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Background: Architectural space has many effects on human mental and physical health. From a cognitive perspective, some effects are self-conscious and visible in behavior, while some are hidden and their understanding requires meticulous analysis. The range of effects is from positive to negative. Many studies have been conducted in the field of environmental psychology, but due to the use of traditional methods, they failed to provide an answer to explain how architectural space affects the brain. Today, with the emergence of the new trend of neuroscience, the way of this effect has been clarified. Aims: The current research was carried out with the aim of identifying the cognitive effects of architectural space on brain activities based on neuroscience and sought to clarify the different levels of short-term and long-term effects of architectural space on the brain. Methods: The current research has achieved the purpose of the study through qualitative approach and a descriptive-analytical research method, using the review of existing sources and studies, and has specifically addressed the effects of architecture on cognition and brain activities. The study period was between January 1st. 2010 and December 22nd. 2020. The following databases were used: Science Citation Index Expanded, Social Sciences Citation Index, Arts, and Humanities Citation Index, and Emerging Sources Citation Index. Results: The results of the research indicate that the architectural space can be categorized in three different levels in terms of the importance of the effects from simple to complex. At low level, architectural space affects metabolic settings, basic and immune responses; at middle level, it affects orientation and stress; and at high level, emotion, memory and attention are affected by architectural space. Conclusion: It seems that the current research field is a step in the direction of clarifying the effects of architecture for the researchers of environmental psychological fields and opens a clear path to achieve a healthy space in this field.

Nowadays, the product development processes have faced challenges for more effective, agile characteristics. Moreover, traditional methods for data retrieval from customers for their behavioral prediction have lost their efficiency. Social media platforms have provided enormous potentials for discovery of customer behavioral models. In the current study we investigated the association between brain activities and consumers' behaviour. Additionally, we investigated whether pre-trained Python models for sentiment analyses predict consumer behaviour and assessed it's association with brain activities during decision-making tasks. Neural and behavioral responses of participants used for analysis of their decision making processes when choosing their product of interest. This has been accomplished while the participants' brain activities were recorded at pre-test (baseline) and during each decision-making tasks. Results of this study revealed significant association between certain resting-state EEG power spectral densities and consumer decisions. Moreover, sentiment analysis models showed good accuracy in predicting product like/disliking. These findings demonstrates the potential of combination of neuroscience and sentiment analysis methods in consumers' behaviour research especially for agile product development processes. [ABSTRACT FROM AUTHOR]

Background: Architectural space has many effects on human mental and physical health. From a cognitive perspective, some effects are self-conscious and visible in behavior, while some are hidden and their understanding requires meticulous analysis. The range of effects is from positive to negative. Many studies have been conducted in the field of environmental psychology, but due to the use of traditional methods, they failed to provide an answer to explain how architectural space affects the brain. Today, with the emergence of the new trend of neuroscience, the way of this effect has been clarified. Aims: The current research was carried out with the aim of identifying the cognitive effects of architectural space on brain activities based on neuroscience and sought to clarify the different levels of short-term and long-term effects of architectural space on the brain. Methods: The current research has achieved the purpose of the study through qualitative approach and a descriptive-analytical research method, using the review of existing sources and studies, and has specifically addressed the effects of architecture on cognition and brain activities. The study period was between January 1st. 2010 and December 22nd. 2020. The following databases were used: Science Citation Index Expanded, Social Sciences Citation Index, Arts, and Humanities Citation Index, and Emerging Sources Citation Index. Results: The results of the research indicate that the architectural space can be categorized in three different levels in terms of the importance of the effects from simple to complex. At low level, architectural space affects metabolic settings, basic and immune responses; at middle level, it affects orientation and stress; and at high level, emotion, memory and attention are affected by architectural space. Conclusion: It seems that the current research field is a step in the direction of clarifying the effects of architecture for the researchers of environmental psychological fields and opens a clear path to achieve a healthy space in this field. [ABSTRACT FROM AUTHOR]

