Task switching processes reflect a faculty of cognitive flexibility. The underlying neural mechanisms and functional cortical networks have frequently been investigated using neurophysiological (EEG) or functional imaging methods. However, task switching processes are subject to strong intra-individual variability, especially when tested under varying levels of working memory demands. This intra-individual variability compromises the reliable estimation of neurophysiological processes and related functional neuroanatomical networks. In this study, we combine residue iteration decomposition (RIDE) of event-related potentials (ERPs) and source localization methods to circumvent this problem. Due to strong intra-individual variability, behavioral effects between memory-based and cue-based task switching were not reflected by classical ERPs, but were so after applying RIDE. Using RIDE, modulations paralleling the behavioral data were specifically reflected by processes related to the updating of internal representations for response selection (reflected by the C-cluster in the P3-component time range) rather than by stimulus and motor-related processes (reflected by the S-cluster and R-cluster). The C-cluster-processes were associated with activation differences in the inferior parietal cortex, including the temporo-parietal junction (TPJ, BA40) and likely reflect mechanisms related to the updating of internal representations and task sets for response selection. The results underline the necessity to use temporal decomposition methods to control the problem of intra-individual signal variability to decipher the neurophysiology and functional neuroanatomy of cognitive processes.

• MeSH
• Adult MeSH
• Electroencephalography methods   MeSH
• Evoked Potentials MeSH
• Individuality MeSH
• Cognition physiology   MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Cerebral Cortex physiology   MeSH
• Neural Pathways physiology   MeSH
• Memory physiology   MeSH
• Image Processing, Computer-Assisted MeSH
• Signal Processing, Computer-Assisted MeSH
• Cues * MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Sensorimotor integration is essential for successful motor control and the somatosensory modality has been shown to have strong effects on the execution of motor plans. The primary (SI) and the secondary somatosensory (SII) cortices are known to differ in their neuroanatomical connections to prefrontal areas, as well as in their involvement to encode cognitive aspects of tactile processing. Here, we ask whether the area-specific processing architecture or the structural neuroanatomical connections with prefrontal areas determine the efficacy of sensorimotor integration processes for motor control. In a system neurophysiological study including EEG signal decomposition (i.e., residue iteration decomposition, RIDE) and source localization, we investigated this question using vibrotactile stimuli optimized for SI or SII processing. The behavioral data show that when being triggered via the SI area, inhibitory control of motor processes is stronger as when being triggered via the SII area. On a neurophysiological level, these effects were reflected in the C-cluster as a result of a temporal decomposition of EEG data, indicating that the sensory processes affecting motor inhibition modulate the response selection level. These modulations were associated with a stronger activation of the right inferior frontal gyrus extending to the right middle frontal gyrus as parts of a network known to be involved in inhibitory motor control when response inhibition is triggered over SI. In addition, areas important for sensorimotor integration like the postcentral gyrus and superior parietal cortex showed activation differences. The data suggest that connection patterns are more important for sensorimotor integration and control than the more restricted area-specific processing architecture.

• MeSH
• Analysis of Variance MeSH
• Adult MeSH
• Electroencephalography MeSH
• Evoked Potentials physiology   MeSH
• Inhibition, Psychological * MeSH
• Humans MeSH
• Brain Mapping * MeSH
• Adolescent MeSH
• Young Adult MeSH
• Motor Activity physiology   MeSH
• Psychomotor Performance physiology   MeSH
• Cluster Analysis MeSH
• Somatosensory Cortex anatomy & histology   physiology   MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Adolescent MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

The ability to exert cognitive control is a major function of the prefrontal cortex, the efficiency of which depends on the phasic release of norepinephrine (NE) at particular time points. However, different aspects of information are simultaneously processed at any given moment. This raises the question of whether the norepinephrine system is also capable of specifically modulating selected aspects of all ongoing information processing, especially when several of those processes are carried out by the same functional neuroanatomical structure at the same time. We examine this question in humans using a flanker paradigm by integrating neurophysiological (EEG) and pupil diameter data using novel signal processing techniques including Residue Iteration Decomposition (RIDE) and source localization. We show that during conflict monitoring, motor response-related processes are more strongly modulated by the NE system than stimulus-related processes or central decision processes between stimulus and response. This was the case even though these processes occurred at the same time point and were mediated by overlapping medial frontal cortical structures. The results indicate that the NE system exerts specific modulatory effects for different informational contents that are simultaneously processed in the medial frontal cortex.

• MeSH
• Adult MeSH
• Electroencephalography methods   MeSH
• Cognition physiology   MeSH
• Humans MeSH
• Brain Mapping methods   MeSH
• Young Adult MeSH
• Brain physiology   MeSH
• Norepinephrine metabolism   MeSH
• Signal Processing, Computer-Assisted MeSH
• Reflex, Pupillary physiology   MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Due to the high intra-individual variability in attention deficit/hyperactivity disorder (ADHD), there may be considerable bias in knowledge about altered neurophysiological processes underlying executive dysfunctions in patients with different ADHD subtypes. When aiming to establish dimensional cognitive-neurophysiological constructs representing symptoms of ADHD as suggested by the initiative for Research Domain Criteria, it is crucial to consider such processes independent of variability. We examined patients with the predominantly inattentive subtype (attention deficit disorder, ADD) and the combined subtype of ADHD (ADHD-C) in a flanker task measuring conflict control. Groups were matched for task performance. Besides using classic event-related potential (ERP) techniques and source localization, neurophysiological data was also analyzed using residue iteration decomposition (RIDE) to statistically account for intra-individual variability and S-LORETA to estimate the sources of the activations. The analysis of classic ERPs related to conflict monitoring revealed no differences between patients with ADD and ADHD-C. When individual variability was accounted for, clear differences became apparent in the RIDE C-cluster (analog to the P3 ERP-component). While patients with ADD distinguished between compatible and incompatible flanker trials early on, patients with ADHD-C seemed to employ more cognitive resources overall. These differences are reflected in inferior parietal areas. The study demonstrates differences in neuronal mechanisms related to response selection processes between ADD and ADHD-C which, according to source localization, arise from the inferior parietal cortex. Importantly, these differences could only be detected when accounting for intra-individual variability. The results imply that it is very likely that differences in neurophysiological processes between ADHD subtypes are underestimated and have not been recognized because intra-individual variability in neurophysiological data has not sufficiently been taken into account.

• Publication type
• Journal Article MeSH