Beta Band Research Articles

Neurophysiological trajectories in Alzheimer’s disease progression

Alzheimer’s disease (AD) is characterized by the accumulation of amyloid-β and misfolded tau proteins causing synaptic dysfunction, and progressive neurodegeneration and cognitive decline. Altered neural oscillations have been consistently demonstrated in AD. However, the trajectories of abnormal neural oscillations in AD progression and their relationship to neurodegeneration and cognitive decline are unknown. Here, we deployed robust event-based sequencing models (EBMs) to investigate the trajectories of long-range and local neural synchrony across AD stages, estimated from resting-state magnetoencephalography. The increases in neural synchrony in the delta-theta band and the decreases in the alpha and beta bands showed progressive changes throughout the stages of the EBM. Decreases in alpha and beta band synchrony preceded both neurodegeneration and cognitive decline, indicating that frequency-specific neuronal synchrony abnormalities are early manifestations of AD pathophysiology. The long-range synchrony effects were greater than the local synchrony, indicating a greater sensitivity of connectivity metrics involving multiple regions of the brain. These results demonstrate the evolution of functional neuronal deficits along the sequence of AD progression.

Neurophysiological and Autonomic Correlates of Metacognitive Control of and Resistance to Distractors in Ecological Setting: A Pilot Study.

In organisational contexts, professionals are required to decide dynamically and prioritise unexpected external inputs deriving from multiple sources. In the present study, we applied a multimethodological neuroscientific approach to investigate the ability to resist and control ecological distractors during decision-making and to explore whether a specific behavioural, neurophysiological (i.e., delta, theta, alpha and beta EEG band), or autonomic (i.e., heart rate-HR, and skin conductance response-SCR) pattern is correlated with specific personality profiles, collected with the 10-item Big Five Inventory. Twenty-four participants performed a novel Resistance to Ecological Distractors (RED) task aimed at exploring the ability to resist and control distractors and the level of coherence and awareness of behaviour (metacognition ability), while neurophysiological and autonomic measures were collected. The behavioural results highlighted that effectiveness in performance did not require self-control and metacognition behaviour and that being proficient in metacognition can have an impact on performance. Moreover, it was shown that the ability to resist ecological distractors is related to a specific autonomic profile (HR and SCR decrease) and that the neurophysiological and autonomic activations during task execution correlate with specific personality profiles. The agreeableness profile was negatively correlated with the EEG theta band and positively with the EEG beta band, the conscientiousness profile was negatively correlated with the EEG alpha band, and the extroversion profile was positively correlated with the EEG beta band. Taken together, these findings describe and disentangle the hidden relationship that lies beneath individuals' decision to inhibit or activate intentionally a specific behaviour, such as responding, or not, to an external stimulus, in ecological conditions.

Improving Neuroplasticity through Robotic Verticalization Training in Patients with Minimally Conscious State: A Retrospective Study.

In disorders of consciousness, verticalization is considered an effective type of treatment to improve motor and cognitive recovery. Our purpose is to investigate neurophysiological effects of robotic verticalization training (RVT) in patients with minimally conscious state (MCS). Thirty subjects affected by MCS due to traumatic or vascular brain injury, attending the intensive Neurorehabilitation Unit of the IRCCS Neurolesi (Messina, Italy), were included in this retrospective study. They were equally divided into two groups: the control group (CG) received traditional verticalization with a static bed and the experimental group (EG) received advanced robotic verticalization using the Erigo device. Each patient was evaluated using both clinical scales, including Levels of Cognitive Functioning (LCF) and Functional Independence Measure (FIM), and quantitative EEG pre (T0) and post each treatment (T1). The treatment lasted for eight consecutive weeks, and sessions were held three times a week, in addition to standard neurorehabilitation. In addition to a notable improvement in clinical parameters, such as functional (FIM) (p < 0.01) and cognitive (LCF) (p < 0.01) outcomes, our findings showed a significant modification in alpha and beta bands post-intervention, underscoring the promising effect of the Erigo device to influence neural plasticity and indicating a noteworthy difference between pre-post intervention. This was not observed in the CG. The observed changes in alpha and beta bands underscore the potential of the Erigo device to induce neural plasticity. The device's custom features and programming, tailored to individual patient needs, may contribute to its unique impact on brain responses.

