Early Caregiver Predictability Shapes Neural Indices of Statistical Learning Later in Infancy.

Caregivers play an outsized role in shaping early life experiences and development, but we often lack mechanistic insight into how exactly caregiver behavior scaffolds the neurodevelopment of specific learning processes. Here, we capitalized on the fact that caregivers differ in how predictable their behavior is to ask if infants' early environmental input shapes their brains' later ability to learn about predictable information. As part of an ongoing longitudinal study in South Africa, we recorded naturalistic, dyadic interactions between 103 (46 females and 57 males) infants and their primary caregivers at 3-6 months of age, from which we calculated the predictability of caregivers' behavior, following caregiver vocalization and overall. When the same infants were 6-12-months-old they participated in an auditory statistical learning task during EEG. We found evidence of learning-related change in infants' neural responses to predictable information during the statistical learning task. The magnitude of statistical learning-related change in infants' EEG responses was associated with the predictability of their caregiver's vocalizations several months earlier, such that infants with more predictable caregiver vocalization patterns showed more evidence of statistical learning later in the first year of life. These results suggest that early experiences with caregiver predictability influence learning, providing support for the hypothesis that the neurodevelopment of core learning and memory systems is closely tied to infants' experiences during key developmental windows.

Classification of cyclic alternating patterns of sleep using EEG signals.

Cyclic alternating patterns (CAP) occur in electroencephalogram (EEG) signals during non-rapid eye movement sleep. The analysis of CAP can offer insights into various sleep disorders. The first step is the identification of phases A and B for the CAP cycles. In this work, we develop an easy-to-implement accurate system to differentiate between CAP A and CAP B. Small segments of the EEG signal are processed using Gaussian filters to obtain sub-band components. Features are extracted using some statistical characteristics of these signal components. Minimum redundancy maximum relevance test is employed to identify the more significant features. Three different machine learning classifiers are considered and their performance is compared. The results are analyzed for both the balanced and unbalanced datasets. The k-nearest neighbour (kNN) classifier achieves 79.14 % accuracy and F-1 score of 79.24 % for the balanced dataset. The proposed method outperforms the existing methods for CAP classification. It is easy-to-implement and can be considered as a candidate for real-time deployment.

Is frontal EEG gamma power a neural correlate of language in toddlerhood? An examination of late talking and expressive language ability.

Few studies have examined neural correlates of late talking in toddlers, which could aid in understanding etiology and improving diagnosis of developmental language disorder (DLD). Greater frontal gamma activity has been linked to better language skills, but findings vary by risk for developmental disorders, and this has not been investigated in late talkers. This study examined whether frontal gamma power (30-50 Hz), from baseline-state electroencephalography (EEG), was related to DLD risk (categorical late talking status) and a continuous measure of expressive language in n = 124 toddlers. Frontal gamma power was significantly associated with late talker status when controlling for demographic factors and concurrent receptive language (ß = 1.96, McFadden's Pseudo R2 = 0.21). Demographic factors and receptive language did not significantly moderate the association between frontal gamma power and late talker status. A continuous measure of expressive language ability was not significantly associated with gamma (r = -0.07). Findings suggest that frontal gamma power may be useful in discriminating between groups of children that differ in DLD risk, but not for expressive language along a continuous spectrum of ability.

Improving working memory by electrical stimulation and cross-frequency coupling.

Working memory (WM) is essential for the temporary storage and processing of information required for complex cognitive tasks and relies on neuronal theta and gamma oscillations. Given the limited capacity of WM, researchers have investigated various methods to improve it, including transcranial alternating current stimulation (tACS), which modulates brain activity at specific frequencies. One particularly promising approach is theta-gamma peak-coupled-tACS (TGCp-tACS), which simulates the natural interaction between theta and gamma oscillations that occurs during cognitive control in the brain. The aim of this study was to improve WM in healthy young adults with TGCp-tACS, focusing on both behavioral and neurophysiological outcomes. Thirty-one participants completed five WM tasks under both sham and verum stimulation conditions. Electroencephalography (EEG) recordings before and after stimulation showed that TGCp-tACS increased power spectral density (PSD) in the high-gamma region at the stimulation site, while PSD decreased in the theta and delta regions throughout the cortex. From a behavioral perspective, although no significant changes were observed in most tasks, there was a significant improvement in accuracy in the 14-item Sternberg task, indicating an improvement in phonological WM. In conclusion, TGCp-tACS has the potential to promote and improve the phonological component of WM. To fully realize the cognitive benefits, further research is needed to refine the stimulation parameters and account for individual differences, such as baseline cognitive status and hormonal factors.

