Donna Lang

Prospective Graduate Students / Postdocs

This faculty member is currently not actively recruiting graduate students or Postdoctoral Fellows, but might consider co-supervision together with another faculty member.

Associate Professor

Research Classification

Research Interests

Structural Neuroimaging
Cardiovascular Function
Microvascular integrity

Relevant Thesis-Based Degree Programs

Affiliations to Research Centres, Institutes & Clusters

Research Options

I am available and interested in collaborations (e.g. clusters, grants).
I am interested in and conduct interdisciplinary research.
I am interested in working with undergraduate students on research projects.


In 1995, as a new graduate student in the department of psychiatry, I began investigating the morphological phenomena of schizophrenia and related psychotic disorders. These initial in-vivo investigations involved the application of CT (Computed Tomography) imaging to examine phenotypic characteristics of brain morphology in families affected by schizophrenia. Since that time, my research has moved forward into multi-modal applications of MRI (magnetic resonance imaging) to investigate the effects of antipsychotic medications on brain structure in schizophrenia, the relationships between structure, symptoms and cognition in psychotic disorders and first-episode psychosis, and more recently, the interactions between substance abuse, psychosis and systemic infections on brain morphology.

Currently, all my neuroimaging research data are obtained at UBC on the high-field research scanner, which produces exceptionally high quality scans and gives researchers the capability to examine physiological, biochemical and physical markers in the brain. This has allowed me, along with the residents and graduate students I work with, to examine the neurocircuitry and metabolic characteristics of psychotic disorders using diffusion tensor imaging and susceptibility-weighted imaging. My current projects involve the investigation of the effects of exercise on hipppocampal volume and vascularization in chronic schizophrenia patients and in adolescent psychosis patients. Additionally, I am involved in a large longitudinal imaging study of multi-diagnosis addiction, psychosis and infection subjects over the course of 5-8 years. Some of the goals of this study include investigating the interactions of life circumstances, addiction, mental illness and physical illnesses in an urban population, and how these interactions have affected quality of life, health care access, persistence of mental disorder/addictions and neurobiological integrity.

Research Methodology

Neuroimaging data analysis

Great Supervisor Week Mentions

Each year graduate students are encouraged to give kudos to their supervisors through social media and our website as part of #GreatSupervisorWeek. Below are students who mentioned this supervisor since the initiative was started in 2017.


My supervisor is great because of the support she provides. Not only does she make sure that I'm supported financially but she cares about my personal well-being and my career and we can openly talk about both. She's created an environment where I'm not afraid to talk about personal or professional struggles and wins. She is a #GreatSupervisor

Peter Senften (2019)


Graduate Student Supervision

Doctoral Student Supervision

Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.

Exercise, symptom severity, and neuroplasticity in schizophrenia (2020)

Schizophrenia is a debilitating disorder marked by psychosis and deficits in cognition and social functioning. It is further characterized by metabolic, neurovascular and cardiovascular deficits that interact with, or compound adverse medication-linked cardiovascular effects. Neuroanatomic deficits are seen even at early stages of illness. Reductions in frontal and temporal lobe grey matter, particularly the hippocampus, are among the most consistent findings. Prefrontal-limbic network deficits are associated with more severe positive symptoms and more cognitive impairments in psychosis patients. Additionally, reduced cardiorespiratory fitness has been linked to decreased hippocampal volume and cortical thickness. Exercise interventions are known to mitigate the negative antipsychotic-associated cardiometabolic side effects and promote hippocampal growth and cortical expansion. Yet, the efficacy of exercise as a non-pharmacological intervention to address anatomic and clinical deficits in psychosis patients is unclear. This study examines the effect of exercise on hippocampal and neocortical plasticity, and clinical outcomes in chronic schizophrenia, early psychosis and in an animal model as proof of principle. First, hippocampal volume increase and symptom severity decrease in chronically treated schizophrenia patients were observed. Compared to healthy volunteers, chronically treated patients had decreased fusiform cortical thickness. Patients who participated in the aerobic intervention had a greater increase in orbitofrontal cortical thickness compared to patients in the resistance training group. Second, early psychosis patients who completed the aerobic intervention had increased thickness in the entorhinal and fusiform cortices. For the aerobic group only, increases in the entorhinal and fusiform temporal gyri were associated with decreasing psychosis symptom severity, particularly for general psychopathology. Last, exercising rats had greater layer II entorhinal cortical thickness compared to sedentary rats, but there was no effect of exercise observed for rats treated with olanzapine. Greater entorhinal cortical thickness was associated with increased activity and improved fasting glucose and fasting insulin levels in rats. The cardiovascular burden in schizophrenia, and antipsychotic treatment has a strong negative impact on patient outcomes. Clinically appropriate exercise represents a non-pharmacologic, safe approach to reduce psychotic symptoms, and remediate neuroanatomic deficits while improving cardiovascular health, counteracting the adverse effects of antipsychotic medication.