Early cortico-muscular coherence and cortical network changes in Parkinson's patients treated with MRgFUS.

To investigate cortical network changes using Magnetoencephalography (MEG) signals in Parkinson's disease (PD) patients undergoing Magnetic Resonance-guided Focused Ultrasound (MRgFUS) thalamotomy. We evaluated the MEG signals in 16 PD patients with drug-refractory tremor before and after 12-month from MRgFUS unilateral lesion of the ventralis intermediate nucleus (Vim) of the thalamus contralateral to the most affected body side. We recorded patients 24 h before (T0) and 24 h after MRgFUS (T1). We analyzed signal epochs recorded at rest and during the isometric extension of the hand contralateral to thalamotomy. We evaluated cortico-muscular coherence (CMC), the out-strength index from non-primary motor areas to the pre-central area and connectivity indexes, using generalized partial directed coherence. Statistical analysis was performed using RMANOVA and post hoct-tests. Most changes found at T1 compared to T0 occurred in the beta band and included: (1) a re-adjustment of CMC distribution; (2) a reduced out-strength from non-primary motor areas toward the precentral area; (3) strongly reduced clustering coefficient values. These differences mainly occurred during motor activation and with few statistically significant changes at rest. Correlation analysis showed significant relationships between changes of out-strength and clustering coefficient in non-primary motor areas and the changes in clinical scores. One day after MRgFUS thalamotomy, PD patients showed a topographically reordered CMC and decreased cortico-cortical flow, together with a reduced local connection between different nodes. These findings suggest that the reordered cortico-muscular and cortical-networks in the beta band may represent an early physiological readjustment related to MRgFUS Vim lesion.

A brain functional network feature extraction method based on directed transfer function and graph theory for MI-BCI decoding tasks.

The development of Brain-Computer Interface (BCI) technology has brought tremendous potential to various fields. In recent years, prominent research has focused on enhancing the accuracy of BCI decoding algorithms by effectively utilizing meaningful features extracted from electroencephalographic (EEG) signals. This paper proposes a method for extracting brain functional network features based on directed transfer function (DTF) and graph theory. The method incorporates the extracted brain network features with common spatial pattern (CSP) to enhance the performance of motor imagery (MI) classification task. The signals from each electrode of the EEG, utilizing a total of 32 channels, are used as input signals for the network nodes. In this study, 26 healthy participants were recruited to provide EEG data. The brain functional network is constructed in Alpha and Beta bands using the DTF method. The node degree (ND), clustering coefficient (CC), and global efficiency (GE) of the brain functional network are obtained using graph theory. The DTF network features and graph theory are combined with the traditional signal processing method, the CSP algorithm. The redundant network features are filtered out using the Lasso method, and finally, the fused features are classified using a support vector machine (SVM), culminating in a novel approach we have termed CDGL. For Beta frequency band, with 8 electrodes, the proposed CDGL method achieved an accuracy of 89.13%, a sensitivity of 90.15%, and a specificity of 88.10%, which are 14.10, 16.69, and 11.50% percentage higher than the traditional CSP method (75.03, 73.46, and 76.60%), respectively. Furthermore, the results obtained with 8 channels were superior to those with 4 channels (82.31, 83.35, and 81.74%), and the result for the Beta frequency band were better than those for the Alpha frequency band (87.42, 87.48, and 87.36%). Similar results were also obtained on two public datasets, where the CDGL algorithm's performance was found to be optimal. The feature fusion of DTF network and graph theory features enhanced CSP algorithm's performance in MI task classification. Increasing the number of channels allows for more EEG signal feature information, enhancing the model's sensitivity and discriminative ability toward specific activities in brain regions. It should be noted that the functional brain network features in the Beta band exhibit superior performance improvement for the algorithm compared to those in the Alpha band.

