Download Bischoff_Thesis_notes



Ch 2
o SMA
 SMA-proper
 reciprocal connections to motor cortex
 projects to BG
 projections from BG via thalamus (Tokuno et al., 1992)
 projections from somatosensory area 3a
 internally generated sequences
 pre-SMA
 receives connections from prefrontal cortex, area 46 area F5
and anterior cingulate cortex
 externally generated sequences
o Prefrontal
 learning of new sequences
 she says that in the DAJ model, prefrontal activity increased as the
sequences were learned due to a strengthening of the prefrontal-striatal
synapses involved in the correct movements
 #is this true? or does the activity stay the same and just the
prefrontal-striatal connection weights are increased. it doesn't
seem to me that this would affect activity in the prefrontal
cortex unless there were recipocal connections from the basal
ganglia (which i believe there are, however I don't believe they
were included in the DAJ model)#
Ch 3 – Basal ganglia
o 5 segregated cirtcuits (Alexander et al., 1986)
 oculomotor circuit – voluntary eye movement
 two prefrontal circuits
 lateral prefrontal – visual attention
 lateral orbitofrontal – cognitive behavior
 limbic circuit – emotional or motivational behavior
 skeletomotor circuit – voluntary skeletal movement
o Striatum
 Made of putamen, caudate, and nucleus accumbens
 Medium spiny neurons – up to 96% (DiFiglia et al., 1976; Wilson &
Groves, 1980)
 Project to the pallidum
 Usually silent, occasionally firing in bursts of spikes 0.1 to 2
seconds
 Fire at a rate no larger than 40 Hz (Wilson & Groves, 1981;
Wilson, 1990)
 2 states in membrane potential – hyperpolarized (off) or
depolarized near spike threshold (on), (Nisenbaum & Wilson,
1995)




response level is dependent on recent voltage history – less
time spent in off state the higher the next response (Nisenbaum
et al., 1994)
Two systems differentiated by neurotransmitter (Gerfen, 1985;
Graybiel et al., 1989; Graybiel, 1990)
 Striosomes
o Receive inputs from areas related to limbic system
o Specialized compartments with no AChE
o Inputs from dopaminergic neurons of ventral SNc and
clustered dopaminergic cells of the SNr
o Project to dopaminergic cells of the SNc (Gerfen &
Young, 1988)
 Matrix
o Inputs related to sensorimotor processing (from
sensorimotor cortex, parieto-temporal-occipital
association cortex, areas of lateral frontal cortex)
o Inputs from dopaminergic neurons in the midbrain
VTA, retrorubral area, and dorsal tier of SNc
o Contains clusters of cells (matrisomes) related to arm
movement for example, that correspond to projecting
cells of the arm area of motor cortex
 #Is it body-part or action-specific?#
o main source of projections to GABAergic neurons of
the SNr (Gerfen & Young, 1988)
o matriosomes project to either GPe or GPi, rarely to both
TANs
 Cholinergic interneurons (Aosaki et al., 1995)
 Number of TANs firing in response to performance of a task
increases from 10-20% to 60-70% once it is learned
o #Is this the number of TANs that are actually tonically
active during an action, or the number of TANs that
show their characteristic response (inactivation) during
an action?#
 long term changes - retain responsiveness after 4 weeks
(Aosaki et al., 1995)
 Number of firing TANs reduced to unlearned levels with
injection of MPTP (Kimura et al., 1993)
o Dopamine agonist restored firing to CS
o Reponse rates did not increase w/ additional training
o Kimura et al., 1993 – TANs must receive input from
nigrostriatal neurons and cortex
o Dopamine involved with acquisition of response
 Tend to lie along striosome-matrix borders
o In position to communicate reward signal from
striosomes (via dopamine) to matrix
Putamen – skeletomotor function


