358 citations · 885 across the 15 of their papers we have counts for
7 papers · 1 filter
Replay in Deep Learning: Current Approaches and Missing Biological Elements
Tyler L. Hayes, Giri P. Krishnan, Maxim Bazhenov +3
Replay is the reactivation of one or more neural patterns, which are similar to the activation patterns experienced during past waking experiences. Replay was first observed in bio…
The Unreasonable Effectiveness of Deep Learning in Artificial Intelligence
Terrence J. Sejnowski
Deep learning networks have been trained to recognize speech, caption photographs and translate text between languages at high levels of performance. Although applications of deep…
Differential covariance: A new method to estimate functional connectivity in fMRI
Tiger w. Lin, Giri P. Krishnan, Maxim Bazhenov +1
Measuring functional connectivity from fMRI is important in understanding processing in cortical networks. However, because brain's connection pattern is complex, currently used me…
Gradient Descent for Spiking Neural Networks
Dongsung Huh, Terrence J. Sejnowski
Much of studies on neural computation are based on network models of static neurons that produce analog output, despite the fact that information processing in the brain is predomi…
Differential Covariance: A New Class of Methods to Estimate Sparse Connectivity from Neural Recordings
Tiger W. Lin, Anup Das, Giri P. Krishnan +2
With our ability to record more neurons simultaneously, making sense of these data is a challenge. Functional connectivity is one popular way to study the relationship between mult…
The effect of neural adaptation of population coding accuracy
J. M. Cortes, D. Marinazzo, P. Series +3
Most neurons in the primary visual cortex initially respond vigorously when a preferred stimulus is presented, but adapt as stimulation continues. The functional consequences of ad…