Unravelling the multisensory learning advantage: Different patterns of within and across frequency-specific interactions drive uni- and multisensory neuroplasticity

In the field of learning theory and practice, the superior efficacy of multisensory learning over uni-sensory is well-accepted. However, the underlying neural mechanisms at the macro-level of the human brain remain largely unexplored. This study addresses this gap by providing novel empirical evidence and a theoretical framework for understanding the superiority of multisensory learning. Through a cognitive, behavioral, and electroencephalographic assessment of carefully controlled uni-sensory and multisensory training interventions, our study uncovers a fundamental distinction in their neuroplastic patterns. A multilayered network analysis of pre- and post- training EEG data allowed us to model connectivity within and across different frequency bands at the cortical level. Pre-training EEG analysis unveils a complex network of distributed sources communicating through cross-frequency coupling, while comparison of pre- and post-training EEG data demonstrates significant differences in the reorganizational patterns of uni-sensory and multisensory learning. Uni-sensory training primarily modifies cross-frequency coupling between lower and higher frequencies, whereas multisensory training induces changes within the beta band in a more focused network, implying the development of a unified representation of audiovisual stimuli. In combination with behavioural and cognitive findings this suggests that, multisensory learning benefits from an automatic top-down transfer of training, while uni-sensory training relies mainly on limited bottom-up generalization. Our findings offer a compelling theoretical framework for understanding the advantage of multisensory learning.

Real-time dynamic analysis of EEG Response for Live Indian Classical Vocal Stimulus with Therapeutic Indications

Numerous studies have been conducted on the connection between music and the brain, and it has been established that listening to music directly affects brain activity and stimulation. The potential benefits of music therapy, which uses music as a tool for healing and fostering well-being, have come to light in a number of circumstances. However, there is a gap in understanding the effects of Indian classical music (ICM) on the brain and its therapeutic applications. Yaman and Puria Dhanashree were the two chosen ragas, which share same notes (swaras) and differs in two of their counter notes. The brain responses are captured from five volunteers through 24 channel Electroencephalogram (EEG) cap using a smartphone, which is utilized to allocate electrodes to different regions of the brain. In this work, different automated approaches for identifying brain regions evoked to live ICM stimuli are proposed, considering input and output uncertainties. These approaches are based on automated energy and Mahalanobis distance measurements, and, a region-specific real-time algorithm based on eigen perturbation, which provides a measure to capture the time evolution of brain activity. This identification is relevant in understanding dynamic changes in brain responses during musical experiences providing a more comprehensive perception and processing of ICM in the human brain. Also, significant change in beta band power reduction was observed after music. These approaches can help integrate it into evidence-based music therapy for cognitive, emotional, and psychological conditions. The findings of this study provide evidence indicating ragas activate different brain regions based on listener’s musical knowledge and is a first step for mhealth based applications.

The neurophysiological effect of mild hypothermia in gyrencephalic brains submitted to ischemic stroke and spreading depolarizations.

Characterize the neurophysiological effects of mild hypothermia on stroke and spreading depolarizations (SDs) in gyrencephalic brains. Left middle cerebral arteries (MCAs) of six hypothermic and six normothermic pigs were permanently occluded (MCAo). Hypothermia began 1 h after MCAo and continued throughout the experiment. ECoG signals from both frontoparietal cortices were recorded. Five-minute ECoG epochs were collected 5 min before, at 5 min, 4, 8, 12, and 16 h after MCAo, and before, during, and after SDs. Power spectra were decomposed into fast (alpha, beta, and gamma) and slow (delta and theta) frequency bands. In the vascular insulted hemisphere under normothermia, electrodes near the ischemic core exhibited power decay across all frequency bands at 5 min and the 4th hour after MCAo. The same pattern was registered in the two furthest electrodes at the 12th and 16th hour. When mild hypothermia was applied in the vascular insulted hemispheres, the power decay was generalized and seen even in electrodes with uncompromised blood flow. During SD analysis, hypothermia maintained increased delta and beta power during the three phases of SDs in the furthest electrode from the ischemic core, followed by the second furthest and third electrode in the beta band during preSD and postSD segments. However, in hypothermic conditions, the third electrode showed lower delta, theta, and alpha power. Mild hypothermia attenuates all frequency bands in the vascularly compromised hemisphere, irrespective of the cortical location. During SD formation, it preserves power spectra more significantly in electrodes further from the ischemic core.

