Neuromagnetic Decomposition of Social Interaction

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Relationship between activity in human primary motor cortex during action observation and the mirror neuron system

The attenuation of the beta cortical oscillations during action observation has been interpreted as evidence of a mirror neuron system (MNS) in humans. Here we investigated the modulation of beta cortical oscillations with the viewpoint of an observed action. We asked subjects to observe videos of an actor making a variety of arm movements. We show that when subjects were observing arm movements there was a significant modulation of beta oscillations overlying left and right sensorimotor cortices. This pattern of attenuation was driven by the side of the screen on which the observed movement occurred and not by the hand that was observed moving. These results are discussed in terms of the firing patterns of mirror neurons in F5 which have been reported to have similar properties

Relationship between Activity in Human Primary Motor Cortex during Action Observation and the Mirror Neuron System

The attenuation of the beta cortical oscillations during action observation has been interpreted as evidence of a mirror neuron system (MNS) in humans. Here we investigated the modulation of beta cortical oscillations with the viewpoint of an observed action. We asked subjects to observe videos of an actor making a variety of arm movements. We show that when subjects were observing arm movements there was a significant modulation of beta oscillations overlying left and right sensorimotor cortices. This pattern of attenuation was driven by the side of the screen on which the observed movement occurred and not by the hand that was observed moving. These results are discussed in terms of the firing patterns of mirror neurons in F5 which have been reported to have similar properties

Neuromagnetic activation and oscillatory dynamics of stimulus-locked processing during naturalistic viewing

Naturalistic stimuli such as watching a movie while in the scanner provide an ecologically valid paradigm that has the potential of extracting valuable information on how the brain processes complex stimuli in realistic visual and auditory contexts. Naturalistic viewing is also easier to conduct with challenging participant groups including patients and children. Given the high temporal resolution of MEG, in the present study, we demonstrate how a short movie clip can be used to map distinguishable activation and connectivity dynamics underlying the processing of specific classes of visual stimuli such as face and hand manipulations, as well as contrasting activation dynamics for auditory words and non-words. MEG data were collected from 22 healthy volunteers (6 females, 3 left handed, mean age – 27.7 ± 5.28 years) during the presentation of naturalistic audiovisual stimuli. The MEG data were split into trials with the onset of the stimuli belonging to classes of interest (words, non-words, faces, hand manipulations). Based on the components of the averaged sensor ERFs time-locked to the visual and auditory stimulus onset, four and three time-windows, respectively, were defined to explore brain activation dynamics. Pseudo-Z, defined as the ratio of the source-projected time-locked power to the projected noise power for each vertex, was computed and used as a proxy of time-locked brain activation. Statistical testing using the mean-centered Partial Least Squares analysis indicated periods where a given visual or auditory stimuli had higher activation. Based on peak pseudo-Z differences between the visual conditions, time-frequency resolved analyses were performed to assess beta band desynchronization in motor-related areas, and inter-trial phase synchronization between face processing areas. Our results provide the first evidence that activation and connectivity dynamics in canonical brain regions associated with the processing of particular classes of visual and auditory stimuli can be reliably mapped using MEG during presentation of naturalistic stimuli. Given the strength of MEG for brain mapping in temporal and frequency domains, the use of naturalistic stimuli may open new techniques in analyzing brain dynamics during ecologically valid sensation and perception

Quick reorganization of memory traces for morphologically complex words in young children

Formation of neural mechanisms for morphosyntactic processing in young children is still poorly understood. Here, we addressed neural processing and rapid online acquisition of familiar and unfamiliar combinations of morphemes. Three different types of morphologically complex words - derived, inflected, and novel (pseudostem + real suffix) - were presented in a passive listening setting to 16 typically developing 3-4-year old children (as part of a longitudinal Helsinki SLI follow-up study). The mismatch negativity (MMN) component of event-related potentials (ERP), an established index of long-term linguistic memory traces in the brain, was analysed separately for the initial and final periods of the exposure to these items. We found MMN response enhancement for the inflected words towards the end of the recording session, whereas no response change was observed for the derived or novel complex forms. This enhancement indicates rapid build-up of a new memory trace for the combination of real morphemes, suggesting a capacity for online formation of whole-form lexicalized representations as one of the morphological mechanisms in the developing brain. Furthermore, this enhancement increased with age, suggesting the development of automatic morphological processing circuits in the age range of 3-4 years.Peer reviewe

Cognitive Impairments in Schizophrenia as Assessed Through Activation and Connectivity Measures of Magnetoencephalography (MEG) Data

