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Gifford, B.

Publications and source records attributed to Gifford, B..

2 recordsLinked to original sources

Critical scaling of cortical ensembles without cooperative amplification

Cortical neurons are sparsely and weakly connected, motivating the long-standing idea that they must act collectively, as cell assemblies, to exert substantial influence on surrounding networks. Yet a few spikes in a single pyramidal neuron can recruit thousands of cortical neurons according to a power law with exponent ~0.285, consistent with a two-dimensional system near a critical percolation transition. Here we holographically stimulated ensembles of 1 to 16 layer 2/3 pyramidal neurons in visual cortex of awake mice while imaging hundreds of neighbouring neurons. Across two orders of magnitude in evoked spike count, network responses followed the same scaling law observed for single-neuron perturbations, with no detectable threshold at which co-activation produced additional amplification. Recruitment was sublinear, suppression increased with ensemble size, and ongoing scale-free avalanche dynamics remained stationary. Nevertheless, ensemble identity became increasingly decodable from surrounding activity. Thus, coordinated firing increases representational specificity without escaping the critical dynamics governing propagation: cortical ensembles convey identity without gaining disproportionate causal impact.

neuroscience↗

Critical Scaling of Novelty in the Cortex

The ability to detect and transmit novel events is essential for adaptive behavior in uncertain environments. Here, we investigate how holographically triggered, unanticipated action potentials propagate through the primary visual cortex of resting mice, focusing on pyramidal neuron communication. We find that these novel spikes -- uncorrelated with ongoing activity -- exert a disproportionately large influence on neighboring neurons, whose response scales as a power law (exponent [~]0.2-0.3). Even a few such spikes can recruit a large fraction of the local network, enabling robust decoding of perturbation origin despite high trial-by-trial variability and ongoing activity dominated by large activity fluctuations in the form of scale-invariant, parabolic neuronal avalanches. Simulations confirm this scaling to small, local perturbations aligns with the high susceptibility of complex systems near criticality. These results suggest that critical dynamics facilitate efficient transmission of novel signals, revealing a fundamental mechanism for cortical novelty detection.

neuroscience↗