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Abstract: Computational modelling of cognitive processes has largely focused on cortical areas, but recent studies suggest that multiple subcortical areas contribute to different cognitive computations. To make progress in our understanding of how neural dynamics relate to behaviour, theoretical frameworks are needed to clarify why and how subcortical structures are engaged during cognitive tasks, as well as to guide and interpret future experimental studies on subcortical-cortical interactions.
In the first part of my talk, I will present a computational framework that introduces the concept of ‘dynamical modes’: population-level neural activity patterns in the cortex that can be interpreted as basic cognitive building blocks. I then consider the pulvinar, the largest part of the visual thalamus that is reciprocally connected to multiple visual and association cortical areas. I put forward a framework of pulvino-cortical interactions based on computations on (cortical) dynamical modes to clarify the pulvinar’s involvement in attention, confidence, and communication. Next, I present a circuit model of subcortical-cortical interactions during motor planning, constrained by multisite recordings in the mouse. I propose that subcortical inputs to the thalamus selectively gate dynamical modes relevant for movement planning and execution. Finally, I discuss the generation and control of spindles in the thalamocortical network, a hallmark oscillation during sleep that is thought to be crucial for the consolidation of episodic memories. Overall, the modelling results support the existence of computational principles for large-scale subcortical-cortical interactions in the brain that will prove useful in the present era of large-scale data collection and analysis.
Bio: Dr. Jaramillo is a Group Leader at the Campus Institute for the Dynamics of Biological Networks in Göttingen, Germany. Before this, he was a Postdoctoral Associate in the lab of Prof. Xiao-Jing Wang at the New York University Center for Neural Science (2015-2020) where he proposed influential models of thalamocortical contributions to working memory, decision making and confidence. He received a PhD in Computational Neuroscience in Berlin, Germany under the supervision of Prof. Richard Kempter (2014). He converged onto Computational Neuroscience after majoring in Electronics Engineering (Universidad Pontificia Bolivariana Medellin, Colombia) and obtaining a joint Erasmus Mundus master in Applied Physics and Nanotechnology (Delft University of Technology: Delft, The Netherlands and Chalmers University of Technology, Gothenburg, Sweden).