Articles

Title: Νeuronal population codes for cognition

Summary:

Recent technological advances in high-density multi-electrode arrays have driven a paradigm shift in systems neuroscience, moving our focus from single-neuron properties to the coordinated activity of large neuronal populations. Within this population-level framework, information is encoded in complex, distributed patterns of activity that require appropriate computational tools to interpret. Parallel to this shift, the brain is increasingly conceptualized as a complex, dynamic, and non-linear system, where neurological and cognitive disorders can be viewed as disruptions in network dynamics. Recurrent Neural Networks (RNNs) have emerged as an excellent computational framework for modeling these dynamical systems, serving as powerful models of higher-order cortical regions, such as the prefrontal cortex. In this talk, I will present experiments that employ simultaneous extracellular recordings across multiple brain regions. I will describe how neuronal population codes can be characterized during cognitive tasks and illustrate how RNNs can be employed to better understand the dynamical regimes of neuronal populations.

Short Bio:

Panos Sapountzis is an Assistant Professor of Physiology and Neurophysiology at the School of Medicine, University of Crete. He holds a BSc from the department of Applied Mathematics from the University of Crete and a PhD in Neuroscience from the University of Nottingham. His research investigates the neural circuit mechanisms underlying cognitive functions, such as visual attention and working memory. To explore these mechanisms, he conducts multi-area, electrophysiological extracellular recordings in behaving non-human primates paired with computational methods to characterize how cognitive functions are implemented at the level of neural populations and brain-wide networks.

Time, Date & Location: 15:00, July 16, 2026, Fotakis Room, FORTH Campus