Timing the clinical onset of epileptic spasms in infantile epileptic spasms syndrome: A tertiary health center's experience.

OBJECTIVE: Lead time to treatment (clinical onset of epileptic spasms [ES] to initiation of appropriate treatment) is known to predict outcomes in infantile epileptic spasms syndrome (IESS). Timing the clinical onset of ES is crucial to establish lead time. We investigated how often ES onset could be established to the nearest week. We aimed to (1) ascertain the exact date or estimate the nearest week of ES onset and (2) compare clinical/demographic factors between patients where date of ES onset was determined or estimated to the nearest week and patients whose date of ES onset could not be estimated to the nearest week. Reasons for difficulties in estimating date of ES onset were explored. METHODS: Retrospective chart review of new onset IESS patients (January 2019-May 2022) extracted the date or week of the clinical onset of ES. Predictors of difficulty in date of ES onset estimation to the nearest week were examined by regression analysis. Sources contributing to difficulties determining date of ES onset were assessed after grouping into categories (provider-, caregiver-, disease-related). RESULTS: Among 100 patients, date of ES onset was estimated to the nearest week in 47%. On univariable analysis, age at diagnosis (p = .021), development delay (p = .007), developmental regression/stagnation (p = .021), ES intermixed with other seizures (p = .011), and nonclustered ES at onset (p = .005) were associated with difficulties estimating date of ES onset. On multivariable analysis, failure to establish date of ES onset was related to ES intermixed with other seizures (p = .004) and nonclustered ES at onset (p = .003). Sources contributing to difficulties determining date of ES onset included disease-related factors (ES characteristics, challenges interpreting electroencephalograms) and provider/caregiver-related factors (delayed diagnosis). SIGNIFICANCE: Difficulties with estimation of lead time (due to difficulties timing ES onset) can impact clinical care (prognostication), as even small increments in lead time duration can have adverse developmental consequences.

BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods.

The rate of progress in human neurosciences is limited by the inability to easily apply a wide range of analysis methods to the plethora of different datasets acquired in labs around the world. In this work, we introduce a framework for creating, testing, versioning and archiving portable applications for analyzing neuroimaging data organized and described in compliance with the Brain Imaging Data Structure (BIDS). The portability of these applications (BIDS Apps) is achieved by using container technologies that encapsulate all binary and other dependencies in one convenient package. BIDS Apps run on all three major operating systems with no need for complex setup and configuration and thanks to the comprehensiveness of the BIDS standard they require little manual user input. Previous containerized data processing solutions were limited to single user environments and not compatible with most multi-tenant High Performance Computing systems. BIDS Apps overcome this limitation by taking advantage of the Singularity container technology. As a proof of concept, this work is accompanied by 22 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms.

Network localization of pediatric lesion-induced dystonia.

Objective: Dystonia is a movement disorder defined by involuntary muscle contractions leading to abnormal postures or twisting and repetitive movements. Classically dystonia has been thought of as a disorder of the basal ganglia, but newer results in idiopathic dystonia and lesion-induced dystonia in adults point to broader motor network dysfunction spanning the basal ganglia, cerebellum, premotor cortex, sensorimotor, and frontoparietal regions. It is unclear whether a similar network is shared between different etiologies of pediatric lesion-induced dystonia. Methods: Three cohorts of pediatric patients with lesion-induced dystonia were identified. The lesion etiologies included hypoxia, kernicterus, and stroke versus comparison subjects with acquired lesions not associated with dystonia. Multivariate lesion-symptom mapping and lesion network mapping were used to evaluate the anatomy and networks associated with dystonia. Results: Multivariate lesion-symptom mapping showed that lesions of the putamen (stroke: r = 0.50, p <0.01; hypoxia, r = 0.64, p <0.001) and globus pallidus (kernicterus, r = 0.61, p <0.01) were associated with dystonia. Lesion network mapping using normative connectome data from healthy children demonstrated that these regional findings occurred within a common brain-wide network that involves the basal ganglia, anterior and medial cerebellum, and cortical regions that overlap the cingulo-opercular and somato-cognitive-action networks. Interpretation: We interpret these findings as novel evidence for a unified dystonia brain network that involves the somato-cognitive-action network, which is involved in higher order coordination of movement. Elucidation of this network gives insight into the functional origins of dystonia and provides novel targets to investigate for therapeutic intervention.

Using causal methods to map symptoms to brain circuits in neurodevelopment disorders: moving from identifying correlates to developing treatments.

