Download Contribution of Pedunculopontine Tegmental Nucleus Neurons to

J Neurophysiol
88: 715–731, 2002; 10.1152/jn.00484.2001.
Contribution of Pedunculopontine Tegmental Nucleus Neurons to
Performance of Visually Guided Saccade Tasks in Monkeys
YASUSHI KOBAYASHI,1 YUKA INOUE,1,2 MASARU YAMAMOTO,1 TADASHI ISA,1,3,4 AND
HIROSHI AIZAWA1,5
1
Department of Integrative Physiology, National Institute for Physiological Sciences; 2The Japan Society for the Promotion
of Science; 3The Graduate University for Advanced Studies; 4Core Research for the Evolutionary Science and Technology,
Japan Science and Technology Corporation, Myodaiji, Okazaki 444-8585, Japan; and 5Department of Physiology, School of
Medicine, Hirosaki University, Hirosaki 036-8562, Japan
Received 12 June 2001; accepted in final form 25 March 2002
Kobayashi, Yasushi, Yuka Inoue, Masaru Yamamoto, Tadashi
Isa, and Hiroshi Aizawa. Contribution of pedunculopontine tegmental nucleus neurons to performance of visually guided saccade tasks in
monkeys. J Neurophysiol 88: 715–731, 2002; 10.1152/jn.00484.2001.
The cholinergic pedunculopontine tegmental nucleus (PPTN) is one of
the major ascending arousal systems in the brain stem and is linked to
motor, limbic, and sensory systems. Based on previous studies, we
hypothesized that PPTN would be related to the integrative control of
movement, reinforcement, and performance of tasks in behaving animals.
To investigate how PPTN contributes to the behavioral control, we
analyzed the activity of PPTN neurons during visually guided saccade
tasks in three monkeys in relation to saccade preparation, execution,
reward, and performance of the task. During visually guided saccades, we
observed saccade-related burst (26/70) and pause neurons (19/70), indicating that a subset of PPTN neurons are related to both saccade execution and fixation. Burst neurons exhibited greater selectivity for saccade
direction than pause neurons. The preferred directions for both burst and
pause neurons were not aligned with either horizontal or vertical axes, nor
biased strongly in either the ipsilateral or the contralateral direction. The
spatial representation of the saccade-related activity of PPTN neurons is
different from other brain stem saccade systems and may therefore relay
saccade-related activity from different areas. Increasing discharges were
observed around reward onset in a subset of neurons (22/70). These
neurons responded to the freely delivered rewards within ⬃140 ms.
However, during the saccade task, the latencies of the responses around
reward onset ranged between 100 ms before and 200 ms after the reward
onset. These results suggest that the activity observed after appropriate
saccade during the task may include response associated with reward. We
found that the reaction time to the appearance of the fixation point (FP)
was longer when the animal tended to fail in the ensuring task. This
reaction time to FP appearance (RTFP) served as an index of motivation.
The RTFP could be predicted by the neuronal activity of a subset of
PPTN neurons (13/70) that varied their activity levels with task performance, discharging at a higher rate in successful versus error trials. A
combination of responses related to saccade execution, reward delivery,
and task performance was observed in PPTN neurons. We conclude from
the multimodality of responses in PPTN neurons that PPTN may serve as
an integrative interface between the various signals required for performing purposive behaviors.
INTRODUCTION
Address for reprint requests: Y. Kobayashi, Osaka University Graduate
School of Frontier Biosciences, Laboratories for Neuroscience Visual Neuroscience Group, 1-3 Machikaneyama, Toyonaka 500-8531, Japan.
The costs of publication of this article were defrayed in part by the payment
of page charges. The article must therefore be hereby marked ‘‘advertisement’’
in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
www.jn.org
The pedunculopontine tegmental nucleus (PPTN) and laterodorsal tegmental nucleus (LDTN) are major sources of
cholinergic projections in the brain stem and contain both
cholinergic and glutamatergic neurons (Hallanger and Wainer
1988). PPTN is a part of the reticular activating system, which
provides background excitation for several sensory and motor
systems and is essential for perception (Lindsley 1958) and
cognitive processes (Steckler et al. 1994a). Reciprocal connections have been demonstrated between PPTN and the output
structures of the basal ganglia: the subthalamic nucleus, the
globus pallidus, and the substantia nigra (Edley and Graybiel
1983; Lavoie and Parent 1994), and between PPTN and catecholaminergic systems in the brain stem: the locus coeruleus
(LC) and the dorsal raphe nucleus (DRN) (Koyama and
Kayama 1993). The basal ganglia–PPTN– catecholaminergic
system complex is thought to play an important role in gating
movement and controlling several attentive behaviors (AstonJones et al. 1996; Garcia-Rill 1991). Despite the abundance of
anatomical data, however, the functional role of PPTN neurons
for behavioral control is not sufficiently understood.
A role for PPTN in the control of movement has been
suggested by a number of observations (arm movement: Matsumura et al. 1997; locomotion and posture control: GarciaRill 1991). It has also been shown that lesions of PPTN reduce
the frequency of eye movements during REM sleep (Shouse
and Siegel 1992). The frontal eye field (FEF) (Bruce and
Goldberg 1985) and substantia nigra pars reticulata (SNr)
(Hikosaka and Wurtz 1983) are related to controlling saccadic
eye movements, and both FEF neurons (Matsumura et al.
2000) and GABAergic SNr neurons (Gerfen et al. 1982;
Granata and Kitai 1991) project to the PPTN. These findings
suggest that PPTN may contribute to controlling eye movements, particularly saccades.
The cholinergic PPTN also strongly innervates the intermediate layer of the superior colliculus (SC) in various mammalian species (Beninato and Spencer 1986; Graybiel 1978; Hall
0022-3077/02 $5.00 Copyright © 2002 The American Physiological Society
715
716
Y. KOBAYASHI, Y. INOUE, M. YAMAMOTO, T. ISA, AND H. AIZAWA
et al. 1989; Henderson and Sherriff 1991; Jeon et al. 1993; Ma
et al. 1991; Schnurr et al. 1992). SC is involved in the generation of saccades (Sparks and Hartwich-Young 1989). The
neuronal activity of the intermediate layer of SC preceding
saccade execution is influenced by attentional shifts (Sheliga et
al. 1997), movement selection (Glimcher and Sparks 1992),
and the degree of motor preparation (Basso and Wurtz 1998;
Dorris and Munoz 1998). To clarify the role of the cholinergic
input to the intermediate layer of SC in saccades, we previously examined the effect of microinjection of nicotine into the
SC on visually guided saccades in monkeys. After injection of
nicotine, the saccadic reaction times decreased dramatically
(Aizawa et al. 1999), suggesting that cholinergic inputs to SC
influence saccade initiation.
PPTN also projects to the dopaminergic neurons of the
substantia nigra pars compacta (SNc) (Beninato and Spencer
1986) that encode an error signal for reinforcement learning
(Schultz 1998). PPTN receives limbic inputs from the hypothalamus, the ventral tegmental area (Semba and Fibiger
1992), and the limbic cortex in monkeys (Chiba et al. 2001).
A recent computational model (Brown et al. 1999) predicts
that PPTN is a major source of the excitatory signal to the
SNc and is an important component of reinforcement learning, demonstrating that PPTN may be involved in reinforcement mechanisms.
Performance of the behavioral tasks may depend on the
attentive and motivational state of the animal. Many studies
suggest that PPTN and LDTN control wakefulness or vigilance levels and may induce a global attentive state in
response to a novel stimulus (Datta and Siwek 1997;
Koyama et al. 1994; Steriade 1996a,b). Several motivated
behaviors of rats driven by rewards are controlled by PPTN
(Bechara and van der Kooy 1989; Bechara et al. 1995;
Stefurak and van der Kooy 1994).
In conditioned cats, reversible blockage of PPTN by muscimol injection caused elongation of inter-trial intervals in a
lever-release task (Condé et al. 1998). Bilateral lesions of
PPTN in rats did not affect performance in a simple maze task
(the cross-maze task: requiring simple memory of place), but
did decrease performance in another maze task (the radialmaze task) which required simple memory of place and sustained attention during search (Dellu et al. 1991). In addition,
lesions of PPTN in rats did not produce marked deficits in the
accuracy of a delayed nonmatching to position task, although
motivational processes were affected (Steckler et al. 1994b).
Overall, these results suggest that PPTN may also be involved in the motivation or sustained attention required for
correct performance of the task.
Given these anatomical and physiological results, we hypothesized that PPTN can relay signals related to motor control, limbic function, and motivation and that PPTN may function as an important interface for behavioral control by
integrating various signals on each neuron. To investigate how
PPTN neurons were related to control of visually guided saccade tasks, we recorded the neuronal activity in relation to
saccade execution/initiation, reinforcement processes (reward
for the task), and task performance. A preliminary account has
been presented in an abstract form (Kobayashi et al. 1999).
J Neurophysiol • VOL
METHODS
Electrophysiology
All experimental procedures were performed in accordance with
the National Institutes of Health Guidelines for the Care and Use of
Laboratory Animals and approved by the Committee for Animal
Experiment at Okazaki National Institutes. The details of the surgical
and data acquisition methods have been published previously (Aizawa
and Wurtz 1998; Aizawa et al. 1999). Briefly, three male Japanese
monkeys (Macaca fuscata) weighing 7–13 kg were anesthetized with
halothane and implanted with scleral search coils (Fuchs and Robinson 1966), a head holder, and a recording chamber tilted 40° posterior
to the vertical axis. The monkeys were allowed to recover for ⱖ3 wk
and then trained to perform a visually guided saccade task for a liquid
reward, sitting in a primate chair with their heads in a fixed position.
The activity of single neurons was recorded using tungsten microelectrodes (FHC) with an impedance of 1– 6 M⍀. Electrodes were
positioned through stainless steel guide tubes (23 gauge) using a
micromanipulator (Narishige MO-95). The guide tubes were held in
position with a delrin grid that was fixed to the recording cylinder
(Crist et al. 1988). Eye movements were recorded using the magnetic
search coil (Fuchs and Robinson 1966) with a resolution of 0.1 deg.
Horizontal and vertical eye positions were sampled at 1 kHz. Single
neuronal discharges were also collected at 1 kHz via a template
matching spike discriminator (Alpha-Omega MSD) that produced a
pulse for each spike that matched a spike waveform template. To
examine the relationship between spike width and firing pattern, we
also collected 50 action potentials at 40 kHz for each neuron to
analyze its spike width.
Behavioral task
Monkeys were trained on two visually guided saccade tasks. Visual
stimuli consisted of small squares of light (0.8 deg square) backprojected on a tangential screen positioned 28 cm from the eyes.
