bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/803718

Probing the neural dynamics of mnemonic representations in humans

Liu, W.·Kohn, N.·Fernandez, G.
View original source ↗Export metadata ↓

Abstract

Memories are not stored as static engrams, but as dynamic representations affected by processes occurring after initial encoding. Previous studies revealed changes in activity and mnemonic representations in visual processing areas, parietal lobe, and hippocampus underlying repeated retrieval and suppression. However, these neural changes are usually induced by memory modulation immediately after memory formation. Here, we investigated 27 healthy participants with a two-day functional Magnetic Resonance Imaging design to probe how established memories are dynamically modulated by retrieval and suppression 24 hours after learning. Behaviorally, we demonstrated that established memories can still be strengthened by repeated retrieval. By contrast, repeated suppression had a modest negative effect, and suppression-induced forgetting was associated with individual suppression efficacy. Neurally, we demonstrated item-specific pattern reinstatements in visual processing areas, parietal lobe, and hippocampus. Then, we showed that repeated retrieval reduced activity amplitude in the ventral visual cortex and hippocampus, but enhanced the distinctiveness of activity patterns in the ventral visual cortex and parietal lobe. Critically, reduced activity was associated with enhanced representation of idiosyncratic memory traces in ventral visual cortex and precuneus. In contrast, repeated memory suppression was associated with the reduced lateral prefrontal activity, but relative intact mnemonic representations. Our results replicated most of the neural changes induced by memory retrieval and suppression immediately after learning and extended those findings to established memories after initial consolidation. Active retrieval seems to promote episode-unique mnemonic representations in the neocortex after initial encoding but also consolidation. HighlightsO_LIRepeated retrieval strengthened consolidated memories, while repeated suppression had a modest negative effect. C_LIO_LIPattern reinstatements of individual memories were detected in the visual area, parietal lobe, and hippocampus after 24 hours. C_LIO_LIAfter repeated retrieval, reduced activity amplitude was associated with increased distinctiveness of activity patterns in the ventral visual cortex and right precuneus. C_LIO_LIRepeated suppression was associated with the reduced lateral prefrontal activity, but unchanged mnemonic representations. C_LI

Source connections

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Liu, W., Kohn, N., Fernandez, G.. 2019-10-15. Probing the neural dynamics of mnemonic representations in humans. https://doi.org/10.1101/803718

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↗