Response Latency Research Articles

Click train elicited local gamma synchrony: differing performance and pharmacological responsivity of primary auditory and prefrontal cortices

Auditory neural networks in the brain naturally entrain to rhythmic stimuli. Such synchronization is an accessible index of local network performance as captured by EEG. Across species, click trains delivered ∼ 40 Hz show strong entrainment with primary auditory cortex (Actx) being a principal source. Imaging studies have revealed additional cortical sources, but it is unclear if they are functionally distinct. Since auditory processing evolves hierarchically, we hypothesized that local synchrony would differ between between primary and association cortices. In female SD rats (N = 12), we recorded 40 Hz click train-elicited gamma oscillations using epidural electrodes situated at two distinct sites; one above the prefrontal cortex (PFC) and another above the Actx, after dosing with saline (1 ml/kg, sc) or the NMDA antagonist, MK801 (0.025, 0.05 or 0.1 mpk), in a blocked crossover design. Post-saline, both regions showed a strong 40 Hz auditory steady state response (ASSR). The latencies for the N1 response were ∼ 16 ms (Actx) and ∼ 34 ms (PFC). Narrow band (38–42 Hz) gamma oscillations appeared rapidly (<40 ms from stim onset at Actx but in a more delayed fashion (∼200 ms) at PFC. MK801 augmented gamma synchrony at Actx while dose-dependently disrupting at the PFC. Event-related gamma (but not beta) coherence, an index of long-distance connectivity, was disrupted by MK801. In conclusion, local network gamma synchrony in a higher order association cortex performs differently from that of the primary auditory cortex. We discuss these findings in the context of evolving sound processing across the cortical hierarchy.

Cervical and ocular vestibular-evoked myogenic potentials test results and its relation to vestibular signs and symptoms in individuals with vestibular migraine

ObjectiveThe objective of the present study was to characterize the response rate, latency, and amplitude parameters of the cervical and ocular vestibular evoked myogenic potentials in individuals with vestibular migraine. The objective was also to describe the signs and symptoms exhibited by individuals with vestibular migraine and find out an association with VEMP results.MethodThirty individuals with a diagnosis of vestibular migraine and thirty healthy individuals participated in the study. The diagnosis of the vestibular migraine was made based on the diagnosis criteria given by the Barany Society and the International Headache Society. Cervical and ocular vestibular evoked myogenic potentials were recorded using 500 Hz tone burst stimulus for all the participants in both groups.ResultsThe latency was prolonged, and the amplitude was reduced for both the cervical and ocular vestibular evoked myogenic potentials in individuals with vestibular migraine compared with healthy individuals. There was no association between signs and symptoms exhibited by vestibular migraine individuals and VEMP results.ConclusionsBoth the sacullocollic and otolith ocular pathways are affected in vestibular migraine. Hence, there is a necessity for vestibular evaluation in all patients with vestibular migraine to understand the spectrum of the pathology.

Deciphering the Role of the Nucleus Accumbens Shell Area on Spatial Memory Deficits Induced by Neuropathic Pain in Rats

The nucleus accumbens shell (NAcSh) is a major structure associated with distinct aspects of reward and mnemonic information encoding, relying on spatial data to define optimal behavioral strategies. Chronic pain-derived striatal plasticity is considered one underpinning cause of working memory (WM) impairments. However, it is unclear how the NAcSh is involved in these spatial deficits. To address this, we evaluated the impact of unilateral local NAcSh electrical lesions during the execution of a food-reinforced eight-shaped spatial alternation WM task. Behavioral performance was assessed in rats after the onset of the neuropathic pain model—spared nerve injury (SNI). Our findings indicate that the induction of SNI and/or NAcSh lesions did not significantly impact the animals’ performance accuracy or motor activity during the execution of the behavioral task, but altered their response latency patterns. In addition, these manipulations did not induce significant antinociceptive effects. Collectively, these results suggest that the NAcSh may participate in specific aspects of spatial information integration and processing under neuropathic pain conditions.

Functional and structural maturation of auditory cortex from 2 months to 2 years old.

