Brain Synchronization Research Articles

Neuro-Cognitive Insights Into Engineering Design: Exploring Electroencephalography Predictive Associations With Task Performance

Abstract This paper investigates the relationship between brain activity, measured by electroencephalography (EEG) data, and the performance assessment result of engineering design activities involving different cognitive processes. Employing a novel signal processing pipeline, we analyzed EEG variations of 37 subjects during two design tasks that mostly leverage, respectively, convergent and divergent thinking: the design with morphological table (task and the problem-solving task. The EEG recordings underwent meticulous artifact removal, allowing for a comprehensive investigation into the statistical relationships between frequency bands, channels, and design outcome performance metrics. The developed models linking better design outcomes with brain (de)synchronization demonstrated remarkable accuracy, precision, and recall across performance metrics for both tasks. Notably, the EEG data in theta band measured from the frontal area at both hemispheres and a left parietal/occipital channel were essential for estimating better design performance with brain desynchronization. On the contrary, the model based on brain synchronization produces precise estimations of design performance with alpha band and channels in temporal and parietal areas. These findings highlight EEG variation as a viable proxy for design performance, paving the way for more effective performance prediction models with fewer sensors. Overall, this research contributes to the emerging field of neurocognitive design assessment and underscores the potential for EEG-based predictions in engineering design tasks.

Meeting the multidimensional self: fostering selfhood at the interface of Creative Arts Therapies and neuroscience.

Intriguing explorations at the intersection of the fields of neuroscience and psychology are driven by the quest to understand the neural underpinnings of "the self" and their psychotherapeutic implications. These translational efforts pertain to the unique Creative Arts Therapies (CATs) and the attributes and value of the self-related processes they offer. The self is considered as a multi-layered complex construct, comprising bodily and mental constituents, subjective-objective perspectives, spatial and temporal dimensions. Neuroscience research, mostly functional brain imaging, has proposed cogent models of the constitution, development and experience of the self, elucidating how the multiple dimensions of the self are supported by integrated hierarchical brain processes. The psychotherapeutic use of the art-forms, generating aesthetic experiences and creative processes, touch upon and connect the various layers of self-experience, nurturing the sense of self. The present conceptual analysis will describe and interweave the neural mechanisms and neural network configuration suggested to lie at the core of the ongoing self-experience, its deviations in psychopathology, and implications regarding the psychotherapeutic use of the arts. The well-established, parsimonious and neurobiologically plausible predictive processing account of brain-function will be discussed with regard to selfhood and consciousness. The epistemic affordance of the experiential CATs will further be portrayed, enabling and facilitating the creation of updated self-models of the body in the world. The neuropsychological impact of the relational therapeutic encounter will be delineated, acknowledging the intersubjective brain synchronization through communicative verbal and non-verbal means and aesthetic experiences. The recognition and assimilation of neuroscientific, phenomenological and clinical perspectives concerning the nested dimensionality of the self, ground the relational therapeutic process and the neuroplastic modulations that CATs have to offer on the premise of fostering, shaping and integrating selfhood.

Dance of two brains: Interval subdivision in alternated condition enhances resistance to interference by others

The accomplishment of interpersonal sensorimotor synchronization is a challenging endeavor because it requires the achievement of a balance between accurate temporal control within individuals and smooth communication between them. This raises a critical question: How does the brain comprehend and process the perceptual information of others to guarantee accurate temporal control of action goals in a social context? A joint synchronization - continuation tapping task was conducted together with varying relative phases (0°/180°) and intervals of tempos (400 ms/800 ms/1600 ms) while neural data was collected using fNIRS (functional near-infrared spectroscopy). Individuals showed better behavioral performance and greater interpersonal brain synchronization(IBS) in the left dorsolateral prefrontal cortex at alternated condition (180° relative phase) compared to symmetric condition (0° relative phase), suggesting that the individual can better maintain behavioral performance and show improved IBS when the partner taps between the individual's gaps. Meanwhile, in most levels of alternated condition, IBS is inversely proportional to interference from partner, implying the counteraction of IBS against interference from others. In addition, when the interval of tempo was 1600 ms, behavioral performance showed a sharp decline, accompanied by a decrease in IBS, reflecting that IBS in SMS reflects effective information exchange between individuals rather than ineffective interference with each other. This study provides insight into the mechanisms underlying sensorimotor synchronization between individuals.

