Spatial diversity of spontaneous activity in the cortex

Abstract

The neocortex is a layered sheet across which a basic organization is thought to widely apply. The variety of spontaneous activity patterns is similar throughout the cortex, consistent with the notion of a basic cortical organization. However, the basic organization is only an outline which needs adjustments and additions to account for the structural and functional diversity across cortical layers and areas. Such diversity suggests that spontaneous activity is spatially diverse in any particular behavioral state. Accordingly, this review summarizes the laminar and areal diversity in cortical activity during fixation and slow oscillations, and the effects of attention, anesthesia and plasticity on the cortical distribution of spontaneous activity. Among questions that remain open, characterizing the spatial diversity in spontaneous membrane potential may help elucidate how differences in circuitry among cortical regions supports their varied functions. More work is also needed to understand whether cortical spontaneous activity not only reflects cortical circuitry, but also contributes to determining the outcome of plasticity, so that it is itself a factor shaping the functional diversity of the cortex.

A distinct population of L6 neurons in mouse V1 mediate cross-callosal communication

“…These long-range cortical inputs may also cause CP neurons to have more diverse activity correlations with brain states. Unlike CT neurons, whose spontaneous population activity in the dark was strongly positively correlated with arousal, the spontaneous activity of the CP population in the dark may be negatively, positively, or un-correlated with the arousal level, indicating more complex (e.g., multisensory, higher cognitive) origins of forces that drive and modulate their spontaneous firing 49 . During grating stimuli, the population activity of CP neurons becomes more positively correlated with arousal than in the dark, suggesting a switch of cortical dynamics and brain state when the animal was exposed to strong sensory stimulation.…”

Enhanced Burst-Suppression and Disruption of Local Field Potential Synchrony in a Mouse Model of Focal Cortical Dysplasia Exhibiting Spike-Wave Seizures

“…In addition to the general suppression of neuronal activity associated with anesthetics, a more complex mode of action is linked to the large-scale modulation of neural networks across brain regions (Cimenser et al, 2011; Lewis et al, 2012; McCarthy et al, 2012). Although the fundamental circuitry of the mammalian cortex is remarkably similar across brain regions, significant differences in the specific details of individual computational units exist that may account for differential effects of anesthesia across brain region and cortical layer (Tan, 2015; Miller, 2016). In the current study, laminar recordings of extracellular signals indicated significant changes in spectral power values across anesthetic state but not between cortical lamina of the S1 cortex though there was a trend for increased power levels in the superficial layers as observed in some animals.…”

“…In the current study, the spectral profile of burst activity was similar to slow-wave activity in both control and FL animals with the majority of spectral power reflected in the lower frequencies (1–20 Hz) and highest values in the delta (1–4 Hz) and theta (4–8 Hz) bands. Slow-wave oscillations are a common feature of non-REM (i.e., slow-wave) sleep, anesthesia, and are commonly observed in cortical slices (Tan, 2015). In fact, slow waves may represent global changes in information flow that entrain much of the cortex (Massimini et al, 2004) or may represent distinct features that shape activity in specific functional circuits (Kenet et al, 2003).…”

Experience-dependent plasticity modulates ongoing activity in the antennal lobe and enhances odor representations

“…Hence, a sensory-experience-dependent dampening of the internal noise of neural networks can contribute to more effective and specific processing of incoming information. Investigating the presence and mechanisms of this phenomenon is important for understanding how higher brain regions, such as the habenula ( Baker et al., 2015 ; Jetti et al., 2014 ; Mizumori and Baker, 2017 ), thalamus ( Kirouac, 2015 ; MacLean et al., 2005 ), or the cortex ( Blaeser et al., 2017 ; Tan, 2015 ) contribute to the switching of brain states. Our results revealed that experience-dependent alterations are not only restricted to higher brain regions, but can specifically modulate sensory representations at the first stage of sensory pathways, such as the antennal lobe.…”