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To facilitate language comprehension, the brain uses contextual information and prior knowledge to predict future content. Recent breakthroughs allow us to study pre-word onset prediction during naturalistic narrative listening by mapping contextual word embeddings from Large Language Models onto ECoG data. Long-range prediction encoding has been observed in fMRI data, where including multiple upcoming word embeddings enhances the model's fit to brain data. This study examines if similar predictive information is detectable in MEG data, which offers higher temporal resolution than fMRI but lower signal-to-noise ratio than ECoG. We found that pre-onset predictive signatures are present in MEG, even in data of limited length (1 hour) and in single participants. Unlike in fMRI, adding future embeddings does not improve encoding. These findings offer a novel avenue for studying predictive processing using MEG signals and call for further investigation to explain the differences observed between fMRI and MEG approaches.

The ability to manipulate and recognize abstract representations seems to be a fundamental aspect of human nature, existing since the dawn of our species and transcending cultural barriers. In contrast, non-human primates exhibit very limited proficiency in recognizing abstract representations. This research delves into this human singularity for visual abstraction, through neuroimaging experiments conducted in both humans and non-human primates. Stimuli presenting the same concept (e.g. a house or a face) but varying in abstraction levels (photos, drawings, symbols, and words) were initially presented to a monkey, while intracranial recording of his brain were obtained (16 Utah arrays distributed in V1, V4 and IT). Preliminary results indicate that monkey display early signs of abstraction, particularly for evolutionarily ancient categories such as faces. MEG and fMRI recordings of human subjects are also currently underway, striving to unveil the neuronal mechanisms that set our species apart in the domain of visual abstraction.

Speech comprehension is remarkable for the immediacy with which the listener hears what is being said. Here, we focus on the neural underpinnings of this process in isolated spoken words. We analysed source-localised MEG data for nouns using Representational Similarity Analysis to probe the spatiotemporal coordinates of phonology, lexical form, and the semantics of emerging word candidates. Phonological model fit was detectable within 40–50 ms, engaging a bilateral network including superior and middle temporal cortex and extending into anterior temporal and inferior parietal regions. Lexical form emerged within 60–70 ms, and model fit to semantics from 100-110 ms. Strikingly, the majority of vertices in a central core showed model fit to all three dimensions, consistent with a distributed neural substrate for early speech analysis. The early interpretation of speech seems to be conducted in a unified integrative representational space, in conflict with conventional views of a linguistically stratified representational hierarchy. [ABSTRACT FROM AUTHOR]

Neural oscillations are electrophysiological indicators of synchronous neuronal activity in the brain. Recent work suggests aberrant patterns of neuronal activity in patients with poststroke aphasia. Yet, there is a lack of systematic explorations of neural oscillations in poststroke aphasia. Investigating changes in the dynamics of neuronal activity after stroke may be helpful to identify neural markers of aphasia and language recovery and increase the current understanding of successful language rehabilitation. This review summarizes research on neural oscillations in poststroke aphasia and evaluates their potential as biomarkers for specific linguistic processes. We searched the literature through PubMed, Web of Science, and EBSCO, and selected 31 studies that met the inclusion criteria. Our analyses focused on neural oscillation activity in each frequency band, brain connectivity, and therapy‐induced changes during language recovery. Our review highlights potential neurophysiological markers; however, the literature remains confounded, casting doubt on the reliability of these findings. Future research must address these confounds to confirm the robustness of cross‐study findings on neural oscillations in poststroke aphasia. There is a lack of systematic explorations of neural oscillations in poststroke aphasia. Investigating changes in the dynamics of neuronal activity after stroke may help to identify neural markers of aphasia and language recovery. Our study also increases the current understanding of successful language rehabilitation. [ABSTRACT FROM AUTHOR]

Introduction: Recent research has recognized executive dysfunction as another component affected in Primary Progressive Aphasia (PPA). This systematic review aimed to examine what information distinctive neurophysiological markers can provide in the evaluation of executive function (EF) deficits in PPA, and to what effect executive function deficits can be assessed through the characteristics of functional markers. Methods: We conducted a systematic literature search following the PRISMA guidelines across studies that employed neuropsychological assessments and neurophysiological imaging techniques (EEG, MEG; PET, SPECT, fMRI, fNIRS) to investigate executive dysfunction correlates in PPA. Results: Findings from nine articles including a total number of 111 individuals with PPA met our inclusion criteria and were synthesized. Although research on the neural correlates of EF deficits is scarce, MEG studies revealed widespread oscillatory slowing, with increased delta and decreased alpha power, where alterations in alpha, theta, and beta activities were significant predictors of executive function deficits. PET findings demonstrated significant correlations between executive dysfunction and hypometabolism in frontal brain regions. fMRI results indicated elevated homotopic connectivity in PPA patients, with a broader and more anterior distribution of abnormal hippocampal connections of which were associated with reduced executive performance. Conclusion: Our study provides indirect support for the assumption regarding the significance of the frontal regions and inferior frontal junction in executive control and demonstrates that neurophysiological tools can be a useful aid to further investigate clinical-neurophysiological correlations in PPA. [ABSTRACT FROM AUTHOR]

Background. The left and right temporoparietal junctions (TPJs) are two brain areas involved in several brain networks, largely studied for their diverse roles, from attentional orientation to theory of mind and, recently, predictive processing. In predictive processing, one crucial concept is prior precision, that is, the reliability of the predictions of incoming stimuli. This has been linked with modulations of alpha power as measured with electrophysiological techniques, but TPJs have seldom been studied in this framework. Methods. The present article investigates, using magnetoencephalography, whether spontaneous oscillations in pre-stimulus alpha power in the left and right TPJs can modulate brain responses during a linguistic task that requires predictive processing in literal and non-literal sentences. Results. Overall, results show that pre-stimulus alpha power in the rTPJ was associated with post-stimulus responses only in the left superior temporal gyrus, while lTPJ pre-stimulus alpha power was associated with post-stimulus activity in Broca's area, left middle temporal gyrus, and left superior temporal gyrus. Conclusions. We conclude that both the right and left TPJs have a role in linguistic prediction, involving a network of core language regions, with differences across brain areas and linguistic conditions that can be parsimoniously explained in the context of predictive processing. [ABSTRACT FROM AUTHOR]