Input from MC, PM and SMA
Somatotopic organization (Crutcher & DeLong, 1984a;
Alexander & Crutcher, 1990a)
o Leg – dorsolateral zone
o Orofacial – ventromedial
o Arm – in between
o Extend along rostrocaudal axis
o #see putting a spin on the axis paper#
 arm region – projections from arm regions of MC, SMA, and
PM
o non-overlapping
o segregation continues in pallidum and thalamus
(Mitchell et al., 1987; Alexander et al., 1990;
Wichmann et al., 1994b)
 topographic projection back to putamen from dorsolateral STN
and VL portion of thalamus (Parent, 1986)
 movement-related and pre-movement-related activity in
monkeys performing elbow flexion-extension task (Alexander
& Crutcher, 1990c; 1990b; Crutcher & Alexander, 1990)
 pre-movement and movement-related activity in precued
reaching task (Jaeger et al., 1993)
 Shim et al., (1996) – sequential movement task – 70%
responsive for action regardless of order in sequence, some
depended on placement in sequence
 Caudate – oculomotor function
 Input from FEF and SEF
 Nucleus Accumbens – emotional / motivational
 Input from limbic regions and orbitofrontal cortex
o Globus Pallidus
 Ventral pallidum – limbic circuit
 External segment (GPe) – indirect
 Excessive activity → hyperkinetic disorders
 Convergence ratio – 300:1 (Alexander, 1994)
 High spontaneous discharge rate with pauses (mean firing rate
of 56 spikes/sec) or low spontaneous discharge with occasional
high frequency bursts (mean firing rate of 9.6 spikes/sec),
(Mitchell et al., 1987)
 Input from striatum is GABA and enkephalin
 Internal segment (GPi) – direct
 Excessive activity → hypokinetic disorders
 Convergence ratio – 100:1 (Alexander, 1994)
 High spontaneous discharge rate without pauses (mean firing
rate of 71 spikes/sec), (Mitchell et al., 1987)
 Input from striatum is GABA and neuropeptide substance P
 Correlation of neural activity with movement parameters

o
o
o
o
Most studies correlate activity here with direction of movement
(Mitchell et al., 1987; Brotchie et al., 1991a)
 Mink & Thach (1991b) – no relationship between pallidal
firing and movement velocity, amplitude, joint position, or
force production in wrist movements
 Georgopoulos et al. (1983) – globus pallidus and STN relationships to direction, amplitude, and peak velocity of
movement
 Turner & Anderson (1997) – both segments discharges
temporally related to arm movement as well as movement
direction and amplitude
 Nambu (1990) – discharge during delay period of go/no-go
task + movement and visual-stimulu sensitive cells
 Depletion of dopamine (or blockade of D2 receptors) raises levels of
enkephalin and lowers substance P levels and vice versa
Subthalamic Nucleus
 Input from GPe
 Somatopically organized (Wichmann et al., 1994b)
 Excitatory glutamatergic projections to both GPe and GPi
 Inhibitory input from SNc in rats (Campbell et al., 1985; Kreiss et al.,
1997)
 Accounts for increase in STN firing rate after lesions of SNc in
rats (Hassani et al., 1996)
 Rhesus monkeys – low-frequency tonic discharge of 20-30 Hz
(DeLong et al., 1985)
 Somatotopic projections from MC and SMA (Nambu et al., 1996)
 SMA – medial half
 MC – lateral half
 Mean firing rate – 18.8 ± 10.3 Hz (Wichmann et al., 1994b)
Substantia Nigra Pars Compacta
 Large projection neurons which send dopaminergic projections to
striatum (Yelnik et al., 1987)
 Cortical input from PFC (Naito & Kita, 1994)
 Dopamine modulates striatal projections to direct and indirect
pathways
Parkinson’s Disease
 Caused by reduction in dopamine production in SNc
 Symptoms: akinesia, bradykinesia, tremor
 Reduces amount of GABA in the putamen (Griffiths et al., 1994)
 May be due to degeneration of nigostriatal dopaminergic axons
which contain GABA receptors
 Reduces number of dopamine uptake sites in the striatum (Joyce,
1993)
SMA-BG Relationship
 Striatum and STN receive topographic projections from pre-SMA and
SMA (Parthasarathy et al., 1992; Inase et al., 1996; Namnu et al.,
1996) which are organized somatoptopically (Alexander & Crutcher,
1990a)
 Strong projection from ventrolateral pars oralis thalamus (VLo) of
macaque (receives input from GPi, Sakai et al.,, 1996) to SMA
(Shindo et al., 1995)
 Miyachi et al. (1997) – inactivation of anterior caudate and putamen
disrupted learning a new sequence, injections into middle-posterior
putamen disrupted execution of well-learned sequences
 Jenkins et al. (1994) – human PET – putamen equally active during
learning sequence and executed overlearned sequence
 Grafton (1995a) – learning related increases in putamen and SMA
 Reduction in SMA activity in Parkinson’s (Playford et al., 1992;
Grafton et al., 1995b)
 Rescued with dopamine agonists (Rascol et al., 1994)
 Unilateral posteroventral pallidotomy – contralateral SMA
activation increased, contralateral globus pallidus reduced
activation
 Parkinson’s patients have difficulty with sequential tasks
 Bennett et al., (1995) – reach-grasp, take-to-mouth with cup
o 8/9 PD patients paused (mean 340ms) between actions
 Castiello & Bennet (1994) – PD patients grasp small or large
cylinder (precision or power), cylinder was sometimes
switched at movement onset
o PD patients – plateau in grip type switch (mean size of
plateau – 398 ms)
 Increased inhibition of cortex causes prolonged movement time
and pauses between movements
o Comparison of BG and Cerebellum
 3 main differences
 BG receives input from whole cortex, cerebellum only from
sensorimotor parts
 Cerebellum projects to premotor and motor cortex, BG also
projects to prefrontal cortex #What about developmental refs
from my quals that stress a relationship between cerebellum
and prefrontal cortex?#
 Cerebellum gets somatosensory info from spinal cord and has
inputs and outputs to brain stem nuclei, BG has few
connections with brain stem and no connections with spinal
cord (Cote & Crutcher, 1991)
 Connections
 Cerebellum
o Projections from prestriate cortex, V5 and V5a of
temporal cortex, and parietal 7a via pons (Glickstein et
al., 1980; Ungerleider et al., 1984)
o Dentate and interpositus project to VPLo, VPLc, VLc,
and X



