Synchronous Activity Research Articles

Periaqueductal gray activates antipredatory neural responses in the amygdala of foraging rats.

Pavlovian fear conditioning research suggests that the interaction between the dorsal periaqueductal gray (dPAG) and basolateral amygdala (BLA) acts as a prediction error mechanism in the formation of associative fear memories. However, their roles in responding to naturalistic predatory threats, characterized by less explicit cues and the absence of reiterative trial-and-error learning events, remain unexplored. In this study, we conducted single-unit recordings in rats during an 'approach food-avoid predator' task, focusing on the responsiveness of dPAG and BLA neurons to a rapidly approaching robot predator. Optogenetic stimulation of the dPAG triggered fleeing behaviors and increased BLA activity in naive rats. Notably, BLA neurons activated by dPAG stimulation displayed immediate responses to the robot, demonstrating heightened synchronous activity compared to BLA neurons that did not respond to dPAG stimulation. Additionally, the use of anterograde and retrograde tracer injections into the dPAG and BLA, respectively, coupled with c-Fos activation in response to predatory threats, indicates that the midline thalamus may play an intermediary role in innate antipredatory-defensive functioning.

Periaqueductal gray activates antipredatory neural responses in the amygdala of foraging rats

Pavlovian fear conditioning research suggests that the interaction between the dorsal periaqueductal gray (dPAG) and basolateral amygdala (BLA) acts as a prediction error mechanism in the formation of associative fear memories. However, their roles in responding to naturalistic predatory threats, characterized by less explicit cues and the absence of reiterative trial-and-error learning events, remain unexplored. In this study, we conducted single-unit recordings in rats during an ‘approach food-avoid predator’ task, focusing on the responsiveness of dPAG and BLA neurons to a rapidly approaching robot predator. Optogenetic stimulation of the dPAG triggered fleeing behaviors and increased BLA activity in naive rats. Notably, BLA neurons activated by dPAG stimulation displayed immediate responses to the robot, demonstrating heightened synchronous activity compared to BLA neurons that did not respond to dPAG stimulation. Additionally, the use of anterograde and retrograde tracer injections into the dPAG and BLA, respectively, coupled with c-Fos activation in response to predatory threats, indicates that the midline thalamus may play an intermediary role in innate antipredatory-defensive functioning.

Neuromuscular conditions in post-stroke ankle-foot dysfunction reflected by surface electromyography

BackgroundRating scales and linear indices of surface electromyography (sEMG) cannot quantify all neuromuscular conditions associated with ankle-foot dysfunction in hemiplegic patients. This study aimed to reveal potential neuromuscular conditions of ankle-foot dysfunction in hemiplegic patients by nonlinear network indices of sEMG.MethodsFourteen male patients with hemiplegia and 10 age- and sex-matched healthy male adults were recruited and tested in static standing position. The characteristics of the root mean square (RMS), median frequency (MF), and three nonlinear indices, the clustering coefficient (C), the average shortest path length (L), and the degree centrality (DC), of eight groups of muscles in bilateral calves were observed.ResultsCompared to those of the control group, the RMS of the medial gastrocnemius (MG), flexor digitorum longus (FDL), and extensor digitorum longus (EDL) on the affected side were significantly lower (P < 0.05), and the RMS of the tibial anterior (TA) and EDL on the unaffected side were significantly higher (P < 0.05). The MF of the EDL on the affected side was significantly higher than that on the control side (P < 0.05). The C of the unaffected side was significantly higher than that of the control group, whereas the L was lower (P < 0.05). Compared to those of the control group, the DC of the TA, EDL, and soleus (SOL) on the unaffected sides were higher (P < 0.05), and the DC of the MG on the affected sides was lower (P < 0.05).ConclusionThe change trends and clinical significance of these three network indices, including C, L, and DC, are not in line with those of the traditional linear indices, the RMS and the MF. The C and L may reflect the degree of synchronous activation of muscles during a certain motor task. The DC might be able to quantitatively assess the degree of muscle involvement and reflect the degree of involvement of a single muscle. Linear and nonlinear indices may reveal more neuromuscular conditions in hemiplegic ankle-foot dysfunction from different aspects.Trial registrationChiCTR2100055090.

Propagation of transient explosive synchronization in a mesoscale mouse brain network model of epilepsy.