Dynamics of parkinsonian oscillations mediated by transmission delays in a mean-field model of the basal ganglia.

Neural interactions in the brain are affected by transmission delays which may critically alter signal propagation across different brain regions in both normal and pathological conditions. The effect of interaction delays on the dynamics of the generic neural networks has been extensively studied by theoretical and computational models. However, the role of transmission delays in the development of pathological oscillatory dynamics in the basal ganglia (BG) in Parkinson's disease (PD) is overlooked. Here, we investigate the effect of transmission delays on the discharge rate and oscillatory power of the BG networks in control (normal) and PD states by using a Wilson-Cowan (WC) mean-field firing rate model. We also explore how transmission delays affect the response of the BG to cortical stimuli in control and PD conditions. Our results show that the BG oscillatory response to cortical stimulation in control condition is robust against the changes in the inter-population delays and merely depends on the phase of stimulation with respect to cortical activity. In PD condition, however, transmission delays crucially contribute to the emergence of abnormal alpha (8-13 Hz) and beta band (13-30 Hz) oscillations, suggesting that delays play an important role in abnormal rhythmogenesis in the parkinsonian BG. Our findings indicate that in addition to the strength of connections within and between the BG nuclei, oscillatory dynamics of the parkinsonian BG may also be influenced by inter-population transmission delays. Moreover, phase-specificity of the BG response to cortical stimulation may provide further insight into the potential role of delays in the computational optimization of phase-specific brain stimulation therapies.

Exploring brain network oscillations during seizures in drug-naïve patients with juvenile absence epilepsy.

We aimed to investigate the brain network activity during seizures in patients with untreated juvenile absence epilepsy. Thirty-six juvenile absence epilepsy (JAE) patients with a current high frequency of seizures (more than five seizures during a 2 h EEG examination) were included. Each participant underwent a 2 h video EEG examination. Five 10 s EEG epochs for inter-ictal, pre-ictal, and post-ictal, and five 5 s EEG epochs for ictal states were extracted. Five 10 s resting-state EEG epochs for each participant from a sex- and age-matched healthy control (HC) were enrolled. The topological parameters of the brain networks were calculated using a graph theory analysis. Compared with the resting state of the HC group, the global efficiency, local efficiency, and clustering coefficients of the JAE group decreased in the inter-ictal state. In addition, the ictal state showed significantly increased global and local efficiency and clustering coefficients (p < 0.05) and a decreased small-world index and the shortest path length (p < 0.05) in the theta and alpha bands, compared to the remaining states within the JAE group. Moreover, subgroup analysis revealed that those JAE patients with typical 3 Hz discharges had upgraded global efficiency, local efficiency, and clustering coefficients in both delta and beta1 bands, compared to those JAE patients with non-3 Hz discharges during seizures. The present study supported the idea that the changes in the EEG brain networks in JAE patients are characterized by decreased global and local efficiency and clustering coefficient in the alpha band. Moreover, the onset of seizures is accompanied by excessively enhanced network efficiency. JAE patients with different ictal discharge patterns may have different functional network oscillations.

