Theta Rhythm Research Articles

Effects of acute administration of 4-allyl-2,6-dimethoxyphenol in mouse models of seizures

Epilepsy, a chronic neurological disorder characterized by recurrent unprovoked seizures, presents a substantial challenge in approximately one-third of cases exhibiting resistance to conventional pharmacological treatments. This study investigated the effect of 4-allyl-2,6-dimethoxyphenol, a phenolic compound derived from various natural sources, in different models of induced seizures and its impact on animal electroencephalographic (EEG) recordings. Adult male Swiss albino mice were pre-treated (i.p.) with a dose curve of 4-allyl-2,6-dimethoxyphenol (50, 100, or 200 mg/kg), its vehicle (Tween), or standard antiepileptic drug (Diazepam; or Phenytoin). Subsequently, the mice were subjected to different seizure-inducing models – pentylenetetrazole (PTZ), 3-mercaptopropionic acid (3-MPA), pilocarpine (PILO), or maximal electroshock seizure (MES). EEG analysis was performed on other animals surgically implanted with electrodes to evaluate brain activity. Significant results revealed that animals treated with 4-allyl-2,6-dimethoxyphenol exhibited increased latency to the first myoclonic jerk in the PTZ and PILO models; prolonged latency to the first tonic-clonic seizure in the PTZ, 3-MPA, and PILO models; reduced total duration of tonic-clonic seizures in the PTZ and PILO models; decreased intensity of convulsive seizures in the PTZ and 3-MPA models; and diminished mortality in the 3-MPA, PILO, and MES models. EEG analysis indicated an increase in the percentage of total power attributed to beta waves following 4-allyl-2,6-dimethoxyphenol administration. Notably, the substance protected from behavioral and electrographic seizures in the PTZ model, preventing increases in the average amplitude of recording signals while also inducing an increase in the participation of theta and gamma waves. These findings suggest promising outcomes for the tested phenolic compound across diverse pre-clinical seizure models, highlighting the need for further comprehensive studies to elucidate its underlying mechanisms and validate its clinical relevance in epilepsy management.

Using synchronized brain rhythms to bias memory-guided decisions

Functional interactions between the prefrontal cortex and hippocampus, as revealed by strong oscillatory synchronization in the theta (6–11 Hz) frequency range, correlate with memory-guided decision-making. However, the degree to which this form of long-range synchronization influences memory-guided choice remains unclear. We developed a brain-machine interface that initiated task trials based on the magnitude of prefrontal-hippocampal theta synchronization, then measured choice outcomes. Trials initiated based on strong prefrontal-hippocampal theta synchrony were more likely to be correct compared to control trials on both working memory-dependent and -independent tasks. Prefrontal-thalamic neural interactions increased with prefrontal-hippocampal synchrony and optogenetic activation of the ventral midline thalamus primarily entrained prefrontal theta rhythms, but dynamically modulated synchrony. Together, our results show that prefrontal-hippocampal theta synchronization leads to a higher probability of a correct choice and strengthens prefrontal-thalamic dialogue. Our findings reveal new insights into the neural circuit dynamics underlying memory-guided choices and highlight a promising technique to potentiate cognitive processes or behavior via brain-machine interfacing.

Using synchronized brain rhythms to bias memory-guided decisions.

Functional interactions between the prefrontal cortex and hippocampus, as revealed by strong oscillatory synchronization in the theta (6-11 Hz) frequency range, correlate with memory-guided decision-making. However, the degree to which this form of long-range synchronization influences memory-guided choice remains unclear. We developed a brain-machine interface that initiated task trials based on the magnitude of prefrontal-hippocampal theta synchronization, then measured choice outcomes. Trials initiated based on strong prefrontal-hippocampal theta synchrony were more likely to be correct compared to control trials on both working memory-dependent and -independent tasks. Prefrontal-thalamic neural interactions increased with prefrontal-hippocampal synchrony and optogenetic activation of the ventral midline thalamus primarily entrained prefrontal theta rhythms, but dynamically modulated synchrony. Together, our results show that prefrontal-hippocampal theta synchronization leads to a higher probability of a correct choice and strengthens prefrontal-thalamic dialogue. Our findings reveal new insights into the neural circuit dynamics underlying memory-guided choices and highlight a promising technique to potentiate cognitive processes or behavior via brain-machine interfacing.