Generalized epileptic attacks, which exhibit widespread disruption of brain activity, are characterized by recurrent, spontaneous, and synchronized bursts of neural activity that self-initiate and self-terminate through critical transitions. Here we utilize the general framework of explosive synchronization (ES) from complex systems science to study the role of network structure and resource dynamics in the generation and propagation of seizures. We show that a combination of resource constraint and adaptive coupling in a Kuramoto network oscillator model can reliably generate seizure-like synchronization activity across different network topologies, including a biologically derived mesoscale mouse brain network. The model, coupled with a novel algorithm for tracking seizure propagation, provides mechanistic insight into the dynamics of transition to the synchronized state and its dependence on resources; and identifies key brain areas that may be involved in the initiation and spatial propagation of the seizure. The model, though minimal, efficiently recapitulates several experimental and theoretical predictions from more complex models and makes novel experimentally testable predictions.

Neuromodulation Treatments Targeting Pathological Synchrony for Tinnitus in Adults: A Systematic Review.

(1) Background: Tinnitus involves the conscious awareness of a tonal or composite noise for which there is no identifiable corresponding external acoustic source. For many people, tinnitus is a disorder associated with symptoms of emotional distress, cognitive dysfunction, autonomic arousal, behavioural changes, and functional disability. Many symptoms can be addressed effectively using education or cognitive behavioural therapy. However, there is no treatment that effectively reduces or alters tinnitus-related neurophysiological activity and thus the tinnitus percept. In this systematic review, we evaluated the effectiveness of neuromodulation therapies for tinnitus that explicitly target pathological synchronous neural activity. (2) Methods: Multiple databases were searched for randomised controlled trials of neuromodulation interventions for tinnitus in adults, with 24 trials included. The risk of bias was assessed, and where appropriate, meta-analyses were performed. (3) Results: Few trials used acoustic, vagal nerve, or transcranial alternating current stimulation, or bimodal stimulation techniques, with limited evidence of neuromodulation or clinical effectiveness. Multiple trials of transcranial direct current stimulation (tDCS) were identified, and a synthesis demonstrated a significant improvement in tinnitus symptom severity in favour of tDCS versus control, although heterogeneity was high. (4) Discussion: Neuromodulation for tinnitus is an emerging but promising field. Electrical stimulation techniques are particularly interesting, given recent advances in current flow modelling that can be applied to future studies.

Aberrant neural oscillations in poststroke aphasia.

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

Effects of two-person synchronized cycling exercise on interpersonal cooperation: A near-infrared spectroscopy hyperscanning study

ObjectiveAlthough psychological research indicating the synchronous activities can promote interpersonal cooperation, thus far there is no direct evidence that two-person synchronous exercise effectively enhances interpersonal cooperative behaviors in Physical exercise field. This suggests that, although synchronization phenomenon is widespread in sports and is considered a potential tool for enhancing teamwork, its specific effects and functioning mechanisms still need to be clarified by further scientific research. This study intends to use two-person synchronized cycling exercise to investigate the synchronized exercise effect on interpersonal cooperative behavior and its underlying neural mechanisms. MethodsEighty college students without regular exercise habits will be randomly assigned to the experimental group (10 male dyads and 10 female dyads) and the control group (10 male dyads and 10 female dyads). During the experiment, dyads in the experimental group performed a 30-minute synchronized cycling exercise with synchronized pedaling movements; dyads in the control group rested sedentary in the same environment for 30 minutes. Interpersonal cooperative behavior was assessed with the Prisoner's Dilemma task, and the interpersonal neural synchronization(INS) data were collected in the prefrontal cortex using near-infrared hyperscanning. ResultsThis study compared behavior and brain activity before and after synchronous exercise. Behavioral results revealed that, compared to pre-exercise, dyads in the post-exercise had higher average cooperation rates, higher cooperation efficiency and shorter cooperation response times. Compared to post-sedentary, dyads in the post-exercise had shorter cooperation response times and higher cooperation efficiency. Furthermore, brain data showed that,compared to pre-exercise, dyads in the post-exercise had stronger INS in the dorsolateral prefrontal cortex(DLPFC), whereas the dyads in the post-exercise had stronge INS in the DLPFC compared to post-sedentary. After controlling for dyads' anxiety and mood states, this study also found a marginally significant negative correlation between INS differences in the left DLPFC and cooperation response time differences. ConclusionsThis research confirms, from both behavioral and neuroscience perspectives, that one synchronization cycle can significantly enhance interpersonal cooperative behavior, and this positive effect is closely associated with increased INS in the left DLPFC. This study provides new insights into understanding how positive interactive exercises promote interpersonal cooperation through specific neural mechanisms.

