Speaker
Description
A fundamental question in neuroscience is how a neuron’s specialized responses arise from the synaptic inputs distributed across its dendritic tree. Individual dendrites may function as independent computational subunits, receiving specialized inputs, driving somatic output through active mechanisms, and triggering bursts or plasticity when synaptic input coincides with back-propagating action potentials. These computational properties of cortical neurons have inspired models of sensory and motor processing, learning, and attention. However, directly testing these ideas in vivo has been challenging because available methods for causal dendritic manipulation have lacked sufficient sensitivity and spatial resolution.
In this talk, I will present recent work using novel optical and electrical probes to investigate the role of apical dendrites in sensory processing in visual cortical neurons. Specifically, we tested the hypothesis that apical dendrites convey information about the context surrounding a neuron’s receptive field.
First, I will show how two-photon imaging with the new glutamate sensor iGluSnFR4 enables measurement of the synaptic inputs driving apical dendrites in vivo (Aggarwal et al 2025). Combining this approach with dendritic pruning, we show causally that apical dendrites of visual cortical neurons integrate excitatory inputs from distant regions of visual space and amplify responses to large stimuli, revealing a causal dendritic contribution to the processing of sensory context (Liu et al, 2026).
Second, I will show how high-density Neuropixels probes enable the recording of extracellular signatures of back-propagating action potentials and dendritic spikes from cortical dendrites with high signal-to-noise ratio and temporal resolution (Ye et al, 2025). These unpublished data reveal that visual stimuli differentially engage two modes of somato-dendritic communication, with contextual stimuli strongly recruiting both back-propagation and forward-propagating dendritic electrogenesis.