Различия в спектральной мощности ЭЭГ и поведении детей с аутистическими расстройствами несиндромального происхождения и с синдромом Дауна

<p style="text-align: justify;">The diverse nature of the autistic spectrum disorders group (ASD) may be associated with EEG patterns, which may be specific for different profiles of ASD. Approximately 15% of children with Down syndrome (DS) exhibit autistic features, and the cognitive impairment associated with this syndrome remains unclear. We aimed to explore the potential similarities in behavioral disorders and their EEG correlates between non-syndromic ASD and DS children with comorbid autistic features. Three groups of right-handed boys participated in the experiments: typically developed boys (“control”) — N = 36; mean age = 7.11, SD = 0.86; DS group age N = 15, mean age 7.2 (SD = 0.94), and ASD group; N — 36; mean age — 7.11, SD — 0.86; DS group age N — 15, mean age 7.2 (SD — 0.94), and ASD group; N — 39; mean age — 6.24 (SD — 0.91). Increased theta rhythm spectral power in EEG was found in the frontal and temporal areas, while the alpha rhythm in the occipital area exhibited a reduction in children with DS and ASD as compared with control. The alterations in bioelectric activity, such as increased spectral power f theta in the frontal area and a reduction of EEG spectral power in the occipital alpha band, were partially similar in children with DS and with ASD, albeit less pronounced in DS. A distinctive EEG characteristic of DS was the heightened spectral power of beta rhythm compared to the control group. The Psychoeducational Profile testing in DS revealed inferior results in verbal development (p < 0.05) and cognitive representations (p < 0.05) compared to both the control and ASD groups. However, no differences were found in the total cognitive development scale between DS and ASD. At the behavioral level, impaired verbal and non-verbal intelligence was more prominent in DS than in ASD.</p>

How to design optimal brain stimulation to modulate phase-amplitude coupling?

Objective. Phase-amplitude coupling (PAC), the coupling of the amplitude of a faster brain rhythm to the phase of a slower brain rhythm, plays a significant role in brain activity and has been implicated in various neurological disorders. For example, in Parkinson’s disease, PAC between the beta (13–30 Hz) and gamma (30–100 Hz) rhythms in the motor cortex is exaggerated, while in Alzheimer’s disease, PAC between the theta (4–8 Hz) and gamma rhythms is diminished. Modulating PAC (i.e. reducing or enhancing PAC) using brain stimulation could therefore open new therapeutic avenues. However, while it has been previously reported that phase-locked stimulation can increase PAC, it is unclear what the optimal stimulation strategy to modulate PAC might be. Here, we provide a theoretical framework to narrow down the experimental optimisation of stimulation aimed at modulating PAC, which would otherwise rely on trial and error. Approach. We make analytical predictions using a Stuart–Landau model, and confirm these predictions in a more realistic model of coupled neural populations. Main results. Our framework specifies the critical Fourier coefficients of the stimulation waveform which should be tuned to optimally modulate PAC. Depending on the characteristics of the amplitude response curve of the fast population, these components may include the slow frequency, the fast frequency, combinations of these, as well as their harmonics. We also show that the optimal balance of energy between these Fourier components depends on the relative strength of the endogenous slow and fast rhythms, and that the alignment of fast components with the fast rhythm should change throughout the slow cycle. Furthermore, we identify the conditions requiring to phase-lock stimulation to the fast and/or slow rhythms. Significance. Together, our theoretical framework lays the foundation for guiding the development of innovative and more effective brain stimulation aimed at modulating PAC for therapeutic benefit.