Visual displays and data storage were controlled using computers
running a QNIX-based real-time data acquisition system REX (Hays
et al. 1982) and a Windows-based real-time data acquisition system
(Reflective computing, Tempo for Windows) with a dynamic link to
Matlab (MathWorks). At the beginning of each trial, the fixation point
(FP) appeared at the center of the screen, and monkeys were required
to move their eyes to the FP. To monitor fixation of monkeys, we
applied a window (2–7 deg square) that quickly narrowed to approximately 2 deg in every recording session once the monkeys adjusted
to the task. If the monkeys did not make a gaze shift to the FP within
3000 ms, the trial was regarded as an error trial. The trial was then
aborted and the computer program moved to the next trial. The
duration of fixation on the central FP was varied randomly between
400 and 1000 ms. Trials in which monkeys could not maintain fixation
to the FP for the duration (400 –1000 ms) were rejected as error trials.
Data sampling started from 500 ms before FP onset for every trial.
The saccade target (ST) was presented at an amplitude of 5–15 deg
distant from the FP in eight directions (0, 45, 90, 135, 180, 225, 270,
and 315 deg). The target amplitude was determined by the largest
saccadic modulation evoked by a target location for each recorded
neuron (mean amplitude: 12 deg). If the saccade-related modulation
was weak, we set the target amplitude to 10 deg. Three tasks were
randomly shuffled within a block of trials. In the Step paradigm, the
ST appeared in the peripheral visual field concurrent with the offset of
the FP. In the Gap paradigm, the ST appeared 170 –200 ms following
the disappearance of the FP. On catch trials, the FP disappeared and
after a gap of 200 ms, the FP reappeared in the central position. Catch
trials comprised ⬍12% of the trials in a block to reduce anticipatory
error to the saccade target, but we did not systematically compare the
data between blocks that included catch trials and those that did not.
88 • AUGUST 2002 •
www.jn.org
ACTIVITY OF PPTN DURING VISUALLY GUIDED SACCADES
Saccadic reaction time (SRT) was defined as the interval between ST
onset and the saccade onset. The Step and Gap paradigms were
included to increase the range of SRT, because SRTs in Gap trials are
shorter than those in Step trials (Fischer and Boch 1983; Paré and
Munoz 1996). Monkeys were rewarded with fruit juice 200 –500 ms
after correctly performing a saccade to the ST and then maintaining
fixation for 100 –300 ms in the ST window (size 2–7 deg), the size of
which also gradually decreased during recording sessions. Small
percentage of trials with SRTs below 80 ms were considered as trials
with anticipatory saccades, because they commonly exhibited lower
peak velocities and larger targeting errors as reported in a previous
study (Fischer and Weber 1993). Trials with SRTs above 500 ms were
considered as error trials and were not rewarded. Inter-trial intervals
ranged from 1100 to 2000 ms.
Identification of recording sites
The location of PPTN was verified using penetration record maps
and magnetic resonance imaging (MRI; Hitachi MRI system, 2.2T).
Recording sites were plotted on sagittal magnetic resonance (MR)
images and images parallel to the recording chamber angle for each
monkey (e.g., see Fig. 1). To reconstruct the recording sites based on
MR images, recordings were made for selected penetrations through
implanted guide tubes in the grid chamber system. We used two
landmarks to fit the MR image and penetration records: auditory
responses in the inferior colliculus, fiber activity of the superior
cerebellar peduncle, and reached PPTN. PPTN was located 3–5 mm
lateral from midline and 3–7 mm deeper than where auditory responses were observed. We recorded single units in that location and
confirmed high-frequency tonic fiber activity (⬎20 Hz) within 3–5
mm from single units, since PPTN is close to the cerebellar peduncle.
Fiber activity was identified as a discharge pattern of spikes including
a positive potential and brief spike width (⬍1 ms).
Histology
At the conclusion of the experiments, one monkey (the other
monkeys are still alive) was deeply anesthetized with pentobarbital
717
(Nembutal; ⬎150 mg/kg) and perfused with 10% formaldehyde. The
brain was removed, frozen, cut into 50-␮m coronal sections, mounted
on microscope slides, and stained using cresyl violet. Recording sites
were marked by placing electrolytic lesions at selected recording sites
and were verified to be in PPTN after reconstruction of the electrode
tracks.
Data analysis
For all analyses, we did not prescreen the neurons for any specific
firing pattern, and 70 neurons with more than or equal to five completed trials for each condition were used for analysis of task related
firing pattern (Gap/Step and 8 directions). Three neurons were used
only for the tests pertaining to reward responses. To evaluate the
relationship between neuronal discharge and specific events, we produced rasters and continuously varying spike density functions (Richmond et al. 1987) aligned on the events. To generate the spike density
function, a Gaussian pulse of fixed width (␴-value ⫽ 4 ms) was
substituted for each spike and then summed together to produce a
continuous function in time. A mean spike density function was
computed by averaging the spike densities over a series of trials.
Onset and offset of saccades were identified by velocity criteria
(threshold 30 deg/s) during off-line analysis.
To clarify the relationship between neuronal activity of PPTN and
the execution of visually guided saccades, the activity preceding and
during saccadic eye movement and its directional property were
examined. To examine the contribution of PPTN neurons to saccade
initiation, the pretarget activity and its correlation with SRT were
analyzed. To examine the activity in relation to reinforcement process,
we analyzed the discharges around rewards delivered during the
saccade task and the freely given rewards without saccade tasks.
To investigate the relationship between neuronal activity and task
performance, we analyzed tonic discharges and responses to the FP
with the successful or erroneous outcome of the task. The relationship
between the performance and neuronal activity was estimated by
success rate and firing rate. The firing rates were calculated in a
time-window for every trial, and then the data, which were composed
of firing rate and success or error, were collected according to their
FIG. 1. Reconstruction of pedunculopontine tegmental nucleus (PPTN). A: recorded neurons are plotted on a coronal
section through the midbrain and the pons in 1 monkey. The
anterior-posterior level was determined by comparison with
the midbrain portion of sections in the atlas of Kusama and
Mabuchi (1970). B: recording sites plotted on a sagittal section
of MR images in the same monkey. SC, IC, and CB indicate
superior colliculus, inferior colliculus, and cerebellum, respectively.
J Neurophysiol • VOL
88 • AUGUST 2002 •
www.jn.org
718
Y. KOBAYASHI, Y. INOUE, M. YAMAMOTO, T. ISA, AND H. AIZAWA
firing rate into several bins (i.e., every 2 spikes/s). The success rate
was calculated for each bin according to the number of successful and
erroneous trials for each firing rate bin.
To investigate performance of the task (preparation for appearance
of the FP or a motivational state), we analyzed the reaction time to the
FP appearance (RTFP). In the off-line analysis, the RTFP was defined
as the interval between the time of FP onset and the time at which the
eye entered the computer-controlled FP window (size: 2 deg square).
The correlation between the tonic discharges or the responses to the
FP and RTFP was also examined. To examine motivation toward the
task, we classified error trials into three types depending on which
portion of the task the monkey failed to perform and analyzed the
relationship between the error type and RTFP. In addition, we analyzed the RTFP in relation to success or error of the task.
Previous studies in cats (Dormont et al. 1998) and rats (Koyama et
al. 1998) suggested that the width of the action potential in PPTN
neurons correlated with the neurotransmitter that they carry (glutamatergic, brief spikes; cholinergic, broad spikes). To investigate the
relationship between various aspects of the task (saccade execution,
task performance and activity around reward) and the presumed
neuronal transmitter type for each neuron, we examined the correlation between firing pattern and spike width, which was measured as
the duration of the negative phase of the spike waveform.
RESULTS
Recorded neurons
We analyzed 73 neurons (11 neurons in monkey A, 15
neurons in monkey B, and 47 neurons in monkey C) in PPTN.
Reconstructions of the locations of recorded PPTN neurons on
the coronal sections through the midbrain and pons in monkey
A are shown in Fig. 1A, and recording sites were plotted on
sagittal MR images for this monkey (Fig. 1B). The average
firing rate of the 73 PPTN neurons during inter-trial intervals
ranged from 0.1 to 74 spikes/s with a mean of 15 spikes/s. The
width of action potentials of PPTN neurons varied from 0.2 to
1.4 ms. For the analyses of discharge in every condition of the
task, 70 neurons with more than or equal to five trials in each
condition (Gap/Step and 8 directions) were used. For the other
three neurons, we investigated activity only in the Step paradigm and examined activity around the time of reward delivery. For the 70 neurons, the total trial number was 9391 for the
three monkeys, and the success rate on all trials was 82.5%.
Among the error trials, the monkeys did not make a gaze shift
to the FP or did not fixate to the FP in 87% of error trials, while
the monkeys did not make a correct saccade to the ST in the
remaining 13%.
Neuronal activity related to saccade execution
To quantify the relationship between the activity of PPTN
neurons and the execution of visually guided saccades, the
activity during saccades to the targets located in different
directions was examined. Typical saccade-related activities
toward the target for two separate neurons are shown in Fig. 2,
A and B. Both rastergrams and spike density histograms are
aligned with the time of saccade onset. A sudden increase (Fig.
2A) or decrease (Fig. 2B) in activity could be observed before
the saccade. These modulations of activity were associated
with the onset of saccade rather than that of target appearance
(indicated by open circles in Fig. 2). We did not classify
saccade-related activities into either visually evoked or movement-related; however, the responses to the saccade target
were not observed in the error trials where the monkeys did not
make a saccade to the presented target (data not shown).
To investigate the contribution of PPTN activity to saccade
execution, we classified neurons as burst type or pause type
according to the saccade-related activity. The saccade-related
activity was defined by either an increase or a decrease in
discharge at the time of saccade onset as opposed to the ST
onset, by averaging the number of spikes occurring ⫺50 to
⫹50 ms from saccade onset in the Step task for eight directions. We defined the fixation activity as the firing rate between
250 and 350 ms before the ST onset in the Step task. The
percentage change was computed as a percentage ratio (the
Gap-related activity divided by the pretarget activity in the
Step task).
Neurons were defined as saccade burst neurons if the largest
modulation in saccadic activity (subtraction of the fixation
activity from the saccade-related activity) for stimuli in eight
directions was above 10 spikes/s. This criteria was similar to
that used in a study of saccade-related activity in FEF (Everling
and Munoz 2000). Thirty-seven percent of PPTN neurons were
classified as saccade burst neurons (26/70). Their mean firing
rate was 39.8 spikes/s (ranging from 20.9 to 111.7 spikes/s) for
FIG. 2. Activity of a burst neuron (A) and a pause
neuron (B) during the Step task. Saccades were directed
toward the ipsilateral side in A and contralateral side in
B. Rastergrams are aligned with the saccade onset (0
ms). The trials are sorted according to the saccadic
reaction times (SRTs). Open circles indicated saccade
target (ST) onset. The spike density functions for each
neuron lie below the rastergrams.