Self-reinforced Synchronization of persulfate activation and photocatalysis by Tri-metal heterojunction catalyst for efficient degradation of Sulfadiazine

The outstanding performance of advanced oxidation processes based on self-generated active species in the decomposition of antibiotics has attracted widespread attention. Herein, a novel heterojunction flower-shaped microsphere Iron-based Hydroxide/Tungstate Antimony Oxide (FSW) composed of nanosheets with synchronous persulfate activation and photocatalytic properties were proposed to achieve efficient degradation of sulfadiazine (SDZ) by enhanced active oxidation species. Constructed FSW/PMS/vis system realized the improved removal of SDZ at pH 2–6, with a degradation efficiency of 96.6 % in just 6 min (electron transfer efficiency, 6.19 × 10–4 A/cm2; kinetic rate, 2-ORR). Investigation of density functional theory demonstrated the superiority of FSW catalysts (Eads = -1.63 eV), indicating that FSW can not only enhance the adsorption of PMS but also activate PMS to generate a large number of free radical ions, realizing rapid carrier movement and effective charge transfer, which highlights the application prospects of the system in eliminating antibiotics in environmental water bodies.

Cross-Frequency Coupling as a Biomarker for Early Stroke Recovery

Background The application of neuroimaging-based biomarkers in stroke has enriched our understanding of post-stroke recovery mechanisms, including alterations in functional connectivity based on synchronous oscillatory activity across various cortical regions. Phase-amplitude coupling, a type of cross-frequency coupling, may provide additional mechanistic insight. Objective To determine how the phase of prefrontal cortex delta (1-3 Hz) oscillatory activity mediates the amplitude of motor cortex beta (13-20 Hz) oscillations in individual’s early post-stroke. Methods Participants admitted to an inpatient rehabilitation facility completed resting and task-based EEG recordings and motor assessments around the time of admission and discharge along with structural neuroimaging. Unimpaired controls completed EEG procedures during a single visit. Mixed-effects linear models were performed to assess within- and between-group differences in delta-beta prefrontomotor coupling. Associations between coupling and motor status and injury were also determined. Results Thirty individuals with stroke and 17 unimpaired controls participated. Coupling was greater during task versus rest conditions for all participants. Though coupling during affected extremity task performance decreased during hospitalization, coupling remained elevated at discharge compared to controls. Greater baseline coupling was associated with better motor status at admission and discharge and positively related to motor recovery. Coupling demonstrated both positive and negative associations with injury involving measures of lesion volume and overlap injury to anterior thalamic radiation, respectively. Conclusions This work highlights the utility of prefrontomotor cross-frequency coupling as a potential motor status and recovery biomarker in stroke. The frequency- and region-specific neurocircuitry featured in this work may also facilitate novel treatment strategies in stroke.

Nondifferentiable activity in the brain.

Spike raster plots of numerous neurons show vertical stripes, indicating that neurons exhibit synchronous activity in the brain. We seek to determine whether these coherent dynamics are caused by smooth brainwave activity or by something else. By analyzing biological data, we find that their cross-correlograms exhibit not only slow undulation but also a cusp at the origin, in addition to possible signs of monosynaptic connectivity. Here we show that undulation emerges if neurons are subject to smooth brainwave oscillations while a cusp results from nondifferentiable fluctuations. While modern analysis methods have achieved good connectivity estimation by adapting the models to slow undulation, they still make false inferences due to the cusp. We devise a new analysis method that may solve both problems. We also demonstrate that oscillations and nondifferentiable fluctuations may emerge in simulations of large-scale neural networks.

Periaqueductal gray activates antipredatory neural responses in the amygdala of foraging rats.

Pavlovian fear conditioning research suggests that the interaction between the dorsal periaqueductal gray (dPAG) and basolateral amygdala (BLA) acts as a prediction error mechanism in the formation of associative fear memories. However, their roles in responding to naturalistic predatory threats, characterized by less explicit cues and the absence of reiterative trial-and-error learning events, remain unexplored. In this study, we conducted single-unit recordings in rats during an 'approach food-avoid predator' task, focusing on the responsiveness of dPAG and BLA neurons to a rapidly approaching robot predator. Optogenetic stimulation of the dPAG triggered fleeing behaviors and increased BLA activity in naive rats. Notably, BLA neurons activated by dPAG stimulation displayed immediate responses to the robot, demonstrating heightened synchronous activity compared to BLA neurons that did not respond to dPAG stimulation. Additionally, the use of anterograde and retrograde tracer injections into the dPAG and BLA, respectively, coupled with c-Fos activation in response to predatory threats, indicates that the midline thalamus may play an intermediary role in innate antipredatory defensive functioning.