Benign epileptiform variants in EEG: A comprehensive study of 3000 patients

BackgroundThe analysis of EEG demands expertise and keen observation to distinguish epileptiform discharges from benign epileptiform variants (BEVs), a frequent source of erroneous interpretation. The prevalence of BEVs varies based on geographical, racial, and ethnic characteristics. However, most data on BEVs originates from Western populations, and additional studies on different cohorts would enrich the existing literature. MethodsWe reviewed EEGs from our institutional database to study the prevalence of benign epileptiform variants and analyzed their frequency, topography, and other characteristics. Additionally, we investigated the co-existence of epileptiform discharges with BEVs. ResultsWe identified 296 patients with BEVs after reviewing 3000 EEGs (9.9%). The most common BEV was small sharp spikes (SSS), observed in 114 patients (3.8%). Wicket waves, 6 Hz spike and slow wave, 14 and 6 Hz positive bursts, and Rhythmic Temporal Theta of Drowsiness (RTTD) were identified in 67 (2.2%), 40 (1.3%), 39 (1.3%), and 35 (1.16%) patients, respectively and one patient with Subclinical Rhythmic EEG Discharges in Adults (SREDA). Additionally, we observed the co-existence of epileptiform discharges with BEVs, most commonly with SSS (27.8%). ConclusionsThe present study is a large study with 3000 EEGs to describe the BEV characteristics. BEVs were seen in 9.9% of patients, BSSS being the most common. There were minor differences in frequency, gender or age distribution compared to existing literature. We demonstrated the co-existence of epileptiform discharges. Morphological characteristics remain the cornerstone in recognising BEVs. EEG readers need to be aware of features of BEVs to avoid wrongly interpretation.

Dopamine and deep brain stimulation accelerate the neural dynamics of volitional action in Parkinson's disease.

The ability to initiate volitional action is fundamental to human behaviour. Loss of dopaminergic neurons in Parkinson's disease is associated with impaired action initiation, also termed akinesia. Both dopamine and subthalamic deep brain stimulation (DBS) can alleviate akinesia, but the underlying mechanisms are unknown. An important question is whether dopamine and DBS facilitate de novo build-up of neural dynamics for motor execution or accelerate existing cortical movement initiation signals through shared modulatory circuit effects. Answering these questions can provide the foundation for new closed-loop neurotherapies with adaptive DBS, but the objectification of neural processing delays prior to performance of volitional action remains a significant challenge. To overcome this challenge, we studied readiness potentials and trained brain signal decoders on invasive neurophysiology signals in 25 DBS patients (12 female) with Parkinson's disease during performance of self-initiated movements. Combined sensorimotor cortex electrocorticography and subthalamic local field potential recordings were performed OFF therapy (n = 22), ON dopaminergic medication (n = 18) and on subthalamic deep brain stimulation (n = 8). This allowed us to compare their therapeutic effects on neural latencies between the earliest cortical representation of movement intention as decoded by linear discriminant analysis classifiers and onset of muscle activation recorded with electromyography. In the hypodopaminergic OFF state, we observed long latencies between motor intention and motor execution for readiness potentials and machine learning classifications. Both, dopamine and DBS significantly shortened these latencies, hinting towards a shared therapeutic mechanism for alleviation of akinesia. To investigate this further, we analysed directional cortico-subthalamic oscillatory communication with multivariate granger causality. Strikingly, we found that both therapies independently shifted cortico-subthalamic oscillatory information flow from antikinetic beta (13-35 Hz) to prokinetic theta (4-10 Hz) rhythms, which was correlated with latencies in motor execution. Our study reveals a shared brain network modulation pattern of dopamine and DBS that may underlie the acceleration of neural dynamics for augmentation of movement initiation in Parkinson's disease. Instead of producing or increasing preparatory brain signals, both therapies modulate oscillatory communication. These insights provide a link between the pathophysiology of akinesia and its' therapeutic alleviation with oscillatory network changes in other non-motor and motor domains, e.g. related to hyperkinesia or effort and reward perception. In the future, our study may inspire the development of clinical brain computer interfaces based on brain signal decoders to provide temporally precise support for action initiation in patients with brain disorders.