In school-age children, the myelination of the auditory radiation thalamocortical pathway is associated with the latency of auditory evoked responses, with the myelination of thalamocortical axons facilitating the rapid propagation of acoustic information. Little is known regarding this auditory system function-structure association in infants and toddlers. The present study tested the hypothesis that maturation of auditory radiation white-matter microstructure (e.g., fractional anisotropy (FA); measured using diffusion-weighted MRI) is associated with the latency of the infant auditory response (P2m measured using magnetoencephalography, MEG) in a cross-sectional (2 to 24 months) as well as longitudinal cohort (2 to 29 months) of typically developing infants and toddlers. In the cross-sectional sample, non-linear maturation of P2m latency and auditory radiation diffusion measures were observed. After removing the variance associated with age in both P2m latency and auditory radiation diffusion measures, auditory radiation still accounted for significant variance in P2m latency. In the longitudinal sample, latency and FA associations could be observed at the level of a single child. Findings provide strong support for a contribution of auditory radiation white matter to rapid cortical auditory encoding processes in infants.

Using reaction time procedures to assess implicit attitudes toward violence in a nonconvicted male sample.

In this study, we sought to capture implicit attitudes toward violence by administering response latency measures. We then examined their associations with explicit (e.g., assessed with self-report) attitudes toward violence and self-reported violent behavior in a combined sample of males from a Canadian university and males from the general community (N = 251; 156 students and 95 community members). To date, there have been mixed findings regarding these associations; some of this inconsistency may be due to the difficulty in accurately conceptualizing and assessing implicit attitudes toward violence. Therefore, we administered three response latency measures to assess this construct: a violence evaluation implicit association test (VE-IAT), a personalized VE-IAT (P-VE-IAT), and a violence evaluation relational responding task, along with three self-report measures of explicit attitudes toward violence and three self-report measures of violent behavior. More positive implicit attitudes toward violence were related to more positive explicit attitudes toward violence (for VE-IAT and P-VE-IAT; r = 0.18 to 0.22), greater likelihood of violence (for VE-IAT; r = 0.18 and for P-VE-IAT; r = 0.16), and greater propensity for violence (for the VE-IAT; r = 0.16). All measures of explicit attitudes toward violence and violent behavior were moderately to strongly associated with one another (r = 0.42 to 0.81). Furthermore, implicit attitudes toward violence explained additional variance in some violent outcomes above explicit attitudes alone. Our findings suggest that scores on certain reaction time measures are important for understanding likelihood and propensity for violence, especially when combined with explicit attitude measures.

Musical experience enhances time discrimination: Evidence from cortical responses.

Time discrimination, a critical aspect of auditory perception, is influenced by numerous factors. Previous research has suggested that musical experience can restructure the brain, thereby enhancing time discrimination. However, this phenomenon remains underexplored. In this study, we seek to elucidate the enhancing effect of musical experience on time discrimination, utilizing both behavioral and electroencephalogram methodologies. Additionally, we aim to explore, through brain connectivity analysis, the role of increased connectivity in brain regions associated with auditory perception as a potential contributory factor to time discrimination induced by musical experience. The results show that the music-experienced group demonstrated higher behavioral accuracy, shorter reaction time, and shorter P3 and mismatch response latencies as compared to the control group. Furthermore, the music-experienced group had higher connectivity in the left temporal lobe. In summary, our research underscores the positive impact of musical experience on time discrimination and suggests that enhanced connectivity in brain regions linked to auditory perception may be responsible for this enhancement.

Optimizing CNN inference speed over big social data through efficient model parallelism for sustainable web of things

The rapid development of artificial intelligence and networking technologies has catalyzed the popularity of intelligent services based on deep learning in recent years, which in turn fosters the advancement of Web of Things (WoT). Big social data (BSD) plays an important role during the processing of intelligent services in WoT. However, intelligent BSD services are computationally intensive and require ultra-low latency. End or edge devices with limited computing power cannot realize the extremely low response latency of those services. Distributed inference of deep neural networks (DNNs) on various devices is considered a feasible solution by allocating the computing load of a DNN to several devices. In this work, an efficient model parallelism method that couples convolution layer (Conv) split with resource allocation is proposed. First, given a random computing resource allocation strategy, the Conv split decision is made through a mathematical analysis method to realize the parallel inference of convolutional neural networks (CNNs). Next, Deep Reinforcement Learning is used to get the optimal computing resource allocation strategy to maximize the resource utilization rate and minimize the CNN inference latency. Finally, simulation results show that our approach performs better than the baselines and is applicable for BSD services in WoT with a high workload.

Effects of post-saccadic oscillations on visual processing times.