A wide variety of model systems and experimental techniques can provide insight into the structure and function of the human brain in typical development and in neurodevelopmental disorders. Unfortunately, this work, whether based on manipulation of animal models or observational and correlational methods in humans, has a high attrition rate in translating scientific discovery into practicable treatments and therapies for neurodevelopmental disorders.With new computational and neuromodulatory approaches to interrogating brain networks, opportunities exist for "bedside-to bedside-translation" with a potentially shorter path to therapeutic options. Specifically, methods like lesion network mapping can identify brain networks involved in the generation of complex symptomatology, both from acute onset lesion-related symptoms and from focal developmental anomalies. Traditional neuroimaging can examine the generalizability of these findings to idiopathic populations, while non-invasive neuromodulation techniques such as transcranial magnetic stimulation provide the ability to do targeted activation or inhibition of these specific brain regions and networks. In parallel, real-time functional MRI neurofeedback also allow for endogenous neuromodulation of specific targets that may be out of reach for transcranial exogenous methods.Discovery of novel neuroanatomical circuits for transdiagnostic symptoms and neuroimaging-based endophenotypes may now be feasible for neurodevelopmental disorders using data from cohorts with focal brain anomalies. These novel circuits, after validation in large-scale highly characterized research cohorts and tested prospectively using noninvasive neuromodulation and neurofeedback techniques, may represent a new pathway for symptom-based targeted therapy.

Face-Processing Performance is an Independent Predictor of Social Affect as Measured by the Autism Diagnostic Observation Schedule Across Large-Scale Datasets.

Face-processing deficits, while not required for the diagnosis of autism spectrum disorder (ASD), have been associated with impaired social skills-a core feature of ASD; however, the strength and prevalence of this relationship remains unclear. Across 445 participants from the NIMH Data Archive, we examined the relationship between Benton Face Recognition Test (BFRT) performance and Autism Diagnostic Observation Schedule-Social Affect (ADOS-SA) scores. Lower BFRT scores (worse face-processing performance) were associated with higher ADOS-SA scores (higher ASD severity)-a relationship that held after controlling for other factors associated with face processing, i.e., age, sex, and IQ. These findings underscore the utility of face discrimination, not just recognition of facial emotion, as a key covariate for the severity of symptoms that characterize ASD.

Regional Distribution of Brain Injury After Cardiac Arrest: Clinical and Electrographic Correlates.

BACKGROUND AND OBJECTIVES: Disorders of consciousness, EEG background suppression, and epileptic seizures are associated with poor outcome after cardiac arrest. Our objective was to identify the distribution of diffusion MRI-measured anoxic brain injury after cardiac arrest and to define the regional correlates of disorders of consciousness, EEG background suppression, and seizures. METHODS: We analyzed patients from a single-center database of unresponsive patients who underwent diffusion MRI after cardiac arrest (n = 204). We classified each patient according to recovery of consciousness (command following) before discharge, the most continuous EEG background (burst suppression vs continuous), and the presence or absence of seizures. Anoxic brain injury was measured with the apparent diffusion coefficient (ADC) signal. We identified ADC abnormalities relative to controls without cardiac arrest (n = 48) and used voxel lesion symptom mapping to identify regional associations with disorders of consciousness, EEG background suppression, and seizures. We then used a bootstrapped lasso regression procedure to identify robust, multivariate regional associations with each outcome variable. Last, using area under receiver operating characteristic curves, we then compared the classification ability of the strongest regional associations to that of brain-wide summary measures. RESULTS: Compared to controls, patients with cardiac arrest demonstrated ADC signal reduction that was most significant in the occipital lobes. Disorders of consciousness were associated with reduced ADC most prominently in the occipital lobes but also in deep structures. Regional injury more accurately classified patients with disorders of consciousness than whole-brain injury. Background suppression mapped to a similar set of brain regions, but regional injury could no better classify patients than whole-brain measures. Seizures were less common in patients with more severe anoxic injury, particularly in those with injury to the lateral temporal white matter. DISCUSSION: Anoxic brain injury was most prevalent in posterior cerebral regions, and this regional pattern of injury was a better predictor of disorders of consciousness than whole-brain injury measures. EEG background suppression lacked a specific regional association, but patients with injury to the temporal lobe were less likely to have seizures. Regional patterns of anoxic brain injury are relevant to the clinical and electrographic sequelae of cardiac arrest and may hold importance for prognosis. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence that disorders of consciousness after cardiac arrest are associated with widely lower ADC values on diffusion MRI and are most strongly associated with reductions in occipital ADC.