Theta Frequency Bands Research Articles

Early development of electrophysiological activity: Contribution of periodic and aperiodic components of the EEG signal.

Brain function rapidly changes in the first 2 years of life. In the last decades, resting-state EEG has been widely used to explore those changes. Previous studies have focused on the relative power of the signal in established frequency bands (i.e., theta, alpha, and beta). However, EEG power is a mixture of a 1/f-like background power (aperiodic) in combination with narrow peaks that appear over that curve (periodic activity, e.g., alpha peak). Therefore, it is possible that relative power captures both, aperiodic and periodic brain activity, contributing to changes in electrophysiological activity observed in infancy. For this reason, we explored the early developmental trajectory of the relative power in theta, alpha, and beta frequency bands from infancy to toddlerhood and compared it with changes in periodic activity in a longitudinal study with three waves at age 6, 9, and 16 to 18 months. Finally, we tested the contribution of periodic activity and aperiodic components of the EEG to age changes in relative power. We found that relative power and periodic activity trajectories differed in this period in all the frequency bands but alpha. Furthermore, aperiodic EEG activity flattened between 6 and 18 months. More importantly, only alpha relative power was exclusively related to periodic activity, whereas aperiodic components of the signal significantly contributed to the relative power of activity in theta and beta bands. Thus, relative power in these frequencies is influenced by developmental changes of the aperiodic activity, which should be considered for future studies.

Individual differences in late positive potential amplitude and theta power predict cue-induced eating

Cue-induced reward-seeking behaviors are regulated by both the affective and cognitive control systems of the brain. This study aimed at investigating how individual differences in affective and cognitive responses to cues predicting food rewards contribute to the regulation of cue-induced eating. We recorded electroencephalogram (EEG) from 59 adults while they viewed emotional and food-related images that preceded the delivery of food rewards (candies) or non-food objects (beads). We measured the amplitude of the late positive potential (LPP) in response to a variety of motivationally relevant images and power in the theta (4-8 Hz) frequency band after candies or beads were dispensed to the participants. We found that individuals with larger LPP responses to food images than to pleasant images (C>P group) ate significantly more during the experiment than those with the opposite response pattern (P>C group, p < 0.001). Furthermore, we found that individuals with higher theta power after dispensation of the candy than of the bead (θCA>θBE) ate significantly more than those with the opposite response pattern (θBE>θCA, p < 0.001). Finally, we found that the crossed P>C and θBE>θCA group ate less (p < 0.001) than did the other three groups formed by crossing the LPP and theta group assignments, who exhibited similar eating behavior on average (p = 0.662). These findings demonstrate that individual differences in both affective and cognitive responses to reward-related cues underlie vulnerability to cue-induced behaviors, underscoring the need for individualized treatments to mitigate maladaptive behaviors.

Neural correlates of perceptual texture change during active touch.

Texture changes occur frequently during real-world haptic explorations, but the neural processes that encode perceptual texture change remain relatively unknown. The present study examines cortical oscillatory changes during transitions between different surface textures during active touch. Participants explored two differing textures whilst oscillatory brain activity and finger position data were recorded using 129-channel electroencephalography and a purpose-built touch sensor. These data streams were fused to calculate epochs relative to the time when the moving finger crossed the textural boundary on a 3D-printed sample. Changes in oscillatory band power in alpha (8-12 Hz), beta (16-24 Hz) and theta (4-7 Hz) frequency bands were investigated. Alpha-band power reduced over bilateral sensorimotor areas during the transition period relative to ongoing texture processing, indicating that alpha-band activity is modulated by perceptual texture change during complex ongoing tactile exploration. Further, reduced beta-band power was observed in central sensorimotor areas when participants transitioned from rough to smooth relative to transitioning from smooth to rough textures, supporting previous research that beta-band activity is mediated by high-frequency vibrotactile cues. The present findings suggest that perceptual texture change is encoded in the brain in alpha-band oscillatory activity whilst completing continuous naturalistic movements across textures.

