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Nineteen-channel EEGs were recorded from the scalp surface of 30 healthy subjects (16 males and 14 females, mean age: 34 years, SD: 11.7 years) at rest and under trains of intermittent photic stimulation (IPS) at rates of 5, 10 and 20 Hz. Digitalized data were submitted to spectral analysis with fast fourier transformation providing the basis for the computation of global field power (GFP). For quantification, GFP values in the frequency ranges of 5, 10 and 20 Hz at rest were divided by the corresponding data obtained under IPS. All subjects showed a photic driving effect at each rate of stimulation. GFP data were normally distributed, whereas ratios from photic driving effect data showed no uniform behavior due to high interindividual variability. Suppression of alpha-power after IPS with 10 Hz was observed in about 70% of the volunteers. In contrast, ratios of alpha-power were unequivocal in all subjects: IPS at 20 Hz always led to a suppression of alpha-power. Dividing alpha-GFP with 20-Hz IPS by alpha-GFP at rest (R = a-GFPIPS/a-GFPrest) thus resulted in ratios lower than 1. We conclude that ratios from GFP data with 20-Hz IPS may provide a suitable paradigm for further investigations. Key words: EEG, Brain mapping, Intermittent photic stimulation, IPS, Global field power ratios
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
During meditation, practitioners are required to center their attention on a specific object for extended periods of time. When their thoughts get diverted, they learn to quickly disengage from the distracter. We hypothesized that learning to respond to the dual demand of engaging attention on specific objects and disengaging quickly from distracters enhances the efficiency by which meditation practitioners can allocate attention. We tested this hypothesis in a global-to-local task while measuring electroencephalographic activity from a group of eight highly trained Buddhist monks and nuns and a group of eight age and education matched controls with no previous meditation experience. Specifically, we investigated the effect of attentional training on the global precedence effect, i.e., faster detection of targets on a global than on a local level. We expected to find a reduced global precedence effect in meditation practitioners but not in controls, reflecting that meditators can more quickly disengage their attention from the dominant global level. Analysis of reaction times confirmed this prediction. To investigate the underlying changes in brain activity and their time course, we analyzed event-related potentials. Meditators showed an enhanced ability to select the respective target level, as reflected by enhanced processing of target level information. In contrast with control group, which showed a local target selection effect only in the P1 and a global target selection effect in the P3 component, meditators showed effects of local information processing in the P1, N2, and P3 and of global processing for the N1, N2, and P3. Thus, meditators seem to display enhanced depth of processing. In addition, meditation altered the uptake of information such that meditators selected target level information earlier in the processing sequence than controls. In a longitudinal experiment, we could replicate the behavioral effects, suggesting that meditation modulates attention already after a 4-day meditation retreat. Together, these results suggest that practicing meditation enhances the speed with which attention can be allocated and relocated, thus increasing the depth of information processing and reducing response latency.
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.
Post‐traumatic stress disorder (PTSD) is associated with a hypersensitivity to potential threat. This hypersensitivity manifests through differential patterns of emotional information processing and has been demonstrated in behavioral and neurophysiological experimental paradigms. However, the majority of research has been focused on adult patients with PTSD. To examine possible differences in underlying neurophysiological patterns for adolescent patients with PTSD after childhood sexual and/or physical abuse (CSA/CPA), ERP correlates of emotional word processing in 38 healthy participants and 40 adolescent participants with PTSD after experiencing CSA/CPA were studied. The experimental paradigm consisted of a passive reading task with neutral, positive (e.g., paradise), physically threatening (e.g., torment), and socially threatening (i.e., swearing, e.g., son of a bitch) words. A modulation of P3 amplitudes by emotional valence was found, with positive words inducing less elevated amplitudes over both groups. Interestingly, in later processing, the PTSD group showed augmented early late positive potential (LPP) amplitudes for socially threatening stimuli, while there were no modulations within the healthy control group. Also, region‐specific emotional modulations for anterior and posterior electrode clusters were found. For the anterior LPP, highest activations have been found for positive words, while socially and physically threatening words led to strongest modulations in the posterior LPP cluster. There were no modulations by group or emotional valence at the P1 and EPN stage. The findings suggest an enhanced conscious processing of socially threatening words in adolescent patients with PTSD after CSA/CPA, pointing to the importance of a disjoined examination of threat words in emotional processing research.
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.