Investigating cortical excitability and inhibition in patients with schizophrenia: A TMS-EEG study.

BACKGROUND: Transcranial magnetic stimulation (TMS) combined with electromyography (EMG) has widely been used as a non-invasive brain stimulation tool to assess excitation/inhibition (E/I) balance. E/I imbalance is a putative mechanism underlying symptoms in patients with schizophrenia. Combined TMS-electroencephalography (TMS-EEG) provides a detailed examination of cortical excitability to assess the pathophysiology of schizophrenia. This study aimed to investigate differences in TMS-evoked potentials (TEPs), TMS-related spectral perturbations (TRSP) and intertrial coherence (ITC) between patients with schizophrenia and healthy controls. MATERIALS AND METHODS: TMS was applied over the motor cortex during EEG recording. Differences in TEPs, TRSP and ITC between the patient and healthy subjects were analysed for all electrodes at each time point, by applying multiple independent sample t-tests with a cluster-based permutation analysis to correct for multiple comparisons. RESULTS: Patients demonstrated significantly reduced amplitudes of early and late TEP components compared to healthy controls. Patients also showed a significant reduction of early delta (50-160 ms) and theta TRSP (30-250ms),followed by a reduction in alpha and beta suppression (220-560 ms; 190-420 ms). Patients showed a reduction of both early (50-110 ms) gamma increase and later (180-230 ms) gamma suppression. Finally, the ITC was significantly lower in patients in the alpha band, from 30 to 260 ms. CONCLUSION: Our findings support the putative role of impaired GABA-receptor mediated inhibition in schizophrenia impacting excitatory neurotransmission. Further studies can usefully elucidate mechanisms underlying specific symptoms clusters using TMS-EEG biometrics.

Causal decoding of individual cortical excitability states.

Brain responsiveness to stimulation fluctuates with rapidly shifting cortical excitability state, as reflected by oscillations in the electroencephalogram (EEG). For example, the amplitude of motor-evoked potentials (MEPs) elicited by transcranial magnetic stimulation (TMS) of motor cortex changes from trial to trial. To date, individual estimation of the cortical processes leading to this excitability fluctuation has not been possible. Here, we propose a data-driven method to derive individually optimized EEG classifiers in healthy humans using a supervised learning approach that relates pre-TMS EEG activity dynamics to MEP amplitude. Our approach enables considering multiple brain regions and frequency bands, without defining them a priori, whose compound phase-pattern information determines the excitability. The individualized classifier leads to an increased classification accuracy of cortical excitability states from 57% to 67% when compared to µ-oscillation phase extracted by standard fixed spatial filters. Results show that, for the used TMS protocol, excitability fluctuates predominantly in the µ-oscillation range, and relevant cortical areas cluster around the stimulated motor cortex, but between subjects there is variability in relevant power spectra, phases, and cortical regions. This novel decoding method allows causal investigation of the cortical excitability state, which is critical also for individualizing therapeutic brain stimulation.

Interrelation of Elasticity and Thermal Bath in Nanotube Cantilevers.

We report the first study on the thermal behavior of the stiffness of individual carbon nanotubes, which is achieved by measuring the resonance frequency of their fundamental mechanical bending modes. We observe a reduction of the Young's modulus over a large temperature range with a slope -(173±65) ppm/K in its relative shift. These findings are reproduced by two different theoretical models based on the thermal dynamics of the lattice. These results reveal how the measured fundamental bending modes depend on the phonons in the nanotube via the Young's modulus. An alternative description based on the coupling between the measured mechanical modes and the phonon thermal bath in the Akhiezer limit is discussed.

Oral Human Papillomavirus: a multisite infection.

BACKGROUND: The Human Papillomavirus (HPV) has different strategies for persist in the cells. This characteristic has led us to consider the presence of the virus in tissues of the oral cavity that had no clinical signs of infection. The aim of this study was to detect the presence of DNA-HPV at multiple sites of the oral cavity. MATERIAL AND METHODS: A case-control study was designed: Oral Squamous Carcinoma Group (OSCG), healthy n=72 and Control Group (CG), n=72, healthy volunteers paired by sex and age with OSCG. Four samples were taken from OSCG: saliva, biopsy, brush scraping of lesion and contralateral healthy side. In CG a saliva sample and a scratch of the posterior border of tongue were collected. HPV was detected by PCR using Bioneer Accuprep genomic DNA Extraction kit, and consensus primers MY09 and MY11. Chi square test was applied. RESULTS: 432 samples were obtained from 144 individuals. DNA-HPV was detected in 30 (42%) of OSCG subjects and 3(4%) of CG. Two or more positive samples were obtained in 67% of the OSCG, 67% in saliva and 60% in biopsy; in CG 100% of the individuals were positive in the two samples. CONCLUSIONS: HPV is frequently present in oral cavity as a multifocal infection, even without the presence of clinical lesions.