Dynamic mechanisms that couple the brain and breathing to the external environment

Brain and breathing activities are closely related. However, the exact neurophysiological mechanisms that couple the brain and breathing to stimuli in the external environment are not yet agreed upon. Our data support that synchronization and dynamic attunement are two key mechanisms that couple local brain activity and breathing to external periodic stimuli. First, we review the existing literature, which provides strong evidence for the synchronization of brain and breathing in terms of coherence, cross-frequency coupling and phase-based entrainment. Second, using EEG and breathing data, we show that both the lungs and localized brain activity at the Cz channel attune the temporal structure of their power spectra to the periodic structure of external auditory inputs. We highlight the role of dynamic attunement in playing a key role in coordinating the tripartite temporal alignment of localized brain activity, breathing and input dynamics across longer timescales like minutes. Overall, this perspective sheds light on potential mechanisms of brain-breathing coupling and its alignment to stimuli in the external environment.

Brain wave modulation and EEG power changes during auditory beats stimulation

Auditory beats stimulation (ABS) has received increased attention for its potential to modulate neural oscillations through a phenomenon described as brain entrainment (i.e synchronization of brain’s electrocortical activity to external stimuli at a specific frequency). Recently, a new form of ABS has emerged, inspired by isochronic tones stimulation (ITd).This study investigated neural oscillatory responses induced by ITd in comparison with formerly well-established ABS protocols, such as gamma-binaural beats (BB) and white noise (WN).We recorded the electroencephalographic brain activity in 28 participants during 4 min of BB, ITd, and WN presentation.Data demonstrated that while both BB and WN enhanced oscillatory power on the EEG gamma band, consistently with the expected brain entrainment effect, ITd yielded greater changes in EEG power (p < 0.001). This was confirmed by time-based analysis, which showed a progressive increase in normalized EEG power within the ITd window compared to BB (p < 0.05). Findings also revealed that ITd elicited acute changes in the alpha band of EEG oscillations, through a progressive decrease in power over time, which was distinctly different from the pattern observed while listening BB and WN. Such dual alpha-gamma effects underline the promising and unique potential of ITd to modulate neural oscillations which selectively differ from BB and WN.This study contributes to the evolution of ABS research, highlighting the promise of ITd for cognitive enhancement and clinical applications.

Unraveling Brain Synchronisation Dynamics by Explainable Neural Networks using EEG Signals: Application to Dyslexia Diagnosis

The electrical activity of the neural processes involved in cognitive functions is captured in EEG signals, allowing the exploration of the integration and coordination of neuronal oscillations across multiple spatiotemporal scales. We have proposed a novel approach that combines the transformation of EEG signal into image sequences, considering cross-frequency phase synchronisation (CFS) dynamics involved in low-level auditory processing, with the development of a two-stage deep learning model for the detection of developmental dyslexia (DD). This deep learning model exploits spatial and temporal information preserved in the image sequences to find discriminative patterns of phase synchronisation over time achieving a balanced accuracy of up to 83%. This result supports the existence of differential brain synchronisation dynamics between typical and dyslexic seven-year-old readers. Furthermore, we have obtained interpretable representations using a novel feature mask to link the most relevant regions during classification with the cognitive processes attributed to normal reading and those corresponding to compensatory mechanisms found in dyslexia.Graphical

The acquired dyad inclination and decreased interpersonal brain communication in the pursuit of collective benefit