Magnetoencephalography (MEG) is a non-invasive neuroimaging technique that assesses neurophysiology through the detection of the magnetic fields generated by neural currents. In this way, it is sensitive to brain activity, both in individual regions and brain-wide networks. Conventional MEG systems employ an array of sensors that must be cryogenically cooled to low temperature, in a rigid one-size-fits-all helmet. Systems are typically designed to fit adults and are therefore challenging to use for paediatric measurements. Despite this, MEG has been employed successfully in research to investigate neurodevelopmental disorders, and clinically for presurgical planning for paediatric epilepsy. Here, we review the applications of MEG in children, specifically focussing on autism spectrum disorder and attention-deficit hyperactivity disorder. Our review demonstrates the significance of MEG in furthering our understanding of these neurodevelopmental disorders, while also highlighting the limitations of current instrumentation. We also consider the future of paediatric MEG, with a focus on newly developed instrumentation based on optically pumped magnetometers (OPM-MEG). We provide a brief overview of the development of OPM-MEG systems, and how this new technology might enable investigation of brain function in very young children and infants. [ABSTRACT FROM AUTHOR]

Laryngeal dystonia (LD) is an isolated, task‐specific, focal dystonia characterized by intermittent spasms of laryngeal muscles impairing speech production. Although recent studies have demonstrated neural alterations in LD, the consistency of findings across studies is not well‐established, limiting their translational applicability. We conducted a systematic literature search to identify studies reporting stereotactic coordinates of peak structural and functional abnormalities in LD patients compared to healthy controls, followed by a coordinate‐based activation likelihood estimation meta‐analysis. A total of 21 functional and structural neuroimaging studies, including 31 experiments in 521 LD patients and 448 healthy controls, met the study inclusion criteria. The multimodal meta‐analysis of these studies identified abnormalities in the bilateral primary motor cortices, the left inferior parietal lobule and striatum, the right insula, and the supplementary motor area in LD patients compared to healthy controls. The meta‐analytical findings reinforce the current view of dystonia as a neural network disorder and consolidate evidence for future investigations probing these targets with new therapies. [ABSTRACT FROM AUTHOR]

• Nonlinear maturation of auditory cortex function and structure during infancy and toddlerhood. • Increased myelination in auditory radiations contributes to decreases in auditory evoked response latencies during infancy. • Associations between white-matter structure and speed of auditory response can be observed at the level of individual child. In school-age children, the myelination of the auditory radiation thalamocortical pathway is associated with the latency of auditory evoked responses, with the myelination of thalamocortical axons facilitating the rapid propagation of acoustic information. Little is known regarding this auditory system function-structure association in infants and toddlers. The present study tested the hypothesis that maturation of auditory radiation white-matter microstructure (e.g., fractional anisotropy (FA); measured using diffusion-weighted MRI) is associated with the latency of the infant auditory response (the P2m response, measured using magnetoencephalography, MEG) in a cross-sectional (N = 47, 2 to 24 months, 19 females) as well as longitudinal cohort (N = 18, 2 to 29 months, 8 females) of typically developing infants and toddlers. Of 18 longitudinal infants, 2 infants had data from 3 timepoints and 16 infants had data from 2 timepoints. In the cross-sectional sample, non-linear maturation of P2m latency and auditory radiation diffusion measures were observed. Auditory radiation diffusion accounted for significant variance in P2m latency, even after removing the variance associated with age in both P2m latency and auditory radiation diffusion measures. In the longitudinal sample, latency and FA associations could be observed at the level of a single child. Findings provide strong support for the hypothesis that an increase in thalamocortical neural conduction velocity, due to increased axon diameter and/or myelin maturation, contributes to a decrease in the infant P2m auditory evoked response latency. Infant multimodal brain imaging identifies brain mechanisms contributing to the rapid changes in neural circuit activity during the first two years of life. [ABSTRACT FROM AUTHOR]

Speech is often structurally and semantically ambiguous. Here we study how the human brain uses sentence context to resolve lexical ambiguity. Twenty-one participants listened to spoken narratives while magneto-encephalography (MEG) was recorded. Stories were annotated for grammatical word class (noun, verb, adjective) under two hypothesised sources of information: "bottom-up": the most common word class given the word's phonology; "top-down": the correct word class given the context. We trained a classifier on trials where the hypotheses matched (about 90%) and tested the classifier on trials where they mismatched. The classifier predicted top-down word class labels, and anti-correlated with bottom-up labels. Effects peaked ∼100 ms after word onset over mid-frontal MEG sensors. Phonetic information was encoded in parallel, though peaking later (∼200 ms). Our results support that lexical representations are built in a context-sensitive manner, which precedes sensory phonetic processing. We showcase multivariate analyses for teasing apart subtle representational distinctions from neural time series. [ABSTRACT FROM AUTHOR]

Background/Objectives: This study explored the potential of Hinoki aromatherapy to induce biomarkers of dysmenorrhea relief through working memory. Structural magnetic resonance imaging and magnetoencephalography (MEG) were used to examine their effects on neurophysiological responses to a visual working memory (VWM) test. Behavioral performance was measured to understand its effects on the overall working memory. Methods: Twenty-four healthy participants completed the VWM task during nonmenstruation and menstruation. Behavioral (accuracy and reaction time) and neurophysiological (event-related fields, source estimation, and permutation t-test on source data) measures were assessed without and with Hinoki aromatherapy. Results: A significant difference in the ratio of accuracy to reaction time was found without and with aromatherapy in participants with dysmenorrhea, suggesting that aromatherapy may improve working memory performance in this population. MEG analysis revealed high temporal resolution of evoked latency and intensity during the VWM task. Source localization of the activation aimed to identify brain areas involved in dysmenorrhea. Aromatherapy reduced signals in these areas, which may also contribute to reducing dysmenorrhea-related visual signals. Conclusions: Based on these findings, Hinoki aromatherapy may be a promising treatment option for alleviating dysmenorrhea and improving related symptoms by reducing activity in brain pain processing regions. These regions include the left entorhinal cortex, inferior temporal gyrus, primary visual cortex, retrosplenial cortex, and presubiculum. Furthermore, decreased activity in these areas with aromatherapy suggests that they could be used as biomarkers of dysmenorrhea relief. [ABSTRACT FROM AUTHOR]