Barefoot walking improves cognitive ability in adolescents.

Walking can have a positive impact on cognitive function in adolescents. This study aimed to compare the effects of walking with sneakers and barefoot on cognitive ability in adolescents. Fifty-nine adolescent male students were included in the study and assigned to the control (n = 20), sneaker (n = 19), and barefoot (n = 20) groups. The barefoot and sneakers group performed a 40-min walking exercise four times a week for 12 weeks during the morning physical activity time, while the control group performed self-study. Electroencephalogram (EEG) and brain activity variables were measured before and after the exercise program. The results showed that after 12 weeks, the barefoot group had a significant decrease in Gamma and H-beta waves and a significant increase in sensorimotor rhythm (SMR) and Alpha waves. Conversely, the control group showed a significant decrease in SMR waves and increase in Theta waves. The sneaker group showed a significant decrease in SMR waves alone. In an eyes-open resting state, the barefoot group showed a significant increase in H-beta, M-beta, SMR, and Alpha waves. The barefoot group also had a significant increase in cognitive speed and concentration and a significant decrease in brain stress. Taken together, barefoot walking can effectively enhance cognitive ability in adolescents, as demonstrated by the significant variation in EEG activity. This research highlights the potential benefits of barefoot walking as a simple and effective form of exercise for enhancing cognitive function in adolescents.

Multi-origins of pathological theta oscillation from neuron to network inferred by a combined data and model study with cubature Kalman filter

The brain rhythm is strongly associated with the brain function. Alzheimer's disease (AD) is characterized reflected by the brain rhythm switching from the alpha band (9–12 Hz) to the theta band (4–8 Hz), accompanied with the loss of brain function. However, extracting the implicating intrinsic characteristic variations of the brain network by utilizing the Electroencephalogram (EEG) information is challenging. Kaman observer, serving as an effective Bayesian technique, can provide a visualization service for probing the intrinsic characteristics underlying the pathological theta oscillations. This work first establishes an excitation-inhibitory neural network model and explores the role of the fraction of the inhibitory neurons and inhibitory synapses in the pathological theta oscillation. The results indicate that the reduced inhibitory neuronal proportion and attenuated inhibitory synaptic weight are the main neural bases of the frequency reduction of neural oscillation. Then, we further explore the intrinsic spiking characteristic by considering spike frequency adaptation (SFA) to the inhibitory neurons. The results show that the SFA reduces the firing rate of neurons, which facilitates the theta rhythm. The enhancement of SFA current by increasing the time constant of its gating variable can further decrease the theta frequency from 7 Hz to 4 Hz. Furthermore, for this high-dimensional nonlinear excitation-inhibitory neural network model, cubature Kalman filter (CKF) is employed to estimate the above potential variations from the EEG data. The observation results show that the attenuated trends of the inhibitory neuronal proportion and the decreased inhibitory SFA current result in the descending brain rhythm. Finally, the theoretical simulation is deduced by utilizing the mean field theory for simplifying high-dimensional model to verify the simulation results. The theoretical variations of inhibitory parameters and adaptation gating variable are consistent with the simulation results. In summary, we investigate the multi-origin factors related to inhibitory neuronal intrinsic characteristics from forward model simulation and inverse EEG estimation process. And we further verify the simulation and data-driven results by theoretical derivation. This work enhances the understanding of the systematic function of inhibitory intrinsic characteristics on pathological theta oscillation and provides an effective method to decode the dynamics underlying neural activities.

Modeling the contribution of theta-gamma coupling to sequential memory, imagination, and dreaming.

