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Speech production involves widely distributed brain regions. This MEG study focuses on the spectro-temporal dynamics that contribute to the setup of this network. In 21 participants performing a cue-target reading paradigm, we analyzed local oscillations during preparation for overt and covert reading in the time-frequency domain and localized sources using beamforming. Network dynamics were studied by comparing different dynamic causal models of beta phase coupling in and between hemispheres. While a broadband low frequency effect was found for any task preparation in bilateral prefrontal cortices, preparation for overt speech production was specifically associated with left-lateralized alpha and beta suppression in temporal cortices and beta suppression in motor-related brain regions. Beta phase coupling in the entire speech production network was modulated by anticipation of overt reading. We propose that the processes underlying the setup of the speech production network connect relevant brain regions by means of beta synchronization and prepare the network for left-lateralized information routing by suppression of inhibitory alpha and beta oscillations.

Little is known about the spatiotemporal dynamics of cortical responses that integrate slightly asynchronous somatosensory inputs from both hands. This study aimed to clarify the timing and magnitude of interhemispheric interactions during early integration of bimanual somatosensory information in different somatosensory regions and their relevance for bimanual object manipulation and exploration. Using multi-fiber probabilistic diffusion tractography and MEG source analysis of conditioning-test (C-T) median nerve somatosensory evoked fields in healthy human subjects, we sought to extract measures of structural and effective callosal connectivity between different somatosensory cortical regions and correlated them with bimanual tactile task performance. Neuromagnetic responses were found in major somatosensory regions, i.e., primary somatosensory cortex SI, secondary somatosensory cortex SII, posterior parietal cortex, and premotor cortex. Contralateral to the test stimulus, SII activity was maximally suppressed by 51% at C-T intervals of 40 and 60 ms. This interhemispheric inhibition of the contralateral SII source activity correlated directly and topographically specifically with the fractional anisotropy of callosal fibers interconnecting SII. Thus, the putative pathway that mediated inhibitory interhemispheric interactions in SII was a transcallosal route from ipsilateral to contralateral SII. Moreover, interhemispheric inhibition of SII source activity correlated directly with bimanual tactile task performance. These findings were exclusive to SII. Our data suggest that early interhemispheric somatosensory integration primarily occurs in SII, is mediated by callosal fibers that interconnect homologous SII areas, and has behavioral importance for bimanual object manipulation and exploration.

Event-related potentials (ERPs) are widely used in basic neuroscience and in clinical diagnostic procedures. In contrast, neurophysiological insights from ERPs have been limited, as several different mechanisms lead to ERPs. Apart from stereotypically repeated responses (additive evoked responses), these mechanisms are asymmetric amplitude modulations and phase-resetting of ongoing oscillatory activity. Therefore, a method is needed that differentiates between these mechanisms and moreover quantifies the stability of a response. We propose a constrained subspace independent component analysis that exploits the multivariate information present in the all-to-all relationship of recordings over trials. Our method identifies additive evoked activity and quantifies its stability over trials. We evaluate identification performance for biologically plausible simulation data and two neurophysiological test cases: Local field potential (LFP) recordings from a visuo-motor-integration task in the awake behaving macaque and magnetoencephalography (MEG) recordings of steady-state visual evoked fields (SSVEFs). In the LFPs we find additive evoked response contributions in visual areas V2/4 but not in primary motor cortex A4, although visually triggered ERPs were also observed in area A4. MEG-SSVEFs were mainly created by additive evoked response contributions. Our results demonstrate that the identification of additive evoked response contributions is possible both in invasive and in non-invasive electrophysiological recordings., (Copyright © 2011 Elsevier Inc. All rights reserved.)

To understand the function of networks we have to identify the structure of their interactions, but also interaction timing, as compromised timing of interactions may disrupt network function. We demonstrate how both questions can be addressed using a modified estimator of transfer entropy. Transfer entropy is an implementation of Wiener's principle of observational causality based on information theory, and detects arbitrary linear and non-linear interactions. Using a modified estimator that uses delayed states of the driving system and independently optimized delayed states of the receiving system, we show that transfer entropy values peak if the delay of the state of the driving system equals the true interaction delay. In addition, we show how reconstructed delays from a bivariate transfer entropy analysis of a network can be used to label spurious interactions arising from cascade effects and apply this approach to local field potential (LFP) and magnetoencephalography (MEG) data.

