150 Psychologie
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Das ereigniskorrelierte Potential (EKP) P300 ist eines der am häufigsten untersuchten Potentiale des Elektroenzephalogramms (EEG). Wegen der bedeutsamen Rolle der P300 in der kognitiven Forschung mit gesunden Probanden und psychiatrischen Patienten kommt der Suche nach ihren neuronalen Generatoren ein hoher Stellenwert zu. Man geht im Allgemeinen davon aus, dass sie kein einheitliches Potential darstellt und von mehreren weit verstreuten Quellen generiert wird. Die Fragen nach der genauen Anzahl der P300-Subkomponenten, ihrer Lokalisierung sowie den ihnen zugrunde liegenden kognitiven Prozesse sind jedoch nach wie vor ungelöst. Die Zielsetzung der vorliegenden Arbeit war, die P300 mit Hilfe der Kombination vom EEG und der funktionalen Magnetresonanztomografie (fMRT) in ihre Subkomponenten zu untergliedern und deren Quellen zu lokalisieren. Zu diesem Zweck wurden drei kombinierte EEG/fMRT-Studien durchgeführt. Die ersten beiden Studien beinhalten eine abgewandelte Form des klassischen Oddballparadigmas. Bei der dritten Studie handelt es sich um ein Arbeitsgedächtnisexperiment. Durch die Verknüpfung der fMRT-Ergebnisse mit EKP-Daten aus den beiden Oddball-Experimenten konnten die neuronalen Quellen der zwei wichtigsten Subkomponenten der P300, der P3a und P3b, lokalisiert werden. Es konnte gezeigt werden, dass inferiore und posteriore parietale (IPL bzw. PPC) und inferior temporale (IT) Areale zur Entstehung der P3b beitrugen, während hauptsächlich die präzentralen Regionen (PrCS) die P3a generierten. Die Ergebnisse des Arbeitsgedächtnisexperiments bestätigten die P3b-Quellenlokalisierung der Oddball-Untersuchung mit einr Beteiligung von PPC und IT an der Generierung der P3b-Komponente. Das Arbeitsgedächtnisexperiment verdeutlichte aber auch, dass eine komplexere Abrufanforderung (mit langen Reaktionszeiten) zu einer anhaltenden Aktivität im PPC und einer späten Antwort im ventrolateralen präfrontalen Kortex (VLPFC) führte, die eine zweite P3b-Subkomponente generierten. Durch eine umfassende zeitlich-räumliche Trennung der neuronalen Aktivität beim Arbeitsgedächtnisabruf konnten darüber hinaus die einzelnen Stufen der beteiligten Informationsverarbeitungsprozesse (mentale Chronometrie) beschrieben werden. Diese Anwendung ging über die „reine“ Quellenlokalisation der P300-Komponenten hinaus. Die Ergebnisse zeigten frühe transiente Aktivierungen im IT, die sich zeitlich mit dem Beginn einer anhaltenden Aktivität im PPC überlappten. Darüber hinaus wurden eine späte transiente Aktivität im VLPFC und eine späte anhaltende Aktivität im medialen frontalen und motorischen Kortex (MFC bzw. MC) beobachtet. Es liegt nahe, dass diese neuronalen Signaturen einzelne Stufen kognitiver Aufgabenverarbeitungsschritte wie Reizevaluation (IT), Operationen am Gedächtnispuffer (PPC), aktiven Abruf (VLPFC) und Reaktionsorganisation (MFC und MC) reflektieren. Die vorgestellten Quellenmodelle zeigten übereinstimmend, dass mehrere kortikale Generatoren das P300-EKP erzeugen. Dabei trugen neben den erwarteten parietalen interessanterweise auch inferior temporale und inferior frontale Quellen zur P3b bei, während die P3a vor allem auf anterioren Generatoren im prämotorischen Kortex basierte. Diese Ergebnisse bestätigen teilweise die bisherigen Lokalisationsmodelle, die weitgehend auf neuropsychologischen und invasiven neurophysiologischen Befunden beruhen, widersprechen ihnen aber auch zum Teil, besonders was die Abwesenheit der postulierten präfrontalen und hippocampalen Beiträge zur P3a bzw. P3b betrifft.