People perform better collectively than individually, a phenomenon known as the collective benefit. To pursue the benefit, they may learn from previous behaviors, come to know whose initial opinion should be valued, and develop the inclination to take it as the collective one. Such learning may affect interpersonal brain communication. To test these hypotheses, this study recruited participant dyads to conduct a perceptual task on which they made individual decisions first and then the collective one. The enhanced interpersonal brain synchronization (IBS) between participants was explored when individual decisions were in disagreement vs. agreement. Computational modeling revealed that participant dyads developed the dyad inclination of taking the higher-able participants', not the lower-able ones' decisions as their collective ones. Brain analyses unveiled the enhanced IBS at frontopolar areas, premotor areas, supramarginal gyri, and right temporal-parietal junctions. The premotor IBS correlated negatively with dyad inclination and collective benefit in the absence of correction. The Granger causality analyses further supported the negative relation of dyad inclination with inter-brain communication. This study highlights that dyads learn to weigh individuals' decisions, resulting in dyad inclinations, and explores associated inter-brain communication, offering insights into the dynamics of collective decision-making.

Electroencephalogram synchronization measure as a predictive biomarker of Vagus nerve stimulation response in refractory epilepsy: A retrospective study.

There are currently no established biomarkers for predicting the therapeutic effectiveness of Vagus Nerve Stimulation (VNS). Given that neural desynchronization is a pivotal mechanism underlying VNS action, EEG synchronization measures could potentially serve as predictive biomarkers of VNS response. Notably, an increased brain synchronization in delta band has been observed during sleep-potentially due to an activation of thalamocortical circuitry, and interictal epileptiform discharges are more frequently observed during sleep. Therefore, investigation of EEG synchronization metrics during sleep could provide a valuable insight into the excitatory-inhibitory balance in a pro-epileptogenic state, that could be pathological in patients exhibiting a poor response to VNS. A 19-channel-standard EEG system was used to collect data from 38 individuals with Drug-Resistant Epilepsy (DRE) who were candidates for VNS implantation. An EEG synchronization metric-the Weighted Phase Lag Index (wPLI)-was extracted before VNS implantation and compared between sleep and wakefulness, and between responders (R) and non-responders (NR). In the delta band, a higher wPLI was found during wakefulness compared to sleep in NR only. However, in this band, no synchronization difference in any state was found between R and NR. During sleep and within the alpha band, a negative correlation was found between wPLI and the percentage of seizure reduction after VNS implantation. Overall, our results suggest that patients exhibiting a poor VNS efficacy may present a more pathological thalamocortical circuitry before VNS implantation. EEG synchronization measures could provide interesting insights into the prerequisites for responding to VNS, in order to avoid unnecessary implantations in patients showing a poor therapeutic efficacy.

Resting-State Network Functional Connectivity Analysis: A Multimodal Imaging and Computational Modeling Approach

Functional connectivity is referred to as the temporal interaction between different brain regions that are spatially distant from each other. It is commonly examined during resting states by classifying resting-state functional connectivity (rs-FC) patterns and their associated synchronized activity to understand the underlying neural mechanisms that support cognitive processes. With the advancement of cutting-edge neuronal systems, multimodal imaging, and computational advances have served as promising tools for rs-FC studies. Despite having reviewed resting-state networks and their influence on a range of health anomalies in the existing literature, there nevertheless remains a lack of reviews that delve into diverse imaging modalities and computational modeling approaches for rs-FC analysis. Therefore, this systematic review aims to provide an understanding of these technologies that analyze the resting-state network functional connectivity and their correlation to cognitive functions. Through a systematic approach to analyzing studies, the most frequently employed modality was functional magnetic resonance imaging (fMRI) due to its high spatial resolution. Key findings demonstrated that higher functional connectivity levels are often linked to greater Exin ratios, which subsequently affect large-scale functional brain synchronization. Across various computational models, a non-parametric classifier has shown promise for rs-FC analysis in various contexts due to its ability to handle multiple EEG features. Moreover, the multivariate model is identified to have superior performance with a predictive area under the curve (AUC) of ~0.77. Overall, the present study underscores the vitality of using imaging and computational tools in elucidating the intricacies of rs-FC and its effects on individual cognition.

