bioRxiv Science⌕ Search

bioRxiv · 10.1101/2022.11.11.516158

Consequences of blindness for neural dynamics in mouse visual cortex

Abstract

The role of experience in the development and maintenance of emergent network properties such as cortical oscillations and states is poorly understood. To define how early-life experience affects cortical dynamics in adult visual cortex, we examined the effects of two forms of blindness, bilateral loss of retinal input (enucleation) and degradation of visual input (eyelid-suture), on spontaneous activity in awake head-fixed mice of both sexes. Neither form of deprivation fundamentally altered the state-dependent regulation of firing-rates or local field potentials. However, each form of deprivation did cause a unique set of changes in network behavior. Laminar analysis revealed two different generative mechanisms for low-frequency synchronization, one prevalent during movement, the other during quiet-wakefulness. The former was absent in enucleated mice, suggesting a mouse homolog of human alpha oscillations. In addition, neurons in enucleated animals were less correlated and fired more regularly, but showed no change in mean firing-rate. Chronic lid-suture decreased firing rates during quiet-wakefulness, but not during movement, with no effect on neural correlations or regularity. Sutured animals showed a broadband increase in dEEG power and an increased occurrence, but reduced central frequency, of narrowband gamma oscillations. The complementary--rather than additive--effects of lid-suture and enucleation suggest that the development of these emergent network properties does not require vision but is plastic to modified input. Our results suggest a complex interaction of internal set-points and experience determines the expression of mature cortical activity, with low-frequency synchronization being particularly susceptible to early deprivation. SIGNIFICANCE STATEMENTThe developmental rules that guide how cortex balances internal homeostatic set points with external inputs to establish the emergent network level dynamics critical to its function are unclear. Using multiple methods of early deprivation, we show that the development of dynamics in mouse visual cortex is not dependent on the type of input. Rather, specific neural rhythms, firing-rate set points, and neural correlations are differentially modified by experience. Our deprivations identify one specific rhythm as a likely homolog to human alpha and suggest a mechanism for its loss in blindness. Our results advance our understanding of the regulatory mechanism leading to normal cortical processing, which is altered in blindness and multiple neural disorders.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Colonnese, P., Phillips, M. A., Boley, N. C., Colonnese, M. T.. 2022-11-13. Consequences of blindness for neural dynamics in mouse visual cortex. https://doi.org/10.1101/2022.11.11.516158

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