Neurologist-Scientist in neuromodulation

Arjun Balachandar, MD, FRCPC, PhD-Candidate

Neurologist and aspiring clinician-scientist studying how neural signals can be used to build better, personalized brain stimulation therapies for neurological disorders.

My central focus: decode the neural activity underlying clinical states and use those biomarkers to drive adaptive brain stimulation that improves gait, sleep, severe movement symptoms, and neuropsychiatric dysfunction.

Arjun Balachandar logo
Neuromodulation
Deep Brain Stimulation
Brain-Computer Interfaces
Motor Neurophysiology
Movement Disorders
Computational Clinical Biomarkers

About

From Neural Biomarkers to Personalized Neuromodulation

Headshot of Dr. Arjun Balachandar

I am a neurologist specializing in movement disorders and a PhD candidate in neuromodulation under Drs. Alfonso Fasano and George Ibrahim, focused on leveraging intracranial electrophysiology and neural signal processing to advance neuromodulation interventions. The goal is to translate these biomarkers into actionable adaptive interventions that improve real clinical outcomes.

University of Toronto logo

PhD, Clinician-Scientist Training Program • 2024–

Adult Neurology Residency • 2019–2024

Doctor of Medicine • 2015–2019

University Health Network logo

Movement Disorders Fellow • 2024–

Research

Core research themes

My research is organized around two translational questions. First, can we understand the neural activity underlying clinical states? Second, how can we convert intracranial neural signals into actionable biomarkers that guide personalized neuromodulation treatment? Key areas include understanding and treating gait dysfunction using cortical BCIs, sleep-state decoding from DBS, and neural biomarkers for understudied movement disorders such as status dystonicus and pediatric dystonia.

Adaptive Neuromodulation for Parkinson's Disease

Developing closed-loop cortical and deep brain stimulation strategies that use neural signals to personalize therapy in Parkinson's disease.

Gait Impairment and Freezing of Gait

Building brain-machine interface and neuromodulation interventions to address gait dysfunction and freezing episodes that remain difficult to treat.

Status Dystonicus, Pediatric Dystonia and Severe Movement Disorders

Characterizing circuit-level biomarkers, including pallidal beta-band signatures, to better define and treat poorly understood pediatric movement disorders.

Sleep and Behavioral State Decoding from DBS

Using machine learning with chronic deep brain recordings to decode sleep states and other clinically relevant brain states.

Computational Methods in Translational Neurology

Applying machine learning to clinical and biometric signals using smartphone accelerometry and voice data to improve diagnosis, phenotyping, and automated-detection in various disorders including tremor and post-stroke dysphagia.

Pediatric DBS Safety and Outcomes

Studying surgical safety, complications, and clinical outcomes across pediatric deep brain stimulation targets and indications to inform evidence-based care.

Projects

Current and emerging initiatives

TORONTO WESTERN HOSPITAL

Adaptive Cortical Neuromodulation for Freezing of Gait

Co-Primary Investigator on a Michael J. Fox Foundation-funded study developing an electrocorticography-based brain-machine interface and adaptive cortical neuromodulation strategies for freezing of gait in Parkinson's disease, with the goal of enabling personalized symptom-responsive therapy.

Parkinson's DiseaseFreezing of GaitECoGBCIAdaptive Stimulation

THE HOSPITAL FOR SICK CHILDREN

Intracranial Biomarkers of Status Dystonicus & Generalized Dystonia

Analyzing longitudinal multi-year pallidal DBS recordings in pediatric status dystonicus and generalized dystonia to identify biomarkers linked to clinical severity, including excessive beta-band activity and functional connectivity signatures, to improve biomarker-guided diagnosis, monitoring, and treatment targeting.

Status DystonicusPediatric DBSIntracranial BiomarkersNature Communications

TORONTO WESTERN HOSPITAL

Automated Sleep Detection from DBS Recordings

Built machine-learning pipelines to detect sleep states using deep brain stimulation recordings in movement disorders, supporting closed-loop therapeutic development and objective sleep-state monitoring in clinical care.

DBSMachine LearningSleepBiomarkersMovement Disorders Journal

THE HOSPITAL FOR SICK CHILDREN

Pediatric DBS Safety Across Targets and Indications

Analyzed multicenter CHILD-DBS registry data to quantify surgical complications and safety outcomes across pediatric DBS targets and indications to guide evidence-based care in children.

Pediatric DBSCHILD-DBS RegistrySurgical SafetyNeurology 2025

SUNNYBROOK HEALTH SCIENCES CENTRE

Machine Learning Assisted Swallowing Assessment (MASA)

Worked with the Stroke Innovation (& Machine learning) Lab [SiLab] as co-Investigator on a Sunnybrook innovation grant applying clinical ML tools to improve post-stroke dysphagia screening in real-world care settings, employing neural networks trained using voice audio recordings alone to support scalable non-invasive screening pathways.

Clinical AIStrokeDigital HealthSunnybrook AFP

TORONTO WESTERN HOSPITAL

Smartphone Accelerometer & ML-based Neurologic Phenotyping

Developed computational approaches using smartphone accelerometry to classify tremor syndromes and support the development of automated tools for earlier diagnosis.

Smartphone BiomarkersTremorDystoniaTranslational Neurotech

Publications

Selected recent work

Nature Reviews Bioengineering · 2026 · Accepted

Neuromodulation for Gait Disorders

Balachandar A, Sorrento G, Moraud E, Bonizzato M, Fasano A.

Movement Disorders · 2026

Beta-band and aperiodic activity across new and chronic STN DBS in Parkinson's disease

Balachandar A, Boogers A, Naghdlou S, Lozano A, Kalia S, Tinkhauser G, Fasano A.

Nature Communications · 2025

Status dystonicus is a distinct state characterized by pallidal beta-band activity

Balachandar A, Vogt L, Mithani K, Coleman S, Ebden M, Fasano A, Gorodestky C, Ibrahim G.

CV

Curriculum Vitae

Recent Highlights

Selected recent grants and honors. Full details are available in the downloadable CV.

Recent Grants

  • 2026 • American Brain Foundation Next Generation Research Grant in Parkinson's Disease ($150,000 USD / 2 years)
  • 2024 • Parkinson Canada Clinician-Scientist Research Fellowship ($150,000 CAD / 2 years)
  • 2024 • Michael J. Fox Foundation grant (Co-Primary Investigator, $1,668,130.61 CAD)
  • 2023 • Sunnybrook AFP Innovation Grant (Co-Investigator, $53,161.50 CAD)

Recent Awards

  • 2025 • International Congress Travel Grant (MDS Congress)
  • 2024 • PGME Research Award - Joseph M. West Family Memorial Fund and Starr Medal ($13,750 CAD)
  • 2024 • Department of Medicine Outstanding Resident Researcher Award
  • 2024 • Resident Scholarship to the AAN Annual Meeting
Download CV (PDF)