A historical perspective on the neurobiology of speech and language: from the 19th century to the present.

In this essay, we review 19th century conceptions on the neurobiology of speech and language, including the pioneer work of Franz Gall, Jean-Baptiste Bouillaud, Simon Alexandre Ernest Aubertin, Marc Dax, Paul Broca, and Carl Wernicke. We examine how these early investigations, anchored in the study of neurological disorders, have broadened their scope via neuropsychological and psycholinguistic theories and models. Then, we discuss how major technological advances have led to an important paradigm shift, through which the study of the brain slowly detached from the study of disease to become the study of individuals of all ages, with or without brain pathology or language disorders. The profusion of neuroimaging studies that were conducted in the past four decades, inquiring into various aspects of language have complemented-and often challenged-classical views on language production. Our understanding of the "motor speech center," for instance, has been entirely transformed. The notion of cerebral dominance has also been revisited. We end this paper by discussing the challenges and controversies of 21st century neurobiology of speech and language as well as modern views of the neural architecture supporting speech and language functions.

Delayed modulation of alpha band activity increases response inhibition deficits in adolescents with AD(H)D.

Deficiencies in inhibitory control are one of the hallmarks of attention-deficit-(hyperactivity) disorder (AD(H)D). Response inhibition demands can become increased through additional conflicts, namely when already integrated representations of perception-action associations have to be updated. Yet, the neural mechanisms of how such conflicts worsen response inhibition in AD(H)D are unknown, but, if identified, could help to better understand the complex nature of AD(H)D-associated impulsivity. We investigated both behavioral performance and EEG activity in the theta and alpha band of adolescents (10-18 years of age) with AD(H)D (n = 28) compared to neurotypical (NT) controls (n = 33) in a conflict-modulated Go/Nogo paradigm. We used multivariate pattern analysis (MVPA) and EEG-beamforming to examine how changes in representational content are coded by oscillatory activity and to delineate the cortical structures involved in it. The presented behavioral and neurophysiological data show that adolescents with AD(H)D are more strongly affected by increased response inhibition demands through additional conflicts than NT controls. Precisely, AD(H)D participants showed higher false alarm rates than NT controls in both, non-overlapping and overlapping Nogo trials, but performed even worse in the latter. This is likely due to an inefficient updating of representations related to delayed modulations of alpha band activity in the ventral stream and orbitofrontal regions. Theta band activity is also modulated by conflict but was not differentially affected in the two groups. By this, the present study provides novel insights into underlying neurophysiological mechanisms of the complex nature of response inhibition deficits in adolescents with AD(H)D, stressing the importance to examine the interplay of theta and alpha band activity more closely to better understand inhibitory control deficits in AD(H)D.

Optogenetic targeting of cortical astrocytes selectively improves NREM sleep in an Alzheimer's disease mouse model.

Alzheimer's disease (AD) is a progressive neurodegenerative condition marked by memory impairments and distinct histopathological features such as amyloid-beta (Aß) accumulations. Alzheimer's patients experience sleep disturbances at early stages of the disease. APPswe/PS1dE9 (APP) mice exhibit sleep disruptions, including reductions in non-rapid eye movement (NREM) sleep, that contribute to their disease progression. In addition, astrocytic calcium transients associated with a sleep-dependent brain rhythm, slow oscillations prevalent during NREM sleep, are disrupted in APP mice. However, at present it is unclear whether restoration of circuit function by targeting astrocytic activity could improve sleep in APP mice. To that end, APP mice expressing channelrhodopsin-2 (ChR2) targeted to astrocytes underwent optogenetic stimulation at the slow oscillation frequency. Optogenetic stimulation of astrocytes significantly increased NREM sleep duration but not duration of rapid eye movement (REM) sleep. Optogenetic treatment increased delta power and reduced sleep fragmentation in APP mice. Thus, optogenetic activation of astrocytes increased sleep quantity and improved sleep quality in an AD mouse model. Astrocytic activity provides a novel therapeutic avenue to pursue for enhancing sleep and slowing AD progression.

Generalized spike-waves in idiopathic generalized epilepsies: Does their frequency matter?

