Prestimulus Network Integration of Auditory Cortex Predisposes Near-Threshold Perception Independently of Local Excitability.

An ever-increasing number of studies are pointing to the importance of network properties of the brain for understanding behavior such as conscious perception. However, with regards to the influence of prestimulus brain states on perception, this network perspective has rarely been taken. Our recent framework predicts that brain regions crucial for a conscious percept are coupled prior to stimulus arrival, forming pre-established pathways of information flow and influencing perceptual awareness. Using magnetoencephalography (MEG) and graph theoretical measures, we investigated auditory conscious perception in a near-threshold (NT) task and found strong support for this framework. Relevant auditory regions showed an increased prestimulus interhemispheric connectivity. The left auditory cortex was characterized by a hub-like behavior and an enhanced integration into the brain functional network prior to perceptual awareness. Right auditory regions were decoupled from non-auditory regions, presumably forming an integrated information processing unit with the left auditory cortex. In addition, we show for the first time for the auditory modality that local excitability, measured by decreased alpha power in the auditory cortex, increases prior to conscious percepts. Importantly, we were able to show that connectivity states seem to be largely independent from local excitability states in the context of a NT paradigm.

Thalamocortical interactions underlying visual fear conditioning in humans.

Despite a strong focus on the role of the amygdala in fear conditioning, recent works point to a more distributed network supporting fear conditioning. We aimed to elucidate interactions between subcortical and cortical regions in fear conditioning in humans. To do this, we used two fearful faces as conditioned stimuli (CS) and an electrical stimulation at the left hand, paired with one of the CS, as unconditioned stimulus (US). The luminance of the CS was rhythmically modulated leading to "entrainment" of brain oscillations at a predefined modulation frequency. Steady-state responses (SSR) were recorded by MEG. In addition to occipital regions, spectral analysis of SSR revealed increased power during fear conditioning particularly for thalamus and cerebellum contralateral to the upcoming US. Using thalamus and amygdala as seed-regions, directed functional connectivity was calculated to capture the modulation of interactions that underlie fear conditioning. Importantly, this analysis showed that the thalamus drives the fusiform area during fear conditioning, while amygdala captures the more general effect of fearful faces perception. This study confirms ideas from the animal literature, and demonstrates for the first time the central role of the thalamus in fear conditioning in humans.

Prestimulus oscillatory alpha power and connectivity patterns predispose perceptual integration of an audio and a tactile stimulus.

To efficiently perceive and respond to the external environment, our brain has to perceptually integrate or segregate stimuli of different modalities. The temporal relationship between the different sensory modalities is therefore essential for the formation of different multisensory percepts. In this magnetoencephalography study, we created a paradigm where an audio and a tactile stimulus were presented by an ambiguous temporal relationship so that perception of physically identical audiotactile stimuli could vary between integrated (emanating from the same source) and segregated. This bistable paradigm allowed us to compare identical bimodal stimuli that elicited different percepts, providing a possibility to directly infer multisensory interaction effects. Local differences in alpha power over bilateral inferior parietal lobules (IPLs) and superior parietal lobules (SPLs) preceded integrated versus segregated percepts of the two stimuli (audio and tactile). Furthermore, differences in long-range cortical functional connectivity seeded in rIPL (region of maximum difference) revealed differential patterns that predisposed integrated or segregated percepts encompassing secondary areas of all different modalities and prefrontal cortex. We showed that the prestimulus brain states predispose the perception of the audiotactile stimulus both in a global and a local manner. Our findings are in line with a recent consistent body of findings on the importance of prestimulus brain states for perception of an upcoming stimulus. This new perspective on how stimuli originating from different modalities are integrated suggests a non-modality specific network predisposing multisensory perception.

Monitoring driver's sleepiness on-board for preventing road accidents.

Driver sleepiness due to sleep deprivation is a causative factor of many road accidents. Reducing the extent of the sleepy driving problem by developing a countermeasure device that will monitor the sleepiness level of the driver is crucial to improve the safety of the roads. Among numerous physiological measurements, the electroencephalographic (EEG) signal seems to be the most sensitive to detect sleepiness. Previous studies in the field have found consistent alterations of EEG signal during sleepy driving, though they face methodological limitations. We present here preliminary results from a real-driving experiment in which a more complete experimental setup was followed. The subjects were exposed to driving conditions twice: once after they had a normal sleep during the previous night, and once after they remained awake for at least 24 hours prior to the experiment. Significant alterations were observed in the alpha and beta EEG frequencies bands between the two sessions. Electroopthalmographic (EOG) measurements revealed an increased number of eye blinking during the sleep-deprived session in comparison to the control condition. Both measurements can be used for the successful design of a sleepiness detection countermeasure device.

A Visual Cortical Network for Deriving Phonological Information from Intelligible Lip Movements.