J Neurophysiol • VOL
88 • AUGUST 2002 •
www.jn.org
ACTIVITY OF PPTN DURING VISUALLY GUIDED SACCADES
their preferred directions during the saccade. Figure 2A shows
a representative example of a burst neuron.
Neurons were defined as saccade pause neurons if all the
modulations in saccadic activity for stimuli in eight directions
reflected a reduction in discharge rate (i.e., ⬍0 spikes/s).
Twenty-seven percent of PPTN neurons were classified as
saccade pause neurons (19/70). The saccade pause neurons
exhibited tonic discharges (mean ⫽ 28.5 spikes/s, ranging from
11.5 to 74.2 spikes/s) while fixating a target spot and exhibited
a pause in firing (mean decrease ⫽ ⫺13.3 spikes/s, ranging
from ⫺34.2 to ⫺5.7 spikes/s) during saccades (Fig. 2B).
The influence of saccadic direction on saccade-related activity in a burst neuron and a pause neuron is shown in Fig. 3,
A and B, respectively. The saccade amplitude was 10° during
the recordings. Burst neurons were strongly modulated by
saccade direction, whereas pause neurons were not. Figure 3, C
and F, shows the population data for directional tuning among
the burst neurons (n ⫽ 26) and the pause neurons (n ⫽ 19),
respectively. The amplitudes of saccades were within 5–15
deg. The peak and valley of the curves were centered on the
best modulated directions for each neuron.
To quantify the relationship between saccade-related activity
in PPTN and saccade direction, we used a linear regression
analysis. Saccade-related activities in eight directions were
fitted to a cosine function as follows: f ⫽ fo ⫹ A[cos (w ⫺
wp)], where fo is the intercept of the regression equation, A is
the change in firing rate of the neuron as a function of direction
(w; 0, 45, 90, 135, 180, 225, 270, and 315 deg), and wp is the
preferred direction of the neuron. The correlation coefficients
between the discharge and the cosine function of the direction
were statistically significant in 18 of 26 burst neurons and in 7
of 19 pause neurons (P ⬍ 0.05). The correlation coefficients
between the discharge and the cosine function of the direction
were larger in burst-type neurons [0.71 ⫾ 0.21 (SD), n ⫽ 26]
than in the pause-type neurons [0.55 ⫾ 0.24 (SD), n ⫽ 19; P ⬍
0.05, t-test]. This result suggests that the burst activity was
modulated as a cosine function of the saccade direction, but the
pause in firing was less directionally dependent.
The burst neurons exhibited strong tuning for the cosine
function of the saccade direction; however, the preferred directions for each burst neuron were not distributed in directions
aligned with horizontal or vertical meridians. Furthermore, the
preferred directions of burst neurons were not biased into either
the ipsilateral (15/26) or the contralateral (11/26) hemifields
(Fig. 3D). Although the directional selectivity was weak, the
computed preferred directions of pause neurons were not distributed in directions aligned with horizontal or vertical meridians, but biased to the ipsilateral side (14/19) rather than the
contralateral side (5/19) (Fig. 3E).
Neuronal activity related to saccade initiation
To examine whether PPTN controls the initiation of the
visually guided saccade, we analyzed neuronal discharges and
SRTs in the Gap and Step tasks. Figure 4, A and B, shows the
distribution and cumulative percentage of SRTs, respectively,
obtained from three monkeys performing the Gap and Step
tasks while the 70 PPTN neurons were recorded. Consistent
with previous findings (Fischer and Boch 1983; Paré and
Munoz 1996), responses in the Gap task exhibited shorter
FIG. 3. Directional selectivity in burst neuron and pause neuron. Activity of a burst (A) and a pause (B) neuron in response to
stimuli in 8 directions. Rastergrams (for 5 trials) and spike density functions are aligned with saccade onset (0 ms). The population
data of directional tuning is shown for burst neurons (C) (n ⫽ 26) and pause neurons (F) (n ⫽ 19). The peak and valley of the curves
are centered on the best modulated directions for each neuron. Each data point represents the mean. Vertical bars indicate the SE.
Dotted lines indicate the average firing rate during fixation. Preferred directions in burst neurons (D) and pause neurons (E). IPSI,
ipsilateral; CONTRA, contralateral; UP, upward; DOWN, downward.
J Neurophysiol • VOL
719
88 • AUGUST 2002 •
www.jn.org
720
Y. KOBAYASHI, Y. INOUE, M. YAMAMOTO, T. ISA, AND H. AIZAWA
FIG. 4. Distribution of SRTs. A: distribution of SRTs
of 3 monkeys obtained in the Gap task and Step task
during sessions in which 70 PPTN neurons were recorded.
B: cumulative distribution of SRTs from all recordings
during the Gap task (solid line) and Step task (dashed
line).
SRTs than in the Step task [Gap task, 145.5 ⫾ 18 (SD) ms, n ⫽
3511 and Step task, 158.6 ⫾ 24 (SD) ms, n ⫽ 3537, P ⬍ 0.01,
t-test].
Pretarget activity was computed as the mean activity spanning 50 ms before to 50 ms after target presentation for the Gap
task and Step task in eight directions. To estimate the motor
preparation processes related to the shorter SRT in the Gap
task, we used the methods of Dorris and colleagues (1997). The
Gap-related activity was defined as the modulation in activity
during the end of gap period (by subtracting the pretarget
activity in the Step task from the pretarget activity in the Gap
task). The percentage change in modulation was computed as
a percentage ratio (the Gap-related activity divided by the
pretarget activity in the Step task).
The activities related to Gap/Step task for a burst (Fig. 5, A
and B) and a pause neuron (Fig. 5, C and D) are shown,
contrasting the activities during the Step task (Fig. 5, A and C)
and the Gap task (Fig. 5, B and D). Most burst neurons (21/26)
exhibited the Gap-related activity above 0 spikes/s [3.3 ⫾ 9.1
(SD) spikes/s; 116 ⫾ 293% (SD) in percentage change; Fig.
5E], and most pause neurons (13/19) exhibited modulation
below 0 spikes/s [⫺5.7 ⫾ 9.4 (SD) spikes/s; ⫺34%⫾ 36 (SD)
in percentage change; Fig. 5F]. Gap-related activity, assessed
both by the difference of firing rate and by percentage modulation, was larger in burst neurons than in pause neurons (P ⬍
0.05, t-test). The small arrows in Fig. 5, B and D, indicate the
time at which the activity exceeded a significant level (P ⬍
0.05, t-test) compared with activity during fixation (250 –350
ms before the ST onset).
Those burst neurons that showed a significant percentage
modulation toward the end of the gap period (n ⫽ 10), gradually increased their firing rate up until saccade onset (Fig. 5B).
The activities 50 –100 ms after FP offset were significantly
different from those during fixation (P ⬍ 0.05, t-test). In
contrast, the pause neurons that showed a significant percentage modulation toward the end of the gap period (n ⫽ 8)
gradually decreased their firing rate up until saccade onset (Fig.
5D). The activities after FP offset were significantly different
from those during fixation (P ⬍ 0.05, t-test).
We analyzed how SRT varied with changes in activity
during the end of the gap period on a trial-by-trial basis. For
this analysis, we selected data from neurons for which the
number of successful trials toward the best modulated direction
was above 20 (35 of 45 saccade related neurons; 24 burst
neurons and 11 pause neurons). The slope and intercept of the
J Neurophysiol • VOL
regression line and correlation coefficient between SRTs and
firing rate were calculated. The correlation coefficients were
small in both burst and pause neurons [the absolute value of r;
estimator of a contribution of activity to SRT, 0.18 ⫾ 0.11
(SD), n ⫽ 35], and a significant correlation was found for only
a few neurons [2 of 35 (2 burst neurons), P ⬍ 0.05] between
the two parameters. The absolute value of correlation coefficient was smaller than that for neurons in the intermediate
layers of SC (about 0.5 for buildup neurons) (Dorris and
Munoz 1998).
If the activity of burst and pause neurons in PPTN was
related to the SRT, the slope of the regression line would be
expected to be negative for burst neurons and positive for
pause neurons. There was, however, no significant difference
(P ⫽ 0.46, t-test) in the slopes of the regression lines for
trial-by-trial analyses between burst neurons [⫺0.07 ⫾ 0.21
(SD) ms/(spikes/s), n ⫽ 22] and pause neurons [⫺0.01 ⫾ 0.18
(SD) ms/(spikes/s), n ⫽ 13]. This result indicates that the
correlation between neuronal activity of burst/pause neurons in
PPTN during the gap period and SRTs for visually guided
saccade is smaller than that for SC neurons.
Neuronal activity around onset of reward
A group of PPTN neurons exhibited abrupt increases in
activity around reward onset (juice drop) after appropriate
saccade to the ST in the saccade task. These peri-reward
activities were observed in 22 of the 70 neurons, and their
mean firing during ⫺200 to ⫹300 ms from reward onset
[22.5 ⫾ 24.5 (SD) spikes/s] were significantly larger than
control activity [11.3 ⫾ 14.3 (SD) spikes/s, the mean firing rate
400 –500 ms before the reward onset, P ⬍ 0.05, t-test]. In this
analysis, we did not measure any EMG related to licking or the
precise timing of the reward drop, we carefully monitored
facial and licking movements during recording session with a
video monitor. These changes in activities around reward onset
were not associated with any distinct orofacial sensory event or
movement (data not shown). We suspect that the activity
around reward was auditory response induced by click noise
produced by the opening of the valve. Unfortunately we did not
control this condition in the present study.
The latency of the peri-reward responses was defined as the
time at which the firing rate first exceeded the control activity
from onset of the electronic feeder pulse [P ⫽ 0.05, Kolmogorov-Smirnov test (K-S test)] (Shidara and Kawano 1993).
88 • AUGUST 2002 •
www.jn.org
ACTIVITY OF PPTN DURING VISUALLY GUIDED SACCADES
721
FIG. 5. Gap-related activity of a burst neuron and a pause
neuron. The activity of a burst neuron during a Step task (A)
and a Gap task (B). The activity of a pause neuron during a
Step task (C) and a Gap task (D). Rastergrams are aligned with
the ST onset (0 ms). Triangles in the rastergrams indicate
saccade onsets. The spike density function of each neuron is
below the rastergram. Gray bars with arrows indicate the offset
of FP. Small arrows in (B) and (D) indicate the time at which
the activity exceeded significance (P ⬍ 0.01, t-test) compared
with activity during fixation. Histograms of percentage change
in Gap-related activity in burst neurons (E) and pause neurons
(F).
