Temporal Structure Research Articles

Graphene Plasmonic Time Crystals

The concept of photonic crystals has recently been extended to the time domain and attracted great interest. Unfortunately, realizing photonic time crystals is a challenging task due to the practical difficulty in modulating dielectric constants with large modulation depth. This problem can be resolved using graphene, the conductivity of which is tunable with significantly large contrast. Herein, graphene plasmonic time crystals, as new kinds of photonic time crystals in atomically thin 2D material, are proposed and their optical properties are investigated. Their band structures are analytically calculated and the propagations of graphene plasmons in temporal crystalline structures are numerically evaluated. Periodically driven by temporally modulating the Fermi energy, graphene plasmons exhibit in‐gap amplification and defect‐immune topological edge states, revealing the nature as plasmonic time crystals. Graphene plasmonic time crystals are realized soon after this proposal due to the possibility of modulating its conductivity with large contrast by simple electrical gating.

Mesial temporal lobe spiking reveals distinct patterns of blood oxygen level-dependent functional magnetic resonance imaging activation using simultaneous intracranial electroencephalography-functional magnetic resonance imaging.

Temporal lobe epilepsy (TLE) has a high probability of becoming drug resistant and is frequently considered for surgical intervention. However, 30% of TLE cases have nonlesional magnetic resonance imaging (MRI) scans, which is associated with worse surgical outcomes. Characterizing interactions between temporal and extratemporal structures in these patients may help understand these poor outcomes. Simultaneous intracranial electroencephalography-functional MRI (iEEG-fMRI) can measure the hemodynamic changes associated with interictal epileptiform discharges (IEDs) recorded directly from the brain. This study was designed to characterize the whole brain patterns of IED-associated fMRI activation recorded exclusively from the mesial temporal lobes of patients with nonlesional TLE. Eighteen patients with nonlesional TLE undergoing iEEG monitoring with mesial temporal IEDs underwent simultaneous iEEG-fMRI at 3 T. IEDs were marked, and statistically significant clusters of fMRI activation were identified. The locations of IED-associated fMRI activation for each patient were determined, and patients were grouped based on the location and pattern of fMRI activation. Two patterns of IED-associated fMRI activation emerged: primarily localized (n = 7), where activation was primarily located within the ipsilateral temporal lobe, and primarily diffuse (n = 11), where widespread bilateral extratemporal activation was detected. The primarily diffuse group reported significantly fewer focal to bilateral tonic-clonic seizures and had better postsurgical outcomes. Simultaneous iEEG-fMRI can measure the hemodynamic changes associated with focal IEDs not visible on scalp EEG, such as those arising from the mesial temporal lobe. Significant fMRI activation associated with these IEDs was observed in all patients. Two distinct patterns of IED-associated activation were seen: primarily localized to the ipsilateral temporal lobe and more widespread, bilateral activation. Patients with widespread IED associated-activation had fewer focal to bilateral tonic-clonic seizures and better postsurgical outcome, which may suggest a neuroprotective mechanism limiting the spread of ictal events.

Gender and age-specific patterns of ambulance calls in Khanty-Mansiysk depending on the epidemiological situation

