Intraoperative changes in large-scale thalamic circuitry following laser ablation of hypothalamic hamartomas.

BACKGROUND AND OBJECTIVES: Gelastic seizures due to hypothalamic hamartomas (HH) are challenging to treat, in part due to an incomplete understanding of seizure propagation pathways. Although magnetic resonance imaging-guided laser interstitial thermal therapy (MRgLITT) is a promising intervention to disconnect HH from ictal propagation networks, the optimal site of ablation to achieve seizure freedom is not known. In this study, we investigated intraoperative post-ablation changes in resting-state functional connectivity to identify large-scale networks associated with successful disconnection of HH. METHODS: Children who underwent MRgLITT for HH at two institutions were consecutively recruited and followed for a minimum of one year. Seizure freedom was defined as Engel score of 1A at the last available follow-up. Immediate pre- and post- ablation resting-state functional MRI scans were acquired while maintaining a constant depth of general anesthetic. Multivariable generalized linear models were used to identify intraoperative changes in large-scale connectivity associated with seizure outcomes. RESULTS: Twelve patients underwent MRgLITT for HH, five of whom were seizure-free at their last follow-up. Intraprocedural changes in thalamocortical circuitry involving the anterior cingulate cortex were associated with seizure-freedom. Children who were seizure-free demonstrated an increase and decrease in connectivity to the pregenual and dorsal anterior cingulate cortices, respectively. In addition, children who became seizure-free demonstrated increased thalamic connectivity to the periaqueductal gray immediately following MRgLITT. DISCUSSION: Successful disconnection of HH is associated with intraoperative, large-scale changes in thalamocortical connectivity. These changes provide novel insights into the large-scale basis of gelastic seizures and may represent intraoperative biomarkers of treatment success.

Longitudinal point-of-care assessment of psychomotor vigilance in children in the epilepsy monitoring unit.

The epilepsy monitoring unit (EMU) is a complex and dynamic operational environment, where the cognitive and behavioural consequences of medical and environmental changes often go unnoticed. The psychomotor vigilance task (PVT) has been used to detect changes in cognition and behaviour in numerous contexts, including among astronauts on spaceflight missions, pilots, and commercial drivers. Here, we piloted serial point-of-care administration of the PVT in children undergoing invasive monitoring in the EMU. Seven children completed the PVT throughout their hospital admission and their performance was associated with daily seizure counts, interictal epileptiform discharges, number of antiseizure medications (ASMs) administered, and sleep quality metrics. Using mixed-effects models, we found that PVT reaction time and accuracy were adversely affected by greater number of ASMs and interictal epileptiform activity. We show that serial point-of-care PVT is simple and feasible in the EMU and may enable greater understanding of individual patient responses to medical and environmental alterations, inform clinical decision-making, and support quality-improvement and research initiatives.

Neurostimulation treatments for epilepsy: Deep brain stimulation, responsive neurostimulation and vagus nerve stimulation.

Epilepsy is a common and debilitating neurological disorder, and approximately one-third of affected individuals have ongoing seizures despite appropriate trials of two anti-seizure medications. This population with drug-resistant epilepsy (DRE) may benefit from neurostimulation approaches, such as vagus nerve stimulation (VNS), deep brain stimulation (DBS) and responsive neurostimulation (RNS). In some patient populations, these techniques are FDA-approved for treating DRE. VNS is used as adjuvant therapy for children and adults. Acting via the vagus afferent network, VNS modulates thalamocortical circuits, reducing seizures in approximately 50 â€‹% of patients. RNS uses an adaptive (closed-loop) system that records intracranial EEG patterns to activate the stimulation at the appropriate time, being particularly well-suited to treat seizures arising within eloquent cortex. For DBS, the most promising therapeutic targets are the anterior and centromedian nuclei of the thalamus, with anterior nucleus DBS being used for treating focal and secondarily generalized forms of DRE and centromedian nucleus DBS being applied for treating generalized epilepsies such as Lennox-Gastaut syndrome. Here, we discuss the indications, advantages and limitations of VNS, DBS and RNS in treating DRE and summarize the spatial distribution of neuroimaging observations related to epilepsy and stimulation using NeuroQuery and NeuroSynth.