Figure 6A shows the results from an experiment in which
rewards were given twice in each trial, 200 –350 ms after the
saccade end. The neuron responded to repetitive reward pulses
with the 152-ms latency for the first pulse. The response may
not be a specific after-saccadic response, because the burst
onset was synchronized with each reward onset (Fig. 6A).
During saccade task, the responses after the reward onset were
observed in 13 of the 22 neurons [response latencies exceeded
50 ms after reward onset; mean 210 ⫾ 65 (SD) ms (n ⫽ 13)].
Interestingly, the other neurons’ (9/22) activity around reward preceded onset of reward [mean ⫺102 ⫾ 90 (SD) ms
from reward onset]. In Fig. 6B rewards were also given at a
relatively constant interval (200 –300 ms) from the saccade end
during task and the neuron exhibited an increase in activity
J Neurophysiol • VOL
preceding the reward (195 ms before reward onset or about 100
ms after saccade end).
To dissociate the peri-reward activity from the other taskrelated factors, we recorded the response to freely given reward
in 7 of 73 neurons (free-reward task). In testing responses to
free rewards, we stopped the control of visual display, and
rewards were given at random intervals in the darkness, regardless of the eye movements. Five of seven neurons tested
exhibited responses to free rewards, and the onset of the
responses to free rewards were 100 –220 ms after reward [mean
of latencies; 142 ⫾ 46 (SD) ms]. These neurons did not show
any responses after spontaneous saccade in the dark. A typical
response to free rewards is shown in Fig. 6C, data from the
same neuron as in Fig. 6B. The neuron exhibited an increase in
88 • AUGUST 2002 •
www.jn.org
722
Y. KOBAYASHI, Y. INOUE, M. YAMAMOTO, T. ISA, AND H. AIZAWA
FIG. 6. Neuronal activity around onset of reward.
The burst of activity after the reward is shown for
one neuron (A). Rewards were given twice and this
neuron exhibited bursts corresponding to each reward. B: neuronal activity observed before reward
onset in another neuron. C: activity in response to a
freely delivered reward (given independent of the
task) for the same neuron shown in (B). Rastergrams
were aligned with the onset of reward (0 ms). Open
circles and open triangles indicate the time of ST
onset and the saccade onset, respectively. The spike
density functions for each neuron lie below the rastergram.
activity before reward onset during the saccade task (Fig. 6B),
but was activated after approximately 200 ms from reward
onset if rewards were given independently of the saccade task
(Fig. 6C). Thus the activity preceding reward onset during the
saccade task may be either an after-saccadic response (visual or
motor-related and so on) or a response associated with reward.
However, the possibility that the pre-reward response was evoked
only by after-saccadic events may be rejected because this neuron
did not exhibit increased responses in after-saccadic period, when
the monkey made saccade toward the FP (data not shown) and
was not activated after spontaneous saccades in the dark in freereward task. One possible account for the pre-reward activity
J Neurophysiol • VOL
during the saccade task is that it may reflect the behavioral context
in which the saccade was performed or be a prediction of reward
given after successful saccades.
Tonic activity in relation to success or error of the task
More than half of recorded PPTN neurons (75%, 52 of 70
analyzed neurons) exhibited tonic activity at the onset of a trial
prior to FP onset. The average firing rate of the 52 neurons at
the onset of a trial ranged from 0.2 to 76 spikes/s with a mean
of 16 spikes/s. In a small population of seven neurons, we
observed different levels of tonic activity depending on the
88 • AUGUST 2002 •
www.jn.org
ACTIVITY OF PPTN DURING VISUALLY GUIDED SACCADES
723
strate the differential distributions in firing rates between successful and error trials, the cumulative percentages of firing
rate before FP onset for both successful and error trials are
shown in Fig. 7C. Both the intercept and the saturation point of
the curves were different between successful trials and error
trials.
To evaluate the relationship between performance of task
and firing rate, we calculated the success rates against the firing
rate before FP onset. The success rates are plotted against firing
rates for the neuron shown in Fig. 7, A and B (Fig. 7D) and for
all seven neurons (Fig. 7E). Each curve in Fig. 7E indicates
that the success rates were increasing saturated functions of the
firing rates. These results indicate that PPTN neurons vary their
level of tonic activity in accordance with the outcome of the
upcoming trial.
Relationship between task performance and RTFP
To investigate the level of motivation, we measured performance of the task during recording sessions. The monkeys
maintained wakefulness throughout all recording sessions even
if they succeeded or failed in the trials, because the error ratio
was almost constant throughout the session, as shown in Fig.
8A (cumulative error and successful trials were plotted against
the elapsed time in the session).
To evaluate the level of motivation or preparation for the FP
appearance for each trial, we measured RTFP. RTFPs in the
FIG. 7. Tonic activity related to success or error of the task. Rastergrams
and spike densities are aligned with FP onset (0 ms) for 20 successful trials (A)
and for 20 error trials (B) in 1 neuron. Open circles indicate onset of ST;
crosses indicate fixation point (FP) offset; open triangles indicate saccade
onset; and asterisks indicate reward onset. C: cumulative percentage of mean
firing rate which is calculated between 0 and 500 ms before FP onset for
successful trials (solid line) and for error trials (dashed line) of the neuron
illustrated in (A) and (B). D: relationship between success rate and mean firing
rate before FP onset for data shown in (C). Success rate was calculated every
2 spikes/s. Success and error of trial was defined as 1 and 0, respectively, and
success rate was calculated by mean of the value. Vertical bars indicate SE. E:
relationship between success rate and firing rate 0 –100 ms before FP onset for
7 neurons. Success rates were calculated every 20 spikes/s.
outcome of the upcoming trial. Figure 7A shows the tonic
activity in successful trials, which started before FP onset and
lasted until a visually guided saccade was made to the ST.
Visually guided saccades to the target were executed approximately 1000 ms after FP onset. Figure 7B shows the activity
of the same neuron in error trials. These seven neurons exhibited significantly different activities between successful trials
and error trials (P ⬍ 0.05, t-test). For these seven neurons, the
mean firing rate 0 –100 ms before FP onset was 29.4 ⫾ 19.0
(SD) spikes/s in successful trials and 21.1 ⫾ 8.4 (SD) spikes/s
in error trials. The activities of the seven neurons were larger
in successful trials than in error trials for all the following
intervals examined: 1) 0 –100 ms before FP onset; 2) 100 –200
ms after FP onset; and 3) 1000 –1100 ms after FP onset (n ⫽
7, P ⬍ 0.05, t-test). In successful trials, the tonic activities were
sustained in the period that began before FP onset and lasted
after the execution of the visually guided saccade. To demon-
J Neurophysiol • VOL
FIG. 8. Analysis of performance of the task. A: cumulative successful and
error trials in a recording session shown in Fig. 7, A and B, plotted against
elapsed time of the session. B: relationship between the level of performance
and reaction time to FP appearance (RTFP) for all data. Vertical bars indicate
SD. C: cumulative percentage of RTFP for successful trials (solid line) and for
error trials (dashed line) in a recording session shown in Fig. 7, A and B. D:
relationship between success rate and RTFP for all data (7960 trials, from the
70 neurons). Success rates were calculated every 300 ms of RTFP that ranged
from 0 to 2399 ms. Data between 2400 and 2999 ms were omitted, as were
Type I errors. Vertical bars indicate SE.
88 • AUGUST 2002 •
www.jn.org
724
Y. KOBAYASHI, Y. INOUE, M. YAMAMOTO, T. ISA, AND H. AIZAWA
successful trials were shorter than those in the error trials
[successful trials; 181 ⫾ 296 (SD) ms, error trials: 2642 ⫾ 930
(SD) ms, for 70 neurons, P ⬍ 0.01, t-test]. Note that if the
monkey was already fixating on the location where the FP
would appear, RTFPs were set to 0 ms. Further, if the monkey
did not look to the FP, RTFPs were set to 3000 ms.
We segregated error trials into three types depending on
which portion of the task the monkey failed to perform. Type
I errors occurred when the monkey did not look to the FP at all.
Type II errors occurred when the monkey looked to the FP but
failed to maintain fixating FP. Type III errors occurred when
the monkey succeeded in fixating the FP but did not look to the
ST. The level of motivation was assumed to be the lowest in
type I errors and then in Type II errors, then in Type III errors.
RTFPs were compared among the type of error in Fig. 8B and
were found to be the shortest in the successful trials, and then
progressively and significantly longer in Type III, Type II, and
Type I errors, respectively (P ⬍ 0.05, t-test for all comparisons). Thus RTFP appears to be a good index for the motivation to perform the upcoming trial. The cumulative percentage
for RTFP is shown for both successful and error trials in Fig.
8C and demonstrates a differential distribution of RTFP between successful and error trials. To evaluate the relationship
between task performance and RTFP, the success rates were
plotted against RTFP in Fig. 8D. We observed that the success
rate was a decreasing function of RTFP (r ⫽ ⫺0.81, RTFP
ranged from 0 to 2399 ms). The success or error of the task
performance (evaluated by 1 or 0, respectively) was also negatively correlated with RTFP [r ⫽ ⫺0.68, P ⬍ 0.01, n ⫽ 7960
trials (RTFP ⬍2400 ms)]. For this analysis, we rejected trials
whose RTFPs ranged from 2400 to 2999, because the number
of trials was too small. Also, we rejected the trials whose
RTFPs were 3000 ms, because these were always Type I
errors. Thus we could predict the outcome of the trial via the
RTFP.
Neuronal activity related to FP appearance and task
performance
Correlation between the tonic activity and the RTFP
In another subpopulation of neurons, an increase in activity
in response to FP onset was observed with a latency of approximately 100 ms. The FP-related activity was evaluated by
comparing the mean firing rate 100 –200 ms before FP onset
with that 100 –200 ms after FP onset [34 of the 70 neurons
were significant, P ⬍ 0.05, t-test, 11.8 ⫾ 17.4 (SD) spikes/s for
before FP onset and 24.5 ⫾ 24.9 (SD) spikes/s for after FP
onset]. The latency of the FP-related activity was taken as the
time at which the frequency exceeded the control frequency
(0 –100 ms before FP onset) at the significant level (K-S test,
P ⫽ 0.05) (Shidara and Kawano 1993). The mean response
latency to FP onset was 115 ⫾ 13.1 (SD) ms (n ⫽ 34). The
temporal pattern of FP-related activity was also investigated.
The FP-related activities were classified into two groups. One
group (n ⫽ 29) of neurons exhibited a tonic increase in activity
in response to FP, whereas another minor group (n ⫽ 5)
exhibited only a phasic increase.
