Challenging the point neuron dogma: FS basket cells as 2-stage nonlinear integrators
Alexandra TzilivakiiD, George KastellakisiD, Panayiota PoiraziiD
Abstract
Interneurons are critical for the proper functioning of neural circuits and are typically considered to act as linear point neurons. However, exciting new findings reveal complex, sub- and/or supralinear computations in the dendrites of various interneuron types. These findings challenge the point neuron dogma and call for a new theory of interneuron arithmetic. Using detailed, biophysically constrained models, we predict that dendrites of FS basket cells in both the hippocampus and mPFC come in two flavors: supralinear, supporting local sodium spikes within large-volume branches and sublinear, in small-volume branches. Synaptic activation of varying sets of these dendrites leads to somatic firing variability that cannot be explained by the point neuron reduction. Instead, a 2-stage Artificial Neural Network (ANN), with both sub- and supralinear hidden nodes, captures the variance. We propose that FS basket cells have substantially expanded computational capabilities sub-served by their non-linear dendrites and act as a 2-layer ANN.
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