This study aimed to reveal the influence of emotional valence and sensory modality on neural activity in response to multimodal emotional stimuli using scalp EEG. In this study, 20 healthy participants completed the emotional multimodal stimulation experiment for three stimulus modalities (audio, visual, and audio-visual), all of which are from the same video source with two emotional components (pleasure or unpleasure), and EEG data were collected using six experimental conditions and one resting state. We analyzed power spectral density (PSD) and event-related potential (ERP) components in response to multimodal emotional stimuli, for spectral and temporal analysis. PSD results showed that the single modality (audio only/visual only) emotional stimulation PSD differed from multi-modality (audio-visual) in a wide brain and band range due to the changes in modality and not from the changes in emotional degree. The most pronounced N200-to-P300 potential shifts occurred in monomodal rather than multimodal emotional stimulations. This study suggests that emotional saliency and sensory processing efficiency perform a significant role in shaping neural activity during multimodal emotional stimulation, with the sensory modality being more influential in PSD. These findings contribute to our understanding of the neural mechanisms involved in multimodal emotional stimulation. [ABSTRACT FROM AUTHOR]

We study synchronization through the combination of electrical synapse and hybrid synapse, and analyse frequency responses in a network constituted of two subnetworks (layers). We prove the onset of synchronization for two coupled nondelayed neurons when we set properly the coupling strength of electrical and chemical synapses, and neurotransmitter parameters of chemical synapse with constant initial conditions. The chemical synapse takes into consideration inhibitory and excitatory behaviors of the neuron. We further prove that for random initial conditions of few sets of identical nodes which constitute a network with two layers, global synchronization is possible for specific values of coupling strength and inner matrix configuration. To ensure great accuracy of the global synchronization, we add a controller and for all settings of electrical and chemical parameters, we always observe global synchronization in both layers and then, the associated network. Five different network topologies were used for the analysis. We finally verify the robustness of the global synchronization by using an external sinusoidal stimuli and observe that the control action is very powerful to maintain the global synchronization dynamic of the network. We observe equally that the instantaneous frequency can toggle between delta oscillations, awake state of the brain, up to gamma oscillations which are the frequencies of intensive activities of the brain. [ABSTRACT FROM AUTHOR]

Gliclazide (GLD), a sulphonylurea is efficacious in the treatment of diabetes type-2. However, there is limited information on its activity in the brain, especially in diabetics. This research investigated the brain activities of GLD following streptozotocin-induced diabetes in Wistar rats. Twenty five adult male Wistar rats (200–250 g) were grouped (n = 5) as: Control (distilled water, 5 mL/kg) and GLD (150 mg/kg) groups; and the diabetic groups, untreated streptozotocin (STZ, 35 mg/kg), and STZ (35 mg/kg) treated with GLD (150 mg/kg) for two and four weeks, and already on high fat diet. The animals’ body weights and blood glucose levels were checked weekly. After the experimental duration, spontaneous alternation and novel object recognition tests were carried out and the animals sacrificed. Perfusion with phosphate buffered saline preceded brain excision for biochemical analyses, with halves fixed in 10% neutral buffered formalin for histology. Compared with the control, results showed (p