Postoperative cerebellar mutism syndrome is an acquired Autism-like network disturbance.

BACKGROUND: Cerebellar mutism syndrome (CMS) is a common and debilitating complication of posterior fossa tumour surgery in children. Affected children exhibit communication and social impairments that overlap phenomenologically with subsets of deficits exhibited by children with Autism spectrum disorder (ASD). Although both CMS and ASD are thought to involve disrupted cerebro-cerebellar circuitry, they are considered independent conditions due to an incomplete understanding of their shared neural substrates. METHODS: In this study, we analyzed post-operative cerebellar lesions from 90 children undergoing posterior fossa resection of medulloblastoma, 30 of whom developed CMS. Lesion locations were mapped to a standard atlas, and the networks functionally connected to each lesion were computed in normative adult and paediatric datasets. Generalizability to ASD was assessed using an independent cohort of children with ASD and matched controls (n=427). RESULTS: Lesions in children who developed CMS involved the vermis and inferomedial cerebellar lobules. They engaged large-scale cerebellothalamocortical circuits with a preponderance for the prefrontal and parietal cortices in the paediatric and adult connectomes, respectively. Moreover, with increasing connectomic age, CMS-associated lesions demonstrated stronger connectivity to the midbrain/red nuclei, thalami and inferior parietal lobules and weaker connectivity to prefrontal cortex. Importantly, the CMS-associated lesion network was independently reproduced in ASD and correlated with communication and social deficits, but not repetitive behaviours. CONCLUSIONS: Our findings indicate that CMS-associated lesions result in an ASD-like network disturbance that occurs during sensitive windows of brain development. A common network disturbance between CMS and ASD may inform improved treatment strategies for affected children.

Dissociable default-mode subnetworks subserve childhood attention and cognitive flexibility: Evidence from deep learning and stereotactic electroencephalography.

Cognitive flexibility encompasses the ability to efficiently shift focus and forms a critical component of goal-directed attention. The neural substrates of this process are incompletely understood in part due to difficulties in sampling the involved circuitry. We leverage stereotactic intracranial recordings to directly resolve local-field potentials from otherwise inaccessible structures to study moment-to-moment attentional activity in children with epilepsy performing a flexible attentional task. On an individual subject level, we employed deep learning to decode neural features predictive of task performance indexed by single-trial reaction time. These models were subsequently aggregated across participants to identify predictive brain regions based on AAL atlas and FIND functional network parcellations. Through this approach, we show that fluctuations in beta (12-30 Hz) and gamma (30-80 Hz) power reflective of increased top-down attentional control and local neuronal processing within relevant large-scale networks can accurately predict single-trial task performance. We next performed connectomic profiling of these highly predictive nodes to examine task-related engagement of distributed functional networks, revealing exclusive recruitment of the dorsal default mode network during shifts in attention. The identification of distinct substreams within the default mode system supports a key role for this network in cognitive flexibility and attention in children. Furthermore, convergence of our results onto consistent functional networks despite significant inter-subject variability in electrode implantations supports a broader role for deep learning applied to intracranial electrodes in the study of human attention.

Emerging Neurotechnologies: Implications for Professional Relations and Communication.

Rapid advances in neurotechnology and neurosurgery are positioned to revolutionize care for patients suffering from debilitating neurological and psychiatric disease. Enthusiasm for the adoption of these technologies is tempered by ethical dilemmas regarding resource allocation, provision of care, communication with patients and other providers, and other potential pitfalls. In the present work, we discuss bioethical implications of novel neurotechnologies for medical practice. In particular, we examine the implications of neurotechnological advancement through the lens of professional communication. Emerging challenges within this domain are presented in the context of physician interactions with four key partners: (i) patients; (ii) other physicians; (iii) industry; and (iv) society-at-large. Anticipated issues as well as mitigation strategies are discussed as they relate to communication with these stakeholders.