Basolateral amygdala parvalbumin interneurons coordinate oscillations to drive reward behaviors

The basolateral amygdala (BLA) mediates both fear and reward learning.1,2 Previous work has shown that parvalbumin (PV) interneurons in the BLA contribute to BLA oscillatory states integral to fear expression.3,4,5,6,7 However, despite it being critical to our understanding of reward behaviors, it is unknown whether BLA oscillatory states and PV interneurons similarly contribute to reward processing. Local field potentials in the BLA were collected as male and female mice consumed sucrose reward, where prominent changes in the beta band (15-30Hz) emerged with reward experience. During consumption of one water bottle during a two-water-bottle choice test, rhythmic optogenetic stimulation of BLA PVs produced a robust bottle preference, showing that PVs can sufficiently drive reward seeking. Finally, to demonstrate that PV activity is necessary for reward value use, PVs were chemogenetically inhibited following outcome devaluation, rendering mice incapable of using updated reward representations to guide their behavior. Taken together, these experiments provide novel information about the physiological signatures of reward while highlighting BLA PV interneuron contributions to behaviors that are BLA dependent. This work builds upon established knowledge of PV involvement in fear expression and provides evidence that PV orchestration of unique BLA network states is involved in both learning types.

An Analysis of the Correlation between the Asymmetry of Different EEG-Sensor Locations in Diverse Frequency Bands and Short-Term Subjective Well-Being Changes.

We focus on finding a correlation between the asymmetries of electroencephalography (EEG) signals and subjective well-being (SWB) when changed on short time scales via environmental conditions. Most research in this field focuses on frontal alpha asymmetry. We systematically examine different sensor locations and filter the sensor data into the delta band, the theta band, the alpha band, the beta band, and the gamma band, or leave the EEG signal unfiltered. We confirm that frontal alpha asymmetry is correlated to SWB. However, asymmetries between other sensors and/or filtering the data to other bands also shows a linear correlation to SWB values. Asymmetries of anterior brain regions show statistically significant results not only in the alpha band but also in the delta band and theta band, or when the data is not filtered into a specific band. Asymmetries of posterior regions show a trend to be correlated to SWB when EEG activity is higher on the opposite hemisphere and filtered into different frequency bands. Thus, our results let us conclude that focusing just on frontal sensors and the alpha band might not reveal the whole picture of brain regions and frequency bands involved in SWB.

Structural EEG signal analysis for sleep apnea classification.

Diagnosing the sleep apnea can be critical in preventing the person having sleep disorder from unhealthy results. The aim of this study is to obtain a sleep apnea scoring approach by comparing parametric and non-parametric power spectral density (PSD) estimation methods from EEGsignals recorded from different brain regions (C4-M1 and O2-M1) for transient signal analysis of sleep apnea patients. Power Spectral Density (PSD) methods (Burg, Yule-Walker, periodogram, Welch and multi-taper) are examined for the detection of apnea transition states including pre-apnea, intra-apnea and post-apnea together with statistical methods. In the experimental studies, EEG recordings available in the database were analyzed with PSD methods. Results showed that there are statistically significant differences between parametric and non-parametric methods applied for PSD analysis of apnea transition states in delta, theta, alpha and beta bands. Moreover, it was also revealed that PSD of EEG signals obtained from C4-M1 and O2-M1 channels were also found statistically different as proved by classification using the K-nearest neighbour (KNN) method. It was concluded that not only applying different PSD methods, but also EEG signals from different brain regions provided different statistical results in terms of apnea transition states as obtained from KNN classification.

The influence of prosthetic suspension on gait and cortical modulations is persons with a transfemoral amputation: socket-suspended versus bone-anchored prosthesis

