Fast Band Research Articles

Characterizing Sleep Spindles in Sheep

Sleep spindles are distinctive transient patterns of brain activity that typically occur during non-rapid eye movement (NREM) sleep in humans and other mammals. Thought to be important for the consolidation of learning, they may also be useful for indicating the progression of aging and neurodegenerative diseases. The aim of this study was to characterize sleep spindles in sheep (Ovis aries). We recorded electroencephalographs wirelessly from six sheep over a continuous period containing 2 nights and a day. We detected and characterized spindles using an automated algorithm. We found that sheep sleep spindles fell within the classical range seen in humans (10–16 Hz), but we did not see a further separation into fast and slow bands. Spindles were detected predominantly during NREM sleep. Spindle characteristics (frequency, duration, density, topography) varied between individuals, but were similar within individuals between nights. Spindles that occurred during NREM sleep in daytime were indistinguishable from those found during NREM sleep at night. Surprisingly, we also detected numerous spindle-like events during unequivocal periods of wake during the day. These events were mainly local (detected at single sites), and their characteristics differed from spindles detected during sleep. These “wake spindles” are likely to be events that are commonly categorized as “spontaneous alpha activity” during wake. We speculate that wake and sleep spindles are generated via different mechanisms, and that wake spindles play a role in cognitive processes that occur during the daytime.

Effect of calorie on cognitive function among traumatic brain injury (tbi) patients: a pilot study

Cognitive recovery is a major concern to traumatic brain injury (TBI) patients and their caregivers as patients need to resume normal life after hospital discharge. A recent discovery showed that low calorie was beneficial for cognitive function with lower mortality rate and produced better clinical outcomes in critically-ill and medical intensive care unit patients. However, the effect of low calorie on cognitive function among TBI patients has not been determined yet. Hence this study was conducted to provide preliminary evidence of the relation between calorie and cognitive function and to determine calorie adequacy for optimal cognitive recovery among them. This pilot study involved ten patients recruited from Hospital Sultanah Nur Zahirah, Kuala Terengganu. The patients underwent a series of nutritional assessments including 24-hours diet recall combined with food diary; neuropsychology test [Montreal Cognitive Assessment (MoCA)], and eye-open-eye-close paradigm of electroencephalography (EEG) for two to six days. Socio-demography, nutritional and neuropsychology data were analyzed using SPSS version 22 with the percentage of calorie intake (%CI) was set as the independent variable; whilst duration to finish trail-making subtest (FT), and the total score (TS) of MoCA were the dependent variables. EEG data were analyzed using Fast-Fourier Transform (FFT) and power ratio (PR) which is the ratio of slow to fast frequency brain band was calculated. Then the comparison of %CI, FT, TS, and PR were done between day-1 and discharge-day (early or follow-up visit in EEG). Six male and four female patients with mild TBI, median age 24.0 years (IQR = 9.5) were included in the study. Scatter dot plot between %CI to FT and TS showed that the graph increased at the beginning before it became a plateau at 70%. The %CI had significant negative correlation with FT (r = -0.717; p = 0.000) but positive correlation with TS (r = 0.789; p = 0.000). Results revealed that cognitive function was improved at low %CI, approximately below CI of 70%. Improvement in neuropsychology test results was strengthened by the significant differences of median EEG power ratio between follow-up and first visit (p = 0.000). In this pilot study, it appears that cognitive function showed improvement with low calorie intake among TBI patients.

Dual-Tasking as Diagnostic and Rehabilitation Tool in Traumatic Brain Injury Patients