Which is more deleterious to cognitive performance? Interictal epileptiform discharges vs anti-seizure medication.

Children with epilepsy commonly have comorbid neurocognitive impairments that severely affect their psychosocial well-being, education, and future career prospects. Although the provenance of these deficits is multifactorial, the effects of interictal epileptiform discharges (IEDs) and anti-seizure medications (ASMs) are thought to be particularly severe. Although certain ASMs can be leveraged to inhibit IED occurrence, it remains unclear whether epileptiform discharges or the medications themselves are most deleterious to cognition. To examine this question, 25 children undergoing invasive monitoring for refractory focal epilepsy performed one or more sessions of a cognitive flexibility task. Electrophysiological data were recorded to detect IEDs. Between repeated sessions, prescribed ASMs were either continued or titrated to <50% of the baseline dose. Hierarchical mixed-effects modeling assessed the relationship between task reaction time (RT), IED occurrence, ASM type, and dose while controlling for seizure frequency. Both presence (ß ± SE = 49.91 ± 16.55 ms, p = .003) and number of IEDs (ß ± SE = 49.84 ± 12.51 ms, p < .001) were associated with slowed task RT. Higher dose oxcarbazepine significantly reduced IED frequency (p = .009) and improved task performance (ß ± SE = -107.43 ± 39.54 ms, p = .007). These results emphasize the neurocognitive consequences of IEDs independent of seizure effects. Furthermore, we demonstrate that inhibition of IEDs following treatment with select ASMs is associated with improved neurocognitive function.

Interictal discharges delay target-directed eye movements and impair attentional set-shifting in children with epilepsy.

OBJECTIVE: The theory of transient cognitive impairment in epilepsy posits that lapses in attention result from ephemeral disruption of attentional circuitry by interictal events. Eye movements are intimately associated with human attention and can be monitored in real time using eye-tracking technologies. Here, we sought to characterize the associations between interictal epileptiform discharges (IEDs), gaze, and attentional behavior in children with epilepsy. METHODS: Eleven consecutive children undergoing invasive monitoring with stereotactic electrodes for localization-related epilepsy performed an attentional set-shifting task while tandem intracranial electroencephalographic signals and eye-tracking data were recorded. Using an established algorithm, IEDs were detected across all intracranial electrodes on a trial-by-trial basis. Hierarchical mixed-effects modeling was performed to delineate associations between trial reaction time (RT), eye movements, and IEDs. RESULTS: Hierarchical mixed-effects modeling revealed that both the presence of an IED (ß ± SE = 72.74 ± 24.21 ms, p = .003) and the frequency of epileptiform events (ß ± SE = 67.54 ± 17.30 ms, p < .001) were associated with prolonged RT on the attentional set-shifting task. IED occurrence at the time of stimulus presentation was associated with delays in gaze initiation toward the visual targets (p = .017). SIGNIFICANCE: The occurrence of epileptiform activity in close temporal association with stimulus presentation is associated with delays in target-directed gaze and prolonged response time, hallmarks of momentary lapses in attention. These findings provide novel insights into the mechanisms of transient impairments in children and support the use of visual tracking as a correlate of higher order attentional behavior.

Decoding Intracranial EEG With Machine Learning: A Systematic Review.

