Theoretical Neuroscience Podcast On models of the mind - with Grace Lindsay - #1
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Oct 13, 2023 Grace Lindsay, author of 'Models of the Mind', discusses the history of electricity in neuroscience, limitations of pen and paper calculations, failed neuroscience papers, origins of AI and the perceptron, neural coding and information processing, hierarchy of feature extractors in the visual system, firing rate models and ring networks, different types of models in computational neuroscience, reinforcement learning, and challenges in theoretical neuroscience.
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Hubel And Wiesel Revealed Orientation Tuning In V1
- Hubel and Wiesel found V1 neurons tuned to oriented edges, supporting a hierarchical build-up from LGN point detectors to orientation-selective cells.
- Simple cells respond to specific positions; complex cells pool nearby simple cells for spatial invariance.
Rate Models Explain Head Direction Ring Attractors
- Continuous firing-rate models simplify neurons to rates, enabling dynamical-systems analysis and elegant explanations like ring attractors for head direction.
- Ring networks use spatially structured recurrent connectivity to store directional memory as an attractor state.
Hebb's Rule Gives Local Associative Plasticity
- Hebbian learning ('neurons that fire together wire together') provides a local associational rule that can strengthen pathways without explicit reward.
- The basic form lacks external feedback and thus differs from reinforcement mechanisms that use reward prediction errors.