bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2025.02.17.638684

Evidence for abstract codes in parietal cortex guiding prospective working memory

Lee, J.·De Vito, D.·Miller, J. A.·Nee, D. E.
View original source ↗Export metadata ↓

Abstract

The recent past helps us predict and prepare for the near future. Such preparation relies on working memory (WM) which actively maintains and manipulates information providing a temporal bridge. Numerous studies have shown that recently presented visual stimuli can be decoded from fMRI signals in visual cortex (VC) and the intra-parietal sulcus (IPS) suggesting that these areas sustain the recent past. Yet, in many cases, concrete, sensory signals of past information must be transformed into the abstract codes to guide future cognition. However, this process remains poorly understood. Here, human participants used WM to maintain a separate spatial location in each hemifield wherein locations were embedded in a learned spatial sequence. On each trial, participants made a sequence-match decision to a probe and then updated their WM with the probe. The same abstract sequence guided judgments in each hemifield, allowing the separate detection of concrete spatial locations (hemifield-specific) and abstract sequence positions (hemifield-general), and also tracking of representations of the past (last location/position) and future (next location/position). Consistent with previous reports, concrete past locations held in WM could be decoded from VC and IPS. Moreover, in anticipation of the probe, representations shifted from past to future locations in both areas. Critically, we observed abstract coding of future sequence positions in the IPS whose magnitude related to speeded performance. These data suggest that the IPS sustains abstract codes to facilitate future preparation and reveal a transformation of the sensory past into abstract codes guiding future behavior. Significant StatementTo act efficiently, we must use the recent past to prepare for what comes next. For this purpose, working memory (WM) is critical. Although substantial research has shown that WM retains recently presented sensory information, preparation for the future involves abstraction wherein shared meaning is aggregated while superfluous sensory details are discarded. The mechanisms underlying this process remain unclear. Analyzing functional MRI signals in the intraparietal sulcus (IPS), we found that distinct sensory states with shared predictive meaning were initially maintained in a sensory-like fashion, but over time, became aggregated indicative of abstraction. Abstraction was associated with behavioral efficiency highlighting its role in preparation. These findings reveal neural mechanisms supporting the transformation from past to future in WM.

Source connections

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Lee, J., De Vito, D., Miller, J. A., Nee, D. E.. 2025-02-17. Evidence for abstract codes in parietal cortex guiding prospective working memory. https://doi.org/10.1101/2025.02.17.638684

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↗