Is there link between hypoxemia severity and impaired functional connectivity? electrophysiological evidence from patients with obstructive sleep apnea syndrome

AbstractBackgroundApneas occur more than 30 times per hour in severe obstructive sleep apnea syndrome (OSAS) patients. Each apnea results in decrease of oxygen saturation that leads to recurring intermittent hypoxemia (IH). IH was suggested as a possible factor to contribute cognitive impairment in OSAS. In the present study, we aimed to investigate the functional connectivity in low and high hypoxemia OSAS sub‐groups.MethodThe study included 56 severe OSAS patients and age‐, gender‐ and education matched 33 healthy controls (HC). The OSAS group was divided into two subgroups according to their minimum SO2 level: low‐hypoxemia OSAS (SO2 dropped never below 80%, LHO, n = 29) and high‐hypoxemia OSAS (SO2 dropped below 80%, HHO, n = 27). All participants underwent detailed neuropsychological testing and an EEG recording, using auditory classical oddball paradigm. Imaginary coherency (ICOH) was calculated for intra‐hemispheric, inter‐hemispheric and midline electrode pairs in delta, theta, alpha, beta, and gamma frequency bands.ResultLHO patients did not differ from HC in any frequency band. HHO patients showed reduced intra hemispheric ICOH values at delta, theta and beta frequency bands compared to LHO patients. HHO patients also showed decreased intra hemispheric ICOH values at theta, alpha and beta frequency bands compered to HC. Inter hemispheric group differences were found at beta band indicating decreased ICOH values in HHO patients compared to LHO patients. Midline gamma ICOH values decreased in HHO patients compared to both HC and LHO patients. HHO patients showed decreased memory scores compared to both HC and LHO groups and decreased attention scores compared only to HC.ConclusionAs far as we know, this is the first study to investigate event‐related ICOH changes in OSAS. Above results indicates that decreased connectivity in OSAS may be due to increased IH. Patients with low levels of hypoxemia did not differ from healthy controls, yet patients with high hypoxemia showed diffuse functional connectivity changes. Coherency measures revealed a parallel pattern with the neuropsychological tests underpinning the adverse effect of IH on cognitive functions. Considering OSAS as a modifiable risk factor for developing Alzheimer’s disease, treatment methods to prevent intermittent hypoxemia (i.e., positive airway pressure treatment) gains additional importance.

Age‐related cognitive decline are manifested by decreased event‐related delta and theta oscillations

AbstractBackgroundEvent‐related oscillations (EROs) during cognitive paradigms reflect several cognitive functions in the brain. Event‐related delta responses are related to signal detection and decision making processes whereas theta is associated with working memory and selective attention (Yener and Başar, 2013; Başar et al., 2016). During physiological aging, EROs may be altered. The aim of the current study was to investigate time‐frequency measurements of event‐related oscillations in younger and older healthy participants.MethodFifty‐nine healthy participants were included in this study. They were divided into two subgroups as younger and older according to the age median score. Thirty younger healthy participants (mean age 22.37 years; standard deviation: 2.85) and 25 older healthy adults (mean age 56.48 years; standard deviation: 9.71) were completed a visual oddball task during EEG recording. Event‐related band power was assessed using event‐related spectral perturbation. Inter‐trial coherence values were analyzed by phase‐locking measurements. Event‐related power and phase‐locking analysis were performed for delta (0.5‐3.5 Hz), and theta frequency band (4‐7 Hz) over frontal (F3, Fz, F4), central (C3, Cz, C4), parietal (P3, Pz, P4), occipital (O1, Oz, O2) electrode locations. Repeated measures of ANOVA were used for statistical analysis.ResultThere were main GROUP effects for both event‐related delta [F(1,53) = 6.328, p = .015, ηp 2 = .107, Figure 1] and theta power [F(1,53) = 28.069, p&lt;.001, ηp 2 = .346, Figure 2], indicating older healthy adults had reduced power values compared to younger healthy individuals (for all; p&lt;.016). Furthermore, an interaction effect of Anterior‐Posterior Electrode Location x Group was found for theta power [F(3,159) = 13.869, p&lt;.001, ηp 2 = .207], showing older healthy individuals had reductions in all electrode locations (for all; p&lt;.017). Lastly, event‐related theta phase‐locking values were found to be reduced in older healthy adults [F(1,53) = 5.512, p = .023, ηp 2 = .094, Figure 3].ConclusionThe present study demonstrated older healthy participants had decreased event‐related delta and theta responses during visual oddball paradigm. These reductions may be explained by the alterations in cognitive capacities such as working memory/attention and decline in processing information during healthy aging. Acknowledgement: The inclusion of younger healthy participants in this study was supported by Ankara University Scientific Research Projects Coordination Unit (Project Number: 16L02000001).

