Similar coding of freely chosen and externally cued intentions in a fronto-parietal network

Wisniewski, David; Goschke, Thomas; Haynes, John­–Dylan

doi:10.1016/j.neuroimage.2016.04.044

Cited by 48 publications

(64 citation statements)

References 74 publications

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“…Interestingly, the dmPFC cluster partly overlapped with results from the reward outcome decoding. Additionally, we found a double dissociation in task coding between the right dmPFC and left parietal cortex ( Figure 4B, both ROIs defined a priori from previous experiments 17,29 ), with the former only encoding tasks at the time of decision-making, and the latter only encoding tasks during intention maintenance. An ANOVA using the factors 'time in trial' (time of decision vs intention maintenance) and 'ROI' (right dmPFC vs left parietal cortex) revealed moderate evidence for a time x ROI interaction (BF10 = 5.39).…”

Section: Time Of Decision-makingsupporting

confidence: 53%

“…executing the wrong behavior has no effect on received outcomes (see 13 for a related argument, but 14 ). Previous work demonstrated that implementation of chosen actions, is supported by a brain network including the frontopolar 15 , lateral prefrontal and parietal cortex [16][17][18] . Some initial evidence suggests that rewarding correct performance indeed enhances neural task representations 19 , but this work did not address the issue of varying degrees of control over choice outcomes.…”

Section: Introductionmentioning

confidence: 99%

“…We hypothesized that the lateral prefrontal cortex, and especially the parietal cortex to play a key role in the implementation of chosen behavior. The parietal cortex represents chosen tasks and actions 1,17 , subjective stimulus and action values 21,22 , as well as associations between choice options and their outcomes 23 . Here, we tested whether task representations in these brain regions were enhanced when rewards were choice-contingent vs when they were not.…”

Section: Introductionmentioning

confidence: 99%

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Outcome contingency selectively affects the neural coding of outcomes but not of tasks

Wisniewski

Forstmann

Braß

2018

Preprint

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27Humans make choices every day, which are often intended to lead to desirable outcomes. While we often 28 have some degree of control over the outcomes of our actions, in many cases this control remains limited. 29Here, we investigate the effect of control over outcomes on the neural correlates of outcome valuation 30 and implementation of behavior, as desired outcomes can only be reached if choices are implemented as 31 intended. In a value-based decision-making task, reward outcomes were either contingent on trial-by-trial 32 choices between two different tasks, or were unrelated to these choices. Using fMRI, multivariate pattern 33 analysis, and model-based neuroscience methods, we identified reward representations in a large 34 network including the striatum, dorso-medial prefrontal cortex (dmPFC) and parietal cortex. These 35 representations were amplified when rewards were contingent on subjects' choices. We further assessed 36 the implementation of chosen tasks by identifying brain regions encoding tasks during a preparation or 37 maintenance phase, and found them to be encoded in the dmPFC and parietal cortex. Importantly, 38 outcome contingency did not affect neural coding of chosen tasks. This suggests that controlling choice 39 outcomes selectively affects the neural coding of these outcomes, but has no effect on the means to reach 40 them. Overall, our findings highlight the role of the dmPFC and parietal cortex in processing of value-41 related and task-related information, linking motivational and control-related processes in the brain. 42These findings inform current debates on the neural basis of motivational and cognitive control, as well 43 as their interaction. 44 Significance statement 45We all make hundreds of choices every day, and we want them to have positive consequences. Often, the 46 link between a choice and its outcomes is fairly clear (healthy diet -> lower risk of cardiovascular disease), 47 but we do not always have a high degree of control over the outcomes of our choices (genetic risk factors 48 -> high risk despite a healthy diet). Control over outcomes is a key factor for decision-making, yet its neural 49 correlates remain poorly understood. Here, subjects performed a value-based decision-making task, while 50 we manipulated the degree of control over choice outcomes. We found that more control enhances the 51 neural coding of choice outcomes, but had no effect on the implementation of the chosen behavior. 52 53 . CC-BY 4.0 International license It is made available under a was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

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Section: Time Of Decision-makingsupporting

confidence: 53%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Outcome contingency selectively affects the neural coding of outcomes but not of tasks

Wisniewski

Forstmann

Braß

2018

Preprint

Self Cite

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“…To ensure that the classifier does not reflect neural activity coding low level information of the visual cues, for each speaking condition, there were two visual cues, leading to a total of four conditions for each participants (cf. Reverberi et al , 2012; Wisniewski et al , 2016). …”

