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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