Attention and decision-making processes are fundamental to cognition. However, they are usually experimentally confounded, making it difficult to link neural observations to specific processes. Here we separated the effects of selective attention from the effects of decision-making on brain activity obtained from human participants (both sexes), using a two-stage task where the attended stimulus and decision were orthogonal and separated in time. Multivariate pattern analyses of multimodal neuroimaging data revealed the dynamics of perceptual and decision-related information coding through time with magnetoencephalography (MEG), through space with functional magnetic resonance imaging (fMRI), and their combination (MEG-fMRI fusion). Our MEG results showed an effect of attention before decision-making could begin, and fMRI results showed an attention effect in early visual and frontoparietal regions. Model-based MEG-fMRI fusion suggested that attention boosted stimulus information in the frontoparietal and early visual regions before decision-making was possible. Together, our results suggest that attention affects neural stimulus representations in the frontoparietal regions independent of decision-making. [ABSTRACT FROM AUTHOR]

Dipole localization, a fundamental challenge in electromagnetic source imaging, inherently constitutes an optimization problem aimed at solving the inverse problem of electric current source estimation within the human brain. The accuracy of dipole localization algorithms is contingent upon the complexity of the forward model, often referred to as the head model, and the signal-to-noise ratio (SNR) of measurements. In scenarios characterized by low SNR, often corresponding to deep-seated sources, existing optimization techniques struggle to converge to global minima, thereby leading to the localization of dipoles at erroneous positions, far from their true locations. This study presents a novel hybrid algorithm that combines simulated annealing with the traditional quasi-Newton optimization method, tailored to address the inherent limitations of dipole localization under low-SNR conditions. Using a realistic head model for both electroencephalography (EEG) and magnetoencephalography (MEG), it is demonstrated that this novel hybrid algorithm enables significant improvements of up to 45% in dipole localization accuracy compared to the often-used dipole scanning and gradient descent techniques. Localization improvements are not only found for single dipoles but also in two-dipole-source scenarios, where sources are proximal to each other. The novel methodology presented in this work could be useful in various applications of clinical neuroimaging, particularly in cases where recordings are noisy or sources are located deep within the brain. [ABSTRACT FROM AUTHOR]

Background: Neurophysiological studies recognized that Autism Spectrum Disorder (ASD) is associated with altered patterns of over- and under-connectivity. However, little is known about network organization in children with ASD in the early phases of development and its correlation with the severity of core autistic features. Methods: The present study aimed at investigating the association between brain connectivity derived from MEG signals and severity of ASD traits measured with different diagnostic clinical scales, in a sample of 16 children with ASD aged 2 to 6 years. Results: A significant correlation emerged between connectivity strength in cortical brain areas implicated in several resting state networks (Default mode, Central executive, Salience, Visual and Sensorimotor) and the severity of communication anomalies, social interaction problems, social affect problems, and repetitive behaviors. Seed analysis revealed that this pattern of correlation was mainly caused by global rather than local effects. Conclusions: The present evidence suggests that altered connectivity strength in several resting state networks is related to clinical features and may contribute to neurofunctional correlates of ASD. Future studies implementing the same method on a wider and stratified sample may further support functional connectivity as a possible biomarker of the condition. [ABSTRACT FROM AUTHOR]

A four-port annular ring patch antenna with a symmetrical slotted partial ground structure for mid-band 5G/Bluetooth/Wi-Fi/ISM band/WLAN and IoT applications at an operating frequency of 2.5 GHz is proposed. The proposed geometry is fabricated over the FR-4 epoxy substrate with dielectric constant 4.4, thickness of the substrate 1.6 mm, and loss tangent of 0.02. Moreover, the complete electrical dimension of presented design is 0.62 λ 0 × 0.48 λ 0 × 0.013 λ 0 , where λ 0 is wavelength in the free space corresponding to the resonating frequency (i.e., 2.5 GHz). In the proposed work, for enhancing the isolation a vertical slotted strip is used in the middle of the ground plane. Furthermore, we also enhanced the MIMO parameters performances, such as a low envelope correlation coefficient (ECC) between antenna elements, good diversity gain (DG), low channel capacity loss (CCL), acceptable mean effective gain (MEG), and better total active reflection coefficient (TARC) in the operating band. Moreover, due to four elements the presented work provide the higher data rates, excellent throughput of the signals and improve communication reliability as well as signal strength. The values of different parameters obtained for the proposed structure are as follows; antenna realized gain of 4.65 dBi, total efficiency of 96%, ECC < 0.025, DG is 9.98 dB, CCL < 0.012 bits/s/Hz, and MEG lies in between - 3 dB and - 12 dB. Throughout the band, the maximum isolation achieved among all ports is < - 26.4 dB. The overall frequency range for which reflection coefficient < - 10 dB is 2.36 to 2.99 GHz. [ABSTRACT FROM AUTHOR]

In order to alleviate the existing global energy and environmental difficulties related to the usage of fossil fuels, there is requirement of improved energy alternatives such as limitless solar energy. The creation of low-cost photovoltaic devices and their design are of significant interest which represent the pinnacle of effective solar energy harvesting. PbS colloidal quantum dot solar cell has a promising ability for ultra-thin solar cell applications. In the present work, the device architecture indium tin oxide/SnO2/PbS–TBAI/MoO3/Au has been used in which MoO3 (molybdenum trioxide) is employed as HTL (hole transport layer) with 3.0 eV bandgap and SnO2 (tin (IV) oxide) as ETL (electron transport layer) with 3.5 eV bandgap and PbS–TBAI (tetrabutylammonium iodide) is used as an absorber layer with 1.2 eV bandgap. Further, 1D solar cell capacitance simulation program tool (SCAPS-1D) is used to obtain energy band diagram, quantum energy and current density curve. The achieved value of power conversion efficiency is 30.16%, Voc (open-circuit voltage) is 0.9025 V, Jsc (short-circuit current density) is 38.746 mA/cm2 and fill factor is 86.14%. For further optimization, the impact of temperature, thickness of active layer and work function on the PV parameters has been studied. [ABSTRACT FROM AUTHOR]

Abstract Background Alzheimer’s Disease (AD) is the most common form of dementia. Its early stage, amnestic Mild Cognitive Impairment (aMCI), is characterized by disrupted information flow in the brain. Previous studies have yielded inconsistent results when using electrophysiological techniques to investigate functional connectivity changes in AD, and a contributing factor may be the study of brain activity divided into frequencies. Methods Our study aimed to address this issue by employing a cross-frequency approach to compare the functional networks of 172 healthy subjects and 105 aMCI patients. Using magnetoencephalography, we constructed source-based multilayer graphs considering both intra- and inter-frequency functional connectivity. We then assessed changes in network organization through three centrality measures, and combined them into a unified centrality score to provide a comprehensive assessment of centrality disruption in aMCI. Results The results revealed a noteworthy shift in centrality distribution in aMCI patients, both in terms of spatial distribution and frequency. Posterior brain regions decrease synchrony between their high-frequency oscillations and other regions’ activity across all frequencies, while anterior regions increase synchrony between their low-frequency oscillations and other regions’ activity across all frequencies. Thus, posterior regions reduce their relative importance in favor of anterior regions. Conclusions Our findings provide valuable insights into the intricate changes that occur in functional brain networks during the early stages of AD, demonstrating that considering the interplays between different frequency bands enhances our understanding of AD network dynamics and setting a precedent for the study of functional networks using a multilayer approach.

