*Corresponding author.

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Neurocomputing 38}40 (2001) 1181}1184

How much do they tell us to move?

Valeria Del Prete��*, Orna Steinberg�, Alessandro Treves�, Eilon Vaadia��SISSA, Cognitive Neuroscience, Trieste, Italy

�Hadassah Medical School and Center for Neural Computation, The Hebrew University of Jerusalem, Israel

Abstract

A previous study revealed that neuronal activity in primary motor cortex (MI) and supple-mentary motor area (SMA) of the monkey depends both on which arm(s) moved and on thedirection of movement. At the level of single cells, no di!erences were found between the areasin the information conveyed about each correlate. We constructed pseudosimultaneous re-sponse vectors and applied a decoding algorithm to quantify di!erences at a population level.We found that, on average, samples of 20 MI units carried less information about bothmovement type and direction than SMA units in a time window of 500 ms across the movementonset; a more detailed temporal analysis has revealed that SMA precedesM1 in motor planningand execution and that along the trial M1 cells carry as much information about direction asSMA cells. � 2001 Elsevier Science B.V. All rights reserved.

Keywords: Neural coding; Moto cortex; Information theory

The precise roles of di!erent motor areas in planning and executing complex taskshas not been clari"ed yet. Recent studies performed both on humans and on monkeyshave shown that the supplementary motor area is involved in tasks requiring bi-manual coordination [2,4]. This conclusion has been supported by the analysis ofactivity recorded extracellularly both in the primary motor cortex (M1) and in thesupplementary motor area (SMA) [1]. Here we apply information theoretic measuresto extensive neuronal recordings from a behaving monkey, to explore subtler quantit-ative di!erences between the two areas. The monkey was trained to movea manipulandum either with the left arm or with the right one, or with both in thesame direction, or with both in opposite directions. There were thus a total of fourmovement &types', and each could be carried out in eight possible directions, yielding

0925-2312/01/$ - see front matter � 2001 Elsevier Science B.V. All rights reserved.PII: S 0 9 2 5 - 2 3 1 2 ( 0 1 ) 0 0 5 5 8 - 6

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Fig. 1. Information about dir vs type in M1 and SMA single cells.

32 di!erent correlates of the neural activity. Eighty-seven and 103 cells were recorded,respectively, in the right M1 and in the right SMA areas. The activity was quanti"edby the number of spikes emitted in a given time window along the trial, and expressedas the "ring rate r�

�of unit i in trial k. Trials (10}20) were typically recorded for each

cell and each correlate. Experimental procedures are described in detail elsewhere [1].First, we evaluated the mutual information I(s, r) at a single neuron level, to extractthe amount of information each cell carried, separately, about either movement typeor direction.

I"

�����

P(s)�drP(r�s) log��P(r�s)P(r) �. (1)

In Eq. (1) p"4 in the case of the information about type and p"8 in the case of theinformation about the direction. In this "rst analysis the spikes were counted from100 ms before the movement onset up to 400 ms after the movement onset. The resultsare shown in Fig. 1; the scatterplot reveals a very broad distribution of selectivities,with many cells conveying limited amounts of information about either type ordirection, of the order of 0.1}0.3 bits and very few conveying much information aboutboth type and direction. No clustering into cell classes (e.g. a &direction selective' class)could be detected, nor any signi"cant di!erence between MI and SMA.Population analysis was carried out constructing pseudosimultaneous response

vectors r�, and applying a decoding algorithm to extract from each such responsevector a prediction of the movement s (either type or direction) it correlated with. Itshould be noted that the use of pseudosimultaneous response vectors is tantamount tothe assumption of a trial-to-trial variability (the &noise') independent from cell to cell.Other experiments have indicated that the results are not substantially di!erent fromthose obtained with genuine simultaneous recordings, but this of course should be

1182 V. Del Prete et al. / Neurocomputing 38}40 (2001) 1181}1184

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Fig. 2. Info in M1 and SMA right cells for a time window of 500 ms (on the left) and for di!erent timewindows (on the right, curve for 20 cells).