BackgroundPersons with a transfemoral amputation (TFA) often experience difficulties in daily-life ambulation, including an asymmetrical and less stable gait pattern and a greater cognitive demand of walking. However, it remains unclear whether this is effected by the prosthetic suspension, as eliminating the non-rigid prosthetic connection may influence stability and cortical activity during walking. Spatiotemporal and stability-related gait parameters, as well as cortical activity during walking, were evaluated between highly active individuals (MFC-level K3-4) with a TFA and able-bodied (AB) persons, and between persons with a bone-anchored prosthesis (BAP) and those with a socket-suspended prosthesis (SSP).Methods18 AB persons and 20 persons with a unilateral TFA (10 BAP-users, 10 SSP-users) walked on a treadmill at their preferred speed. Spatiotemporal and margin of stability parameters were extracted from three-dimensional movement recordings. In addition, 126-channel electroencephalogram (EEG) was recorded. Brain-related activity from several cortical areas was isolated using independent component analysis. Source-level data were divided into gait cycles and subjected to time–frequency analysis to determine gait-cycle dependent modulations of cortical activity.ResultsPersons with TFA walked with smaller and wider steps and with greater variability in mediolateral foot placement than AB subjects; no significant differences were found between BAP- and SSP-users. The EEG analysis yielded four cortical clusters in frontal, central (both hemispheres), and parietal areas. No statistically significant between-group differences were found in the mean power over the entire gait cycle. The event-related spectral perturbation maps revealed differences in power modulations (theta, alpha, and beta bands) between TFA and AB groups, and between BAP- and SSP-users, with largest differences observed around heel strike of either leg.ConclusionsThe anticipated differences in gait parameters in persons with TFA were confirmed, however no significant effect of the fixed suspension of a BAP was found. The preliminary EEG findings may indicate more active monitoring and control of stability in persons with TFA, which appeared to be timed differently in SSP than in BAP-users. Future studies may focus on walking tasks that challenge stability to further investigate differences related to prosthetic suspension.

Coherent activity within and between hemispheres: cortico-cortical connectivity revealed by rTMS of the right posterior parietal cortex.

Low frequency (1 Hz) repetitive transcranial stimulation (rTMS) applied over right posterior parietal cortex (rPPC) has been shown to reduce cortical excitability both of the stimulated area and of the interconnected contralateral homologous areas. In the present study, we investigated the whole pattern of intra- and inter-hemispheric cortico-cortical connectivity changes induced by rTMS over rPPC. To do so, 14 healthy participants underwent resting state EEG recording before and after 30 min of rTMS at 1 Hz or sham stimulation over the rPPC (electrode position P6). Real stimulation was applied at 90% of motor threshold. Coherence values were computed on the electrodes nearby the stimulated site (i.e., P4, P8, and CP6) considering all possible inter- and intra-hemispheric combinations for the following frequency bands: delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12Hz), low beta (12-20 Hz), high beta (20-30 Hz), and gamma (30-50 Hz). Results revealed a significant increase in coherence in delta, theta, alpha and beta frequency bands between rPPC and the contralateral homologous sites. Moreover, an increase in coherence in theta, alpha, beta and gamma frequency bands was found between rPPC and right frontal sites, reflecting the activation of the fronto-parietal network within the right hemisphere. Summarizing, subthreshold rTMS over rPPC revealed cortico-cortical inter- and intra-hemispheric connectivity as measured by the increase in coherence among these areas. Moreover, the present results further confirm previous evidence indicating that the increase of coherence values is related to intra- and inter-hemispheric inhibitory effects of rTMS. These results can have implications for devising evidence-based rehabilitation protocols after stroke.

Resting-state EEG rhythms are abnormal in post COVID-19 patients with brain fog without cognitive and affective disorders

ObjectivesSeveral persons experiencing post-covid-19 (post-COVID) with “brain fog” (e.g., fatigue, cognitive and psychiatric disorders, etc.) show abnormal resting-state electroencephalographic (rsEEG) rhythms reflecting a vigilance dysfunction. Here, we tested the hypothesis that in those post-COVID persons, abnormal rsEEG rhythms may occur even when cognitive and psychiatric disorders are absent. MethodsThe experiments were performed on post-COVID participants about one year after hospitalization for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Inclusion criteria included a “brain fog” claim, no pre-infection, and actual organic chronic disease. Matched controls (no COVID) were also enrolled. All participants underwent clinical/neuropsychological assessment (including fatigue assessment) and rsEEG recordings. The eLORETA freeware estimated regional rsEEG cortical sources at individual delta (<4 Hz), theta (4–7 Hz), and alpha (8–13 Hz) bands. Beta (14–30 Hz) and gamma (30–40 Hz) bands were pre-fixed. ResultsMore than 90% of all post-COVID participants showed no cognitive or psychiatric disorders, and 75% showed ≥ 2 fatigue symptoms. The post-COVID group globally presented lower posterior rsEEG alpha source activities than the Control group. This effect was more significant in the long COVID-19 patients with ≥ 2 fatigue symptoms. ConclusionsIn post-COVID patients with no chronic diseases and cognitive/psychiatric disorders, “brain fog” can be associated with abnormal posterior rsEEG alpha rhythms and subjective fatigue. SignificanceThese abnormalities may be related to vigilance and allostatic dysfunctions.

