8
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: not found

      Oscillatory entrainment mechanisms and anticipatory predictive processes in children with autism spectrum disorder

      1 , 2 , 1 , 2 , 3 , 1 , 2 , 3 , 4
      Journal of Neurophysiology
      American Physiological Society

      Read this article at

      ScienceOpenPublisherPubMed
      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

          We examined behavioral and EEG indices of predictive processing in children with ASD to rhythmically predictable stimuli. Although behavioral measures of predictive processing and evoked neural responses were intact in the ASD group, neurophysiological measures of preparatory activity and entrainment were impaired. When sensory events are presented in a predictable temporal pattern, performance and neuronal responses in ASD may be governed more by the occurrence of the events themselves and less by their anticipated timing.

          Abstract

          Anticipating near-future events is fundamental to adaptive behavior, whereby neural processing of predictable stimuli is significantly facilitated relative to nonpredictable events. Neural oscillations appear to be a key anticipatory mechanism by which processing of upcoming stimuli is modified, and they often entrain to rhythmic environmental sequences. Clinical and anecdotal observations have led to the hypothesis that people with autism spectrum disorder (ASD) may have deficits in generating predictions, and as such, a candidate neural mechanism may be failure to adequately entrain neural activity to repetitive environmental patterns, to facilitate temporal predictions. We tested this hypothesis by interrogating temporal predictions and rhythmic entrainment using behavioral and electrophysiological approaches. We recorded high-density electroencephalography in children with ASD and typically developing (TD) age- and IQ-matched controls, while they reacted to an auditory target as quickly as possible. This auditory event was either preceded by predictive rhythmic visual cues or was not preceded by any cue. Both ASD and control groups presented comparable behavioral facilitation in response to the Cue versus No-Cue condition, challenging the hypothesis that children with ASD have deficits in generating temporal predictions. Analyses of the electrophysiological data, in contrast, revealed significantly reduced neural entrainment to the visual cues and altered anticipatory processes in the ASD group. This was the case despite intact stimulus-evoked visual responses. These results support intact behavioral temporal prediction in response to a cue in ASD, in the face of altered neural entrainment and anticipatory processes.

          NEW & NOTEWORTHY We examined behavioral and EEG indices of predictive processing in children with ASD to rhythmically predictable stimuli. Although behavioral measures of predictive processing and evoked neural responses were intact in the ASD group, neurophysiological measures of preparatory activity and entrainment were impaired. When sensory events are presented in a predictable temporal pattern, performance and neuronal responses in ASD may be governed more by the occurrence of the events themselves and less by their anticipated timing.

          Related collections

          Most cited references110

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

          Matplotlib: A 2D Graphics Environment

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

            Silhouettes: A graphical aid to the interpretation and validation of cluster analysis

              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data

              This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages.
                Bookmark

                Author and article information

                Contributors
                Journal
                Journal of Neurophysiology
                Journal of Neurophysiology
                American Physiological Society
                0022-3077
                1522-1598
                November 01 2021
                November 01 2021
                : 126
                : 5
                : 1783-1798
                Affiliations
                [1 ]Department of Pediatrics, The Cognitive Neurophysiology Laboratory, Albert Einstein College of Medicine, Bronx, New York
                [2 ]Department of Neuroscience, Albert Einstein College of Medicine, Bronx, New York
                [3 ]Department of Neuroscience, The Cognitive Neurophysiology Laboratory, The Ernest J. Del Monte Institute for Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York
                [4 ]Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, New York
                Article
                10.1152/jn.00329.2021
                34644178
                c9570e75-6b3b-4627-bd62-3fad80621813
                © 2021
                History

                Comments

                Comment on this article