 30min), for a total duration of ~ 2
hours and 20 minutes.
Screening: To determine your eligibility to participate in this study, we will first test your visual acuity
and cognitive function. Those with !20/20 vision, or corrected vision (contacts only), and have scored
>25/30 on the MoCA will proceed to the pre-test training.
Pre-Test Training: Before data collection, you will be invited to be in a room and a ‘mock’ scanner
that will simulate what you will be doing and seeing during data collection. The instructions of each
task will be explained to you and you will be provided practice trials until you achieve correct
responses in 80% of the trials or 8 consecutive good trials.
Data collection: Data collection consists of three (3) tasks presented in a random order. For each
task, you will be visualizing a same virtual environment that resembles a museum room. Like in a
video game, the virtual environment presented on the screen will be animated and move in different
directions. The tasks three (3) tasks that will be tested are the following:
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1. Discrimination of direction: You will be asked to identify the direction of your perceived selfmotion within the virtual environment using a joystick.
2. Active steering: You will be asked to move within the virtual environment using the joystick so
that you remain centered in the moving room.
3. Discrimination of direction at different speeds: In this task, the virtual environment will be
moving at different speeds for each trial. Similar to the discrimination task, you will be asked to
indicate your perceived direction of self-motion by using the joystick.
Advantages of the proposed study
There are no advantages from participating in this research project. However, the knowledge acquired
will contribute to better understand which brain areas are involved in the control of locomotor steering
and hence how a lesion in such regions may lead to mobility problems in stroke.
Inconveniences of the proposed study
The requirements imposed by the use of magnetic resonance imaging may cause certain discomfort
due to the need to remain still and the noise, which is generated by the MRI when images are being
acquired. You may also feel a certain sense of stress or anxiety or a sense of claustrophobia.
Risks associated to this research project
According to the latest knowledge there is no known health risk associated with the use of this
technique when all the necessary steps of precaution are taken as long as you do not have any
contra-indications.
Due to the strong magnetic field emitted by the MRI, it is necessary to take certain precautions. This is
why before participating in a MRI session you must complete two detailed screening forms in order to
detect any contra-indications before submitting to an examination, for example, a cardiac pacemaker,
an aneurysm clip, a metal prostheses or cardiac valve replacement, the presence of metal in an eye or
any part of the body, tattoos, body piercing, certain dental work or if you suffer from claustrophobia.
(See annexed questionnaire).
Verification of the presence of the contra-indications will be strictly reinforced by the technologist on
duty at the Unité de neuroimagerie fonctionnelle.
Risks associated with pregnancy
Some recent studies suggest that MRI could entail certain risks for embryo and fetus health. These
risks are attributed to the radiofrequency magnetic field that may cause heating, as well as the
gradient fields that can produce a lot of noise from their interaction with the static magnetic field.
Consequently, pregnant and breast-feeding women are excluded from the study. Women that could
potentially become pregnant must take a pregnancy test before participating in this study.
Information return and incidental findings
Research scans are not subject to any neuroradiological evaluation. However, the magnetic
resonance examination could highlight problems that you have not been aware of up until now. This is
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the reason why, in the presence of any particularity of concern at the time of your examination, you will
be invited to undergo a new examination with a scanner at 1.5 Tesla for verification. Upon the
confirmation of an anomaly, a neurologist will forward these data to your family doctor or will provide
follow-up.
Voluntary participation and possibility to withdraw
Your participation in this research project is completely voluntary. You are therefore free to refuse to
participate in this study. You may also withdraw at any time during the project, without giving any
reasons by informing the principal investigator or associated personnel about your decision.
The principal investigator of the project, the Comité mixte d’éthique de la recherche du RNQ, the
Comité d’éthique de la recherche des établissements du CRIR or the funding organization can
terminate your participation, without your consent, if new results or information indicate that your
participation in this research project is not anymore in your interest, if you do not respect the
instructions of the research project or if there exist administrative reasons for terminating the project.
If you decide to withdraw from the project or if your participation is terminated, the information that has
already been acquired from you in the course of the project will be conserved as long as necessary to
meet regulatory requirements.
Any new information that is acquired in the course of the project and which may affect your decision to
continue to participate in this research project will be communicated to you without delay verbally and
in writing.
Confidentiality
During your participation in this study, the researchers and their personnel will collect and record all
information that concerns you in a research file. Only information needed for the correct performance
of the study will be collected.
This information may include your past and present health condition as well as the results of all the
tests, examinations, and procedures that you will undergo during this study. Your file may also include
other information such as your name, gender and date of birth.
All of the information collected in the course of the study will remain strictly confidential, within the
limitations specified by law. In order to preserve your identity and the confidentiality of this information,
you will only be identified by a code number. The key of the code linking your name to your research
file will be kept by the study researcher.
The study researcher will use the study data for research purposes in order the meet the scientific
objectives of the study as described in the consent form.