An Open-Source Deep Learning-Based GUI Toolbox For Automated Auditory Brainstem Response Analyses (ABRA).

In this paper, we introduce a new, open-source software developed in Python for analyzing Auditory Brainstem Response (ABR) waveforms. ABRs are a far-field recording of synchronous neural activity generated by the auditory fibers in the ear in response to sound, and used to study acoustic neural information traveling along the ascending auditory pathway. Common ABR data analysis practices are subject to human interpretation and are labor-intensive, requiring manual annotations and visual estimation of hearing thresholds. The proposed new Auditory Brainstem Response Analyzer (ABRA) software is designed to facilitate the analysis of ABRs by supporting batch data import/export, waveform visualization, and statistical analysis. Techniques implemented in this software include algorithmic peak finding, threshold estimation, latency estimation, time warping for curve alignment, and 3D plotting of ABR waveforms over stimulus frequencies and decibels. The excellent performance on a large dataset of ABR collected from three labs in the field of hearing research that use different experimental recording settings illustrates the efficacy, flexibility, and wide utility of ABRA.

Microstate-based brain network dynamics distinguishing temporal lobe epilepsy patients: A machine learning approach

Temporal lobe epilepsy (TLE) stands as the predominant adult focal epilepsy syndrome, characterized by dysfunctional intrinsic brain dynamics. However, the precise mechanisms underlying seizures in these patients remain elusive. Our study encompassed 116 TLE patients compared with 51 healthy controls. Employing microstate analysis, we assessed brain dynamic disparities between TLE patients and healthy controls, as well as between drug-resistant epilepsy (DRE) and drug-sensitive epilepsy (DSE) patients. We constructed dynamic functional connectivity networks based on microstates and quantified their spatial and temporal variability. Utilizing these brain network features, we developed machine learning models to discriminate between TLE patients and healthy controls, and between DRE and DSE patients. Temporal dynamics in TLE patients exhibited significant acceleration compared to healthy controls, along with heightened synchronization and instability in brain networks. Moreover, DRE patients displayed notably lower spatial variability in certain parts of microstate B, E and F dynamic functional connectivity networks, while temporal variability in certain parts of microstate E and G dynamic functional connectivity networks was markedly higher in DRE patients compared to DSE patients. The machine learning model based on these spatiotemporal metrics effectively differentiated TLE patients from healthy controls and discerned DRE from DSE patients. The accelerated microstate dynamics and disrupted microstate sequences observed in TLE patients mirror highly unstable intrinsic brain dynamics, potentially underlying abnormal discharges. Additionally, the presence of highly synchronized and unstable activities in brain networks of DRE patients signifies the establishment of stable epileptogenic networks, contributing to the poor responsiveness to antiseizure medications. The model based on spatiotemporal metrics demonstrated robust predictive performance, accurately distinguishing both TLE patients from healthy controls and DRE patients from DSE patients.

Visual detection of seizures in mice using supervised machine learning.

Seizures are caused by abnormally synchronous brain activity that can result in changes in muscle tone, such as twitching, stiffness, limpness, or rhythmic jerking. These behavioral manifestations are clear on visual inspection and the most widely used seizure scoring systems in preclinical models, such as the Racine scale in rodents, use these behavioral patterns in semiquantitative seizure intensity scores. However, visual inspection is time-consuming, low-throughput, and partially subjective, and there is a need for rigorously quantitative approaches that are scalable. In this study, we used supervised machine learning approaches to develop automated classifiers to predict seizure severity directly from noninvasive video data. Using the PTZ-induced seizure model in mice, we trained video-only classifiers to predict ictal events, combined these events to predict an univariate seizure intensity for a recording session, as well as time-varying seizure intensity scores. Our results show, for the first time, that seizure events and overall intensity can be rigorously quantified directly from overhead video of mice in a standard open field using supervised approaches. These results enable high-throughput, noninvasive, and standardized seizure scoring for downstream applications such as neurogenetics and therapeutic discovery.