What a single electroencephalographic (EEG) channel can tell us about Alzheimer's disease patients with mild cognitive impairment

AbstractBackgroundAbnormalities in the neurophysiological oscillatory mechanisms generating dominant resting‐state eyes closed electroencephalographic (rsEEG) rhythms portray the Alzheimer’s disease (AD) continuum, from the preclinical to the dementia stage. Here, we tested whether these abnormalities may be reproducible by analyzing the rsEEG signals acquired in bipolar configuration with a montage consisting of only four centro‐parietal and parieto‐occipital channels (C3‐P3, C4‐P4, P3‐O1, and P4‐O2) in patients with mild cognitive impairment (MCI) due to AD (ADMCI).MethodTo evaluate the study hypotheses, clinical, neuropsychological, anthropometric, genetic, cerebrospinal fluid (CSF), MRI, and rsEEG data in 70 Nold and 75 ADMCI subjects from an international archive were used in the present study. The subgroups were matched for age, gender, and education. In all subjects, rsEEG recordings lasted about 3‐5 minutes. The rsEEG data were recorded with a sampling frequency of 128‐512 Hz and related antialiasing bandpass between 0.01 Hz and 60‐100 Hz. Electrode montage included 19 scalp monopolar sensors placed following 10‐20 System. The rsEEG rhythms were investigated at individual delta, theta, and alpha frequency bands as well as fixed beta (14‐30 Hz) and gamma (30‐40 Hz) bands.ResultResults confirmed previous evidence about the abnormalities of the delta, theta, and alpha rhythms in ADMCI patients compared to Nold subjects. Moreover, as compared to the Nold group, the ADMCI group showed increased delta power density and decreased alpha power density at the C3‐P3, C4‐P4, P3‐O1, and P4‐O2 bipolar channels. Increased theta power density for ADMCI patients was observed only at the C3‐P3 bipolar channel. Best classification accuracy between the ADMCI and Nold individuals reached 81% (area under the receiver operating characteristic curve) using Alpha2/Theta power density computed at the C3‐P3 bipolar channel.ConclusionThe current findings provide evidence in the potential use of rsEEG low‐channel portable devices as a topographic biomarker of cognitive decline within the extensive screening of in elderly population at risk of developing AD‐ or other dementia‐related disorders. Moreover, the confirmation of this hypothesis would have exciting applications in the framework of telehealth home monitoring of global brain functions.

ID: 209661 Pilot Study Investigating Sensing Utility to Optimize Deep Brain Stimulation Parameters in Parkinson's Disease

Optimizing deep brain stimulation (DBS) programming for movement disorders requires a trial-and-error process evaluating clinical benefit and adverse effects. Recent advances in sensing technology may enable improvements in selecting optimal settings.1 The use of this technology in programming and comparing clinical outcomes to standard of care has not been fully evaluated. For this study, we assessed whether recorded acute local field potential (LFP) biomarkers can be used in the clinic to optimize DBS parameter programming, and we characterized the reliability of LFP biomarkers, specifically within the theta (4-8Hz), beta (13-30Hz), and gamma (35-90Hz) frequency bands.2

Brain neural synchronization mechanisms are affected by aging in cognitively unimpaired seniors and patients with Alzheimer’s disease and mild cognitive impairment

AbstractBackgroundThe resting state eyes‐closed electroencephalographic (rsEEG) alpha (8‐12 Hz) rhythms reflect cortical neural synchronization mechanisms underpinning the inhibition of sensory, cognitive, and motor areas in parietal, temporal, and occipital cortex during a condition of low vigilance. Here we tested the hypothesis that age may diversely affect rsEEG alpha (8‐12 Hz) rhythms recorded in normal elderly (Nold) seniors and patients with Alzheimer’s disease and mild cognitive impairment (ADMCI).MethodClinical, magnetic resonance imaging (MRI) and rsEEG datasets in 63 ADMCI and 60 Nold individuals were taken from an international archive. The rsEEG rhythms were investigated at individual delta, theta, and alpha frequency bands as well as fixed beta (14‐30 Hz) and gamma (30‐40 Hz) bands. Each group was stratified into three subgroups based on age ranges (i.e., tertiles).ResultAs compared to the younger Nold subgroups, the older one showed greater reductions in the rsEEG alpha rhythms with major topographical effects in posterior regions (Figure 1). On the contrary, in relation to the younger ADMCI subgroups, the older one displayed lesser reduction in those rhythms (Figure 1). Furthermore, a decrease in the total grey matter (GM) volume and total cortical thickness as well as an increase in the white matter (WM) hypointensity were found in the older ADMCI subgroups compared to the younger ADMCI subgroups (Figure 2).ConclusionThe results of the present study suggest that in Nold seniors, the aging factor may significantly affect neurophysiological brain neural synchronization mechanisms underpinning the generation of dominant rsEEG alpha rhythms. In contrast, rsEEG alpha rhythms in ADMCI patients may be more affected by the disease variants, with more deleterious effects observed in early‐ than the late‐onset ADMCI patients. In the ADMCI patients, the mere effects of the aging factor may be hidden by dysfunctions in subcortical structures, including the cholinergic basal forebrain and thalamus.