Advances in intracranial electroencephalography (iEEG) and neurophysiology have enabled the study of previously inaccessible brain regions with high fidelity temporal and spatial resolution. Studies of iEEG have revealed a rich neural code subserving healthy brain function and which fails in disease states. Machine learning (ML), a form of artificial intelligence, is a modern tool that may be able to better decode complex neural signals and enhance interpretation of these data. To date, a number of publications have applied ML to iEEG, but clinician awareness of these techniques and their relevance to neurosurgery, has been limited. The present work presents a review of existing applications of ML techniques in iEEG data, discusses the relative merits and limitations of the various approaches, and examines potential avenues for clinical translation in neurosurgery. One-hundred-seven articles examining artificial intelligence applications to iEEG were identified from 3 databases. Clinical applications of ML from these articles were categorized into 4 domains: i) seizure analysis, ii) motor tasks, iii) cognitive assessment, and iv) sleep staging. The review revealed that supervised algorithms were most commonly used across studies and often leveraged publicly available timeseries datasets. We conclude with recommendations for future work and potential clinical applications.

The anterior and centromedian thalamus: Anatomy, function, and dysfunction in epilepsy.

The thalamus is a densely connected collection of nuclei that play a critical role in gating information flow across the neocortex. Through diffuse reciprocal cortico-thalamo-cortical connectivity, the anterior and centromedian nuclei exert remarkable control over cortically expressed activity. Consequently, mounting evidence implicates these thalamic centres in both the genesis and propagation of aberrant epileptiform activity across the brain. The present work reviews existing literature with regards to the anatomy, function, and dysfunction of the anterior and centromedian thalamic nuclei as they relate to epileptogenesis and ictal dynamics in humans. A confluence of electrophysiological, anatomical, and neuromodulatory evidence links these thalamic hubs to a variety of epilepsy syndromes. These data are discussed as they relate to targeted thalamic neuromodulation.

Connectomic profiling and Vagus nerve stimulation Outcomes Study (CONNECTiVOS): a prospective observational protocol to identify biomarkers of seizure response in children and youth.

INTRODUCTION: Vagus nerve stimulation (VNS) is a neuromodulation therapy that can reduce the seizure burden of children with medically intractable epilepsy. Despite the widespread use of VNS to treat epilepsy, there are currently no means to preoperatively identify patients who will benefit from treatment. The objective of the present study is to determine clinical and neural network-based correlates of treatment outcome to better identify candidates for VNS therapy. METHODS AND ANALYSIS: In this multi-institutional North American study, children undergoing VNS and their caregivers will be prospectively recruited. All patients will have documentation of clinical history, physical and neurological examination and video electroencephalography as part of the standard clinical workup for VNS. Neuroimaging data including resting-state functional MRI, diffusion-tensor imaging and magnetoencephalography will be collected before surgery. MR-based measures will also be repeated 12 months after implantation. Outcomes of VNS, including seizure control and health-related quality of life of both patient and primary caregiver, will be prospectively measured up to 2 years postoperatively. All data will be collected electronically using Research Electronic Data Capture. ETHICS AND DISSEMINATION: This study was approved by the Hospital for Sick Children Research Ethics Board (REB number 1000061744). All participants, or substitute decision-makers, will provide informed consent prior to be enrolled in the study. Institutional Research Ethics Board approval will be obtained from each additional participating site prior to inclusion. This study is funded through a Canadian Institutes of Health Research grant (PJT-159561) and an investigator-initiated funding grant from LivaNova USA (Houston, TX; FF01803B IIR).

Connectomic Profiles and Cognitive Trajectories After Epilepsy Surgery in Children.

