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Mamashli, F.

Publications and source records attributed to Mamashli, F..

7 recordsLinked to original sources

Cortical Excitation-Inhibition Balance in Autism Varies by Brain Region and Age

Autism spectrum disorder (ASD) is characterized by differences in social communication, interaction, and restricted and repetitive behaviors. The hypothesis that ASD involves altered cortical excitation-inhibition (EI) balance has been extensively investigated, yet evidence remains mixed, partly because EI balance changes substantially during typical maturation. We used resting-state magnetoencephalography (MEG) to examine developmental trajectories of cortical EI alterations with regional specificity in a large cross-sectional cohort (N = 172; 92 typically developing, 80 ASD; ages 6-32). Functional EI (fEI), derived from critical brain dynamics, was estimated across 500 cortical parcellations. Group-averaged fEI maps revealed broadly similar large-scale topographic patterns across groups. Age-stratified analyses revealed increased global fEI in childhood and decreased fEI in adolescence in ASD, with no evidence of a group difference in adulthood. Parcel-wise regressions identified a significant main effect of diagnosis in right dorsolateral prefrontal cortex, where typically developing individuals showed higher fEI across all ages. A significant group-by-age interaction in left inferior parietal cortex indicated diverging developmental trajectories. Finally, fEI in paracentral and precuneus regions was associated with the magnitude of ASD symptoms. These findings indicate that EI imbalance in ASD is neither globally distributed nor static, but expressed through regionally and developmentally specific differences, with relevance for ASD heterogeneity.

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Decreased auditory cortical activations and altered long-range alpha-band connectivity characterize passive auditory spatial attention in ASD

Autism Spectrum Disorder (ASD) is a developmental condition characterized by difficulties in social interaction, communication and sensory processing. The ability to orient towards sounds is a key component of social interactions, yet auditory spatial attention remains relatively understudied in ASD, despite prior research indicating differences in this domain. Here, we investigate the neural signatures associated with passive auditory spatial attention in children with ASD (n = 21, ages 6-17) relative to age- and IQ-matched typically developing (TD) children (n = 31), using source-localized magnetoencephalography (MEG). Participants listened passively, while watching a silenced movie, to non-social auditory stimuli designed to either remain lateralized to one hemifield (stay trials), or to change in location from one side to the contralateral hemifield (jump trials). Linear mixed effects modeling showed lower cortical activation in the auditory cortex in the ASD group in response to jump trials, relative to the TD group. Additionally, functional connectivity analyses showed higher alpha-band functional connectivity in the ASD group between left auditory cortex seeds and right prefrontal and left parietal regions known to be recruited during auditory spatial attention. Right prefrontal alpha-band connectivity estimates were associated with behaviorally assessed auditory processing scores, whereas left parietal connectivity estimates were associated with ASD symptomatology. Our results align with the hypothesis that auditory spatial attention generally, and specifically orientation to sounds even when experienced passively, differs in ASD individuals.

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Decoding auditory working memory content from EEG aftereffects of auditory-cortical TMS

Working memory (WM), short term maintenance of information for goal directed behavior, is essential to human cognition. Identifying the neural mechanisms supporting WM is a focal point of neuroscientific research. One prominent theory hypothesizes that WM content is carried in "activity-silent" brain states involving short-term synaptic changes. Information carried in such brain states could be decodable from content-specific changes in responses to unrelated "impulse stimuli". Here, we used single-pulse transcranial magnetic stimulation (spTMS) as the impulse stimulus and then decoded content maintained in WM from EEG using multivariate pattern analysis (MVPA) with robust non-parametric permutation testing. The decoding accuracy of WM content significantly enhanced after spTMS was delivered to the posterior superior temporal cortex during WM maintenance. Our results show that WM maintenance involves brain states, which are activity silent relative to other intrinsic processes visible in the EEG signal.

