Phd in PHD PROGRAM IN BEHAVIORAL NEUROSCIENCE

Thesis title: Mixed and flexible temporal dynamic in macaque prefrontal cortex during strategy and associative tasks: contribution of putative pyramidal cells and interneurons

The prefrontal cortex (PFC) plays a key role in several cognitive processes related to goal-directed behavior, including short-term memory, response generation, and mapping associations between stimuli and responses. Several neurophysiological studies have elucidated the involvement of different areas within the PFC in these processes. However, relatively little is known at the microcircuitry level, especially how local cell types composed of interneurons and pyramidal neurons contribute to the coding mechanisms of these processes. A large body of literature has shown that intrinsic firing features and duration metrics of extracellularly recorded waveforms are good predictors of membership in a specific cell type. To fill this gap, we investigated the coding properties of cells recorded in the dorsolateral and dorsomedial macaque prefrontal cortex while performing a strategy task (N= 1306) and two mapping tasks of novel (N= 881) and familiar (N= 552) stimulus-response associations (NovelMap and FamMap). First, we applied an unbiased clustering to classify cells in broad spiking putative pyramidal cells (BS) and narrow spiking putative interneurons (NS), in agreement with the trough-to-peak duration of the cell mean waveforms. We found a more robust ability of interneurons than pyramidal cells to carry information about novel and familiar associations in NovelMap and FamMap during the delay period. We found the same higher selective coding for stimulus and response in the strategi task, where we could dissociate these two signals. Great attention has been given to characterize how cells at the population level interact to represent information over time during the delay period, resulting in an ongoing debate regarding the coding scheme used. Based on this, we investigated how BS and NS populations represented such task-related information over time according to a static or dynamic temporal coding scheme, and we statistically quantified the intensity of the stability of the coding. A direct comparison of the population coding schemes highlighted how a dynamic coding characterizes the NS population compared to the BS population, where the representation was static for both stimulus and response in the strategy task. A direct comparison of coding schemes showed greater stability in the BS population for novel and familiar associations in NovelMap and FamMap and for stimulus and response in the strategy task than in the NS population. The marked reduction in stability in the NS population suggests the presence of a dynamic coding scheme in the NovelMap task. Surprisingly, a direct comparison between NovelMap and FamMap showed a general increase in stability in familiar associations in FamMap, but with differences based on cell type. Such differences involved an earlier rise in stability in FamMap by BS populations and a change in the coding scheme from dynamic to static by NS populations in comparison with the NovelMap task. These findings shed light on the cellular mechanisms underlying the local processing of task-related information.