Sleep is a highly stereotyped phenomenon, requiring robust spatiotemporal coordination of neural activity. Understanding how the brain coordinates neural activity with sleep onset can provide insights into the physiological functions subserved by sleep and the pathologic phenomena associated with sleep onset. We quantified whole-brain network changes in synchrony and information flow during the transition from wakefulness to light non-rapid eye movement (NREM) sleep, using MEG imaging in a convenient sample of 14 healthy human participants (11 female; mean 63.4 years [SD 11.8 years]). We furthermore performed computational modeling to infer excitatory and inhibitory properties of local neural activity. The transition from wakefulness to light NREM was identified to be encoded in spatially and temporally specific patterns of long-range synchrony. Within the delta band, there was a global increase in connectivity from wakefulness to light NREM, which was highest in frontoparietal regions. Within the theta band, there was an increase in connectivity in fronto-parieto-occipital regions and a decrease in temporal regions from wakefulness to Stage 1 sleep. Patterns of information flow revealed that mesial frontal regions receive hierarchically organized inputs from broad cortical regions upon sleep onset, including direct inflow from occipital regions and indirect inflow via parieto-temporal regions within the delta frequency band. Finally, biophysical neural mass modeling demonstrated changes in the anterior-to-posterior distribution of cortical excitation-to-inhibition with increased excitation-to-inhibition model parameters in anterior regions in light NREM compared with wakefulness. Together, these findings uncover whole-brain corticocortical structure and the orchestration of local and long-range, frequency-specific cortical interactions in the sleep-wake transition.SIGNIFICANCE STATEMENT Our work uncovers spatiotemporal cortical structure of neural synchrony and information flow upon the transition from wakefulness to light non-rapid eye movement sleep. Mesial frontal regions were identified to receive hierarchically organized inputs from broad cortical regions, including both direct inputs from occipital regions and indirect inputs via the parieto-temporal regions within the delta frequency range. Biophysical neural mass modeling revealed a spatially heterogeneous, anterior-posterior distribution of cortical excitation-to-inhibition. Our findings shed light on the orchestration of local and long-range cortical neural structure that is fundamental to sleep onset, and support an emerging view of cortically driven regulation of sleep homeostasis.

Time–frequency parameterization for oscillations in specific frequency bands reflects the dynamic changes in the brain. It is related to cognitive behavior and diseases and has received significant attention in neuroscience. However, many studies do not consider the impact of the aperiodic noise and neural activity, including their time-varying fluctuations. Some studies are limited by the low resolution of the time–frequency spectrum and parameter-solved operation. Therefore, this paper proposes super-resolution time–frequency periodic parameterization of (transient) oscillation (STPPTO). STPPTO obtains a super-resolution time–frequency spectrum with Superlet transform. Then, the time–frequency representation of oscillations is obtained by removing the aperiodic component fitted in a time-resolved way. Finally, the definition of transient events is used to parameterize oscillations. The performance of this method is validated on simulated data and its reliability is demonstrated on magnetoencephalography. We show how it can be used to explore and analyze oscillatory activity under rhythmic stimulation. [ABSTRACT FROM AUTHOR]

In this article, an F-shaped four-port multiple-input multiple-output (MIMO) antenna is designed and analyzed. In the designed antenna for achieving high isolation, we introduced a novel isolation technique that appears like plus-shaped wall placed in between the antenna elements. The antenna is designed on a low-cost FR-4 epoxy substrate with total dimensions of 0.61 $ \lambda _{0}\times 0.61\lambda _{0}\times 0.03\lambda _{0} $ λ 0 × 0.61 λ 0 × 0.03 λ 0 (31 mm × 31 mm × 1.58 mm) where $ \lambda _{0} $ λ 0 is the free space wavelength at 5.8 GHz and experimentally verified. This MIMO antenna design covers operating the range of frequencies 5.47–6.20 GHz ( $ |S_{11}| \lt - $ | S 11 | < − 10 dB) which provides a bandwidth of 730 MHz. In terms of performance, the proposed antenna achieves high isolation of $ \lt -45.52 $ < − 45.52 dB with an improved reflection coefficient of $ -30.44 $ − 30.44 dB, a peak gain of 3.77 dBi and a radiation efficiency more than 82% across the entire operating band. Moreover, the achieved MIMO diversity parameters of the proposed antenna are envelope correlation coefficient < 0.005, diversity gain $ \lt 9.99 $ < 9.99 dB, mean effective gain $ \lt -3 $ < − 3 dB and total active reflection coefficient $ \lt -10 $ < − 10 dB in the operating band of frequency. The simulated and measured results show a good agreement between them. Finally, after analyzing the performance of the proposed MIMO configuration, we can say that this antenna is suitable for C-band, WiMAX, Wireless-Fidelity (Wi-Fi), Wireless Local-Area Network (WLAN), Bluetooth and Industrial, Scientific, & Medical (ISM) bands applications. [ABSTRACT FROM AUTHOR]