BACKGROUND: The number of ambulance calls serves as an objective indicator of the disruption in population health associated with maladaptation or an increase in health disorders in harsh conditions of the North. This becomes especially apparent when the epidemiological situation shifts, highlighting the importance of this issue. AIM: To study the gender- and age-specific patterns of emergency calls for ambulance services in the population of Khanty-Mansiysk during varying epidemiological conditions using long-term monitoring data. MATERIAL AND METHODS: Data on daily counts of ambulance calls was obtained from the for the period from 2015 to 2021 stratified by age and gender. The data were analyzed using wavelet analysis. RESULTS: When analyzing gender disparities during a pandemic, the coefficient representing the ratio of calls made by women to men decreased as the number of calls made by men increased. The distribution of calls by age revealed two distinct risk groups: young children and older adults. During the pandemic, there were no significant qualitative changes in the distribution of calls. Several scenarios of desynchronosis induced by the COVID-19 pandemic were identified. In infants, the changes in the epidemiological situation did not affect constant rhythms. The changes in the constant circadian rhythms to long-term and intercalary intra-annual rhythms were observed among children and youth. In adolescents and young adults, the pandemic acted as a synchronizer. In older age-groups, the circadian rhythms were maintained throughout the entire period. The period of the pandemic was characterized by addition of rhythms with a shorter period. CONCLUSION: The distribution of ambulance calls across age-groups is characterized by the presence of two distinct risk groups — early childhood and the 2nd adult age. During the pandemic, the structure of calls did not demonstrate qualitative changes. The COVID-19 pandemic was a desynchronizing factor in the temporal structure of health disorders affecting long-term and near-annual rhythms and inducing the intercalary intra-annual rhythms.

Tau propagation in the brain olfactory circuits is associated with smell perception changes in aging

The direct access of olfactory afferents to memory-related cortical systems has inspired theories about the role of the olfactory pathways in the development of cortical neurodegeneration in Alzheimer’s disease (AD). In this study, we used baseline olfactory identification measures with longitudinal flortaucipir and PiB PET, diffusion MRI of 89 cognitively normal older adults (73.82 ± 8.44 years; 56% females), and a transcriptomic data atlas to investigate the spatiotemporal spreading and genetic vulnerabilities of AD-related pathology aggregates in the olfactory system. We find that odor identification deficits are predominantly associated with tau accumulation in key areas of the olfactory pathway, with a particularly strong predictive power for longitudinal tau progression. We observe that tau spreads from the medial temporal lobe structures toward the olfactory system, not the reverse. Moreover, we observed a genetic background of odor perception-related genes that might confer vulnerability to tau accumulation along the olfactory system.

Timescales of Autogenic Noise in River Bedform Evolution and Stratigraphy

AbstractBedform evolution and preserved cross strata are known to respond to floods. However, it is unclear if autogenic dynamics mask the flood signal in bedform evolution and cross strata. To address this, we characterize the temporal structure of autogenic noise in steady‐state bedform evolution in a physical experiment. Results reveal the existence of bedform groups—quasi‐stable collections of bedforms—that migrate at a similar speed as bedforms. We find that bedform and bedform‐group turnover timescales are the key autogenic timescales of bed evolution that set the transition time‐periods between different noise regimes in bedform evolution. Results suggest that bedform‐group turnover timescale sets the lower limit for detecting flood signals in bedform evolution, and floods with duration shorter than bedform turnover timescale can be severely degraded in bedform evolution and cross strata. Our work provides a new framework for interrogating fluvial cross strata for reconstruction of past floods.

Temporal local clustering coefficient uncovers the hidden pattern in temporal networks.

Identifying and extracting topological characteristics are essential for understanding associated structures and organizational principles of complex networks. For temporal networks where the network topology varies with time, beyond the classical patterns such as small-worldness and scale-freeness extracted from the perspective of traditional aggregated static networks, the temporality and simultaneity of time-varying interactions should also be included. Here we extend the traditional analysis on the local clustering coefficient C in static networks and study the dynamical local clustering coefficient of temporal networks. We demonstrate that the temporal local clustering coefficient TC conveys the hidden information of nodes' neighboring connectance when interactions occur at various rhythms. By systematically analyzing various empirical datasets, we find that TC uncovers different interaction patterns in different types of temporal networks. Specifically, we show that TC has a strong positive correlation with C in efficiency-related networks, whereas they are uncorrelated in social activity-related networks. Moreover, TC helps to exclude interference from accidental interactions and reflect the actual clustering properties of network nodes. Our results shed light on the importance of digging into dynamical characteristics to fundamentally understand the underlying temporal structures of real complex systems.

