Faculty Bibliography

Neural activity exhibits complex dynamics related to various brain functions, internal states and behaviors. Understanding how neural dynamics explain specific measured behaviors requires dissociating behaviorally relevant and irrelevant dynamics, which is not achieved with current neural dynamic models as they are learned without considering behavior. We develop preferential subspace identification (PSID), which is an algorithm that models neural activity while dissociating and prioritizing its behaviorally relevant dynamics. Modeling data in two monkeys performing three-dimensional reach and grasp tasks, PSID revealed that the behaviorally relevant dynamics are significantly lower-dimensional than otherwise implied. Moreover, PSID discovered distinct rotational dynamics that were more predictive of behavior. Furthermore, PSID more accurately learned behaviorally relevant dynamics for each joint and recording channel. Finally, modeling data in two monkeys performing saccades demonstrated the generalization of PSID across behaviors, brain regions and neural signal types. PSID provides a general new tool to reveal behaviorally relevant neural dynamics that can otherwise go unnoticed.

Epilepsy is a common neurological disorder affecting over 70 million people worldwide, with a high rate of pharmaco-resistance, diverse comorbidities including progressive cognitive and behavioural disorders, and increased mortality from direct (e.g. sudden unexpected death in epilepsy, accidents, drowning) or indirect effects of seizures and therapies. Extensive research with animal models and human studies provides limited insights into the mechanisms underlying seizures and epileptogenesis, and these have not translated into significant reductions in pharmaco-resistance, morbidities or mortality. To help define changes in molecular signalling networks associated with seizures in epilepsy with a broad range of aetiologies, we examined the proteome of brain samples from epilepsy and control cases. Label-free quantitative mass spectrometry was performed on the hippocampal cornu ammonis 1-3 region (CA1-3), frontal cortex and dentate gyrus microdissected from epilepsy and control cases (n = 14/group). Epilepsy cases had significant differences in the expression of 777 proteins in the hippocampal CA1 - 3 region, 296 proteins in the frontal cortex and 49 proteins in the dentate gyrus in comparison to control cases. Network analysis showed that proteins involved in protein synthesis, mitochondrial function, G-protein signalling and synaptic plasticity were particularly altered in epilepsy. While protein differences were most pronounced in the hippocampus, similar changes were observed in other brain regions indicating broad proteomic abnormalities in epilepsy. Among the most significantly altered proteins, G-protein subunit beta 1 (GNB1) was one of the most significantly decreased proteins in epilepsy in all regions studied, highlighting the importance of G-protein subunit signalling and G-protein-coupled receptors in epilepsy. Our results provide insights into common molecular mechanisms underlying epilepsy across various aetiologies, which may allow for novel targeted therapeutic strategies.

Background: The corticoreticulospinal tract (CReST) is a major descending motor pathway in humans, but little is known about its relative innervation of proximal versus distal upper extremity (UE) muscles. In addition, CReST is believed to reorganize after corticospinal injury, but changes in its projections to different paretic muscles remain unknown. Here, we used transcranial magnetic stimulation (TMS) to probe the functional connectivity of the contralesional CReST to an arm muscle (biceps (BIC)) and an intrinsic hand muscle (first dorsal interosseous (FDI)) in healthy and stroke subjects.
Method(s): In this cross-sectional observational study, we examined 15 healthy (F: 7; mean age: 54 (44-81) years; mean UE Fugl-Meyer Assessment (FMA) score: 65 (63-66)) and 16 chronic stroke subjects (F: 10; mean age 62 (44-85) years; mean UE FMA score: 49 (23-64); mean time since stroke: 5 (0.5-14.4) years). We applied TMS to the contralesional hemisphere (assigned in healthy subjects) to elicit ipsilateral motor evoked potentials (iMEPs). We measured contralesional CReST functional connectivity (iMEP presence/absence) and projection strength (iMEP size; mV*ms) to the paretic BIC and FDI. We also measured paretic muscle maximum voluntary contraction and segmental FMA subscores. We examined differences in CReST projections between muscles and subject groups using Fisher's exact tests and general linear mixed models, and examined neurophysiologicalbehavioral relationships with Pearson's and Spearman's correlations.
Result(s): The contralesional CReST made functional connections to both muscles of most subjects (iMEP presence/absence: healthy BIC 14/1, healthy FDI 15/0; stroke BIC 11/5, stroke FDI 15/1). CReST functional connectivity did not differ between muscles in either healthy or stroke subjects (all p>0.172), and did not differ between subject groups for either muscle (all p=1.0). However, CReST projection strength for the muscles diverged between subject groups, manifesting as larger iMEPs in FDIs than BICs in healthy subjects (1.9 mV*ms, p=0.042) and larger iMEPs in BICs than FDIs in stroke subjects (1.0 mV*ms, p=0.042). Muscle iMEP sizes did not significantly differ between healthy and stroke subjects. Muscle strength related to iMEP size in only the paretic BIC of stroke subjects (r(6)=0.853, p=0.007). There was no relationship between FMA subscores and iMEP size for either muscle in either subject group.
Conclusion(s): Our findings indicate that the contralesional CReST has readily identifiable connections to the paretic BIC and FDI. In healthy subjects, the identification of a stronger CReST projection strength to the FDI challenges the notion of a proximal innervation bias by the reticulospinal tract. The shift in projection strength to the BIC after stroke reinforces the concept that the CReST reorganizes after CST injury, with circumscribed behavioral relevance. To confirm a recovery role of the CReST, a longitudinal observation of recovering behavior relating to changing CReST neurophysiology is required.