A Review on the Cognitive Neural Mechanisms of Anaphor Processing During Language Comprehension.

Anaphora is an essential means of maintaining textual coherence, the phenomenon of replacing one word or phrase in the preceding part of a discourse with another. At least two crucial stages are involved in anaphor processing: bonding and resolution. The links between the anaphor and potential antecedents are established in the former stage, which would be evaluated and integrated into the latter stage. We reviewed relevant event-related potential (ERP) studies that examined the time course of anaphor processing and neural oscillation studies that explored energy changes in alpha, theta, and gamma frequency bands, which were associated with attention, working memory retrieval, and integration, respectively. The existing neuroimaging studies revealed the involvement of language processing networks and the Theory of Mind (ToM). Further research should explore the neural correlates and the effects of potential factors on anaphor processing, which could help gain a more comprehensive picture from multiple perspectives.

Effects of emotional decorative pictures on cognitive load as assessed by pupil dilation and EEG frequency band power

AbstractThe present study examined the effects of decorative pictures (DP) on cognitive load during learning factual knowledge from texts assessed by physiological proxies, namely pupil dilation and the electroencephalogram (EEG) theta (4–6 Hz) and alpha (8–13 Hz) frequency band power at frontal and parietal electrodes, respectively. In a complete within‐subjects design the presence of DP positioned beside learning texts and the emotional content of the DP (i.e., negative, neutral, and positive DP) were manipulated. For DP present, pupil dilation and the EEG alpha frequency band power indicated increased cognitive load, specifically for negative DP. Behavioral performance measures (i.e., learning times and learning outcomes) were not affected by the presence of DP. Subjective effort ratings were also not affected by DP, although specifically the negative DP were subjectively perceived as distracting. In sum, DP only moderately affected cognitive load allowing subjects to compensate.

Language-related brain areas in childhood epilepsy with centrotemporal spikes studied with MEG

ObjectiveChildren with self-limited epilepsy with centrotemporal spikes (SeLECTS) typically indicate cognitive impairment with widespread speech impairment. We explored how epilepsy affects language-related brain areas and areas in their vicinity. MethodsTwenty-two children with SeLECTS and declined verbal comprehension (DVC), 21 with SeLECTS and normal verbal comprehension (NVC), and 23 healthy controls (HCs) underwent high-sampling magnetoencephalography recordings. According to a previous study, 24 language-related regions of interest were selected bilaterally, and the relative spectral power was estimated using a minimum norm estimate. ResultsThe highest mean power spectral density was observed in the delta band for the DVC group, in the theta band for the NVC group, and in the alpha band for HCs within language-specific brain regions. The distinctions between the DVC and NVC groups in the delta and theta frequency bands were primarily concentrated in the right linguistic brain area. ConclusionsChildren with SeLECTS may have developmental problems in language-related brain areas, with different developmental levels observed in the DVC, NVC, and HC groups. The DVC group could have inferior speech comprehension due to a more significant number of seizures and more left-sided spike locations. SignificanceChildren having SeLECTS showed impaired brain maturation, leading to associated language impairment.

