EEG Source Imaging Indices of Cognitive Control Show Associations with Dopamine System Genes.

Cognitive or executive control is a critical mental ability, an important marker of mental illness, and among the most heritable of neurocognitive traits. Two candidate genes, catechol-O-methyltransferase (COMT) and DRD4, which both have a roles in the regulation of cortical dopamine, have been consistently associated with cognitive control. Here, we predicted that individuals with the COMT Met/Met allele would show improved response execution and inhibition as indexed by event-related potentials in a Go/NoGo task, while individuals with the DRD4 7-repeat allele would show impaired brain activity. We used independent component analysis (ICA) to separate brain source processes contributing to high-density EEG scalp signals recorded during the task. As expected, individuals with the DRD4 7-repeat polymorphism had reduced parietal P3 source and scalp responses to response (Go) compared to those without the 7-repeat. Contrary to our expectation, the COMT homozygous Met allele was associated with a smaller frontal P3 source and scalp response to response-inhibition (NoGo) stimuli, suggesting that while more dopamine in frontal cortical areas has advantages in some tasks, it may also compromise response inhibition function. An interaction effect emerged for P3 source responses to Go stimuli. These were reduced in those with both the 7-repeat DRD4 allele and either the COMT Val/Val or the Met/Met homozygous polymorphisms but not in those with the heterozygous Val/Met polymorphism. This epistatic interaction between DRD4 and COMT replicates findings that too little or too much dopamine impairs cognitive control. The anatomic and functional separated maximally independent cortical EEG sources proved more informative than scalp channel measures for genetic studies of brain function and thus better elucidate the complex mechanisms in psychiatric illness

The invisible maze task (IMT): Interactive exploration of sparse virtual environments to investigate action-driven formation of spatial representations

© Springer Nature Switzerland AG 2018. The neuroscientific study of human navigation has been constrained by the prerequisite of traditional brain imaging studies that require participants to remain stationary. Such imaging approaches neglect a central component that characterizes navigation - the multisensory experience of self-movement. Navigation by active movement through space combines multisensory perception with internally generated self-motion cues. We investigated the spatial microgenesis during free ambulatory exploration of interactive sparse virtual environments using motion capture synchronized to high resolution electroencephalographic (EEG) data as well AS psychometric and self-report measures. In such environments, map-like allocentric representations must be constructed out of transient, egocentric first-person perspective 3-D spatial information. Considering individual differences of spatial learning ability, we studied if changes in exploration behavior coincide with spatial learning of an environment. To this end, we analyzed the quality of sketch maps (a description of spatial learning) that were produced after repeated learning trials for differently complex maze environments. We observed significant changes in active exploration behavior from the first to the last exploration of a maze: a decrease in time spent in the maze predicted an increase in subsequent sketch map quality. Furthermore, individual differences in spatial abilities as well as differences in the level of experienced immersion had an impact on the quality of spatial learning. Our results demonstrate converging evidence of observable behavioral changes associated with spatial learning in a framework that allows the study of cortical dynamics of navigation

Familiarity with speech affects cortical processing of auditory distance cues and increases acuity

Several acoustic cues contribute to auditory distance estimation. Nonacoustic cues, including familiarity, may also play a role. We tested participants' ability to distinguish the distances of acoustically similar sounds that differed in familiarity. Participants were better able to judge the distances of familiar sounds. Electroencephalographic (EEG) recordings collected while participants performed this auditory distance judgment task revealed that several cortical regions responded in different ways depending on sound familiarity. Surprisingly, these differences were observed in auditory cortical regions as well as other cortical regions distributed throughout both hemispheres. These data suggest that learning about subtle, distance-dependent variations in complex speech sounds involves processing in a broad cortical network that contributes both to speech recognition and to how spatial information is extracted from speech. © 2012 Wisniewski et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Toward a new cognitive neuroscience: Modeling natural brain dynamics