Increased Thalamic Connectivity in Juvenile Myoclonic Epilepsy Based on Electroencephalography Source-Level Analysis.

Background: This study investigated alterations in the intrinsic thalamic network of patients with juvenile myoclonic epilepsy (JME) based on an electroencephalography (EEG) source-level analysis. Materials and Methods: We enrolled patients newly diagnosed with JME as well as healthy controls. The assessments were conducted in the resting state. We computed sources based on the scalp electrical potentials using a minimum-norm imaging method and a standardized, low-resolution, brain electromagnetic tomography approach. To create a functional connectivity matrix, we used the Talairach atlas to define thalamic nodes and applied the coherence method to measure brain synchronization as edges. We then calculated the intrinsic thalamic network using graph theory. We compared the intrinsic thalamic network of patients with JME with those of healthy controls. Results: This study included 67 patients with JME and 66 healthy controls. EEG source-level analysis revealed significant differences in the intrinsic thalamic networks between patients with JME and healthy controls. The measures of functional connectivity (radius, diameter, and characteristic path length) were significantly lower in patients with JME than in healthy controls (radius: 2.769 vs. 3.544, p = 0.015; diameter: 4.464 vs. 5.443, p = 0.024; and characteristic path length: 2.248 vs. 2.616, p = 0.046). Conclusions: We demonstrated alterations in the intrinsic thalamic network in patients with JME compared with those in healthy controls based on the EEG source-level analysis. These findings indicated increased thalamic connectivity in the JME group. These intrinsic thalamic network changes may be related to the pathophysiology of JME.

Deep brain stimulation of the central thalamus restores arousal and motivation in a zolpidem-responsive patient with akinetic mutism after severe brain injury.

After severe brain injury, zolpidem is known to cause spectacular, often short-lived, restorations of brain functions in a small subgroup of patients. Previously, we showed that these zolpidem-induced neurological recoveries can be paralleled by significant changes in functional connectivity throughout the brain. Deep brain stimulation (DBS) is a neurosurgical intervention known to modulate functional connectivity in a wide variety of neurological disorders. In this study, we used DBS to restore arousal and motivation in a zolpidem-responsive patient with severe brain injury and a concomitant disorder of diminished motivation, more than 10years after surviving hypoxic ischemia. We found that DBS of the central thalamus, targeted at the centromedian-parafascicular complex, immediately restored arousal and was able to transition the patient from a state of deep sleep to full wakefulness. Moreover, DBS was associated with temporary restoration of communication and ability to walk and eat in an otherwise wheelchair-bound and mute patient. With the use of magnetoencephalography (MEG), we revealed that DBS was generally associated with a marked decrease in aberrantly high levels of functional connectivity throughout the brain, mimicking the effects of zolpidem. These results imply that 'pathological hyperconnectivity' after severe brain injury can be associated with reduced arousal and behavioral performance and that DBS is able to modulate connectivity towards a 'healthier baseline' with lower synchronization, and, can restore functional brain networks long after severe brain injury. The presence of hyperconnectivity after brain injury may be a possible future marker for a patient's responsiveness for restorative interventions, such as DBS, and suggests that lower degrees of overall brain synchronization may be conducive to cognition and behavioral responsiveness.

Having a chat and then watching a movie: how social interaction synchronises our brains during co-watching.