Lying is a pervasive phenomenon with important social and economic implications. However, despite substantial interest in the prevalence and determinants of lying, little is known about its biological foundations. Here we study a potential hormonal influence, focusing on the steroid hormone testosterone, which has been shown to play an important role in social behavior. In a double-blind placebo-controlled study, 91 healthy men (24.32±2.73 years) received a transdermal administration of 50 mg of testosterone (n=46) or a placebo (n=45). Subsequently, subjects participated in a simple task, in which their payoff depended on the self-reported outcome of a die-roll. Subjects could increase their payoff by lying without fear of being caught. Our results show that testosterone administration substantially decreases lying in men. Self-serving lying occurred in both groups, however, reported payoffs were significantly lower in the testosterone group (p<0.01). Our results contribute to the recent debate on the effect of testosterone on prosocial behavior and its underlying channels.

Frequency modulations (FM) play a decisive role in our everyday communication. To investigate the processing of FM direction we measured change-related auditory cortex responses with human magnetoencephalography. First, we tested for FM direction selectivity by presenting FM sweeps with the same FM directions in a repeated series (RS). These series were interrupted by a deviant with the opposite FM direction. Second, we tested for the representation of abstract rules and presented series of FM sweeps with alternating FM directions (AS). The AS series were interrupted by a deviant which was a repetition of the series' last FM sweep but broke the alternating pattern. For the RS, the deviant did not evoke significant change-related responses in the auditory cortex. However, for the first stimulus after the deviant, significantly stronger responses compared to standards were observed bilaterally in the auditory cortex at about 200 ms after stimulus onset. For the AS, we observed a similar bilateral change-related signal enhancement for a deviant FM sweep breaking the alternating series. Since this response enhancement occurred for both RS and AS even after a single FM sweep repetition, we conclude that these activities represent local signal enhancements rather than change-related responses due to abstract rule violation. In sum, our data indicate repetition enhancement due to spectro-temporal interactions between successive complex FM sweeps. These enhancement effects were observed for the first but not further repetitions suggesting a second-order repetition suppression of the initial repetition enhancement., (Copyright © 2011 Elsevier B.V. All rights reserved.)

Background: Transfer entropy (TE) is a measure for the detection of directed interactions. Transfer entropy is an information theoretic implementation of Wiener's principle of observational causality. It offers an approach to the detection of neuronal interactions that is free of an explicit model of the interactions. Hence, it offers the power to analyze linear and nonlinear interactions alike. This allows for example the comprehensive analysis of directed interactions in neural networks at various levels of description. Here we present the open-source MATLAB toolbox TRENTOOL that allows the user to handle the considerable complexity of this measure and to validate the obtained results using non-parametrical statistical testing. We demonstrate the use of the toolbox and the performance of the algorithm on simulated data with nonlinear (quadratic) coupling and on local field potentials (LFP) recorded from the retina and the optic tectum of the turtle (Pseudemys scripta elegans) where a neuronal one-way connection is likely present., Results: In simulated data TE detected information flow in the simulated direction reliably with false positives not exceeding the rates expected under the null hypothesis. In the LFP data we found directed interactions from the retina to the tectum, despite the complicated signal transformations between these stages. No false positive interactions in the reverse directions were detected., Conclusions: TRENTOOL is an implementation of transfer entropy and mutual information analysis that aims to support the user in the application of this information theoretic measure. TRENTOOL is implemented as a MATLAB toolbox and available under an open source license (GPL v3). For the use with neural data TRENTOOL seamlessly integrates with the popular FieldTrip toolbox.

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis.

The analysis of cortical and subcortical networks requires the identification of their nodes, and of the topology and dynamics of their interactions. Exploratory tools for the identification of nodes are available, e.g. magnetoencephalography (MEG) in combination with beamformer source analysis. Competing network topologies and interaction models can be investigated using dynamic causal modelling. However, we lack a method for the exploratory investigation of network topologies to choose from the very large number of possible network graphs. Ideally, this method should not require a pre-specified model of the interaction. Transfer entropy--an information theoretic implementation of Wiener-type causality--is a method for the investigation of causal interactions (or information flow) that is independent of a pre-specified interaction model. We analysed MEG data from an auditory short-term memory experiment to assess whether the reconfiguration of networks implied in this task can be detected using transfer entropy. Transfer entropy analysis of MEG source-level signals detected changes in the network between the different task types. These changes prominently involved the left temporal pole and cerebellum--structures that have previously been implied in auditory short-term or working memory. Thus, the analysis of information flow with transfer entropy at the source-level may be used to derive hypotheses for further model-based testing., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