Decades of brain imaging experiments have revealed important insights into the architecture of the human brain and the detailed anatomic basis for the neural dynamics supporting human cognition. However, technical restrictions of traditional brain imaging approaches including functional magnetic resonance tomography (fMRI), positron emission tomography (PET), and magnetoencephalography (MEG) severely limit participants' movements during experiments. As a consequence, our knowledge of the neural basis of human cognition is rooted in a dissociation of human cognition from what is arguably its foremost, and certainly its evolutionarily most determinant function, organizing our behavior so as to optimize its consequences in our complex, multi-scale, and ever-changing environment. The concept of natural cognition, therefore, should not be separated from our fundamental experience and role as embodied agents acting in a complex, partly unpredictable world. To gain new insights into the brain dynamics supporting natural cognition, we must overcome restrictions of traditional brain imaging technology. First, the sensors used must be lightweight and mobile to allow monitoring of brain activity during free participant movements. New hardware technology for electroencephalography (EEG) and near infrared spectroscopy (NIRS) allows recording electrical and hemodynamic brain activity while participants are freely moving. New data-driven analysis approaches must allow separation of signals arriving at the sensors from the brain and from non-brain sources (neck muscles, eyes, heart, the electrical environment, etc.). Independent component analysis (ICA) and related blind source separation methods allow separation of brain activity from non-brain activity from data recorded during experimental paradigms that stimulate natural cognition. Imaging the precisely timed, distributed brain dynamics that support all forms of our motivated actions and interactions in both laboratory and real-world settings requires new modes of data capture and of data processing. Synchronously recording participants’ motor behavior, brain activity, and other physiology, as well as their physical environment and external events may be termed mobile brain/body imaging ('MoBI'). Joint multi-stream analysis of recorded MoBI data is a major conceptual, mathematical, and data processing challenge. This Research Topic is one result of the first international MoBI meeting in Delmenhorst Germany in September 2013. During an intense workshop researchers from all over the world presented their projects and discussed new technological developments and challenges of this new imaging approach. Several of the presentations are compiled in this Research Topic that we hope may inspire new research using the MoBI paradigm to investigate natural cognition by recording and analyzing the brain dynamics and behavior of participants performing a wide range of naturally motivated actions and interactions

Neurophysiologic Markers of Abnormal Brain Activity in Schizophrenia

Cortical electrophysiologic event-related potentials are multidimensional measures of information processing that are well-suited for efficiently parsing automatic and controlled components of cognition that span the range of deficits evidenced in schizophrenia patients. These information processes are key cognitive measures that are recognized as informative and valid targets for understanding the neurobiology of schizophrenia. These measures may be used in concert with the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) neurocognitive measures in the development of novel treatments for schizophrenia and related neuropsychiatric disorders. The employment of novel event-related potential paradigms designed to carefully characterize the early spectrum of perceptual and cognitive information processing allows investigators to identify the neurophysiologic basis of cognitive dysfunction in schizophrenia and to examine the associated clinical and functional impairments

Two independent frontal midline theta oscillations during conflict detection and adaptation in a Simon-type manual reaching task

© 2017 the authors. One of the most firmly established factors determining the speed of human behavioral responses toward action-critical stimuli is the spatial correspondence between the stimulus and response locations. If both locations match, the time taken for response production is markedly reduced relative to when they mismatch, a phenomenon called the Simon effect. While there is a consensus that this stimulus-response (S-R) conflict is associated with brief (4-7 Hz) frontal midline theta (fmθ) complexes generated in medial frontal cortex, it remains controversial (1) whether there are multiple, simultaneously active theta generator areas in the medial frontal cortex that commonly give rise to conflict-related fmθ complexes; and if so, (2) whether they are all related to the resolution of conflicting task information. Here, we combined mental chronometry with high-density electroencephalographic measures during a Simon-type manual reaching task and used independent component analysis and time-frequency domain statistics on source-level activities to model fmθ sources. During target processing, our results revealed two independent fmθ generators simultaneously active in or near anterior cingulate cortex, only one of them reflecting the correspondence between current and previous S-R locations. However, this fmθ response is not exclusively linked to conflict but also to other, conflict-independent processes associated with response slowing. These results paint a detailed picture regarding the oscillatory correlates of conflict processing in Simon tasks, and challenge the prevalent notion that fmθ complexes induced by conflicting task information represent a unitary phenomenon related to cognitive control, which governs conflict processing across various types of response-override tasks

Attenuated mismatch negativity in patients with first-episode antipsychotic-naive schizophrenia using a source-resolved method