VPLo projects to motor cortex and SMA and X
and VLc project to premotor cortex (Matelli et
al., 1989)
o Projects to VLo weakly (rarely overlapping with
projections from GPi), (Rouillier et al., 1994)
o Sparse projection from areas 8, 9, and 46 (Glickstein et
al., 1980)
 Basal ganglia
o Projections from entire cortex
o Projects to VLo, then to SMA, PM, and MC
 Pallidothalamic and cerebrothalamic projections to cortex can
overlap
o i.e. F4 gets input from VLo, VLc, and X
Functional Differences
 Both active during simple repetitive arm movements (Brooks et
al., 1993)
 Both active during premovement phase (Deiber et al., 1996)
 Repetitive finger movement paced by metronome – (Friston et
al., 1992) - Increase in cerebellum after practice
 Basal ganglia increase with sequences (Jenkins et al., 1994)
o Cerebellum increase during learning a sequence
(Jenkins et al., 1992)
 Timing – cerebellum seems to be involved in timing at a finer
scale than basal ganglia
 cerebellum may be specialized in using sensory information
and acquiring in motor skills
 basal ganglia may be more involved in movements which are
either internally generated or guided by external cues as well as
the learning of sequential movements
Ch 4 – The Motor Cortex and Thalamus
o Motor cortex
 Columns of pyramidal neurons reciprocally connected with thalamus
 Most corticocortical reciprocal connections are mutually excitatory
 Receives projections from SMA and projects to putamen
 Active after SMA and before putamen – serial processing
o Thalamus
 All sensory systems (except olfactory) pass through thalamus on way
to cortex
 Each part of thalamus receives connections from each area of cortex
that it projects to (Jones, 1985)
 3 Main Divisions
 Dorsal thalamus – projects to cortex and striatum (reciprocal
connections)