A statistical population reconstruction model for wildlife populations: A case study with white‐tailed deer and fisher

AbstractHarvested wildlife populations should ideally be monitored to inform harvest policies and decision‐making to help achieve management objectives. When the age of harvested individuals can be obtained, these data (i.e., age‐at‐harvest data) can be used to estimate trends of abundances, demographic rates, and harvest probabilities by the statistical reconstruction of the living population. This approach was developed primarily within the frequentist framework and requires the inclusion of auxiliary data (e.g., radiotelemetry data). We developed a novel Bayesian hierarchical approach allowing the population reconstruction from the definition of the species' life cycle without auxiliary data. The hierarchical model assumes that individuals are harvested from an open population whose fluctuations result from demographic processes, and the definition of a superpopulation composed of pseudo‐individuals from which the harvested population is drawn. We evaluated the ability of our model to estimate abundances, survival, recruitment, and harvest probabilities based on simulations guided by the demographic processes of a long‐lived mammal population. We considered model performance across scenarios, including varying age and temporal structures, superpopulation size, and prior information. We showed how prior information selected based on life history characteristics affects the accuracy of estimated parameters. We found that the model estimates accurate demographic parameters and abundances when the age‐at‐harvest matrix comprises more than two age classes. Furthermore, an increase in demographic information (number of age groups and years) increased the precision of the estimated parameters. We apply our model to a population of harvested (2012–2021) white‐tailed deer (Odocoileus virginianus) and a mammalian carnivore, the fisher (Pekania pennanti), from Rhode Island, USA. Our model estimated biologically realistic population size and demographic rates for both species. Our approach provides robustness to track the population abundance of harvested species through time and estimate fundamental demographic parameters. Such results can be used to monitor whether population objectives are being met and whether harvest policy changes are required. Furthermore, this information can be critical for evaluating the effect of harvest on population growth and projecting trajectories of age‐structured populations under different harvest scenarios. Therefore, our framework can help to guide management decisions and species conservation.

Inter-subject correlation of electroencephalographic and behavioural responses reflects time-varying engagement with natural music.

Musical engagement can be conceptualized through various activities, modes of listening and listener states. Recent research has reported that a state of focused engagement can be indexed by the inter-subject correlation (ISC) of audience responses to a shared naturalistic stimulus. While statistically significant ISC has been reported during music listening, we lack insight into the temporal dynamics of engagement over the course of musical works-such as those composed in the Western classical style-which involve the formulation of expectations that are realized or derailed at subsequent points of arrival. Here, we use the ISC of electroencephalographic (EEG) and continuous behavioural (CB) responses to investigate the time-varying dynamics of engagement with functional tonal music. From a sample of adult musicians who listened to a complete cello concerto movement, we found that ISC varied throughout the excerpt for both measures. In particular, significant EEG ISC was observed during periods of musical tension that built to climactic highpoints, while significant CB ISC corresponded more to declarative entrances and points of arrival. Moreover, we found that a control stimulus retaining envelope characteristics of the intact music, but little other temporal structure, also elicited significantly correlated EEG and CB responses, though to lesser extents than the original version. In sum, these findings shed light on the temporal dynamics of engagement during music listening and clarify specific aspects of musical engagement that may be indexed by each measure.

Identifying behavioral links to neural dynamics of multifiber photometry recordings in a mouse social behavior network

Objective. Distributed hypothalamic-midbrain neural circuits help orchestrate complex behavioral responses during social interactions. Given rapid advances in optical imaging, it is a fundamental question how population-averaged neural activity measured by multi-fiber photometry (MFP) for calcium fluorescence signals correlates with social behaviors is a fundamental question. This paper aims to investigate the correspondence between MFP data and social behaviors. Approach: We propose a state-space analysis framework to characterize mouse MFP data based on dynamic latent variable models, which include a continuous-state linear dynamical system and a discrete-state hidden semi-Markov model. We validate these models on extensive MFP recordings during aggressive and mating behaviors in male-male and male-female interactions, respectively. Main results: Our results show that these models are capable of capturing both temporal behavioral structure and associated neural states, and produce interpretable latent states. Our approach is also validated in computer simulations in the presence of known ground truth. Significance: Overall, these analysis approaches provide a state-space framework to examine neural dynamics underlying social behaviors and reveals mechanistic insights into the relevant networks.

