The neurophysiology of biological motion perception in schizophrenia.

IntroductionThe ability to recognize human biological motion is a fundamental aspect of social cognition that is impaired in people with schizophrenia. However, little is known about the neural substrates of impaired biological motion perception in schizophrenia. In the current study, we assessed event-related potentials (ERPs) to human and nonhuman movement in schizophrenia.MethodsTwenty-four subjects with schizophrenia and 18 healthy controls completed a biological motion task while their electroencephalography (EEG) was simultaneously recorded. Subjects watched clips of point-light animations containing 100%, 85%, or 70% biological motion, and were asked to decide whether the clip resembled human or nonhuman movement. Three ERPs were examined: P1, N1, and the late positive potential (LPP).ResultsBehaviorally, schizophrenia subjects identified significantly fewer stimuli as human movement compared to healthy controls in the 100% and 85% conditions. At the neural level, P1 was reduced in the schizophrenia group but did not differ among conditions in either group. There were no group differences in N1 but both groups had the largest N1 in the 70% condition. There was a condition × group interaction for the LPP: Healthy controls had a larger LPP to 100% versus 85% and 70% biological motion; there was no difference among conditions in schizophrenia subjects.ConclusionsConsistent with previous findings, schizophrenia subjects were impaired in their ability to recognize biological motion. The EEG results showed that biological motion did not influence the earliest stage of visual processing (P1). Although schizophrenia subjects showed the same pattern of N1 results relative to healthy controls, they were impaired at a later stage (LPP), reflecting a dysfunction in the identification of human form in biological versus nonbiological motion stimuli

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 339)

This bibliography lists 105 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during July 1990. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Development of neural responses to hearing their own name in infants at low and high risk for autism spectrum disorder

The own name is a salient stimulus, used by others to initiate social interaction. Typically developing infants orient towards the sound of their own name and exhibit enhanced event-related potentials (ERP) at 5 months. The lack of orientation to the own name is considered to be one of the earliest signs of autism spectrum disorder (ASD). In this study, we investigated ERPs to hearing the own name in infants at high and low risk for ASD, at 10 and 14 months. We hypothesized that low-risk infants would exhibit enhanced frontal ERP responses to their own name compared to an unfamiliar name, while high-risk infants were expected to show attenuation or absence of this difference in their ERP responses. In contrast to expectations, we did not find enhanced ERPs to own name in the low-risk group. However, the high-risk group exhibited attenuated frontal positive-going activity to their own name compared to an unfamiliar name and compared to the low-risk group, at the age of 14 months. These results suggest that infants at high risk for ASD start to process their own name differently shortly after one year of age, a period when frontal brain development is happening at a fast rate

Neurofly 2008 abstracts : the 12th European Drosophila neurobiology conference 6-10 September 2008 Wuerzburg, Germany

This volume consists of a collection of conference abstracts

Electrophysiological markers of predictive coding in multisensory integration and autism spectrum disorder

Publiekssamenvatting De manier waarop we de wereld om ons heen waarnemen is niet alleen gebaseerd op informatie die we via onze zintuigen ontvangen, maar wordt ook gevormd door onze ervaringen uit het verleden. Een recent geïntroduceerde theorie over de verwerking en integratie van sensorische informatie en eerdere ervaringen, de zogeheten predictive coding theorie, gaat ervan uit dat ons brein continu een intern predictiemodel van de wereld om ons heen genereert op basis van informatie die we ontvangen via onze zintuigen en gebeurtenissen die we in het verleden hebben meegemaakt. Het kunnen voorspellen wat we in bepaalde situaties zullen gaan zien, horen, voelen, ruiken en proeven, stelt ons in staat om te anticiperen op sensorische prikkels. Om deze reden reageren we vaak sneller en accurater op voorspelbare sensorische signalen. Op neuraal niveau zijn er ook aanwijzingen gevonden voor de aanwezigheid van een intern predictiemodel. Na het horen van een geluid, bijvoorbeeld van de claxon van een auto, genereert ons brein automatisch elektrische activiteit die met behulp van elektro-encefalografie (EEG) te meten is. Wanneer we datzelfde geluid zelf initiëren, door bijvoorbeeld zelf op de claxon te drukken, kunnen we beter voorspellen wanneer het geluid optreedt en hoe dit ongeveer zal klinken. Deze toename in voorspelbaarheid van het geluid is terug te zien in een vermindering van het EEG signaal. Wanneer we luisteren naar een reeks voorspelbare geluiden waarin onverwacht een geluid wordt weggelaten genereert het brein ook een duidelijk elektrisch signaal, een zogeheten predictie error, dat kan worden gemeten met behulp van EEG. De sterkte van dit signaal wordt verondersteld samen te hangen met de hoeveelheid cognitieve vermogens die aan de onverwachtse verstoring van de voorspelling worden toegewezen. De bevindingen beschreven in dit proefschrift laten zien dat het zelf initiëren van een geluid bij mensen met autisme spectrum stoornis (ASS) niet automatisch resulteert in een afname in elektrische hersenactiviteit. Ook is gevonden dat een plotselinge verstoring in sensorische stimulatie bij mensen met ASS kan resulteren in verhoogde elektrische hersenactiviteit. Deze bevindingen suggereren dat mensen met ASS minder goed in staat lijken te zijn om te anticiperen op sensorische prikkels, en mogelijk meer moeite hebben met de verwerking van onverwachtse verstoringen in sensorische stimulatie. Een verminderd vermogen om te kunnen anticiperen op sensorische prikkels en omgaan met onverwachtse verstoringen in sensorische stimulatie kan niet alleen leiden tot atypische gedragsreacties, waaronder onder- en overgevoeligheid voor sensorische prikkels (symptomen die veel voorkomen bij ASS), maar heeft mogelijk ook gevolgen voor de sociale cognitieve vaardigheden. In sociale situaties is het kunnen anticiperen op hetgeen een ander zegt of doet van cruciaal belang. Het begrijpen van sarcasme vereist bijvoorbeeld de integratie van subtiele verschillen in auditieve (toonhoogte en prosodie) en visuele informatie (gezichtsuitdrukkingen, lichaamstaal). Het juist interpreteren van dergelijke dubbelzinnige sociale signalen is vaak lastig voor mensen met ASS. De bevindingen beschreven in dit proefschrift suggereren dat de oorzaak hiervoor mogelijk ligt in verstoringen in het vermogen om te kunnen anticiperen op sensorische prikkels. Toekomstig onderzoek moet uitwijzen of mensen met ASS ook meer moeite hebben met het anticiperen op sensorische prikkels en verwerken van onverwachtse verstoringen in andere sensorische domeinen. Naast het vergroten van wetenschappelijke kennis over de sensorische informatieverwerking in ASS kan verder onderzoek naar de neurale mechanismen van sensorische anticipatie potentieel leiden tot een elektrofysiologische marker voor ASS die kan worden toegepast als diagnostisch hulpmiddel. Met name voor mensen waarbij de gedragskenmerken niet altijd goed te beoordelen zijn kan een dergelijke biomarker mogelijk als objectief meetinstrument worden ingezet in de klinische praktijk