Boosting Prefrontal Brain Responsiveness by Interoceptive Attentiveness during Synchronized Breathing, Motor, and Cognitive Task

Background: this study explored the prefrontal cortex (PFC) hemodynamic variations produced by the association of an Interoceptive Attentiveness (IA) condition with a simple breath, motor, and cognitive synchronization task. Methods: 18 healthy individuals performed different synchronization activities (breath, motor, and cognitive) under both IA and control conditions, while levels of oxygenated (O2Hb) and deoxygenated hemoglobin were measured using functional Near-Infrared Spectroscopy (fNIRS). Results: findings revealed higher O2Hb levels in the prefrontal brain region during the experimental condition (IA) in contrast to the control condition. Notably, this difference was particularly evident during the cognitive task as opposed to the other tasks (breath and motor). In contrast, no significant differences were found for the PFC lateralization effect. Conclusions: This evidence holds potential for rehabilitation professionals suggesting that the combination of deliberate attention to the breath and a cognitive synchronization task (such as a vocal exercise executed simultaneously) could boost PFC responsiveness.

Shaping the olfactory map: cell type-specific activity patterns guide circuit formation.

The brain constructs spatially organized sensory maps to represent sensory information. The formation of sensory maps has traditionally been thought to depend on synchronous neuronal activity. However, recent evidence from the olfactory system suggests that cell type-specific temporal patterns of spontaneous activity play an instructive role in shaping the olfactory glomerular map. These findings challenge traditional views and highlight the importance of investigating the spatiotemporal dynamics of neural activity to understand the development of complex neural circuits. This review discusses the implications of new findings in the olfactory system and outlines future research directions.

Serotonin modulates infraslow oscillation in the dentate gyrus during Non-REM sleep.

Synchronous neuronal activity is organized into neuronal oscillations with various frequency and time domains across different brain areas and brain states. For example, hippocampal theta, gamma and sharp wave oscillations are critical for memory formation and communication between hippocampal subareas and the cortex. In this study, we investigated the neuronal activity of the dentate gyrus (DG) with electrophysiological and optical imaging tools during sleep-wake cycles. We found that the activity of major glutamatergic cell populations in the DG is organized into in-fraslow oscillations (0.01 - 0.03 Hz) during NREM sleep. Although the DG is considered a sparsely active network during wakefulness, we found that 50% of granule cells and about 25% of mossy cells exhibit increased activity during NREM sleep. Further experiments revealed that the infraslow oscillation in the DG is modulated by rhythmic serotonin release during sleep, which oscillates at the same frequency but in an opposite phase. Genetic manipulation of 5-HT receptors revealed that this neuromodulatory regulation is mediated by 5-HT1a receptors and the knockdown of these receptors leads to memory impairment. Together, our results provide novel mechanistic insights into how the 5-HT system can influence hippocampal activity patterns during sleep.

The role of atrial pacing site in reducing filling pressures by accelerated pacing in virtual HFpEF patients

Abstract Background Patients with heart failure with preserved ejection fraction (HFpEF) and pacemakers have been shown to benefit from moderately accelerated pacing rates compared to the standard 60bpm. HFpEF patients often present with prolonged P-wave duration (PWD) and atrial fibrillation. Right atrial appendage pacing (RAAP) lengthens PWD, RA septal (RASP) has a neutral effect, while Bachmann’s bundle pacing (BBP) normalizes or shortens PWD compared to sinus rhythm. The mechanical and hemodynamic effects of atrial pacing site selection remain unknown. Aim To investigate the impact of RAAP, RASP and BBP on cardiac mechanics and hemodynamics in an established cohort of virtual HFpEF patients undergoing accelerated pacing. Method HFpEF with prolonged PWD was simulated using the validated CircAdapt computational model of the human cardiovascular system. First, left ventricular (LV) diastolic dysfunction was simulated by decreasing LV myocardial relaxation rate and compliance, such that mean left atrial (LA) pressure (mLAP) was 15mmHg. Second, PWD was prolonged by prescribing a gradual electrical activation delay from RA to LA of 140ms. We then simulated atrial pacing with three different lead positions (Fig.1, left) and gradually increased pacing rate with a constant 120-ms paced atrioventricular (AV) delay. The CircAdapt model computed regional LA strain and mLAP with RAAP, RASP, and BBP. Cardiac output (5L/min) and mean arterial pressure (92mmHg) were kept constant in all simulations. Results Simulated BBP demonstrated the most synchronous LA mechanical activation and function, characterized by uniform segmental LA strain patterns and highest LA reservoir strain (LASR) (Fig.1, middle, with colored arrows highlighting the mechanical dyssynchrony). Hemodynamically (Fig.1, right), BBP acutely decreased mLAP (-1.0mmHg) at the initial heart rate of 60bpm, while RAAP increased it (+0.3mmHg). As pacing rate accelerated, BBP reduces filling pressure (mLAP: -2.8mmHg), more than RASP (-1.8mmHg) or RAAP (-1.2mmHg) at 80bpm. At high pacing rates, RASP and RAAP adversely increase mLAP, due to the prolonged atrial contraction duration and shorter LV filling time. Conclusion Our simulations of different atrial pacing sites in virtual HFpEF patients suggest that BBP yields the most synchronous LA activation pattern and a more substantial reduction in filling pressures with accelerated atrial pacing compared to RASP. Reduction in mLAP with accelerated pacing was attenuated with RAAP. While our study concentrated on a specific paced AV interval, the favorable outcomes observed with BBP could be further improved by including different, rate-adaptive, AV protocols.Fig 1.