Hemodynamic and Electrophysiological Biomarkers of Interpersonal Tuning during Interoceptive Synchronization

This research explored the influence of interoception and social frame on the coherence of inter-brain electrophysiological (EEG) and hemodynamic (collected by functional Near Infrared Spectroscopy, fNIRS) functional connectivity during a motor synchronization task. Fourteen dyads executed a motor synchronization task with the presence and absence of interoceptive focus. Moreover, the motor task was socially or not-socially framed by enhancing the shared intentionality. During the experiment, delta, theta, alpha, and beta frequency bands, and oxygenated and de-oxygenated hemoglobin (O2Hb and HHb) were collected through an EEG-fNIRS hyperscanning paradigm. Inter-brain coherence indices were computed for the two neurophysiological signals and then they were correlated to explore the reciprocal coherence of the functional connectivity EEG-fNIRS in the dyads. Findings showed significant higher correlational values between delta and O2Hb, theta and O2Hb, and alpha and O2Hb for the left hemisphere in the focus compared to the no focus condition and to the right hemisphere (both during focus and no focus condition). Additionally, greater correlational values between delta and O2Hb, and theta and O2Hb were observed in the left hemisphere for the focus condition when the task was socially compared to non-socially framed. This study showed that the focus on the breath and shared intentionality activate coherently the same left frontal areas in dyads performing a joint motor task.

Chemical suppression of harmaline-induced body tremor yields recovery of pairwise neuronal coherence in cerebellar nuclei neurons.

Neuronal oscillations occur in health and disease; however, their characteristics can differ across conditions. During voluntary movement in freely moving rats, cerebellar nuclei (CN) neurons display intermittent but coherent oscillations in the theta frequency band (4-12 Hz). However, in the rat harmaline model of essential tremor, a disorder attributed to cerebellar malfunction, CN neurons display aberrant oscillations concomitantly with the emergence of body tremor. To identify the oscillation features that may underlie the emergence of body tremor, we analyzed neuronal activity recorded chronically from the rat CN under three conditions: in freely behaving animals, in harmaline-treated animals, and during chemical suppression of the harmaline-induced body tremor. Suppression of body tremor did not restore single neuron firing characteristics such as firing rate, the global and local coefficients of variation, the likelihood of a neuron to fire in bursts or their tendency to oscillate at a variety of dominant frequencies. Similarly, the fraction of simultaneously recorded neuronal pairs oscillating at a similar dominant frequency (<1 Hz deviation) and the mean frequency deviation within pairs remained similar to the harmaline condition. Moreover, the likelihood that pairs of CN neurons would co-oscillate was not only significantly lower than that measured in freely moving animals, but was significantly worse than chance. By contrast, the chemical suppression of body tremor fully restored pairwise neuronal coherence; that is, unlike in the harmaline condition, pairs of neurons that oscillated at the same time and frequency displayed high coherence, as in the controls. We suggest that oscillation coherence in CN neurons is essential for the execution of smooth movement and its loss likely underlies the emergence of body tremor.

Differences in electroencephalography oscillations between normal aging and mild cognitive impairment during semantic memory retrieval.

Semantic memory remains relatively stable with normal cognitive aging and declines in early stages of neurodegenerative disease. We measured electroencephalography (EEG) oscillatory correlates of semantic memory retrieval to examine the effects of normal and pathological aging. Twenty-nine cognitively healthy young adults (YA), 22 cognitively healthy aging adults (HA) and 20 patients with mild cognitive impairment (MCI) completed a semantic memory retrieval task with concurrent EEG recording in which they judged whether two words (features of objects) led to retrieval of an object (retrieval) or not (non-retrieval). Event-related power changes contrasting the two conditions (retrieval vs. non-retrieval) within theta, alpha, low-beta and high-beta EEG frequency bands were examined for normal aging (YA vs. HA) and pathological aging effects (HA vs. MCI). With no behavioural differences between the two normal age groups, we found later theta and alpha event-related power differences between conditions only in YA and a high-beta event-related power difference only in HA. For pathological aging effects, with reduced accuracy in MCI, we found different EEG patterns of early event-related beta power differences between conditions in MCI compared with HA and an event-related low-beta power difference only in HA. Beta oscillations were correlated with behavioural performance only in HA. We conclude that the aging brain relies on faster (beta) oscillations during the semantic memory task. With pathological aging, retrieval accuracy declines and pattern of beta oscillation changes. The findings provide insights about age-related neural mechanisms underlying semantic memory and have implications for early detection of pathological aging.

Machine learning for the detection of social anxiety disorder using effective connectivity and graph theory measures.