Objective: To fabricate a lightweight, breathable, comfortable, and able to contour to the curvilinear body shape, electrodes built on a flexible substrate are a significant growth in wearable health monitoring. This research aims to create a GNP/FE electrode-based EEG signal acquisition system that is both efficient and inexpensive. Methodology: Three distinct electrode concentrations were developed for EEG signal acquisition, three distinct electrode concentrations (1.5:1.5, 2:1, and 3:0). The high strength-to-weight ratio to form the tribofilm in the fabrication of the electrode will provide good efficiency. The EEG signal is first subjected to a wavelet transform, which serves as a preliminary analysis. The use of biopotential signals in wearable systems as biofeedback or control commands is expected to substantially impact point-of-care health monitoring systems, rehabilitation devices, human–computer/machine interfaces (HCI/HMI), and brain–computer interfaces (BCIs). The graphene oxide (GO), glycerol (GL), and polyvinyl alcohol (PVA) GO/GL/PVA plastic electrodes were measured and compared to that of a commercially available electrode using the biopic equipment. The GO/GL/PVA plastic electrode was able to detect EEG signals satisfactorily after being used for two months, demonstrating good conductivity and lower noise than the commercial electrode. The GO/GL/PVA nanocomposite mixture was put into the electrode mold as soon as it was ready and then rapidly chilled. Results: The quality of an acquired EEG signal could be measured in several ways including by its error percentage, correlation coefficient, and signal-to-noise ratio (SNR). The fabricated electrode yield detection ranged from 0.81 kPa−1 % to 34.90 kPa−1%. The performance was estimated up to the response of 54 ms. Linear heating at the rate of 40 °C per minute was implemented on the sample ranges from 0 °C to 240 °C. During the sample electrode testing in EEG signal analysis, it obtained low impedance with a good quality of signal acquisition when compared to a conventional wet type of electrode. Conclusions: A large database was frequently built from all of the simulated signals in MATLAB code. Through the experiment, all of the required data were collected, checked against all other signals, and proven that they were accurate representations of the intended database. Evidence suggests that graphene nanoplatelets (GNP) hematite (FE2O3) polyvinylidene fluoride (PVDF) GNP/FE2O3@PVDF electrodes with a 3:0 concentration yielded the best outcomes. [ABSTRACT FROM AUTHOR]

Background and Purpose: In people with Parkinson disease (PD), gait performance deteriorating during dual-task walking has been noted in previous studies. However, the effects of different types of dual tasks on gait performance and brain activation are still unknown. The purpose of this study was to investigate cognitive and motor dual-task walking performance on multiarea brain activity in individuals with PD. Methods: Twenty-eight participants with PD were recruited and performed single walking (SW), walking while performing a cognitive task (WCT), and walking while performing a motor task (WMT) at their self-selected speed. Gait performance including walking speed, stride length, stride time, swing cycle, temporal and spatial variability, and dual-task cost (DTC) was recorded. Brain activation of the prefrontal cortex (PFC), premotor cortex (PMC), and supplementary motor areas (SMA) were measured using functional near-infrared spectroscopy during walking. Results: Walking performance deteriorated upon performing a secondary task, especially the cognitive task. Also, a higher and more sustained activation in the PMC and SMA during WCT, as compared with the WMT and SW, in the late phase of walking was found. During WMT, however, the SMA and PMC did not show increased activation compared with during SW. Moreover, gait performance was negatively correlated with PMC and SMA activity during different walking tasks. Discussion and Conclusions: Individuals with mild to moderate PD demonstrated gait deterioration during dual-task walking, especially during WCT. The SMA and PMC were further activated in individuals with PD when performing cognitive dual-task walking. Supplemental Digital Content is Available in the Text. Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A383). [ABSTRACT FROM AUTHOR]

This study aimed to reveal the influence of emotional valence and sensory modality on neural activity in response to multimodal emotional stimuli using scalp EEG. In this study, 20 healthy participants completed the emotional multimodal stimulation experiment for three stimulus modalities (audio, visual, and audio-visual), all of which are from the same video source with two emotional components (pleasure or unpleasure), and EEG data were collected using six experimental conditions and one resting state. We analyzed power spectral density (PSD) and event-related potential (ERP) components in response to multimodal emotional stimuli, for spectral and temporal analysis. PSD results showed that the single modality (audio only/visual only) emotional stimulation PSD differed from multi-modality (audio-visual) in a wide brain and band range due to the changes in modality and not from the changes in emotional degree. The most pronounced N200-to-P300 potential shifts occurred in monomodal rather than multimodal emotional stimulations. This study suggests that emotional saliency and sensory processing efficiency perform a significant role in shaping neural activity during multimodal emotional stimulation, with the sensory modality being more influential in PSD. These findings contribute to our understanding of the neural mechanisms involved in multimodal emotional stimulation.

