Structured networks support sparse traveling waves in rodent somatosensory cortex

Abstract

Neurons responding to different whiskers are spatially intermixed in the superficial layer 2/3 (L2/3) of the rodent barrel cortex, where a single whisker deflection activates a sparse, distributed neuronal population that spans multiple cortical columns. How the superficial layer of the rodent barrel cortex is organized to support such distributed sensory representations is not clear. In a computer model, we tested the hypothesis that sensory representations in L2/3 of the rodent barrel cortex are formed by activity propagation horizontally within L2/3 from a site of initial activation. The model explained the observed properties of L2/3 neurons, including the low average response probability in the majority of responding L2/3 neurons, and the existence of a small subset of reliably responding L2/3 neurons. Sparsely propagating traveling waves similar to those observed in L2/3 of the rodent barrel cortex occurred in the model only when a subnetwork of strongly connected neurons was immersed in a much larger network of weakly connected neurons.

The impact of a closed-loop thalamocortical model on the spatiotemporal dynamics of cortical and thalamic traveling waves

“…The cortical wave area increased proportionally with the intracortical connectivity (Fig. 3 a), reaching a noticeable wave structure when the intracortical connections reached 50%; this was consistent with a previous report using another model setup 33 . When the intracortical connectivity was below 25%, the cortical wave structure lost continuity and reduced to isolated dot patterns.…”

“…We assume that every neuron in TC is excitatory and that every neuron of RE is inhibitory. In contrast, neurons in the cortex layer are randomly chosen from both classes to keep the composition at 80% excitatory and 20% inhibitory 33 (Fig. 1 e).…”

“…Supplementary Video S2 provides a “zoomed-in” view of the spontaneous wave propagation simulated in the cortex, showing a 10 10 array instead of a 60 60 array to match experimentally observed structures. Next, we modified the model to contain 80% excitatory and 20% inhibitory cortical neurons to match ratios seen experimentally 33 , 41 ; we also assumed 99% intracortical connectivity, with stochastic inputs. In this case, our model produced oscillations with spontaneous random wave directions (Fig.…”

“…To date, a wide range of models have been developed for traveling waves or spatiotemporal neural activity in neuronal networks 20 , 22 – 25 , neural fields 26 – 29 , networks of coupled oscillators 30 , 31 , and the thalamocortical network 32 . The modeling scale of network size varied between hundreds and tens of thousands of neurons 33 . The generation of diverse wave patterns—similar to those seen in experiments—mostly relied on neural field continuum approximations 34 .…”

Unraveling the spatiotemporal brain dynamics during a simulated reach-to-eat task

“…In conclusion, this study demonstrates that phase-encoded design and analysis can be used to unravel sequential activations among brain regions at a temporal resolution higher than the native sampling rate of fMRI. The sequence of activations showed a surprisingly coherent traveling wave of activity similar to those seen in invasive experiments in the barrel cortex of awake rodents during whisking movements (e.g., Moldakarimov et al, 2018) as well as with voltage sensitive dyes in tangential slices (e.g., Wu et al, 2008). Although the dynamics of those activations are much faster than what we have observed, the similarities in spatial coherence are an intriguing avenue for future research.…”