The role of hidden hearing loss in tinnitus: Insights from early markers of peripheral hearing damage

Since the presence of tinnitus is not always associated with audiometric hearing loss, it has been hypothesized that hidden hearing loss may act as a potential trigger for increased central gain along the neural pathway leading to tinnitus perception. In recent years, the study of hidden hearing loss has improved with the discovery of cochlear synaptopathy and several objective diagnostic markers. This study investigated three potential markers of peripheral hidden hearing loss in subjects with tinnitus: extended high-frequency audiometric thresholds, the auditory brainstem response, and the envelope following response. In addition, speech intelligibility was measured as a functional outcome measurement of hidden hearing loss. To account for age-related hidden hearing loss, participants were grouped according to age, presence of tinnitus, and audiometric thresholds. Group comparisons were conducted to differentiate between age- and tinnitus-related effects of hidden hearing loss. All three markers revealed age-related differences, whereas no differences were observed between the tinnitus and non-tinnitus groups. However, the older tinnitus group showed improved performance on low-pass filtered speech in noise tests compared to the older non-tinnitus group. These low-pass speech in noise scores were significantly correlated with tinnitus distress, as indicated using questionnaires, and could be related to the presence of hyperacusis. Based on our observations, cochlear synaptopathy does not appear to be the underlying cause of tinnitus. The improvement in low-pass speech-in-noise could be explained by enhanced temporal fine structure encoding or hyperacusis. Therefore, we recommend that future tinnitus research takes into account age-related factors, explores low-frequency encoding, and thoroughly assesses hyperacusis.

Aspectual Processing Shifts Visual Event Apprehension

AbstractWhat is the relationship between language and event cognition? Past work has suggested that linguistic/aspectual distinctions encoding the internal temporal profile of events map onto nonlinguistic event representations. Here, we use a novel visual detection task to directly test the hypothesis that processing telic versus atelic sentences (e.g., “Ebony folded a napkin in 10 seconds” vs. “Ebony did some folding for 10 seconds”) can influence whether the very same visual event is processed as containing distinct temporal stages including a well‐defined endpoint or lacking such structure, respectively. In two experiments, we show that processing (a)telicity in language shifts how people later construe the temporal structure of identical visual stimuli. We conclude that event construals are malleable representations that can align with the linguistic framing of events.

Mediating Mundane Life

Abstract The recent and ongoing exodus of Venezuelans to the surrounding Latin American region has sparked international humanitarian intervention. Drawing on research conducted in Brazil in late 2019, this article focuses on the state-led humanitarian response to Venezuelan migration and its collaborative efforts with the military and leading organizations. Looking at two sites of institutional care, I argue that temporal structures created by military-humanitarian agencies work to govern the everyday mobilities of urban migrants living without shelter, who are often framed as criminals or threats within neoliberal securitization narratives. This article further reveals conflicting temporalities with regard to the practice of waiting, whereby the act is viewed as risky when visible in urban public spaces but favored in institutional settings where it can be closely monitored.