BACKGROUND AND OBJECTIVES: Neurocognitive outcomes after surgery for temporal lobe epilepsy in childhood are variable. Postoperative changes are not directly predicted by seizure freedom, and associations between epilepsy, neuropsychological function, and developing neural networks are poorly understood. Here, we leveraged whole-brain connectomic profiling in magnetoencephalography (MEG) to retrospectively study associations between brain connectivity and neuropsychological function in children with temporal lobe epilepsy undergoing resective surgery. METHODS: Clinical and MEG data were retrospectively analyzed for children who underwent temporal lobe epilepsy surgery at the Hospital for Sick Children from 2000 to 2021. Resting-state connectomes were constructed from neuromagnetic oscillations via the weighted-phase lag index. Using a partial least-squares (PLS) approach, we assessed multidimensional associations between patient connectomes, neuropsychological scores, and clinical covariates. Bootstrap resampling statistics were performed to assess statistical significance. RESULTS: A total of 133 medical records were reviewed, and 5 PLS analyses were performed. Each PLS analysis probed a particular neuropsychological domain and the associations between its baseline and postoperative scores and the connectomic data. In each PLS analysis, a significant latent variable was identified, representing a specific percentage of the variance in the data and relating neural networks to clinical covariates, which included changes in rote verbal memory (n = 41, p = 0.01, σ2 = 0.38), narrative/verbal memory (n = 57, p = 0.00, σ2 = 0.52), visual memory (n = 51, p = 0.00, σ2 = 0.43), working memory (n = 44, p = 0.00, σ2 = 0.52), and overall intellectual function (n = 59, p = 0.00, σ2 = 0.55). Children with more diffuse, bilateral intrinsic connectivity across several frequency bands showed lower scores on all neuropsychological assessments but demonstrated a greater propensity for gains after resective surgery. DISCUSSION: Here, we report that connectomes characterized by diffuse connectivity, reminiscent of developmentally immature networks, are associated with lower preoperative cognition and postoperative cognitive improvement. These findings provide a potential means to understand neurocognitive function in children with temporal lobe epilepsy and expected changes postoperatively.

Brainstem Associated Somatosensory Evoked Potentials and Response to Vagus Nerve Stimulation: An Investigation of the Vagus Afferent Network.

Despite decades of clinical usage, selection of patients with drug resistant epilepsy who are most likely to benefit from vagus nerve stimulation (VNS) remains a challenge. The mechanism of action of VNS is dependent upon afferent brainstem circuitry, which comprises a critical component of the Vagus Afferent Network (VagAN). To evaluate the association between brainstem afferent circuitry and seizure response, we retrospectively collected intraoperative data from sub-cortical recordings of somatosensory evoked potentials (SSEP) in 7 children with focal drug resistant epilepsy who had failed epilepsy surgery and subsequently underwent VNS. Using multivariate linear regression, we demonstrate a robust negative association between SSEP amplitude (p < 0.01), and seizure reduction. There was no association between SSEP latency and seizure outcomes. Our findings provide novel insights into the mechanism of VNS and inform our understanding of the importance of brainstem afferent circuitry within the VagAN for seizure responsiveness following VNS.

Predicting response to psychiatric surgery: a systematic review of neuroimaging findings.

Background: Psychiatric surgery, including deep brain stimulation and stereotactic ablation, is an important treatment option in severe refractory psychiatric illness. Several large trials have demonstrated response rates of approximately 50%, underscoring the need to identify and select responders preoperatively. Recent advances in neuroimaging have brought this possibility into focus. We systematically reviewed the psychiatric surgery neuroimaging literature to assess the current state of evidence for preoperative imaging predictors of response. Methods: We performed this study in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-analysis of Observational Studies in Epidemiology (MOOSE) frameworks, and preregistered it using PROSPERO. We systematically searched the Medline, Embase and Cochrane databases for studies reporting preoperative neuroimaging analyses correlated with clinical outcomes in patients who underwent psychiatric surgery. We recorded and synthesized the methodological details, imaging results and clinical correlations from these studies. Results: After removing duplicates, the search yielded 8388 unique articles, of which 7 met the inclusion criteria. The included articles were published between 2001 and 2018 and reported on the outcomes of 101 unique patients. Of the 6 studies that reported significant findings, all identified clusters of hypermetabolism, hyperconnectivity or increased size in the frontostriatal limbic circuitry. Limitations: The included studies were few and highly varied, spanning 2 decades. Conclusion: Although few studies have analyzed preoperative imaging for predictors of response to psychiatric surgery, we found consistency among the reported results: most studies implicated overactivity in the frontostriatal limbic network as being correlated with clinical response. Larger prospective studies are needed. Registration: www.crd.york.ac.uk/prospero/display_record.php?RecordID=131151.