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Characterizing directional dynamics of semantic prediction based on inter-regional temporal generalization

The event-related potential/field component N400(m) has been widely used as a neural index for semantic prediction. It has long been hypothesized that feedback information from inferior frontal areas plays a critical role in generating the N400. However, due to limitations in causal connectivity estimation, direct testing of this hypothesis has remained difficult. Here, magnetoencephalography (MEG) data was obtained during a classic N400 paradigm where the semantic predictability of a fixed target noun was manipulated in simple German sentences. To estimate causality, we implemented a novel approach based on machine learning and temporal generalization to estimate the effect of inferior frontal gyrus (IFG) on temporal areas. In this method, a support vector machine (SVM) classifier is trained on each time point of the neural activity in IFG to classify less predicted (LP) and highly predicted (HP) nouns and then tested on all time points of superior/middle temporal sub- regions activity (and vice versa, to establish spatio-temporal evidence for or against causality). The decoding accuracy was significantly above chance level when the classifier was trained on IFG activity and tested on future activity in superior and middle temporal gyrus (STG/MTG). The results present new evidence for a model predictive speech comprehension where predictive IFG activity is fed back to shape subsequent activity in STG/MTG, implying a feedback mechanism in N400 generation. In combination with the also observed strong feedforward effect from left STG/MTG to IFG, our findings provide evidence of dynamic feedback and feedforward influences between IFG and temporal areas during N400 generation.

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Decoding auditory working memory content from intracranial high frequency activity in humans

Working memory (WM), the human brains system for maintaining and manipulating information over short timescales, is critical for goal-directed behavior. Classic neurophysiological models, which emphasize persistent delay activity, are being challenged by an idea that WM is maintained through dynamic and activity-silent mechanisms, where the memory trace is preserved by transient changes in the connections between neurons. To date, human evidence for this alternative model has been limited to non-invasive studies. Here, leveraging high-resolution intracranial stereo-EEG with advanced machine learning decoding techniques, we investigate neuronal mechanisms of human auditory WM. Neuronal activity is quantified as broadband high frequency activity (70-190 Hz), a correlate of neuronal firing activity. Our multivariate pattern analyses, validated via robust non-parametric permutation testing, show that WM content is represented in multiple brain regions, exhibiting dynamic rather than persistent delay activity. Crucially, by using task-irrelevant sounds to probe latent mnemonic states, we provide the first human intracranial evidence of activity silent WM maintenance in a local sensory network.

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Auditory aspects of multisensory working memory are retrieved better than visual aspects

Working memory (WM) reflects the transient maintenance of information in the absence of external input, which can be attained via multiple senses separately or simultaneously. Pertaining to WM, the prevailing literature suggests the dominance of vision over other sensory systems. However, this imbalance may be stemming from challenges in finding comparable stimuli across modalities. Here, we addressed this problem by using a balanced multisensory retro-cue WM design, which employed combinations of auditory (ripple sounds) and visuospatial (Gabor patches) patterns, adjusted relative to each participants discrimination ability. In three separate experiments, the participant was asked to determine whether the (retro-cued) auditory and/or visual items maintained in WM matched or mismatched the subsequent probe stimulus. In Experiment 1, all stimuli were audiovisual, and the probes were either fully mismatching, only partially mismatching, or fully matching the memorized item. Experiment 2 was otherwise same as Experiment 1, but the probes were unimodal. In Experiment 3, the participant was cued to maintain only the auditory or visual aspect of an audiovisual item pair. In two of the three experiments, the participant matching performance was significantly more accurate for the auditory than visual attributes of probes. When the perceptual and task demands are bimodally equated, auditory attributes can be matched to multisensory items in WM at least as accurately as, if not more precisely than, their visual counterparts.

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Maturation Trajectories of Cortical Resting-State Networks Depend on the Mediating Frequency Band

The functional significance of resting state networks and their abnormal manifestations in psychiatric disorders are firmly established, as is the importance of the cortical rhythms in mediating these networks. Resting state networks are known to undergo substantial reorganization from childhood to adulthood, but whether distinct cortical rhythms, which are generated by separable neural mechanisms and are often manifested abnormally in psychiatric conditions, mediate maturation differentially, remains unknown. Using magnetoencephalography (MEG) to map frequency band specific maturation of resting state networks from age 7 to 29 in 162 participants (31 independent), we found significant changes with age in networks mediated by the beta (13-30Hz) and gamma (31-80Hz) bands. More specifically, gamma band mediated networks followed an expected asymptotic trajectory, but beta band mediated networks followed a linear trajectory. Network integration increased with age in gamma band mediated networks, while local segregation increased with age in beta band mediated networks. Spatially, the hubs that changed in importance with age in the beta band mediated networks had relatively little overlap with those that showed the greatest changes in the gamma band mediated networks. These findings are relevant for our understanding of the neural mechanisms of cortical maturation, in both typical and atypical development.

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