Continuous Neural Correlates of Imbalanced Reinforcement Learning in Obsessive-Compulsive Disorder and Healthy Individuals

Sakai, Y.; Abe, Y.; Narumoto, J.; Tanaka, S. C.

doi:10.1101/2025.01.28.635211

Home/Archive/bioRxiv

bioRxiv · 10.1101/2025.01.28.635211

Continuous Neural Correlates of Imbalanced Reinforcement Learning in Obsessive-Compulsive Disorder and Healthy Individuals

Sakai, Y.·Abe, Y.·Narumoto, J.·Tanaka, S. C.

View original source ↗Export metadata ↓

Abstract

AimObsessive-compulsive disorder (OCD) is characterized by imbalanced reinforcement learning. This study investigated neural correlates of this imbalance by examining resting-state functional connectivity (rs-fMRI) in non-medicated OCD patients and healthy controls (HCs) exhibiting varying degrees of memory trace imbalance. MethodsWe employed network-based statistics (NBS), suitable for identifying network-level alterations of rs-fMRI data from 49 OCD patients and 53 HCs (Core Discovery Dataset: Core-DS) to identify a significant network. We validated this network in an independent dataset of 10 OCD patients and 18 HCs (Independent Validation Dataset: IndV-DS). Additionally, we compared functional connectivity in the identified network between subgroups of HCs with imbalanced (OCD-like) and balanced learning profiles (Extension Dataset: Ext-DS; n=10 each). ResultsNBS identified an OCD network with increased connectivity in OCD patients (padjusted = 0.022), comprising regions in the dorsolateral prefrontal cortex (DLPFC), parietal cortex, retrosplenial cortex, and hippocampal formation. This networks increased connectivity in OCD patients was replicated in IndV-DS (p = 0.0027). Importantly, imbalanced HCs showed a significant increase in functional connectivity, particularly between the DLPFC and presubiculum, in the identified OCD network, compared to balanced HCs (p = 0.0051, padjusted = 0.066). ConclusionIncreased functional connectivity in the OCD network, especially between the DLPFC and presubiculum, is present in both OCD patients and a subgroup of HCs with learning imbalances. These findings provide evidence for a continuous neural basis of imbalanced reinforcement learning, suggesting a continuum of traits associated with OCD between patients and "healthy" individuals.

Explore related subjects

neuroscience Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Sakai, Y., Abe, Y., Narumoto, J., Tanaka, S. C.. 2025-01-30. Continuous Neural Correlates of Imbalanced Reinforcement Learning in Obsessive-Compulsive Disorder and Healthy Individuals. https://doi.org/10.1101/2025.01.28.635211

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↗