Die Wahrnehmung von Objekten gelingt uns jeden Tag unzählige Male – zumeist rasend schnell und problemlos. Obwohl fast immer mehrere unserer Sinne gleichzeitig bei ihrer Wahrnehmung angesprochen werden, erscheinen uns diese Objekte dennoch als ganzheitlich und geschlossen. Für die neuronale Verarbeitung eines bellenden Hundes zum Beispiel empfängt die Großhirnrinde zumindest Eingangsdaten des Seh- und des Hörsystems. Sie werden auf getrennten Pfaden und in spezialisierten Arealen mit aufsteigender Komplexität analysiert. Dieses Funktionsprinzip der parallel verteilten Verarbeitung stellt die Wissenschaftler aber auch vor das so genannte »Bindungsproblem«: Wo und wie werden die Details wieder zu einem Ganzen – zu einer neuronalen Repräsentation – zusammengefügt? Am Institut für medizinische Psychologie der Universitätsklinik Frankfurt untersuchen Neurokognitionsforscher die crossmodale Objekterkennung mit einer Kombination modernster Verfahren der Hirnforschung und kommen dabei den Ver - arbeitungspfaden in der Großhirnrinde auf die Spur.
We examined the neural signatures of stimulus features in visual working memory (WM) by integrating functional magnetic resonance imaging (fMRI) and event-related potential data recorded during mental manipulation of colors, rotation angles, and color–angle conjunctions. The N200, negative slow wave, and P3b were modulated by the information content of WM, and an fMRI-constrained source model revealed a progression in neural activity from posterior visual areas to higher order areas in the ventral and dorsal processing streams. Color processing was associated with activity in inferior frontal gyrus during encoding and retrieval, whereas angle processing involved right parietal regions during the delay interval. WM for color–angle conjunctions did not involve any additional neural processes. The finding that different patterns of brain activity underlie WM for color and spatial information is consistent with ideas that the ventral/dorsal “what/where” segregation of perceptual processing influences WM organization. The absence of characteristic signatures of conjunction-related brain activity, which was generally intermediate between the 2 single conditions, suggests that conjunction judgments are based on the coordinated activity of these 2 streams. Keywords: EEG, fMRI, source analysis, visual, working memory
Human deep sleep is characterized by reduced sensory activity, responsiveness to stimuli, and conscious awareness. Given its ubiquity and reversible nature, it represents an attractive paradigm to study the neural changes which accompany the loss of consciousness in humans. In particular, the deepest stages of sleep can serve as an empirical test for the predictions of theoretical models relating the phenomenology of consciousness with underlying neural activity. A relatively recent shift of attention from the analysis of evoked responses toward spontaneous (or “resting state”) activity has taken place in the neuroimaging community, together with the development of tools suitable to study distributed functional interactions. In this review we focus on recent functional Magnetic Resonance Imaging (fMRI) studies of spontaneous activity during sleep and their relationship with theoretical models for human consciousness generation, considering the global workspace theory, the information integration theory, and the dynamical core hypothesis. We discuss the venues of research opened by these results, emphasizing the need to extend the analytic methodology in order to obtain a dynamical picture of how functional interactions change over time and how their evolution is modulated during different conscious states. Finally, we discuss the need to experimentally establish absent or reduced conscious content, even when studying the deepest sleep stages.
Dreams and psychosis share several important features regarding symptoms and underlying neurobiology, which is helpful in constructing a testable model of, for example, schizophrenia and delirium. The purpose of the present communication is to discuss two major concepts in dreaming and psychosis that have received much attention in the recent literature: insight and dissociation. Both phenomena are considered functions of higher order consciousness because they involve metacognition in the form of reflective thought and attempted control of negative emotional impact. Insight in dreams is a core criterion for lucid dreams. Lucid dreams are usually accompanied by attempts to control the dream plot and dissociative elements akin to depersonalization and derealization. These concepts are also relevant in psychotic illness. Whereas insightfulness can be considered innocuous in lucid dreaming and even advantageous in psychosis, the concept of dissociation is still unresolved. The present review compares correlates and functions of insight and dissociation in lucid dreaming and psychosis. This is helpful in understanding the two concepts with regard to psychological function as well as neurophysiology.