Successful lip-reading requires a mapping from visual to phonological information [1]. Recently, visual and motor cortices have been implicated in tracking lip movements (e.g., [2]). It remains unclear, however, whether visuo-phonological mapping occurs already at the level of the visual cortex-that is, whether this structure tracks the acoustic signal in a functionally relevant manner. To elucidate this, we investigated how the cortex tracks (i.e., entrains to) absent acoustic speech signals carried by silent lip movements. Crucially, we contrasted the entrainment to unheard forward (intelligible) and backward (unintelligible) acoustic speech. We observed that the visual cortex exhibited stronger entrainment to the unheard forward acoustic speech envelope compared to the unheard backward acoustic speech envelope. Supporting the notion of a visuo-phonological mapping process, this forward-backward difference of occipital entrainment was not present for actually observed lip movements. Importantly, the respective occipital region received more top-down input, especially from left premotor, primary motor, and somatosensory regions and, to a lesser extent, also from posterior temporal cortex. Strikingly, across participants, the extent of top-down modulation of the visual cortex stemming from these regions partially correlated with the strength of entrainment to absent acoustic forward speech envelope, but not to present forward lip movements. Our findings demonstrate that a distributed cortical network, including key dorsal stream auditory regions [3-5], influences how the visual cortex shows sensitivity to the intelligibility of speech while tracking silent lip movements.

Limbic areas are functionally decoupled and visual cortex takes a more central role during fear conditioning in humans.

Going beyond the focus on isolated brain regions (e.g. amygdala), recent neuroimaging studies on fear conditioning point to the relevance of a network of mutually interacting brain regions. In the present MEG study we used Graph Theory to uncover changes in the architecture of the brain functional network shaped by fear conditioning. Firstly, induced power analysis revealed differences in local cortical excitability (lower alpha and beta power) between CS+ and CS- localized to somatosensory cortex and insula. What is more striking however is that the graph theoretical measures unveiled a re-organization of brain functional connections, not evident using conventional power analysis. Subcortical fear-related structures exhibited reduced connectivity with temporal and frontal areas rendering the overall brain functional network more sparse during fear conditioning. At the same time, the calcarine took on a more central role in the network. Interestingly, the more the connectivity of limbic areas is reduced, the more central the role of the occipital cortex becomes. We speculated that both, the reduced coupling in some regions and the emerging centrality of others, contribute to the efficient processing of fear-relevant information during fear learning.

Large-scale network-level processes during entrainment.

Visual rhythmic stimulation evokes a robust power increase exactly at the stimulation frequency, the so-called steady-state response (SSR). Localization of visual SSRs normally shows a very focal modulation of power in visual cortex and led to the treatment and interpretation of SSRs as a local phenomenon. Given the brain network dynamics, we hypothesized that SSRs have additional large-scale effects on the brain functional network that can be revealed by means of graph theory. We used rhythmic visual stimulation at a range of frequencies (4-30 Hz), recorded MEG and investigated source level connectivity across the whole brain. Using graph theoretical measures we observed a frequency-unspecific reduction of global density in the alpha band "disconnecting" visual cortex from the rest of the network. Also, a frequency-specific increase of connectivity between occipital cortex and precuneus was found at the stimulation frequency that exhibited the highest resonance (30 Hz). In conclusion, we showed that SSRs dynamically re-organized the brain functional network. These large-scale effects should be taken into account not only when attempting to explain the nature of SSRs, but also when used in various experimental designs.

Flicker-Driven Responses in Visual Cortex Change during Matched-Frequency Transcranial Alternating Current Stimulation.

We tested a novel combination of two neuro-stimulation techniques, transcranial alternating current stimulation (tACS) and frequency tagging, that promises powerful paradigms to study the causal role of rhythmic brain activity in perception and cognition. Participants viewed a stimulus flickering at 7 or 11 Hz that elicited periodic brain activity, termed steady-state responses (SSRs), at the same temporal frequency and its higher order harmonics. Further, they received simultaneous tACS at 7 or 11 Hz that either matched or differed from the flicker frequency. Sham tACS served as a control condition. Recent advances in reconstructing cortical sources of oscillatory activity allowed us to measure SSRs during concurrent tACS, which is known to impose strong artifacts in magnetoencephalographic (MEG) recordings. For the first time, we were thus able to demonstrate immediate effects of tACS on SSR-indexed early visual processing. Our data suggest that tACS effects are largely frequency-specific and reveal a characteristic pattern of differential influences on the harmonic constituents of SSRs.

Managing urinary incontinence through hand-held real-time decision support aid.