Background: The pathophysiology of depression in Parkinson's disease (PD) is not fully understood. Studies based upon functional MRI (fMRI) showed the alterations in the blood-oxygen-level-dependent (BOLD) fluctuations in multiple brain regions pertaining to depression in PD. However, large variance was observed across previous studies. Therefore, we conducted a meta-analysis to quantitatively evaluate the results in previous publications and completed an independent regions-of-interests (ROIs)-based analysis using our own data to validate the results of the meta-analysis. Methods: We searched PubMed, Embase, and Web of Science to identify fMRI studies in PD patients with depression. Using signed differential mapping (SDM) method, we performed a voxel-based meta-analysis. Then, a validation study by using multiscale entropy (MSE) in 28 PD patients with depression and 25 PD patients without depression was conducted. The fMRI scan was completed in anti-depression-medication-off state. The ROIs of the MSE analysis were the regions identified by the meta-analysis. Results: A total of 126 PD patients with depression and 153 PD patients without depression were included in meta-analysis. It was observed that the resting-state activities within the posterior cingulate gyrus, supplementary motor area (SMA), and cerebellum were altered in depressed patients. Then, in the validation study, these regions were used as ROIs. PD patients with depression had significantly lower MSE of the BOLD fluctuations in these regions (posterior cingulate gyrus: F = 0.856, p = 0.049; SMA: F = 0.914, p = 0.039; cerebellum: F = 0.227, p = 0.043). Conclusion: Our study revealed that the altered BOLD activity in cingulate, SMA, and cerebellum of the brain were pertaining to depression in PD. [ABSTRACT FROM AUTHOR]

BackgroundThe pathophysiology of depression in Parkinson’s disease (PD) is not fully understood. Studies based upon functional MRI (fMRI) showed the alterations in the blood-oxygen-level-dependent (BOLD) fluctuations in multiple brain regions pertaining to depression in PD. However, large variance was observed across previous studies. Therefore, we conducted a meta-analysis to quantitatively evaluate the results in previous publications and completed an independent regions-of-interests (ROIs)-based analysis using our own data to validate the results of the meta-analysis.MethodsWe searched PubMed, Embase, and Web of Science to identify fMRI studies in PD patients with depression. Using signed differential mapping (SDM) method, we performed a voxel-based meta-analysis. Then, a validation study by using multiscale entropy (MSE) in 28 PD patients with depression and 25 PD patients without depression was conducted. The fMRI scan was completed in anti-depression-medication-off state. The ROIs of the MSE analysis were the regions identified by the meta-analysis.ResultsA total of 126 PD patients with depression and 153 PD patients without depression were included in meta-analysis. It was observed that the resting-state activities within the posterior cingulate gyrus, supplementary motor area (SMA), and cerebellum were altered in depressed patients. Then, in the validation study, these regions were used as ROIs. PD patients with depression had significantly lower MSE of the BOLD fluctuations in these regions (posterior cingulate gyrus: F = 0.856, p = 0.049; SMA: F = 0.914, p = 0.039; cerebellum: F = 0.227, p = 0.043).ConclusionOur study revealed that the altered BOLD activity in cingulate, SMA, and cerebellum of the brain were pertaining to depression in PD.

Background: Using resting-state functional connectivity (rsFC), we investigated alternations in spontaneous brain activities reflected by functional connectivity density (FCD) in patients with optic neuritis (ON). Methods: We enrolled 28 patients with ON (18 males, 10 females) and 24 healthy controls (HCs; 16 males, 8 females). All subjects underwent functional magnetic resonance imaging (fMRI) in a quiet state to determine the values of rsFC, long-range FCD (longFCD), and short-range FCD (IFCD). Receiver operating characteristic (ROC) curves were generated to distinguish patients from HCs. Results: The ON group exhibited obviously lower longFCD values in the left inferior frontal gyrus triangle, the right precuneus and the right anterior cingulate, and paracingulate gyri/median cingulate and paracingulate gyri. The left median cingulate and paracingulate gyri and supplementary motor area (SMA) were also significantly lower. Obviously reduced IFCD values were observed in the left middle temporal gyrus/angular gyrus/SMA and right cuneus/SMA compared with HCs. Conclusion: Abnormal neural activities were found in specific brain regions in patients with ON. Specifically, they showed significant changes in rsFC, longFCD, and IFCD values. These may be useful to identify the specific mechanism of change in brain function in ON. [ABSTRACT FROM AUTHOR]