Seizure clusters, an intermediate between single seizure and status epilepticus, are associated with morbidity, impaired quality of life, and premature mortality. The relationship between seizure clusters and sudden unexplained death in epilepsy (SUDEP) is poorly understood. Here, we define seizure clusters; review comorbid psychiatric disorders and memory deficits associated with seizure clusters; and review cases of witnessed SUDEP for which seizure frequency prior to death is available. Patients with a history of seizure clusters have a 2.5 fold increased risk for SUDEP, and one third of patients with monitored in hospital SUDEP experienced a cluster of generalized tonic clonic seizures prior to death. Understanding the effects of seizure frequency and duration on SUDEP risk could yield new insights in SUDEP pathophysiology and new targets for intervention.

Rationale: Seizure clusters may be related to Sudden Unexpected Death in Epilepsy (SUDEP). Two or more generalized convulsive seizures (GCS) were captured during video electroencephalography in 7/11 (64%) patients with monitored SUDEP in the MORTEMUS study. It follows that seizure clusters may be associated with epilepsy severity and possibly with SUDEP risk. We aimed to determine if electroclinical seizure features worsen from seizure to seizure within a cluster and possible associations between GCS clusters, markers of seizure severity, and SUDEP risk. Methods: Patients were consecutive, prospectively consented participants with drug-resistant epilepsy from a multi-center study. Seizure clusters were defined as two or more GCS in a 24-h period during the recording of prolonged video-electroencephalography in the Epilepsy monitoring unit (EMU). We measured heart rate variability (HRV), pulse oximetry, plethysmography, postictal generalized electroencephalographic suppression (PGES), and electroencephalography (EEG) recovery duration. A linear mixed effects model was used to study the difference between the first and subsequent seizures, with a level of significance set at p < 0.05. Results: We identified 112 GCS clusters in 105 patients with 285 seizures. GCS lasted on average 48.7 ± 19 s (mean 49, range 2-137). PGES emerged in 184 (64.6%) seizures and postconvulsive central apnea (PCCA) was present in 38 (13.3%) seizures. Changes in seizure features from seizure to seizure such as seizure and convulsive phase durations appeared random. In grouped analysis, some seizure features underwent significant deterioration, whereas others improved. Clonic phase and postconvulsive central apnea (PCCA) were significantly shorter in the fourth seizure compared to the first. By contrast, duration of decerebrate posturing and ictal central apnea were longer. Four SUDEP cases in the cluster cohort were reported on follow-up. Conclusion: Seizure clusters show variable changes from seizure to seizure. Although clusters may reflect epilepsy severity, they alone may be unrelated to SUDEP risk. We suggest a stochastic nature to SUDEP occurrence, where seizure clusters may be more likely to contribute to SUDEP if an underlying progressive tendency toward SUDEP has matured toward a critical SUDEP threshold.

The specificity and implementation of current MRI-based diagnostic criteria for multiple sclerosis (MS) are imperfect. Approximately 1 in 5 of individuals diagnosed with MS are eventually determined not to have the disease, with overreliance on MRI findings a major cause of MS misdiagnosis. The central vein sign (CVS), a proposed MRI biomarker for MS lesions, has been extensively studied in numerous cross sectional studies and may increase diagnostic specificity for MS. CVS has desirable analytical, measurement, and scalability properties. "Central Vein Sign: A Diagnostic Biomarker in Multiple Sclerosis (CAVS-MS)" is an NIH-supported, 2-year, prospective, international, multicenter study conducted by the North American Imaging in MS Cooperative (NAIMS) to evaluate CVS as a diagnostic biomarker for immediate translation into clinical care. Study objectives include determining the concordance of CVS and McDonald Criteria to diagnose MS, the sensitivity of CVS to detect MS in those with typical presentations, and the specificity of CVS among those with atypical presentations. The study will recruit a total of 400 participants (200 with typical and 200 with atypical presentations) across 11 sites. T2*-weighted, high-isotropic-resolution, segmented echo-planar MRI will be acquired at baseline and 24 months on 3-tesla scanners, and FLAIR* images (combination of FLAIR and T2*) will be generated for evaluating CVS. Data will be processed on a cloud-based platform that contains clinical and CVS rating modules. Imaging quality control will be conducted by automated methods and neuroradiologist review. CVS will be determined by Select6* and Select3* lesion methods following published criteria at each site and by central readers, including neurologists and neuroradiologists. Automated CVS detection and algorithms for incorporation of CVS into McDonald Criteria will be tested. Diagnosis will be adjudicated by three neurologists who served on the 2017 International Panel on the Diagnosis of MS. The CAVS-MS study aims to definitively establish CVS as a diagnostic biomarker that can be applied broadly to individuals presenting for evaluation of the diagnosis of MS.

Sialidosis type 1 is a rare lysosomal storage disorder caused by mutations of the neuraminidase gene. Specific features suggesting this condition include myoclonus, ataxia and macular cherry-red spots. However, phenotypic variability exists. Here, we present detailed clinical and video description of three patients with this rare condition. We also provide an in-depth characterization of eye movement abnormalities, as an additional tool to investigate pathophysiological mechanisms and to facilitate diagnosis. In our patients, despite phenotypic differences, eye movement deficits largely localized to the cerebellum.