Guidelines for estimating occupancy from autocorrelated camera trap detections

Abstract Site occupancy models (SOMs) are a common tool for studying the spatial ecology of wildlife. When observational data are collected using passive monitoring field methods, including camera traps or autonomous recorders, detections of animals may be temporally autocorrelated, leading to biased estimates and incorrectly quantified uncertainty. We presently lack clear guidance for understanding and mitigating the consequences of temporal autocorrelation when estimating occupancy models with camera trap data. We use simulations to explore when and how autocorrelation gives rise to biased or overconfident estimates of occupancy. We explore the impact of sampling design and biological conditions on model performance in the presence of autocorrelation, investigate the usefulness of several techniques for identifying and mitigating bias and compare performance of the SOM to a model that explicitly estimates autocorrelation. We also conduct a case study using detections of 22 North American mammals. We show that a join count goodness‐of‐fit test previously proposed for identifying clustered detections is effective for detecting autocorrelation across a range of conditions. We find that strong bias occurs in the estimated occupancy intercept when survey durations are short and detection rates are low. We provide a reference table for assessing the degree of bias to be expected under all conditions. We further find that discretizing data with larger windows decreases the magnitude of bias introduced by autocorrelation. In our case study, we find that detections of most species are autocorrelated and demonstrate how larger detection windows might mitigate the resulting bias. Our findings suggest that autocorrelation is likely widespread in camera trap data and that many previous studies of occupancy based on camera trap data may have systematically underestimated occupancy probabilities. Moving forward, we recommend that ecologists estimating occupancy from camera trap data use the join count goodness‐of‐fit test to determine whether autocorrelation is present in their data. If it is, SOMs should use large detection windows to mitigate bias and more accurately quantify uncertainty in occupancy model parameters. Ecologists should not use gaps between detection periods, which are ineffective at mitigating temporal structure in data and discard useful data.

A study on brain asymmetry in temporal lobe epilepsy

Objective: Temporal lobe epilepsy (TLE) accompanied by hippocampal sclerosis (HS) is the most common type of focal epilepsies. Hemispheric asymmetry is a feature of brain organization in both invertebrates and vertebrates and may be the key to some neurodegenerative diseases. In this context, we aimed to investigate the volumetric asymmetry difference in cerebral structures between TLE patients and the healthy control group, based on magnetic resonance imaging (MRI) data that may be used as a new neuroimaging marker for TLE cases. Patients and Methods: In this retrospective study the cranial MRIs of fourteen clinically manifesting, radiologically HS-identified, and diagnosed TLE patients and fourteen healthy individuals from the Radiology Department of Yeditepe University Hospital were evaluated. Volume measurements and asymmetry index (AI) calculations in the total brain, hippocampus, temporal lobe, amygdala, thalamus, nucleus accumbens (NAc), premotor cortex, primary and somatosensory cortices were performed using the medical NeuroQuant® software. A negative AI value represented asymmetry towards the right due to reduced left hemispheric volume; a positive AI value represented asymmetry towards the left due to reduced right hemispheric volume. Subsequently, differences in volume and asymmetric patterns were investigated among TLE subgroups (right and left-sided TLE) and controls. Results: The left-sided TLE patients showed significant bilateral total brain volume reduction compared to the control group. Significant ipsilateral volumetric declines were also detected in the premotor cortex, the temporal lobe, and NAc with remarkable asymmetry to the right side. No significant changes were detected in right-sided TLE patients compared to the other groups. Conclusion: Overall, findings suggest that TLE patients had volumetric alterations with symmetry changes beyond the mesial temporal structures. With further investigations, the asymmetry measures can provide additional knowledge for TLE diagnosis.

Enhancing the Diagnostic Utility of ASL Imaging in Temporal Lobe Epilepsy through FlowGAN: An ASL to PET Image Translation Framework.