Saccadic eye movements enable us to search for the target of interest in a crowded scene or, in the case of goal-directed saccades, to simply bring the image of the peripheral target to the very centre of the fovea. This mechanism extends the use of the superior image processing performance of the fovea over a large visual field. We know that visual information is processed quickly at the end of each saccade but estimates of the times involved remain controversial. This study aims to investigate the processing of visual information during post fixation oscillations of the eyeball. A new psychophysical test measures the combined eye movement response latencies, including fixation duration and visual processing times. When the test is used in conjunction with an eye tracker, each component that makes up the 'integrated saccade latency' time, from the onset of the peripheral stimulus to the correct interpretation of the information carried by the stimulus, can be measured and the discrete components delineated. The results show that the time required to process and encode the stimulus attribute of interest at the end of a saccade is longer than the time needed to carry out the same task in the absence of an eye movement. We propose two principal hypotheses, each of which can account for this finding. 1. The known inhibition of afferent retinal signals during fast eye movements extends beyond the end point of the saccade. 2. The extended visual processing times measured when saccades are involved are caused by the transient loss of spatial resolution due to eyeball instability during post-saccadic oscillations. The latter can best be described as retinal image smear with greater loss of spatial resolution expected for stimuli of low luminance contrast.

Detecting lies in investigative interviews through the analysis of response latencies and error rates to unexpected questions

In this study, we propose an approach to detect deception during investigative interviews by integrating response latency and error analysis with the unexpected question technique. Sixty participants were assigned to an honest (n = 30) or deceptive group (n = 30). The deceptive group was instructed to memorize the false biographical details of a fictitious identity. Throughout the interviews, participants were presented with a randomized sequence of control, expected, and unexpected open-ended questions about identity. Responses were audio recorded for detailed examination. Our findings indicate that deceptive participants showed markedly longer latencies and higher error rates when answering expected (requiring deception) and unexpected questions (for which premeditated deception was not possible). Longer response latencies were also observed in participants attempting deception when answering control questions (which necessitated truthful answers). Moreover, a within-subject analysis highlighted that responding to unexpected questions significantly impaired individuals’ performance compared to answering control and expected questions. Leveraging machine-learning algorithms, our approach attained a classification accuracy of 98% in distinguishing deceptive and honest participants. Additionally, a classification analysis on single response levels was conducted. Our findings underscore the effectiveness of merging response latency metrics and error rates with unexpected questioning as a robust method for identity deception detection in investigative interviews. We also discuss significant implications for enhancing interview strategies.

Quantifying response latency in video surveillance systems using object detection techniques

Quantifying response latency in video surveillance systems using object detection techniques

The family size effect in visual and auditory word recognition

ABSTRACT Words with larger morphological families elicit shorter response times in visual lexical decision, but in auditory lexical decision, family size effects have been reported to be facilitative, absent, or inhibitory. We revisit the auditory family size effect and different family size definitions by re-analysing data from two large lexical decision experiments. The results suggest that words with larger families elicit smaller response latencies not only in visual but also in auditory lexical decision. However, in auditory lexical decision, this effect is insignificant when the word contains a prefix. In both modalities, it is the degree of semantic similarity and the degree of form overlap between a word and its family members, rather than the mere presence of overlap, that seem to drive the family size effect.

Desloratadine ameliorates paclitaxel-induced peripheral neuropathy and hypersensitivity reactions in mice.