Objective: Purpose of this study was to investigate the behavioral and brain activity impairments in patients after moderate traumatic brain injury (mTBI) in comparison with the normal ranges while dual-tasks performing. We would like to evaluate dual-tasking as diagnostic and rehabilitation tool and to test hypothesis of brain aging after mTBI. Material and Methods: Electroencephalographic (EEG), stabilographic and clinical study was performed in 11 patients (mean age 28.8 ± 8.4 years) for up to 1 - 12 months after a mTBI in comparison with 17 healthy subjects (26.7 ± 5.1 years). All the participants performed two motor and two cognitive tasks presented separately, and simultaneously (dual-tasking). Results: Clinical examination revealed predominantly cognitive deficit in mTBI patients with intact postural control. EEG data demonstrated coherence decrease for slow (delta-theta) rhythms in frontal-temporal areas predominantly for left hemisphere during cognitive tasks performance. In contrast, EEG coherence for slow spectral bands increased in the same areas in healthy volunteers. EEG coherence increased for fast spectral bands—alpha2 and beta, predominantly in right hemisphere while both healthy adults and patients performed motor components of dual tasks. Rehabilitation course with dual tasks, led to a predominant reduction in cognitive deficits, and EEG coherence increases at the frontal-temporal areas of the left hemisphere. Conclusions: Dual-tasks may be used as diagnostic tool in patients after mTBI. This approach demonstrates predominant cognitive deficit, and left hemispheric dysfunction in patients similar to elderly persons and support the hypothesis of brain aging after TBI. Pilot studies also suggested rehabilitation effect of dual-tasking in mTBI patients.

Comparison of 3-D Raytracing and Finite Frequency Tomography

We performed 3-D seismic tomography using teleseismic arrival time at Southwest Mexico. The Mexican subduction zone results from successive fragmentation events that affected the ancient Farallon plate as various segments of the East Pacific rise approached the paleo-trench off western North America. The complexity in this region is related to two subducting oceanic plates, the Rivera and Cocos plates, that have different ages, compositions, convergence velocities and subduction dip angles. In this study, we compared the 3-D raytracing tomography model with finite frequency tomography model. Final models show the differences in amplitude and pattern between the raytracing and finite frequency. 3D raytracing models produced sharper images of fast velocity structures in the mantle. The deeper slabs are more coherent and show less broadening with depth than using 1D finite frequency kernels. However, although the finite frequency and 3-D ray tracing models show some differences in amplitude and pattern, the overall agreement of the models supports the interpretation of Yang et al. (2009) that slab rollback is occurring in South Western Mexico. One possible different interpretation between the raytracing and finite frequency theory results concerns the deep structure of the Rivera slab. The finite frequency models show that the Rivera slab is clearly observable at a depth of about 300km but fades away at greater depths. However, the 3-D ray tracing model shows a clear fast velocity band down to a depth of 400 km and thus our model does not support a slab tear of the Rivera plate above 400 km depth

Spectral organization of focal seizures within the thalamotemporal network.

ObjectiveTo investigate dynamic changes in neural activity between the anterior nucleus of the thalamus (ANT) and the seizure onset zone (SOZ) in patients with drug‐resistant temporal lobe epilepsy (TLE) based on anatomic location, seizure subtype, and state of vigilance (SOV).MethodsEleven patients undergoing stereoelectroencephalography for seizure localization were recruited prospectively for local field potential (LFP) recording directly from the ANT. The SOZ was identified using line length and epileptogenicity index. Changes in power spectral density (PSD) were compared between the two anatomic sites as seizures (N = 53) transitioned from interictal baseline to the posttermination stage.ResultsAt baseline, the thalamic LFPs were significantly lower and distinct from the SOZ with the presence of higher power in the fast ripple band (P < 0.001). Temporal changes in ictal power of neural activity within ANT mimic those of the SOZ, are increased significantly at seizure onset (P < 0.05), and are distinct for seizures that impaired awareness or that secondarily generalized (P < 0.05). The onset of seizure was preceded by a decrease in the mean power spectral density (PSD) in ANT and SOZ (P < 0.05). Neural activity correlated with different states of vigilance at seizure onset within the ANT but not in the SOZ (P = 0.005).InterpretationThe ANT can be recruited at the onset of mesial temporal lobe seizures, and the recruitment pattern differs with seizure subtypes. Furthermore, changes in neural dynamics precede seizure onset and are widespread to involve temporo‐thalamic regions, thereby providing an opportunity to intervene early with closed‐loop DBS.