Ventral thalamus – includes reticular nucleus of thalamus
(RTN) – innervated by cortex and reciprocally connected with
dorsal thalamus
 Epithalamus – associated with hypothalamus – no direct
input/output with cortex
3 Main Neuronal Elements
 Extrinsc afferents to the nucleus
 The principal neurons (relay neurons) – can be excitatory or
inhibitory, but usually excitatory to cortex and striatum
(Bloomfield et al., 1987; Sherman & Koch, 1990)
 Interneurons (intrinsic neurons) – GABAergic inhibitory input
to relay neurons
Dorsal thalamus
 No contralateral connections
 VLo – input from globus pallidus
 LGN – retinotopic map – pattern seems to exist in other parts
of thalamus too (Jones, 1985; Sherman & Koch, 1990)
 Holsapple et al., (1991) – projections of VLo and VPLo to MC
 Jinnai et al., (1993) – caudal VLo → MC, rostral Vlo → SMA
 Rouiller et al. (1994) – MC receives projections from VLo and
VPLo
 Forlano et al. (1993) – neurons in VLo have directional
movement preferences, but don’t respond to passive movement
 Vitek et al. (1996) – 21% of VLo neurons have motor response
o On border with VPLo (receives projections from
cerebellum)
o Somatotopic arrangement
 Vitek et al., (1994a) – somatotopy in VPLo – longer latency
and smaller amplitude than VLo
o VPLo could be relay of proprioceptive info to MC
o VLo – more active response – planning or inhibiting
movement
Deiber et al (1996) – increase rCBF in thalamus during motor
preparation
Ch 5 – An Hypothesis on Basal Ganglia Function
o Hypothesis:
 Indirect pathway – movement inhibition
 Direct pathway – provides next sensory state to cortex
o Evidence
 Striatal neurons rarely project to GPe and GPi (Graybiel et al., 1989)
 GPe projections – neurons contain D2 receptors and express
enkephalin, GPi projections – neurons contain D1 receptors and
express substance P (Gerfen & Wilson, 1996)

Dopamine has opposing effects on the two receptor types –
decreases in dopamine increases enkephalin and decreases
substance P (Gerfen & Wilson, 1996)
 GPi releases inhibition of thalamus during movement (Mitchell et al.,
1987; 1991b; 1991c; Mink & Thach, 1991a)
 STN excitation increases tonic inhibition of the thalamus by GPi
(Hamada & DeLong, 1992b, 1992a)
 Preparatory movement areas project to the indirect, movement-related
areas project to direct pathway (Nambu et al., 1990; Yoshida et al.,
1993)
o Overview
 PFC – WM and sequence learning (Barone & Joseph, 1989; Jenkins et
al., 1994)
 Projects to pre-SMA (Luppino et al., 1993) – source of
sequences the pre-SMA knows
 Pre-SMA – preparing visually-guided movement sequence (Halsband
et al., 1994; Tanji & Mushiake, 1996)
 Projects sequential information to SMA and indirect pathway
of basal ganglia
 SMA – internal generation of sequences and repetitive movements
(Passingham et al., 1989; Tanji & Shima, 1994)
 Contain information on the overall sequence
 Keep track of which movement is next
 Project current movement to MC and direct pathway of basal
ganglia
 Project next movement to premovement population in MC and
indirect pathway of basal ganglia
 Basal ganglia
 Indirect pathway – brake pedal
o Inhibits motor commands from being performed
 Direct pathway – gas
o Provides cortex with next sensory state info
 Motor Cortex
 Carries out motor command
 Handles fine-tuning of movement
 Projects motor parameters to brainstem and direct pathway of
basal ganglia
o Inhibition of movement
 SMA_PROPER
   10ms
 s  INPUT  0.2*VLO _ SMAP _ INH


MC


SMA _ PROPER _ INH  sigmoid u,0, 40,0,60
  10ms
s  0.85* SMA _ PROPER _ INH  0.2*VLO _ MC _ INH






PUT

MC _ INH  sigmoid (u, 20, 45, 0,100)

two membrane potential states in striatum
o new function – sigma_updown – the higher the
membrane potential, the faster the time constant
o results in quicker response to synaptic input (“up” state)
  sigma _ updown u,0,60,0.04,0.006

s  0.6* SMA _ PROPER _ INH  0.8* MC _ INH  1* SNC

GPE


PUT _ INH  sigmoid u,0,90,0,60
  10ms
s  0.3* PUT _ INH  30
 GPE  sigmoid u,0, 40, 20,68
STN
   10ms
 s  0.2* GPE  0.75* SNC  40
 STN  sigmoid u, 20, 40,18,34
GPI
   10ms
 s  0.5* PUT _ MVT  0.5* STN  40
 GPI  sigmoid u, 20,58,60,100
VLO
 VLO_MC_INH
o   10ms
o s  0.2* GPI  0.3* MC _ INH  15
o VLO _ MC _ INH  sigmoid u,0,30,0,90