Paclitaxel (PTX) serves as a primary chemotherapy agent against diverse solid tumors including breast cancer, lung cancer, head and neck cancer and ovarian cancer, having severe adverse effects including PTX-induced peripheral neuropathy (PIPN) and hypersensitivity reactions (HSR). A recommended anti-allergic agent diphenhydramine (DIP) has been used to alleviate PTX-induced HSR. Desloratadine (DLT) is a third generation of histamine H1 receptor antagonist, but also acted as a selective antagonist of 5HTR2A. In this study we investigated whether DLT ameliorated PIPN-like symptoms in mice and the underlying mechanisms. PIPN was induced in male mice by injection of PTX (4 mg/kg, i.p.) every other day for 4 times. The mice exhibited 50% reduction in mechanical threshold, paw thermal response latency and paw cold response latency compared with control mice. PIPN mice were treated with DLT (10, 20 mg/kg, i.p.) 30 min before each PTX administration in the phase of establishing PIPN mice model and then administered daily for 4 weeks after the model wasestablished. We showed that DLT administration dose-dependently elevated the mechanical, thermal and cold pain thresholds in PIPN mice, whereas administration of DIP (10 mg/kg, i.p.) had no ameliorative effects on PIPN-like symptoms. We found that the expression of 5HTR2A was selectively elevated in the activated spinal astrocytes of PIPN mice. Spinal cord-specific 5HTR2A knockdown by intrathecal injection of AAV9-5Htr2a-shRNA significantly alleviated the mechanical hyperalgesia, thermal and cold hypersensitivity in PIPN mice, while administration of DLT (20 mg/kg) did not further ameliorate PIPN-like symptoms. We demonstrated that DLT administration alleviated dorsal root ganglion neuronal damage and suppressed sciatic nerve destruction, spinal neuron apoptosis and neuroinflammation in the spinal cord of PIPN mice. Furthermore, we revealed that DLT administration suppressed astrocytic neuroinflammation via the 5HTR2A/c-Fos/NLRP3 pathway and blocked astrocyte-neuron crosstalk by targeting 5HTR2A. We conclude that spinal 5HTR2A inhibition holds promise as a therapeutic approach for PIPN and we emphasize the potential of DLT as a dual-functional agent in ameliorating PTX-induced both PIPN and HSR in chemotherapy. In summary, we determined that spinal 5HTR2A was selectively activated in PIPN mice and DLT could ameliorate the PTX-induced both PIPN- and HSR-like pathologies in mice. DLT alleviated the damages of DRG neurons and sciatic nerves, while restrained spinal neuronal apoptosis and CGRP release in PIPN mice. The underlying mechanisms were intensively investigated by assay against the PIPN mice with 5HTR2A-specific knockdown in the spinal cord by injection of adeno-associated virus 9 (AAV9)-5Htr2a-shRNA. DLT inhibited astrocytic NLRP3 inflammasome activation-mediated spinal neuronal damage through 5HTR2A/c-FOS pathway. Our findings have supported that spinal 5HTR2A inhibition shows promise as a therapeutic strategy for PIPN and highlighted the potential advantage of DLT as a dual-functional agent in preventing against PTX-induced both PIPN and HSR effects in anticancer chemotherapy.

Anti-neurofascin-155 antibody mediated a distinct phenotype of chronic inflammatory demyelinating polyradiculoneuropathy.

To investigate Ranvier's autoantibodies prevalence and isotypes in various peripheral neuropathy variants, compare clinical features between seronegative and seropositive patients, and elucidate immune mechanisms underlying antibody generation. Antibodies against anti-neurofascin-155 (NF155), NF186, contactin-1 (CNTN1), CNTN2, contactin-associated protein 1 (CASPR1), and CASPR2 were identified through cell-based assays. Plasma cytokines were analyzed in anti-NF155 antibody-positive chronic inflammatory demyelinating polyneuropathy (NF155+ CIDP) and Ranvier's antibodies-negative CIDP (Ab- CIDP) patients using a multiplexed fluorescent immunoassay, validated in vitro in a cell culture model. In 368 plasma samples, 50 Ranvier's autoantibodies were found in 45 individuals, primarily in CIDP cases (25 out of 69 patients) and in 10 out of 122 Guillain-Barré syndrome patients. Anti-NF155 and CNTN1-IgG were exclusive to CIDP. Fourteen samples were NF155-IgG, primarily IgG4 subclass, linked to CIDP features including early onset, tremor, sensory disturbance, elevated CSF protein, prolonged motor latency, conduction block, and poor treatment response. NF155-IgG had low sensitivity (20.28%) but high specificity (100%) for CIDP, rising to 88.88% with tremor and prolonged motor latency. Cytokine profiling in NF155+ CIDP revealed distinct immune responses involving helper T cells, toll-like receptor pathways. Some NF155+ CIDP patients had circulating NF155-specific B cells producing NF155-IgG without antigen presence, suggesting therapeutic potential. The study emphasizes the high specificity and sensitivity of NF155-IgG for diagnosing CIDP characterized by distinctive features. Further investigation into circulating NF155-specific B cell phenotypes may pave the way for B cell directed therapy.

MADDPG-Based Offloading Strategy for Timing-Dependent Tasks in Edge Computing

With the increasing popularity of the Internet of Things (IoT), the proliferation of computation-intensive and timing-dependent applications has brought serious load pressure on terrestrial networks. In order to solve the problem of computing resource conflict and long response delay caused by concurrent application service applications from multiple users, this paper proposes an improved edge computing timing-dependent, task-offloading scheme based on Multi-Agent Deep Deterministic Policy Gradient (MADDPG) that aims to shorten the offloading delay and improve the resource utilization rate by means of resource prediction and collaboration among multiple agents to shorten the offloading delay and improve the resource utilization. First, to coordinate the global computing resource, the gated recurrent unit is utilized, which predicts the next computing resource requirements of the timing-dependent tasks according to historical information. Second, the predicted information, the historical offloading decisions and the current state are used as inputs, and the training process of the reinforcement learning algorithm is improved to propose a task-offloading algorithm based on MADDPG. The simulation results show that the algorithm reduces the response latency by 6.7% and improves the resource utilization by 30.6% compared with the suboptimal benchmark algorithm, and it reduces nearly 500 training rounds during the learning process, which effectively improves the timeliness of the offloading strategy.

