Combined electrophysiological and morphological phenotypes in patients with genetic generalized epilepsy and their healthy siblings.

OBJECTIVE: Genetic generalized epilepsy (GGE) is characterized by aberrant neuronal dynamics and subtle structural alterations. We evaluated whether a combination of magnetic and electrical neuronal signals and cortical thickness would provide complementary information about network pathology in GGE. We also investigated whether these imaging phenotypes were present in healthy siblings of the patients to test for genetic influence. METHODS: In this cross-sectional study, we analyzed 5 min of resting state data acquired using electroencephalography (EEG) and magnetoencephalography (MEG) in patients, their siblings, and controls, matched for age and sex. We computed source-reconstructed power and connectivity in six frequency bands (1-40 Hz) and cortical thickness (derived from magnetic resonance imaging). Group differences were assessed using permutation analysis of linear models for each modality separately and jointly for all modalities using a nonparametric combination. RESULTS: Patients with GGE (n = 23) had higher power than controls (n = 35) in all frequencies, with a more posterior focus in MEG than EEG. Connectivity was also increased, particularly in frontotemporal and central regions in theta (strongest in EEG) and low beta frequencies (strongest in MEG), which was eminent in the joint EEG/MEG analysis. EEG showed weaker connectivity differences in higher frequencies, possibly related to drug effects. The inclusion of cortical thickness reinforced group differences in connectivity and power. Siblings (n = 18) had functional and structural patterns intermediate between those of patients and controls. SIGNIFICANCE: EEG detected increased connectivity and power in GGE similar to MEG, but with different spectral sensitivity, highlighting the importance of theta and beta oscillations. Cortical thickness reductions in GGE corresponded to functional imaging patterns. Our multimodal approach extends the understanding of the resting state in GGE and points to genetic underpinnings of the imaging markers studied, providing new insights into the causes and consequences of epilepsy.

Dynamics of nonlinguistic statistical learning: From neural entrainment to the emergence of explicit knowledge.

Humans are highly attuned to patterns in the environment. This ability to detect environmental patterns, referred to as statistical learning, plays a key role in many diverse aspects of cognition. However, the spatiotemporal neural mechanisms underlying implicit statistical learning, and how these mechanisms may relate or give rise to explicit learning, remain poorly understood. In the present study, we investigated these different aspects of statistical learning by using an auditory nonlinguistic statistical learning paradigm combined with magnetoencephalography. Twenty-four healthy volunteers were exposed to structured and random tone sequences, and statistical learning was quantified by neural entrainment. Already early during exposure, participants showed strong entrainment to the embedded tone patterns. A significant increase in entrainment over exposure was detected only in the structured condition, reflecting the trajectory of learning. While source reconstruction revealed a wide range of brain areas involved in this process, entrainment in areas around the left pre-central gyrus as well as right temporo-frontal areas significantly predicted behavioral performance. Sensor level results confirmed this relationship between neural entrainment and subsequent explicit knowledge. These results give insights into the dynamic relation between neural entrainment and explicit learning of triplet structures, suggesting that these two aspects are systematically related yet dissociable. Neural entrainment reflects robust, implicit learning of underlying patterns, whereas the emergence of explicit knowledge, likely built on the implicit encoding of structure, varies across individuals and may depend on factors such as sufficient exposure time and attention.

Heritability of Magnetoencephalography Phenotypes Among Patients With Genetic Generalized Epilepsy and Their Siblings.

OBJECTIVE: To assess whether neuronal signals in patients with genetic generalized epilepsy (GGE) are heritable, we examined magnetoencephalography resting-state recordings in patients and their healthy siblings. METHODS: In a prospective, cross-sectional design, we investigated source-reconstructed power and functional connectivity in patients, siblings, and controls. We analyzed 5 minutes of cleaned and awake data without epileptiform discharges in 6 frequency bands (1-40 Hz). We further calculated intraclass correlations to estimate heritability for the imaging patterns within families. RESULTS: Compared with controls (n = 45), patients with GGE (n = 25) showed widespread increased functional connectivity (θ to γ frequency bands) and power (δ to γ frequency bands) across the spectrum. Siblings (n = 18) fell between the levels of patients and controls. Heritability of the imaging metrics was observed in regions where patients strongly differed from controls, mainly in ß frequencies, but also for δ and θ power. Network connectivity in GGE was heritable in frontal, central, and inferior parietal brain areas and power in central, temporo-parietal, and subcortical structures. Presence of generalized spike-wave activity during recordings and medication were associated with the network patterns, whereas other clinical factors such as age at onset, disease duration, or seizure control were not. CONCLUSION: Metrics of brain oscillations are well suited to characterize GGE and likely relate to genetic factors rather than the active disease or treatment. High power and connectivity levels co-segregated in patients with GGE and healthy siblings, predominantly in the ß band, representing an endophenotype of GGE.

