Analysis of Graph Invariants in Functional Neocortical Circuitry Reveals Generalized Features Common to Three Areas of Sensory Cortex

Abstract

Correlations in local neocortical spiking activity can provide insight into the underlying organization of cortical microcircuitry. However, identifying structure in patterned multi-neuronal spiking remains a daunting task due to the high dimensionality of the activity. Using two-photon imaging, we monitored spontaneous circuit dynamics in large, densely sampled neuronal populations within slices of mouse primary auditory, somatosensory, and visual cortex. Using the lagged correlation of spiking activity between neurons, we generated functional wiring diagrams to gain insight into the underlying neocortical circuitry. By establishing the presence of graph invariants, which are label-independent characteristics common to all circuit topologies, our study revealed organizational features that generalized across functionally distinct cortical regions. Regardless of sensory area, random and -nearest neighbors null graphs failed to capture the structure of experimentally derived functional circuitry. These null models indicated that despite a bias in the data towards spatially proximal functional connections, functional circuit structure is best described by non-random and occasionally distal connections. Eigenvector centrality, which quantifies the importance of a neuron in the temporal flow of circuit activity, was highly related to feedforwardness in all functional circuits. The number of nodes participating in a functional circuit did not scale with the number of neurons imaged regardless of sensory area, indicating that circuit size is not tied to the sampling of neocortex. Local circuit flow comprehensively covered angular space regardless of the spatial scale that we tested, demonstrating that circuitry itself does not bias activity flow toward pia. Finally, analysis revealed that a minimal numerical sample size of neurons was necessary to capture at least 90 percent of functional circuit topology. These data and analyses indicated that functional circuitry exhibited rules of organization which generalized across three areas of sensory neocortex.

Behavioral assessment of sensitivity to intracortical microstimulation of primate somatosensory cortex

“…However, though the basic structure of these two sensory cortices is similar (35), differences in their microcircuitry have been reported (36,37). Furthermore, rodents can more readily detect very short asynchronies in ICMS pulses (delivered through two electrodes) when these are delivered to somatosensory cortex than to auditory cortex (38), suggesting that somatosensory cortex is more sensitive than auditory cortex to small differences in neural timing (on the order of 1-3 ms).…”

The mechanics of state-dependent neural correlations

“…It is tempting to try to infer the structure of these circuits and the physiological properties of neurons within them from multicellular recordings from subsets of neurons. Such an approach is fraught with difficulties 49 , many of which are due to the fact that only part of the population is observed. Here we describe an alternative strategy that is more modest in scope, but provides a general framework for discussing how modulations in spiking correlations depend on biophysical changes in the underlying circuit to which the neurons belong.…”

Progress and challenges for understanding the function of cortical microcircuits in auditory processing

“…Such population activity patterns may differ between the synchronized and the desynchronized state of the cortical network 90 , and identifying inter-connected modules using network science methods can reveal whether and how the modules are transformed between the different brain states. Shared variability in neuronal populations can potentially be explained by distinct patterns of connections between neurons 91 , whereas diverse response patterns may correspond to different coupling patterns between single neurons and neuronal populations 92 —network analysis of activity in cortical slices already identifies functional modules, that exhibit similar organization across sensory cortex 93 , 94 (Fig. 4c ).…”