Gamma oscillations nested in a theta rhythm are observed in the hippocampus, where are assumed to play a role in sequential episodic memory, i.e., memorization and retrieval of events that unfold in time. In this work, we present an original neurocomputational model based on neural masses, which simulates the encoding of sequences of events in the hippocampus and subsequent retrieval by exploiting the theta-gamma code. The model is based on a three-layer structure in which individual Units oscillate with a gamma rhythm and code for individual features of an episode. The first layer (working memory in the prefrontal cortex) maintains a cue in memory until a new signal is presented. The second layer (CA3 cells) implements an auto-associative memory, exploiting excitatory and inhibitory plastic synapses to recover an entire episode from a single feature. Units in this layer are disinhibited by a theta rhythm from an external source (septum or Papez circuit). The third layer (CA1 cells) implements a hetero-associative net with the previous layer, able to recover a sequence of episodes from the first one. During an encoding phase, simulating high-acetylcholine levels, the network is trained with Hebbian (synchronizing) and anti-Hebbian (desynchronizing) rules. During retrieval (low-acetylcholine), the network can correctly recover sequences from an initial cue using gamma oscillations nested inside the theta rhythm. Moreover, in high noise, the network isolated from the environment simulates a mind-wandering condition, randomly replicating previous sequences. Interestingly, in a state simulating sleep, with increased noise and reduced synapses, the network can "dream" by creatively combining sequences, exploiting features shared by different episodes. Finally, an irrational behavior (erroneous superimposition of features in various episodes, like "delusion") occurs after pathological-like reduction in fast inhibitory synapses. The model can represent a straightforward and innovative tool to help mechanistically understand the theta-gamma code in different mental states.

Development of spontaneous recurrent seizures accompanied with increased rates of interictal spikes and decreased hippocampal delta and theta activities following extended kindling in mice

Interictal epileptiform discharges refer to aberrant brain electrographic signals between seizures and feature intermittent interictal spikes (ISs), sharp waves, and/or abnormal rhythms. Recognition of these epileptiform activities by electroencephalographic (EEG) examinations greatly aids epilepsy diagnosis and localization of the seizure onset zone. ISs are a major form of interictal epileptiform discharges recognized in animal models of epilepsy. Progressive changes in IS waveforms, IS rates, and/or associated fast ripple oscillations have been shown to precede the development of spontaneous recurrent seizures (SRS) in various animal models. IS expressions in the kindling model of epilepsy have been demonstrated but IS changes during the course of SRS development in extended kindled animals remain to be detailed. We hence addressed this issue using a mouse model of kindling-induced SRS. Adult C57 black mice received twice daily hippocampal stimulations until SRS occurrence, with 24-h EEG monitoring performed following 50, 80, and ≥ 100 stimulations and after observation of SRS. In the stimulated hippocampus, increases in spontaneous ISs rates, but not in IS waveforms nor IS-associated fast ripples, along with decreased frequencies of hippocampal delta and theta rhythms, were observed before SRS onset. Comparable increases in IS rates were further observed in the unstimulated hippocampus, piriform cortex, and entorhinal cortex, but not in the unstimulated parietal cortex and dorsomedial thalamus. These data provide original evidence suggesting that increases in hippocampal IS rates, together with reductions in hippocampal delta and theta rhythms are closely associated with development of SRS in a rodent kindling model.

An EEG study on artistic and engineering mindsets in students in creative processes

This study aims to take higher-education students as examples to understand and compare artistic and engineering mindsets in creative processes using EEG. Fifteen Master of Fine Arts (MFA) visual arts and fifteen Master of Engineering (MEng) design engineering students were recruited and asked to complete alternative uses tasks wearing an EEG headset. The results revealed that (1) the engineering-mindset students responded to creative ideas faster than artistic-mindset students. (2) Although in creative processes both artistic- and engineering-mindset students showed Theta, Alpha, and Beta wave activity, the active brain areas are slightly different. The active brain areas of artistic-mindset students in creative processes are mainly in the frontal and occipital lobes; while the whole brain (frontal, oriental, temporal, and occipital lobes) was active in creative processes of engineering-mindset students. (3) During the whole creative process, the brain active level of artistic-mindset students was higher than that of engineering-mindset students. The results of this study fills gaps in existing research where only active brain areas and band waves were compared between artistic- and engineering-mindset students in creative processes. For quick thinking in terms of fluency of generating creative ideas, engineering students have an advantage in comparison to those from the visual arts. Also, the study provided more evidence that mindset can affect the active levels of the brain areas. Finally, this study provides educators with more insights on how to stimulate students’ creative ability.