Neural Oscillations and Functional Significances for Prioritizing Dual-Task Walking in Parkinson's Disease.

Task prioritization involves allocating brain resources in a dual-task scenario, but the mechanistic details of how prioritization strategies affect dual-task walking performance for Parkinson's disease (PD) are little understood. We investigated the performance benefits and corresponding neural signatures for people with PD during dual-task walking, using gait-prioritization (GP) and manual-prioritization (MP) strategies. Participants (N = 34) were asked to hold two inter-locking rings while walking and to prioritize either taking big steps (GP strategy) or separating the two rings (MP strategy). Gait parameters and ring-touch time were measured, and scalp electroencephalograph was performed. Compared with the MP strategy, the GP strategy yielded faster walking speed and longer step length, whereas ring-touch time did not significantly differ between the two strategies. The MP strategy led to higher alpha (8-12 Hz) power in the posterior cortex and beta (13-35 Hz) power in the left frontal-temporal area, but the GP strategy was associated with stronger network connectivity in the beta band. Changes in walking speed and step length because of prioritization negatively correlated with changes in alpha power. Prioritization-related changes in ring-touch time correlated negatively with changes in beta power but positively with changes in beta network connectivity. A GP strategy in dual-task walking for PD can enhance walking speed and step length without compromising performance in a secondary manual task. This strategy augments attentional focus and facilitates compensatory reinforcement of inter-regional information exchange.

Oscillatory and non-oscillatory features of the magnetoencephalic sensorimotor rhythm in Parkinson’s disease

Parkinson’s disease (PD) is associated with changes in neural activity in the sensorimotor alpha and beta bands. Using magnetoencephalography (MEG), we investigated the role of spontaneous neuronal activity within the somatosensory cortex in a large cohort of early- to mid-stage PD patients (N = 78) on Parkinsonian medication and age- and sex-matched healthy controls (N = 60) using source reconstructed resting-state MEG. We quantified features of the time series data in terms of oscillatory alpha power and central alpha frequency, beta power and central beta frequency, and 1/f broadband characteristics using power spectral density. Furthermore, we characterised transient oscillatory burst events in the mu-beta band time-domain signals. We examined the relationship between these signal features and the patients’ disease state, symptom severity, age, sex, and cortical thickness. PD patients and healthy controls differed on PSD broadband characteristics, with PD patients showing a steeper 1/f exponential slope and higher 1/f offset. PD patients further showed a steeper age-related decrease in the burst rate. Out of all the signal features of the sensorimotor activity, the burst rate was associated with increased severity of bradykinesia, whereas the burst duration was associated with axial symptoms. Our study shows that general non-oscillatory features (broadband 1/f exponent and offset) of the sensorimotor signals are related to disease state and oscillatory burst rate scales with symptom severity in PD.

Abstract P05: Testing patterns and referrals for monoclonal protein detection at John Peter Smith hospital

