Spontaneous cortical activity alternates between motifs defined by regional axonal projections

Abstract

In lightly anaesthetized or awake adult mice using millisecond timescale voltage sensitive dye imaging, we show that a palette of sensory-evoked and hemisphere-wide activity motifs are represented in spontaneous activity. These motifs can reflect multiple modes of sensory processing including vision, audition, and touch. Similar cortical networks were found with direct cortical activation using channelrhodopsin-2. Regional analysis of activity spread indicated modality specific sources such as primary sensory areas, and a common posterior-medial cortical sink where sensory activity was extinguished within the parietal association area, and a secondary anterior medial sink within the cingulate/secondary motor cortices for visual stimuli. Correlation analysis between functional circuits and intracortical axonal projections indicated a common framework corresponding to long-range mono-synaptic connections between cortical regions. Maps of intracortical mono-synaptic structural connections predicted hemisphere-wide patterns of spontaneous and sensory-evoked depolarization. We suggest that an intracortical monosynaptic connectome shapes the ebb and flow of spontaneous cortical activity.

Mesoscale infraslow spontaneous membrane potential fluctuations recapitulate high-frequency activity cortical motifs

“…We demonstrate the presence of spontaneous infraslow activity in anaesthetized mouse cortex and that this activity exhibits regionally selective patterns, correlates with independent measures of electroencephalography (EEG) and local field potential (LFP), and is bilaterally synchronous. Importantly, intrahemispheric, spontaneous infraslow activity exhibits a patterned regional structure that is analogous to cortical motifs within higher-frequency (0.5-6 Hz) activity that we have previously described 27 . This builds upon pioneering studies in cat visual cortex which illustrated that cortical orientation representations are dynamically represented in ongoing spontaneous activity, and further, that these events may serve a preparatory role in setting default cortical sensory input parameters 30,31 .…”

“…Furthermore, descriptions of resting-state infraslow activity in humans, non-human primates and rodents have demonstrated these networks to be robust and persistent in task-negative awake states in addition to states of natural sleep and anaesthesia 5,9,32 . Furthermore, our previous data indicated that connectivity maps from quiet awake and anaesthetized states are similar 27,33 . We observed spontaneous infraslow (o0.1 Hz) fluctuations in baseline DC-EEG and LFP recordings (Fig.…”

“…VSD imaging of spontaneous cortical infraslow activity. We have characterized repeating structures resembling sensorimotor activity, which we have referred to as cortical motifs, within higher-frequency spontaneous activity in anaesthetized and quiet awake mice 27 . We used a similar strategy to investigate the spatiotemporal structure of spontaneous infraslow cortical activity and examine how this activity relates to our previously published observations.…”

“…2). A broad local peak in the power spectra indicated oscillatory activity associated with the slow oscillation (1 Hz) 34,37 and delta oscillation (1.5-4 Hz), which predominate under anaesthesia and natural sleep and can be observed in states of quiet wakefulness 27,33,34 . As in our DC-EEG and LFP recordings of spontaneous activity, we observe the presence of substantial power in the infraslow frequency (o0.1 Hz) range indicating a significant presence of infraslow spontaneous activity in our cortical VSD signals ( Supplementary Fig.…”

“…This imaging paradigm is ideally suited for this study as VSD imaging directly reflects underlying electrical activity with high spatial and temporal resolution allowing for imaging of nearly the entire dorsal neocortex while maintaining high spatial resolution and at rates sufficient to resolve multiple time signatures of ongoing activity. The signal is dependent on neuronal activity 27 and the red spectral properties of the dye 28 mitigate potentially confounding neuroimaging artifacts such as flavoprotein autofluorescence, intrinsic signal responses, and heartbeat and respiration artifacts 28,29 . Such confounding artifacts are potentially present in all the signals attributed to green epifluorescence (including genetically encoded Ca 2 þ indicators).…”