In some of these neurons, either the tonic (8/29) or the
phasic (2/5) response to FP onset was related to success or
error of the task (P ⬍ 0.05, t-test). For example, Fig. 10, A and
B, shows the response of a tonic neuron in successful trials
(Fig. 10A) and error trials (Fig. 10B), respectively. Ten of the
34 neurons showed differential responses 100 –200 ms after FP
onset between successful and error trials [successful trials:
35.0 ⫾ 24.8 (SD) spikes/s; error trials: 21.5 ⫾ 18.5 (SD)
spikes/s, P ⬍ 0.01, t-test]. Four of these 10 neurons also
exhibited the tonic activity related to success or error, which
started before the FP onset as shown in Fig. 7. As shown
below, this difference between successful and error trials cannot be explained simply by the position of the eye at FP onset.
Figure 10, A and B, shows discharges to FP appearance in
successful and error trials, respectively, ordered by RTFPs
(recall that RTFPs of 0 ms indicate that the monkey was
already fixating the location where the FP would appear). As
shown in the lower raster traces in Fig. 10A, if the RTFP was
longer, the response following FP onset was weaker or the
same as the tonic activity shown above. Further, the rastergram
To test whether the tonic discharges of the neuron that
showed a different level of activity between successful and
error trials could account for the RTFP, a trial-by-trial
correlation between RTFP and mean firing rate (computed
0 –100 ms before FP onset) of the tonic activity was analyzed in the successful trials (Fig. 9, A and B) for the seven
neurons. A significant negative correlation was found between RTFP and mean firing rate before FP onset (correlation coefficient r ⫽ ⫺0.21, n ⫽ 156, P ⬍ 0.05) for the data
shown in Fig. 9B. For every seven neurons, the significant
correlation (P ⬍ 0.05) was observed in the tonic activity
with RTFP. In addition, to examine the temporal profile of
the correlation between the tonic activity and RTFP, we
computed them in 100-ms bins beginning from ⫺550 ms
before to 1550 ms after FP appearance. The significant
correlations (P ⬍ 0.05) lasted until about 1500 ms after FP
onset for these seven neurons (data not shown). Thus the
variability of RTFP is related to the variability of tonic
discharges, which lasted until the end of a trial.
FIG. 9. Trial-by-trial correlation between RTFP and mean firing rate of
tonic discharge. A: rastergram and spike density illustrating both spike and
RTFP (the time eyes reached the FP indicated by open squares). This neuron
is the same as shown in Fig. 7A (for only successful trials). B: RTFP plotted
against mean firing rate before FP onset for each trial. The regression line is
illustrated on the plot.
J Neurophysiol • VOL
88 • AUGUST 2002 •
www.jn.org
ACTIVITY OF PPTN DURING VISUALLY GUIDED SACCADES
725
FIG. 10. FP-related activity. Responses to FP appearance in successful trials (A) and in error trials (B) are illustrated.
Rastergrams are aligned with the FP onset (0 ms). The trials are sorted according to RTFP (indicated by open squares). The spike
density of each neuron is below the rastergram. Spatial property of FP-related activity, which was affected by success or error of
the trial (C–F). FP-related activity for successful trials (C) and error trials (D). The location of each square indicates the retinal
position when the FP onset and the size of each square indicates the average firing rate 100 –200 ms after the FP appeared. In the
horizontal axis, positive numbers indicate ipsilateral and negative numbers indicate contralateral. In the vertical axis, positive
numbers indicate upward and negative numbers indicate downward, respectively. E: the FP-related responses were classified by
dividing the plotted data in (C) and (D) into four quadrants by horizontal and vertical axes. Mean of firing rate for successful and
error trial for each quadrant is plotted by closed circle and open triangle, respectively. F: relationship between eccentricity of retinal
position of FP and mean firing rate for successful and error trial. Vertical bars in (E) and (F) indicate SEM.
is more finely locked to FP onset than the time when the eyes
reached the FP, and the spike density function shows an abrupt
rise after FP onset. The result suggests that the response to the
FP is visually evoked.
An alternative explanation for the difference in FP-related
activity between successful and error trials was suggested that
it is due to the retinal position of the FP when it appeared. To
examine this possibility, the following analyses were performed. In Fig. 10, C and D, the plotted positions indicate the
retinal position of the FP when it appeared, and the size of the
plotted squares indicates the mean firing rate after FP onset for
each trial. The retinal position was calculated by subtracting
the eye position at FP onset from the FP position. When the FP
appeared on the center of the screen, the eye position was
almost randomly localized away from the FP, ranging from 0
to 60° away in all directions. Because FP-related responses
were larger in the right visual field for both successful and error
trials reflecting the neuron’s receptive field, this receptive field
property could also give rise to the different activity between
successful and error trials. To examine the relationship between FP-related response and the eye position at FP onset, we
segregated the FP-related activity (represented by the retinal
position of the FP when it appeared) by horizontal and vertical
J Neurophysiol • VOL
axes into four quadrants and compared those responses between successful and error trials for each quadrant. Significant
differences were shown in the case of the data illustrated in
Fig. 10, A and B, for all four quadrants (Fig. 10E). All of the
10 neurons showed significant differences in responses between successful and error trials for more than two quadrants
(P ⬍ 0.05, t-test).
In addition, we analyzed the firing rate in successful or error
trials as a function of eccentricity of the retinal position of the
FP (Fig. 10F). The firing data were assigned into four bins
(0 –5 deg, 5–10 deg, 10 –20 deg, and ⬎20 deg) according to the
retinal position from fovea. In Fig. 10F, although a centerpeaked receptive field property was observed in both successful and error trials, the firing rates were significantly larger in
successful trials than in error trials for each distance bin (P ⬍
0.05, t-test). All 10 neurons showed significantly larger responses in successful than in error trials for small eccentricities
(0 –5 deg, P ⬍ 0.05, t-test), and at least one more eccentricity
bin (P ⬍ 0.05, t-test). Thus the responses to FP onset were
larger in successful trials than in error trials regardless of FP
location. We also confirmed that RTFPs were less dependent
on the retinal position of the FP when it appeared (data not
shown). Thus for this subset of neurons, the activity in re-
88 • AUGUST 2002 •
www.jn.org
726
Y. KOBAYASHI, Y. INOUE, M. YAMAMOTO, T. ISA, AND H. AIZAWA
FIG. 11. Location of recorded neurons for monkey C. A:
sagittal MR image and reconstructed recording sites. B: distribution of the performance-related group neurons and the rewardrelated group neurons. C: distribution of saccade burst neurons
and saccade pause neurons.
sponse to FP varies the level of firing with performance of the
task.
Distribution of location, spike width, and response to the
events for neurons
To investigate the distribution of neurons within the PPTN,
the location of recorded neurons was examined in relation to its
activity pattern (Fig. 11). Neurons were classified into four
task-related groups, as follows: 1) the performance-related
group, which exhibited differential activity between successful
and error trials (n ⫽ 13), with tonic discharge (n ⫽ 7) or
response only to the FP appearance (n ⫽ 6); 2) saccade pause
(n ⫽ 19); 3) saccade burst (n ⫽ 26); and 4) reward-related
group (with response around reward onset, n ⫽ 22). Neurons
that exhibited performance-related, saccade-burst, saccadepause, and reward-related activity were distributed almost
evenly throughout PPTN. There was no tendency for a differential distribution of different types of neurons (Fig. 11, B and
C). Because previous studies in cats (Dormont et al. 1998) and
rats (Koyama et al. 1998) have suggested that the spike width
and firing rate of PPTN neurons are correlated with the type of
transmitter (glutamatergic neurons, carry brief spikes, and
high-frequency; cholinergic neurons, carry broad spikes, and
low frequency), we measured the width of the action potentials
in 30 of 70 neurons and compared the spike width and 1)
neuron distribution; 2) spontaneous firing rate during inter-trial
intervals; and 3) the four activity patterns during the task.
There was no apparent segregation between the spike width
and either distribution of neuron or spontaneous firing rate and
J Neurophysiol • VOL
FIG. 12. Analysis of width of action potentials. A: action potentials for
performance-related group neurons. B: action potentials for reward-related
group neurons. Arrows indicate hump-like slow positive potentials. C: distribution of spike width for performance-related group neurons (open columns)
and for reward-related group neurons (closed columns). The width of the
action potential was measured as the duration of the negative phase of the spike
waveform.
88 • AUGUST 2002 •
www.jn.org
ACTIVITY OF PPTN DURING VISUALLY GUIDED SACCADES
727
between the firing rate and activity pattern during the tasks
(data not shown). However, a slight segregation in spike width
was found for the performance-related group neurons versus
for the reward-related group neurons (Fig. 12, A–C). Action
potentials for the performance-related group neurons and for
the reward-related group neurons are shown in Fig. 12, A and
B, respectively. Hump-like slow positive potentials (arrows in
Fig. 12, A and B), which were suggested to be generated by
cholinergic neurons (Koyama et al. 1998), were more frequently observed in performance-related group neurons than
reward-related group neurons. Spike widths were compared
(Fig. 12C) between performance-related group [0.42 ⫾ 0.17
(SD) ms, n ⫽ 9] and reward-related group [0.31 ⫾ 0.10 (SD)
ms, n ⫽ 10]; however, the difference was not significant (P ⫽
FIG. 14. Distribution of task-dependent response patterns among the recorded neurons.
0.09, t-test). In addition, in each group of the response pattern,
the distribution of neurons was not segregated by their width of
action potential.
The activity of one neuron that exhibited both FP-related
response affected by task performance and additionally exhibited saccade-related response to ST onset is shown in Fig. 13.
The neuron showed a differential activity between successful
and error trials, which was time-locked to FP onset (Fig. 13, A
and B, for successful and error trials, respectively) and response to ST (Fig. 13C). The responses to FP against retinal
position of the FP when it appeared are shown in Fig. 13D. The
responses to ST against retinal position of the ST when it
appeared are shown in Fig. 13E. Response to ST was directionally selective (directed to left-up); however, FP-related
response was less directionally selective and had a wider
response field to visual stimulus than the response to ST. Thus
the response aligned to the onset of a stimulus was altered by
its behavioral context, in which the target was presented as FP
or ST.
Figure 14 shows the classification of the recorded 70 neurons into the four groups. The majority (56/70) of neurons
exhibited some response in visually guided saccade task. Interestingly, 22 of these 56 neurons (39%) exhibited response
patterns that were characteristic of two or more groups. Thus a
population of PPTN neurons exhibited activity patterns in
various combinations related to task performance, reward and
the execution of visually guided saccades.