γ-band oscillations are thought to play a crucial role in information processing in cortical networks. In addition to oscillatory activity between 30 and 60 Hz, current evidence from electro- and magnetoencephalography (EEG/MEG) and local-field potentials (LFPs) has consistently shown oscillations >60 Hz (high γ-band) whose function and generating mechanisms are unclear. In the present paper, we summarize data that highlights the importance of high γ-band activity for cortical computations through establishing correlations between the modulation of oscillations in the 60-200 Hz frequency and specific cognitive functions. Moreover, we will suggest that high γ-band activity is impaired in neuropsychiatric disorders, such as schizophrenia and epilepsy. In the final part of the paper, we will review physiological mechanisms underlying the generation of high γ-band oscillations and discuss the functional implications of low vs. high γ-band activity patterns in cortical networks., (Copyright © 2010. Published by Elsevier Ltd.)

Understanding causal relationships, or effective connectivity, between parts of the brain is of utmost importance because a large part of the brain's activity is thought to be internally generated and, hence, quantifying stimulus response relationships alone does not fully describe brain dynamics. Past efforts to determine effective connectivity mostly relied on model based approaches such as Granger causality or dynamic causal modeling. Transfer entropy (TE) is an alternative measure of effective connectivity based on information theory. TE does not require a model of the interaction and is inherently non-linear. We investigated the applicability of TE as a metric in a test for effective connectivity to electrophysiological data based on simulations and magnetoencephalography (MEG) recordings in a simple motor task. In particular, we demonstrate that TE improved the detectability of effective connectivity for non-linear interactions, and for sensor level MEG signals where linear methods are hampered by signal-cross-talk due to volume conduction.

The short-term retention of information has been related to oscillatory activity in the gamma-band. In recent auditory spatial short-term memory studies we have found stimulus-specific components of parieto-occipital gamma-band activity (GBA) which might reflect the activation of local networks tuned to task-relevant stimulus features. The present magnetoencephalography study (N=22) tested this interpretation by assessing whether the topography of stimulus-specific GBA depends on task demands. Sample sounds were characterized by both a variable interaural time delay and a variable central frequency. In separate task blocks, either the lateralization or the frequency of the same stimuli had to be maintained. Statistical probability mapping of differences in oscillatory responses to the retention of sample sounds replicated the contralateral posterior topography for GBA components distinguishing between medial and lateral sounds in the spatial memory task. In contrast, lower- and higher-frequency stimuli were accompanied by frontal GBA components in the frequency task. Memory for lateralization versus frequency selectively enhanced oscillatory activity for these posterior versus frontal components, directly demonstrating their modulation by task demands. Incorrect "non-match" responses were negatively correlated with delay-phase GBA to the relevant feature, whereas incorrect "match" responses correlated positively with GBA to the irrelevant feature. In summary, the topography of stimulus-specific GBA to identical stimuli reflected the selective representation of task-relevant features. Task performance was predicted by both enhanced stimulus-specific GBA for the task-relevant stimulus attribute and reduced gamma-band representations of the task-irrelevant stimulus feature. Stimulus-specific GBA may reflect the memory representation that is used in subsequent recognition.

When 2 visual stimuli are presented one after another in different locations, they are often perceived as one, but moving object. Feedback from area human motion complex hMT/V5+ to V1 has been hypothesized to play an important role in this illusory perception of motion. We measured event-related responses to illusory motion stimuli of varying apparent motion (AM) content and retinal location using Electroencephalography. Detectable cortical stimulus processing started around 60-ms poststimulus in area V1. This component was insensitive to AM content and sequential stimulus presentation. Sensitivity to AM content was observed starting around 90 ms post the second stimulus of a sequence and most likely originated in area hMT/V5+. This AM sensitive response was insensitive to retinal stimulus position. The stimulus sequence related response started to be sensitive to retinal stimulus position at a longer latency of 110 ms. We interpret our findings as evidence for feedback from area hMT/V5+ or a related motion processing area to early visual cortices (V1, V2, V3).