Background: Using resting-state functional connectivity (rsFC), we investigated alternations in spontaneous brain activities reflected by functional connectivity density (FCD) in patients with optic neuritis (ON).Methods: We enrolled 28 patients with ON (18 males, 10 females) and 24 healthy controls (HCs; 16 males, 8 females). All subjects underwent functional magnetic resonance imaging (fMRI) in a quiet state to determine the values of rsFC, long-range FCD (longFCD), and short-range FCD (IFCD). Receiver operating characteristic (ROC) curves were generated to distinguish patients from HCs.Results: The ON group exhibited obviously lower longFCD values in the left inferior frontal gyrus triangle, the right precuneus and the right anterior cingulate, and paracingulate gyri/median cingulate and paracingulate gyri. The left median cingulate and paracingulate gyri and supplementary motor area (SMA) were also significantly lower. Obviously reduced IFCD values were observed in the left middle temporal gyrus/angular gyrus/SMA and right cuneus/SMA compared with HCs.Conclusion: Abnormal neural activities were found in specific brain regions in patients with ON. Specifically, they showed significant changes in rsFC, longFCD, and IFCD values. These may be useful to identify the specific mechanism of change in brain function in ON.

Objective: To fabricate a lightweight, breathable, comfortable, and able to contour to the curvilinear body shape, electrodes built on a flexible substrate are a significant growth in wearable health monitoring. This research aims to create a GNP/FE electrode-based EEG signal acquisition system that is both efficient and inexpensive. Methodology: Three distinct electrode concentrations were developed for EEG signal acquisition, three distinct electrode concentrations (1.5:1.5, 2:1, and 3:0). The high strength-to-weight ratio to form the tribofilm in the fabrication of the electrode will provide good efficiency. The EEG signal is first subjected to a wavelet transform, which serves as a preliminary analysis. The use of biopotential signals in wearable systems as biofeedback or control commands is expected to substantially impact point-of-care health monitoring systems, rehabilitation devices, human–computer/machine interfaces (HCI/HMI), and brain–computer interfaces (BCIs). The graphene oxide (GO), glycerol (GL), and polyvinyl alcohol (PVA) GO/GL/PVA plastic electrodes were measured and compared to that of a commercially available electrode using the biopic equipment. The GO/GL/PVA plastic electrode was able to detect EEG signals satisfactorily after being used for two months, demonstrating good conductivity and lower noise than the commercial electrode. The GO/GL/PVA nanocomposite mixture was put into the electrode mold as soon as it was ready and then rapidly chilled. Results: The quality of an acquired EEG signal could be measured in several ways including by its error percentage, correlation coefficient, and signal-to-noise ratio (SNR). The fabricated electrode yield detection ranged from 0.81 kPa−1 % to 34.90 kPa−1%. The performance was estimated up to the response of 54 ms. Linear heating at the rate of 40 °C per minute was implemented on the sample ranges from 0 °C to 240 °C. During the sample electrode testing in EEG signal analysis, it obtained low impedance with a good quality of signal acquisition when compared to a conventional wet type of electrode. Conclusions: A large database was frequently built from all of the simulated signals in MATLAB code. Through the experiment, all of the required data were collected, checked against all other signals, and proven that they were accurate representations of the intended database. Evidence suggests that graphene nanoplatelets (GNP) hematite (FE2O3) polyvinylidene fluoride (PVDF) GNP/FE2O3@PVDF electrodes with a 3:0 concentration yielded the best outcomes.

Conventional acoustic brain stimulators that transmit low frequency (< 1 MHz) bursts in a pulse repetition frequency with large-sized transducers are barely compatible with small animal models because of broad beam width, possible stimulation of auditory pathways, and blocking of field-of-view for in vivo imaging of brain hemodynamics and neuronal activities. A miniaturized ultrasound stimulator with higher stimulation frequencies will enhance spatial specificity and enable simultaneous eliciting and monitoring brain activities. Moreover, the use of non-periodic pulse sequences may reduce unintended stimulations on auditory cortex, which might be caused by transmitting periodic bursting patterns. A platform for ultrasound brain stimulations for small animal models, including a soft housing 10 MHz needle transducer with a beam size of 680 μm, random transmission sequences, and optical imaging systems, was developed. The platform can deliver focal stimulations to the visual and barrel cortex of mice and monitor subsequent brain activities. The stimulated sites in both the visual and primary somatosensory cortices (S1) showed approximately two to three times higher neuronal calcium signal levels than those in peripheral regions. Activities in the auditory cortex were elicited by periodic sequence stimulation, while it was reduced by 67 and 35% for barrel and visual cortex stimulation with the random sequence, respectively. [ABSTRACT FROM AUTHOR]

