October 2020
Volume 20, Issue 11
Open Access
Vision Sciences Society Annual Meeting Abstract  |   October 2020
Using decoders to understand working memory representations of 3D space in primate prefrontal neuronal ensembles
Author Affiliations & Notes
  • MILAD KHAKI
    UNIVERSITY OF WESTERN (ONTARIO)
  • MEGAN ROUSSY
    UNIVERSITY OF WESTERN (ONTARIO)
  • NASIM MORTAZAVI
    UNIVERSITY OF WESTERN (ONTARIO)
  • ROGELIO LUNA
    UNIVERSITY OF WESTERN (ONTARIO)
  • ADAM SACHS
    UNIVERSITY OF OTTAWA
  • JULIO MARTINEZ-TRUJILLO
    UNIVERSITY OF WESTERN (ONTARIO)
    BRAIN AND MIND INSTITUTE
  • Footnotes
    Acknowledgements  We acknowledge the support of the NSERC and CIHR
Journal of Vision October 2020, Vol.20, 1474. doi:https://doi.org/10.1167/jov.20.11.1474
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      MILAD KHAKI, MEGAN ROUSSY, NASIM MORTAZAVI, ROGELIO LUNA, ADAM SACHS, JULIO MARTINEZ-TRUJILLO; Using decoders to understand working memory representations of 3D space in primate prefrontal neuronal ensembles. Journal of Vision 2020;20(11):1474. doi: https://doi.org/10.1167/jov.20.11.1474.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Neurons in the primate lateral prefrontal cortex (LPFC) encode and maintain 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. Therefore, 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. In this task, a target is presented in one of nine locations in the virtual arena. The target disappears during a two-second delay period, and then the subject is required to navigate to the remembered location using a joystick. Neural recordings were conducted in two male rhesus macaques using two 10×10 Utah arrays located in the LPFC (area 8A), resulting in a total of 3847 neurons. Using a novel high-efficiency classification technique, we decoded the target location on a single trial basis during different trial epochs. This method resulted in high decoding accuracy using a minimum number of neurons containing the greatest amount of target-specific information. Ensembles of 8-12 neurons resulted in 60%-90% decoding accuracy (chance= ~11). Importantly, we were also able to decode trial outcomes (correct or incorrect). Furthermore, to elucidate the underlying mechanism in which neural ensembles encode and maintain target locations in 3D space, we decoded each 3D location based on depth and direction (i.e. front, middle, back, right, center, and left). The results indicate that target direction and depth were retained with similar accuracy by neural ensembles. Moreover, we show that LPFC neurons vary in the amount of information they maintain regarding either depth or direction of a remembered target in 3D space.

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