Observing Erotic Videos with Heterosexual Content Induces Different Cerebral Responses in Homosexual and Heterosexual Men

ABSTRACT To determine the cerebral functionality associated with the perception and processing of erotic stimuli in men with different sexual orientation, this work evaluated the electroencephalographic activity (EEG) from several cortical areas, as well as subjective arousal in homosexual and heterosexual men during observation of an erotic film with heterosexual content. The heterosexual men rated the erotic video with higher general and sexual arousal than the homosexual participants. During observation of the neutral and erotic videos, both groups showed a decreased amplitude of the alpha band in prefrontal and parietal cortices, indicating increased attention. When watching the erotic video, the homosexual men showed an increased amplitude of the theta and fast bands only in the prefrontal cortex, which could be related to the cognitive processing of the erotic stimulus. These EEG results should broaden our knowledge of the cortical mechanisms related to the different perception and processing of erotic stimuli in men with different sexual orientations.

Neural Dynamics of Olfactory Perception: Low- and High-Frequency Modulations of Local Field Potential Spectra in Mice Revealed by an Oddball Stimulus.

Recent brain connectome studies have evidenced distinct and overlapping brain regions involved in processing olfactory perception. However, neural correlates of hypo- or anosmia in olfactory disorder patients are poorly known. Furthermore, the bottom-up and top-down processing of olfactory perception have not been well-documented, resulting in difficulty in locating the disease foci of olfactory disorder patients. The primary aim of this study is to characterize the bottom-up process of the neural dynamics across peripheral and central brain regions in anesthetized mice. We particularly focused on the neural oscillations of local field potential (LFP) in olfactory epithelium (OE), olfactory blub (OB), prefrontal cortex (PFC), and hippocampus (HC) during an olfactory oddball paradigm in urethane anesthetized mice. Odorant presentations evoked neural oscillations across slow and fast frequency bands including delta (1–4 Hz), theta (6–10 Hz), beta (15–30 Hz), low gamma (30–50 Hz), and high gamma (70–100 Hz) in both peripheral and central nervous systems, and the increases were more prominent in the infrequently presented odorant. During 5 s odorant exposures, the oscillatory responses in power were persistent in OE, OB, and PFC, whereas neural oscillations of HC increased only for short time at stimulus onset. These oscillatory responses in power were insignificant in both peripheral and central regions of the ZnSO4-treated anosmia model. These results suggest that olfactory stimulation induce LFP oscillations both in the peripheral and central nervous systems and suggest the possibility of linkage of LFP oscillations in the brain to the oscillations in the peripheral olfactory system.

EEG correlation during the solving of simple and complex logical-mathematical problems.

Solving logical-mathematical word problems is a complex task that requires numerous cognitive operations, including comprehension, reasoning, and calculation. These abilities have been associated with activation of the parietal, temporal, and prefrontal cortices. It has been suggested that the reasoning involved in solving logical-mathematical problems requires the coordinated functionality of all these cortical areas. In this study was evaluated the activation and electroencephalographic (EEG) correlation of the prefrontal, temporal, and parietal regions in young men while solving logical-mathematical word problems with two degrees of difficulty: simple and complex. During the solving of complex problems, higher absolute power and EEG correlation of the alpha and fast bands between the left frontal and parietal cortices were observed. A temporal deactivation and functional decoupling of the right parietal-temporal cortices also were obtained. Solving complex problems probably require activation of a left prefrontal-parietal circuit to maintain and manipulate multiple pieces of information. The temporal deactivation and decreased parietal-temporal correlation could be associated to text processing and suppression of the content-dependent reasoning to focus cognitive resources on the mathematical reasoning. Together, these findings support a pivotal role for the left prefrontal and parietal cortices in mathematical reasoning and of the temporal regions in text processing required to understand and solve written mathematical problems.