DISCUSSION
FIG. 13. Neuronal activity exhibiting both FP-related activity and activity
to ST. Activity for FP in successful trials (A) and error trials (B), aligned with
FP onset. Squares indicate RTFP and open circles indicate ST onset. C: the
activity aligned with ST onset (0 ms). Triangles indicate the SRT. Spatial
property of the response of the neuron, when the visual stimulus was either the
FP (D) or ST (E). The location of each square indicates retinal position when
the visual stimuli appeared, and the size of each square indicates response
modulation to FP in (D) (subtraction of firing rate 100 –200 ms after FP onset
from firing rate 0 –100 ms before the FP onset) and response modulation to ST
in (E), and subtraction of firing rate 100 –200 ms after ST onset from firing rate
0 –100 ms before ST onset, respectively. The computed intervals for after FP
onset and for ST onset are shown by large columns in (A) and (C), respectively.
In the horizontal axis positive numbers indicate ipsilateral and negative numbers indicate contralateral. In the vertical axis positive numbers indicate
upward and negative numbers indicate downward.
J Neurophysiol • VOL
Neuronal activity of PPTN related to saccade
This study, for the first time, showed that PPTN neurons
may be involved in regulation of saccadic eye movements. To
clarify the contribution of neuronal activity of PPTN to saccade
execution, we will discuss the saccade-related burst and pause,
and their directional property.
The preferred directions of saccade-related activity in PPTN
was not biased ipsiversively or contraversively nor aligned
with horizontal or vertical axes (Fig. 3, D and E). The source
of this saccade-related activity has several possibilities.
Crossed descending projections from SC terminate in the pedunculopontine/parabrachial area in rats (Redgrave et al.
88 • AUGUST 2002 •
www.jn.org
728
Y. KOBAYASHI, Y. INOUE, M. YAMAMOTO, T. ISA, AND H. AIZAWA
1987), cats (Huerta and Harting 1982), and monkeys (May and
Porter 1992). Thus a possible source of the ipsiversive saccaderelated burst in PPTN might originate from the contralateral
SC. The source of the saccade-related activity directed to the
contraversive side may originate from the cerebral cortex,
because PPTN receives ipsilateral projections from motor areas
in the cerebral cortex in cats (Edley and Graybiel 1983) and
monkeys (Matsumura et al. 2000) and from infralimbic and
prelimbic areas (Chiba et al. 2001) and FEF (Matsumura et al.
2000) in monkeys. The saccade-related burst may be caused by
the disinhibition of GABAergic input from SNr (Gerfen et al.
1982; Granata and Kitai 1991). The possible source of the
saccade-related pause may be derived from SC, basal ganglia,
and cerebral cortex. The responses related to saccade amplitude should also be investigated to compare PPTN responses
with SC, SNr, and cerebral FEF.
Recent studies have shown that a gradual increase in
“buildup” activity during the gap period, which can be observed in a group of neurons in the intermediate layers of SC,
is highly correlated with the initiation of saccades and SRT
(Dorris et al. 1997; Dorris and Munoz 1998; Sparks et al.
2000). Moreover, it has been shown that the activity of fixation
neurons in the rostral pole of SC, which decreases during the
gap period, suppresses initiation of saccades (Dorris and
Munoz 1995). Recent studies suggest that a candidate for the
origin of the activity in buildup and fixation neurons during the
gap period is FEF (Dias and Bruce 1994; Everling and Munoz
2000). Because PPTN neurons massively innervate to SC in
several mammalian species (Beninato and Spencer 1986; Graybiel 1978; Hall et al. 1989; Henderson and Sherriff 1991; Jeon
et al. 1993; Ma et al. 1991; Schnurr et al. 1992), PPTN may
also be a source of buildup activity in SC. A recent study in our
laboratory demonstrated that in slice preparations of the rat SC,
activation of nicotinic acetylcholine receptors on neurons in the
intermediate layer of SC induced inward currents and depolarization, which may gate the signal transmission in the direct
visuomotor pathway from the superficial to the intermediate
layer of SC (Isa et al. 1998). Another recent result suggests that
the cholinergic system may facilitate initiation of saccades
through SC, indicating that neural mechanism observed in SC
slice of rats also applies to behaving monkeys (Aizawa et al.
1999). Thus PPTN may contribute to SC in giving rise to
buildup activity and controlling SRT with cholinergic input to
the intermediate layer of SC through the activation of nicotinic
acetylcholine receptors. During the gap period, PPTN burst
neurons increased their firing rate, whereas pause neurons
decreased their firing rate (Fig. 5). Although the contrast in
Gap-related activity between burst and pause neurons became
apparent in averaged data, an obvious correlation between
SRTs and Gap-related activity was not observed on a trial-bytrial basis. These results suggest that the contribution of a
single PPTN neuron to SRT is weaker than that of buildup
neurons in SC, where the neural activity is significantly correlated to SRT (Dorris et al. 1997; Dorris and Munoz 1998).
Although the ongoing influence of PPTN activity on SRT of
visually guided saccades was weak, the present results suggest
that PPTN may integrate several saccade-related signals coming from SC, basal ganglia, and cerebral cortex and send them
back to these areas. Therefore PPTN is ideally situated to work
cooperatively for initiation and execution of saccade.
J Neurophysiol • VOL
Neuronal activity of PPTN around reward onset
Recent studies have emphasized that the dopaminergic neurons of SNc process reward-related information necessary for
reinforcement learning (for review see Schultz 1998). PPTN is
thought to be one of the most important input sources to SNc
(Futami et al. 1995; Takakusaki et al. 1996). Accordingly, we
observed an increase in the activity of PPTN neurons around
reward onset (Fig. 6).
PPTN receives limbic inputs from the hypothalamus, the
ventral tegmental area (Semba and Fibiger 1992; Steininger et
al. 1992), and the limbic cortex in monkeys (Chiba et al. 2001),
all of which may be sources of the activity around reward
observed in the present study. The glutamatergic and cholinergic inputs from PPTN make synaptic connections with dopaminergic neurons in SNc (Futami et al. 1995; Takakusaki et
al. 1996). Electrical stimulation of PPTN induces a time-locked
burst in dopaminergic neurons in the rat SNc (Lokwan et al.
1999). The mean latency of responses to the freely delivered
reward was slightly shorter in the PPTN (100 –220 ms; mean,
146 ms) than in SNc (151 ms; Mirenowicz and Schultz 1994).
Thus the reward-related activity in dopaminergic neurons of
SNc may come from PPTN. In a recent study of cats, reinforcement-related single-unit activity in PPTN has been demonstrated, which was preferentially observed on broadly spiking neurons presumed to be cholinergic (Dormont et al. 1998).
These results suggest that cholinergic reward-related signals
from PPTN may be sent to dopaminergic neurons of SNc
(Takakusaki et al. 1996).
In monkeys, PPTN contains both cholinergic and other types
of neurons, but it is not known which type of neuron contributes to the specific processing. In the present study, we observed no preferential distribution in spike-width and location
of neurons and little correlation of spike-width with several
firing properties (the performance of the trial, saccade execution, and reward) and with average firing rate. We speculate the
possibility that, in monkeys, there is little correlation between
response pattern and the neurotransmitter type of PPTN. However, it is difficult to measure spike-width precisely using metal
extracellular recording electrodes.
Neuronal activity of PPTN related to arousal and motivation
The cholinergic system is one of the most important modulatory neurotransmitter systems in the brain and is thought to
control activity that depends on selective attention (Perry et al.
1999). It may be possible that the cholinergic PPTN, noradrenergic LC, and serotonergic DRN in the brain stem act
together in the control of arousal and global attention, as
previously hypothesized (Garcia-Rill 1991).
Motor performance is dramatically reduced by PPTN lesion.
Bilateral lesions of PPTN in rats resulted in significant increases in reaction and movement times (Scarnati and Florio
1997), and reversible inactivation of PPTN by lidocaine or
muscimol dramatically affects inter-trial intervals and motor
execution of a lever-release task in conditioned cats (Conde et
al. 1998). It is possible that PPTN is involved in processes
related to selecting the appropriate motor program or maintaining the attentional state to perform a task. We observed that a
subset of PPTN neurons exhibited tonic activity or activity
88 • AUGUST 2002 •
www.jn.org
ACTIVITY OF PPTN DURING VISUALLY GUIDED SACCADES
after FP appearance related to the outcome of the trial (Figs. 7
and 10). These activities may contribute to the maintenance of
attentional or motivational state required to perform the task.
Many studies suggest that PPTN may induce a global attentive state in response to a novel stimulus (Steriade 1996a,b).
Recently, context-dependent activity in PPTN neurons has
been demonstrated (Dormont et al. 1998) in operantly conditioned cats performing a lever-release movement. In that study,
the neurons were activated shortly after the cue stimulus was
presented. We observed similar activity in our visually guided
saccade task. Early in a trial, phasic activities immediately
following the appearance of the FP were observed. In some
neurons, this activity was related to success or error outcome of
the trial (Figs. 10 and 13) and was less dependent on the
location of the visual stimulus on the retina, compared with the
response to ST onset (Fig. 13). Thus the response property
(wider visual receptive field to FP or the relationship to performance of task) of PPTN neurons was dynamically modified
by the behavioral context and may be commensurate with
global attentional or motivational state to perform the task or
the level of wakefulness in behaving animals.
Neuronal activity in a brain stem cholinergic nucleus
(LDTN) relates to tonic activation processes in thalamocortical
systems (Steriade et al. 1990). Projection from PPTN to LGN
is known as the reticular activation system, and the projection
is cholinergic (McDonald et al. 1993). Electrical stimulation of
the brain stem parabrachial region (including PPTN) can also
control visual responses of LGN in cats (Uhlrich et al. 1995).
Both the tonic activity and the response to FP of PPTN related
to behavioral performance (Figs. 7 and 10) were observed. In
Fig. 10, we showed that the activity after FP onset was related
to the outcome of the trial. The neurons showed a visual
response (finely time-locked to the onset of FP rather than to
the onset of fixation), regardless of eye position at FP onset,
and also displayed a response depending on the performance of
the trial. These activities may enhance the responsiveness of
the thalamus and control both sensory and motor processing
and may be related to attentional mechanisms required to
improve both sensory processing and behavioral performance.
Lesion studies in rats have suggested a relationship between
motivation and PPTN (Bechara and van der Kooy 1989; Bechara et al. 1995; Stefurak and van der Kooy 1994). We
investigated a correlation between RTFP and success rate to
evaluate the level of motivation for the upcoming trial task (or
efficacy of the task). We found that the RTFP was a decreasing
function of success rate (Fig. 8D), suggesting that RTFP is a
parameter that may indicate the level of motivation. We have
demonstrated the correlation of the tonic activity and the activity in response to the FP with RTFP, indicating that the
relationship between activity of PPTN and motivation.