Border cells without theta rhythmicity in the medial prefrontal cortex

The medial prefrontal cortex (mPFC) is a key brain structure for higher cognitive functions such as decision-making and goal-directed behavior, many of which require awareness of spatial variables including one’s current position within the surrounding environment. Although previous studies have reported spatially tuned activities in mPFC during memory-related trajectory, the spatial tuning of mPFC network during freely foraging behavior remains elusive. Here, we reveal geometric border or border-proximal representations from the neural activity of mPFC ensembles during naturally exploring behavior, with both allocentric and egocentric boundary responses. Unlike most of classical border cells in the medial entorhinal cortex (MEC) discharging along a single wall, a large majority of border cells in mPFC fire particularly along four walls. mPFC border cells generate new firing fields to external insert, and remain stable under darkness, across distinct shapes, and in novel environments. In contrast to hippocampal theta entrainment during spatial working memory tasks, mPFC border cells rarely exhibited theta rhythmicity during spontaneous locomotion behavior. These findings reveal spatially modulated activity in mPFC, supporting local computation for cognitive functions involving spatial context and contributing to a broad spatial tuning property of cortical circuits.

Control in context: The theta rhythm provides evidence for reactive control but no evidence for proactive control.

A prime goal of psychological science is to understand how humans can flexibly adapt to rapidly changing contexts. The foundation of this cognitive flexibility rests on contextual adjustments of cognitive control, which can be tested using the list-wide proportion congruency effect (LWPC). Blocks with mostly incongruent (MI) trials show smaller conflict interference effects compared to blocks with mostly congruent (MC) trials. A critical debate is how proactive and reactive control processes drive contextual adjustments. In this preregistered study (N = 30), we address this conundrum, by using the theta rhythm as a key neural marker for cognitive control. In a confound-minimized Stroop paradigm with short alternating MC and MI blocks, we tested reaction times, error rates, and participants' individualized theta activity (2-7 Hz) in the scalp-recorded electroencephalogram. An LWPC effect was found for both, reaction times and error rates. Importantly, the results provided clear evidence for reactive control processes in the theta rhythm: Theta power was higher in rare incongruent compared with congruent trials in MC blocks, but there was no such modulation in MI blocks. However, regarding proactive control, there were no differences in sustained theta power between MC and MI blocks. A complementary analysis of the alpha activity (8-14 Hz) also revealed no evidence for sustained attentional resources in MI blocks. These findings suggest that contextual adjustments rely mainly on reactive control processes in the theta rhythm. Proactive control, in the present study, may be limited to a flexible attentional shift but does not seem to require sustained theta activity.

Septal stimulation attenuates hippocampal seizure with subregion specificity.

Deep brain stimulation (DBS) is a promising approach for the treatment of epilepsy. However, the optimal target for DBS and underlying mechanisms are still not clear. Here, we compared the therapeutic effects of DBS on distinct septal subregions, aimed to find the precise targets of septal DBS and related mechanisms for the clinical treatment. Assisted by behavioral test, electroencephalography (EEG) recording and analyzing, selectively neuronal manipulation and immunohistochemistry, we assessed the effects of DBS on the three septal subregions in kainic acid (KA)-induced mouse seizure model. DBS in the medial septum (MS) not only delayed generalized seizure (GS) development, but reduced the severity; DBS in the vertical diagonal band of Broca (VDB) only reduced the severity of GS, while DBS in the horizontal diagonal band of Broca (HDB) subregion showed no anti-seizure effect. Notably, DBS in the MS much more efficiently decreased abnormal activation of hippocampal neurons. EEG spectrum analysis indicated that DBS in the MS and VDB subregions mainly increased the basal hippocampal low-frequency (delta and theta) rhythm. Furthermore, ablation of cholinergic neurons in the MS and VDB subregions blocked the anti-seizure and EEG-modulating effects of septal DBS, suggesting the seizure-alleviating effect of DBS was dependent on local cholinergic neurons. DBS in the MS and VDB, rather than HDB, attenuates hippocampal seizure by activation of cholinergic neurons-augmented hippocampal delta/theta rhythm. This may be of great therapeutic significance for the clinical treatment of epilepsy with septal DBS. The optical target of deep brain stimulation in the septum is still not clear. This study demonstrated that stimulation in the medial septum and vertical diagonal band of Broca subregions, but not the horizontal diagonal band of Broca, could alleviate hippocampal seizure through cholinergic neurons-augmented hippocampal delta/theta rhythm. This study may shed light on the importance of precise regulation of deep brain stimulation therapy in treating epileptic seizures.