Abstract TP542: EEG Detection of Secondary Worsening of Neuronal Function in Malignant MCA Infarction: Development of a Tool to Identify Patients for Decompressive Hemicraniectomy

Hemicraniectomy (HC) improves mortality in Malignant Middle cerebral artery Infarctions (MMI), but patient selection and optimal timing for HC remains unclear. A continuous method to monitor for the risk and development of herniation from infarction would allow a better selection of patients for HC We hypothesized that certain EEG features reflective of worsening mass effect will be easier to detect on quantitative EEG (qEEG) analysis trends We studied qEEG trends before, during clinical deterioration (drop in GCS by at least 3 points) and after administration of osmotherapy. qEEG trends included rhythmicity spectra 0-25 Hz (scale 0- 2uV/Hz), Color Density Power Spectra (CSA) 0-20Hz (scale 0-2uV/Hz), amplitude integrated EEG (aEEG): 0-100uV and VsRhythmicity spectrogram 1 - 25 Hz (-3-3 Zscore) Trends demonstrated bilateral loss of power on beta and alpha frequencies and increase in theta preceded clinical deterioration by approximately 1 hour (left &gt; right). Patient2 subsequently had a robust theta power increase (+z score, red) in left &gt; right hemisphere which coincide with clinical deterioration on vsRhythmmicity Spectrogram. Also, there was a decreased of fast and slow frequencies bands on rhythmicity spectrogram and CSA with a diffuse attenuation outlined by aEEG (Left &gt; right). Following osmotherapy gradual improvement in all frequencies is seen but with an incomplete recovery in patient1 with lower alpha and theta power on right posterior and anterior quadrants suggested ongoing uncal and sub-falcine herniation, later confirmed on imaging Changes on qEEG reflecting impaired perfusion during acute herniation can manifest as decreased power in all frequency bands of varying severity prior to clinical deterioration. These changes can be completely or partially reversed with osmotherapy. Partial EEG response to osmotherapy may represent a potential sign of patients who will fail medical management and need DC. qEEG may be a helpful tool in HC patient selection

Dimensionality reduction based on determinantal point process and singular spectrum analysis for hyperspectral images

Dimensionality reduction is of high importance in hyperspectral data processing, which can effectively reduce the data redundancy and computation time for improved classification accuracy. Band selection and feature extraction methods are two widely used dimensionality reduction techniques. By integrating the advantages of the band selection and feature extraction, the authors propose a new method for reducing the dimension of hyperspectral image data. First, a new and fast band selection algorithm is proposed for hyperspectral images based on an improved determinantal point process (DPP). To reduce the amount of calculation, the dual-DPP is used for fast sampling representative pixels, followed by k-nearest neighbour-based local processing to explore more spatial information. These representative pixel points are used to construct multiple adjacency matrices to describe the correlation between bands based on mutual information. To further improve the classification accuracy, two-dimensional singular spectrum analysis is used for feature extraction from the selected bands. Experiments show that the proposed method can select a low-redundancy and representative band subset, where both data dimension and computation time can be reduced. Furthermore, it also shows that the proposed dimensionality reduction algorithm outperforms a number of state-of-the-art methods in terms of classification accuracy.

Neurophysiological Mechanisms of Resilience as a Protective Factor in Patients with Internet Gaming Disorder: A Resting-State EEG Coherence Study.

Background: Resilience, an important protective factor against Internet gaming disorder (IGD), is the ability to recover from negative emotional experiences and constitutes a flexible adaptation to stress. Despite the importance of resilience in predicting IGD, little is known about the relationships between resilience and the neurophysiological features of IGD patients. Methods: We investigated these relationships using resting-state electroencephalography (EEG) coherence, by comparing IGD patients (n = 35) to healthy controls (n = 36). To identify the resilience-related EEG features, the IGD patients were divided into two groups based on the 50th percentile score on the Connor–Davidson Resilience Scale: IGD with low resilience (n = 16) and IGD with high resilience (n = 19). We analyzed differences in EEG coherence among groups for each fast frequency band. The conditional indirect effects of resilience were examined on the relationships between IGD and resilience-related EEG features through clinical symptoms. Results: IGD patients with low resilience had higher alpha coherence in the right hemisphere. Particularly, resilience moderated the indirect effects of IGD on alpha coherence in the right hemisphere through depressive symptoms and stress level. Conclusion: These neurophysiological findings regarding the mechanisms underlying resilience may help to establish effective preventive measures against IGD.