The study data may be published in scientific journals or shared with other persons during scientific
discussions. No publication or scientific communication will disclose any information that would allow
you to be identified. In addition, the research project data may also help for other data analysis related
to the project or for the development of future research projects. Your personal information, such as
your name and address, will be destroyed 5 years after the end of this project.
For monitoring and control purposes, your research file may be consulted by a person designated by
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the Comité mixte d’éthique de la recherche du RNQ, by the Comité d’éthique de la recherche des
établissements du CRIR, by the establishments or by an authorized person of certain authorized
public organizations. All of these persons and organizations adhere to the rules of confidentiality.
For protection purpose and in order to contact you quickly, your name, address, phone number as well
as the beginning date and the ending date of your participation in the project will be conserved by the
principal investigator in a repertory for one year after the completion of the project.
You have the right to consult your research file to verify the correctness of the collected information, to
have out-of-date or unjustified information corrected or deleted, and to make copies, for as long as the
study researcher possesses this information.
Subsequent studies
Do you allow other members of the research team to contact you to participate in other prospective
research projects? ! Yes
! No
These would be projects similar to this one. Only the lead researcher on the project will have access
to this information. Your details will not be kept longer than five years and the period of recall does not
exceed that period. Of course, during this call, you are free to accept or decline participation in
research projects proposed.
Financial compensation
Transportation and parking costs incurred through your participation in this study will be reimbursed,
up to a maximum of $75.
Source of funding for the project
The researcher was granted with funding from the funding organization to conduct the present project.
All the pertaining costs and expenses will be covered by the received grant.
Compensation in case of prejudice and research subject's rights
In the event of complications resulting from your participation in this research project, you will receive
the necessary medical care, at no cost.
By taking part of this project, you do not resign any of your legal rights nor do you free the
researchers, the funding organization or the establishment of any civil and professional
responsibilities.
Emergency procedures
Please note that the Institut Universitaire de Gériatrie de Montréal is not a hospital that has an
emergency unit. In case of a medical condition requiring an immediate action, the first care would be
offered by the employees on site and, if necessary, dispositions would be taken in order to transfer
you to the emergency service of a nearby hospital.
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Identification of persons/resources
If you have questions related to this research project or if you encounter a problem that you believe
results from your participation in this research project, you can communicate with the principal
investigator of this project, Dr. Anouk Lamontagne at 450-688-9550 extension 531.
For any questions concerning your rights as a participant in this research project or if you have
complaints or comments you would like to express, you can contact a local commissioner for the
quality of services of the IUGM at (514) 340-3517.
If you have any questions about your rights and recourse or your participation in this research study,
you can contact Me Anik Nolet, Research Ethics Co-ordinator for the CRIR’S Institutions at (514) 5274527 extension 2649 or by e-mail [email protected]
Ethical surveillance of the research project
Le Comité mixte d’éthique de la recherche du RNQ and the Comité d’éthique de la recherche des
établissements du CRIR has approved the present research project and they will keep track of the
project. In addition, the ethics committee will beforehand approve any revision and modification of the
information and consent form and of the research protocol. For any information, you can contact the
Comité mixte d’éthique de la recherche du RNQ at (514) 340-2800 extension 3250.
You can also contact Me Anik Nolet, Research Ethics Coordinator of the CRIR establishments at (514)
527-4527 extension 2643 or by e-mail at [email protected]
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Consentement
Project title:
Visuomotor control of locomotion: a functional Magnetic Resonance
Imaging studyInformation
I. Consent of participant
I have read and understood the present information and consent form. I confirm that the project has
been explained to me, that my questions have been answered and that I have been given enough
time to make my decision.
I consent to participate in this research project at the described conditions. I have been given a signed
and dated copy of the information and consent form.
Name and signature of participant
Date
II. Signature of the person who obtained the consent if different from the principal investigator
of the research project.
I have explained the terms of the present information and consent form to the participant and I have
answered the questions that he/she has asked me.
Name and signature of the person who obtains the consent
Date
III. Signature and engagement of the principal investigator of this project
I certify that the terms of the present information and consent form have been explained to the
research participant, that the questions of the participant with respect to this have been answered and
that it has been clearly indicated to him/her that he/she remains free to withdraw from the present
study without prejudice.
I commit with the research team to respect the agreements described in the information and consent
form and to give a signed copy to the research participant.
Name and signature of the principal investigator of this research project
Date
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PRELIMINARY SCREENING FOR MAGNETIC RESONANCE IMAGING STUDY (MRI)
Please print
Last name :
Date of birth :
First name :
Sex : F ¹
M ¹
Weight : ___ kg ___ lbs
(day/month/year) Height : ___ m ___ pi
Investigator :
Identification number :
In order to ensure the safety of everyone having access to the area of Functional
Neuroimaging Unit, it is of the utmost importance that this questionnaire be
completed by the subject and investigator
1. Have you ever had any previous operation?
No
Yes If yes, please specify the type of surgery and the date :
Head
Chest or heart
Abdomen
Arms, hands
Legs, feet
Vertebral column
Eyes
Others :
2. Are you carrying any of the following :
Pacemaker?
