Research Post # 1
This week I read a several research papers to gain background knowledge on neuroscience and machine learning (ML) applications to neuroscience datasets. One paper that I found interesting was about the applications of human brain connectomics to clinical psychiatry (linked here).
Connectomics is the study of connections between neurons in the human brain. We can take various measures of connectomics through noninvasive techniques such as functional magnetic resonance imaging (fMRIs), diagnostic tests, prognostic indicators, and therapeutic predictors.
There are two main models of applying connectomics to psychiatry: the “internal medicine” model and the “surgical” model. The internal medicine model is essentially using brain imaging as a tool to diagnose diseases. By observing abnormalities in the imaging, doctors can diagnose patients with more certainty. However there are two main problems with this model. First, in studies pertaining to this method thus far, sample sizes have been inadequate leading to false positive findings; people were “diagnosed” when they did not really have the disease. Second, since every person’s brain is different there are consistent fluctuations in measurements from individuals, making it challenging to study connectivity at a reliable level. Even when looking at the same individual, after a period of time, the test may yield different results. This only stresses the unreliability of the internal medicine model.
Dissimilarly, the “surgical” model focuses on using imaging as a method of treatment and does not face the same challenges. There are two key benefits of the surgical model. First, unlike the internal medicine model, consistent results were conceived across a variety of subjects as well as temporally on the same individual. This consistency depicts the reliability of the model. Reliability is critical as reliable results within individuals can potentially allow for personalized treatment. The second benefit is brain imaging can identify which part of the brain is causing the disorder, even if the disorder is not well defined.
Surgeons may take advantage of the second benefit by targeting brain regions using neuromodulation techniques like deep brain stimulations (DBS) and transcranial magnetic stimulation (TMS). Neuromodulation is the technology that acts directly upon nerves, often to ail a mental illness; DBS and TMS are some examples of neuromodulation procedures. After a comprehensive psychiatric evaluation, regions of the brain would be classified as the most relevant to various psychiatric conditions (e.g: obsessive compulsive disorder, depression, anxiety, etc.). Then, an MRI would be used to localize a targeted brain region based on its connectivity to the relevant brain regions and after that, DBS and TMS would be utilized to treat the patient.
There are several applications of connectomics in clinical psychiatry, primarily in treatment. As of now the surgical model is feasible to incorporate into present-day psychiatry, and in the future, there is hope that connectomics will evolve to also allow for a successful internal medicine model as well. In the field of psychiatry, researchers predict that psychiatrists may need to learn about the use of connectomics to monitor and modulate neurobehavioral systems as it becomes more prevalent to the treatment and diagnoses of psychiatric conditions.