Activities of the Right Temporo-Parieto-Occipital Junction Reflect Spatial Hearing Ability in Cochlear Implant Users.

Spatial hearing is critical for us not only to orient ourselves in space, but also to follow a conversation with multiple speakers involved in a complex sound environment. The hearing ability of people who suffered from severe sensorineural hearing loss can be restored by cochlear implants (CIs), however, with a large outcome variability. Yet, the causes of the CI performance variability remain incompletely understood. Despite the CI-based restoration of the peripheral auditory input, central auditory processing might still not function fully. Here we developed a multi-modal repetition suppression (MMRS) paradigm that is capable of capturing stimulus property-specific processing, in order to identify the neural correlates of spatial hearing and potential central neural indexes useful for the rehabilitation of sound localization in CI users. To this end, 17 normal hearing and 13 CI participants underwent the MMRS task while their brain activity was recorded with a 256-channel electroencephalography (EEG). The participants were required to discriminate between the probe sound location coming from a horizontal array of loudspeakers. The EEG MMRS response following the probe sound was elicited at various brain regions and at different stages of processing. Interestingly, the more similar this differential MMRS response in the right temporo-parieto-occipital (TPO) junction in CI users was to the normal hearing group, the better was the spatial hearing performance in individual CI users. Based on this finding, we suggest that the differential MMRS response at the right TPO junction could serve as a central neural index for intact or impaired sound localization abilities.

Disturbed Balance of Inhibitory Signaling Links Hearing Loss and Cognition.

Neuronal hyperexcitability in the central auditory pathway linked to reduced inhibitory activity is associated with numerous forms of hearing loss, including noise damage, age-dependent hearing loss, and deafness, as well as tinnitus or auditory processing deficits in autism spectrum disorder (ASD). In most cases, the reduced central inhibitory activity and the accompanying hyperexcitability are interpreted as an active compensatory response to the absence of synaptic activity, linked to increased central neural gain control (increased output activity relative to reduced input). We here suggest that hyperexcitability also could be related to an immaturity or impairment of tonic inhibitory strength that typically develops in an activity-dependent process in the ascending auditory pathway with auditory experience. In these cases, high-SR auditory nerve fibers, which are critical for the shortest latencies and lowest sound thresholds, may have either not matured (possibly in congenital deafness or autism) or are dysfunctional (possibly after sudden, stressful auditory trauma or age-dependent hearing loss linked with cognitive decline). Fast auditory processing deficits can occur despite maintained basal hearing. In that case, tonic inhibitory strength is reduced in ascending auditory nuclei, and fast inhibitory parvalbumin positive interneuron (PV-IN) dendrites are diminished in auditory and frontal brain regions. This leads to deficits in central neural gain control linked to hippocampal LTP/LTD deficiencies, cognitive deficits, and unbalanced extra-hypothalamic stress control. Under these conditions, a diminished inhibitory strength may weaken local neuronal coupling to homeostatic vascular responses required for the metabolic support of auditory adjustment processes. We emphasize the need to distinguish these two states of excitatory/inhibitory imbalance in hearing disorders: (i) Under conditions of preserved fast auditory processing and sustained tonic inhibitory strength, an excitatory/inhibitory imbalance following auditory deprivation can maintain precise hearing through a memory linked, transient disinhibition that leads to enhanced spiking fidelity (central neural gain⇑) (ii) Under conditions of critically diminished fast auditory processing and reduced tonic inhibitory strength, hyperexcitability can be part of an increased synchronization over a broader frequency range, linked to reduced spiking reliability (central neural gain⇓). This latter stage mutually reinforces diminished metabolic support for auditory adjustment processes, increasing the risks for canonical dementia syndromes.

A Tactile Virtual Reality for the Study of Active Somatosensation.

