Probabilistic computation in dendritic trees

Dendritic trees possess a plethora of voltage-dependent conductances that render them sophisticated computational devices well beyond the realm of traditional cable theory. Previous functional approaches to active dendritic processing were limited because they studied dendritic computations at the single neuron-level, or, at best, in purely feed-forward neural networks. However, many computations in the nervous system, especially those underlying learning and memory, are carried out by the dynamics of recurrently-coupled neural circuits, and thus it becomes pressing to identify the computational benefits active dendritic trees bring to such network-level computations.


This is a collaborative project between Balázs Ujfalussy (Budapest CNS Group) and Máté Lengyel (University of Cambridge).


B. Ujfalussy, T Kiss, P. Érdi: Parallel Computational Subunits in Dentate Granule Cells Generate Multiple Place Fields PLoS Comput Biol (2009) 5(9):e1000500.