In this paper, we present an intelligent system for the diagnosis and treatment of urinary incontinence (UI) for males as well as females, called e-URIN. e-URIN is an intelligent system for diagnosis and treatment of urinary incontinence according to symptoms that are realized in one patient and usually recorded through his clinical examination as well as specific test results. The user-friendly proposed intelligent system is accommodated on a hospital server supporting e-health tools, for use through pocket PCs under wireless connection as a decision support system for resident doctors, as well as an educational tool for medical students. It is based on expert system knowledge representation provided from urology experts in combination with rich bibliographic search and study ratified with statistical results from clinical practice. Preliminary experimental results on a real patient hospital database provide acceptable performance that can be improved using more than one computational intelligence approaches in the future.

Alcohol affects the brain's resting-state network in social drinkers.

Acute alcohol intake is known to enhance inhibition through facilitation of GABA(A) receptors, which are present in 40% of the synapses all over the brain. Evidence suggests that enhanced GABAergic transmission leads to increased large-scale brain connectivity. Our hypothesis is that acute alcohol intake would increase the functional connectivity of the human brain resting-state network (RSN). To test our hypothesis, electroencephalographic (EEG) measurements were recorded from healthy social drinkers at rest, during eyes-open and eyes-closed sessions, after administering to them an alcoholic beverage or placebo respectively. Salivary alcohol and cortisol served to measure the inebriation and stress levels. By calculating Magnitude Square Coherence (MSC) on standardized Low Resolution Electromagnetic Tomography (sLORETA) solutions, we formed cortical networks over several frequency bands, which were then analyzed in the context of functional connectivity and graph theory. MSC was increased (p<0.05, corrected with False Discovery Rate, FDR corrected) in alpha, beta (eyes-open) and theta bands (eyes-closed) following acute alcohol intake. Graph parameters were accordingly altered in these bands quantifying the effect of alcohol on the structure of brain networks; global efficiency and density were higher and path length was lower during alcohol (vs. placebo, p<0.05). Salivary alcohol concentration was positively correlated with the density of the network in beta band. The degree of specific nodes was elevated following alcohol (vs. placebo). Our findings support the hypothesis that short-term inebriation considerably increases large-scale connectivity in the RSN. The increased baseline functional connectivity can -at least partially- be attributed to the alcohol-induced disruption of the delicate balance between inhibitory and excitatory neurotransmission in favor of inhibitory influences. Thus, it is suggested that short-term inebriation is associated, as expected, to increased GABA transmission and functional connectivity, while long-term alcohol consumption may be linked to exactly the opposite effect.

On the classification of emotional biosignals evoked while viewing affective pictures: an integrated data-mining-based approach for healthcare applications.

Recent neuroscience findings demonstrate the fundamental role of emotion in the maintenance of physical and mental health. In the present study, a novel architecture is proposed for the robust discrimination of emotional physiological signals evoked upon viewing pictures selected from the International Affective Picture System (IAPS). Biosignals are multichannel recordings from both the central and the autonomic nervous systems. Following the bidirectional emotion theory model, IAPS pictures are rated along two dimensions, namely, their valence and arousal. Following this model, biosignals in this paper are initially differentiated according to their valence dimension by means of a data mining approach, which is the C4.5 decision tree algorithm. Then, the valence and the gender information serve as an input to a Mahalanobis distance classifier, which dissects the data into high and low arousing. Results are described in Extensible Markup Language (XML) format, thereby accounting for platform independency, easy interconnectivity, and information exchange. The average recognition (success) rate was 77.68% for the discrimination of four emotional states, differing both in their arousal and valence dimension. It is, therefore, envisaged that the proposed approach holds promise for the efficient discrimination of negative and positive emotions, and it is hereby discussed how future developments may be steered to serve for affective healthcare applications, such as the monitoring of the elderly or chronically ill people.

A framework combining delta Event-Related Oscillations (EROs) and Synchronisation Effects (ERD/ERS) to study emotional processing.

Event-Related Potentials (ERPs) or Event-Related Oscillations (EROs) have been widely used to study emotional processing, mainly on the theta and gamma frequency bands. However, the role of the slow (delta) waves has been largely ignored. The aim of this study is to provide a framework that combines EROs with Event-Related Desynchronization (ERD)/Event-Related Synchronization (ERS), and peak amplitude analysis of delta activity, evoked by the passive viewing of emotionally evocative pictures. Results showed that this kind of approach is sensitive to the effects of gender, valence, and arousal, as well as, the study of interhemispherical disparity, as the two-brain hemispheres interplay roles in the detailed discrimination of gender. Valence effects are recovered in both the central electrodes as well as in the hemisphere interactions. These findings suggest that the temporal patterns of delta activity and the alterations of delta energy may contribute to the study of emotional processing. Finally the results depict the improved sensitivity of the proposed framework in comparison to the traditional ERP techniques, thereby delineating the need for further development of new methodologies to study slow brain frequencies.