Background: Many systems in nature are characterized by complex behaviour where large cascades of events, or avalanches, unpredictably alternate with periods of little activity. Snow avalanches are an example. Often the size distribution f(s) of a system's avalanches follows a power law, and the branching parameter sigma, the average number of events triggered by a single preceding event, is unity. A power law for f(s), and sigma = 1, are hallmark features of self-organized critical (SOC) systems, and both have been found for neuronal activity in vitro. Therefore, and since SOC systems and neuronal activity both show large variability, long-term stability and memory capabilities, SOC has been proposed to govern neuronal dynamics in vivo. Testing this hypothesis is difficult because neuronal activity is spatially or temporally subsampled, while theories of SOC systems assume full sampling. To close this gap, we investigated how subsampling affects f(s) and sigma by imposing subsampling on three different SOC models. We then compared f(s) and sigma of the subsampled models with those of multielectrode local field potential (LFP) activity recorded in three macaque monkeys performing a short term memory task., Results: Neither the LFP nor the subsampled SOC models showed a power law for f(s). Both, f(s) and sigma, depended sensitively on the subsampling geometry and the dynamics of the model. Only one of the SOC models, the Abelian Sandpile Model, exhibited f(s) and sigma similar to those calculated from LFP activity., Conclusion: Since subsampling can prevent the observation of the characteristic power law and sigma in SOC systems, misclassifications of critical systems as sub- or supercritical are possible. Nevertheless, the system specific scaling of f(s) and sigma under subsampling conditions may prove useful to select physiologically motivated models of brain function. Models that better reproduce f(s) and sigma calculated from the physiological recordings may be selected over alternatives.

Both functional magnetic resonance imaging (fMRI)-constrained source analysis and independent component analysis (ICA) claim to estimate the neuronal sources of electroencephalographic (EEG) scalp signals. In fMRI-constrained source analysis, event-related potential (ERP) generator locations are defined by fMRI activation patterns, and their contribution to the scalp ERP signal is probed. In contrast, ICA assumes that networks of cortical generators can be separated on the basis of their statistical independence. While good arguments can be put forward to justify both approaches, it is unclear how results from both methods compare. A clarification of these issues is of utmost importance to reconcile findings made using identical paradigms but these two complementary analysis methods. As both methods share the concept of spatially static sources a natural space to compare both methods and to crossvalidate the respective findings is at the level of source activity in the form of dipole source waves and independent component time courses and their corresponding maps. We used fMRI-constrained source analysis and ICA followed by clustering using the Kuhn-Munkres algorithm to analyze data from a working memory experiment. We demonstrate that crossvalidation is indeed possible using an appropriate statistical test. However, the sensitivity of this crossvalidation approach is ultimately limited by the low number of dimensions that contribute significant variance to the grand average scalp ERP. We conclude that testing at the single-subject level is preferable for crossvalidation purposes if the signal-to-noise ratio of the data allows for this approach.

Recent studies have suggested an active role of cortical alpha oscillations for cognitive functions including short-term memory. We used magnetoencephalography to assess alpha activity during an auditory spatial delayed matching-to-sample task compared with a nonmemory control condition. In the memory task, participants had to memorize the lateralization angle of a noise stimulus S1 and compare it with another lateralized sound S2 presented after an 800-ms delay phase. Whereas alpha desynchronization following S1 was observed over superior temporal areas under both conditions, only the memory task was accompanied by posterior parietal alpha synchronization during the subsequent delay period. The findings are consistent with the notion of alpha activity reflecting active inhibition of interfering processes during memory maintenance of spatial sounds.

Parallel cortical pathways have been proposed for the processing of auditory pattern and spatial information, respectively. We tested this segregation with human functional magnetic resonance imaging (fMRI) and separate electroencephalographic (EEG) recordings in the same subjects who listened passively to four sequences of repetitive spatial animal vocalizations in an event-related paradigm. Transitions between sequences constituted either a change of auditory pattern, location, or both pattern+location. This procedure allowed us to investigate the cortical correlates of natural auditory "what" and "where" changes independent of differences in the individual stimuli. For pattern changes, we observed significantly increased fMRI responses along the bilateral anterior superior temporal gyrus and superior temporal sulcus, the planum polare, lateral Heschl's gyrus and anterior planum temporale. For location changes, significant increases of fMRI responses were observed in bilateral posterior superior temporal gyrus and planum temporale. An overlap of these two types of changes occurred in the lateral anterior planum temporale and posterior superior temporal gyrus. The analysis of source event-related potentials (ERPs) revealed faster processing of location than pattern changes. Thus, our data suggest that passive processing of auditory spatial and pattern changes is dissociated both temporally and anatomically in the human brain. The predominant role of more anterior aspects of the superior temporal lobe in sound identity processing supports the role of this area as part of the auditory pattern processing stream, while spatial processing of auditory stimuli appears to be mediated by the more posterior parts of the superior temporal lobe.