M110 - ELECTROPHYSIOLOGIC DIFFERENCES TO ALCOHOL CHALLENGE IN INDIVIDUALS POLYMORPHIC AT ADH1B LOCI

Background The ADH Class 1 is the major group for metabolizing alcohol in humans. Subunits which constitute class 1 ADH are encoded by the three genes ADH1A, ADH1B, and ADH1C, giving rise to A, B, and C subunits. Genetic polymorphisms, occur at ADH1B to give rise to ADH1B1, ADH1B2, and ADH1B3 subunits. Concerning the ADH1B gene, individuals with the ADH1B3 genotype appear to be more resistant to the stimulating effects of alcohol, possibly due to a faster-metabolizing capacity of this variant compared to the wild-type (ADH1B1). The purpose of this study was to examine the effect of ADH1B polymorphisms on electroencephalography, using the alcohol clamp technique. We hypothesize that individuals heterozygous for the ADH1B3 allele will have lower alpha power in frontoparietal electrodes, suggesting less relaxation effect during alcohol ingestion compared to those homozygous for ADH1B1. Methods A pilot sample of individuals (N=28) genotyped at the ADH1B locus received continuous EEG recording during infusion, using the alcohol clamp technique. The collected EEG data was analyzed using EEGLAB, an open source electrophysiological data analysis software application. The data was preprocessed using FASTER, an EEGLAB plugin for Automated EEG artifact Rejection. The FASTER process applies independent component analysis and statistical thresholds for artifact rejection. The accepted EEG epochs were then submitted to the pwelch FFT implementation using the inbuilt functions of EEGLAB, which computed the power of the EEG in 0.24 Hz steps over a total range of 1.5 – 40 Hz. The power spectra were averaged over epochs and averaged amplitude peaks extracted. The estimates of power within the delta (1.5–3.2 Hz), theta (3.8– 7.02 Hz), alpha (7.8–12.5 Hz), and slow (13.2–18.75 Hz) and fast (19.5–39.8 Hz) beta frequency bands were computed as the area under the PSD curve. Results Subjects with ADH1B1/1 have increased alpha power in CZ, FZ and PZ leads during baseline (i.e. pre-alcohol exposure) eye-closed resting EEG, with the greatest difference (between ADH1B1/1 and ADH1B1/3 observed in the PZ leads (P Discussion Based on rich evidence from neurophysiological studies, increased alpha power is indicative of hypoarousal; therefore, our data subjects more evidence for cortical hypoarousal in anticipation of alcohol challenge among individuals with ADH1B1/1 polymorphism.

A Novel Method for Extracting Maximum Kurtosis Component and Its Applications in Rolling Bearing Fault Diagnosis

Rolling bearing plays an important role in the overall operation of the mechanical system; therefore, it is necessary to monitor and diagnose the bearings. Kurtosis is an important index to measure impulses. Fast Kurtogram method can be applied to the fault diagnosis of rolling bearings by extracting maximum kurtosis component. However, the final result may disperse the effective fault information to different frequency bands or find wrong frequency band, resulting in inaccurate frequency band selection or misdiagnosis. In order to find the maximum component of kurtosis accurately, an algorithm of frequency band multidivisional and overlapped based on EWT (MDO‐EWT) is proposed in this paper. This algorithm changes the traditional Fast Kurtogram frequency bands division method and filtering method. It builds the EWT boundaries based on the maximum kurtosis component in each iteration and finally obtains the maximum kurtosis component. Through the simulation signal and the rolling bearing inner and outer ring fault signals verification, it is proved that the proposed method has a good performance on accuracy and effectiveness.

Observing Erotic Videos With Heterosexual Content Induces Different Cerebral Responses in Homosexual and Heterosexual Men

ABSTRACT To determine the cerebral functionality associated with the perception and processing of erotic stimuli in men with different sexual orientation, this work evaluated the electroencephalographic activity (EEG) from several cortical areas, as well as subjective arousal in homosexual and heterosexual men during observation of an erotic film with heterosexual content. The heterosexual men rated the erotic video with higher general and sexual arousal than the homosexual participants. During observation of the neutral and erotic videos, both groups showed a decreased amplitude of the alpha band in prefrontal and parietal cortices, indicating increased attention. When watching the erotic video, the homosexual men showed an increased amplitude of the theta and fast bands only in the prefrontal cortex, which could be related to the cognitive processing of the erotic stimulus. These EEG results should broaden our knowledge of the cortical mechanisms related to the different perception and processing of erotic stimuli in men with different sexual orientations.

