Search bioRxivSearch

bioRxiv · 10.1101/2021.01.26.428350

Sensitivity enhancement and selection are shared mechanisms for spatial and feature-based attention

Abstract

Human observers use cues to guide visual attention to the most behaviorally relevant parts of the visual world. Cues are often separated into two forms: those that rely on spatial location and those that use features, such as motion or color. These forms of cueing are known to rely on different populations of neurons. Despite these differences in neural implementation, attention may rely on shared computational principles, enhancing and selecting sensory representations in a similar manner for all types of cues. Here we examine whether evidence for shared computational mechanisms can be obtained from how attentional cues enhance performance in estimation tasks. In our tasks, observers were cued either by spatial location or feature to two of four dot patches. They then estimated the color or motion direction of one of the cued patches, or averaged them. In all cases we found that cueing improved performance. We decomposed the effects of the cues on behavior into model parameters that separated sensitivity enhancement from sensory selection and found that both were important to explain improved performance. We found that a model which shared parameters across forms of cueing was favored by our analysis, suggesting that observers have equal sensitivity and likelihood of making selection errors whether cued by location or feature. Our perceptual data support theories in which a shared computational mechanism is re-used by all forms of attention. Significance StatementCues about important features or locations in visual space are similar from the perspective of visual cortex, both allow relevant sensory representations to be enhanced while irrelevant ones can be ignored. Here we studied these attentional cues in an estimation task designed to separate different computational mechanisms of attention. Despite cueing observers in three different ways, to spatial locations, colors, or motion directions, we found that all cues led to similar perceptual improvements. Our results provide behavioral evidence supporting the idea that all forms of attention can be reconciled as a single repeated computational motif, re-implemented by the brain in different neural architectures for many different visual features.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Birman, D., Gardner, J. L.. 2021-01-27. Sensitivity enhancement and selection are shared mechanisms for spatial and feature-based attention. https://doi.org/10.1101/2021.01.26.428350

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

KEEP EXPLORING

Related preprints

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

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

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