Dendritic computation

Columbia’s NeuroTechnology Center brings together cellular, systems and computational neuroscientists to examine dendritic computation, cortical circuitry, neuronal cell types and emerging neurotechnologies. The programme connects synaptic physiology and dendritic integration with neuronal morphology, cortical microcircuits, transcriptomics and methods for studying the mammalian brain. Speakers are Peter Jonas, Gábor Tamás, Idan Segev, Henrike Planert, Lida Kanari and Jonathan Ting, with two panel discussions. The online symposium takes place on 10 December 2026, 11:00–16:00 EST (America/New_

…potentials which are critical to computation and plasticity. Therefore, the ability to image voltage across an entire dendritic tree would represent a major advance in systems neuroscience. Recent advances in genetically encoded voltage indicators (GEVIs) have brought this possibility closer to reality. However, due to the fundamental tradeoff between imaging speed and volume, it has been impossible thus far to image an entire dendritic tree using volumetric imaging at high speeds. To get aro

Predictions about sensory inputs (e.g. contextual signals from associative cortical areas to sensory areas) arrive primarily in the superficial layers of the cortical sheet, where they are received by the distal apical dendrites of pyramidal neurons. These distal apical dendrites are long tree-like extensions which are electro- tonically segregated from the cell body under passive propagation of membrane potential. At the same time, incoming sensory inputs primarily target the region closest to the cell body. The relative coupling of activity between these neuronal regions (i.e. simultaneous v

Panayiota Poirazi discusses dendritic computation and why artificial networks may benefit from richer neuron models. The conversation examines how dendrites contribute to learning and memory, the relationship between biological detail and useful abstraction, and the potential of dendritic mechanisms to improve artificial intelligence.

…spatial scale for understanding dendritic computation? We have developed a method to construct compartmental models at any level of spatial complexity. Through carefully chosen parameter fits, solvable in the least-squares sense, we obtain accurate reduced co