The success of deep brain stimulation (DBS) relies on applying carefully titrated therapeutic stimulation at specific targets. Once implanted, the electrical stimulation parameters at each electrode contact can be modified. Iteratively adjusting the stimulation parameters enables testing for the optimal stimulation settings. Due to the large parameter space, the currently employed empirical testing of individual parameters based on acute clinical response is not sustainable. Within the constraints of short clinical visits, optimization is particularly challenging when clinical features lack immediate feedback, as seen in DBS for dystonia and depression and with the cognitive and axial side effects of DBS for Parkinson’s disease. A personalized approach to stimulation parameter selection is desirable as the increasing complexity of modern DBS devices also expands the number of available parameters. This review describes three emerging imaging and electrophysiological methods of personalizing DBS programming. Normative connectome-base stimulation utilizes large datasets of normal or disease-matched connectivity imaging. The stimulation location for an individual patient can then be varied to engage regions associated with optimal connectivity. Electrophysiology-guided open- and closed-loop stimulation capitalizes on the electrophysiological recording capabilities of modern implanted devices to individualize stimulation parameters based on biomarkers of success or symptom onset. Finally, individual functional MRI (fMRI)-based approaches use fMRI during active stimulation to identify parameters resulting in characteristic patterns of functional engagement associated with long-term treatment response. Each method provides different but complementary information, and maximizing treatment efficacy likely requires a combined approach.

Background: Tuberous Sclerosis Complex (TSC) is a multisystemic neurocutaneous disorder in which hamartomas confer significant medical risks, including mortality, by disruption of local tissues. However, only recently have multiple studies assessed specific aetiologies of mortality in TSC. Methods: A literature review of all available studies examining mortality in TSC was conducted until December 15, 2024. Results: We identified 13 studies reporting 411 deaths from 6735 individuals with TSC. Crude mortality per 100 individuals ranged from 1.4-13.8 over average intervals of 11-45 years. Mortality risk ranged from 3.0-4.9 (mean 4.3) versus the general population. Mean life expectancy was 66.2 years compared to 81.8 in the general population. In seven studies that reported specific aetiologies of mortality, 6/7 (85%) had renal (commonly renal failure or angiomyolipoma hemorrhage) or brain disease (most frequently sudden unexpected death in epilepsy or brain tumours) as the most common cause of mortality. Intellectual delay conferred increased mortality risk. Lymphangioleiomyomatosis conferred significant risk of mortality in adult women and cardiac rhabdomyomas were the dominant cause of neonatal mortality. Conclusions: Mortality in TSC is elevated compared to the general population, with brain and renal disease most frequently culpable. Future studies should assess the impact of disease modifying therapies on mortality in TSC.

PET imaging is increasingly recognized as an important diagnostic tool to investigate patients with cognitive disturbances of possible neurodegenerative origin. PET with 2-[18F]fluoro-2-deoxy-D-glucose ([18F]FDG), assessing glucose metabolism, provides a measure of neurodegeneration and allows a precise differential diagnosis among the most common neurodegenerative diseases, such as Alzheimer’s disease, frontotemporal dementia or dementia with Lewy bodies. PET tracers specific for the pathological deposits characteristic of different neurodegenerative processes, namely amyloid and tau deposits typical of Alzheimer’s Disease, allow the visualization of these aggregates in vivo. [18F]FDG and amyloid PET imaging have reached a high level of clinical validity and are since 2022 investigations that can be offered to patients in standard clinical care in most of Canada.

This article will briefly review and summarize the current knowledge on these diagnostic tools, their integration into diagnostic algorithms as well as perspectives for future developments.

