Human sensory Long-Term Potentiation (LTP) predicts visual memory performance and is modulated by the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism

Spriggs, M. J.; Thompson, C. S.; Moreau, D.; McNair, N. A.; Wu, C. C.; Lamb, Y. N.; Mckay, N. S.; King, R. O. C.; Antia, U.; Shelling, A. N.; Hamm, J. P.; Teyler, T. J.; Russell, B. R.; Waldie, K. W.; Kirk, I. J.

doi:10.1101/284315

bioRxiv · 10.1101/284315

Human sensory Long-Term Potentiation (LTP) predicts visual memory performance and is modulated by the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism

Spriggs, M. J.·Thompson, C. S.·Moreau, D.·McNair, N. A.·Wu, C. C.·Lamb, Y. N.·Mckay, N. S.·King, R. O. C.·Antia, U.·Shelling, A. N.·Hamm, J. P.·Teyler, T. J.·Russell, B. R.·Waldie, K. W.·Kirk, I. J.

View original source ↗Export metadata ↓

Abstract

BackgroundLong-Term Potentiation (LTP) is recognised as a core neuronal process underlying long-term memory. However, a direct relationship between LTP and human memory performance is yet to be demonstrated. The first aim of the current study was thus to assess the relationship between LTP and human long-term memory performance. With this also comes an opportunity to explore factors thought to mediate the relationship between LTP and long-term memory, and to gain additional insight into variations in memory function and memory decline. The second aim of the current study was to explore the relationship between LTP and memory in groups differing with respect to BDNF Val66Met; a single nucleotide polymorphism implicated in memory function.\n\nMethods28 participants (15 female) were split into three genotype groups (Val/Val, Val/Met, Met/Met) and were presented with both an EEG paradigm for inducing LTP-like enhancements of the visually-evoked response, and a test of visual memory.\n\nResultsThe magnitude of LTP 40 minutes after induction was predictive of long-term memory performance. Additionally, the BDNF Met allele was associated with both reduced LTP and reduced memory performance.\n\nConclusionsThe current study not only presents the first evidence for a relationship between sensory LTP and human memory performance, but also demonstrates how targeting this relationship can provide insight into factors implicated in variation in human memory performance. It is anticipated that this will be of utility to future clinical studies of disrupted memory function.

Explore related subjects

neuroscience Preprint

Keep this discovery

BibTeX RIS

Spriggs, M. J., Thompson, C. S., Moreau, D., McNair, N. A., Wu, C. C., Lamb, Y. N., Mckay, N. S., King, R. O. C., Antia, U., Shelling, A. N., Hamm, J. P., Teyler, T. J., Russell, B. R., Waldie, K. W., Kirk, I. J.. 2018-03-18. Human sensory Long-Term Potentiation (LTP) predicts visual memory performance and is modulated by the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism. https://doi.org/10.1101/284315

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↗