Stable Task Representations under Attentional Load Revealed with Multivariate Pattern Analysis of Human Brain Activity

Chan, Jason L.; Kucyi, Aaron; DeSouza, Joseph F. X.

doi:10.1162/jocn_a_00819

Cited by 6 publications

(3 citation statements)

References 59 publications

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“…5d; see also (Todd et al 2005;Shulman et al 2007;Asplund et al 2010), nevertheless discriminated the switching rule from the hold rules; its peak classification performance was better than chance, t(13) = 2.26, P < 0.05. This decoding result may fit well with the proposition that the TPJ is involved in evaluating/analyzing the meaning of behaviorally relevant stimuli (Doricchi et al 2010;Geng and Mangun 2011;Chan et al 2015;Vossel et al 2015). Along this vein, a recent study (Lee and McCarthy 2016) demonstrated that the activation pattern in the TPJ correlated across tasks with cognitive demands as varied as biological motion, theory of mind, and attention reorienting.…”

Section: Multivariate Resultssupporting

confidence: 78%

Functional Fractionation of the Cingulo-opercular Network: Alerting Insula and Updating Cingulate

2018

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The anterior insula (AI) and dorsal anterior cingulate cortex (dACC) are engaged in various cognitive and affective processes. An influential account posits that the AI and dACC's ubiquitous engagements reflect their role in the transient capture of attention by salient stimuli. Using fMRI here we tested this claim and functionally dissociated these regions. In the first experiment, we compared these regions' responses to emotion-laden and emotion-neutral salient "oddball" movie events. We found that while the AI only responded transiently to the onset and offset of neutral events, its response to affective events was sustained, challenging the transient attention capture account. By contrast, dACC remained transient regardless of event type. A second experiment distinguished the information encoded by these brain regions with the presentation of behaviorally salient events that require either maintaining the current task set or updating to a different one; the AI was found to signal the presence of the behaviorally relevant events, while the dACC was associated with switching of attention settings in response to the events. We conclude that AI and dACC are involved in signaling the presence of potentially or de facto behaviorally significant events and updating internal attention settings in response to these events, respectively.

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Section: Multivariate Resultssupporting

confidence: 78%

Functional Fractionation of the Cingulo-opercular Network: Alerting Insula and Updating Cingulate

2018

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“…A similar result was observed in the DLPFC, where the classifier decoded the two types of saccades 64.25% of the time. Our findings are at least partially consistent with Chan et al (2015) [ 39 ] who showed that the SVM predicted the saccade type in several cortical regions, among these the FEF and IPS. However, the highest accuracy observed by Chan and colleagues was 57.3% in the FEF and 58.8% in the IPS.…”

Section: Discussion: Cortical Activitysupporting

confidence: 93%

An fMRI Investigation of Preparatory Set in the Human Cerebral Cortex and Superior Colliculus for Pro- and Anti-Saccades

2016

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Previous studies have identified several cortical regions that show larger BOLD responses during preparation and execution of anti-saccades than pro-saccades. We confirmed this finding with a greater BOLD response for anti-saccades than pro-saccades during the preparation phase in the FEF, IPS and DLPFC and in the FEF and IPS in the execution phase. We then applied multi-voxel pattern analysis (MVPA) to establish whether different neural populations are involved in the two types of saccade. Pro-saccades and anti-saccades were reliably decoded during saccade execution in all three cortical regions (FEF, DLPFC and IPS) and in IPS during saccade preparation. This indicates neural specialization, for programming the desired response depending on the task rule, in these regions. In a further study tailored for imaging the superior colliculus in the midbrain a similar magnitude BOLD response was observed for pro-saccades and anti-saccades and the two saccade types could not be decoded with MVPA. This was the case both for activity related to the preparation phase and also for that elicited during the execution phase. We conclude that separate cortical neural populations are involved in the task-specific programming of a saccade while in contrast, the SC has a role in response preparation but may be less involved in high-level, task-specific aspects of the control of saccades.

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“…This might enable fast transfer of abstract rules (Cole et al, 2011) and stable selective attention towards task-relevant information (Zhang et al, 2013). Stable task representations have also been observed under varying attentional loads (Chan, Kucyi, & DeSouza, 2015), further highlighting the context-independent coding of tasks. Thus, our findings of such invariant neural representations do not rule out a dynamic adjustment of task specific neurons, as the adaptive coding hypothesis (Duncan, 2001(Duncan, , 2010Waskom et al, 2014) suggests.…”

Section: Influence Of Switching On Task Representation In Fronto-parimentioning

confidence: 85%

Switch independent task representations in frontal and parietal cortex

Loose

Wisniewski

Rusconi

et al. 2017

Preprint

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Alternating between two tasks is effortful and impairs performance. Previous functional magnetic resonance imaging (fMRI) studies have found increased activity in fronto-parietal cortex when task switching is required. One possibility is that the additional control demands for switch trials are met by strengthening task representations in the human brain. Alternatively, on switch trials the residual representation of the previous task might impede the buildup of a neural task representation. This would predict weaker task representations on switch trials, thus also explaining the performance costs. To test this, participants were cued to perform one of two similar tasks, with the task being repeated or switched between successive trials. MVPA was used to test which regions encode the tasks and whether this encoding differs between switch and repeat trials. As expected, we found information about task representations in frontal and parietal cortex, but there was no difference in the decoding accuracy of task-related information between switch and repeat trials. Using cross-classification we found that the fronto-parietal cortex encodes tasks using a similar spatial pattern in switch and repeat trials. Thus, task representations in frontal and parietal cortex are largely switch-independent. We found no evidence that neural information about task representations in these regions can explain behavioral costs usually associated with task switching. Significance statementAlternating between two tasks is effortful and slows down performance. One possible explanation is that the representations in the human brain need time to build up and are thus weaker on switch trials, explaining performance costs. Alternatively, task representations might even be enhanced in order to overcome the previous task. Here we used a combination of fMRI and a brain classifier to test whether the additional control demands under switching conditions lead to an increased or decreased strength of task representations in fronto-parietal brain regions. We found that task . CC-BY-NC 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

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Stable Task Representations under Attentional Load Revealed with Multivariate Pattern Analysis of Human Brain Activity

Cited by 6 publications

References 59 publications

Functional Fractionation of the Cingulo-opercular Network: Alerting Insula and Updating Cingulate

Functional Fractionation of the Cingulo-opercular Network: Alerting Insula and Updating Cingulate

An fMRI Investigation of Preparatory Set in the Human Cerebral Cortex and Superior Colliculus for Pro- and Anti-Saccades

Switch independent task representations in frontal and parietal cortex

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