Neural pattern similarity differentially relates to memory performance in younger and older adults
(2019)
Age-related memory decline is associated with changes in neural functioning, but little is known about how aging affects the quality of information representation in the brain. Whereas a long-standing hypothesis of the aging literature links cognitive impairments to less distinct neural representations in old age (“neural dedifferentiation”), memory studies have shown that overlapping neural representations of different studied items are beneficial for memory performance. In an electroencephalography (EEG) study, we addressed the question whether distinctiveness or similarity between patterns of neural activity supports memory differentially in younger and older adults. We analyzed between-item neural pattern similarity in 50 younger (19–27 years old) and 63 older (63–75 years old) male and female human adults who repeatedly studied and recalled scene–word associations using a mnemonic imagery strategy. We compared the similarity of spatiotemporal EEG frequency patterns during initial encoding in relation to subsequent recall performance. The within-person association between memory success and pattern similarity differed between age groups: For older adults, better memory performance was linked to higher similarity early in the encoding trials, whereas young adults benefited from lower similarity between earlier and later periods during encoding, which might reflect their better success in forming unique memorable mental images of the joint picture–word pairs. Our results advance the understanding of the representational properties that give rise to subsequent memory, as well as how these properties may change in the course of aging.
How is semantic information stored in the human mind and brain? Some philosophers and cognitive scientists argue for vectorial representations of concepts, where the meaning of a word is represented as its position in a high-dimensional neural state space. At the intersection of natural language processing and artificial intelligence, a class of very successful distributional word vector models has developed that can account for classic EEG findings of language, that is, the ease versus difficulty of integrating a word with its sentence context. However, models of semantics have to account not only for context-based word processing, but should also describe how word meaning is represented. Here, we investigate whether distributional vector representations of word meaning can model brain activity induced by words presented without context. Using EEG activity (event-related brain potentials) collected while participants in two experiments (English and German) read isolated words, we encoded and decoded word vectors taken from the family of prediction-based Word2vec algorithms. We found that, first, the position of a word in vector space allows the prediction of the pattern of corresponding neural activity over time, in particular during a time window of 300 to 500 ms after word onset. Second, distributional models perform better than a human-created taxonomic baseline model (WordNet), and this holds for several distinct vector-based models. Third, multiple latent semantic dimensions of word meaning can be decoded from brain activity. Combined, these results suggest that empiricist, prediction-based vectorial representations of meaning are a viable candidate for the representational architecture of human semantic knowledge.
Most current models assume that the perceptual and cognitive processes of visual word recognition and reading operate upon neuronally coded domain-general low-level visual representations – typically oriented line representations. We here demonstrate, consistent with neurophysiological theories of Bayesian-like predictive neural computations, that prior visual knowledge of words may be utilized to ‘explain away’ redundant and highly expected parts of the visual percept. Subsequent processing stages, accordingly, operate upon an optimized representation of the visual input, the orthographic prediction error, highlighting only the visual information relevant for word identification. We show that this optimized representation is related to orthographic word characteristics, accounts for word recognition behavior, and is processed early in the visual processing stream, i.e., in V4 and before 200 ms after word-onset. Based on these findings, we propose that prior visual-orthographic knowledge is used to optimize the representation of visually presented words, which in turn allows for highly efficient reading processes.
Based on Eysenck’s biopsychological trait theory, brain arousal has long been considered to explain individual differences in human personality. Yet, results from empirical studies remained inconclusive. However, most published results have been derived from small samples and, despite inherent limitations, EEG alpha power has usually served as an exclusive indicator for brain arousal. To overcome these problems, we here selected N = 468 individuals of the LIFE-Adult cohort and investigated the associations between the Big Five personality traits and brain arousal by using the validated EEG- and EOG-based analysis tool VIGALL. Our analyses revealed that participants who reported higher levels of extraversion and openness to experience, respectively, exhibited lower levels of brain arousal in the resting state. Bayesian and frequentist analysis results were especially convincing for openness to experience. Among the lower-order personality traits, we obtained the strongest evidence for neuroticism facet ‘impulsivity’ and reduced brain arousal. In line with this, both impulsivity and openness have previously been conceptualized as aspects of extraversion. We regard our findings as well in line with the postulations of Eysenck and consistent with the recently proposed ‘arousal regulation model’. Our results also agree with meta-analytically derived effect sizes in the field of individual differences research, highlighting the need for large (collaborative) studies.
Intention attribution in children and adolescents with autism spectrum disorder: an EEG study
(2021)
The ability to infer intentions from observed behavior and predict actions based on this inference, known as intention attribution (IA), has been hypothesized to be impaired in individuals with autism spectrum disorder (ASD). The underlying neural processes, however, have not been conclusively determined. The aim of this study was to examine the neural signature of IA in children and adolescents with ASD, and to elucidate potential links to contextual updating processes using electroencephalography. Results did not indicate that IA or early contextual updating was impaired in ASD. However, there was evidence of aberrant processing of expectation violations in ASD, particularly if the expectation was based on IA. Results are discussed within the context of impaired predictive coding in ASD.