Biology subjects

Aabedi, A. A.

Publications and source records attributed to Aabedi, A. A..

4 recordsLinked to original sources

bioRxiv2025

Electrocorticographic Detection of Speech Networks in Glioma-infiltrated Cortex

Direct cortical stimulation (DCS) is the clinical gold standard for identifying functional cortex in the human brain, which is essential for the safe removal of brain lesions. Defining the electro-physiological properties of DCS- positive cortical regions may facilitate the identification of critical language regions, thereby permitting safe glioma resections in communities without access. Leveraging a multicenter electrophysiologic dataset of DCS- positive language regions spatially matched with subdural arrays, we analyzed regions identified as functionally critical (DCS+) versus functionally non-critical (DCS-) during intraoperative language mapping. In IDH-mutant gliomas, DCS+ regions exhibited significantly greater speech-related neural activity and enhanced encoding and decoding of linguistic and semantic features. We demonstrate that resting-state classifiers distinguish DCS+ from DCS- regions in IDH-mutant tumors. Task-based and resting-state electrophysiologic distinctions were pathology-specific and not present in IDH-wildtype glioblastomas. These findings may accelerate DCS mapping by guiding surgeons to priority regions, improving efficiency, and patient outcomes.

neuroscience↗

bioRxiv2025

Aperiodic neural dynamics define a novel signature of glioma-induced excitation-inhibition dysregulation

Diffuse gliomas remodel neuronal circuits with prognostic and therapeutic significance for patients. Electrophysiologic measures of cortical excitability hold promise for monitoring disease progression and evaluating therapeutic responses. The power law exponent (aperiodic slope) reflects the balance between excitatory and inhibitory activity within neuronal networks, a critical aspect of normal brain function often disrupted in neurological conditions. Despite its potential, the significance of the aperiodic slope in glioma-infiltrated tissue and its underlying cellular processes has not been fully investigated. Here, we integrate multi-modal electrophysiological analysis with transcriptomic profiling to analyze the aperiodic slope in both normal and glioma-infiltrated cortex. We determine that glioma infiltration induces a flattening of the aperiodic slope, indicating a shift toward excitation dominance that varies according to tumor subtype and correlates with impairments in semantic naming. Single-nucleus RNA sequencing revealed that cortical regions with flat aperiodic slope exhibit transcriptional programs enriched in glutamatergic signaling, membrane depolarization, and excitatory synaptic transmission. The aperiodic slope responds to pharmacologically induced changes in cortical inhibition during propofol administration, a GABAA agonist. Our results establish the aperiodic slope as a robust biomarker of glioma-associated excitation-inhibition imbalance, with potential applications in tumor classification and treatment monitoring.

cancer biology↗

bioRxiv2021

Functional alterations in cortical processing of speech in glioma-infiltrated cortex

Recent developments in the biology of malignant gliomas have demonstrated that glioma cells interact with neurons through both paracrine signaling and electrochemical synapses. Glioma-neuron interactions consequently modulate the excitability of local neuronal circuits, and it is unclear the extent to which glioma-infiltrated cortex can meaningfully participate in neural computations. For example, gliomas may result in a local disorganization of activity that impedes the transient synchronization of neural oscillations. Alternatively, glioma-infiltrated cortex may retain the ability to engage in synchronized activity, in a manner similar to normal-appearing cortex, but exhibit other altered spatiotemporal patterns of activity with subsequent impact on cognitive processing. Here, we use subdural electrocorticography to sample both normal-appearing and glioma-infiltrated cortex during speech. We find that glioma-infiltrated cortex engages in synchronous activity during task performance in a manner similar to normal-appearing cortex, but recruits a diffuse spatial network. On a temporal scale, we show that glioma-infiltrated cortex has lower capacity for information encoding when performing nuanced tasks such as speech production of monosyllabic versus polysyllabic words. As a result, temporal decoding strategies for distinguishing monosyllabic from polysyllabic words were feasible for signals arising from normal-appearing cortex, but not from glioma-infiltrated cortex. These findings inform our understanding of cognitive processing in chronic disease states and have implications for neuromodulation and prosthetics in patients with malignant gliomas. Significance StatementAs gliomas proliferate, they infiltrate healthy brain tissue. Often, patients with such tumors in the language areas of the brain develop aphasia. Understanding how gliomas interact with normal neural circuits is critical for developing neuroprostheses that restore speech. Recent evidence demonstrates that glioma cells interact synaptically with neurons, and thus can modulate neural circuits. However, it is unclear the extent to which glioma-infiltrated cortex participates in cognitive processing. Using electrocorticography to record both glioma-infiltrated and normal-appearing cortex during speech, we found that glioma-infiltrated cortex is capable of coordinated neural responses, but has reduced capacity for information encoding. Instead, glioma-infiltrated cortex recruits a broader network of cortical regions during speech, which may represent a compensatory mechanism with implications for future neuroprostheses.

neuroscience↗

bioRxiv2020

Convergence of Heteromodal Lexical Retrieval in the Lateral Prefrontal Cortex

Lexical retrieval requires selecting and retrieving the most appropriate word from the lexicon to express a desired concept. Prior studies investigating the neuroanatomic underpinnings of lexical retrieval used lesion models that rely on stereotyped vascular distributions, functional neuroimaging methods that lack causal certainty, or awake brain mapping that is typically limited to narrow cortical exposures. Further, few studies have probed lexical retrieval with tasks other than picture naming and when non-picture naming lexical retrieval tasks have been applied, both convergent and divergent models emerged. Because of this existing controversy, we set out to test the hypothesis that cortical and subcortical brain regions specifically involved in lexical retrieval in response to visual and auditory stimuli represent overlapping neural systems. Fifty-three patients with dysnomic aphasia due to dominant-hemisphere brain tumors performed four language tasks: picture naming, auditory naming, text reading, and describing line drawings with correct syntax. A subset of participants also underwent the Quick Aphasia Battery which provides a validated measure of lexical retrieval via the word finding subtest. Generalized linear modeling and principal components analysis revealed multicollinearity between picture naming, auditory naming, and word finding, implying redundancies between the linguistic measures. Support vector regression lesion-symptom mapping across participants was used to model accuracies on each of the four language tasks. Picture naming and auditory naming survived cluster-level corrections. Specifically, lesions within overlapping clusters of 8,333 voxels and 21,512 voxels in the left lateral PFC were predictive of impaired picture naming and auditory naming, respectively. These data indicate a convergence of heteromodal lexical retrieval within the PFC. Importance of the StudyLexical retrieval (i.e., selecting and retrieving words to convey desired concepts) is a crucial component of language processing. However, existing studies of the neuroanatomic underpinnings of lexical retrieval lack causal relationships and have provided conflicting evidence, suggesting both convergent and divergent models. In order to resolve these conflicting models, we used lesion-symptom mapping to investigate lexical retrieval in 53 patients with dominant-hemisphere brain tumors. We observed significant associations between performance on visual and auditory naming tasks. Further, performance on these tasks predicted performance on a validated neuropsychological measure of lexical retrieval. Critically, multivariate, nonparametric lesion-symptom mapping within a brain tumor framework revealed that lesions in overlapping regions of the left lateral prefrontal cortex (PFC) predict impaired visual and auditory naming. In a clinical context, this approach to identifying causal brain-behavior relationships could help to guide brain tumor therapies such as cytoreductive surgery and supportive rehabilitation services.

neuroscience↗