Natural exploration of textures involves active sensing, i.e., voluntary movements of tactile sensors (e.g., human fingertips or rodent whiskers) across a target surface. Somatosensory input during moving tactile sensors varies according to both the movement and the surface texture. Combining motor and sensory information, the brain is capable of extracting textural features of the explored surface. Despite the ecological relevance of active sensing, psychophysical studies on active touch are largely missing. One reason for the lack of informative studies investigating active touch is the considerable challenge of assembling an appropriate experimental setup. A possible solution might be in the realm of virtual tactile reality that provides tactile finger stimulation depending on the position of the hand and the simulated texture of a target surface. In addition to rigorous behavioral studies, the investigation of the neuronal mechanisms of active tactile sensing in humans is highly warranted, requiring neurophysiological experiments using electroencephalography (EEG), magnetoencephalography (MEG) and/or functional magnetic resonance imaging (fMRI). However, current neuroimaging techniques impose specific requirements on the tactile stimulus delivery equipment in terms of compatibility with the neurophysiological methods being used. Here, we present a user-friendly, MEG compatible, tactile virtual reality simulator. The simulator consists of a piezo-electric tactile stimulator capable of independently protruding 16 plastic pistons of 1 mm diameter arranged in a 4 × 4 matrix. The stimulator delivers a spatial pattern of tactile stimuli to the tip of a finger depending on the position of the finger moving across a 2-dimensional plane. In order to demonstrate the functionality of the tactile virtual reality, we determined participants' detection thresholds in active and passive touch conditions. Thresholds in both conditions were higher than reported in the literature. It could well be that the processing of the piston-related stimulation was masked by the sensory input generated by placing the finger on the scanning probe. More so, the thresholds for both the active and passive tasks did not differ significantly. In further studies, the noise introduced by the stimulator in neuromagnetic recordings was quantified and somatosensory evoked fields for active and passive touch were recorded. Due to the compatibility of the stimulator with neuroimaging techniques such as MEG, and based on the feasibility to record somatosensory-related neuromagnetic brain activity the apparatus has immense potential for the exploration of the neural underpinnings of active tactile perception.

Reliability of Magnetoencephalography and High-Density Electroencephalography Resting-State Functional Connectivity Metrics.

Resting-state connectivity, for example, based on magnetoencephalography (MEG) or electroencephalography (EEG), is a widely used method for characterizing brain networks and a promising imaging biomarker. However, there is no established standard as to which method, modality, and analysis variant is preferable and there is only limited knowledge on the reproducibility, an important prerequisite for clinical application. We conducted an MEG-/high-density (hd)-EEG-study on 22 young healthy adults, who were measured twice in a scan/rescan design after 7 ± 2 days. Reliability of resting-state (15 min, eyes-closed) connectivity in source space was calculated via intraclass correlation coefficient (ICC) in classical frequency bands (delta-gamma). We investigated the reliability of two commonly used connectivity metrics, namely the imaginary part of coherency and the weighted phase-lag index and the influence of frequency band, vigilance, and the number of trials. We found a strong increase of reliability with more trials and relatively mild effects of vigilance. Reliability was excellent in the alpha band for MEG, as well as hd-EEG (ICC >0.85); in the theta band, reliability was good for MEG and poor for EEG. Other frequency bands showed lower reliability, with delta band being the worst. Furthermore, we investigated the spatial reliability of resting-state connectivity in a vertex-based approach, which reached fair to good reliability (ICC up to 0.67) with 5 min of data. Our results indicate that excellent reliability of global connectivity is achievable in alpha band, and vertex-based connectivity was still fair to good. Moreover, electrophysiological resting-state studies could benefit from more data than used previously. MEG and hd-EEG were similar in their overall performance but showed frequency band-specific differences.

Increased Functional MEG Connectivity as a Hallmark of MRI-Negative Focal and Generalized Epilepsy.

Epilepsy is one of the most prevalent neurological diseases with a high morbidity. Accumulating evidence has shown that epilepsy is an archetypical neural network disorder. Here we developed a non-invasive cortical functional connectivity analysis based on magnetoencephalography (MEG) to assess commonalities and differences in the network phenotype in different epilepsy syndromes (non-lesional/cryptogenic focal and idiopathic/genetic generalized epilepsy). Thirty-seven epilepsy patients with normal structural brain anatomy underwent a 30-min resting state MEG measurement with eyes closed. We only analyzed interictal epochs without epileptiform discharges. The imaginary part of coherency was calculated as an indicator of cortical functional connectivity in five classical frequency bands. This connectivity measure was computed between all sources on individually reconstructed cortical surfaces that were surface-aligned to a common template. In comparison to healthy controls, both focal and generalized epilepsy patients showed widespread increased functional connectivity in several frequency bands, demonstrating the potential of elevated functional connectivity as a common pathophysiological hallmark in different epilepsy types. Furthermore, the comparison between focal and generalized epilepsies revealed increased network connectivity in bilateral mesio-frontal and motor regions specifically for the generalized epilepsy patients. Our study indicated that the surface-based normalization of MEG sources of individual brains enables the comparison of imaging findings across subjects and groups on a united platform, which leads to a straightforward and effective disclosure of pathological network characteristics in epilepsy. This approach may allow for the definition of more specific markers of different epilepsy syndromes, and increased MEG-based resting-state functional connectivity seems to be a common feature in MRI-negative epilepsy syndromes.