con"rmed in the present system. In addition, the construction of the vectors requiresthe arti"cial replication of some of the trials for cells which do not have enough trialswith some correlate. This can be minimized if only cells with enough trials on averageare included in the population. We checked that our results were not in#uenced byany residual replication, by varying the number of pseudosimultaneous trials used. Allsuch analytical procedures are described elsewhere, e.g. in [3]. Of the total number ofcells, we considered for the population analysis 65 MI cells and 71 SMA cells; theseunits had at least 16 trials available for each movement direction and for eachmovement type and a mean "ring rate higher than 1 Hz. Cells with an average "ringrate lower than 1 Hz across the 500 ms were discarded because their low level ofactivity made them liable to distort the decoding procedure. For each of the twopopulations many random subsamples of N"1,2,20 cells were fed into the decod-ing and information extraction program. Fig. 2 on the left shows the results for the fulltime window of 500 ms across movement onset. Quantitative di!erences emerge in thecoding of both direction and type. MI cells carry 70}80% of the information aboutboth type and direction carried by equal samples of SMA cells. Then we consideredshorter time windows along the trial, to investigate whether a more detailed temporalanalysis could dissect subtler di!erences between the two areas. Fig. 2 on the rightshows the information carried on average by samples of 20 cells in either area fordi!erent time windows. We checked that the relative position of the points in the plotwould not change if smaller subsamples of cells were considered, across all possiblesizes up to 20 units; this legitimates an extension of the results to a generic populationof neurons in either area. Some observations emerge from the analysis of the curvesplotted in Fig. 2 on the right, which can help to clarify some di!erences between thetwo areas, speci"cally:

� the information about type is constantly higher in SMA than in M1, while theinformation about direction results roughly the same in M1 and in SMA along thetrial up to 350 ms in the post-movement phase.

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� the information time course is very similar in SMA area both for type and direction,with the highest peak at the movement onset, earlier than it is found forM1 area. InM1 the type and the direction of the movement correspond to di!erent pro"les: thepeak in information about the direction precedes the one about the type of themovement, reaching the maximum at 150 ms after the movement onset, while theinformation about the type seems to be still rising at 250 ms. Moreover, thesupplementary motor area seems the "rst one involved in the preparation of themotor reaction, independently of the property (type or direction) considered,con"rming the intuitive notion of a top-down hierarchy for motor planningincluding in order the pre-frontal, the supplementary motor and the primary motorcortices. Yet information about direction seems to be faster in reaching the primarymotor cortex than information about the type.

As a whole these results suggest that information about di!erent properties in a motoraction is received and transmitted by SMA to lower stages of processing with verysimilar time courses, while the same properties seem to be coded more sequentiallythan simultaneously in M1. The reason underlying this delay in the transmission ofthe information about type between SMA and M1 would be an interesting object offurther investigations.

We have presented a study addressed to clarify the roles of the supplementarymotor area and of the primary motor cortex in coding the type and the direction ina complex task. We have found that along the trial the type is coded in SMA areamore than in M1 area and the direction is coded roughly equally by the two areas. Asa whole our results suggest that the supplementary motor area codes the type morethan the primary motor cortex and that it precedes M1 in planning and execution ofa complex motor action. All analyzed cells were recorded in the right hemisphere.A comparative analysis of activity recorded in the left M1 and SMA areas mightclarify whether these di!erences in the coding are speci"c to the right hemisphere orwhether they extend to the left motor areas.

References

[1] O. Donchin, A. Gribova, O. Steinberg, H. Bergman, E. Vaadia, Primary motor cortex is involved inbimanual coordination, Nature 395 (6699) (1998) 274}278.

[2] W. Lang, M. Lang, F. Uhl, C. Koska, A. Kornhuber, L. Deecke, Exp. Br. Res. 71 (1988) 579}587.[3] E.T. Rolls, A. Treves, M.J. Tovee, The representational capacity of the distributed encoding of

information provided by populations of neurons in primate temporal visual cortex, Exp. Br. Res. 114(1997) 149}162.

[4] P. Viviani, D. Perani, F. Grassi, V. Bettinardi, F. Fazio, Hemispheric asymmetries and bimanualasynchrony in left- and right-handers, Exp. Br. Res. 120 (1998) 531}536.

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