How does co-presence change our neural experience of the world? Can a conversation change how we synchronise with our partner during later events? Using fNIRS hyperscanning, we measured brain activity from 27 pairs of familiar adults simultaneously over frontal, temporal and parietal regions bilaterally, as they co-watched two different episodes of a short cartoon. In-between the two episodes, each pair engaged in a face-to-face conversation on topics unrelated to the cartoon episodes. Brain synchrony was calculated using wavelet transform coherence and computed separately for real pairs and shuffled pseudo) pairs. Findings reveal that real pairs showed increased brain synchrony over right Dorso-Lateral Pre-Frontal cortex (DLPFC) and right Superior Parietal Lobe (SPL), compared to pseudo pairs (who had never seen each other and watched the same movie at different times; uncorrected for multiple comparisons). In addition, co-watching after a conversation was associated with greater synchrony over right TPJ compared to co-watching before a conversation, and this effect was significantly higher in real pairs (who engaged in conversation with each other) compared to pseudo pairs (who had a conversation with someone else; uncorrected for multiple comparisons). The present study has shed the light on the role of social interaction in modulating brain synchrony across people not just during social interaction, but even for subsequent non-social activities. These results have implications in the growing domain of naturalistic neuroimaging and interactive neuroscience.

Romantic relationships attenuated competition between lovers: evidence from brain synchronization.

Competition is an essential component of social interaction and is influenced by interpersonal relationships. This study is based on social exchange theory and explores the relationship between brain synchronization and competition in the binary system of romantic relationships through electroencephalogram hyperscanning technology. The results found that females had a greater win rate in the romantic and friend groups. During the early stage (0-200ms), when the competitive target appeared, the stranger group exhibited greater interbrain synchronicity in the Alpha frequency band. However, during the later stage (600-800ms), the romantic group showed higher Alpha band interbrain synchrony when the competitive target appeared. Significant interbrain synchronizations were observed in the Theta frequency band of the stranger and friend groups at 400-600ms and 800-1000ms. Moreover, these interbrain synchronizations were significantly positively correlated with the winning rates of females in the competition. These findings suggest a close relationship between interpersonal coordination and interbrain synchronization. Furthermore, romantic relationships reduce participants' willingness to compete, affecting their attention regulation, emotional processing, and goal orientation, thus influencing competition. This study investigated the impact of romantic relationships on competition, providing a theoretical foundation for promoting the positive and healthy development of romantic relationships.

The absence of one's intimate partner promotes dyadic competition through enhanced interbrain synchronization between opponents.

Competition is a common occurrence in life, but the influence of intimate relationships on people's competitiveness remains unknown. Grounded in Darwin's theory of sexual selection, this study utilized EEG hyperscanning technology to investigate the influence of the presence of romantic partners and the gender of competitors on the interbrain synchronization of female individuals during competitive contexts. The research results showed that in competitive interactions, there was a significant increase in Theta and Alpha frequency band activity between females and their competitors. Interbrain synchronization was strongest when their partners were not nearby and females competed with same gender competitors. The research results indicate that intimate companionship has an impact on the early alertness and late cognitive execution mechanisms of female individuals in competition, and due to intimate relationships, females pay more attention to same-gender competitors. This study demonstrates that the presence of intimate partners can affect a female's competitive state and brain synchronization with opponents of different genders, improving the theoretical explanation of intimate relationships and competitive interactions.

Modeling Temporal Lobe Epilepsy during Music Large-Scale Form Perception Using the Impulse Pattern Formulation (IPF) Brain Model

Musical large-scale form is investigated using an electronic dance music piece fed into a Finite-Difference Time-Domain physical model of the cochlea, which again is input into an Impulse Pattern Formulation (IPF) Brain model. In previous studies, experimental EEG data showed an enhanced correlation between brain synchronization and the musical piece’s amplitude and fractal correlation dimension, representing musical tension and expectancy time points within the large-scale form of musical pieces. This is also in good agreement with a FitzHugh–Nagumo oscillator model.However, this model cannot display temporal developments in large-scale forms. The IPF Brain model shows a high correlation between cochlea input and brain synchronization at the gamma band range around 50 Hz, and also a strong negative correlation with low frequencies, associated with musical rhythm, during time frames with low cochlea input amplitudes. Such a high synchronization corresponds to temporal lobe epilepsy, often associated with creativity or spirituality. Therefore, the IPF Brain model results suggest that these conscious states occur at times of low external input at low frequencies, where isochronous musical rhythms are present.

