Laminar fMRI and computational theories of brain function.

Recently developed methods for functional MRI at the resolution of cortical layers (laminar fMRI) offer a novel window into neurophysiological mechanisms of cortical activity. Beyond physiology, laminar fMRI also offers an unprecedented opportunity to test influential theories of brain function. Specifically, hierarchical Bayesian theories of brain function, such as predictive coding, assign specific computational roles to different cortical layers. Combined with computational models, laminar fMRI offers a unique opportunity to test these proposals noninvasively in humans. This review provides a brief overview of predictive coding and related hierarchical Bayesian theories, summarises their predictions with regard to layered cortical computations, examines how these predictions could be tested by laminar fMRI, and considers methodological challenges. We conclude by discussing the potential of laminar fMRI for clinically useful computational assays of layer-specific information processing.

Automatic detection of trustworthiness of the face: a visual mismatch negativity study.

Recognizing intentions of strangers from facial cues is crucial in everyday social interactions. Recent studies demonstrated enhanced event-related potential (ERP) responses to untrustworthy compared to trustworthy faces. The aim of the present study was to investigate the electrophysiological correlates of automatic processing of trustworthiness cues in a visual oddball paradigm in two consecutive experimental blocks. In one block, frequent trustworthy (p = 0.9) and rare untrustworthy face stimuli (p = 0.1) were briefly presented on a computer screen with each stimulus consisting of four peripherally positioned faces. In the other block stimuli were presented with reversed probabilities enabling the comparison of ERPs evoked by physically identical deviant and standard stimuli. To avoid attentional effects participants engaged in a central detection task. Analyses of deviant minus standard difference waveforms revealed that deviant untrustworthy but not trustworthy faces elicited the visual mismatch negativity (vMMN) component. The present results indicate that adaptation occurred to repeated unattended trustworthy (but not untrustworthy) faces, i.e., an automatic expectation was elicited towards trustworthiness signals, which was violated by deviant untrustworthy faces. As an evolutionary adaptive mechanism, the observed fast detection of trustworthiness-related social facial cues may serve as the basis of conscious recognition of reliable partners.

Effects of twenty-minute 3G mobile phone irradiation on event related potential components and early gamma synchronization in auditory oddball paradigm.

We investigated the potential effects of 20 min irradiation from a new generation Universal Mobile Telecommunication System (UMTS) 3G mobile phone on human event related potentials (ERPs) in an auditory oddball paradigm. In a double-blind task design, subjects were exposed to either genuine or sham irradiation in two separate sessions. Before and after irradiation subjects were presented with a random series of 50 ms tone burst (frequent standards: 1 kHz, P=0.8, rare deviants: 1.5 kHz, P=0.2) at a mean repetition rate of 1500 ms while electroencephalogram (EEG) was recorded. The subjects' task was to silently count the appearance of targets. The amplitude and latency of the N100, N200, P200 and P300 components for targets and standards were analyzed in 29 subjects. We found no significant effects of electromagnetic field (EMF) irradiation on the amplitude and latency of the above ERP components. In order to study possible effects of EMF on attentional processes, we applied a wavelet-based time-frequency method to analyze the early gamma component of brain responses to auditory stimuli. We found that the early evoked gamma activity was insensitive to UMTS RF exposition. Our results support the notion, that a single 20 min irradiation from new generation 3G mobile phones does not induce measurable changes in latency or amplitude of ERP components or in oscillatory gamma-band activity in an auditory oddball paradigm.

A cartesian time--frequency approach to reveal brain interaction dynamics.

The study of large-scale interactions from magnetoencephalographic data based on the magnitude of the complex coherence computed at channel level is a widely used method to track the coupling between neural signals. Traditionally, a measure based on the magnitude of the complex coherence estimated by Fourier analysis, has been used under the assumption that the neural signals are stationary. Here, we split the complex coherence in its real and imaginary parts and focus on the latter with the advantage that the imaginary part is insensitive to spurious connectivity resulting from volume conducted "self interaction". Furthermore, interacting sources alone contribute to a non-vanishing imaginary part of the complex coherence whereas the contribute of non-interacting sources is also mapped from the magnitude of the complex coherence. Since it has been extensively shown that non-stationary stochastic processes contribute to the generation of neural signals, it is fundamental to be able to define interaction measures that are able to follow the temporal variations in the coupling between neural signals. To this purpose time-frequency domain techniques to estimate the magnitude of the complex coherence have been developed in the past decades. Similarly, we extend the analysis of the imaginary part of complex coherence to the time-frequency domain, by using the short-time Fourier transform to analyze the complex coherence as a function of time. In this way, it is possible to get an indication about the dynamic of the underlying source interaction pattern by looking at channel level interactions without the bias introduced by artifactual self-interaction by volume conduction or by the contribute of non-interacting sources. Furthermore, the corresponding imaginary part of the cross-spectrogram can be used to estimate interactions on a source level by localizing pools of sources interacting at a given frequency and by characterizing their dynamics. The method has been applied to magnetoencephalographic data from a cross-modal visual auditory stimulation and provided evidence for the involvement of temporal and occipital areas in the integrated information processing for simultaneous audio-visual stimulation. Furthermore, the source interaction pattern shows a variation in time that reflects a dynamical synchronization of the involved brain sources in the frequency bands of interest.