OBJECTIVES: We hypothesized that the frequency (in Hertz) of generalized spike-waves (GSWs) in patients with idiopathic generalized epilepsy (IGE) has associations with the syndromic diagnosis as well as with the prognosis of patients (their response to medical treatment). METHODS: This was a retrospective study of a prospectively developed database. All patients with a diagnosis of IGE were studied at the epilepsy center at Shiraz University of Medical Sciences, Shiraz, Iran, from 2008 until 2022. Patients were classified into four IGE syndromes: childhood absence epilepsy; juvenile absence epilepsy; juvenile myoclonic epilepsy; and generalized tonic-clonic seizures alone. RESULTS: Five hundred and eighty-three patients were studied. GSWs were commonly observed in all four syndromes of IGE. Frequency of GSW (in Hertz) did not have a significant association with the syndromic diagnosis of the patients (p = .179). The presence of GSW did not have a significant association with the seizure outcome (becoming seizure free or not) of the patients (p = .416). Frequency of GSW did not have a significant association with the seizure outcome of the patients either (p = .574). CONCLUSION: GSWs are the hallmark electroencephalographic footprints of idiopathic generalized epilepsies; however, neither their presence nor their frequency has practical associations with the syndromic diagnosis of IGEs or their outcome (response to treatment).

Brains in sync, friends in empathy: interbrain neural mechanisms underlying the impact of interpersonal closeness on mutual empathy.

Many everyday empathetic experiences arise within our social interactions and depend significantly on interpersonal closeness. However, the interbrain processes underlying social-oriented empathy by interpersonal closeness remain unclear. To address this gap, we conducted a dyadic social judgement task with dyads of friends and strangers, where targets received social evaluative feedback and empathizers observed the scenario in different experimental trials. Results showed that dyads of friends exhibited greater affect sharing than strangers when witnessing their partners being accepted or rejected. This was supported by the more pronounced event-related potential similarity in friends during the 340-840 ms post-feedback window, mediating the link between interpersonal closeness and affect sharing. Furthermore, witnessing emotional feedback elicited greater interbrain neural synchronization of brain α-oscillation between the empathizer's left prefrontal cortex and the target's left temporoparietal junction in dyads of friends compared with those of strangers. This empathy-related synchronization was associated with mutual affect sharing within dyads of friends but not within dyads of strangers. Our findings highlight the sensitivity of empathy to interpersonal closeness, which links to sustained attention and detailed evaluation in social scenarios, along with functional communication between brain regions for mentalizing and emotional regulation. These insights have therapeutic potential for improving social functioning and relationship satisfaction.

Human in the collaborative loop: a strategy for integrating human activity recognition and non-invasive brain-machine interfaces to control collaborative robots.

Human activity recognition (HAR) and brain-machine interface (BMI) are two emerging technologies that can enhance human-robot collaboration (HRC) in domains such as industry or healthcare. HAR uses sensors or cameras to capture and analyze the movements and actions of humans, while BMI uses human brain signals to decode action intentions. Both technologies face challenges impacting accuracy, reliability, and usability. In this article, we review the state-of-the-art techniques and methods for HAR and BMI and highlight their strengths and limitations. We then propose a hybrid framework that fuses HAR and BMI data, which can integrate the complementary information from the brain and body motion signals and improve the performance of human state decoding. We also discuss our hybrid method's potential benefits and implications for HRC.

Advances and challenges in neuroimaging-based pain biomarkers.

Identifying neural biomarkers of pain has long been a central theme in pain neuroscience. Here, we review the state-of-the-art candidates for neural biomarkers of acute and chronic pain. We classify these potential neural biomarkers into five categories based on the nature of their target variables, including neural biomarkers of (1) within-individual perception, (2) between-individual sensitivity, and (3) discriminability for acute pain, as well as (4) assessment and (5) prospective neural biomarkers for chronic pain. For each category, we provide a synthesized review of candidate biomarkers developed using neuroimaging techniques including functional magnetic resonance imaging (fMRI), structural magnetic resonance imaging (sMRI), and electroencephalography (EEG). We also discuss the conceptual and practical challenges in developing neural biomarkers of pain. Addressing these challenges, optimal biomarkers of pain can be developed to deepen our understanding of how the brain represents pain and ultimately help alleviate patients' suffering and improve their well-being.

Involvement of muscarinic acetylcholine receptor-mediated cholinergic neurotransmission in TMS-EEG responses.

The combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) is emerging as a valuable tool for investigating brain functions in health and disease. However, the detailed neural mechanisms underlying TMS-EEG responses, including TMS-evoked EEG potentials (TEPs) and TMS-induced EEG oscillations (TIOs), remain largely unknown. Combining TMS-EEG with pharmacological interventions provides a unique opportunity to elucidate the roles of specific receptor-mediated neurotransmissions in these responses. Here, we investigated the involvement of muscarinic acetylcholine receptor (mAChR)-mediated cholinergic neurotransmission in TMS-EEG responses by evaluating the effects of mAChR antagonists on TEPs and TIOs in twenty-four healthy participants using a randomized, placebo-controlled crossover design. TEPs and TIOs were measured before and after administering a single oral dose of scopolamine (a non-selective mAChR antagonist), biperiden (an M1 mAChR antagonist), or placebo, with TMS targeting the left medial prefrontal cortex (mPFC), angular gyrus (AG), and supplementary motor area (SMA). The results indicated that mAChR-mediated cholinergic neurotransmission played a role in TEPs, but not TIOs, in a target-specific manner. Specifically, scopolamine significantly increased the amplitude of a local TEP component between approximately 40 and 63 ms post-stimulus when TMS was applied to the SMA, but not the mPFC or AG. Biperiden produced a similar but less pronounced effect. Importantly, the effects of these mAChR antagonists on TEPs were independent of those on sensory-evoked EEG potentials caused by TMS-associated sensory stimulation. These findings expand our understanding of TMS-EEG physiology, providing insights for its application in physiological and clinical research.

An Empirical Study on the Effect of Blended Scents in Driving Environments From a Neuro-Cognitive Perspective.

BACKGROUND: An effective method that is easy to implement and widely applicable for improving driving performance and reducing driving risks remains a challenge. Although fragrances are widely used in daily driving, there is a gap between empirical research on everyday blended fragrances and functional fragrances clinical reports. In this study, a deliberately chosen blend of scent without overtly stimulating or functional proven evidence was tested for its potential to enhance performance in a driving environment. METHOD: Thirty qualified young drivers were recruited to participate in the experiment. They were asked to watch a 15-min first-person perspective driving video to simulate a driving environment and then complete questionnaires and three sets of behavioral experiments while their brain activity was monitored by EEG. RESULT: Participants in the scented environment exhibited statistically significant advantages in two cognitive tasks during behavioral measures. These findings were effectively supported by the EEG data, showing that beta waves exhibited more activity in the occipital and prefrontal cortex, enhanced theta waves were observed in the prefrontal cortex, and the TAB index characterizing driving fatigue was suppressed in the prefrontal cortex. CONCLUSION: This empirical evidence highlights the potential of pleasant, natural, and blended scents in enhancing driving performance, suggesting that promoting the aromatherapy while driving as an easily applicable approach in daily life seems justified and expands the application of aromatherapy in daily life.

Pre-anesthetic brain network metrics as predictors of individual propofol sensitivity.

BACKGROUND AND OBJECTIVE: Numerous factors, including demographic characteristics, have been implicated in modulating individual sensitivity to propofol; however, substantial inter-individual differences persist even after accounting for these factors. This study thus aimed to explore whether pre-anesthesia brain functional network metrics correlate with an individual's sensitivity to propofol. METHODS: A total of 54 subjects, including 30 patients and 24 healthy volunteers, were enrolled. Propofol was administered via a target-controlled infusion device, and anesthesia depth was monitored using a bispectral index monitor. Sensitivity to propofol was quantified using the induction time, measured from infusion onset to the bispectral index, which reached 60. Brain functional network metrics indicative of functional integration and segregation, centrality, and network resilience were computed from pre-anesthetic 60-channel EEG recordings. Linear regression analysis and machine learning predictive models were applied to evaluate the contribution of pre-anesthesia network metrics in predicting individual sensitivity to propofol. RESULTS: Our analysis results revealed that subjects could be categorized into high- or low-sensitivity groups based on their induction time. Individuals with low sensitivity exhibited a greater network degree, clustering coefficient, global efficiency, and betweenness centrality, along with reduced modularity and assortativity coefficient in the alpha band. Furthermore, alpha band network metrics were significantly correlated with individual induction time. Leveraging these network metrics as features enabled the classification of individuals into high- or low-sensitivity groups with an accuracy of 94%. CONCLUSIONS: Using a clinically relevant endpoint that signifies the level of anesthesia suitable for surgical procedures, this study underscored the robust correlation between pre-anesthesia alpha-band network metrics and individual sensitivity to propofol in a cohort that included both patients and healthy volunteers. Our findings offer preliminary insights into the potential utility of pre-anesthetic brain status assessment to predict propofol sensitivity on an individual basis, which may help to develop a more accurate personalized anesthesia plan.