VLO_SMAP_INH
o   10ms
o s  0.2* GPI  0.2* SMA _ PROPER _ INH  18
o VLO _ SMAP _ INH  sigmoid u,0,30,0,90
o Next Sensory State Information
 Why movement-related cells in the basal ganglia are not responsible
for movement initiation (possibly contrary to Redgrave’s hypothesis
on the basal ganglia as action selection, at least superficially)
 Crutcher & Alexander (1990) – movement related putamen
neurons fire an average of 33 ms after the onset of a movement
(after activation of MC – 56ms later, and SMA – 80 ms later)
 Mink & Thach (1991b) – movement-related activity in GPe
and GPi also late
 Turner & Anderson (1997) – GP neurons rarely change
discharge before activity of agonist muscles

SMA_PROPER_MVT
   10ms
 s  INPUT  0.1*VLO _ SMAP _ MVT

 SMA _ PROPER _ MVT  sigmoid u,10, 40,0,50
MC_MVT
   10ms
 s  0.8* SMA _ PROPER _ MVT  0.07 *VLO _ MC _ MVT

 MC _ MVT  sigmoid u, 20,50,0,100
PUT_MVT
   sigma _ updown u,0,60,0.04,0.006

s  0.6* SMA _ PROPER _ MVT  0.8* MC _ MVT  1* SNC

 PUT _ MVT  sigmoid u,0,90,0,60
VLO_MC_MVT
   10ms
 s  0.2* GPI  0.23* MC _ MVT  12

 VLO _ MC _ MVT  sigmoid u,0,30,0,90
VLO_SMAP_MVT
   10ms
 s  0.2* GPI  0.27 * SMA _ PROPER _ MVT  11
 VLO _ SMAP _ MVT  sigmoid u,0,30,0,90
o Contributions of Dopamine
 Excites direct pathway striatum and inhibits indirect pathway striatum
(Gerfen & Wilson, 1996)
 SNC
   10ms
 s  LIMBIC
 SNC  sigmoid u,0,60,0, 20
 healthy – LIMBIC=20
o Results Summary
 Elbow Flexion-Extension
 Replicates Alexander & Crutcher’s results
 Reciprocal Aiming
 Decrease SNc (Parkinson’s), increase STN and GPi/GPe,
decrease MC -> slower movement time
 Slowdown in overall neural activity
 Neural slowdown+slower movement time=pauses between
movements
 Sequential Arm Movements
 Improved SMA-Proper based on Tanji & Shima (1994) –
neurons represent overall sequence and subsequences


Dopamine depletion -> pauses between movements to targets,
velocity was less for each subsequent movement (like
bradykinesia, Agostino et al.,1992)
 Further dopamine depletion – only movement to first target
o Model Comparison
 Alexander & Crutcher
 Basal ganglia either assists in choosing motor command or
facilitates motor command chosen by cortex
 Bischoff: unlikely to initiate but modulates parameters
generated elsewhere
 Connolly & Burns
 Planning goal-oriented and obstacle-avoiding behavior by
driving smooth state transitions
 Bischoff: couldn’t handle complex movements, not
biologically plausible
 Dominey & Arbib
 Basal ganglia gates working memory by allowing
thalamocortical loop
 BG disinhibits SC to allow saccades
 Bischoff: only modeled direct pathway
 Dominey, Arbib, & Joseph
 SNc -> caudate as a reinforcement learning mechanism
 Crowley
 Expanded Dominey & Arbib model to include indirect pathway,
projections from SNc to caudate and STN, and tonically active
neurons in caudate
 Same hypothesis but for oculomotor function
Ch 6 - Modeling the Basal Ganglia in an Elbow Flexion –Extension Task
o Based on Alexander & Crutcher experiments
o Preinstruction (center light), cue (left or right light), postinstruction (center
light), movement (left and right lights)
o Two phases of activity
 Preparatory
 Preventing response before go signal
 Movement
o Neurons selective for flexion and extension
o SMA_PROPER_INH
   10ms
s  29.5* INPUT 5  30.5* INPUT _ DIR 

mut _ inh * SMA _ PROPER _ INH  0.2*VLO _ SMAP _ INH
 #I had to change this to
s  29.5* INPUT 5  0.1* SMA _ PROPER _ MVT 
to get
mut _ inh * SMA _ PROPER _ INH  0.2*VLO _ SMAP _ INH
the model to work where mut_inh was an 11x11 matrix and
mut_inh[i][j]=0.0 if i=j, otherwise mut_inh[i][j]=-0.9#
 SMA _ PROPER _ INH  sigmoid u,0, 40,0,60
o SMA_PROPER_MVT
   10ms
s  10* INPUT 5  30.5* INPUT _ DIR 