Relationship between reinforcement learning and PPTN
The effects of lesions, receptor blocking, electrical selfstimulation, and drug abuse suggest that midbrain dopaminergic systems (SNc and ventral tegmental area) are involved in
processing reward information and learning (for review see
Schultz 1998). Most dopaminergic neurons exhibit phasic activity after primary liquid and food rewards as well as conditioned, reward-predicting visual and auditory stimuli. Re-
J Neurophysiol • VOL
729
cently, Brown and colleagues have presented a sophisticated
computational model of reinforcement learning in the basal
ganglia which includes SNc and PPTN. They successfully
simulated the learning process and the activity of PPTN and
SNc neurons (Brown et al. 1999; see following text). Dopaminergic neurons were activated by rewards during the early
trials of learning sessions, when errors are frequent and rewards unpredictable, but activation by rewards is progressively
reduced as performance consolidated and rewards became
more predictable. The primary reward signal to SNc may
derive from PPTN and suppression of the reward signal after
learning may be caused by GABAergic input from striosomes
(Gerfen 1992). Thus dopaminergic neurons code errors in the
prediction of rewards (Hollerman and Schultz 1998).
In PPTN, neuronal activity around reward was observed
even during our fully conditioned task and this activity sometimes precede reward onset. The activity observed after reward
onset may be a primary reward signal, whereas pre-reward
activity in PPTN may be an excitatory component of the
reward prediction signal sent to SNc. We propose that the
reward-predictive error signal coded by SNc is composed of an
excitatory primary reward signal (derived from PPTN and
other limbic systems), and excitatory (from PPTN) and inhibitory (from striosomes) reward prediction signals.
Takikawa and colleagues (1999) showed that during a saccade task, the dopaminergic neurons in SNc are activated
phasically by the presence of an FP, only in the first trials of
behavioral sessions when the reward is systematically controlled. This response may be related to switching of the task or
a prediction of the reward. The FP-related activity of PPTN in
our study (Fig. 10) may be a source of the phasic response in
SNc and may be inhibited by the basal ganglia (striosomes and
so on) in the following trials.
Signal processing in PPTN
A population of PPTN neurons exhibited both performancerelated activity and activity around reward onset, suggesting
that these neurons may create new motivational states by
integrating signals related to the current motivational state and
the delivery of the reward.
Because PPTN neurons have axon collaterals to both LGN
and the intermediate layer of SC (Billet et al. 1999), it is
possible that PPTN may contribute to improving visual or
motor processing via the thalamus, while sending saccaderelated signals to SC.
Neurons responding to both saccades and rewards were also
observed (shown in Fig. 14). PPTN may also coordinate the
relay of reward information to SNc with information about
saccadic execution. In regards to movement control, PPTN
may integrate saccade-related signals derived from SC, FEF,
and SNr and work cooperatively with SC through their reciprocal connection. Winn and colleagues (Inglis and Winn 1995;
Winn et al. 1997) have presented a computational model in
which PPTN is one critical site through which limbic information concerned with motivation, reinforcement, and the construction of novel associations gains access to a stream of
motor outflow coming from the caudate-putamen and directed
toward pontomedullary systems without reference back to the
cerebral cortex. These hypotheses view PPTN as an integral
88 • AUGUST 2002 •
www.jn.org
730
Y. KOBAYASHI, Y. INOUE, M. YAMAMOTO, T. ISA, AND H. AIZAWA
component of the limbic-motor interface and emphasize the
importance of pontine systems in cognitive processing.
We hypothesized that PPTN integrates signals for saccade
control, reinforcement, and task performance. We observed
multimodal responses in relation to execution of the task.
Signals related to motivation for behaviors (which may be
derived from a conjugating brain stem network, including LC,
DRN, and PPTN), saccade control (derived from SC, SNr, and
FEF), and reward (derived from limbic systems) might be
integrated on each PPTN neuron. PPTN could serve as a
critical interface between the variety of the signals and may
help create attentional/motivational states and reinforce behaviors, according to the history of attentional/motivational states,
action, and reward.
We thank Drs. D. P. Munoz, B. Corneil, and I. Armstrong, J. Gore, A.
LeVasseur, and all the members of Munoz lab for helpful comments, suggestions, and for reviewing English on earlier versions of this manuscript. We also
thank C. Sasaki, Y. Takeshima, and J. Yamamoto for technical assistance.
This study was supported by grants from the Ministry of Education, Science,
Sports, and Culture of Japan to Y. Kobayashi (11780599 and 13035052) and
T. Isa (08458266, 08279207, and 09268238), Care Research for the Evolutionary Science and Technology of the Japan Science and Technology Corporation, the Daiko Foundation, Naito Memorial Foundation, Uehara Memorial
Foundation, and Mitsubishi Foundation.
REFERENCES
AIZAWA H, KOBAYASHI Y, YAMAMOTO M, AND ISA T. Injection of nicotine into
superior colliculus facilitates occurrence of express saccades in monkeys.
J Neurophysiol 82: 1642–1646, 1999.
AIZAWA H AND WURTZ RH. Reversible inactivation of monkey superior
colliculus. I. Curvature of saccadic trajectory. J Neurophysiol 79: 2082–
2096, 1998.
ASTON-JONES G, RAJKOWSKI J, KUBIAK P, VALENTINO RJ, AND SHIPLEY MT.
Role of the locus coeruleus in emotional activation. Prog Brain Res 107:
379 – 402, 1996.
BASSO MA AND WURTZ RH. Modulation of neuronal activity in superior
colliculus by changes in target probability. J Neurosci 18: 7519 –7534, 1998.
BECHARA A, NADER K, AND VAN DER KOOY D. Neurobiology of withdrawal
motivation: evidence for two separate aversive effects produced in morphine-naive versus morphine-dependent rats by both naloxone and spontaneous withdrawal. Behav Neurosci 109: 91–105, 1995.
BECHARA A AND VAN DER KOOY D. The tegmental pedunculopontine nucleus:
a brain-stem output of the limbic system critical for the conditioned place
preferences produced by morphine and amphetamine. J Neurosci 9: 3400 –
3409, 1989.
BENINATO M AND SPENCER RF. A cholinergic projection to the rat superior
colliculus demonstrated by retrograde transport of horseradish peroxidase
and choline acetyltransferase immunohistochemistry. J Comp Neurol 253:
525–538, 1986.
BILLET S, CANT NB, AND HALL WC. Cholinergic projections to the visual
thalamus and superior colliculus. Brain Res 847: 121–123, 1999.
BROWN J, BULLOCK D, AND GROSSBERG S. How the basal ganglia use parallel
excitatory and inhibitory learning pathways to selectively respond to unexpected rewarding cues. J Neurosci 19: 10502–10511, 1999.
BRUCE CJ AND GOLDBERG ME. Primate frontal eye fields. I. Single neurons
discharging before saccades. J Neurophysiol 53: 603– 635, 1985.
CHIBA T, KAYAHARA T, AND NAKANO K. Efferent projections of infralimbic
and prelimbic areas of the medial prefrontal cortex in the Japanese monkey,
Macaca fuscata. Brain Res 888: 83–101, 2001.
CONDÉ H, DORMONT JF, AND FARIN D. The role of the pedunculopontine
tegmental nucleus in relation to conditioned motor performance in the cat.
II. Effects of reversible inactivation by intracerebral microinjections. Exp
Brain Res 121: 411– 418, 1998.
CRIST CF, YAMASAKI DS, KOMATSU H, AND WURTZ RH. A grid system and a
microsyringe for single cell recording. J Neurosci Methods 26: 117–122,
1988.
J Neurophysiol • VOL
DATTA S AND SIWEK DF. Excitation of the brain stem pedunculopontine
tegmentum cholinergic cells induces wakefulness and REM sleep. J Neurophysiol 77: 2975–2988, 1997.
DELLU F, MAYO W, CHERKAOUI J, LE MOAL M, AND SIMON H. Learning
disturbances following excitotoxic lesion of cholinergic pedunculo-pontine
nucleus in the rat. Brain Res 544: 126 –132, 1991.
DIAS EC AND BRUCE CJ. Physiological correlate of fixation disengagement in
the primate’s frontal eye field. J Neurophysiol 72: 2532–2537, 1994.
DORMONT JF, CONDÉ H, AND FARIN D. The role of the pedunculopontine
tegmental nucleus in relation to conditioned motor performance in the cat.
I. Context-dependent and reinforcement-related single unit activity. Exp
Brain Res 121: 401– 410, 1998.
DORRIS MC AND MUNOZ DP. A neural correlate for the gap effect on saccadic
reaction times in monkey. J Neurophysiol 73: 2558 –2562, 1995.
DORRIS MC AND MUNOZ DP. Saccadic probability influences motor preparation signals and time to saccadic initiation. J Neurosci 18: 7015–7026, 1998.
DORRIS MC, PARÉ M, AND MUNOZ DP. Neuronal activity in monkey superior
colliculus related to the initiation of saccadic eye movements. J Neurosci 17:
8566 – 8579, 1997.
EDLEY SM AND GRAYBIEL AM. The afferent and efferent connections of the
feline nucleus tegmenti pedunculopontinus, pars compacta. J Comp Neurol
217: 187–215, 1983.
EVERLING S AND MUNOZ DP. Neuronal correlates for preparatory set associated
with pro-saccades and anti-saccades in the primate frontal eye field. J
Neurosci 20: 387– 400, 2000.
FISCHER B AND BOCH R. Saccadic eye movements after extremely short
reaction times in the monkey. Brain Res 260: 21–26, 1983.
FISCHER B AND WEBER H. Express saccade and visual attention. Behav Brain
Sci 16: 553– 610, 1993.
FUCHS AF AND ROBINSON DA. A method for measuring horizontal and vertical
eye movement chronically in the monkey. J Appl Physiol 21: 1068 –1070,
1966.
FUTAMI T, TAKAKUSAKI K, AND KITAI ST. Glutamatergic and cholinergic inputs
from the pedunculopontine tegmental nucleus to dopamine neurons in the
substantia nigra pars compacta. Neurosci Res 21: 331–342, 1995.
GARCIA-RILL E. The pedunculopontine nucleus. Prog Neurobiol 36: 363–389,
1991.
GERFEN CR. The neostriatal mosaic: multiple levels of compartmental organization. Trends Neurosci 15: 133–139, 1992.
GERFEN CR, STAINES WA, ARBUTHNOTT GW, AND FIBIGER HC. Crossed
connections of the substantia nigra in the rat. J Comp Neurol 207: 283–303,
1982.