Cortical miR-709 links glutamatergic signaling to NREM sleep EEG slow waves in an activity-dependent manner.

MicroRNAs (miRNAs) are key post-transcriptional regulators of gene expression that have been implicated in a plethora of neuronal processes. Nevertheless, their role in regulating brain activity in the context of sleep has so far received little attention. To test their involvement, we deleted mature miRNAs in post-mitotic neurons at two developmental ages, i.e., in early adulthood using conditional Dicer knockout (cKO) mice and in adult mice using an inducible conditional Dicer cKO (icKO) line. In both models, electroencephalographic (EEG) activity was affected and the response to sleep deprivation (SD) altered; while the rapid-eye-movement sleep (REMS) rebound was compromised in both, the increase in EEG delta (1 to 4 Hz) power during non-REMS (NREMS) was smaller in cKO mice and larger in icKO mice compared to controls. We subsequently investigated the effects of SD on the forebrain miRNA transcriptome and found that the expression of 48 miRNAs was affected, and in particular that of the activity-dependent miR-709. In vivo inhibition of miR-709 in the brain increased EEG power during NREMS in the slow-delta (0.75 to 1.75 Hz) range, particularly after periods of prolonged wakefulness. Transcriptome analysis of primary cortical neurons in vitro revealed that miR-709 regulates genes involved in glutamatergic neurotransmission. A subset of these genes was also affected in the cortices of sleep-deprived, miR-709-inhibited mice. Our data implicate miRNAs in the regulation of EEG activity and indicate that miR-709 links neuronal activity during wakefulness to brain synchrony during sleep through the regulation of glutamatergic signaling.

The Effects of Distancing Design Collaboration Necessitated by COVID-19 on Brain Synchrony in Teams Compared to Co-Located Design Collaboration: A Preliminary Study.

Due to the widespread involvement of distributed collaboration triggered by COVID-19, it has become a new trend that has continued into the post-pandemic era. This study investigated collective performance within two collaborative environments (co-located and distancing settings) by assessing inter-brain synchrony patterns (IBS) among design collaborators using functional near-infrared spectroscopy. The preliminary study was conducted with three dyads who possessed 2-3 years of professional product design experience. Each dyad completed two designated design tasks in distinct settings. In the distributed condition, participants interacted through video conferencing in which they were allowed to communicate by verbalization and sketching using a shared digital whiteboard. To prevent the influences of different sketching tools on design outputs, we employed digital sketching for both environments. The interactions between collaborators were identified in three behaviors: verbal only, sketch only, and mixed communication (verbal and sketch). The consequences revealed a higher level of IBS when mixed communication took place in distributed conditions than in co-located conditions. Comparably, the occurrence of IBS increased when participants solely utilized sketching as the interaction approach within the co-located setting. A mixed communication method combining verbalization and sketching might lead to more coordinated cognitive processes when in physical isolation. Design collaborators are inclined to adjust their interaction behaviors in order to adapt to different design environments, strengthen the exchange of ideas, and construct design consensus. Overall, the present paper discussed the performance of virtual collaborative design based on a neurocognitive perspective, contributing valuable insights for the future intervention design that promotes effective virtual teamwork.

Altered Sleep Oscillations as Neurophysiological Biomarkers of Schizophrenia.

