Symptomatic Management of Sudden Unilateral Severe Spasticity Following a Fall in a Patient With Traumatic Spinal Cord Injury: A Case Report-From Etiology To Symptom-Focused.

Autism spectrum disorder (ASD) remains a major challenge for therapeutic development due to its complex neurobiological underpinnings and heterogeneous clinical presentation. Increasing evidence indicates that chronic insomnia is not merely a comorbid condition but is integral to the core pathophysiology of ASD, contributing to neural dysregulation across multiple systems and directly exacerbating core ASD symptoms, including severe irritability, repetitive behaviors, and impaired social communication [, , ]. Addressing these sleep‐related abnormalities is therefore essential for improving clinical outcomes and advancing mechanistic understanding of ASD. Intermittent theta‐burst stimulation (iTBS), a non‐invasive neuromodulatory technique capable of inducing long‐term potentiation (LTP)‐like synaptic plasticity, offers a promising avenue to restore the excitation‐inhibition balance and normalize network communication [, ]. We hypothesized that focal iTBS may be associated with system‐level alterations in large‐scale network organization, potentially reflected by changes in network diversity. Understanding the brain network mechanisms mediating iTBS‐induced modulation represents a crucial step toward optimizing its therapeutic efficacy for ASD. Growing neuroimaging evidence conceptualizes ASD as a disconnection syndrome involving disrupted interactions among large‐scale brain systems [, , ]. However, most earlier connectome studies employed non‐overlapping network models that assume each brain region belongs to a single discrete network, thereby overlooking spatially overlapping organization []. In contrast, evidence indicates that many brain regions simultaneously contribute to multiple subnetworks, forming an overlapping topology supporting cross‐system communication []. Such regions typically display cross‐network coactivation, hub‐like structural properties, and high dynamic adaptability, while disruption of these overlapping hubs has been linked to impaired large‐scale integration in neuropsychiatric conditions [, ]. To capture this aspect of system‐level organization, we modeled the brain's overlapping architecture using the Shannon‐entropy diversity coefficient (H), an information‐theoretic index that quantifies how evenly a node's connectivity is distributed across functional modules []. Higher H indicates broader cross‐system participation, whereas lower H reflects more module‐specific connectivity []. Because iTBS‐induced plasticity may involve not only changes in local coupling strength but also redistribution of regional participation across overlapping cortical systems, the H provides a theoretically appropriate measure for examining stimulation‐related network reorganization. Integrating neuroimaging data with neurotransmitter systems offers a powerful framework for elucidating the biological mechanisms of brain disorders [, , ]. Evidence increasingly shows functional heterogeneity in the human brain is constrained by its intrinsic chemoarchitectural scaffold []. An imbalance between excitation and inhibition (E/I) has been recognized as a shared pathophysiological mechanism underlying both ASD and insomnia []. This imbalance is shaped by regional variations in glutamatergic (mGluR5) and GABAergic (GABA_A) receptor densities, which modulate local E/I balance and consequently large‐scale network connectivity []. Our previous work demonstrated that brain stimulation can alleviate insomnia symptoms by regulating GABAergic neurotransmission [], underscoring the therapeutic relevance of targeting the E/I system. The JuSpace toolbox [], which incorporates normative positron emission tomography (PET)‐derived neurotransmitter maps, enables testing whether ASD‐related network alterations align with underlying neurotransmitter architectures, thereby facilitating cross‐scale analyses of functional‐neurochemical correspondence []. Integrating metrics of network complexity (e.g., Shannon‐entropy diversity) with neurotransmitter profiles can offer new insights into neurobiological mechanisms within a trans‐diagnostic framework.