Positron Emission Tomography (PET) using fluorodeoxyglucose (FDG-PET) is a standard imaging modality for detecting areas of hypometabolism associated with the seizure onset zone (SOZ) in temporal lobe epilepsy (TLE). However, FDG-PET is costly and involves the use of a radioactive tracer. Arterial Spin Labeling (ASL) offers an MRI-based quantification of cerebral blood flow (CBF) that could also help localize the SOZ, but its performance in doing so, relative to FDG-PET, is limited. In this study, we seek to improve ASL's diagnostic performance by developing a deep learning framework for synthesizing FDG-PET-like images from ASL and structural MRI inputs. We included 68 epilepsy patients, out of which 36 had well lateralized TLE. We compared the coupling between FDG-PET and ASL CBF values in different brain regions, as well as the asymmetry of these values across the brain. We additionally assessed each modality's ability to lateralize the SOZ across brain regions. Using our paired PET-ASL data, we developed FlowGAN, a generative adversarial neural network (GAN) that synthesizes PET-like images from ASL and T1-weighted MRI inputs. We tested our synthetic PET images against the actual PET images of subjects to assess their ability to reproduce clinically meaningful hypometabolism and asymmetries in TLE. We found variable coupling between PET and ASL CBF values across brain regions. PET and ASL had high coupling in neocortical temporal and frontal brain regions (Spearman's r > 0.30, p < 0.05) but low coupling in mesial temporal structures (Spearman's r < 0.30, p > 0.05). Both whole brain PET and ASL CBF asymmetry values provided good separability between left and right TLE subjects, but PET (AUC = 0.96, 95% CI: [0.88, 1.00]) outperformed ASL (AUC = 0.81; 95% CI: [0.65, 0.96]). FlowGAN-generated images demonstrated high structural similarity to actual PET images (SSIM = 0.85). Globally, asymmetry values were better correlated between synthetic PET and original PET than between ASL CBF and original PET, with a mean correlation increase of 0.15 (95% CI: [0.07, 0.24], p<0.001, Cohen's d = 0.91). Furthermore, regions that had poor ASL-PET correlation (e.g. mesial temporal structures) showed the greatest improvement with synthetic PET images. FlowGAN improves ASL's diagnostic performance, generating synthetic PET images that closely mimic actual FDG-PET in depicting hypometabolism associated with TLE. This approach could improve non-invasive SOZ localization, offering a promising tool for epilepsy presurgical assessment. It potentially broadens the applicability of ASL in clinical practice and could reduce reliance on FDG-PET for epilepsy and other neurological disorders.

Spectral consistency in sound sequence affects perceptual accuracy in discriminating subdivided rhythmic patterns.

Musical compositions are distinguished by their unique rhythmic patterns, determined by subtle differences in how regular beats are subdivided. Precise perception of these subdivisions is essential for discerning nuances in rhythmic patterns. While musical rhythm typically comprises sound elements with a variety of timbres or spectral cues, the impact of such spectral variations on the perception of rhythmic patterns remains unclear. Here, we show that consistency in spectral cues affects perceptual accuracy in discriminating subdivided rhythmic patterns. We conducted online experiments using rhythmic sound sequences consisting of band-passed noise bursts to measure discrimination accuracy. Participants were asked to discriminate between a swing-like rhythm sequence, characterized by a 2:1 interval ratio, and its more or less exaggerated version. This task was also performed under two additional rhythm conditions: inversed-swing rhythm (1:2 ratio) and regular subdivision (1:1 ratio). The center frequency of the band noises was either held constant or alternated between two values. Our results revealed a significant decrease in discrimination accuracy when the center frequency was alternated, irrespective of the rhythm ratio condition. This suggests that rhythm perception is shaped by temporal structure and affected by spectral properties.

Unveiling current and future trends in customer banking experience research: a bibliometric analysis

PurposeThis research is the first to use bibliometric analysis to provide insight into the landscape and forecast the future of customer experience research in the banking sector.Design/methodology/approachWe used bibliographic coupling and co-word analysis to delineate the existing knowledge structure after reviewing 338 articles from the Web of Science database.FindingsThe bibliographic coupling analysis revealed five key clusters: customer engagement and experience in digital banking; customer experience and service management; customer experience and market resilience; digital transformation and customer experience; and digital technology and customer experience—each representing a significant strand of current research. In addition, the co-word analysis revealed four emerging themes: customer experience through AI and blockchain, digital evolution in banking, experience-driven ecosystems for customer satisfaction, and trust-based holistic banking experience.Practical implicationsThese findings not only sketch an overview of the current research domain but also hint at emerging areas ideal for scholarly investigation. While highlighting the industry’s rapid adaptation to technological advances, this study calls for more integrative research to unravel the complexities of customer experience in the evolving digital banking ecosystem.Originality/valueThis review presents a novel state-of-the-art analysis of customer banking experience research by employing a science mapping via bibliometric analysis to unveil the knowledge and temporal structure.

