Distinctive neurophysiological signatures of analgesia after inflammatory pain in the ACC of freely moving mice.

Preclinical assessments of pain have often relied upon behavioral measurements and anesthetized neurophysiological recordings. Current technologies enabling large scale neural recordings, however, have the potential to unveil quantifiable pain signals in conscious animals for preclinical studies. Although pain processing is distributed across many brain regions, the anterior cingulate cortex (ACC) is of particular interest in isolating these signals given its suggested role in the affective ('unpleasant') component of pain. Here, we explored the utility of the ACC towards preclinical pain research using head-mounted miniaturized microscopes to record calcium transients in freely moving male mice expressing GCaMP6f under the Thy1 promoter. We verified the expression of GCaMP6f in excitatory neurons and found no intrinsic behavioral differences in this model. Using a multimodal stimulation paradigm across naive, pain, and analgesic conditions, we found that while ACC population activity roughly scaled with stimulus intensity, single cell representations were highly flexible. We found only low magnitude increases in population activity after CFA, and insufficient evidence for the existence of a robust nociceptive ensemble in the ACC. However, we found a temporal sharpening of response durations and generalized increases in pairwise neural correlations in the presence of the mechanistically distinct analgesics gabapentin or ibuprofen after (but not before) CFA induced inflammatory pain. This increase was not explainable by changes in locomotion alone. Taken together, these results highlight challenges in isolating distinct pain signals amongst flexible representations in the ACC but suggest a neurophysiological hallmark of analgesia after pain that generalizes to at least two analgesics.Significance Statement Our study measured neural activity in the anterior cingulate cortex (ACC) of transgenic mice to improve measures of pain and analgesia in preclinical models. We found that although ACC population activity scaled with stimulus intensity and could be decoded, single cell representations of sensory stimuli were flexible. Low magnitude increases in ACC population activity were observed after pain, but subpopulations with specific activity changes driven by pain/analgesia were difficult to disambiguate from intrinsic variability. Interestingly, responses were temporally sharpened and exhibited increased cell to cell correlations in the presence of two distinct analgesics after CFA but not before. These distinct neural signatures of analgesia occurring only after pain may broaden our understanding of central mechanisms of pain and analgesia.

Restoration of Visual Function and Cortical Connectivity After Ischemic Injury Through NeuroD1-Mediated Gene Therapy.

Neural circuits underlying brain functions are vulnerable to damage, including ischemic injury, leading to neuronal loss and gliosis. Recent technology of direct conversion of endogenous astrocytes into neurons in situ can simultaneously replenish the neuronal population and reverse the glial scar. However, whether these newly reprogrammed neurons undergo normal development, integrate into the existing neuronal circuit, and acquire functional properties specific for this circuit is not known. We investigated the effect of NeuroD1-mediated in vivo direct reprogramming on visual cortical circuit integration and functional recovery in a mouse model of ischemic injury. After performing electrophysiological extracellular recordings and two-photon calcium imaging of reprogrammed cells in vivo and mapping the synaptic connections formed onto these cells ex vivo, we discovered that NeuroD1 reprogrammed neurons were integrated into the cortical microcircuit and acquired direct visual responses. Furthermore, following visual experience, the reprogrammed neurons demonstrated maturation of orientation selectivity and functional connectivity. Our results show that NeuroD1-reprogrammed neurons can successfully develop and integrate into the visual cortical circuit leading to vision recovery after ischemic injury.

Impaired Adaptation and Laminar Processing of the Oddball Paradigm in the Primary Visual Cortex of Fmr1 KO Mouse.

Both adaptation and novelty detection are an integral part of sensory processing. Recent animal oddball studies have advanced our understanding of circuitry underlying contextual processing in early sensory areas. However, it is unclear how adaptation and mismatch (MM) responses depend on the tuning properties of neurons and their laminar position. Furthermore, given that reduced habituation and sensory overload are among the hallmarks of altered sensory perception in autism, we investigated how oddball processing might be altered in a mouse model of fragile X syndrome (FX). Using silicon probe recordings and a novel spatial frequency (SF) oddball paradigm, we discovered that FX mice show reduced adaptation and enhanced MM responses compared to control animals. Specifically, we found that adaptation is primarily restricted to neurons with preferred oddball SF in FX compared to WT mice. Mismatch responses, on the other hand, are enriched in the superficial layers of WT animals but are present throughout lamina in FX animals. Last, we observed altered neural dynamics in FX mice in response to stimulus omissions. Taken together, we demonstrated that reduced feature adaptation coexists with impaired laminar processing of oddball responses, which might contribute to altered sensory perception in FX syndrome and autism.

Visual Experience-Dependent Oscillations and Underlying Circuit Connectivity Changes Are Impaired in Fmr1 KO Mice.

Fragile X syndrome (FX), the most common inherited form of autism and intellectual disability, is a condition associated with visual perceptual learning deficits. We recently discovered that perceptual experience can encode visual familiarity via persistent low-frequency oscillations in the mouse primary visual cortex (V1). Here, we combine this paradigm with a multifaceted experimental approach to identify neurophysiological impairments of these oscillations in FX mice. Extracellular recordings reveal shorter durations, lower power, and lower frequencies of peak oscillatory activity in FX mice. Directed information analysis of extracellularly recorded spikes reveals differences in functional connectivity from multiple layers in FX mice after the perceptual experience. Channelrhodopsin-2 assisted circuit mapping (CRACM) reveals increased synaptic strength from L5 pyramidal onto L4 fast-spiking cells after experience in wild-type (WT), but not FX, mice. These results suggest differential encoding of visual stimulus familiarity in FX via persistent oscillations and identify circuit connections that may underlie these changes.

Oscillatory Encoding of Visual Stimulus Familiarity.

Familiarity of the environment changes the way we perceive and encode incoming information. However, the neural substrates underlying this phenomenon are poorly understood. Here we describe a new form of experience-dependent low-frequency oscillations in the primary visual cortex (V1) of awake adult male mice. The oscillations emerged in visually evoked potentials and single-unit activity following repeated visual stimulation. The oscillations were sensitive to the spatial frequency content of a visual stimulus and required the mAChRs for their induction and expression. Finally, ongoing visually evoked θ (4-8 Hz) oscillations boost the visually evoked potential amplitude of incoming visual stimuli if the stimuli are presented at the high excitability phase of the oscillations. Our results demonstrate that an oscillatory code can be used to encode familiarity and serves as a gate for oncoming sensory inputs.SIGNIFICANCE STATEMENT Previous experience can influence the processing of incoming sensory information by the brain and alter perception. However, the mechanistic understanding of how this process takes place is lacking. We have discovered that persistent low-frequency oscillations in the primary visual cortex encode information about familiarity and the spatial frequency of the stimulus. These familiarity evoked oscillations influence neuronal responses to the oncoming stimuli in a way that depends on the oscillation phase. Our work demonstrates a new mechanism of visual stimulus feature detection and learning.