0.05* SMA _ PROPER _ INH  0.05* SMA _ PROPER _ MVT 
0.2*VLO _ SMAP _ MVT
#I had to change this to
s  10* INPUT 5  30.5* INPUT _ DIR 
0.05* SMA _ PROPER _ INH  0.05* SMA _ PROPER _ MVT 
0.2*VLO _ SMAP _ MVT  mut _ inh * SMAP _ PROPER _ MVT
to get the model to work where mut_inh was an 11x11 matrix and
mut_inh[i][j]=0.0 if i=j, otherwise mut_inh[i][j]=-0.9#
 SMA _ PROPER _ MVT  sigmoid u,0, 40,0,60
o Experiment
 Phase 1 – center light
 No cortical activation
 Phase 2 – left light
 SMA_MVT activated, primes SMA_INH, activates MC_MVT
and PUT_MVT – disinhibits VLO_SMA_MVT and
VLO_MC_MVT through GPi
 Active flexion movement
 Phase 3 – center light
 MVT areas activity decreases
 SMA_INH was primed by SMA_MVT in Phase 2, now center
light activation is enough to activate it
 SMA_INH primes SMA_MVT, excites MC_INH and
PUT_INH
 PUT_INH inhibits GPe, STN activity increases – activates GPi
 GPi inhibits VLO_MC_MVT and VLO_SMA_MVT
 No movement
 Phase 4 – left and right lights
 SMA_MVT flexion and extension excited by lights
 SMA_MVT flexion was primed by SMA_INH in phase 3 and
laterally inhibits SMA_MVT extension
 SMA_MVT flexion activated – activates MC_MVT and
PUT_MVT – disinhibits VLO_SMA_MVT and
VLO_MC_MVT through GPi
 Active flexion movement
o Discussion


Movement preparation in cortex primes regions responsible for
execution and activates BG which inhibits movement execution until
GO signal
 Regions responsible for execution prime premovement areas for the
next movement
 BG project next expected sensory state to cortex
Ch 7 - Modeling the Basal Ganglia in a Reciprocal Aiming Task
o Task – alternately reach to two targets as fast as possible
o Fitt’s Law - speed-accuracy tradeoff – A=amplitude, MT=movement time,
W=target width, ID=index of difficulty
 MT  a  bID
 ID  log2  2 A / W 
o Hoff & Arbib (1992) – Fitt’s Law explained with control using single
feedback system with delays, duration based on experience with errors
incurred at high velocities
 Slower the movement – more time available for feedback to adjust the
movement
o Winstein et al. (1997) – Parkinson’s and left/right stroke patients
 1) stylus tap on single 8cm wide target
 ID=0
 2) stylus tap between two 8cm wide targets located 37cm apart
 ID=3.21
 3) stylus tap between two 2cm wide targets located 37cm apart
 ID=5.21
 PD – slower overall time, only touched small region of target,
constrained arcs through x,y plane (compared to controls)
 May be related to slower speed
 Prediction: slower speed is due to inability of BG to release
inhibition of movement – decrease in SMA and MC activity –
reduction in speed and variation of movement
o Arm Representation
 3 DOF
 VITE
 Calculates trajectory given current position and target position
using diference vector
 Produces Fitt’s Law
 Drawback – joints are independent
 Min Jerk and Min Torque
 Min Jerk – kinematic
 Min Torque – replicates curvature in human movement (unlike
min jerk)
o Needs iterative learning scheme to learn optimal
trajectory
 Trajectory Generating System
 Hoff & Arbib model


Based on min jerk with delayed feedback
Convert motor cortex joint coordinates to cartesian space
(endpoint position) and used motor cortex firing rate to
determine movement time
o Model
 Input: 3 arrays – one for each joint – targets provided in joint space
 Problem when targets overlap in joint space
 Model predisposed to move to left target first
 Target info goes to pre-SMA
o Projects to SMA_MVT and SMA_INH
 SMA_INH prepares upcoming movement – BG inhibits before
appropriate
 WTA determines output – only fires in relation to movement in
preparation
 SMA_MVT receives info from both targets
 inhibition from SMA_INH – only responds to current target
 MC_MVT
 Movement time calculated from firing rate – fit parameters of
equation to data


