Towards response success prediction: An integrative approach using high-resolution fMRI and autonomic indices. (October 2018)

• Record Type: Journal Article
• Authors: Köhler, Stefanie; Schumann, Andy; de la Cruz, Feliberto; Wagner, Gerd; Bär, Karl-Jürgen
• Is Part Of: Neuropsychologia. Volume 119(2018)
• Page Start: 182
• Page End: 190
• Publication Date: 2018-10
• Subjects: Response inhibition -- Error processing -- High-resolution functional imaging -- Success prediction -- Ventral tegmental area; Neuropsychology -- Periodicals; Neurology -- Periodicals; Psychophysiology -- Periodicals; Neuropsychologie -- Périodiques; Neuropsychology; Periodicals; Electronic journals; 616.8
• DOI: 10.1016/j.neuropsychologia.2018.08.003
• Languages: English
• ISSNs: 0028-3932

Abstract

Abstract: Brainstem and midbrain nuclei are closely linked to effective cognitive performance and autonomic function. In the present study, we aimed to investigate indices of successful and unsuccessful response inhibition paying particular attention to the interplay between locus coeruleus (LC), ventral tegmental area (VTA)/substantia nigra (SN) and, most importantly, peripheral markers. We aimed to get insight in the predictive value of neural and physiological signals in response inhibition. A total of 35 healthy controls were recruited from the local community and a typical task of behavioral response inhibition (Go/No-Go paradigm) was applied. We used high-resolution fMRI, advanced brainstem analyses and specifically corrected for respiratory signal and cardiac noise. Our main results characterize specific neural activation patterns during successful and unsuccessful response inhibition especially comprising the anterior cingulate as well as the medial and lateral prefrontal cortex. A significant activation of the dopaminergic nuclei (VTA/SN) was found during error processing, but not during response inhibition. Most remarkably, specific neural activation patterns (i.e., dorsal anterior cingulate cortex) as well as accompanying autonomic indices (i.e., skin conductance response (SCR)) were identified to hold predictive information on an individual's performance. In summary, the importance of the VTA/SN during error processing was shown. Furthermore, autonomic indices and specific neural activation patterns may contain valuable information to predict task performance. Highlights: High-resolution fMRI and advanced brainstem analyses. Respiratory signal and cardiac noise correction. Involvement of the dopaminergic neurotransmitter system in error processing. Autonomic parameters contain predictive information on performance. Autonomic indices correlate with brain regions involved in behavioral monitoring.