Visualization and visual analytic tools amplify one's perception of data, facilitating deeper and faster insights that can improve decision making. For multidimensional data sets, one of the most common approaches of visualization methods is to map the data into lower dimensions. Scatterplot matrices (SPLOM) are often used to visualize bivariate relationships between combinations of variables in a multidimensional dataset. However, the number of scatterplots increases quadratically with respect to the number of variables. For high dimensional data, the corresponding enormous number of scatterplots makes data exploration overwhelmingly complex, thereby hindering the usefulness of SPLOM in human decision making processes. One approach to address this difficulty utilizes Graph-theoretic Scatterplot Diagnostic (Scagnostics) to automatically extract a subset of scatterplots with salient features and of manageable size with the hope that the data will be sufficient for improving human decisions. In this paper, we use Electroencephalogram (EEG) to observe brain activity while participants make decisions informed by scatterplots created using different visual measures. We focused on 4 categories of Scagnostics measures: Clumpy, Monotonic, Striated, and Stringy. Our findings demonstrate that by adjusting the level of difficulty in discriminating between data sets based on the Scagnostics measures, different parts of the brain are activated: easier visual discrimination choices involve brain activity mostly in visual sensory cortices located in the occipital lobe, while more difficult discrimination choices tend to recruit more parietal and frontal regions as they are known to be involved in resolving ambiguities. Our results imply that patterns of neural activity are predictive markers of which specific Scagnostics measures most assist human decision making based on visual stimuli such as ours., Competing Interests: Conflict of InterestThe authors declare no competing interests., (© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

This paper investigated the effects of cognitive and motor dual tasks on gait performance and brain activities in stroke; 23 stroke subjects performed single walking (SW), walking while performing cognitive task (WCT), and walking while performing motor task (WMT) at self-selected speed. The gait performance was recorded, including speed, cadence, stride time, stride length, and dual task cost (DTC). Brain activities in prefrontal cortex, premotor cortex (PMC), and supplementary motor areas (SMAs) were measured by functional near-infrared spectroscopy during walking. Results showed significant decrease in speed, cadence, and stride length, and increase in stride time was noted in both WCT and WMT compared with SW condition. There was no significant difference in DTC between WCT and WMT. The non-lesioned SMA and most channels of bilateral PMCs exhibited significant increases in the index of hemoglobin differential during WCT and WMT compared with SW. Moreover, gait performance was negatively correlated with bilateral PMCs and lesioned SMA during different walking tasks. In conclusion, deteriorated gait performance was noted in stroke attempting dual tasks. There is no significant difference between the two dual tasks on gait performance. Nevertheless, SMA and especially PMC were crucial in cognitive and motor dual task walking after stroke. [ABSTRACT FROM AUTHOR]

Previous studies report greater activation in the cortical motor network in controlling eccentric contraction (EC) than concentric contraction (CC) of human skeletal muscles despite lower activation level of the muscle associated with EC. It is unknown, however, whether the strength of functional coupling between the primary motor cortex (M1) and other involved areas in the brain differs as voluntary movements are controlled by a network of regions in the primary, secondary and association cortices. Examining fMRI-based functional connectivity (FC) offers an opportunity to measure strength of such coupling. To address the question, we examined functional MRI (fMRI) data acquired during EC and CC (20 contractions each with similar movement distance and speed) of the right first dorsal interosseous (FDI) muscle in 11 young (20-32 years) and healthy individuals and estimated FC between the M1 and a number of cortical regions in the motor control network. The major findings from the behavioral and fMRI-based FC analysis were that (1) no significant differences were seen in movement distance, speed and stability between the EC and CC; (2) significantly stronger mean FC was found for CC than EC. Our finding provides novel insights for a better understanding of the control mechanisms underlying voluntary movements produced by EC and CC. The finding is potentially helpful for guiding the development of targeted sport training and/or therapeutic programs for performance enhancement and injury prevention.

