Recruitment of the default mode network during a demanding act of executive control
- Medical Research Council Cognition and Brain Sciences Unit, United Kingdom
Abstract
In the human brain, a default mode or task-negative network shows reduced activity during many cognitive tasks, and is often associated with internally-directed processes such as mind wandering and thoughts about the self. In contrast to this task-negative pattern, we show increased activity during a large and demanding switch in task set. Furthermore, we employ multi-voxel pattern analysis and find that regions of interest within default mode network are encoding task-relevant information during task performance. Activity in this network may be driven by major revisions of cognitive context, whether internally or externally focused.
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Human subjects: Informed consent, and consent to publish, was obtained through the University of Cambridge ethics committee:CPREC (Cambridge Psychology Research Ethics) 2010.16.
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© 2015, Crittenden 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.
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Recruitment of the default mode network during a demanding act of executive control
eLife 4:e06481.
https://doi.org/10.7554/eLife.06481
Further reading
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- Neuroscience
During rest and sleep, memory traces replay in the brain. The dialogue between brain regions during replay is thought to stabilize labile memory traces for long-term storage. However, because replay is an internally-driven, spontaneous phenomenon, it does not have a ground truth - an external reference that can validate whether a memory has truly been replayed. Instead, replay detection is based on the similarity between the sequential neural activity comprising the replay event and the corresponding template of neural activity generated during active locomotion. If the statistical likelihood of observing such a match by chance is sufficiently low, the candidate replay event is inferred to be replaying that specific memory. However, without the ability to evaluate whether replay detection methods are successfully detecting true events and correctly rejecting non-events, the evaluation and comparison of different replay methods is challenging. To circumvent this problem, we present a new framework for evaluating replay, tested using hippocampal neural recordings from rats exploring two novel linear tracks. Using this two-track paradigm, our framework selects replay events based on their temporal fidelity (sequence-based detection), and evaluates the detection performance using each event's track discriminability, where sequenceless decoding across both tracks is used to quantify whether the track replaying is also the most likely track being reactivated.