Cellular Classes in the Human Brain Revealed In Vivo by Heartbeat-Related Modulation of the Extracellular Action Potential Waveform

Determining cell types is critical for understanding neural circuits but remains elusive in the living human brain. Current approaches discriminate units into putative cell classes using features of the extracellular action potential (EAP); in absence of ground truth data, this remains a problematic procedure. We find that EAPs in deep structures of the brain exhibit robust and systematic variability during the cardiac cycle. These cardiac-related features refine neural classification. We use these features to link bio-realistic models generated from in vitro human whole-cell recordings of morphologically classified neurons to in vivo recordings. We differentiate aspiny inhibitory and spiny excitatory human hippocampal neurons and, in a second stage, demonstrate that cardiac-motion features reveal two types of spiny neurons with distinct intrinsic electrophysiological properties and phase-locking characteristics to endogenous oscillations. This multi-modal approach markedly improves cell classification in humans, offers interpretable cell classes, and is applicable to other brain areas and species

Detecting the neural correlates of episodic memory with mobile EEG: Recollecting objects in the real world

Episodic memory supports recognition of the details of complex real world experiences, providing a continuous record of events embedded within spatial and temporal context. Despite the inherently dynamic nature of real events, the bulk of neuroscientific research to date examines recognition in absence of the detailed contextual information that is known to be a defining characteristic. Given the importance of environmental context for episodic memory, examining ERP correlates of memory in more naturalistic settings is vital for progress in understanding how retrieval operates in daily life. The current study capitalized on recent advances in mobile EEG technology to address this issue and is the first to investigate ERP correlates of episodic retrieval in real world contexts. Participants were guided around a pre-defined route inside a building on campus, while performing a recognition memory task, which paired images of objects with actual physical locations in the building to provide context. Importantly, the findings clearly demonstrate that it is possible to observe reliable neural correlates of memory in real world contexts. Replicating two well established ERP correlates of episodic retrieval reported in prior laboratory based studies, we detected FN400 old/new effects traditionally associated with familiarity between 300 and 500 ms, and a late posterior negativity (LPN) often linked to reconstructive processing or evaluation of retrieval outcomes between 500 and 800 ms. Moreover, the FN400 effect was found to be sensitive to retrieval of context, with more sustained effects for objects encountered in a different context at study and test. Overall, the current work highlights the power of mobile EEG technology for examining complex cognitive functions in more naturalistic real world settings

Exploring and explaining properties of motion processing in biological brains using a neural network

Visual motion perception underpins behaviours ranging from navigation to depth perception and grasping. Our limited access to biological systems constrain our understanding of how motion is processed within the brain. Here we explore properties of motion perception in biological systems by training a neural network to estimate the velocity of image sequences. The network recapitulates key characteristics of motion processing in biological brains, and we use our access to its structure to explore and understand motion (mis)perception. We find that the network captures the biological response to reverse-phi motion in terms of direction. We further find that it overestimates and underestimates the speed of slow and fast reverse-phi motion, respectively, because of the correlation between reverse-phi motion and the spatiotemporal receptive fields tuned to motion in opposite directions. Second, we find that the distribution of spatiotemporal tuning properties in the V1 and MT layers of the network are similar to those observed in biological systems. We then show that compared to MT units tuned to fast speeds, those tuned to slow speeds primarily receive input from V1 units tuned to high spatial frequency and low temporal frequency. Next, we find that there is a positive correlation between the pattern-motion and speed selectivity of MT units. Finally, we show that the network captures human underestimation of low coherence motion stimuli, and that this is due to pooling of noise and signal motion. These findings provide biologically plausible explanations for well-known phenomena, and produce concrete predictions for future psychophysical and neurophysiological experiments