 44.89 

o mvt _ time   0.363  
 *0.005 
 MC _ firing _ rate 


o the parameters were fit to test subject data
 Terminal acceleration of endpoint – linear with movement time
o termAccel  1750   0.3  mvt _ time / 0.0004
o the parameters were fit to test subject data
o PRE_SMA_VIS
   10ms
 s  25* INPUT
 PRE _ SMA _ VIS  sigmoid u,0, 40,0,50
o SMA_PROPER_INH
   10ms
s  0.6* PRE _ SMA _ VIS  0.2*VLO _ SMAP _ INH 

0.1* SMA _ PROPER _ MVT  smapi _ tonic
SMA _ PROPER _ INH  WTA u,0, 40,0,60
where smapi_tonic is set when a movement begins
 #set to what?#
o SMA_PROPER_MVT
   10ms
s  0.8* PRE _ SMA _ VIS  0.1* SMA _ PROPER _ INH 

0.1*VLO _ SMAP _ MVT


 SMA _ PROPER _ MVT  sigmoid u,10, 40,0,50
o Results


Qualitatively similar to Winstein et al.’s (1997) control data
SNc lesioned to 50% dopamine
 No contact with target, no pause between movements
o Because neural part of model taking less time than arm
 Hypothesis: slowdown in putamen function may cause
slowdown in cortex two
o Changed time constants of SMA and MC to depend on
dopamine level
 MC  sigma _ updown  LIMBIC,0, 20,0.04,0.01

SMA  sigma _ updown  LIMBIC,0, 20,0.04,0.01
o With dopamine depletion – takes longer for neurons to
reach maximum and maximum is less than with
dopamine (bc of longer time constant)
o Reduction in MC firing rates causes delays between
movements
o Caused restricted arm trajectory – lower velocity

o Discussion
 Reduction in SNc -> increase in STN and GPi/GPe -> longer
movement time since MC max was decreased
 Cortical slowdown compensates for reduced BG activity
Ch 8 - The Basal Ganglia Sequencing Model
o Extends SMA module for a sequence of three movements
o Tanji & Shima (1994) – SMA neurons selective for sequence order, others
selective for movement no matter where it was in a sequence
o Tanji & Mushiake (1996) - Pre-SMA active for visual stimuli – indicate
sequence to be performed
o Model
 Added array to pre-SMA selective for different sequence permutations
 Added array to SMA selective for different sequence permutations and
subsequences
 SMA_MVT gets projections from SMA_SEQ (initial movement of
sequence) and SMA_INH
 After the current movement begins, SMA_INH primes SMA_MVT for
the next movement
 MC_MVT needs to reach a threshold firing rate to produce target for
movement generator
 Hardcoded relationships between SMA_MVT and SMA_INH
 PRE_SMA_SEQ
   10ms
 s   pre _ sma _ seq  1* SMA _ PROPER _ MVT  23* SEQ
o #Is –pre_sma_seq a typo? Is it supposed to be –u? This
term is in the diff eq for a leaky integrator anyway – is
it supposed to be repeated in s?#

PRE _ SMA _ SEQ  sigmoid u,0, 40,0,50



SEQ is a 1x6 vector representing the sequence to be performed
o #So each element of the vector represents one of 1-2-3,
1-3-2, 2-1-3, 2-3-1, 3-1-2, or 3-2-1? #
SMA_PROPER_SEQ123
   10ms
s   SMA _ PROPER _ SEQ123  1* PRE _ SMA _ SEQ 
 target3 _ SMA _ prime ^ SMA _ PROPER _ MVT 
target2 _ SMA _ prime ^ SMA _ PROPER _ MVT
o #Again, is the –SMA_PROPER_SEQ123 a typo? Does
the ^ operator mean convolution or power?#
 SMA _ PROPER _ SEQ123  sigmoid u, 20, 40,0,50
SMA_PROPER_SEQ12
   10ms
s   SMA _ PROPER _ SEQ12  0.613* PRE _ SMA _ SEQ123 