Oral cancer associated with chronic mechanical irritation of the oral mucosa.

BACKGROUND: Most of the studies dealing with Chronic Mechanical Irritation (CMI) and Oral Cancer (OC) only considered prosthetic and dental variables separately, and CMI functional factors are not registered. Thus, the aim of this study was to assess OC risk in individuals with dental, prosthetic and functional CMI. Also, we examined CMI presence in relation to tumor size. MATERIAL AND METHODS: A case-control study was carried out from 2009 to 2013. Study group were squamous cell carcinoma cases; control group was patients seeking dental treatment in the same institution. RESULTS: 153 patients were studied (Study group n=53, Control group n=100). CMI reproducibility displayed a correlation coefficient of 1 (p<0.0001). Bivariate analysis showed statistically significant associations for all variables (age, gender, tobacco and alcohol consumption and CMI). Multivariate analysis exhibited statistical significance for age, alcohol, and CMI, but not for gender or tobacco. Relationship of CMI with tumor size showed no statistically significant differences. CONCLUSIONS: CMI could be regarded as a risk factor for oral cancer. In individuals with other OC risk factors, proper treatment of the mechanical injuring factors (dental, prosthetic and functional) could be an important measure to reduce the risk of oral cancer.

Optimal spatial filtering for brain oscillatory activity using the Relevance Vector Machine.

Over the past decade, various techniques have been proposed for localization of cerebral sources of oscillatory activity on the basis of magnetoencephalography (MEG) or electroencephalography recordings. Beamformers in the frequency domain, in particular, have proved useful in this endeavor. However, the localization accuracy and efficacy of such spatial filters can be markedly limited by bias from correlation between cerebral sources and short duration of source activity, both essential issues in the localization of brain data. Here, we evaluate a method for frequency-domain localization of oscillatory neural activity based on the relevance vector machine (RVM). RVM is a Bayesian algorithm for learning sparse models from possibly overcomplete data sets. The performance of our frequency-domain RVM method (fdRVM) was compared with that of dynamic imaging of coherent sources (DICS), a frequency-domain spatial filter that employs a minimum variance adaptive beamformer (MVAB) approach. The methods were tested both on simulated and real data. Two types of simulated MEG data sets were generated, one with continuous source activity and the other with transiently active sources. The real data sets were from slow finger movements and resting state. Results from simulations show comparable performance for DICS and fdRVM at high signal-to-noise ratios and low correlation. At low SNR or in conditions of high correlation between sources, fdRVM performs markedly better. fdRVM was successful on real data as well, indicating salient focal activations in the sensorimotor area. The resulting high spatial resolution of fdRVM and its sensitivity to low-SNR transient signals could be particularly beneficial when mapping event-related changes of oscillatory activity.

A frontoparietal network for spatial attention reorienting in the auditory domain: a human fMRI/MEG study of functional and temporal dynamics.

Several studies have identified a supramodal network critical to the reorienting of attention toward stimuli at novel locations and which involves the right temporoparietal junction and the inferior frontal areas. The present functional magnetic resonance imaging (fMRI)\magnetoencephalography (MEG) study investigates: 1) the cerebral circuit underlying attentional reorienting to spatially varying sound locations; 2) the circuit related to the regular change of sound location in the same hemifield, the change of sound location across hemifields, or sounds presented randomly at different locations on the azimuth plane; 3) functional temporal dynamics of the observed cortical areas exploiting the complementary characteristics of the fMRI and MEG paradigms. fMRI results suggest 3 distinct roles: the supratemporal plane appears modulated by variations of sound location; the inferior parietal lobule is modulated by the cross-meridian effect; and the inferior frontal cortex is engaged by the inhibition of a motor response. MEG data help to elucidate the temporal dynamics of this network by providing high-resolution time series with which to measure latency of neural activation manipulated by the reorienting of attention.