Sleep spindles and slow waves are the two main oscillatory activities occurring during nonrapid eye movement (NREM) sleep. Here, we will first describe the electrophysiological characteristics of these sleep oscillations along with the neurophysiological and molecular mechanisms underlying their generation and synchronization in the healthy brain. We will then review the extant evidence of deficits in sleep spindles and, to a lesser extent, slow waves, including in slow wave-spindle coupling, in patients with Schizophrenia (SCZ) across the course of the disorder, from at-risk to chronic stages. Next, we will discuss how these sleep oscillatory deficits point to defects in neuronal circuits within the thalamocortical network as well as to alterations in molecular neurotransmission implicating the GABAergic and glutamatergic systems in SCZ. Finally, after explaining how spindle and slow waves may represent neurophysiological biomarkers with predictive, diagnostic, and prognostic potential, we will present novel pharmacological and neuromodulatory interventions aimed at restoring sleep oscillatory deficits in SCZ, which in turn may serve as target engagement biomarkers to ameliorate the clinical symptoms and the quality of life of individuals affected by this devastating brain disorder.

The architecture of functional brain network modulated by driving under train running noise exposure.

A noisy environment can considerably impact drivers' attention and fatigue, endangering driving safety. Consequently, this study designed a simulated driving experimental scenario to analyse the effects of noise generated during urban rail transit train operation on drivers' functional brain networks. The experiment recruited 16 participants, and the simulated driving scenario was conducted at noise levels of 50, 60, 70, and 80 dB. Functional connectivity between all electrode pairs across various frequency bands was evaluated using the weighted phase lag index (WPLI), and a brain network based on this was constructed. Graph theoretic analysis employed network global efficiency, degree, and clustering coefficient as metrics. Significant increases in the WPLI values of theta and alpha frequency bands were observed in high noise environments (70 dB, 80 dB), as well as enhanced brain synchronisation. Furthermore, concerning the topological metrics of brain networks, it was observed that the global efficiency of brain networks in theta and alpha frequency ranges, as well as the node degree and clustering coefficients, experienced substantial growth in high noise environments (70 dB, 80 dB) as opposed to 50 dB and 60 dB. This finding indicates that high-noise environments impact the reorganisation of functional brain networks, leading to a preference for network structures with improved global efficiency. Such findings may improve our understanding of the neural mechanisms of driving under noise exposure, and thus potentially reduce road accidents to some extent.

Connectivity changes in two-channel prefrontal ERP associated with early cognitive decline in the elderly population: beta band responses to the auditory oddball stimuli.

This study utilized recent advancements in electroencephalography (EEG) technology that enable the measurement of prefrontal event-related potentials (ERPs) to facilitate the early detection of mild cognitive impairment (MCI). We investigated two-channel prefrontal ERP signals obtained from a large cohort of elderly participants and compare among cognitively normal (CN), subjective cognitive decline (SCD), amnestic MCI (aMCI), and nonamnestic MCI (naMCI) groups. Signal processing and ERP component analyses, specifically adapted for two-channel prefrontal ERP signals evoked by the auditory oddball task, were performed on a total of 1,754 elderly participants. Connectivity analyses were conducted to assess brain synchronization, especially in the beta band involving the phase locking value (PLV) and coherence (COH). Time-frequency, time-trial, grand average, and further statistical analyses of the standard and target epochs were also conducted to explore differences among the cognition groups. The MCI group's response to target stimuli was characterized by greater response time variability (p < 0.001) and greater variability in the P300 latency (p < 0.05), leading to less consistent responses than those of the healthy control (HC) group (CN+SCD subgroups). In the connectivity analyses of PLV and COH waveforms, significant differences were observed, indicating a loss of synchronization in the beta band in response to standard stimuli in the MCI group. In addition, the absence of event-related desynchronization (ERD) indicated that information processing related to readiness and task performance in the beta band was not efficient in the MCI group. Furthermore, the observed decline in the P200 amplitude as the standard trials progressed suggests the impaired attention and inhibitory processes in the MCI group compared to the HC group. The aMCI subgroup showed high variability in COH values, while the naMCI subgroup showed impairments in their overall behavioral performance. These findings highlight the variability and connectivity measures can be used as markers of early cognitive decline; such measures can be assessed with simple and fast two-channel prefrontal ERP signals evoked by both standard and target stimuli. Our study provides deeper insight of cognitive impairment and the potential use of the prefrontal ERP connectivity measures to assess early cognitive decline.