Section: Methodsmentioning

confidence: 99%

Brains in dialogue: decoding neural preparation of speaking to a conversational partner

Kuhlen

Bogler

Brennan

et al. 2017

Social Cognitive and Affective Neuroscience

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In dialogue, language processing is adapted to the conversational partner. We hypothesize that the brain facilitates partner-adapted language processing through preparatory neural configurations (task sets) that are tailored to the conversational partner. In this experiment, we measured neural activity with functional magnetic resonance imaging (fMRI) while healthy participants in the scanner (a) engaged in a verbal communication task with a conversational partner outside of the scanner, or (b) spoke outside of a conversational context (to test the microphone). Using multivariate searchlight analysis, we identify cortical regions that represent information on whether speakers plan to speak to a conversational partner or without having a partner. Most notably a region that has been associated with processing social-affective information and perspective taking, the ventromedial prefrontal cortex, as well as regions that have been associated with prospective task representation, the bilateral ventral prefrontal cortex, are involved in encoding the speaking condition. Our results suggest that speakers prepare, in advance of speaking, for the social context in which they will speak.

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“…The development of multivoxel pattern analysis (MVPA) methods (Haxby et al, 2001;Haynes & Rees, 2006; N. Kriegeskorte, Goebel, & Bandettini, 2006) has further led to a variety of findings related to the representation of multiple aspects of cognitive control across the MD network. These include attentional effects, adaptive coding, and coding of target features and task rules (Erez & Duncan, 2015;Etzel, Cole, Zacks, Kay, & Braver, 2016;Nee & Brown, 2012;Nelissen, Stokes, Nobre, & Rushworth, 2013;Wisniewski, Goschke, & Haynes, 2016;Woolgar, Thompson, Bor, & Duncan, 2011).…”

Section: Introductionmentioning

confidence: 99%

Individual-subject functional localization increases univariate activation but not multivariate pattern discriminability in the ‘multiple-demand’ frontoparietal network

Shashidhara

Spronkers

Erez

2019

Preprint

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The frontoparietal 'multiple-demand' (MD) control network plays a key role in goal-directed behavior. Recent developments of multivoxel pattern analysis (MVPA) for fMRI data allows for more fine-grained investigations into the functionality and properties of brain systems. In particular, MVPA in the MD network was used to gain better understanding of control processes such as attentional effects, adaptive coding, and representation of multiple task-relevant features, but its use for this network has been limited by overall low decoding levels. A common practice of applying MVPA is by investigating pattern discriminability within a region-of-interest (ROI) using a template mask, thus ensuring that the same brain areas are studied in all participants. This approach offers high sensitivity, but does not take into account differences between individuals in the spatial organization of brain regions. An alternative approach uses independent localizer data for each subject to select the most responsive voxels and define individual ROIs within the boundaries of a group template. Such an approach allows for a refined and targeted localization based on the unique pattern of activity of individual subjects while ensuring that functionally similar brain regions are studied for all subjects. In the current study we tested whether using individual ROIs leads to changes in decodability of task-related neural representations as well as univariate activity across the MD network compared to when using a group template. We used three localizer tasks to separately define subject-specific ROIs: spatial working memory, verbal working memory, and a Stroop task. We then systematically assessed univariate and multivariate results in a separate rule-based criterion task. All the localizer tasks robustly recruited the MD network and evoked highly reliable activity patterns in individual subjects. Consistent with previous studies, we found a clear benefit of the subject-specific ROIs for univariate results from the criterion task, with increased activity in the individual ROIs based on the localizers' data, compared to the activity observed when using the group template. In contrast, there was no benefit of the subject-specific ROIs, as well as no cost, for multivariate results. Both univariate and multivariate results were similar in the individual ROIs defined by each of the three localizers. Our results provide an important empirical evidence for researchers in the field of cognitive control for the use of individual ROIs in the frontoparietal network 2 for both univariate and multivariate analysis of fMRI data, and serve as another step towards standardization and increased comparability across studies.

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Similar coding of freely chosen and externally cued intentions in a fronto-parietal network

Cited by 48 publications

References 74 publications

Outcome contingency selectively affects the neural coding of outcomes but not of tasks

Outcome contingency selectively affects the neural coding of outcomes but not of tasks

Brains in dialogue: decoding neural preparation of speaking to a conversational partner

Individual-subject functional localization increases univariate activation but not multivariate pattern discriminability in the ‘multiple-demand’ frontoparietal network

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