Zobrazeno 1 - 10
of 457
pro vyhledávání: '"Abbott, L. F."'
Autor:
Clark, David G., Abbott, L. F.
In neural circuits, synaptic strengths influence neuronal activity by shaping network dynamics, and neuronal activity influences synaptic strengths through activity-dependent plasticity. Motivated by this fact, we study a recurrent-network model in w
Externí odkaz:
http://arxiv.org/abs/2302.08985
Publikováno v:
Phys. Rev. Lett. 131, 118401 (2023)
Neural networks are high-dimensional nonlinear dynamical systems that process information through the coordinated activity of many connected units. Understanding how biological and machine-learning networks function and learn requires knowledge of th
Externí odkaz:
http://arxiv.org/abs/2207.12373
Understanding the asymptotic behavior of gradient-descent training of deep neural networks is essential for revealing inductive biases and improving network performance. We derive the infinite-time training limit of a mathematically tractable class o
Externí odkaz:
http://arxiv.org/abs/2202.02649
Neural circuits exhibit complex activity patterns, both spontaneously and evoked by external stimuli. Information encoding and learning in neural circuits depend on how well time-varying stimuli can control spontaneous network activity. We show that
Externí odkaz:
http://arxiv.org/abs/2201.09916
Backpropagation (BP) uses detailed, unit-specific feedback to train deep neural networks (DNNs) with remarkable success. That biological neural circuits appear to perform credit assignment, but cannot implement BP, implies the existence of other powe
Externí odkaz:
http://arxiv.org/abs/2106.04089
Autor:
Chung, SueYeon, Abbott, L. F.
Publikováno v:
Current Opinion in Neurobiology, Volume 70, October 2021, Pages 137-144
Advances in experimental neuroscience have transformed our ability to explore the structure and function of neural circuits. At the same time, advances in machine learning have unleashed the remarkable computational power of artificial neural network
Externí odkaz:
http://arxiv.org/abs/2104.07059
Brains process information through the collective dynamics of large neural networks. Collective chaos was suggested to underlie the complex ongoing dynamics observed in cerebral cortical circuits and determine the impact and processing of incoming in
Externí odkaz:
http://arxiv.org/abs/2006.02427
Autor:
Ingrosso, Alessandro, Abbott, L. F.
The construction of biologically plausible models of neural circuits is crucial for understanding the computational properties of the nervous system. Constructing functional networks composed of separate excitatory and inhibitory neurons obeying Dale
Externí odkaz:
http://arxiv.org/abs/1812.11424
Ongoing studies have identified similarities between neural representations in biological networks and in deep artificial neural networks. This has led to renewed interest in developing analogies between the backpropagation learning algorithm used to
Externí odkaz:
http://arxiv.org/abs/1812.06488
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