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Master's Student Supervision

Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.

Stimulant and opioid dependence effects on enlarged perivascular spaces in a marginalized population (2022)

The full abstract for this thesis is available in the body of the thesis, and will be available when the embargo expires.

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The effects of exercise on white matter in the brain and emotion recognition in a treatment resistant schizophrenia population (2021)

Treatment-resistant schizophrenia is characterized by deficits in cognition, emotion recognition, cardiovascular health, and brain white matter (WM). Reductions in frontal-temporal white matter (WM) volumes in schizophrenia are associated with psychotic symptoms, cognitive deficits, poor emotional recognition, and cardiometabolic disorder. Regular exercise is posited to attenuate or restore functionality in multiple domains, but the efficacy of exercise as a non-pharmacological treatment for schizophrenia is unknown. Our goal was to examine the effects of exercise on WM in treatment-resistant schizophrenia. Fifteen treatment-resistant schizophrenia patients and 10 age, gender and education matched healthy volunteers were included in a 12-week exercise intervention. At baseline, compared to healthy volunteers, patients had decreased myelin water fraction (MWF) in the genu, callosal body, splenium, external capsule, cingulum, superior longitudinal fasciculus, and forceps minor with corrected p-values ranging from 0.03 to 0.04 and hedges’ g effect sizes ranging from -0.76 to -1.03. Patients also had decreased fractional anisotropy (FA) in the genu (p = 0.03, g = -1.29) and the forceps minor (p = 0.03, g = -1.23). Patients also had slower reaction times in emotion expression tasks (p
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Evaluation of automated hippocampal segmentation software in a clinically heterogeneous sample (2013)

Accurate, efficient processing of magnetic resonance images (MRI) offers potential value for both basic and clinical neuroscience; however, the current gold standard method of doing so is manual segmentation, a labor-intensive process with inherent variability. Limitations associated with manual segmentation have motivated the development of automated software programs for structural MRI processing and volumetric analysis of subcortical brain structures. The three most commonly used platforms are FSL, FreeSurfer, and SPM. As each platform uses a unique mathematical algorithm for image analysis, it is necessary to determine which program offers optimal subcortical segmentation, particularly for high field-strength imaging. The current study compared automated volumetric analysis of the human hippocampus with manualsegmentation values in a clinically complex population in order to determine which method provides the most robust results in the presence of motion artifact, a common problem in MR, and visible anatomic anomalies of the hippocampi. MRI data included in the current study was obtained from residents of Vancouver B.C’s Downtown Eastside (DTES) social housing projects, the majority of whom experience co-occurring addiction/polysubstance abuse and severe mental illness. A large number of these MRI scans are characterized by abnormal hippocampal morphology, perhaps resultant of neuropsychiatric illness, addiction, infection, or interactions of these factors. Intraclass correlations (ICC) were used to determine which set of automated hippocampal volumes best correlated with manual measures in motion artifact-free MRI data with and without bilateral abnormal hippocampal cavities. FreeSurfer volumes were most correlated with manual measurements regardless of whether MRI data included hippocampal cavities or not (ICC=0.88, no cavities; 0.48 with cavities), followed by FSL/FIRST (ICC=0.64, no cavities; ICC=0.43, with cavities), and SPM8.0/AAL (ICC=0.039, with cavities; ICC=0.035, no cavities). FSL/FIRST was the most sensitive to severe motion artifact(ICC=0.62), followed by FreeSurfer 5.1 (ICC=0.85), manual segmentation (ICC=0.96), and SPM8.0/AAL (ICC=0.99). ICCs for FreeSurfer 5.1 vs. FSL/FIRST were 0.87 (no motion artifact, no hippocampal cavities), 0.87 (no motion artifact, bilateral hippocampal spaces), and 0.64 (MRI scans with severe motion artifact). These data suggest automated segmentation methods are sensitive to MRI data with compromised image quality and deviations in normal hippocampal morphology.

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Membership Status

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