Abstract Background: Multiple myeloma (MM) is an incurable disease. Blacks have a higher incidence of MM and are diagnosed at a younger age compared to other populations. Safety-net hospitals (SNH) treat a high proportion of Black patients. Early detection of myeloma is important to prevent permanent organ dysfunction. Serum monoclonal protein testing using expanded panel aids in the diagnosis and monitoring of monoclonal gammopathies. This test result has 16 discrete components and any out-of-range value can be confusing to the ordering providers, triggering referrals to hematology oncology (hemonc). We sought to identify the testing and referral patterns at John Peter Smith (JPS) Hospital, a SNH in North Texas. Methods: Data was obtained from JPS Data Analytics and Reporting department. All serum monoclonal protein expanded panel (LAB174) orders and results for patients tested from 1-1-2022 to 12-31-2022 were abstracted from EPIC EMR. Demographic information was collected along with details about ordering providers and referrals. We sorted the data and excluded all orders by oncology providers as well as all inpatient orders. Data analysis was completed using Excel. Results: A total of 1063 tests were performed on 1026 patients. 39% were Non-Hispanic White (NHW), 36% were Black, and 13% were Hispanic. Median age was 57 years. Monoclonal band was seen in 143 (13%) samples; immunoglobulin (IG) kappa (k) 59, IG lambda (λ) 68, both IG k and IG λ 9. Results with gamma (γ) and beta (β) band were seen in 22 and 3 respectively. Measurable k band (&amp;gt;0.1 g/dL) was seen in 12 tests, &amp;gt; 1 g/dL in 5, and &amp;gt; 3 g/dL in only 1 test. Measurable λ band seen in 9 tests, &amp;gt; 1 g/dL in 3, and &amp;gt; 3 g/dL in no tests. Serum protein electrophoresis (SPEP) was normal in 525, and immunofixation (IFE) was normal in 507. Polyclonal SPEP was noted in 169 tests. Hypogammaglobinemia was seen in 11. 72 out of 369 (20%) Blacks had abnormal bands vs 47 out of 397 (12%) NHW. Two-tailed t-test was significant at p-value 0.00327. Referrals were generated to hemonc in 201 patients. Rheumatology accounted for 19% of tests, nephrology 18%, neurology 19%, and remaining were from primary care and other specialties. 212 patients were referred to hematology oncology using ICD10 diagnosis code R77.8. Rheumatologists referred 48 patients, which is 25% of all patients that they tested. Referrals from neurology: 39 (20%) and nephrology: 25 (13%). Conclusions: At JPS, clinical care providers are conducting tests to identify precursor conditions to myeloma. The test positivity rate was 13% in the non-oncology outpatient setting. Blacks had a higher percentage of positivity, reinforcing the need for a higher index of suspicion. The complexity of the test results, however, is overwhelming to the ordering providers, triggering referrals to the hemonc division, prompting recruitment and training of midlevel providers within hemonc to ensure proper monitoring of patients with precursor conditions. JPS Office of Clinical Research is planning to participate in early detection clinical trials for myeloma. Citation Format: Kavya Athipatla, Melissa Howell, Anuradha Lingam, Kayani Narra. Testing patterns and referrals for monoclonal protein detection at John Peter Smith hospital [abstract]. In: Proceedings of the Blood Cancer Discovery Symposium; 2024 Mar 4-6; Boston, MA. Philadelphia (PA): AACR; Blood Cancer Discov 2024;5(2_Suppl):Abstract nr P05.

Characterization of Vagus Nerve Stimulation (VNS) Dose-Dependent Effects on EEG Power Spectrum and Synchronization.

This study investigates the dose-dependent EEG effects of Vagus Nerve Stimulation (VNS) in patients with drug-resistant epilepsy. This research examines how varying VNS intensities impacts EEG power spectrum and synchronization in a cohort of 28 patients. Patients were categorized into responders, partial-responders, and non-responders based on seizure frequency reduction. The methods involved EEG recordings at incremental VNS intensities, followed by spectral and synchronization analysis. The results reveal significant changes in EEG power, particularly in the delta and beta bands across different intensities. Notably, responders exhibited distinct EEG changes compared to non-responders. Our study has found that VNS intensity significantly influences EEG power topographic allocation and brain desynchronization, suggesting the potential use of acute dose-dependent effects to personalized VNS therapy in the treatment of epilepsy. The findings underscore the importance of individualized VNS dosing for optimizing therapeutic outcomes and highlight the use of EEG metrics as an effective tool for monitoring and adjusting VNS parameters. These insights offer a new avenue for developing individualized VNS therapy strategies, enhancing treatment efficacy in epilepsy.