Hyperoxia is present in many anaesthesia protocols used in animal blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies. However, little data exist on the influence of hyperoxia on the magnitude of stimulus-induced relative changes in BOLD fMRI signal (DeltaBOLD%). No study to date has investigated these effects in a time-resolved manner, although cerebral vasoregulation offers sites for a time-dependent interaction of hyperoxia and DeltaBOLD%. Here we investigated time-dependent effects of an inspiratory oxygen fraction of 90%. We tightly clamped end tidal CO(2) and body temperature and recorded physiological parameters relevant to rCBF in (fentanyl/isoflurane) anaesthetized monkeys while using visual stimulation to elicit DeltaBOLD%. To clarify whether changes in DeltaBOLD% arose from changes in baseline blood oxygenation or rather altered neuronal or vascular reactivity, we directly measured changes in rCBV using monocrystalline ion oxide nanoparticles (MION) as contrast agent. In visual cortex we found a biphasic modulation of stimulus-induced DeltaBOLD% under hyperoxia: We observed first a significant decrease in DeltaBOLD% by -24% for data averaged over the time interval of 0-180 min post onset of hyperoxia followed by a subsequent recovery to baseline. rCBV response amplitudes were decreased by 21% in the same time interval (0-180 min). In the LGN, we neither found a significant modulation of DeltaBOLD% nor of MION response amplitude. The cerebrovascular effects of hyperoxia may, therefore, be regionally specific and cannot be explained by a deoxyhemoglobin dilution model accounting for plasma oxygenation without assuming altered neuronal activity or altered neurovascular coupling.

The present study investigated the relation of brain activity patterns measured with functional magnetic resonance imaging (fMRI) and slow event-related potentials (ERPs) associated with a complex cognitive task. A second goal was to examine the neural correlates of spatial imagery of haptically--instead of visually--acquired representations. Using a mental image scanning task, spatial imagery requirements were systematically manipulated by parametrically varying the distance between haptically acquired landmarks. Results showed a close relation between slow ERPs and the blood oxygenation level dependent (BOLD) signal in human parietal lobe. Reaction times of mental scanning correlated with the distances between landmarks on the learned display. In parallel, duration and amplitude of slow ERPs and duration of the haemodynamic response systematically varied as a function of mental scanning distance. Source analysis confirmed that the ERP imagery effect likely originated from the same cortical substrate as the corresponding BOLD effect. This covariation of the BOLD signal with slow ERPs is in line with recent findings in animals demonstrating a tight link between local field potentials and the BOLD signal. The parietal location of the imagery effect is consistent with the idea that externally triggered (perceptual) and mentally driven (imagery) spatial processes are both mediated by the same supramodal brain areas.

We used the combination of functional magnetic resonance imaging and event-related potentials to decompose the processing stages (mental chronometry) of working memory retrieval. Our results reveal an early transient activation of inferotemporal cortex, which was accompanied by the onset of a sustained activation of posterior parietal cortex. We furthermore observed late transient responses in ventrolateral prefrontal cortex and late sustained activity in medial frontal and premotor areas. We propose that these neural signatures reflect the cognitive stages of task processing, perceptual evaluation (inferotemporal cortex), storage buffer operations (posterior parietal cortex), active retrieval (ventrolateral prefrontal cortex), and action selection (medial frontal and premotor cortex). This is also supported by their differential temporal contribution to specific subcomponents of the P300 cognitive potential.

Constraints from functional magnetic resonance imaging (fMRI) were used to identify the sources of the visual P300 event-related potential (ERP). Healthy subjects performed a visual three-stimulus oddball paradigm with a difficult discrimination task while fMRI and high-density ERP data were acquired in separate sessions. This paradigm allowed us to differentiate the P3b component of the P300, which has been implicated in the detection of rare events in general (target and distractor), from the P3a component, which is mainly evoked by distractor events. The fMRI-constrained source model explained >99% of the variance of the scalp ERP for both components. The P3b was mainly produced by parietal and inferior temporal areas, whereas frontal areas and the insula contributed mainly to the P3a. This source model reveals that both higher visual and supramodal association areas contribute to the visual P3b and that the P3a has a strong frontal contribution, which is compatible with its more anterior distribution on the scalp. The results point to the involvement of distinct attentional subsystems in target and distractor processing.