Clustering time series by extremal dependence

AbstractThe goal of this paper is to characterize the temporal dependence structure on the extremes of time series and use such dependency to group them. In particular, three similarity measures to capture extremal dependence are proposed, being their performance assessed in different scenarios. This will involve the use of classical time series clustering algorithms, as well as rigorous evaluation of their performance in both simulated scenarios and real-world time series data sets. The focus will be on comparing the performance of these similarity measures with different clustering methods, and illustrate the efficacy of extremal dependence-based clustering in meteorological data. To achieve this, we will consider a dataset consisting of daily maximum temperatures recorded at 500 stations across Europe.

Low-grade glioma of the temporal lobe and tumor-related epilepsy in children.

Low-grade glioma is the most common brain tumor among children and adolescents. When these tumors arise in the temporal lobe, patients frequently present with seizures that are poorly controlled with antiepileptic drugs. Here we summarize the clinical features, pathophysiology, preoperative evaluation, surgical treatment, and outcomes of pediatric patients with low-grade gliomas in the temporal lobe. We reviewed the literature on pediatric low-grade gliomas in the temporal lobe, focusing on cohort studies and systematic reviews that described surgical treatment strategies and reported both oncologic and epilepsy outcomes. The differential diagnoses of pediatric low-grade gliomas in the temporal lobe include ganglioglioma, dysembryoplastic neuroepithelial tumor, desmoplastic infantile ganglioglioma, papillary glioneuronal tumor, pilocytic astrocytoma, pleomorphic xanthoastrocytoma, angiocentric glioma, and polymorphous low-grade neuroepithelial tumor of the young. There is no consensus on the optimal surgical approach for these tumors: lesionectomy alone, or extended lesionectomy with anterior temporal lobectomy, with or without removal of mesial temporal structures. Gross total resection and shorter preoperative duration of epilepsy are strongly associated with favorable seizure outcomes, defined as Engel Class I or Class II, approaching 90% in most series. The risk of surgical complications ranges from 4 to 17%, outweighing the lifetime risks of medically refractory epilepsy. Pediatric patients with temporal low-grade glioma and tumor-related epilepsy are best managed by a multidisciplinary epilepsy surgery team. Early and appropriate surgery leads to prolonged survival and a greater likelihood of seizure freedom, improving their overall quality of life.

Effects of Temporal Processing on Speech-in-Noise Perception in Middle-Aged Adults.

Auditory temporal processing is a vital component of auditory stream segregation, or the process in which complex sounds are separated and organized into perceptually meaningful objects. Temporal processing can degrade prior to hearing loss, and is suggested to be a contributing factor to difficulties with speech-in-noise perception in normal-hearing listeners. The current study tested this hypothesis in middle-aged adults-an under-investigated cohort, despite being the age group where speech-in-noise difficulties are first reported. In 76 participants, three mechanisms of temporal processing were measured: peripheral auditory nerve function using electrocochleography, subcortical encoding of periodic speech cues (i.e., fundamental frequency; F0) using the frequency following response, and binaural sensitivity to temporal fine structure (TFS) using a dichotic frequency modulation detection task. Two measures of speech-in-noise perception were administered to explore how contributions of temporal processing may be mediated by different sensory demands present in the speech perception task. This study supported the hypothesis that temporal coding deficits contribute to speech-in-noise difficulties in middle-aged listeners. Poorer speech-in-noise perception was associated with weaker subcortical F0 encoding and binaural TFS sensitivity, but in different contexts, highlighting that diverse aspects of temporal processing are differentially utilized based on speech-in-noise task characteristics.