0.853* PRE _ SMA _ SEQ312  0.27 * SMA _ PROPER _ SEQ123 
0.056* SMA _ PROPER _ SEQ31 
target1 _ TAR _ prime ^ SMA _ PROPER _ MVT  .max()


o #Is target1_TAR_prime supposed to be
target1_SMA_prime? What about
SMA_PROPER_SEQ31 and PRE_SMA_SEQ312?#
 SMA _ PROPER _ SEQ12  sigmoid u, 20, 40,0,50
#What about SMA_PROPER_SEQ23?#
SMA_PROPER_MVT
   sigma _ updown  LIMBIC,0, 20,0.04,0.008
s = -sma_proper_mvt +


target1_SMA_wts* SMA_PROPER_SEQ123+
target1_SMA_wts* SMA_PROPER_SEQ132+
target2_SMA_wts* SMA_PROPER_SEQ213+
target2_SMA_wts* SMA_PROPER_SEQ231+
target3_SMA_wts* SMA_PROPER_SEQ312+
target3_SMA_wts* SMA_PROPER_SEQ321+
0.1* VLO_SMAP_MVT + smapmgo
o smapmgo=0.713*SMA_PROPER_INH when a
movement starts
 #What is this?#
 SMA _ PROPER _ MVT  sigmoid u,10, 40,0,50
SMA_PROPER_INH

  sigma _ updown  LIMBIC,0, 20,0.04,0.008
s = -sma_proper_inh - 0.2* VLO_SMAP_INH +
target1_SMA_wts* SMA_PROPER_SEQ21+
target1_SMA_wts* SMA_PROPER_SEQ31+

target2_SMA_wts* SMA_PROPER_SEQ12+
target2_SMA_wts* SMA_PROPER_SEQ32+
target3_SMA_wts* SMA_PROPER_SEQ13+
target3_SMA_wts* SMA_PROPER_SEQ23


SMA _ PROPER _ INH  sigmoid u,0, 40,0,60
o Results
 Initialized -> seq123 and seq12 active until target 1 reached
 Seq12 primes target 2 neurons in SMA_PROPER_INH and seq23
 Target 1 reached – seq23 reaches full activation
 Seq23 primes target 3 neurons in SMA_PROPER_INH
 Drop dopamine -> seq123 active longer
 Reason: MC_MVT peaks for each movement lower than for
previous one -> buildup of bradykinesia
o Reason: each movement depended on activation from
previous movement
 Drop dopamine even farther -> MC neurons never reach threshold and
final movement not performed
o Discussion
 Model becomes bradykinetic when dopamine is decreased
 Beginnings of pause between each submovement
 Reduce dopamine to 50% -> only performed 1st movement
 Reduce dopamine -> akinesia, took longer to initiate 1st movement
 Model showed deficits with higher levels of dopamine than
Parkinson’s patients do
 Possibly because dopamine receptors become sensitized when
dopamine is decreased
 Indirect pathway is overactive (inhibits motor programs), direct
pathway is less capable of responding to current motor command
 Slower time constant and higher GPi inhibition -> SMA doesn’t know
status of current motor program so doesn’t command the next
movement
Ch 9 – Synthetic PET
o Synthetic PET
 1) Compute PETA – simulated value of raw PET activity for each
region A of network
 2) Compare activities for two different tasks
o Computing Raw PET Activity


Integrated synaptic activity of a region – integral of absolute value of
connection strength times firing rate of presynaptic neuron over all
synapses in a region
Assumptions
 Synaptic contacts are within the region where cell body is
located
 Inhibitory and excitatory synapses make equal contributions in
blood flow
 All cells in a region can be lumped together
t1

rPETA    wB A t  dt , for region A, B is all regions that project to
t0 B

A, and wB→A(t) is activity (firing rate * synaptic strength) of synapses
from region B to region A at time t, and time interval t0 to t1
corresponds to duration of the scan.
o Creation of the Synthetic PET Scan
rPETA 1  rPETA  2
 PETA 1/ 2
Max rPETA 1 ; rPETA  2
 can differently consider inhibitory and excitatory synapses (not
possible in actual PET)
o Synthetic PET of the Reciprocal Aiming Task
 Normal vs lesioned model
o Synthetic PET of the Sequential Movements Task
 Normal vs. 50% dopamine
Future research
o Temor
 Need TRN
o Additional regions and projections
 Load effects – need somatosensory – feedback to motor cortex giving
position of joints
 Cortical connections to STN – same as the ones projecting to striatum?
 GPR model includes this and says they are the same
 TANs and striosomes