Inhibitory deficits in Klinefelter syndrome are secondary to deficits in the auditory and motor domain.

Deficits in several cognitive domains are prevalent in men with Klinefelter Syndrome (KS). Verbal deficits are among the most characteristic cognitive impairments of KS, yet other cognitive domains also exhibit deficits. Executive functions, especially working memory capacity and inhibitory control, are frequently affected as well. A common limitation of previous studies addressing potential deficits in inhibitory control is their potential conflation with language-related capabilities, as for example is the case with the Stroop task. Importantly, none of the prior studies utilized the best-accepted approach to study inhibition, namely the Stop Signal Task (SST). This study therefore tested for deficits in inhibitory control in individuals with KS and controls (HC) using a version of the SST with non-semantic auditory stimuli. In addition to the classic behavioral performance measures (e.g., the go reaction time, stopping accuracy, or stop signal reaction time), we also derived parameters of inhibition and attention from electromyography (EMG), electroencephalography (EEG), and Bayesian modeling. Men with KS exhibited prolonged stopping latencies (i.e., stop signal reaction times) and reduced stopping accuracies. Yet, whereas these model-based indices were indicative of attenuated inhibitory control, neither event-related brain potentials nor an EMG-measure of the stopping latency confirmed such deficits. Behavioral and EEG indices, however, provided evidence for deficits in motor response preparation and generation, as well as the early processing of auditory stimuli. In sum, the overall pattern of results does not support the existence of inhibitory deficits in KS per se, but rather suggests that behavioral indices of impaired inhibition may result from early low-level deficits in the auditory and motor domains, as well as a differential weighting in the processing of different aspects of the task.

Orthographic character complexity modulates dynamic neural activity in skilled handwriting.

Handwriting is an outstanding case of a highly complex and efficient fine motor skill. However, little is known about its neural underpinnings during continuous handwriting production. In the present study, we examined the effects of orthographic character complexity (i.e. the stroke number of a Chinese character) on both neural and behavioural activities during an EEG-based naturalistic fluent sentence-handwriting task from 102 adult Chinese native speakers. For each written character, the interval between finishing the preceding character and its onset (inter-character interval) as well as the amplitudes of the onset-synchronized event-related potential (ERP) in pre- and post-onset time windows was defined as dependent variables. The effects of character complexity and other confounding factors were analysed with linear mixed models. Character complexity increased the inter-character interval and significantly affected ERP amplitudes in both pre- and post-onset time windows. The ERP pattern in the pre-event time window exhibited a dipole-like activation in the left motor cortex, and its amplitude increased with character complexity in line with the documented relationship between the lateralized readiness potential and motor complexity. This study demonstrates the feasibility of studying neurocognitive processes in complex naturalistic motor tasks and extends our knowledge about the dynamic pattern of handwriting-related neural activities.

A Comparison of Treatment Practices for Newborn Seizure Management Across Level II and III Neonatal Intensive Care Units in the United States.

BACKGROUND: Neonatal seizures (NS) represent an important clinical manifestation among critically ill infants and are often the first sign of underlying brain injury. Early recognition and treatment are essential to reduce morbidity and mortality. The present study investigated the NS management and treatment approaches employed by level II/III neonatal intensive care units (NICUs) across the United States to identify areas of consensus and variability. METHODS: Personnel associated with level II/III NICUs were directly surveyed with an electronic questionnaire. Access to neurology specialists, on-site electroencephalography (EEG) monitoring, and use of antiseizure medications was directly queried. A total of 51 NICUs participated in this survey. RESULTS: Twenty-five percent of the surveyed NICUs reported having an established clinical practice pathway available for treating NS. Twenty-four percent endorsed having written guidelines that provided a formal definition for the concept of "neonatal seizures." Although the majority of NICUs reported having phenobarbital available for rapid seizure management, most NICUs lacked access to additional antiseizure medications for treatment escalation. Twenty-four percent of the surveyed NICUs had no access to EEG monitoring available to them on-site. Daytime and overnight access to neurology consultants was limited and variable. CONCLUSIONS: Findings were consistent with a lack of equitable access for NS treatment. Areas of potential improvement include development and implementation of a protocol for rapidly treating NS that emphasizes enhanced access to EEG and rapid neurology consultation, acknowledging and improving upon resource limitations. These developments may eventually provide earlier detection, evaluation, and treatment of seizures in newborns, contributing to improved long-term outcomes.