The early diagnosis and classification of social anxiety disorder (SAD) are crucial clinical support tasks for medical practitioners in designing patient treatment programs to better supervise the progression and development of SAD. This paper proposes an effective method to classify the severity of SAD into different grading (severe, moderate, mild, and control) by using the patterns of brain information flow with their corresponding graphical networks. We quantified the directed information flow using partial directed coherence (PDC) and the topological networks by graph theory measures at four frequency bands (delta, theta, alpha, and beta). The PDC assesses the causal interactions between neuronal units of the brain network. Besides, the graph theory of the complex network identifies the topological structure of the network. Resting-state electroencephalogram (EEG) data were recorded for 66 patients with different severities of SAD (22 severe, 22 moderate, and 22 mild) and 22 demographically matched healthy controls (HC). PDC results have found significant differences between SAD groups and HCs in theta and alpha frequency bands (p < 0.05). Severe and moderate SAD groups have shown greater enhanced information flow than mild and HC groups in all frequency bands. Furthermore, the PDC and graph theory features have been used to discriminate three classes of SAD from HCs using several machine learning classifiers. In comparison to the features obtained by PDC, graph theory network features combined with PDC have achieved maximum classification performance with accuracy (92.78%), sensitivity (95.25%), and specificity (94.12%) using Support Vector Machine (SVM). Based on the results, it can be concluded that the combination of graph theory features and PDC values may be considered an effective tool for SAD identification. Our outcomes may provide new insights into developing biomarkers for SAD diagnosis based on topological brain networks and machine learning algorithms.

Specific patterns of coherence and phase lag index in particular regions as biomarkers of cognitive impairment in Parkinson's disease

IntroductionCognitive impairment is a persistent and increasingly reported symptom of patients with Parkinson's disease (PD), significantly affecting daily functioning quality. This study aims to evaluate the functional connectivity of the brain network in patients with Parkinson's disease with various severities of cognitive decline using quantitative electroencephalography (EEG) analysis. MethodsBased on the EEG recorded in the resting state, the coherence and phase lag index were calculated to evaluate functional connectivity in 108 patients with Parkinson's disease divided into three groups according to their cognitive condition: dementia due to PD (PD-D), PD and mild cognitive impairment (PD-MCI) and cognitively normal patients (PD-CogN). ResultsIt was found that there were significantly different coherence values in the PD-D group compared to PD-CogN in different frequency bands. In most cases, there was a decrease in coherence in PD-D compared to PD-CogN. The most specific changes were revealed in the theta frequency band in the temporal right-frontal left and temporal right-frontal right regions. In the alpha frequency band, the most significant decreases were shown in the occipital right-frontal left and occipital left-frontal right areas. There were also statistically significant differences in phase lag index between many areas, especially in the theta frequency range. ConclusionsThese findings indicate that the functional connectivity patterns of coherence and phase lag index – found in a particular frequency band and region – could become a reliable biomarker for identifying cognitive impairment and differentiating its severity in PD patients.

Interplay between alpha and theta band activity enables management of perception-action representations for goal-directed behavior

Goal-directed behavior requires integrated mental representations of perceptions and actions. The neurophysiological underpinnings of these processes, however, are not yet understood. It is particularly undetermined, which oscillatory activities in which brain regions are involved in the management of perception-action representations. We examine this question with a focus on response inhibition processes and show that the dynamics of perception-action representations reflected in theta band activity (TBA) are particularly evident in the supplementary motor area and the occipito-temporal cortex. Mental representations coded in alpha band activity (ABA) during perception-action integration are associated with the occipito-temporal cortex. Crucially, perception-action representations are exchanged between theta and alpha frequency bands. The results imply that ABA functions as dynamic top-down control over binding, retrieval and reconfiguration processes during response inhibition, which in turn are reflected by TBA. Our study thus highlights how the interplay of oscillatory activity enables the management of perception-action representations for goal-directed behavior.

Exergaming in older adults: the effects of game characteristics on brain activity and physical activity.