EEG Multiscale Complexity in Schizophrenia During Picture Naming.

Introduction: Patients with schizophrenia show cognitive deficits that are evident both behaviourally and with EEG recordings. Recent studies have suggested that non-linear analyses of EEG might more adequately reflect the complex, irregular, non-stationary behavior of neural processes than more traditional ERP measures. Non-linear analyses have been mainly applied to EEGs from patients at rest, whereas differences in complexity might be more evident during task performance.Objective: We aimed to investigate changes in non-linear brain dynamics of patients with schizophrenia during cognitive processing.Method: 18 patients and 17 matched healthy controls were asked to name pictures. EEG data were collected at rest and while they were performing a naming task. EEGs were analyzed with the classical Lempel-Ziv Complexity (LZC) and with the Multiscale LZC. Electrodes were grouped in seven regions of interest (ROI).Results: As expected, controls had fewer naming errors than patients. Regarding EEG complexity, the interaction between Group, Task and ROI indicated that patients showed higher complexity values in right frontal regions only at rest, where no differences in complexity between patients and controls were found during the naming task. EEG complexity increased from rest to task in controls in left temporal-parietal regions, while no changes from rest to task were observed in patients. Finally, differences in complexity between patients and controls depended on the frequency bands: higher values of complexity in patients at rest were only observed in fast bands, indicating greater heterogeneity in patients in local dynamics of neuronal assemblies.Conclusion: Consistent with previous studies, schizophrenic patients showed higher complexity than controls in frontal regions at rest. Interestingly, we found different modulations of brain complexity during a simple cognitive task between patients and controls. These data can be interpreted as indicating schizophrenia-related failures to adapt brain functioning to the task, which is reflected in poorer behavioral performance.Highlights: - We measured classical and multiscale Lempel-Ziv Complexity (LZCN and MLZC) of the EEG signal of patients with schizophrenia and controls at rest and while performing a cognitive task. - We found that patients and controls showed a different pattern of brain complexity depending on their cognitive state (at rest or under cognitive challenge). - Our results illustrate the value of the MLZC in the characterization of the pattern of brain complexity in schizophrenia on function of frequency bands. - Nonlinear methodologies of EEG analysis can help to characterize brain dysfunction in schizophrenia.

EEG coherence in a mental arithmetic task performance in first episode schizophrenia and schizoaffective disorder

ObjectivesTo evaluate the coherence values of the cortical bands in patients with first episode schizophrenia and schizoaffective disorder during the performance of a mental arithmetic task. MethodWe analysed EEG coherence in the resting state and subsequently while counting down from 200 in steps of 7 in 32 first episode schizophrenia patients (SZ), 32 patients with first episode schizoaffective disorder (SA) and 40 healthy controls (HC). ResultsTask performance in HC is characterised by decreased coherence in the alpha bands and increased coherence in the beta 2 and gamma bands in frontal sites. In SZ, coherence decreases in the alpha band, whereas in SA it substantially increases in the alpha, beta1, beta 2 and gamma bands. ConclusionsDespite no differences in performance on a behavioural level, SA patients demonstrate a paradoxical increase in both low and fast frequency bands during the performance of a mental arithmetic task, while, patients with SZ show a decreased coherence in the alpha band, presumably alluding to the excessive excitatory (in SA) and inhibitory (in SZ) mechanisms in cognitive processing. SignificanceThe current study provides evidence for the distinction of neurophysiological mechanisms of cognitive processing between SZ and SA.

Learning Task-Related Activities From Independent Local-Field-Potential Components Across Motor Cortex Layers.