Binocular receptive-field construction in the primary visual cortex

ON and OFF thalamic afferents from the two eyes converge in the primary visual cortex to form binocular receptive fields. The receptive fields need to be diverse to sample our visual world but also similar across eyes to achieve binocular fusion. It is currently unknown how the cortex balances these competing needs between receptive-field diversity and similarity. Our results demonstrate that receptive fields in the cat visual cortex are binocularly matched with exquisite precision for retinotopy, orientation/direction preference, orientation/direction selectivity, response latency, and ON-OFF polarity/structure. Specifically, the average binocular mismatches in retinotopy and ON-OFF structure are tightly restricted to 1/20 and 1/5 of the average receptive-field size but are still large enough to generate all types of binocular disparity tuning. Based on these results, we conclude that cortical receptive fields are binocularly matched with the high precision needed to facilitate binocular fusion while allowing restricted mismatches to process visual depth.

Ocular vestibular evoked myogenic potentials in different types of amblyopia

ABSTRACT Clinical relevance The visual system plays an important role in the development of the vestibular-ocular reflex (VOR). In clinical practice, the ocular vestibular evoked myogenic potential (oVEMP) test is used to assess contralateral VOR. Background This study sought to compare the oVEMP in patients with anisometropic, strabismic, and mixed amblyopia using unilateral and bilateral (simultaneous binaural) stimulation. Methods Forty-two amblyopic patients (20 males and 22 females) with a mean age of 10.48 ± 4.00 years (range: 5 – 20 years) were examined. The Titmus stereopsis test, alternate cover test, and best-corrected visual acuity were evaluated. Patients were divided into three groups: anisometropic, strabismic, and mixed amblyopia. The oVEMP responses including the amplitude of electrical activity (n1-p1 complex) and the latencies (n1 and p1) of the VOR responses were recorded under unilateral and bilateral stimulations. Results In the anisometropic and strabismic group, n1 latency was significantly faster in the non-amblyopic eyes compared to amblyopic eyes (Z = −2.04, p = 0.042, andZ = −2.54, p = 0.024 respectively). Mean p1 latency was significantly faster in the non-amblyopic eyes compared to the amblyopic eyes of the strabismic group (Z = −2.31, p = 0.011)In all groups, the p1 latency was faster in the non-amblyopic eye compared to bilateral stimulation (all, p < 0.05). In all groups, the n1-p1 amplitude was not significantly different between the two eyes, and between each eye and bilateral stimulation (all, p > 0.05). No significant correlation was found between the depth of amblyopia and n1 and p1 responses (all, p > 0.05). In all groups there was no significant difference in the latency of n1 and p1 between the amblyopic eye and bilateral stimulation (all, p > 0.05). Conclusion Regardless of its type, amblyopia affects vestibular-ocular reflex responses. Further research is warranted to clarify the effect of the disease and its treatment on the ocular-vestibular system.

Automated escape system: identifying prey's kinematic and behavioral features critical for predator evasion.

Identifying the kinematic and behavioral variables of prey that influence the evasion from predator attacks remains challenging. To address this challenge, we have developed an automated escape system that responds quickly to an approaching predator and pulls the prey away from the predator rapidly, as real prey. Reaction distance, response latency, escape speed, and other variables can be adjusted in the system. By repeatedly measuring the response latency and escape speed of the system, we demonstrated the system's ability to exhibit fast and rapid responses while maintaining consistency across successive trials. Using the live predatory fish species, Coreoperca kawamebari, we show that escape speed and reaction distance significantly affect the outcome of predator-prey interactions. These findings indicate that the developed escape system is useful for identifying kinematic and behavioral features of prey that are critical for predator evasion, as well as for measuring the performance of predators.