The cognitive dysfunction present in patients with schizophrenia is thought to be driven in part by disorganized connections between higher-order cortical fields. Although studies utilizing electroencephalography (EEG), PET and fMRI have contributed significantly to our understanding of these mechanisms, magnetoencephalography (MEG) possesses great potential to answer long-standing questions linking brain interactions to cognitive operations in the disorder. Many experimental paradigms employed in EEG and fMRI are readily extendible to MEG and have expanded our understanding of the neurophysiological architecture present in schizophrenia. Source reconstruction techniques, such as adaptive spatial filtering, take advantage of the spatial localization abilities of MEG, allowing us to evaluate which specific structures contribute to atypical cognition in schizophrenia. Finally, both bivariate and multivariate functional connectivity metrics of MEG data are useful for understanding how these interactions in the brain are impaired in schizophrenia, and how cognitive and clinical outcomes are affected as a result. We also present here data from our own laboratory that illustrates how some of these novel functional connectivity measures, specifically imaginary coherence (IC), are quite powerful in relating disconnectivity in the brain to characteristic behavioral findings in the disorder

Frontal and superior temporal auditory processing abnormalities in schizophrenia

AbstractBackgroundAlthough magnetoencephalography (MEG) studies show superior temporal gyrus (STG) auditory processing abnormalities in schizophrenia at 50 and 100ms, EEG and corticography studies suggest involvement of additional brain areas (e.g., frontal areas) during this interval. Study goals were to identify 30 to 130ms auditory encoding processes in schizophrenia (SZ) and healthy controls (HC) and group differences throughout the cortex.MethodsThe standard paired-click task was administered to 19 SZ and 21 HC subjects during MEG recording. Vector-based Spatial–temporal Analysis using L1-minimum-norm (VESTAL) provided 4D maps of activity from 30 to 130ms. Within-group t-tests compared post-stimulus 50ms and 100ms activity to baseline. Between-group t-tests examined 50 and 100ms group differences.ResultsBilateral 50 and 100ms STG activity was observed in both groups. HC had stronger bilateral 50 and 100ms STG activity than SZ. In addition to the STG group difference, non-STG activity was also observed in both groups. For example, whereas HC had stronger left and right inferior frontal gyrus activity than SZ, SZ had stronger right superior frontal gyrus and left supramarginal gyrus activity than HC.ConclusionsLess STG activity was observed in SZ than HC, indicating encoding problems in SZ. Yet auditory encoding abnormalities are not specific to STG, as group differences were observed in frontal and SMG areas. Thus, present findings indicate that individuals with SZ show abnormalities in multiple nodes of a concurrently activated auditory network

A multiplex connectivity map of valence-arousal emotional model

high number of studies have already demonstrated an electroencephalography (EEG)-based emotion recognition system with moderate results. Emotions are classified into discrete and dimensional models. We focused on the latter that incorporates valence and arousal dimensions. The mainstream methodology is the extraction of univariate measures derived from EEG activity from various frequencies classifying trials into low/high valence and arousal levels. Here, we evaluated brain connectivity within and between brain frequencies under the multiplexity framework. We analyzed an EEG database called DEAP that contains EEG responses to video stimuli and users’ emotional self-assessments. We adopted a dynamic functional connectivity analysis under the notion of our dominant coupling model (DoCM). DoCM detects the dominant coupling mode per pair of EEG sensors, which can be either within frequencies coupling (intra) or between frequencies coupling (cross-frequency). DoCM revealed an integrated dynamic functional connectivity graph (IDFCG) that keeps both the strength and the preferred dominant coupling mode. We aimed to create a connectomic mapping of valence-arousal map via employing features derive from IDFCG. Our results outperformed previous findings succeeding to predict in a high accuracy participants’ ratings in valence and arousal dimensions based on a flexibility index of dominant coupling modes

Bits from Biology for Computational Intelligence

Computational intelligence is broadly defined as biologically-inspired computing. Usually, inspiration is drawn from neural systems. This article shows how to analyze neural systems using information theory to obtain constraints that help identify the algorithms run by such systems and the information they represent. Algorithms and representations identified information-theoretically may then guide the design of biologically inspired computing systems (BICS). The material covered includes the necessary introduction to information theory and the estimation of information theoretic quantities from neural data. We then show how to analyze the information encoded in a system about its environment, and also discuss recent methodological developments on the question of how much information each agent carries about the environment either uniquely, or redundantly or synergistically together with others. Last, we introduce the framework of local information dynamics, where information processing is decomposed into component processes of information storage, transfer, and modification -- locally in space and time. We close by discussing example applications of these measures to neural data and other complex systems