Background: Mismatch negativity (MMN) is a measure of pre-attentive auditory information processing related to change detection. Traditional scalp-level EEG methods consistently find attenuated MMN in patients with chronic but not first-episode schizophrenia. In the current paper, we use a source-resolved method to assess MMN and hypothesize that more subtle changes can be identified with this analysis method. Method: Fifty-six first-episode antipsychotic-naïve schizophrenia (FEANS) patients (31 males, 25 females, mean age 24.6) and 64 matched controls (37 males, 27 females, mean age 24.8) were assessed for duration-, frequency- and combined-type MMN and P3a as well as 4 clinical, 3 cognitive and 3 psychopathological measures. To evaluate and correlate MMN at source-level, independent component analysis (ICA) was applied to the continuous EEG data to derive equivalent current dipoles which were clustered into 19 clusters based on cortical location. Results: No scalp channel group MMN or P3a amplitude differences were found. Of the localized clusters, several were in or near brain areas previously suggested to be involved in the MMN response, including frontal and anterior cingulate cortices and superior temporal and inferior frontal gyri. For duration deviants, MMN was attenuated at the right superior temporal gyrus in patients compared to healthy controls (p = 0.01), as was P3a at the superior frontal cortex (p = 0.01). No individual patient correlations with clinical, cognitive, or psychopathological measures survived correction for multiple comparisons. Conclusion: Attenuated source-localized MMN and P3a peak contributions can be identified in FEANS patients using a method based on independent component analysis (ICA). This indicates that deficits in pre-attentive auditory information processing are present at this early stage of schizophrenia and are not the result of disease chronicity or medication. This is to our knowledge the first study on FEANS patients using this more detailed method. Keywords: Mismatch negativity, Schizophrenia, First episode, EEG, IC

EEG Source Imaging Indices of Cognitive Control Show Associations with Dopamine System Genes

Cognitive or executive control is a critical mental ability, an important marker of mental illness, and among the most heritable of neurocognitive traits. Two candidate genes, catechol-O-methyltransferase (COMT) and DRD4, which both have a roles in the regulation of cortical dopamine, have been consistently associated with cognitive control. Here, we predicted that individuals with the COMT Met/Met allele would show improved response execution and inhibition as indexed by event-related potentials in a Go/NoGo task, while individuals with the DRD4 7-repeat allele would show impaired brain activity. We used independent component analysis (ICA) to separate brain source processes contributing to high-density EEG scalp signals recorded during the task. As expected, individuals with the DRD4 7-repeat polymorphism had reduced parietal P3 source and scalp responses to response (Go) compared to those without the 7-repeat. Contrary to our expectation, the COMT homozygous Met allele was associated with a smaller frontal P3 source and scalp response to response-inhibition (NoGo) stimuli, suggesting that while more dopamine in frontal cortical areas has advantages in some tasks, it may also compromise response inhibition function. An interaction effect emerged for P3 source responses to Go stimuli. These were reduced in those with both the 7-repeat DRD4 allele and either the COMT Val/Val or the Met/Met homozygous polymorphisms but not in those with the heterozygous Val/Met polymorphism. This epistatic interaction between DRD4 and COMT replicates findings that too little or too much dopamine impairs cognitive control. The anatomic and functional separated maximally independent cortical EEG sources proved more informative than scalp channel measures for genetic studies of brain function and thus better elucidate the complex mechanisms in psychiatric illness

Cognition in action: Imaging brain/body dynamics in mobile humans

We have recently developed a mobile brain imaging method (MoBI), that allows for simultaneous recording of brain and body dynamics of humans actively behaving in and interacting with their environment. A mobile imaging approach was needed to study cognitive processes that are inherently based on the use of human physical structure to obtain behavioral goals. This review gives examples of the tight coupling between human physical structure with cognitive processing and the role of supraspinal activity during control of human stance and locomotion. Existing brain imaging methods for actively behaving participants are described and new sensor technology allowing for mobile recordings of different behavioral states in humans is introduced. Finally, we review recent work demonstrating the feasibility of a MoBI system that was developed at the Swartz Center for Computational Neuroscience at the University of California, San Diego, demonstrating the range of behavior that can be investigated with this method. Copyright © 2011 by Walter de Gruyter, Berlin, Boston