2,290 results found
    1. Computational and Systems Biology
    2. Neuroscience

    Biologically plausible learning in recurrent neural networks reproduces neural dynamics observed during cognitive tasks

    Thomas Miconi
    A biologically plausible learning rule allows recurrent neural networks to learn nontrivial tasks, using only sparse, delayed rewards, and the neural dynamics of trained networks exhibit complex dynamics observed in animal frontal cortices.
    1. Neuroscience

    Reward-based training of recurrent neural networks for cognitive and value-based tasks

    H Francis Song et al.
    A two-part neural network models reward-based training and provides a unified framework in which to study diverse computations that can be compared to electrophysiological recordings from behaving animals.
    1. Neuroscience

    Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network

    Aditya Gilra, Wulfram Gerstner
    Recurrent neuronal networks learn to predict movement in a self-supervised way using biologically plausible learning rules.
    1. Neuroscience

    Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks

    Vishwa Goudar, Dean V Buonomano
    A recurrent network model trained to transcribe temporally scaled spoken digits into handwritten digits proposes that the brain flexibly encodes time-varying stimuli as neural trajectories that can be traversed at different speeds.
    1. Computational and Systems Biology
    2. Neuroscience

    Learning: Neural networks subtract and conquer

    Guillaume Hennequin
    Two theoretical studies reveal how networks of neurons may behave during reward-based learning.
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    1. Computational and Systems Biology
    2. Neuroscience

    Fast and flexible sequence induction in spiking neural networks via rapid excitability changes

    Rich Pang, Adrienne L Fairhall
    Biologically plausible changes in the excitabilities of single neurons may suffice to selectively modulate sequential network dynamics, without modifying of recurrent connectivity.
    1. Cancer Biology

    Diagnostic potential for a serum miRNA neural network for detection of ovarian cancer

    Kevin M Elias et al.
    Application of machine learning to serum miRNA profiles generated through next generation sequencing identifies a biologically relevant miRNA signature which can be deployed as a qPCR test to assist the diagnosis of epithelial ovarian cancer.
    1. Neuroscience

    TrpV1 receptor activation rescues neuronal function and network gamma oscillations from Aβ-induced impairment in mouse hippocampus in vitro

    Hugo Balleza-Tapia et al.
    TrpV1 receptor activation rescues cognition-relevant network dynamics in mouse hippocampus in an acute Alzheimer disease model providing a novel therapeutic target.
    1. Neuroscience

    Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior

    Iris IA Groen et al.
    Deep network features exhibit a robust correlation with brain activity in scene-selective cortex, but are not sufficient to explain human scene categorization behavior, which is strongly shaped by information about the function (possibility for action) of the scene.
    1. Neuroscience

    Structural and functional properties of a probabilistic model of neuronal connectivity in a simple locomotor network

    Andrea Ferrario et al.
    A new probabilistic model of connectivity reveals the structural and functional properties of the neural networks controlling locomotion in many individual tadpoles.

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