Visual entrainment is a powerful and widely used research tool to study visual information processing in the brain. While many entrainment studies have focused on frequencies around 14–16 Hz, there is renewed interest in understanding visual entrainment at higher frequencies (e.g., gamma‐band entrainment). Notably, recent groundbreaking studies have demonstrated that gamma‐band visual entrainment at 40 Hz may have therapeutic effects in the context of Alzheimer's disease (AD) by stimulating specific neural ensembles, which utilize GABAergic signaling. Despite such promising findings, few studies have investigated the optimal parameters for gamma‐band visual entrainment. Herein, we examined whether visual stimulation at 32, 40, or 48 Hz produces optimal visual entrainment responses using high‐density magnetoencephalography (MEG). Our results indicated strong entrainment responses localizing to the primary visual cortex in each condition. Entrainment responses were stronger for 32 and 40 Hz relative to 48 Hz, indicating more robust synchronization of neural ensembles at these lower gamma‐band frequencies. In addition, 32 and 40 Hz entrainment responses showed typical patterns of habituation across trials, but this effect was absent for 48 Hz. Finally, connectivity between visual cortex and parietal and prefrontal cortices tended to be strongest for 40 relative to 32 and 48 Hz entrainment. These results suggest that neural ensembles in the visual cortex may resonate at around 32 and 40 Hz and thus entrain more readily to photic stimulation at these frequencies. Emerging AD therapies, which have focused on 40 Hz entrainment to date, may be more effective at lower relative to higher gamma frequencies, although additional work in clinical populations is needed to confirm these findings. Practitioner Points: Gamma‐band visual entrainment has emerged as a therapeutic approach for eliminating amyloid in Alzheimer's disease, but its optimal parameters are unknown.We found stronger entrainment at 32 and 40 Hz compared to 48 Hz, suggesting neural ensembles prefer to resonate around these relatively lower gamma‐band frequencies.These findings may inform the development and refinement of innovative AD therapies and the study of GABAergic visual cortical functions. [ABSTRACT FROM AUTHOR]

Testosterone levels sharply rise during the transition from childhood to adolescence and these changes are known to be associated with changes in human brain structure. During this same developmental window, there are also robust changes in the neural oscillatory dynamics serving verbal working memory processing. Surprisingly, whereas many studies have investigated the effects of chronological age on the neural oscillations supporting verbal working memory, none have probed the impact of endogenous testosterone levels during this developmental period. Using a sample of 89 youth aged 6–14 years‐old, we collected salivary testosterone samples and recorded magnetoencephalography during a modified Sternberg verbal working memory task. Significant oscillatory responses were identified and imaged using a beamforming approach and the resulting maps were subjected to whole‐brain ANCOVAs examining the effects of testosterone and sex, controlling for age, during verbal working memory encoding and maintenance. Our primary results indicated robust testosterone‐related effects in theta (4–7 Hz) and alpha (8–14 Hz) oscillatory activity, controlling for age. During encoding, females exhibited weaker theta oscillations than males in right cerebellar cortices and stronger alpha oscillations in left temporal cortices. During maintenance, youth with greater testosterone exhibited weaker alpha oscillations in right parahippocampal and cerebellar cortices, as well as regions across the left‐lateralized language network. These results extend the existing literature on the development of verbal working memory processing by showing region and sex‐specific effects of testosterone, and are the first results to link endogenous testosterone levels to the neural oscillatory activity serving verbal working memory, above and beyond the effects of chronological age. [ABSTRACT FROM AUTHOR]

Electro/Magneto‐EncephaloGraphy (EEG/MEG) source imaging (EMSI) of epileptic activity from deep generators is often challenging due to the higher sensitivity of EEG/MEG to superficial regions and to the spatial configuration of subcortical structures. We previously demonstrated the ability of the coherent Maximum Entropy on the Mean (cMEM) method to accurately localize the superficial cortical generators and their spatial extent. Here, we propose a depth‐weighted adaptation of cMEM to localize deep generators more accurately. These methods were evaluated using realistic MEG/high‐density EEG (HD‐EEG) simulations of epileptic activity and actual MEG/HD‐EEG recordings from patients with focal epilepsy. We incorporated depth‐weighting within the MEM framework to compensate for its preference for superficial generators. We also included a mesh of both hippocampi, as an additional deep structure in the source model. We generated 5400 realistic simulations of interictal epileptic discharges for MEG and HD‐EEG involving a wide range of spatial extents and signal‐to‐noise ratio (SNR) levels, before investigating EMSI on clinical HD‐EEG in 16 patients and MEG in 14 patients. Clinical interictal epileptic discharges were marked by visual inspection. We applied three EMSI methods: cMEM, depth‐weighted cMEM and depth‐weighted minimum norm estimate (MNE). The ground truth was defined as the true simulated generator or as a drawn region based on clinical information available for patients. For deep sources, depth‐weighted cMEM improved the localization when compared to cMEM and depth‐weighted MNE, whereas depth‐weighted cMEM did not deteriorate localization accuracy for superficial regions. For patients' data, we observed improvement in localization for deep sources, especially for the patients with mesial temporal epilepsy, for which cMEM failed to reconstruct the initial generator in the hippocampus. Depth weighting was more crucial for MEG (gradiometers) than for HD‐EEG. Similar findings were found when considering depth weighting for the wavelet extension of MEM. In conclusion, depth‐weighted cMEM improved the localization of deep sources without or with minimal deterioration of the localization of the superficial sources. This was demonstrated using extensive simulations with MEG and HD‐EEG and clinical MEG and HD‐EEG for epilepsy patients. [ABSTRACT FROM AUTHOR]

Scene memory is prone to systematic distortions potentially arising from experience with the external world. Boundary transformation, a well-known memory distortion effect along the near-far axis of the three-dimensional space, represents the observer's erroneous recall of scenes' viewing distance. Researchers argued that normalization to the prototypical viewpoint with the high-probability viewing distance influenced this phenomenon. Herein, we hypothesized that the prototypical viewpoint also exists in the vertical angle of view (AOV) dimension and could cause memory distortion along scenes' vertical axis. Human subjects of both sexes were recruited to test this hypothesis, and two behavioral experiments were conducted, revealing a systematic memory distortion in the vertical AOV in both the forced choice (n = 79) and free adjustment (n = 30) tasks. Furthermore, the regression analysis implied that the complexity information asymmetry in scenes' vertical axis and the independent subjective AOV ratings from a large set of online participants (n = 1,208) could jointly predict AOV biases. Furthermore, in a functional magnetic resonance imaging experiment (n = 24), we demonstrated the involvement of areas in the ventral visual pathway (V3/V4, PPA, and OPA) in AOV bias judgment. Additionally, in a magnetoencephalography experiment (n = 20), we could significantly decode the subjects' AOV bias judgments ~140 ms after scene onset and the low-level visual complexity information around the similar temporal interval. These findings suggest that AOV bias is driven by the normalization process and associated with the neural activities in the early stage of scene processing. [ABSTRACT FROM AUTHOR]

The semantic knowledge stored in our brains can be accessed from different stimulus modalities. For example, a picture of a cat and the word "cat" both engage similar conceptual representations. While existing research has found evidence for modality-independent representations, their content remains unknown. Modality-independent representations could be semantic, or they might also contain perceptual features. We developed a novel approach combining word/picture cross-condition decoding with neural network classifiers that learned latent modality-independent representations from MEG data (25 human participants, 15 females, 10 males). We then compared these representations to models representing semantic, sensory, and orthographic features. Results show that modality-independent representations correlate both with semantic and visual representations. There was no evidence that these results were due to picture-specific visual features or orthographic features automatically activated by the stimuli presented in the experiment. These findings support the notion that modality-independent concepts contain both perceptual and semantic representations. [ABSTRACT FROM AUTHOR]

