10
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Hierarchical Representation of Multistep Tasks in Multiple-Demand and Default Mode Networks

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Task episodes consist of sequences of steps that are performed to achieve a goal. We used fMRI to examine neural representation of task identity, component items, and sequential position, focusing on two major cortical systems—the multiple-demand (MD) and default mode networks (DMN). Human participants (20 males, 22 females) learned six tasks each consisting of four steps. Inside the scanner, participants were cued which task to perform and then sequentially identified the target item of each step in the correct order. Univariate time course analyses indicated that intra-episode progress was tracked by a tonically increasing global response, plus an increasing phasic step response specific to MD regions. Inter-episode boundaries evoked a widespread response at episode onset, plus a marked offset response specific to DMN regions. Representational similarity analysis (RSA) was used to examine representation of task identity and component steps. Both networks represented the content and position of individual steps, however the DMN preferentially represented task identity while the MD network preferentially represented step-level information. Thus, although both MD and DMN networks are sensitive to step-level and episode-level information in the context of hierarchical task performance, they exhibit dissociable profiles in terms of both temporal dynamics and representational content. The results suggest collaboration of multiple brain regions in control of multistep behavior, with MD regions particularly involved in processing the detail of individual steps, and DMN adding representation of broad task context.

          SIGNIFICANCE STATEMENT Achieving one's goals requires knowing what to do and when. Tasks are typically hierarchical, with smaller steps nested within overarching goals. For effective, flexible behavior, the brain must represent both levels. We contrast response time courses and information content of two major cortical systems—the multiple-demand (MD) and default mode networks (DMN)—during multistep task episodes. Both networks are sensitive to step-level and episode-level information, but with dissociable profiles. Intra-episode progress is tracked by tonically increasing global responses, plus MD-specific increasing phasic step responses. Inter-episode boundaries evoke widespread responses at episode onset, plus DMN-specific offset responses. Both networks represent content and position of individual steps; however, the DMN and MD networks favor task identity and step-level information, respectively.

          Related collections

          Most cited references67

          • Record: found
          • Abstract: found
          • Article: not found

          Situating the default-mode network along a principal gradient of macroscale cortical organization.

          Understanding how the structure of cognition arises from the topographical organization of the cortex is a primary goal in neuroscience. Previous work has described local functional gradients extending from perceptual and motor regions to cortical areas representing more abstract functions, but an overarching framework for the association between structure and function is still lacking. Here, we show that the principal gradient revealed by the decomposition of connectivity data in humans and the macaque monkey is anchored by, at one end, regions serving primary sensory/motor functions and at the other end, transmodal regions that, in humans, are known as the default-mode network (DMN). These DMN regions exhibit the greatest geodesic distance along the cortical surface-and are precisely equidistant-from primary sensory/motor morphological landmarks. The principal gradient also provides an organizing spatial framework for multiple large-scale networks and characterizes a spectrum from unimodal to heteromodal activity in a functional metaanalysis. Together, these observations provide a characterization of the topographical organization of cortex and indicate that the role of the DMN in cognition might arise from its position at one extreme of a hierarchy, allowing it to process transmodal information that is unrelated to immediate sensory input.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Repetition and the brain: neural models of stimulus-specific effects.

            One of the most robust experience-related cortical dynamics is reduced neural activity when stimuli are repeated. This reduction has been linked to performance improvements due to repetition and also used to probe functional characteristics of neural populations. However, the underlying neural mechanisms are as yet unknown. Here, we consider three models that have been proposed to account for repetition-related reductions in neural activity, and evaluate them in terms of their ability to account for the main properties of this phenomenon as measured with single-cell recordings and neuroimaging techniques. We also discuss future directions for distinguishing between these models, which will be important for understanding the neural consequences of repetition and for interpreting repetition-related effects in neuroimaging data.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Information-based functional brain mapping.

              The development of high-resolution neuroimaging and multielectrode electrophysiological recording provides neuroscientists with huge amounts of multivariate data. The complexity of the data creates a need for statistical summary, but the local averaging standardly applied to this end may obscure the effects of greatest neuroscientific interest. In neuroimaging, for example, brain mapping analysis has focused on the discovery of activation, i.e., of extended brain regions whose average activity changes across experimental conditions. Here we propose to ask a more general question of the data: Where in the brain does the activity pattern contain information about the experimental condition? To address this question, we propose scanning the imaged volume with a "searchlight," whose contents are analyzed multivariately at each location in the brain.
                Bookmark

                Author and article information

                Journal
                J Neurosci
                jneuro
                jneurosci
                J. Neurosci
                The Journal of Neuroscience
                Society for Neuroscience
                0270-6474
                1529-2401
                30 September 2020
                30 September 2020
                : 40
                : 40
                : 7724-7738
                Affiliations
                [1] 1Medical Research Council, Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, United Kingdom
                [2] 2Department of Experimental Psychology, University of Oxford, Radcliffe Observatory, Oxford OX2 6GG, United Kingdom
                Author notes
                Correspondence should be addressed to Tanya Wen at tanya.wen@ 123456duke.edu

                Author contributions: T.W., J.D., and D.J.M. designed research; T.W. performed research; T.W. and D.J.M. analyzed data; T.W., J.D., and D.J.M. wrote the paper.

                *J.D. and D.J.M. are joint senior authors.

                Author information
                https://orcid.org/0000-0002-4580-7831
                https://orcid.org/0000-0002-9695-2764
                https://orcid.org/0000-0001-8729-3886
                Article
                JN-RM-0594-20
                10.1523/JNEUROSCI.0594-20.2020
                7531550
                32868460
                278b5a53-a29c-43b6-8793-d40c902540a8
                Copyright © 2020 Wen et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License Creative Commons Attribution 4.0 International, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.

                History
                : 12 March 2020
                : 8 July 2020
                : 31 July 2020
                Funding
                Funded by: http://doi.org/10.13039/501100000265Medical Research Council (MRC)
                Award ID: SUAG/045.G101400
                Categories
                Research Articles
                Behavioral/Cognitive

                default mode network,fmri,hierarchy,multiple-demand network,representational similarity analysis,task episodes

                Comments

                Comment on this article