Cardiac electrodes?
Aneurysm clip?
Cochlear protheses? Hearing aid?
Vascular filtre or catheter?
Neurostimulator?
Electrical stimulator for the bones?
Prosthetic cardiac valve?
Metal or metallic fragments in any part of the body? (e.g. bullet, shrapnel or
No
Yes
metal silvers)?
Insulin pump implant?
Orthopedic prostheses? (e.g.: nail, screw, plate)
Artificial limb(s)?
Permanent make-up? Tattoo(s)?
Body piercing?
Magnetic or non-magnetic implant(s)?
Diaphragm or any intra-uterine devise (IUD)?
85
!
!
!
!
!""#$%&'(*(
Denture or orthodontics devises (e.g. braces)?
Eye implant(s) or prosthesis?
Transdermal patches (e.g. nitroglycerin patch)
Others :
3. Are you pregnant or do you believe you are?
no
yes
4. If any doubt, do you accept to have a pregnancy test?
no
yes
5. Do you suffer from claustrophobia?
no
yes
6. Have you ever been injured by metal objects
no
(e.g: car accident, work accident, war wounds)
If yes, please specify: ___________________________________
yes
7. Have you ever had previous magnetic resonance imaging test? no
yes
8. Have you ever been a:
Mechanist?
Welder?
Heavy machinary operator?
Metal worker ?
no
no
no
no
yes
yes
yes
yes
9. Do you have any respiratory or motor disorder?
no
yes
I fully understand the procedures, advantages and disadvantages of the study using magnetic
resonance imaging which have been explained to me. Further, the application safety measures
have been fully explained to me and all my questions have been answered to my satisfaction. I
certify that all the information provided above are correct and exact to the best of my knowledge
and I freely and voluntarily consent to participate in this MRI study.
___________________________________
Signature (participant/parent/legal sponsor)
_________________
Date
___________________________________
Signature (physician/investigator)
__________________
Date
_
Espace réservé
Participation autorisée :
Investigation:
non
non
_
_
_
oui
oui
86
!""#$%&'()(
56#/!
Steering
-.#/012/34.#!
Motor/
Perceptual
-.#/012/34.#!
56#/!
-.#/012/34.#!
-.#/012/34.#!
-.#/012/34.#!
-.#/012/34.#!
56#/!
Heading
Discrimination
-.#/012/34.#!
Five Conditions
Two Experimental: 1. Heading Discrimination
2. Steering
Three Controls: 1. Rest
2. Motor/Perceptual
3. Passive Viewing
Experimental Block Design
!
!
!
!
-.#/012/34.#!
!
!
56#/!
Passive
Viewing
1 Run =
8-10min
Repeated 5
times
!!"#!!!!!!!!$%#!!!!!!!!!!"#!!!!!!!!!!!!&'(#!!!!!!!!!!!!!!!!!!"#!!!!!!!!$%#!!!!!!!!!"#!!!!!!!!!!!!!!!&'(#!!!!!!!!!!!!!!!"#!!!!!!!!!$%#!!!!!!!!!"#!!!!!!!!!!!!!!!&'(#!!!!!!!!!!!!!!!"#!!!!!!!!$%#!!!!!!!!!"#!!!!!!!!!!!!!&'(#!
!
!
! Trials
in “Heading Discrimination” & “Steering”
Trials in “Motor/Perceptual”
!!!!!!!!$)*#!!!!!!!!!!!!!$)*#! !
!
!!!!!!!+%#!!!!!!!!!!!!!!+%#,!
!
!
!
!
!
!
!
!
!
#/7/32!
!
#/7/32!
!
#/7/32!
!
#/7/32!
!
#/7/32!
89:!
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!
!
!
!
!
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!
#/7/32!
89:!
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#/7/32!
89:!
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89:!
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!
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!!!!$)*#!!!!!!!!!!!!!$)*#!
!!!!!!!!!!!!!!!+%#!!!!!!!!!!!!!!+%#,!
!
!
!
!!!!!!!!!!!
!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!Randomized Order
(3 FOE location x 2 repetitions)
Randomized Order
(3 FOE location x 2 repetitions)
• Scene is static for “Heading Discrimination” Block
• Scene is moving for “Steering” Bloc
87
!
!
!""#$%&'()(
!
!
Discrimination & Steering Tasks (Moving Scene)
* FOE = Field of View
FOE 40o Left
FOE 0o
FOE 40o Right
Motor/Perceptual Control Task (Static Scene)
!
!
Shift Joystick
Left
Shift Joystick
Up
!
Shift Joystick
Right
88