J. Zhang et al., ANALYZING NEURONAL PROCESSING LOCUS IN STIMULUS-RESPONSE ASSOCIATION TASKS, Journal of mathematical psychology, 41(3), 1997, pp. 219-236
Citations number
24
Categorie Soggetti
Psychologym Experimental","Social Sciences, Mathematical Methods","Mathematical, Methods, Social Sciences","Mathematics, Miscellaneous
If a neuron is being recorded while a trained animal performs a 2 x 2
stimulus-response association task, how can we decide whether it is re
lated more to the encoding and analysis of the sensory stimulus, to th
e preparation and execution of the motor response, or to the animal's
decision that associates the two? The difficulty arises because, withi
n a single task, stimulus and response are intrinsically confounded pe
r task instruction; it is only through proper analysis of errors in pe
rformance (behavioral noise) and variance in recorded neural activity
(neuronal noise) that one can identify the sensorimotor significance o
f such activity. A quantitative technique is proposed here, based on t
he framework of signal detection theory, to determine the sensorimotor
''locus'' of a neural process when recorded simultaneously with the a
nimal's performance on a trial-by-trial basis. The premise is that a p
ure sensory process should be influenced only by the nature of the sen
sory stimulus regardless of the nature of the behavioral response, and
vice versa for a pure motor process. From the recorded neural activit
y, we calculate the prediction or discriminability ( by an ideal opera
tor) for the stimulus categories a nd for the response categories. The
se discriminability values are then compared with each other to infer
whether the neural process is more related to stimulus or to response.
An index is derived that quantitatively specifies the processing locu
s of a given neural process along the sensorimotor continuum, with pur
e sensory and pure motor processes at the two extremes. In between lie
s the locus of decision-related processes whose activities allow equal
(but not chance) prediction for stimulus and response categories. The
technique is applied to single-unit activities recorded in monkey pri
mary motor cortex (MI) while the monkey performed a simple go/nogo tas
k involving visual stimulus and hand/wrist movement. We find that sens
orimotor indices of MI neurons are widely distributed, with a preponde
rance of motor-related units (that better predict go/nogo response tha
n go/nogo stimulus) but also sensory-related ones (with predictabiliti
es reversed). (C) 1997 Academic Press.