Low-Cost Classroom and Laboratory Exercises for Investigating Both Wave and Event-Related Electroencephalogram Potentials.

Electroencephalography (EEG) has given rise to a myriad of new discoveries over the last 90 years. EEG is a noninvasive technique that has revealed insights into the spatial and temporal processing of brain activity over many neuroscience disciplines, including sensory, motor, sleep, and memory formation. Most undergraduate students, however, lack laboratory access to EEG recording equipment or the skills to perform an experiment independently. Here, we provide easy-to-follow instructions to measure both wave and event-related EEG potentials using a portable, low-cost amplifier (Backyard Brains, Ann Arbor, MI) that connects to smartphones and PCs, independent of their operating system. Using open-source software (SpikeRecorder) and analysis tools (Python, Google Colaboratory), we demonstrate tractable and robust laboratory exercises for students to gain insights into the scientific method and discover multidisciplinary neuroscience research. We developed 2 laboratory exercises and ran them on participants within our research lab (N = 17, development group). In our first protocol, we analyzed power differences in the alpha band (8-13 Hz) when participants alternated between eyes open and eyes closed states (n = 137 transitions). We could robustly see an increase of over 50% in 59 (43%) of our sessions, suggesting this would make a reliable introductory experiment. Next, we describe an exercise that uses a SpikerBox to evoke an event-related potential (ERP) during an auditory oddball task. This experiment measures the average EEG potential elicited during an auditory presentation of either a highly predictable ("standard") or low-probability ("oddball") tone. Across all sessions in the development group (n=81), we found that 64% (n=52) showed a significant peak in the standard response window for P300 with an average peak latency of 442ms. Finally, we tested the auditory oddball task in a university classroom setting. In 66% of the sessions (n=30), a clear P300 was shown, and these signals were significantly above chance when compared to a Monte Carlo simulation. These laboratory exercises cover the two methods of analysis (frequency power and ERP), which are routinely used in neurology diagnostics, brain-machine interfaces, and neurofeedback therapy. Arming students with these methods and analysis techniques will enable them to investigate this laboratory exercise's variants or test their own hypotheses.

Long-term effects of vagus nerve stimulation on EEG aperiodic components in patients with drug-resistant epilepsy.

Background: Drug-resistant epilepsy (DRE) affects approximately one-third of epilepsy patients who do not achieve adequate seizure control with medication. Vagus nerve stimulation (VNS) is an adjunctive therapy for DRE, but its long-term effects on cortical excitability remain unclear. Objectives: This study aims to elucidate the long-term effects of VNS on electroencephalography (EEG) aperiodic components in patients with DRE. Our objective is to identify biomarkers that can serve as indicators of therapeutic efficacy and provide mechanistic insights into the underlying neural processes. Design: This longitudinal observational study focused on patients with DRE undergoing VNS therapy at Sanbo Brain Hospital. The reduction in seizure frequency rates was quantified over short-term (⩽1 year), medium-term (1-3 years), and long-term (⩾3 years) intervals to assess the therapeutic efficacy of VNS. Both the periodic and aperiodic components of EEG data were analyzed. Methods: Advanced signal processing techniques were utilized to parameterize the periodic and aperiodic components of EEG data, focusing particularly on "offset" and "exponent." These measures were compared before and after VNS therapy. Correlation analyses were conducted to explore the relationship between these EEG parameters and clinical outcomes. Results: In all, 18 patients with DRE participated in this study. During the long-term follow-up period, the responder rate was 55.56%. Significant decreases were observed in aperiodic offset (p = 0.022) and exponent (p = 0.039) among responders. The impact of age on these results was not significant. Correlation analyses revealed a negative association between therapeutic efficacy and a decrease in offset (R = -0.546, p = 0.019) and exponent (R = -0.636, p = 0.019). Conclusion: EEG aperiodic parameters, including offset and exponent, have the potential to serve as promising biomarkers for evaluating the efficacy of VNS. An understanding of the regulatory influence of VNS on cortical excitability through these aperiodic parameters could provide a basis for the development of more effective stimulation parameters and therapeutic strategies.