Publications by authors named "Prabhjot Dhami"

Article Synopsis
  • Current antidepressants show limited effectiveness, prompting research to identify biological targets for new treatments and understand their mechanisms.
  • The study utilized EEG data from two Canadian trials to examine how changes in brain wave patterns (neural oscillations) correlate with symptom improvement in patients undergoing pharmacological and CBT treatments.
  • Findings indicate that early increases in theta waves and late changes in delta and alpha waves are linked to better treatment outcomes, with common patterns observed in both treatment methods, enhancing our understanding of how depression treatments work.
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Understanding how spontaneous brain activity influences the response to neurostimulation is crucial for the development of neurotherapeutics and brain-computer interfaces. Localized brain activity is suggested to influence the response to neurostimulation, but whether fast-fluctuating (i.e.

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Theta burst stimulation (TBS), a specific form of repetitive transcranial magnetic stimulation (TMS), is a promising treatment for youth with Major Depressive Disorder (MDD) who do not respond to conventional therapies. However, given the variable response to TBS, a greater understanding of how baseline features relate to clinical response is needed to identify which patients are most likely to benefit from this treatment. In the current study, we sought to determine if baseline neurophysiology, specifically cortical excitation and/or inhibition, is associated with antidepressant response to TBS.

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Importance: Untreated depression is a growing public health concern, with patients often facing a prolonged trial-and-error process in search of effective treatment. Developing a predictive model for treatment response in clinical practice remains challenging.

Objective: To establish a model based on electroencephalography (EEG) to predict response to 2 distinct selective serotonin reuptake inhibitor (SSRI) medications.

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Cognitive behavioral therapy (CBT) is often recommended as a first-line treatment in depression. However, access to CBT remains limited, and up to 50% of patients do not benefit from this therapy. Identifying biomarkers that can predict which patients will respond to CBT may assist in designing optimal treatment allocation strategies.

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Background: Major depressive disorder (MDD) is associated with various cognitive impairments, including response inhibition. Deficits in response inhibition may also underlie poor antidepressant treatment response. Recent studies revealed that the neurobiological correlates of response inhibition can predict response to pharmacological treatments.

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Background: Theta burst stimulation (TBS) has recently been proposed as a novel treatment for youth depression. However, the impact of TBS on the youth brain and neurophysiological predictors of response to TBS in this population have not been investigated.

Methods: Cortical reactivity was assessed at baseline and following 2 weeks of bilateral dorsolateral prefrontal cortex (DLPFC) TBS treatment in 16 youth with depression (aged 16-24 years old).

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Up to 50% of youth with depression do not respond to conventional first-line treatments. However, little research has been conducted on the pathophysiology of youth depression, hindering the identification of more effective treatments. Our goal was to identify neurophysiological markers that differentiate youth with depression from healthy youth and could serve as targets of novel treatments.

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Background: Conventional treatments for youth depression, such as antidepressants, have modest efficacy, side effects, and ongoing controversies regarding safety. Repetitive transcranial magnetic stimulation (rTMS), specifically theta burst stimulation (TBS), applied to the dorsolateral prefrontal cortex (DLPFC) has demonstrated efficacy for the treatment of depression in adults. However, the feasibility and clinical response to TBS for youth depression has yet to be explored.

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Subsequent to global initiatives in mapping the human brain and investigations of neurobiological markers for brain disorders, the number of multi-site studies involving the collection and sharing of large volumes of brain data, including electroencephalography (EEG), has been increasing. Among the complexities of conducting multi-site studies and increasing the shelf life of biological data beyond the original study are timely standardization and documentation of relevant study parameters. We present the insights gained and guidelines established within the EEG working group of the Canadian Biomarker Integration Network in Depression (CAN-BIND).

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Neurorehabilitation programs are commonly employed with the goal to help restore functionality in patients. However, many of these therapies report only having a small impact. In response to the need for more effective and innovative approaches, rehabilitative methods that take advantage of the neuroplastic properties of the brain have been used to aid with both physical and cognitive impairments.

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