Beside the well‐documented involvement of secondary somatosensory area, the cortical network underlying late somatosensory evoked potentials (P60/N60 and P100/N100) is still unknown. Electroencephalogram and magnetoencephalogram source imaging were performed to further investigate the origin of the brain cortical areas involved in late somatosensory evoked potentials, using sensory inputs of different strengths and by testing the correlation between cortical sources. Simultaneous high‐density electroencephalograms and magnetoencephalograms were performed in 19 participants, and electrical stimulation was applied to the median nerve (wrist level) at intensity between 1.5 and 9 times the perceptual threshold. Source imaging was undertaken to map the stimulus‐induced brain cortical activity according to each individual brain magnetic resonance imaging, during three windows of analysis covering early and late somatosensory evoked potentials. Results for P60/N60 and P100/N100 were compared with those for P20/N20 (early response). According to literature, maximal activity during P20/N20 was found in central sulcus contralateral to stimulation site. During P60/N60 and P100/N100, activity was observed in contralateral primary sensorimotor area, secondary somatosensory area (on both hemispheres) and premotor and multisensory associative cortices. Late responses exhibited similar characteristics but different from P20/N20, and no significant correlation was found between early and late generated activities. Specific clusters of cortical activities were activated with specific input/output relationships underlying early and late somatosensory evoked potentials. Cortical networks, partly common to and distinct from early somatosensory responses, contribute to late responses, all participating in the complex somatosensory brain processing. [ABSTRACT FROM AUTHOR]

Regularities in our surroundings lead to predictions about upcoming events. Previous research has shown that omitted sounds during otherwise regular tone sequences elicit frequency‐specific neural activity related to the upcoming but omitted tone. We tested whether this neural response is depending on the unpredictability of the omission. Therefore, we recorded magnetencephalography (MEG) data while participants listened to ordered or random tone sequences with omissions occurring either ordered or randomly. Using multivariate pattern analysis shows that the frequency‐specific neural pattern during omission within ordered tone sequences occurs independent of the regularity of the omissions. These results suggest that the auditory predictions based on sensory experiences are not immediately updated by violations of those expectations. [ABSTRACT FROM AUTHOR]

A large body of research establishes the efficacy of musical intervention in many aspects of physical, cognitive, communication, social, and emotional rehabilitation. However, the underlying neural mechanisms for musical therapy remain elusive. This study aimed to investigate the potential neural correlates of musical therapy, focusing on the changes in the topology of emotion brain network. To this end, a Bayesian statistical approach and a cross-over experimental design were employed together with two resting-state magnetoencephalography (MEG) as controls. MEG recordings of 30 healthy subjects were acquired while listening to five auditory stimuli in random order. Two resting-state MEG recordings of each subject were obtained, one prior to the first stimulus (pre) and one after the final stimulus (post). Time series at the level of brain regions were estimated using depth-weighted minimum norm estimation (wMNE) source reconstruction method and the functional connectivity between these regions were computed. The resultant connectivity matrices were used to derive two topological network measures: transitivity and global efficiency which are important in gauging the functional segregation and integration of brain network respectively. The differences in these measures between pre- and post-stimuli resting MEG were set as the equivalence regions. We found that the network measures under all auditory stimuli were equivalent to the resting state network measures in all frequency bands, indicating that the topology of the functional brain network associated with emotional regulation in healthy subjects remains unchanged following these auditory stimuli. This suggests that changes in the emotion network topology may not be the underlying neural mechanism of musical therapy. Nonetheless, further studies are required to explore the neural mechanisms of musical interventions especially in the populations with neuropsychiatric disorders. [ABSTRACT FROM AUTHOR]

The wireless and portable equipment demand for boosting the data rate, spectral efficiency, coverage, SNR, and capacity which is fulfilled by MIMO antenna technology. In this research 4 elements hexagonal shaped antenna using MIMO techniques is designed for 2.1 GHz mobile and wireless applications. The antenna has four ports with identical radiators with hexagon shape. The special designed manifold arms of the proposed antenna design provide low correlation among the radiators. The inter-port isolation greater than 15 dB is achieved. The other MIMO antenna parameters like ECC is < 0.08 and the diversity gain is 10 dB in considered in 2:1 VSWR band. The proposed design ensures lower than 0.5 W/kg specific absorption rate (SAR), 3.0 dB mean effective gain (MEG) and 0.4 bits/s/Hz channel capacity loss (CCL). The peak gain of the antenna is 0.45 dBi at resonance. The E-field shows a maximum magnitude/major lobe in the direction of 190 °. The H-Field shows the major radiation in the direction of 187 °. The CST-MWS antenna designing tool is used to simulate and optimize the proposed design and it fabricated on FR-4 substrate. The research focuses on various parameters associated with MIMO antenna viz SAR, S-parameters, envelop correlation coefficient (ECC), radiation patterns, CCL, Diversity Gain surface current distribution, and MEG. [ABSTRACT FROM AUTHOR]

Human experience is imbued by the sense of being an embodied agent. The investigation of such basic self-consciousness has been hampered by the difficulty of comprehensively modulating it in the laboratory while reliably capturing ensuing subjective changes. The present preregistered study fills this gap by combining advanced meditative states with principled phenomenological interviews: 46 long-term meditators (19 female, 27 male) were instructed to modulate and attenuate their embodied self-experience during magnetoencephalographic monitoring. Results showed frequency-specific (high-beta band) activity reductions in frontoparietal and posterior medial cortices (PMC). Importantly, PMC reductions were driven by a subgroup describing radical embodied self-disruptions, including suspension of agency and dissolution of a localized first-person perspective. Neural changes were correlated with lifetime meditation and interview-derived experiential changes, but not with classical self-reports. The results demonstrate the potential of integrating in-depth first–person methods into neuroscientific experiments. Furthermore, they highlight neural oscillations in the PMC as a central process supporting the embodied sense of self. [ABSTRACT FROM AUTHOR]

