Search

What are you looking for?

  1. Probing Biological and Artificial Neural Networks with Task-dependent Neural Manifolds

    Publication
    In recent years, growth in our understanding of the computations performed in both biological and artificial neural networks has largely been driven by either low-level mechanistic studies …

  2. Optimal Quadratic Binding for Relational Reasoning in Vector Symbolic Neural Architectures

    Publication

  3. Minimum perturbation theory of deep perceptual learning

    Publication

  4. Associative memory of structured knowledge

    Publication

  5. Optimal Quadratic Binding for Relational Reasoning in Vector Symbolic Neural Architectures

    Publication

  6. Neural representational geometry underlies few-shot concept learning

    Publication

  7. Stochastic consolidation of lifelong memory

    Publication
    Humans have the remarkable ability to continually store new memories, while maintaining old memories for a lifetime. How the brain avoids catastrophic forgetting of memories due to interference …

  8. The spectrum of covariance matrices of randomly connected recurrent neuronal networks with linear dynamics

    Publication
    A key question in theoretical neuroscience is the relation between the connectivity structure and the collective dynamics of a network of neurons. Here we study the connectivity-dynamics …

  9. Locally ordered representation of 3D space in the entorhinal cortex

    Publication
    As animals navigate on a two-dimensional surface, neurons in the medial entorhinal cortex (MEC) known as grid cells are activated when the animal passes through multiple locations …

  10. New role for circuit expansion for learning in neural networks

    Publication
    Many sensory pathways in the brain include sparsely active populations of neurons downstream from the input stimuli. The biological purpose of this expanded structure is unclear, but it …

  11. Young adult-born neurons improve odor coding by mitral cells

    Publication
    New neurons are continuously generated in the adult brain through a process called adult neurogenesis. This form of plasticity has been correlated with numerous behavioral and cognitive phenomena …

  12. High-dimensional dynamics of generalization error in neural networks

    Publication
    We perform an analysis of the average generalization dynamics of large neural networks trained using gradient descent. We study the practically-relevant "high-dimensional" regime where the number …

  13. Separability and geometry of object manifolds in deep neural networks.

    Publication
    Stimuli are represented in the brain by the collective population responses of sensory neurons, and an object presented under varying conditions gives rise to a collection of neural …

  14. Neural Correlates of Learning Pure Tones or Natural Sounds in the Auditory Cortex.

    Publication
    Associative learning of pure tones is known to cause tonotopic map expansion in the auditory cortex (ACx), but the function this plasticity sub-serves is unclear. We developed …

  15. Functional diversity among sensory neurons from efficient coding principles.

    Publication
    In many sensory systems the neural signal is coded by the coordinated response of heterogeneous populations of neurons. What computational benefit does this diversity confer on information processing …

  16. Coherent chaos in a recurrent neural network with structured connectivity.

    Publication
    … these results are not finite-size effects. Finally, we show that in the regime of weak structured connectivity, coherent chaos emerges also for a generalized structured connectivity …

  17. Brain-wide Organization of Neuronal Activity and Convergent Sensorimotor Transformations in Larval Zebrafish.

    Publication
    Simultaneous recordings of large populations of neurons in behaving animals allow detailed observation of high-dimensional, complex brain activity. However, experimental approaches often focus on singular behavioral paradigms …

  18. Learning Data Manifolds with a Cutting Plane Method.

    Publication
    We consider the problem of classifying data manifolds where each manifold represents invariances that are parameterized by continuous degrees of freedom. Conventional data augmentation methods rely on sampling …

  19. Balanced excitation and inhibition are required for high-capacity, noise-robust neuronal selectivity.

    Publication
    Neurons and networks in the cerebral cortex must operate reliably despite multiple sources of noise. To evaluate the impact of both input and output noise, we determine the …

  20. The Impact of Structural Heterogeneity on Excitation-Inhibition Balance in Cortical Networks

    Publication
    Models of cortical dynamics often assume a homogeneous connectivity structure. However, we show that heterogeneous input connectivity can prevent the dynamic balance between excitation and inhibition, a hallmark …

  21. From Whole-Brain Data to Functional Circuit Models: The Zebrafish Optomotor Response

    Publication
    Detailed descriptions of brain-scale sensorimotor circuits underlying vertebrate behavior remain elusive. Recent advances in zebrafish neuroscience offer new opportunities to dissect such circuits via whole-brain imaging …