Neuronal correlates of parametric working memory in the prefrontal cortex

Abstract

Humans and monkeys have similar abilities to discriminate the difference in frequency between two mechanical vibrations applied sequentially to the fingertips. A key component of this sensory task is that the second stimulus is compared with the trace left by the first (base) stimulus, which must involve working memory. Where and how is this trace held in the brain? This question was investigated by recording from single neurons in the prefrontal cortex of monkeys while they performed the somatosensory discrimination task. Here we describe neurons in the inferior convexity of the prefrontal cortex whose discharge rates varied, during the delay period between the two stimuli, as a monotonic function of the base stimulus frequency. We describe this as 'monotonic stimulus encoding', and we suggest that the result may generalize: monotonic stimulus encoding may be the basic representation of one-dimensional sensory stimulus quantities in working memory. Thus we predict that other behavioural tasks that require ordinal comparisons between scalar analogue stimuli would give rise to monotonic responses similar to those reported here.

Neural correlates of a postponed decision report

“…2, gray), which correspond to the two possible behavioral choices that the monkeys have. Note also that three comparison frequencies (18,22, and 26 Hz) can be judged as either higher or lower than f1; for these, the monkeys must rely on the stored f1 percept to discriminate consistently (10,19,22).…”

“…This cognitive operation requires that subjects compare information of f1 temporally stored in working memory to the current information of f2 to form a decision of whether f2 Ͼ f1 or f2 Ͻ f1, and to immediately report the outcome by pressing one of two push buttons. We found that the activity of the recorded neurons of several cortical areas encodes f1 in a monotonic firing rate code beginning in the primary somatosensory cortex (5-7), continuing in the secondary somatosensory cortex (5), the ventral premotor cortex (19), the prefrontal cortex (10), and the medial premotor cortex (MPc) (18). Except for the primary somatosensory cortex, these cortical areas encode information of f1 during the delay period between f1 and f2 (5,10,11,(17)(18)(19).…”

“…We found that the activity of the recorded neurons of several cortical areas encodes f1 in a monotonic firing rate code beginning in the primary somatosensory cortex (5-7), continuing in the secondary somatosensory cortex (5), the ventral premotor cortex (19), the prefrontal cortex (10), and the medial premotor cortex (MPc) (18). Except for the primary somatosensory cortex, these cortical areas encode information of f1 during the delay period between f1 and f2 (5,10,11,(17)(18)(19). During presentation of f2, some neurons of all these cortical areas respond to f2, but some other neurons reflect past information of f1, or of the difference between f2 and f1, and generate a differential response consistent with the decision motor report (17)(18)(19).…”

“…medial premotor cortex ͉ monkeys ͉ sensory discrimination ͉ working memory S tudies in behaving monkeys that combine psychophysical and neurophysiological experiments have provided new insights into how a neural representation of a sensory stimulus relates to perception (1)(2)(3)(4)(5)(6)(7)(8), memory (9)(10)(11)(12), and decision making (13)(14)(15)(16)(17)(18)(19). In particular, there has been important progress regarding the neural codes associated with these cognitive functions in the visual and somatic modality (20,21).…”

A parieto-frontal network for visual numerical information in the monkey

“…Then, it is conveyed, directly or indirectly, to the LPFC, where the representation is expanded (in the sense that a greater number of neurons convey numerosity information) and held online (i.e., in working memory) to gain control over thought and action. Indeed, working memory of sensory magnitude is well represented by LPFC neurons; Romo and coworkers (32,33) showed that many neurons fire with a rate that is a monotonic function of the frequency of a tactile stimulus. The aITC, by contrast, seems more involved in visual feature analysis (34); its neurons were more sensitive to the exact appearance of the displays than neurons in the F-IPS or the LPFC.…”