Cerebro-muscular and cerebro-cerebral coherence in patients with pre- and perinatally acquired unilateral brain lesions.

The cerebral networks involved in motor control were analyzed in four young hemi-paretic patients (21-25 years) with pre- and perinatally acquired brain lesions (3 with left periventricular brain lesions, 1 with left schizencephaly) by means of MEG source coherence analysis. Previous TMS and fMRI studies on the same patients had investigated their residual ability to move the paretic hand by means of a reorganized primary motor cortex (M1) representation in the contralesional hemisphere. The purpose of this study is to identify the effects of such a cerebral reorganization and the related dynamic aspects which allow the patients to move the paretic arm. Patients underwent a pinch grip task (1-N isometric contraction) using their paretic and non-paretic hands in alternation. MEG signals were recorded using a whole-head 151-channel magnetoencephalograph. EMG was simultaneously recorded as a reference for coherence calculations. 3D coherence mapping was performed in the beta frequency range (14-30 Hz). This approach confirmed the relocation of motor functions from the lesioned (left) to the contralesional (right) hemisphere. In case of left, non-paretic pinch grip, coherent activity originated from contralateral (right) M1 exclusively. In the case of right (paretic) grip, coherent activity in ipsilateral M1 as well as significant coherence of ipsilateral cerebellum with both muscle activity and M1 itself was detected in 3 out of 4 subjects. As expected, the patient with no cerebellar involvement during paretic hand contraction showed the worst motor performance in the grip task. Coupling direction analysis demonstrated that throughout pinch grip the coupling direction goes from M1 to cerebellum. The present study verified the assumption that the intact hemisphere takes over motor control from the paretic (ipsilateral) hand in the presence of early unilateral brain lesion. Moreover, the role of cerebellum in motor deficit compensation and its close interaction with ipsilateral primary motor cortex was studied in detail.

Localizing complex neural circuits with MEG data.

During cognitive processing, the various cortical areas, with specialized functions, supply for different tasks. In most cases then, the information flows are processed in a parallel way by brain networks which work together integrating the single performances for a common goal. Such a step is generally performed at higher processing levels in the associative areas. The frequency range at which neuronal pools oscillate is generally wider than the one which is detectable by bold changes in fMRI studies. A high time resolution technique like magnetoencephalography or electroencephalography is therefore required as well as new data processing algorithms for detecting different coherent brain areas cooperating for one cognitive task. Our experiments show that no algorithm for the inverse problem solution is immune from bias. We propose therefore, as a possible solution, our software LOCANTO (LOcalization and Coherence ANalysis TOol). This new package features a set of tools for the detection of coherent areas. For such a task, as a default, it employs the algorithm with best performances for the neural landscape to be detected. If the neural landscape under attention involves more than two interacting areas the SLoreta algorithm is used. Our study shows in fact that SLoreta performance is not biased when the correlation among multiple sources is high. On the other hand, the Beamforming algorithm is more precise than SLoreta at localizing single or double sources but it gets a relevant localization bias when the sources are more than three and are highly correlated.

Human brain activation during passive listening to sounds from different locations: an fMRI and MEG study.

Recent animal and human studies indicate the existence of a neural pathway for sound localization, which is similar to the "where" pathway of the visual system and distinct from the sound identification pathway. This study sought to highlight this pathway using a passive listening protocol. We employed fMRI to study cortical areas, activated during the processing of sounds coming from different locations, and MEG to disclose the temporal dynamics of these areas. In addition, the hypothesis of different activation levels in the right and in the left hemispheres, due to hemispheric specialization of the human brain, was investigated. The fMRI results indicate that the processing of sound, coming from different locations, activates a complex neuronal circuit, similar to the sound localization system described in monkeys known as the auditory "where" pathway. This system includes Heschl's gyrus, the superior temporal gyrus, the supramarginal gyrus, and the inferior and middle frontal lobe. The MEG analysis allowed assessment of the timing of this circuit: the activation of Heschl's gyrus was observed 139 ms after the auditory stimulus, the peak latency of the source located in the superior temporal gyrus was at 156 ms, and the inferior parietal lobule and the supramarginal gyrus peaked at 162 ms. Both hemispheres were found to be involved in the processing of sounds coming from different locations, but a stronger activation was observed in the right hemisphere.