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Updated: Sep 20, 2026

Double In Utero Electroporation to Target Temporally and Spatially Separated Cell Populations
Published on: June 14, 2020
Reciprocal connections dynamically build consensus between neocortical areas
Mitra Javadzadeh1,2,3, Marine Schimel4,5, Sonja B Hofer6
1Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, UK. javadzadeh@cshl.edu.
Abstract:
The neocortex is organized into specialized areas. Although computations within individual areas have been well studied, it is unclear how these regions function collectively and reconcile potential conflicts to form coherent percepts and decisions. We investigated the joint dynamics of primary (V1) and higher-order lateromedial (LM) visual areas in mice using simultaneous multi-area electrophysiological recordings along with focal optogenetic perturbations to causally manipulate neural activity. We used data-driven nonlinear system identification to construct biologically constrained latent circuit models of both areas. This approach revealed that reciprocal excitatory connections between V1 and LM implement an approximate line attractor in their joint dynamics: this selectively slows the decay of congruent activity patterns while accelerating the decay of inconsistent ones, thereby dynamically achieving inter-area consensus. This mechanism predicts different timescales for consistent versus inconsistent activity patterns across areas, which we verified in our data. These findings, together with our mechanistic theory, identify dynamic consensus building as a general principle of distributed cortical computation.
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