Ilker Yildirim (Yale) | CNCL at Yale

The Gist

Ilker Yildirim from Yale University presents two algorithmic motifs of perception in the mind and brain, focusing on task-performant statistical heuristics and structure-preserving representations to explain how the brain efficiently achieves visual cognition.

Quick Overview

Perception is transformed into cognition through efficient neural algorithms that handle the complex computational challenges of the mind and brain. Ilker Yildirim discusses how task-performant statistical heuristics and structure-preserving representations provide the foundation for visual cognition. Through empirical studies and computational models, the lecture demonstrates how neural networks and dynamical systems account for human-level efficiency and visual processing.

Key Points: Ilker Yildirim is an Assistant Professor of Psychology at Yale University with appointments in the Foundations of Data Science Institute and the Wu Tsai Institute. The lecture explores two primary algorithmic motifs of perception in the mind and brain, connecting raw sensory inputs to higher-level cognition. Task-performant statistical heuristics utilize matched filters and statistical patterns to explain seemingly sophisticated behaviors in biological systems. Structure-preserving representations map external physical and geometric structures into internal neural states to support general-purpose reasoning and planning. Dynamical structure-preserving manifolds combine cognitive science representations with neuroscience dynamical systems to model physical scene prediction. Single-cell recordings in the macaque dorsomedial frontal cortex reveal single-state sufficiency mechanisms that enable rapid trajectory predictions. Multigranular optimization models explain phenomena like inattentional blindness by balancing task-relevant computations against computational costs on the fly. Multilevel computational theories cut across levels of analysis to provide more interpretable and understandable models that predict neural data.