Cortical correlates of perceptual decision making during tactile spatial pattern discrimination.

Perceptual decision making involves a distributed cortical network including areas related to sensory feature extraction, decision formation, and finally signalling the decision through a motor response. Although these processing steps are supposed to occur in sequence, the seemingly instant mapping of a perceptual decision onto a motor response renders these processes almost indistinguishable. To dissociate cortical areas related to sensory decision making from areas that prepare the subsequent motor response, we performed functional magnetic resonance imaging during a tactile spatial pattern discrimination task with interleaved immediate and delayed response conditions. Decision difficulty was manipulated parametrically by adding spatial noise to the tactile patterns, resulting in a rise in decision time with increasing noise. We assumed that areas involved in making the decision should show a variation in their activation with decision time and irrespective of whether (immediate response condition) or not (delayed response condition) a motor response could be prepared in advance. To exhibit these putative decision areas, we used response time, as was obtained in the immediate response condition, as parametric predictor for the difficulty-dependent variations of blood oxygenation level-dependent (BOLD)-activity in both response conditions. BOLD activations in right (contralateral) postcentral sulcus, right intraparietal sulcus (IPS) and bilateral anterior insula (aINS) reflected this parametric modulation in both response conditions, suggesting a role of these areas in tactile decisions independent of decision-specific motor preparation. Furthermore, a multivariate pattern analysis performed on the BOLD responses in the delayed response condition for a single difficulty level independently validated IPS and aINS as decision-related areas.

The contribution of primary and secondary somatosensory cortices to the representation of body parts and body sides: an fMRI adaptation study.

Although the somatosensory homunculus is a classically used description of the way somatosensory inputs are processed in the brain, the actual contributions of primary (SI) and secondary (SII) somatosensory cortices to the spatial coding of touch remain poorly understood. We studied adaptation of the fMRI BOLD response in the somatosensory cortex by delivering pairs of vibrotactile stimuli to the finger tips of the index and middle fingers. The first stimulus (adaptor) was delivered either to the index or to the middle finger of the right or left hand, and the second stimulus (test) was always administered to the left index finger. The overall BOLD response evoked by the stimulation was primarily contralateral in SI and was more bilateral in SII. However, our fMRI adaptation approach also revealed that both somatosensory cortices were sensitive to ipsilateral as well as to contralateral inputs. SI and SII adapted more after subsequent stimulation of homologous as compared with nonhomologous fingers, showing a distinction between different fingers. Most importantly, for both somatosensory cortices, this finger-specific adaptation occurred irrespective of whether the tactile stimulus was delivered to the same or to different hands. This result implies integration of contralateral and ipsilateral somatosensory inputs in SI as well as in SII. Our findings suggest that SI is more than a simple relay for sensory information and that both SI and SII contribute to the spatial coding of touch by discriminating between body parts (fingers) and by integrating the somatosensory input from the two sides of the body (hands).

Comparing tactile pattern and vibrotactile frequency discrimination: a human FMRI study.

We investigated to which extent the discrimination of tactile patterns and vibrotactile frequencies share common cortical areas. An adaptation paradigm has been used to identify cortical areas specific for processing particular features of tactile stimuli. Healthy right-handed subjects performed a delayed-match-to-sample (DMTS) task discriminating between pairs of tactile patterns or vibrotactile frequencies in separate functional MRI sessions. The tactile stimuli were presented to the right middle fingertip sequentially with a 5.5 s delay. Regions of interest (ROIs) were defined by cortical areas commonly activated in both tasks and those that showed differential activation between both tasks. Results showed recruitment of many common brain regions along the sensory motor pathway (such as bilateral somatosensory, premotor areas, and anterior insula) in both tasks. Three cortical areas, the right intraparietal sulcus (IPS), supramarginal gyrus (SMG)/parietal operculum (PO), and PO, were significantly more activated during the pattern than in the frequency task. Further BOLD time course analysis was performed in the ROIs. Significant BOLD adaptation was found in bilateral IPS, right anterior insula, and SMG/PO in the pattern task, whereas there was no significant BOLD adaptation found in the frequency task. In addition, the right hemisphere was found to be more dominant in the pattern than in the frequency task, which could be attributed to the differences between spatial (pattern) and temporal (frequency) processing. From the different spatio-temporal characteristics of BOLD activation in the pattern and frequency tasks, we concluded that different neuronal mechanisms are underlying the tactile spatial and temporal processing.