The 40 Hz auditory steady-state response (ASSR), an oscillatory brain response to periodically modulated auditory stimuli, is a promising, noninvasive physiological biomarker for schizophrenia and related neuropsychiatric disorders. The 40 Hz ASSR might be amplified by synaptic interactions in cortical circuits, which are, in turn, disturbed in neuropsychiatric disorders. Here, we tested whether the 40 Hz ASSR in the human auditory cortex depends on two key synaptic components of neuronal interactions within cortical circuits: excitation via N-methyl-aspartate glutamate (NMDA) receptors and inhibition via gamma-amino-butyric acid (GABA) receptors. We combined magnetoencephalography (MEG) recordings with placebo-controlled, low-dose pharmacological interventions in the same healthy human participants (13 males, 7 females). All participants exhibited a robust 40 Hz ASSR in auditory cortices, especially in the right hemisphere, under a placebo. The GABAA receptor–agonist lorazepam increased the amplitude of the 40 Hz ASSR, while no effect was detectable under the NMDA blocker memantine. Our findings indicate that the 40 Hz ASSR in the auditory cortex involves synaptic (and likely intracortical) inhibition via the GABAA receptor, thus highlighting its utility as a mechanistic signature of cortical circuit dysfunctions involving GABAergic inhibition. [ABSTRACT FROM AUTHOR]

Neural oscillations reflect fluctuations in excitability, which biases the percept of ambiguous sensory input. Why this bias occurs is still not fully understood. We hypothesized that neural populations representing likely events are more sensitive, and thereby become active on earlier oscillatory phases, when the ensemble itself is less excitable. Perception of ambiguous input presented during less-excitable phases should therefore be biased toward frequent or predictable stimuli that have lower activation thresholds. Here, we show such a frequency bias in spoken word recognition using psychophysics, magnetoencephalography (MEG), and computational modelling. With MEG, we found a double dissociation, where the phase of oscillations in the superior temporal gyrus and medial temporal gyrus biased word-identification behavior based on phoneme and lexical frequencies, respectively. This finding was reproduced in a computational model. These results demonstrate that oscillations provide a temporal ordering of neural activity based on the sensitivity of separable neural populations. [ABSTRACT FROM AUTHOR]

The demand for compact, efficient, and versatile antennas has surged in tandem with the rapid evolution of wireless communication technologies. In response, this paper presents a pioneering Quadport-based fractal compact MIMO antenna designed to meet the stringent requirements of modern communication systems. The antenna incorporates a circular-shaped fractal radiating element and a stub-loaded ground region with a Partial ground, resulting in a significant enhancement of isolation performance. Through iterative optimisation, involving the integration of Partial ground, loading stubs, and fractals into the patch area, the antenna achieves optimal dimensions of 0.66λ × 0.83λ while operating across five distinct frequency bands, thereby catering to a wide range of multiband applications. Remarkable performance metrics are demonstrated, including peak isolation of 35 dB and minimum return loss of − 25.80 dB, alongside a peak electric field of 5.51 × 103 V/m. The polarization response for various resonating frequencies is meticulously analysed. The diverse parameters such as Total Active Reflection Coefficient < − 10, Mean Effective Gain around 0, Diversity Gain is around 10, Channel Capacity Loss < 0.2, and Envelope Correlation Coefficient < 0.1 are achieved. Utilising FR4 material for design enables mass production feasibility, further enhancing the antenna's practicality. Comparative analysis against existing literature underscores its superiority, positioning it as an ideal candidate for applications in 6G networks, WiMax, and weather monitoring. Overall, this Quadport-based fractal compact MIMO antenna represents a significant advancement in antenna offering a compelling blend of compactness, multiband capability, and exceptional performance metrics essential for the next generation of communication applications. [ABSTRACT FROM AUTHOR]

Absence seizures are classically associated with behavioral arrest and transient deficits in consciousness, yet substantial variability exists in the severity of the impairment. Despite several decades of research on the topic, the pathophysiology of absence seizures and the mechanisms underlying behavioral impairment remain unclear. Several rationales have been proposed including widespread cortical deactivation, reduced perception of external stimuli, and transient suspension of the default mode network, among others. This review aims to summarize the current knowledge on the neural correlates of impaired consciousness in absence seizures. We review evidence from studies using animal models of absence epilepsy, electroencephalography, functional magnetic resonance imaging, magnetoencephalography, positron emission tomography, and single photon emission computed tomography. [ABSTRACT FROM AUTHOR]

Here, we report onset latencies for multisensory processing of letters in the primary auditory and visual sensory cortices. Healthy adults were presented with 300-ms visual and/or auditory letters (uppercase Roman alphabet and the corresponding auditory letter names in English). Magnetoencephalography (MEG) evoked response generators were extracted from the auditory and visual sensory cortices for both within-modality and cross-sensory activations; these locations were mainly consistent with functional magnetic resonance imaging (fMRI) results in the same subjects. In the primary auditory cortices (Heschl’s gyri) activity to auditory stimuli commenced at 25 ms and to visual stimuli at 65 ms (median values). In the primary visual cortex (Calcarine fissure) the activations started at 48 ms to visual and at 62 ms to auditory stimuli. This timing pattern suggests that the origins of the cross-sensory activations may be in the primary sensory cortices of the opposite modality, with conduction delays (from one sensory cortex to another) of 17–37 ms. Audiovisual interactions for letters started at 125 ms in the auditory and at 133 ms in the visual cortex (60–71 ms after inputs from both modalities converged). Multivariate pattern analysis suggested similar latency differences between the sensory cortices. Combined with our earlier findings for simpler stimuli (noise bursts and checkerboards), these results suggest that primary sensory cortices participate in early cross-modal and interaction processes similarly for different stimulus materials, but previously learned audiovisual associations and stimulus complexity may delay the start of the audiovisual interaction stage.

IntroductionRecent research has recognized executive dysfunction as another component affected in Primary Progressive Aphasia (PPA). This systematic review aimed to examine what information distinctive neurophysiological markers can provide in the evaluation of executive function (EF) deficits in PPA, and to what effect executive function deficits can be assessed through the characteristics of functional markers.MethodsWe conducted a systematic literature search following the PRISMA guidelines across studies that employed neuropsychological assessments and neurophysiological imaging techniques (EEG, MEG; PET, SPECT, fMRI, fNIRS) to investigate executive dysfunction correlates in PPA.ResultsFindings from nine articles including a total number of 111 individuals with PPA met our inclusion criteria and were synthesized. Although research on the neural correlates of EF deficits is scarce, MEG studies revealed widespread oscillatory slowing, with increased delta and decreased alpha power, where alterations in alpha, theta, and beta activities were significant predictors of executive function deficits. PET findings demonstrated significant correlations between executive dysfunction and hypometabolism in frontal brain regions. fMRI results indicated elevated homotopic connectivity in PPA patients, with a broader and more anterior distribution of abnormal hippocampal connections of which were associated with reduced executive performance.ConclusionOur study provides indirect support for the assumption regarding the significance of the frontal regions and inferior frontal junction in executive control and demonstrates that neurophysiological tools can be a useful aid to further investigate clinical-neurophysiological correlations in PPA.

