Conflict detection in sensory input is central to adaptive human behavior. Perhaps unsurprisingly, past research has shown that conflict may even be detected in absence of conflict awareness, suggesting that conflict detection is an automatic process that does not require attention. To test the possibility of conflict processing in the absence of attention, we manipulated task relevance and response overlap of potentially conflicting stimulus features across six behavioral tasks. Multivariate analyses on human electroencephalographic data revealed neural signatures of conflict only when at least one feature of a conflicting stimulus was attended, regardless of whether that feature was part of the conflict, or overlaps with the response. In contrast, neural signatures of basic sensory processes were present even when a stimulus was completely unattended. These data reveal an attentional bottleneck at the level of objects, suggesting that object-based attention is a prerequisite for cognitive control operations involved in conflict detection.
The data and analysis scripts used in this article is available on Figshare https://uvaauas.figshare.com/projects/Preserved_sensory_processing_but_hampered_conflict_detection_when_stimulus_input_is_task-irrelevant/115020
Analyses scripts for manuscript: Preserved sensory processing but hampered conflict detection when stimulus input is task-irrelevantFigshare, https://doi.org/10.21942/uva.14730297.v1.
Raw behavioral dataset for manuscript: Preserved sensory processing but hampered conflict detection when stimulus input is task-irrelevantFigshare, https://doi.org/10.21942/uva.14730396.v1.
Decoded EEG (time-frequency) dataset for manuscript: Preserved sensory processing but hampered conflict detection when stimulus input is task-irrelevantFigshare, https://doi.org/10.21942/uva.14730402.v1.
Decoded EEG (time-domain) dataset for manuscript: Preserved sensory processing but hampered conflict detection when stimulus input is task-irrelevantFigshare, https://doi.org/10.21942/uva.14754870.v1.
Raw EEG dataset for manuscript: Preserved sensory processing but hampered conflict detection when stimulus input is task-irrelevantFigshare, https://doi.org/10.21942/uva.14709420.v1.
- Simon van Gaal
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Human subjects: Written informed consent was obtained from all participants after explanation of the experimental protocol. This study was approved by the local ethics committee of the University of Amsterdam (projects: 2015-BC-4687, 2017-BC-8257, 2019-BC-10711).
- Nicole C Swann, University of Oregon, United States
© 2021, Nuiten 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.
The strength of a fear memory significantly influences whether it drives adaptive or maladaptive behavior in the future. Yet, how mild and strong fear memories differ in underlying biology is not well understood. We hypothesized that this distinction may not be exclusively the result of changes within specific brain regions, but rather the outcome of collective changes in connectivity across multiple regions within the neural network. To test this, rats were fear conditioned in protocols of varying intensities to generate mild or strong memories. Neuronal activation driven by recall was measured using c-fos immunohistochemistry in 12 brain regions implicated in fear learning and memory. The interregional coordinated brain activity was computed and graph-based functional networks were generated to compare how mild and strong fear memories differ at the systems level. Our results show that mild fear recall is supported by a well-connected brain network with small-world properties in which the amygdala is well-positioned to be modulated by other regions. In contrast, this connectivity is disrupted in strong fear memories and the amygdala is isolated from other regions. These findings indicate that the neural systems underlying mild and strong fear memories differ, with implications for understanding and treating disorders of fear dysregulation.