Dichotomous frequency-dependent phase synchrony in the sensorimotor network characterizes simplistic movement

It is hypothesized that disparate brain regions interact via synchronous activity to control behavior. The nature of these interconnected ensembles remains an area of active investigation, and particularly the role of high frequency synchronous activity in simplistic behavior is not well known. Using intracranial electroencephalography, we explored the spectral dynamics and network connectivity of sensorimotor cortical activity during a simple motor task in seven epilepsy patients. Confirming prior work, we see a “spectral tilt” (increased high-frequency (HF, 70–100 Hz) and decreased low-frequency (LF, 3–33 Hz) broadband oscillatory activity) in motor regions during movement compared to rest, as well as an increase in LF synchrony between these regions using time-resolved phase-locking. We then explored this phenomenon in high frequency and found a robust but opposite effect, where time-resolved HF broadband phase-locking significantly decreased during movement. This “connectivity tilt” (increased LF synchrony and decreased HF synchrony) displayed a graded anatomical dependency, with the most robust pattern occurring in primary sensorimotor cortical interactions and less robust pattern occurring in associative cortical interactions. Connectivity in theta (3–7 Hz) and high beta (23–27 Hz) range had the most prominent low frequency contribution during movement, with theta synchrony building gradually while high beta having the most prominent effect immediately following the cue. There was a relatively sharp, opposite transition point in both the spectral and connectivity tilt at approximately 35 Hz. These findings support the hypothesis that task-relevant high-frequency spectral activity is stochastic and that the decrease in high-frequency synchrony may facilitate enhanced low frequency phase coupling and interregional communication. Thus, the “connectivity tilt” may characterize behaviorally meaningful cortical interactions.

Precordial activation sequences from low frequency analysis in left bundle branch block patients: left bundle branch area pacing vs right ventricular pacing

Abstract Introduction Left bundle branch area pacing (LBBAP) provides a more synchronous and physiological ventricular activation than conventional right ventricular pacing (RVP) in LBBB patients. QRS duration (QRSd) is the standard measurement for assessing depolarization synchrony, but it only provides information about the activation time and not about the activation sequence. Purpose Our aim is to assess the activation sequence by precordial activation delay (pAD) using a low-frequency (LF) ECG method comparing baseline and paced ECG in LBBAP and RVP patients. Methods Twelve-lead ECGs recordings were acquired from 29 patients with LBBB (16 LBBAP and 13 RVP) after 24 hours of sequential LBBAP or RVP. LF-ECG was employed for QRS-complex analysis. The activation time for each lead was computed and an activation sequence constructed by linking them. pAD was calculated as the time between the first and the last lead activation. pAD provides information about both, the delay in ventricular depolarization as indicated by its magnitude, and the depolarization direction (as it can take a positive or negative value indicating a left or right ventricle delay, respectively). Results At baseline, both groups (LBBAP and RVP) showed the latest activation at V5-V6, supported by positive median pAD values with no statistically significant differences between both groups (50 (21, 65) vs. 54 (17, 67) ms, p=0.93). LBBAP reduced V6 delay and pAD values compared to the baseline QRS (basal: 50 (21, 65) vs. paced: 2 (-18, 25) ms, p&amp;lt;0.001) while RVP did not exhibit any difference (basal: 54 (17, 67) vs. paced: 36 (19, 53) ms, p=0.33). LBBAP provided lower pAD values when compared to RVP (2 (-18, 25) vs. 36 (19, 53) ms, p&amp;lt;0.01). Conclusions pAD measured using a LF-ECG analysis is a feasible method to evaluate depolarization synchrony and provides complementary information to QRSd. In contrast to RVP, LBBAP generates a physiological ventricular activation sequence in patients with LBBB.Baseline patients characteristicsVentricular activation sequences and pAD