Search bioRxiv⌕ Search

bioRxiv · 10.1101/2023.11.16.567451

Input / Output Relationships for the Primary Hippocampal Circuit.

Abstract

The hippocampus is likely the most studied brain region but little is known about signal throughput -- the simplest, yet most essential of circuit operations -- across its multiple stages from perforant path input to CA1. Here we report that single pulse stimulation of the lateral perforant path (LPP) produces a two-part CA1 response generated by projections to CA3 ("direct path") and the dentate gyrus ("indirect path"). The latter was by far the more potent in driving CA1 output because it engaged the massive recurrent collateral system and elicited a series of fEPSPs and spikes in CA3. The mobilization time for this stereotyped sharp wave-like response resulted in surprisingly slow throughput. The circuit did not convey high frequency LPP trains but transmitted single pulses, or bursts of pulses separated by the period of the theta wave. During these activation patterns CA1 output faithfully reproduced a version of the LPP input. We conclude that the basic hippocampal circuit, despite its considerable complexity, has a default mode in which select cortical signals are reliably transferred to output stations. Significance statementThe hippocampus, a brain structure synonymous with episodic memory, is one of the most studied brain regions in neuroscience today. However, despite this intense interest, surprisingly little is known about how signals are transformed and processed by the hippocampal circuit. As a result, there are currently no "bottom up" hypotheses about how the structure supports its physiological function(s). Here, we use a novel brain slice preparation to describe the signal transformations occurring across the primary hippocampal circuit. The results identify novel circuit operations that challenge the notion of the tri-synaptic circuit and provide evidence for frequency-dependent filters that are critical for determining signal throughput. These findings provide an initial link between basic circuit function(s) and events recorded in behaving animals.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Gunn, B. G., Pruess, B. S., Gall, C. M., Lynch, G.. 2023-11-17. Input / Output Relationships for the Primary Hippocampal Circuit.. https://doi.org/10.1101/2023.11.16.567451

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↗