Recent developments in human neuroimaging make it possible to non-invasively measure neural activity from different cortical layers. This can potentially reveal not only which brain areas are engaged by a task, but also how. Specifically, bottom-up and top-down responses are associated with distinct laminar profiles. Here, we measured lamina-resolved fMRI responses during a visual task designed to induce concurrent bottom-up and top-down modulations via orthogonal manipulations of stimulus contrast and feature-based attention. BOLD responses were modulated by both stimulus contrast (bottom-up) and by engaging feature-based attention (top-down). Crucially, these effects operated at different cortical depths: Bottom-up modulations were strongest in the middle cortical layer and weaker in deep and superficial layers, while top-down modulations were strongest in the superficial layers. As such, we demonstrate that laminar activity profiles can discriminate between concurrent top-down and bottom-up processing, and are diagnostic of how a brain region is activated.
Data and code used for stimulus presentation and analysis are available online at the Donders Research Data Repository: https://data.donders.ru.nl/collections/di/dccn/DSC_3018028.04_752
Dissociable laminar profiles of bottom-up and top-down modulation in the human visual cortexDonders Repository, http://hdl.handle.net/11633/di.dccn.DSC_3018028.04_752.
- Floris P de Lange
- Floris P de Lange
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Human subjects: All participants gave written informed consent and the study was approved by the local ethics committees (CMO region Arnhem-Nijmegen, The Netherlands, and ethics committee of the University Duisburg-Essen, Germany). Protocol CMO 2014/288
- Christian Büchel, University Medical Center Hamburg-Eppendorf, Germany
© 2019, Lawrence et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Mathys et al. conducted the first single-nucleus RNA-seq (snRNA-seq) study of Alzheimer’s disease (AD) (Mathys et al., 2019). With bulk RNA-seq, changes in gene expression across cell types can be lost, potentially masking the differentially expressed genes (DEGs) across different cell types. Through the use of single-cell techniques, the authors benefitted from increased resolution with the potential to uncover cell type-specific DEGs in AD for the first time. However, there were limitations in both their data processing and quality control and their differential expression analysis. Here, we correct these issues and use best-practice approaches to snRNA-seq differential expression, resulting in 549 times fewer DEGs at a false discovery rate of 0.05. Thus, this study highlights the impact of quality control and differential analysis methods on the discovery of disease-associated genes and aims to refocus the AD research field away from spuriously identified genes.
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