The involvement of ipsilateral temporoparietal cortex in tactile pattern working memory as reflected in beta event-related desynchronization.

Cortical oscillatory activity in various frequency bands has been shown to reflect working memory processes operating on visual and auditory stimulus information. Here we use magnetoencephalography to investigate cortical oscillatory activity related to working memory for tactile patterns. Right-handed subjects made same-different judgements on two dot patterns sequentially applied with a 3-s delay to the right middle fingertip. Spectral analysis revealed beta desynchronization (17+/-2.5 Hz) at contralateral postcentral and ipsilateral temporoparietal regions preceding and during the presentation of both tactile stimuli as well as during the early and late delay periods. Whereas contralateral beta desynchronization preceding tactile stimulation may reflect anticipation of incoming stimuli, ipsilateral beta desynchronization may underlie working memory maintenance of tactile patterns. The later hypothesis is supported by a significant positive correlation between subjects' performance and the amplitude of ipsilateral beta desynchronization 800 ms to 500 ms before the onset of the second pattern stimulus. Thus, our results suggest that ipsilateral temporoparietal cortex contributes to the maintenance of tactile pattern information in working memory.

BOLD adaptation in vibrotactile stimulation: neuronal networks involved in frequency discrimination.

The present functional magnetic resonance imaging (fMRI) study investigated human brain regions subserving the discrimination of vibrotactile frequency. An event-related adaptation paradigm was used in which blood-oxygen-level-dependent (BOLD) responses are lower to same compared with different pairs of stimuli (BOLD adaptation). This adaptation effect serves as an indicator for feature-specific responding of neuronal subpopulations. Subjects had to discriminate two vibrotactile stimuli sequentially applied with a delay of 600 ms to their left middle fingertip. The stimulus frequency was in the flutter range of 18-26 Hz. In half of the trials, the two stimuli possessed identical frequency (same), whereas in the other half, a frequency difference of +/-2 Hz was used (diff). As a result, BOLD adaptation was observed in the contralateral primary somatosensory cortex (S1), precentral gyrus, superior temporal gyrus (STG); ipsilateral insula as well as bilateral secondary somatosensory cortex and supplementary motor area. When statistically comparing the BOLD time courses between same and diff trials in these cortical areas, it was found that the vibrotactile BOLD adaptation is initiated in the contralateral S1 and STG simultaneously. These findings suggest that the cortical areas responsive to the frequency difference between two serially presented stimuli sequentially process the frequency of a vibrotactile stimulus and constitute a putative neuronal network underlying human vibrotactile frequency discrimination.

Do cortical maps depend on the timing of sensory input? Experimental evidence and computational model.

Fast adaptations in the functional organization of primary sensory cortex are generally assumed to result from changes of network connectivity. However, the effects of intrinsic neuronal excitability alterations due to the activation of neighboring cortical representational zones, which might as well account for the changes of cortical representative maps, have been paid little attention to. In a recent experiment (Braun et al. 2000b) we showed by neuromagnetic source imaging that random or fixed sequence stimulation of three digits of both hands led to stimulation-timing-induced changes in primary somatosensory (SI) cortical maps. The distance between the cortical representation of thumb and middle finger became significantly shorter during the fixed sequence stimulation. The analysis on the time course of the cortical map changes revealed that these reorganizations occurred within minutes and were fully reversible. The previously reported results were interpreted as the involvement of a superordinate center responsible for detecting and activating the appropriate maps. Here we present an alternative parsimonious explanation that is supported by a computational model. Based on the experimental evidence, we developed a simple model that took intrinsic neuronal excitability together with subthreshold activation into account and assumed partial cortical overlap of the representational zones of neighboring digits. Furthermore, in the model the neuronal excitability decayed slowly with respect to the stimulation frequency. The observed cortical map changes in the experiment could be reproduced by the two-layer feed-forward computational network. Our model thus suggests that the dynamic shifts of cortical maps can be explained by the state and time course of intrinsic neuronal excitability and subthreshold activation, without involving changes in network connectivity.