LLMEffiChecker:Understanding and Testing Efficiency Degradation of Large Language Models

Large Language Models (LLMs) have received much recent attention due to their human-level accuracy. While existing works mostly focus on either improving accuracy or testing accuracy robustness, the computation efficiency of LLMs, which is of paramount importance due to often vast generation demands and real-time requirements, has surprisingly received little attention. In this paper, we make the first attempt to understand and test potential computation efficiency robustness in state-of-the-art LLMs. By analyzing the working mechanism and implementation of 20,543 public-accessible LLMs, we observe a fundamental property in LLMs that could be manipulated in an adversarial manner to reduce computation efficiency significantly. Our interesting observation is that the output length determines the computation efficiency of LLMs instead of the input, where the output length depends on two factors: an often sufficiently large yet pessimistic pre-configured threshold controlling the max number of iterations and a runtime generated end of sentence (EOS) token. Our key motivation is to generate test inputs that could sufficiently delay the generation of EOS such that LLMs would have to go through enough iterations to satisfy the pre-configured threshold. We present LLMEffiChecker , which can work under both white-box setting and black-box setting. In the white-box scenario, LLMEffiChecker develops a gradient-guided technique that searches for a minimal and unnoticeable perturbation at character-level, token-level, and structure-level. In the black-box scenario, LLMEffiChecker employs a causal inference-based approach to find critical tokens and similarly applies three levels of imperceptible perturbation to them. Both the white-box and black-box settings effectively delay the appearance of EOS, compelling these inputs to reach the naturally-unreachable threshold. To demonstrate the effectiveness of LLMEffiChecker , we conduct a systematic evaluation on nine public-available LLMs: Google T5, AllenAI WMT14, Helsinki-NLP translator, Facebook FairSeq, UNICAMP-DL translator, MarianMT, Google FLAN-T5, MBZUAI LaMini-GPT and Salesforce CodeGen. Experimental results show that LLMEffiChecker can increase on average LLMs’ response latency and energy consumption by 325% to 3244% and 344% to 3616%, respectively, by perturbing just one character or token in the input sentence. Our case study shows that inputs generated by LLMEffiChecker significantly affect the battery power in real-world mobile devices ( i.e. , drain more than 30 times battery power than normal inputs).

Images with harder-to-reconstruct visual representations leave stronger memory traces.

Much of what we remember is not because of intentional selection, but simply a by-product of perceiving. This raises a foundational question about the architecture of the mind: how does perception interface with and influence memory? Here, inspired by a classic proposal relating perceptual processing to memory durability, the level-of-processing theory, we present a sparse coding model for compressing feature embeddings of images, and show that the reconstruction residuals from this model predict how well images are encoded into memory. In an open memorability dataset of scene images, we show that reconstruction error not only explains memory accuracy, but also response latencies during retrieval, subsuming, in the latter case, all of the variance explained by powerful vision-only models. We also confirm a prediction of this account with 'model-driven psychophysics'. This work establishes reconstruction error as an important signal interfacing perception and memory, possibly through adaptive modulation of perceptual processing.

Dynamic edge clustering and task scheduling for edge assisted metaverse system in the field of remote work and collaboration

SummaryThe metaverse, a future digital world for living, working, learning, and interacting, is rapidly gaining significance, particularly in the domain of remote work and collaboration. This emerging digital landscape demands high‐performance, low‐latency, and scalable services to provide an immersive user experience. The current technology used in metaverse systems has some limitations, which emphasize the importance of adopting emerging technologies like Edge Computing (EC). However, as the number of users and data volume increases, it can impact both system performance and scalability of the edge‐assisted metaverse system. Additionally, the uneven distribution of edge servers can cause inconsistencies and result in high latency. To overcome these challenges, this paper proposes a dynamic edge clustering and task scheduling approach for edge‐assisted metaverse systems (DTAM) in the field of remote work and collaboration. The proposed approach addresses the challenges of high user volume and uneven resource distribution by incorporating dynamic clustering and edge server assistance to improve clustering performance. Furthermore, a Prioritized Experience Replay‐based Deep Q‐learning algorithm with state augmentation (PERDQSA) for task scheduling is introduced to improve sample efficiency and performance. The performance of the proposed DTAM is evaluated against existing techniques, and experimental results demonstrate its significant superiority in terms of specific metrics such as bandwidth, task response time, energy efficiency, and latency. The experiments demonstrated that DTAM outperforms Transformation‐based Edge Computing Deep Q‐Learning (TransEC‐DQL) in several key metrics. Specifically, DTAM achieves 28.5% reduction in latency, 13.7% reduction in response time, and 6.4% improvement in bandwidth compared to TransEC‐DQL. These results signify that DTAM can deliver a significantly enhanced user experience in the metaverse, particularly in the context of remote work and collaboration.