Motor cortical microcircuits receive inputs from dispersed cortical and subcortical regions in behaving animals. However, how these inputs contribute to learning and execution of voluntary sequential motor behaviors remains elusive. Here, we analyzed the independent components extracted from the local field potential (LFP) activity recorded at multiple depths of rat motor cortex during reward-motivated movement to study their roles in motor learning. Because slow gamma (30–50 Hz), fast gamma (60–120 Hz), and theta (4–10 Hz) oscillations temporally coordinate task-relevant motor cortical activities, we first explored the behavioral state- and layer-dependent coordination of motor behavior in these frequency ranges. Consistent with previous findings, oscillations in the slow and fast gamma bands dominated during distinct movement states, i.e., preparation and execution states, respectively. However, we identified a novel independent component that dominantly appeared in deep cortical layers and exhibited enhanced slow gamma activity during the execution state. Then, we used the four major independent components to train a recurrent network model for the same lever movements as the rats performed. We show that the independent components differently contribute to the formation of various task-related activities, but they also play overlapping roles in motor learning.

Detection of Highly Motivated Time Segments in Brain Computer Interface Signals

ABSTRACTMotivation of a subject, who is associated with the data acquisition of brain computer interface (BCI) experiment, is a very crucial parameter for executing a successful BCI application. This paper proposes a novel method to present the distribution of motivation of a subject during a BCI experiment. The proposed method was successfully applied to the BCI Competition 2003 Data Set III and the BCI Competition 2005 Data Set I using fast Fourier transform-based band power features with a linear discriminant analysis classifier. The results show that not only the motivation of the subject dramatically changes during the trial but also using highly motivated time segments provides 7.86% and 2.00% improvement in the classification accuracy of the BCI Competition 2003 Data Set III and the BCI Competition 2005 Data Set I, respectively.

Synchronous high-frequency oscillations in inhibitory-dominant network motifs consisting of three dentate gyrus-CA3 systems.

Studies on the structural-functional connectomes of the human brain have demonstrated the existence of synchronous firings in a specific brain network motif. In particular, synchronization of high-frequency oscillations (HFOs) has been observed in the experimental data sets of temporal lobe epilepsy (TLE). In addition, both clinical and experimental evidences have accumulated to demonstrate the effect of electrical stimulation on TLE, which, however, remains largely unexplored. In this work, we first employ our previously proposed dentate gyrus (DG)-CA3 network model to investigate the influence of an external electrical stimulus on the HFO transitions. The results indicate that the reinforcing stimulus can induce the HFO transitions of the DG-CA3 system from the gamma band to the fast ripples band. Along with that, the consistent oscillations of neurons within DG-CA3 can also be enhanced with the increasing of stimulus. Then, we expand into a simple motif of three coupled DG-CA3 systems in both the feedforward inhibition and feedback inhibition connections, to investigate the synchronous evolutions of HFOs by regulating both the stimulation strength and inhibitory function. It is shown that the comprehensive effects, which lead to band transition, are independent of the motif configurations. The enhanced external electrical stimulus weakens the synchronism and correlation of connected motifs. In contrast, we demonstrate that the increased inhibitory coupling could facilitate correlation to some extent. Overall, our work highlights the possible origin of synchronous HFOs of hippocampal motifs governed by external inputs and inhibitory connection, which might contribute to a better understanding of the interplay between synchronization dynamics and epileptic structure in the human brain.

Fast hyperspectral band selection based on spatial feature extraction

Hyperspectral images usually consist of hundreds of spectral bands, which can be used to precisely characterize different land cover types. However, the high dimensionality also has some disadvantages, such as the Hughes effect and a high storage demand. Band selection is an effective method to address these issues. However, most band selection algorithms are conducted with the high-dimensional band images, which will bring high computation complexity and may deteriorate the selection performance. In this paper, spatial feature extraction is used to reduce the dimensionality of band images and improve the band selection performance. The experiment results obtained on three real hyperspectral datasets confirmed that the spatial feature extraction-based approach exhibits more robust classification accuracy when compared with other methods. Besides, the proposed method can dramatically reduce the dimensionality of each band image, which makes it possible for band selection to be implemented in real time situations.