EEG를 활용한 사람중심 커뮤니케이션 중재 효과성 연구

Person-Centered care and communication intervention have been widely utilized in emotional care for people with dementia overseas. However, the use of non-pharmacological interventions, including person-centered care, has been lacking in Korea primarily due to a shortageof scientific evidence proving their efficacy. This study aimed to present Person-Centered communication as a method of intervention andto quantitatively assess its impact on the emotional state and agitation of people with dementia. The subjects of the study, people withmild dementia who commute day care centers, were divided into experimental and control groups for the purpose of comparison. Measurementson brainwaves and observations on changes in emotion and behavior were taken before and after the interventions. Brainwaves were examined by measuring signals from two electrodes of EEG on the prefrontal cortex, and observation were taken with the Observed Emotion RateScale (OERS) and the Agitation Behavior Scale (ABS). As a result of the communication intervention, it was found that emotions such as happiness and attentiveness increased, while anger, anxiety·agitation, and sadness decreased, along with a reduction in agitated behavior. EEG measurements showed a decrease in theta waves which are related to emotions, and significant changes in alpha and beta waves whichare related to attentiveness. This study is meaningful in that it quantitatively confirmed the effectiveness of Person-Centered communicationon the emotions and agitated behavior, as well as EEG changes in people with mild dementia. This study suggests using Person-Centered Care and communication intervention for the emotional support of people with dementia.

Effects of computerized cognitive training on biomarker responses in older adults with mild cognitive impairment: A scoping review.

Mild cognitive impairment (MCI) is a widespread condition in older individuals, posing significant risk of dementia. However, limited research has been conducted to explore effective interventions and clarify their impact at the neural level. Therefore, this study aimed to investigate the effects of computerized cognitive training (CCT) and explore the associated neural mechanisms in preventing dementia in older individuals with MCI, with a view to inform future intervention efforts. We reviewed the effects of CCT on biomarker outcomes in older adults with MCI. The search was conducted for studies published between 2010 and May 10, 2023, using three search engines: PubMed, Scopus, and Cumulative Index to Nursing and Allied Health Literature. The inclusion criteria were as follows: studies that involved participants diagnosed with MCI, included CCT, included quantitative assessment of biomarker results, and conducted randomized controlled trials. Sixteen studies that used biomarkers, including magnetic resonance imaging, electroencephalography (EEG), functional near-infrared spectroscopy (fNIRS), and blood or salivary biomarkers, were extracted. The results showed that CCT caused changes in structure and function within the main brain network, including the default mode network, and decreased both theta rhythm activity on EEG and prefrontal activity on fNIRS, with improvement in cognitive function. Furthermore, CCT combined with physical exercise showed more significant structural and functional changes in extensive brain regions compared with CCT alone. Virtual reality-based cognitive training improved not only executive function but also instrumental activities of daily living. CCT causes functional and structural changes in extensive brain regions and improves cognitive function in older adults with MCI. Our findings highlight the potential of individualized intervention methods and biomarker assessment according to the specific causes of MCI. Future research should aim to optimize these personalized therapeutic strategies to maximize the benefits of CCT in older adults with MCI.

