bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2024.03.24.586454

Theta-Gamma Phase-Amplitude Coupling Supports Working Memory Performance in the Human Hippocampus

Salimpour, Y.·Anderson, W.
View original source ↗Export metadata ↓

Abstract

Phase-amplitude coupling (PAC) occurs in the human hippocampus during working memory and supports the contribution of the hippocampus in the maintenance of multiple items. Additionally, PAC has the potential to reveal the neural mechanisms underlying multi-item maintenance in the hippocampus by providing a putative architecture for multi-item representation. Theta and gamma range rhythms are prominent neuronal oscillations in the hippocampus. Studies on the role of theta frequency oscillation in local field potentials in human memory have shown mixed evidence for successful remembering. The role of gamma oscillatory activity in contributing to memory retrieval is not yet fully understood. They also interact with each other in the form of PAC during memory performance. This study aims to investigate the neurophysiological function of theta-gamma PAC in the human hippocampus during a multi-item working memory task and characterize its association with performance. Theta-gamma cross-coupling investigation in the electrocorticographic signals was performed from the hippocampus recording of ten epilepsy patients while they were engaged with the working memory task. The results show strong correlations between PAC levels and the subjects memory performance, but no correlation with theta and gamma power individually, specifically in the retrieval phase of a working memory task. These observations demonstrate the possible role of PAC in memory-related operations, suggesting a PAC-based neural mechanism for working memory in the hippocampus. Significance StatementThe findings from this study elucidate the crucial role of phase-amplitude coupling in the human hippocampus during working memory tasks, specifically in the maintenance of multiple items. By analyzing electrocorticographic recordings from epilepsy patients engaged in a working memory task, our research unveils a direct correlation between PAC levels and memory performance during the retrieval phase, which is not observed when analyzing theta and gamma oscillations individually. These findings suggest a theta-gamma coupling based mechanism within the hippocampus that facilitates working memory, offering new insights into the complex neural processes underlying memory encoding and retrieval. This advancement in understanding the neural architecture of memory not only contributes to the foundational knowledge of cognitive neuroscience but also opens avenues for developing targeted interventions for enhancing memory performance with translational application in treating memory-related neurological disorders.

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Salimpour, Y., Anderson, W.. 2024-03-27. Theta-Gamma Phase-Amplitude Coupling Supports Working Memory Performance in the Human Hippocampus. https://doi.org/10.1101/2024.03.24.586454

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

KEEP EXPLORING

Related preprints

bioRxiv2026

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↗
bioRxiv2026

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↗
bioRxiv2026

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↗