Purpose: To explore the utility of high frequency oscillations (HFO) and long-range temporal correlations (LRTCs) in preoperative assessment of epilepsy. Methods: MEG ripples were detected in 59 drug-resistant epilepsy patients, comprising 5 with parietal lobe epilepsy (PLE), 21 with frontal lobe epilepsy (FLE), 14 with lateral temporal lobe epilepsy (LTLE), and 19 with mesial temporal lobe epilepsy (MTLE) to identify the epileptogenic zone (EZ). The results were compared with clinical MEG reports and resection area. Subsequently, LRTCs were quantified at the source-level by detrended fluctuation analysis (DFA) and life/waiting -time at 5 bands for 90 cerebral cortex regions. The brain regions with larger DFA exponents and standardized life-waiting biomarkers were compared with the resection results. Results: Compared to MEG sensor-level data, ripple sources were more frequently localized within the resection area. Moreover, source-level analysis revealed a higher proportion of DFA exponents and life-waiting biomarkers with relatively higher rankings, primarily distributed within the resection area (p

Neuroimaging studies have increasingly leveraged the information in multivariate patterns of brain activity, transitioning from voxel-by-voxel activation comparisons to multi-voxel pattern analysis (MVPA) and decoding approaches. Representational Similarity Analysis (RSA) has further advanced this field, enabling comparisons of representational structures across neuroimaging modalities and computational models, in particular in fMRI and EEG/MEG research. Recent applications have extended to brain connectivity estimation, enhancing our understanding of neural representations in language and cognition. This special issue, "Patterns Of Language", showcases recent applications and methodological developments of multivariate analysis approaches in the neuroscience of language. [ABSTRACT FROM AUTHOR]

The amplitude envelope of speech is crucial for accurate comprehension. Considered a key stage in speech processing, the phase of neural activity in the theta-delta bands (1-10 Hz) tracks the phase of the speech amplitude envelope during listening. However, the mechanisms underlying this envelope representation have been heavily debated. A dominant model posits that envelope tracking reflects entrainment of endogenous low-frequency oscillations to the speech envelope. Alternatively, envelope tracking reflects a series of evoked responses to acoustic landmarks within the envelope. It has proven challenging to distinguish these two mechanisms. To address this, we recorded MEG while participants (n = 12, 6 female) listened to natural speech, and compared the neural phase patterns to the predictions of two computational models: an oscillatory entrainment model and a model of evoked responses to peaks in the rate of envelope change. Critically, we also presented speech at slowed rates, where the spectro-temporal predictions of the two models diverge. Our analyses revealed transient theta phase-locking in regular speech, as predicted by both models. However, for slow speech, we found transient theta and delta phase-locking, a pattern that was fully compatible with the evoked response model but could not be explained by the oscillatory entrainment model. Furthermore, encoding of acoustic edge magnitudes was invariant to contextual speech rate, demonstrating speech rate normalization of acoustic edge representations. Together, our results suggest that neural phase-locking to the speech envelope is more likely to reflect discrete representation of transient information rather than oscillatory entrainment.SIGNIFICANCE STATEMENT This study probes a highly debated topic in speech perception: the neural mechanisms underlying the cortical representation of the temporal envelope of speech. It is well established that the slow intensity profile of the speech signal, its envelope, elicits a robust brain response that "tracks" these envelope fluctuations. The oscillatory entrainment model posits that envelope tracking reflects phase alignment of endogenous neural oscillations. Here the authors provide evidence for a distinct mechanism. They show that neural speech envelope tracking arises from transient evoked neural responses to rapid increases in the speech envelope. Explicit computational modeling provides direct and compelling evidence that evoked responses are the primary mechanism underlying cortical speech envelope representations, with no evidence for oscillatory entrainment.

Abstract Electroencephalogram (EEG) microstate analysis entails finding dynamics of quasi-stable and generally recurrent discrete states in multichannel EEG time series data and relating properties of the estimated state-transition dynamics to observables such as cognition and behavior. While microstate analysis has been widely employed to analyze EEG data, its use remains less prevalent in functional magnetic resonance imaging (fMRI) data, largely due to the slower timescale of such data. In the present study, we extend various data clustering methods used in EEG microstate analysis to resting-state fMRI data from healthy humans to extract their state-transition dynamics. We show that the quality of clustering is on par with that for various microstate analyses of EEG data. We then develop a method for examining test–retest reliability of the discrete-state transition dynamics between fMRI sessions and show that the within-participant test–retest reliability is higher than between-participant test–retest reliability for different indices of state-transition dynamics, different networks, and different data sets. This result suggests that state-transition dynamics analysis of fMRI data could discriminate between different individuals and is a promising tool for performing fingerprinting analysis of individuals.

Summary: Current generation of mobile and wireless communication can have portable, compact, lightweight, highly reliable, easy to access, high coverage, high capacity, high SNR, and high gain antennas for non‐line‐of‐sight communication. MIMO technology provides these all and has data rate optimization, diversity, spatial multiplexing, and solution of multipath propagation. The current requirement for designing a compact MIMO antenna with better isolation is what spurred the creation of the proposed antenna. In this research, a mathematically inspired generalized antenna is proposed for 1.8/1.9 GHz application in the 1.5–2.1 GHz range. The bandwidth in this case is 600 MHz. The return loss is −78 dB at the resonant with more than 17 dB isolation in the entire band. The envelope correlation coefficient (ECC) is found below 5 × 10−3. The overall size of the antenna is 40 × 81.76 mm2on FR‐4 dielectric laminate. To improve the isolation further, a parasitic element is used between the radiating elements, and it provides 7 dB improvements in isolation and is confirmed by the surface current distribution. The radiation efficiency is more than 90%, and maximum current density of 29.9 A/m2 is found in the entire band. In this study, evaluation and discussion of additional antenna performance parameters channel capacity loss (CCL), mean effective gain (MEG), and specific absorption rate (SAR) are also included. [ABSTRACT FROM AUTHOR]