Cognitive motor control: Spatial and temporal aspects

Current Opinion in Neurobiology

Volumn 12, Issue 6, 2002, Pages 678-683

  Georgopoulos, Apostolos P ^a,b  

^a VETERANS AFFAIRS MEDICAL CENTER   (United States)

^b UNIVERSITY OF MINNESOTA MEDICAL SCHOOL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BEHAVIOR; BRAIN NERVE CELL; BRAIN REGION; CENTRAL NERVOUS SYSTEM; COGNITION; HUMAN; MEMORY; MOTOR CONTROL; MOTOR CORTEX; MOTOR PERFORMANCE; NONHUMAN; PRIORITY JOURNAL; REVIEW; SIGNAL TRANSDUCTION; TASK PERFORMANCE; TEMPORAL CORTEX;

EID: 0036901187     PISSN: 09594388     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0959-4388(02)00382-3     Document Type: Review

References (27)

1. Zhang K., Ginzburg I., McNaughton B.L., Sejnowski T.J. Interpreting neuronal population activity by reconstruction: unified framework with application to hippocampal place cells. J Neurophysiol. 79:1998;1017-1044.
2. Georgopoulos A.P., Pellizzer G., Poliakov A.V., Schieber M.H. Neural coding of finger and wrist movements. J Comput Neurosci. 6:1999;279-288.
3. Schwartz A.B., Moran D.W. Motor cortical activity during drawing movements: population representation during lemniscate drawing. J Neurophysiol. 82:1999;2705-2718.
4. Steinberg O., Donchin O., Gribova A., Cardosa de Oliveira S., Bergman H., Vaadia E. Neuronal populations in primary motor cortex encode bimanual arm movements. Eur J Neurosci. 15:2002;1371-1380. A highly original application of the population vector analysis to bimanual movements. The strength of the work derives from the powerful experimental design - which combined both excellent controls and an ecologically common and meaningful paradigm - as well as from the rigorous analyses.
5. Lewis J.E., Kristan W.B. Jr. A neuronal network for computing population vectors in the leech. Nature. 391:1998;18-19.
6. Levi R., Camhi J.M. Population vector coding by the giant interneurons of the cockroach. J Neurosci. 20:2000;3822-3829. A very important study that tested the population vector method against a plausible alternative hypothesis. The strength of this work derives from the fact that the neural inputs to the giant interneurons could be precisely manipulated; therefore, the two competing hypotheses could be tested in a controlled fashion.
7. Kruse W., Dannenberg S., Kleiser R., Hoffmann K.P. Temporal relation of population vector activity in visual areas MT/MST and in primary motor cortex during visually guided tracking movements. Cereb Cortex. 12:2002;466-476. A meticulous study that demonstrates, for the first time, the reconstruction of a moving stimulus (in temporal cortex) and the accompanying hand movement (in the motor cortex) using the time-varying population vector.
8. Page W.K., Duffy C.J. MST neuronal responses to heading direction during pursuit eye movements. J Neurophysiol. 81:1999;596-610.
9. Eggermot J.J., Mossop J.E. Azimuth coding in primary auditory cortex of the cat. I. Spike synchrony versus spike count representations. J Neurophysiol. 80:1998;2133-2150.
10. Scott S.H., Gribble P.L., Graham K.M., Cabel W. Dissociation between hand motion and population vectors from neural activity in motor cortex. Nature. 413:2001;161-165. An example of inappropriate analytical design leading to misleading results. The authors claim that the population vector did not predict the direction of movement. Curiously, tuning curves and population vectors were calculated using discharge rates from the onset of the target until the end of the movement, but the population vectors were compared to 'directions of movement' that were calculated from the onset of movement to its peak velocity. This is inappropriate, as the time intervals of the inputs (i.e. reaction time plus movement time) and the outputs (just the accelerating part of the initial movement) are incongruent. As many movements were curved, impure inputs have produced confusing outputs. These problems were further complicated by the fact that estimated inputs for 16 directions were used whereas only eight directions were tested. Eight points are insufficient to estimate accurately intermediate points for an intensely curved tuning function. In addition, the exact method for calculating the population vector, a crucial point, was not stated.
11. Lee D.N. A theory of visual control of braking based on information about time-to-collision. Perception. 5:1976;437-459.
12. Lee D.N. Guiding movements by coupling taus. Ecol Psychol. 10:1998;221-250.
13. Lee D.N., Craig C.M., Grealy M.A. Sensory and intrinsic coordination of movement. Proc R Soc Lond Ser B. 266:1999;2029-2035.
14. Flash T., Sejnowski T.J. Computational approaches to motor control. Curr Opin Neurobiol. 11:2001;655-662.
15. Vindras P., Viviani P. Frames of reference and control parameters in visuomanual pointing. J Exp Psychol Hum Percept Perform. 24:1998;569-591.
16. Johnson M.T.V., Mason C.R., Ebner T.J. Central processes for the multiparametric control of arm movements in primates. Curr Opin Neurobiol. 11:2001;684-688. A clear exposition of the case for single cells in CNS structures being involved in processing multiple movement parameters.
17. Reina G.A., Moran D.W., Schwartz A.B. On the relationship between joint angular velocity and motor cortical discharge during reaching. J Neurophysiol. 85:2001;2576-2589. A long overdue and rigorous analysis of the dynamic relations between hand and joint spaces in arm movements.
18. Krakauer J.W., Ghilardi M.-F., Ghez C. Independent learning of internal model for kinematic and dynamic control of reaching. Nat Neurosci. 2:1999;1026-1031.
19. Goldenberg G. Matching and imitation of hand and finger postures in patients with damage in the left or right hemisphere. Neuropsychologia. 37:1999;559-566.
20. Buxbaum L.J., Giovannetti T., Libon D. The role of the dynamic body schema in praxis: evidence from primary progressive apraxia. Brain Cogn. 44:2000;166-191.
21. Gallese V., Fadiga L., Fogassi L., Rizzolatti G. Action recognition in the premotor cortex. Brain. 119:1996;593-609.
22. Buccino G., Binkowski F., Fink G.R., Fadiga L., Fogassi L., Gallese V., Seitz R.J., Zilles K., Rizzolatti G., Freund H.J. Action observation activates premotor and parietal areas in a somatotopic manner: an fMRI study. Eur J Neurocsi. 13:2001;400-404.
23. Goldenberg G., Strauss S. Body-part specificity of imitation disturbances following left and right brain damage. Neurology. 59:2002;893-897. An important addition to the literature on posture imitation. The authors added foot postures to the examination and analysed possible somatotopic representations of specific body parts within the context of imitation. The study derives additional importance from the localisation of the lesion and the bearing that this has on possible explanations of the imitation deficit (see text).
24. Huttenlocher J., Hedges L.V., Duncan S. Categories and particulars: prototype effects in estimating spatial location. Psychol Rev. 98:1991;352-376.
25. Gourtzelidis P., Smyrnis N., Evdokimidis I., Balogh A. Systematic errors of planar arm movements provide evidence for space categorisation and interaction of multiple frames of reference. Exp Brain Res. 139:2001;59-69. A meticulous and methodical investigation of various kinds of systematic errors that occur during movements from memory. An important finding was that new bias can be induced using proper stimuli. This provides a handle for future, ad hoc controlled experiments.
26. Sandberg E.H., Huttenlocher J., Newcombe N. The development of hierarchical representation of two-dimensional space. Child Dev. 67:1996;721-739.
27. Laeng B., Peters M., McCabe B. Memory for locations within regions: spatial biases and visual hemifield differences. Mem Cognit. 26:1998;97-107.