Indigenous Peoples in Canada are comprised of First Nations, Inuit and Métis and are the youngest and fastest growing population in the country. However, there is limited knowledge of how they are affected by multiple sclerosis (MS), the most common nontraumatic neurological disease of young adults, with Canada having one of the highest prevalences in the world. In this narrative review, we outline the limited studies conducted with Indigenous Peoples living with MS in Canada and the gaps in the literature. From the limited data we have, the prevalence of MS in Indigenous Peoples is lower, but the disease appears to be more aggressive. Given the dearth of Canadian data, we explore the worldwide MS studies of Indigenous populations. Lastly, we explore ways in which we can improve our understanding of MS among Indigenous Peoples in Canada, which entails building trust and meaningful relationships with these communities and acknowledging past and ongoing injustices. Furthermore, healthcare professionals conducting research with Indigenous Peoples should undergo training in cultural safety and data sovereignty, including principles of ownership, control, access and possession to have greater engagement with Indigenous communities to conduct more relevant research. With joint efforts between healthcare professionals and Indigenous communities, the scientific research community can be positioned to conduct better, more appropriate and desperately needed research, ultimately with improvements in the delivery of care to Indigenous Peoples living with MS in Canada.

The 7th edition of the Canadian Stroke Best Practice Recommendations (CSBPR) is a comprehensive summary of current evidence-based recommendations, appropriate for use by healthcare providers and system planners, and intended to drive healthcare excellence, improved outcomes and more integrated health systems. This edition includes a new module on the management of cerebral venous thrombosis (CVT). Cerebral venous thrombosis is defined as thrombosis of the veins of the brain, including the dural venous sinuses and/or cortical or deep veins. Cerebral venous thrombosis is a rare but potentially life-threatening type of stroke, representing 0.5–1.0% of all stroke admissions. The reported rates of CVT are approximately 10–20 per million and appear to be increasing over time. The risk of CVT is higher in women and often associated with oral contraceptive use and with pregnancy and the puerperium. This guideline addresses care for adult individuals who present to the healthcare system with current or recent symptoms of CVT. The recommendations cover the continuum of care from diagnosis and initial clinical assessment of symptomatic CVT, to acute treatment of symptomatic CVT, post-acute management, person-centered care, special considerations in the long-term management of CVT, including pregnancy and considerations related to CVT in special circumstances such as trauma and vaccination. This module also includes supporting materials such as implementation resources to facilitate the adoption of evidence into practice and performance measures to enable monitoring of uptake and effectiveness of recommendations.

Acquired prosopagnosia is a rare disorder, but it serves as a model for impairments in expert-level visual processing. This review discusses five key observations made over the past 30 years. First, there are variants, an apperceptive type linked to damage to the inferior occipitotemporal cortex and an amnestic type associated with anterior temporal lesions, both either right or bilateral. Second, these variants are clustered in syndromes with other perceptual deficits, the apperceptive type with field defects, dyschromatopsia and topographagnosia, and the amnestic type with topographagnosia and the auditory disorders of phonagnosia and acquired amusia. Third, extensive testing often shows additional problems with recognizing exemplars of other objects, especially when degrees of expertise are taken into account. Fourth, the prosopagnosic impairment does not affect all facial information. For example, the perception of expression and lip-reading likely depends on other neural substrates than those for processing facial identity. Last, face perception in prosopagnosia is not immutable but can improve with extensive training, though as yet this does not represent a cure for the condition. Continuing work with neural networks and animal models will enhance our understanding of this intriguing condition and what it tells us about how our brains process vision.

The diagnosis of central nervous system tumours has been transformed in recent years from a microscopic morphology-based process to one dominated by the identification of somatic genetic alterations in tumour cells. This switch requires implementing radically different methods, for which appropriate training and financial resources must be allocated. The Canadian Association of Neuropathologists (CANP) has followed a process based on the scientific literature and consensus to develop recommendations for molecular testing of tumours of the brain and spinal cord, aiming to balance the need for treatment-determinant accurate diagnosis and the current limitations inherent in the transition to a new paradigm. The Professional Affairs Committee was charged with this task. A draft was discussed during the CANP general assembly, along with presentations from groups who had implemented molecular technologies, as well as others who relied on external laboratories. The Professional Affairs Committee summarised the consensus and submitted their recommendation to the CANP’s Executive Committee. A final report was posted on the CANP website for a month to allow all members to comment. The recommendations below apply to intrinsic tumours of the central nervous system and do not include metastatic disease or tumours impinging upon the nervous system from outside. These recommendations should be considered clinically relevant, as the results have direct consequences on the patient’s treatment, either through the use of targeted therapies or the trial-proven best application of radiation and/or chemotherapy.

