Binding by synchrony
By Wolf Singer. 2007
85 citations recorded by the source corpus.
where gmin and gmax are the maximum and minimum inhibition, respectively, and T is the inhibition’s period. Similar to the phase-response curve in Lab 4, the timing of a suprathreshold excitatory input determines when spikes occur. If we excite the neuron with a current pulse of width T at phase θIN (from θIN to θIN +T ), the neuron spikes as soon as g(t) is less than a threshold level of inhibition, g0. If we vary θIN between 0 and T , determine the phase at which the neuron will spike, θOUT, for g0 set to just below gmax, just above gmin, and half way between. Sketch θOUT versus θIN for the three cases.
Subfields: Cognitive Neuroscience
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In Cognitive Neuroscience
- J. Urgen Schmidhuber
- Sjoerd van Steenkiste
- Klaus Greff
- David P. Reichert
- Thomas Serre
- Yann LeCun
- Tomaso A. Poggio
- Sungjin Ahn
Citations in the corpus
- On the Binding Problem in Artificial Neural Networks (2020, background): “In particular, its highly distributed nature raises the question of “[. . . ] how the computations occurring simultaneously in spatially segregated processing areas are coordinated and bound together to give rise to coherent percepts and actions” — Singer (2007).”
- Neuronal Synchrony in Complex-Valued Deep Networks (2013, background): “Binding by synchrony theories (Singer, 2007) postulate that neurons in the brain dynamically form synchronous assemblies to signal where distributed representations together correspond to coherent sensory entities.”