Abstract
Neurons in the primate lateral prefrontal cortex (LPFC) encode and maintain working memory (WM) representations in the absence of external stimuli. Neural computations underlying spatial WM in primates are traditionally studied using highly controlled tasks consisting of simple 2D visual stimuli and require a saccadic response. Hence, there is little known about how populations of LPFC neurons may maintain and transform 3D representations of space for animals to navigate towards remembered object locations. To explore this issue, we created a spatial WM task that takes place in a 3D virtual environment. This task presents a target in one of nine virtual locations. The subject is required to navigate to the remembered location by using a joystick after a two-second delay. Neural recordings were conducted in two male rhesus macaques using two 10×10 Utah arrays located in the LPFC (area 8A), resulting in 3847 neurons. We decoded target location on a single-trial basis using a novel high-efficiency classification technique. The method resulted in high decoding accuracy using a minimum number of neurons containing the highest target-specific information. In ensembles of 8-12 neurons, decoding accuracy ranged from 60%-90% (chance = ~11). We determined how neural ensembles encode and maintain information about target locations in three-dimensional space during each trial. Our results demonstrate that ensembles of 2-15 neurons in a group represent each of the nine selected targets that exist during the trial. Ensembles remain consistent over multiple trials of each session, and the specific target of each trial is decoded with 40% to 60% accuracy over chance. These results indicate that in addition to the information encoded in single-neuron activity, temporal dynamics of groups of neurons consistently interacting with each other is also informative and can be used for decoding.