Background: Electroencephalography (EEG) has emerged as a minimally invasive technique to quantify functional changes in neural activity associated with neurodegenerative disorders such as Alzheimer’s Disease (AD). Given its non-invasive approach, EEG has the potential to fill the pressing gap forearly, accurate, and accessible methods to detect and characterize disease progression in AD. Methods: To address these challenges, we conducted a pilot analysis of a custom machine learning-based automated preprocessing and feature extraction pipeline to identify indicators of AD and correlates of disease progression. Results: Our pipeline successfully detected several new and previously established EEG-based measures indicative of AD status and progression. Key findings included alterations in delta and theta band power, network connectivity disruptions, and increased slowing of brain rhythms. Additionally, we observed strong correlations between EEG-derived metrics and clinical measures such as Mini-Mental State Examination (MMSE) scores, supporting the external validity of our approach. These findings highlight the sensitivity of EEG biomarkers in differentiating between early and late stages of AD. Conclusions: Our findings suggest that this automated approach provides a promising initial framework for implementing EEG biomarkers in the AD patient population, paving the way for improved diagnostic and monitoring strategies.

Electroencephalography is an accessible, portable, noninvasive and safe means of evaluating a patient’s brain activity. It can aid in diagnosis and management decisions for post-cardiac arrest patients with seizures, myoclonus and other non-epileptic movements. It also plays an important role in a multimodal approach to neuroprognostication predicting both poor and favorable outcomes. Individuals ordering, performing and interpreting these tests, regardless of the indication, should understand the supporting evidence, logistical considerations, limitations and impact the results may have on postarrest patients and their families as outlined herein.

Background: The combination of PARP inhibitor and immune checkpoint inhibitors have been proposed as a potentially synergistic combinatorial treatment in IDH mutant glioma, targeting dysregulated homologous recombination repair pathways. This study analyzed the cell-free DNA methylome of patients in a phase 2 trial using the PARP inhibitor Olaparib and the PD-1 inhibitor Durvalumab. Methods: Patients with recurrent high-grade IDH-mutant gliomas were enrolled in a phase II open-label study (NCT03991832). Serum was collected at baseline and monthly and cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) was performed. Binomial GLMnet models were developed and model performance was assessed using validation set data. Results: 29 patients were enrolled between 2020–2023. Patients received olaparib 300mg twice daily and durvalumab 1500mg IV every 4 weeks. The overall response rate was 10% via RANO criteria. 144 plasma samples were profiled with cfMeDIP-seq along with 30 healthy controls. The enriched circulating tumour DNA methylome during response periods exhibited a highly specific signature, accurately discriminating response versus failure (AUC 0.98 ± 0.03). Additionally, samples that were taken while on treatment were able to be discriminated from samples off therapy (AUC 0.74 ± 0.11). Conclusions: The cell-free plasma DNA methylome exhibits highly specific signatures that enable accurate prediction of response to therapy.

The innate and adaptive immune systems are critical in defense against pathogens and ensuring homeostasis. The central nervous system (CNS) was initially considered to be impermeable to immune cells due to the blood–brain barrier. However, this has now been debunked, with modern research delineating immune cell trafficking within the CNS, ensuring constant immune surveillance. However, these defenses may be breached in infections, which trigger an inflammatory cascade causing tissue damage. In addition, autoimmune conditions and genetic mutations may also lead to sustained proinflammatory molecule release causing significant CNS damage. Ensuing brain injury from most immune triggers is varied but may be associated with common patterns by virtue of a shared immune driver. MRI plays an important role in identifying these conditions and further enables understanding of their pathophysiology as well as their spatial predilection in the brain. In this review, we discuss basic immunology, the major CNS barriers to infections as well as the current understanding of selected pediatric infections and inflammatory processes.