Exergames are increasingly used in rehabilitation settings for older adults to train physical and cognitive abilities. To meet the potential that exergames hold, they need to be adapted to the individual abilities of the player and their training objectives. Therefore, it is important to know whether and how game characteristics affect their playing. The aim of this study is to investigate the effect of two different kinds of exergame (step game and balance game) played at two difficulty levels on brain activity and physical activity. Twenty-eight older independently living adults played two different exergames at two difficulty levels each. In addition, the same movements as during gaming (leaning sideways with feet in place and stepping sideways) were performed as reference movements. Brain activity was recorded using a 64-channel EEG system to assess brain activity, while physical activity was recorded using an accelerometer at the lower back and a heart rate sensor. Source-space analysis was applied to analyze the power spectral density in theta (4 Hz-7 Hz) and alpha-2 (10 Hz-12 Hz) frequency bands. Vector magnitude was applied to the acceleration data. Friedman ANOVA revealed significantly higher theta power for the exergaming conditions compared to the reference movement for both games. Alpha-2 power showed a more diverse pattern which might be attributed to task-specific conditions. Acceleration decreased significantly from the reference movement to the easy condition to the hard condition for both games. The results indicate that exergaming increases frontal theta activity irrespective of type of game or difficulty level, while physical activity decreases with increasing difficulty level. Heart rate was found to be an inappropriate measure in this population older adults. These findings contribute to understanding of how game characteristics affect physical and cognitive activity and consequently need to be taken into account when choosing appropriate games and game settings for exergame interventions.

Spatial-Temporal EEG Fusion Based on Neural Network for Major Depressive Disorder Detection.

In view of the major depressive disorder characteristics such as high mortality as well as high recurrence, it is important to explore an objective and effective detection method for major depressive disorder. Considering the advantages complementary of different machine learning algorithms in information mining process, as well as the fusion complementary of different information, in this study, the spatial-temporal electroencephalography fusion framework using neural network is proposed for major depressive disorder detection. Since electroencephalography is a typical time series signal, we introduce recurrent neural network embedded in long short-term memory unit for extract temporal domain features to solve the problem of long-distance information dependence. To reduce the volume conductor effect, the temporal electroencephalography data are mapping into a spatial brain functional network using phase lag index, then the spatial domain features were extracted from brain functional network using 2D convolutional neural networks. Considering the complementarity between different types of features, the spatial-temporal electroencephalography features are fused to achieve data diversity. The experimental results show that spatial-temporal features fusion can improve the detection accuracy of major depressive disorder with a highest of 96.33%. In addition, our research also found that theta, alpha, and full frequency band in brain regions of left frontal, left central, right temporal are closely related to MDD detection, especially theta frequency band in left frontal region. Only using single-dimension EEG data as decision basis, it is difficult to fully explore the valuable information hidden in the data, which affects the overall detection performance of MDD.Meanwhile, different algorithms have their own advantages for different application scenarios. Ideally, different algorithms should use their respective advantages to jointly address complex problems in engineering fields.To this end, we propose a computer-aided MDD detection framework based on spatial-temporal EEG fusion using neural network, as shown in Fig.1. The simplified process is as follows: (1) Raw EEG data acquisition and preprocessing. (2) The time series EEG data of each channel are input as recurrent neural network (RNN), and RNN is used to process and extract temporal domain (TD) features. (3) The BFN among different EEG channels is constructed, and CNN is used to process and extract the spatial domain (SD) features of the BFN. (4) Based on the theory of information complementarity, the spatial-temporal information is fused to realize efficient MDD detection. Fig. 1 MDD detection framework based on spatial-temporal EEG fusion.

Theta- and gamma-band oscillatory uncoupling in the macaque hippocampus.

Nested hippocampal oscillations in the rodent give rise to temporal dynamics that may underlie learning, memory, and decision making. Although theta/gamma coupling in rodent CA1 occurs during exploration and sharp-wave ripples emerge in quiescence, it is less clear that these oscillatory regimes extend to primates. We therefore sought to identify correspondences in frequency bands, nesting, and behavioral coupling of oscillations taken from macaque hippocampus. We found that, in contrast to rodent oscillations, theta and gamma frequency bands in macaque CA1 were segregated by behavioral states. In both stationary and freely moving designs, beta2/gamma (15-70 Hz) had greater power during visual search whereas the theta band (3-10 Hz; peak ~8 Hz) dominated during quiescence and early sleep. Moreover, theta-band amplitude was strongest when beta2/slow gamma (20-35 Hz) amplitude was weakest, instead occurring along with higher frequencies (60-150 Hz). Spike-field coherence was most frequently seen in these three bands (3-10 Hz, 20-35 Hz, and 60-150 Hz); however, the theta-band coherence was largely due to spurious coupling during sharp-wave ripples. Accordingly, no intrinsic theta spiking rhythmicity was apparent. These results support a role for beta2/slow gamma modulation in CA1 during active exploration in the primate that is decoupled from theta oscillations. The apparent difference to the rodent oscillatory canon calls for a shift in focus of frequency when considering the primate hippocampus.