GLIMCHER PW AND SPARKS DL. Movement selection in advance of action in
the superior colliculus. Nature 355: 542–545, 1992.
GRANATA AR AND KITAI ST. Inhibitory substantia nigra inputs to the pedunculopontine neurons. Exp Brain Res 86: 459 – 466, 1991.
GRAYBIEL AM. A stereometric pattern of distribution of acetylthiocholinesterase in the deep layers of the superior colliculus. Nature 272: 539 –541,
1978.
HALL WC, FITZPATRICK D, KLATT LL, AND RACZKOWSKI D. Cholinergic
innervation of the superior colliculus in the cat. J Comp Neurol 287:
495–514, 1989.
HALLANGER AE AND WAINER BH. Ascending projections from the pedunculopontine tegmental nucleus and the adjacent mesopontine tegmentum in the
rat. J Comp Neurol 274: 483–515, 1988.
HAYS AV, RICHIMOND BJ, AND OPTICAN LM. A UNIX-based multiple process
system for real-time data acquisition and control. WESCON Conf Proc 2:
1–10, 1982.
HENDERSON Z AND SHERRIFF FE. Distribution of choline acetyltransferase
immunoreactive axons and terminals in the rat and ferret brainstem. J Comp
Neurol 314: 147–163, 1991.
HIKOSAKA O AND WURTZ RH. Visual and oculomotor functions of monkey
substantia nigra pars reticulata. I. Relation of visual and auditory responses
to saccades. J Neurophysiol 49: 1230 –1253., 1983.
HOLLERMAN JR AND SCHULTZ W. Dopamine neurons report an error in the
temporal prediction of reward during learning. Nat Neurosci 1: 304 –309,
1998.
HUERTA MF AND HARTING JK. Tectal control of spinal cord activity: neuroanatomical demonstration of pathways connecting the superior colliculus
with the cervical spinal cord grey. Prog Brain Res 57: 293–328, 1982.
INGLIS WL AND WINN P. The pedunculopontine tegmental nucleus: where the
striatum meets the reticular formation. Prog Neurobiol 47: 1–29, 1995.
88 • AUGUST 2002 •
www.jn.org
ACTIVITY OF PPTN DURING VISUALLY GUIDED SACCADES
ISA T, ENDO T, AND SAITO Y. Nicotinic facilitation of signal transmission in the
local circuits of the rat superior colliculus. Soc Neurosci Abstr 24: 60.13,
1998.
JEON CJ, SPENCER RF, AND MIZE RR. Organization and synaptic connections
of cholinergic fibers in the cat superior colliculus. J Comp Neurol 333:
360 –374, 1993.
KOBAYASHI Y, YAMAMOTO M, ISA T, AND AIZAWA H. Control of saccadic
reaction time by pedunculopontine tegmental nucleus neurons in monkeys.
Soc Neurosci Abstr 25: 661.667, 1999.
KOYAMA Y, HONDA T, KUSAKABE M, KAYAMA Y, AND SUGIURA Y. In vivo
electrophysiological distinction of histochemically-identified cholinergic
neurons using extracellular recording and labelling in rat laterodorsal tegmental nucleus. Neuroscience 83: 1105–1112, 1998.
KOYAMA Y, JODO E, AND KAYAMA Y. Sensory responsiveness of “broad-spike”
neurons in the laterodorsal tegmental nucleus, locus coeruleus and dorsal
raphe of awake rats: implications for cholinergic and monoaminergic neuron-specific responses. Neuroscience 63: 1021–1031, 1994.
KOYAMA Y AND KAYAMA Y. Mutual interactions among cholinergic, noradrenergic and serotonergic neurons studied by ionophoresis of these transmitters in rat brainstem nuclei. Neuroscience 55: 1117–1126, 1993.
KUSAMA T AND MABUCHI M. Stereotaxic Atlas of the Brain of Macaca fuscata.
Tokyo: University of Tokyo Press, 1970.
LAVOIE B AND PARENT A. Pedunculopontine nucleus in the squirrel monkey:
projections to the basal ganglia as revealed by anterograde tract-tracing
methods. J Comp Neurol 344: 210 –231, 1994.
LINDSLEY DB. The reticular system and perceptual discrimination. In: The
Reticular Formation of the Brain. Boston: Little, Brown, and Co., 1958,
513–534.
LOKWAN SJ, OVERTON PG, BERRY MS, AND CLARK D. Stimulation of the
pedunculopontine tegmental nucleus in the rat produces burst firing in A9
dopaminergic neurons. Neuroscience 92: 245–254, 1999.
MA TP, GRAYBIEL AM, AND WURTZ RH. Location of saccade-related neurons
in the macaque superior colliculus. Exp Brain Res 85: 21–35, 1991.
MATSUMURA M, NAMBU A, YAMAJI Y, WATANABE K, IMAI H, INASE M,
TOKUNO H, AND TAKADA M. Organization of somatic motor inputs from the
frontal lobe to the pedunculopontine tegmental nucleus in the macaque
monkey. Neuroscience 98: 97–110, 2000.
MATSUMURA M, WATANABE K, AND OHYE C. Single-unit activity in the primate
nucleus tegmenti pedunculopontinus related to voluntary arm movement.
Neurosci Res 28: 155–165, 1997.
MAY PJ AND PORTER JD. The laminar distribution of macaque tectobulbar and
tectospinal neurons. Vis Neurosci 8: 257–276, 1992.
MCDONALD CT, MCGUINNESS ER, AND ALLMAN JM. Laminar organization of
acetylcholinesterase and cytochrome oxidase in the lateral geniculate nucleus of prosimians. Neuroscience 54: 1091–1101, 1993.
MIRENOWICZ J AND SCHULTZ W. Importance of unpredictability for reward
responses in primate dopamine neurons. J Neurophysiol 72: 1024 –1027,
1994.
PARÉ M AND MUNOZ DP. Saccadic reaction time in the monkey: advanced
preparation of oculomotor programs is primarily responsible for express
saccade occurrence. J Neurophysiol 76: 3666 –3681, 1996.
PERRY E, WALKER M, GRACE J, AND PERRY R. Acetylcholine in mind: a
neurotransmitter correlate of consciousness? Trends Neurosci 22: 273–280,
1999.
REDGRAVE P, MITCHELL IJ, AND DEAN P. Descending projections from the
superior colliculus in rat: a study using orthograde transport of wheatgermagglutinin conjugated horseradish peroxidase. Exp Brain Res 68: 147–167,
1987.
J Neurophysiol • VOL
731
RICHMOND BJ, OPTICAN LM, PODELL M, AND SPITZER H. Temporal encoding of
two-dimensional patterns by single units in primate inferior temporal cortex.
I. Response characteristics. J Neurophysiol 57: 132–146, 1987.
SCARNATI E AND FLORIO T. The pedunculopontine nucleus and related structures. Functional organization. Adv Neurol 74: 97–110, 1997.
SCHNURR B, SPATZ WB, AND ILLING RB. Similarities and differences between
cholinergic systems in the superior colliculus of guinea pig and rat. Exp
Brain Res 90: 291–296, 1992.
SCHULTZ W. Predictive reward signal of dopamine neurons. J Neurophysiol 80:
1–27, 1998.
SEMBA K AND FIBIGER HC. Afferent connections of the laterodorsal and the
pedunculopontine tegmental nuclei in the rat: a retro- and antero-grade
transport and immunohistochemical study. J Comp Neurol 323: 387– 410,
1992.
SHELIGA BM, CRAIGHERO L, RIGGIO L, AND RIZZOLATTI G. Effects of spatial
attention on directional manual and ocular responses. Exp Brain Res 114:
339 –351, 1997.
SHIDARA M AND KAWANO K. Role of Purkinje cells in the ventral paraflocculus
in short-latency ocular following responses. Exp Brain Res 93: 185–195,
1993.
SHOUSE MN AND SIEGEL JM. Pontine regulation of REM sleep components in
cats: integrity of the pedunculopontine tegmentum (PPT) is important for
phasic events but unnecessary for atonia during REM sleep. Brain Res 571:
50 – 63, 1992.
SPARKS DL AND HARTWICH-YOUNG R. The deep layers of the superior colliculus. Rev Oculomot Res 3: 213–255, 1989.
SPARKS D, ROHRER WH, AND ZHANG Y. The role of the superior colliculus in
saccade initiation: a study of express saccades and the gap effect. Vision Res
40: 2763–2777, 2000.
STECKLER T, INGLIS W, WINN P, AND SAHGAL A. The pedunculopontine
tegmental nucleus: a role in cognitive processes? Brain Res Brain Res Rev
19: 298 –318, 1994a.
STECKLER T, KEITH AB, AND SAHGAL A. Lesions of the pedunculopontine
tegmental nucleus do not alter delayed non-matching to position accuracy.
Behav Brain Res 61: 107–112, 1994b.
STEFURAK TL AND VAN DER KOOY D. Tegmental pedunculopontine lesions in
rats decrease saccharin’s rewarding effects but not its memory-improving
effect. Behav Neurosci 108: 972–980, 1994.
STEININGER TL, RYE DB, AND WAINER BH. Afferent projections to the cholinergic pedunculopontine tegmental nucleus and adjacent midbrain extrapyramidal area in the albino rat. I. Retrograde tracing studies. J Comp
Neurol 321: 515–543, 1992.
STERIADE M. Awakening the brain. Nature 383: 24 –25, 1996a.
STERIADE M. Arousal revisiting the reticular activating system. Science 272:
225–226, 1996b.
STERIADE M, DATTA S, PARÉ D, OAKSON G, AND CURRO DOSSI RC. Neuronal
activities in brain-stem cholinergic nuclei related to tonic activation processes in thalamocortical systems. J Neurosci 10: 2541–2559, 1990.
TAKAKUSAKI K, SHIROYAMA T, YAMAMOTO T, AND KITAI ST. Cholinergic and
noncholinergic tegmental pedunculopontine projection neurons in rats revealed by intracellular labeling. J Comp Neurol 371: 345–361, 1996.
TAKIKAWA Y, KAWAGOE R, AND HIKOSAKA O. Emergence of reward-predicting
ability of monkey dopamine neurons: long-term plasticity. Soc Neurosci
Abstr 25: 470.412, 1999.
UHLRICH DJ, TAMAMAKI N, MURPHY PC, AND SHERMAN SM. Effects of brain
stem parabrachial activation on receptive field properties of cells in the cat’s
lateral geniculate nucleus. J Neurophysiol 73: 2428 –2447, 1995.
WINN P, BROWN VJ, AND INGLIS WL. On the relationships between the striatum
and the pedunculopontine tegmental nucleus. Crit Rev Neurobiol 11: 241–
261, 1997.
88 • AUGUST 2002 •
www.jn.org