Hanning FIR window filtering analysis for EEG signals

The window function is a mathematical function in signal processing that is multiplied by a signal to lessen or eliminate the impact of undesired characteristics such as spectral leakage and edge effects that might arise while analyzing finite-duration signals. The Hanning window is just one of several window functionalities available. It is designed to gradually taper the endpoints of a signal to zero, reducing spectral leakage in the frequency domain. Filtering is commonly employed in Electroencephalography (EEG) signal processing to remove noise, artifacts, or undesired frequency components while retaining the desired information. Filtering techniques include band pass, low pass, and high pass and band reject filtering. Hanning window technique using low pass, high pass, band pass, and band reject is used for filtering of EEG signal. The response time analysis for the Hanning window is calculated using low, high, band pass, and band-reject filters for different types of EEG waves alpha, beta gamma, theta, and delta using the signal processing simulation tool MATLAB 2023. The response time for delta wave using a low pass filter has a low response time of 14.125 sec which is comparatively less than another filter. For theta wave high pass filter has a low response time of 11.965 seconds. For alpha wave low pass filter has a low response time of 16.706 seconds whereas for beta wave low pass filter has a low response time of 15.202 seconds. For gamma waves high pass filter has a low response time of 11.349 seconds. Hanning band-reject filter has proven low response time for delta, theta, and gamma waveforms of 16.475 seconds, 16.182 seconds, and 17.743 seconds respectively. The novelty of the work is that the Hanning window improves frequency resolution by balancing the main lobe width with side lobe attenuation Hanning band-reject filter is suited best to figure out the widest main-lobe peak and highest peak for different EEG waveforms.

The Effects of Natural Window Views in Classrooms on College Students’ Mood and Learning Efficiency

Observing peaceful natural environments has been shown to restore cognitive abilities and reduce stress. As a result, visual access to natural environments is becoming increasingly common in educational settings. However, most current research on classroom window views has examined classroom environments in elementary and secondary schools, and only some university classrooms have been used as study sites. This study investigated the relationship between the naturalness of university classroom window views and physiological and emotional responses and standardized tests of attentional focus (learning efficiency) in university students. Thirty participants (undergraduates 21.16 ± 1.01 years old) viewed architectural window views and natural window views for 3 min each, and physiological measures of EEG, HRV index, and psychometric measures of Semantic Differences Questionnaire and Emotional State Questionnaire generated data. Measurements were generated. The results indicated that the natural window view significantly enhanced theta, alpha, and beta waves of brain activity, provided a sense of comfort, relaxation, and pleasure, and increased learning efficiency compared to the architectural window view. The findings support the beneficial associations between window views on university campuses and students’ mood and learning efficiency, emphasizing the importance of considering natural window views in the planning and designing of university classrooms.

Serotonin modulates infraslow oscillation in the dentate gyrus during Non-REM sleep.

Synchronous neuronal activity is organized into neuronal oscillations with various frequency and time domains across different brain areas and brain states. For example, hippocampal theta, gamma and sharp wave oscillations are critical for memory formation and communication between hippocampal subareas and the cortex. In this study, we investigated the neuronal activity of the dentate gyrus (DG) with electrophysiological and optical imaging tools during sleep-wake cycles. We found that the activity of major glutamatergic cell populations in the DG is organized into in-fraslow oscillations (0.01 - 0.03 Hz) during NREM sleep. Although the DG is considered a sparsely active network during wakefulness, we found that 50% of granule cells and about 25% of mossy cells exhibit increased activity during NREM sleep. Further experiments revealed that the infraslow oscillation in the DG is modulated by rhythmic serotonin release during sleep, which oscillates at the same frequency but in an opposite phase. Genetic manipulation of 5-HT receptors revealed that this neuromodulatory regulation is mediated by 5-HT1a receptors and the knockdown of these receptors leads to memory impairment. Together, our results provide novel mechanistic insights into how the 5-HT system can influence hippocampal activity patterns during sleep.