Electroencephalogram (EEG) contains five rhythms, which provide details about various activities of brain. These rhythms are separated using Hilbert–Huang transform for classification of focal and non‐focal EEG signals. For this, the EEG signal is disintegrated into narrow bands intrinsic mode functions (IMFs) using empirical mode decomposition, and analytic representation of IMFs is computed by Hilbert transformation that helps to extract instantaneous frequencies of respective IMFs. Frequency bands of EEG signals known as rhythms are separated from analytic IMFs using instantaneous frequencies. Two efficient parameters Pearson product‐moment correlation coefficient and Spearman rank correlation coefficient extracted from the rhythms are used with different kernel functions of least‐squares support vector machine for the classification of focal and non‐focal EEG signals. Thus, obtained results show improved performance of proposed method as compared to other existing methods. [ABSTRACT FROM AUTHOR]

Objective: Epilepsy is a neuronal disorder for which the electrical discharge in the brain is synchronized, abnormal and excessive. To detect the epileptic seizures and to analyse brain activities during different mental states, various methods in non-linear dynamics have been proposed. This study is an attempt to quantify the complexity of control and epileptic subject with and without seizure as well as to distinguish eye-open (EO) and eye-closed (EC) conditions using threshold-based symbolic entropy. Methods: The threshold-dependent symbolic entropy was applied to distinguish the healthy and epileptic subjects with seizure and seizure-free intervals (i.e. interictal and ictal) as well as to distinguish EO and EC conditions. The original time series data was converted into symbol sequences using quantization level, and word series of symbol sequences was generated using a word length of three or more. Then, normalized corrected Shannon entropy (NCSE) was computed to quantify the complexity. The NCSE values were not following the normal distribution, and the non-parametric Mann-Whitney-Wilcoxon (MWW) test was used to find significant differences among various groups at 0.05 significance level. The values of NCSE were presented in a form of topographic maps to show significant brain regions during EC and EO conditions. The results of the study were compared to those of the multiscale entropy (MSE). Results: The results indicated that the dynamics of healthy subjects are more complex compared to epileptic subjects (during seizure and seizure-free intervals) in both EO and EC conditions. The comparison of the dynamics of epileptic subjects revealed that seizure-free intervals are more complex than seizure intervals. The dynamics of healthy subjects during EO conditions are more complex compared to those during EC conditions. Further, the results clearly demonstrated that threshold-dependent symbolic entropy outperform MSE in distinguishing different physiological and pathological conditions. Conclusion: The threshold symbolic entropy has provided improved accuracy in quantifying the dynamics of healthy and epileptic subjects during EC an EO conditions for each electrode compared to the MSE. [ABSTRACT FROM AUTHOR]

Highlights: [•] Brain signals and personal identification. [•] Brain signals patters. [•] Brain signals channels. [•] Personal verification. [Copyright &y& Elsevier]

The aim of this study was to examine the neural bases for the exceptional mental calculation ability possessed by Chinese abacus experts through PET imaging. We compared the different regional cerebral blood flow (rCBF) patterns using 15O-water PET in 10 abacus experts and 12 non-experts while they were performing each of the following three tasks: covert reading, simple addition, and complex contiguous addition. All data collected were analyzed using SPM2 and MNI templates. For non-experts during the tasks of simple addition, the observed activation of brain regions were associated with coordination of language (inferior frontal network) and visuospatial processing (left parietal/frontal network). Similar activation patterns but with a larger visuospatial processing involvement were observed during complex contiguous addition tasks, suggesting the recruitment of more visuospatial memory for solving the complex problems. For abacus experts, however, the brain activation patterns showed slight differences when they were performing simple and complex addition tasks, both of which involve visuospatial processing (bilateral parietal/frontal network). These findings supported the notion that the experts were completing all the calculation process on a virtual mental abacus and relying on this same computational strategy in both simple and complex tasks, which required almost no increasing brain workload for solving the latter. In conclusion, after intensive training and practice, the neural pathways in an abacus expert have been connected more effectively for performing the number encoding and retrieval that are required in abacus tasks, resulting in exceptional mental computational ability. [ABSTRACT FROM AUTHOR]

Time-resolved reflectance of an optical pulse in adult head models including non-scattering cerebrospinal fluid (CSF) has been analyzed by the finite difference time domain (FDTD) analysis formulated by the authors. Averaged light intensity and mean time of flight dependences on the source-detector separations calculated by the FDTD analysis are in good agreement with previous experiments, hybrid finite element method (FEM) and Monte Carlo calculations, which justify the FDTD analysis. Base on the analysis, time-resolved reflectance sensitivities to detect optical property changes in brain have been analyzed. As a result, it has been become clear that the sensitivities to detect absorption changes of brain are enhanced in time-resolved reflectance compared to the sensitivities in averaged light intensity, whereas the sensitivities to detect scattering property changes of brain are almost the same in time-resolved reflectance and in averaged light intensity. [ABSTRACT FROM AUTHOR]

Gliclazide (GLD), a sulphonylurea is efficacious in the treatment of diabetes type-2. However, there is limited information on its activity in the brain, especially in diabetics. This research investigated the brain activities of GLD following streptozotocin-induced diabetes in Wistar rats. Twenty five adult male Wistar rats (200-250 g) were grouped (n = 5) as: Control (distilled water, 5 mL/kg) and GLD (150 mg/kg) groups; and the diabetic groups, untreated streptozotocin (STZ, 35 mg/kg), and STZ (35 mg/kg) treated with GLD (150 mg/kg) for two and four weeks, and already on high fat diet. The animals' body weights and blood glucose levels were checked weekly. After the experimental duration, spontaneous alternation and novel object recognition tests were carried out and the animals sacrificed. Perfusion with phosphate buffered saline preceded brain excision for biochemical analyses, with halves fixed in 10% neutral buffered formalin for histology. Compared with the control, results showed (p < 0.05) declined spontaneous alternation and exploratory activities with no preference for familiar or novel objects, body weights loss, raised blood glucose, increased malondialdehyde with decreased superoxide dismutase concentrations, and no apparent adverse effect on hippocampal and prefrontal cortical Nissl substance in the untreated diabetic group. The adverse observations were attenuated in the GLD treated diabetic groups; although the spontaneous alternation in the four weeks GLD treated diabetic group improved (p < 0.05), exploration of objects increased (p < 0.05) without preference. The present results showed that treatment with GLD for two and four weeks mitigated STZ activities, even though there was less improvement in neurocognitive activities., (© 2022 The Authors.)

Objective: To quantify the low- to high-frequency range of abnormal brain activities and assess the histopathologic and clinical correlation in patients with glioma., Methods: Twenty-five patients with glioma and 20 healthy controls were examined with a magnetoencephalography (MEG) system. MEG data collected in 6 frequency bands, including 1-4 Hz, 4-8 Hz, 8-12 Hz, 12-30 Hz, 30-45 Hz, and 55-75 Hz, were analyzed by neuropathology to assess neuromagnetic signatures of glioma grade., Results: Compared with controls, patients with glioma showed greatly altered brain activities in 4-8 Hz, 8-12 Hz, and 55-75 Hz. Magnetic source power of brain activities in 4-8 Hz and 55-75 Hz in patients with high-grade gliomas significantly differed from that in patients with low-grade gliomas. The magnitude of source power of brain activities in 4-8 Hz and 55-75 Hz had marked correlation with the grading of gliomas in histopathological analyses., Conclusions: The degree of neuromagnetic source abnormality is a potential biomarker for noninvasive assessment of glioma grade. Because MEG tests can be performed noninvasively and preoperatively, MEG may play an important role in clinical biopsies and surgical planning for patients with brain gliomas in the future., (Copyright © 2018 Elsevier Inc. All rights reserved.)