overview: Researchers explored four existing publicly available psychological and neurological data sets to determine the brain underlying psychiatric disorders such as depression, anxiety, bipolar disorder and schizophrenia. You’ve identified the networks in your region.
sauce: Brigham and Women’s Hospital
Mental illnesses such as schizophrenia and depression affect nearly one in five adults in the United States, and nearly half of those diagnosed with a mental illness also meet the one-second criterion.
With so much overlap, researchers are beginning to suspect a single neurobiological explanation for various psychiatric disorders.
A new study by researchers at Brigham and Women’s Hospital, a founding member of the Mass General Brigham Health Care system, examines four existing publicly available neurological and psychiatric datasets to identify the underlying causes of mental illness. identified a network of brain regions.
The result is nature human behavior.
“Traditionally, neurology and psychiatry have had different diagnostic strategies. Psychiatry.
“Neurology asks, ‘Where are the lesions? And the psychiatrist asks, “What are your symptoms?” We now have the tools to explore the “where” question of mental illness. This study investigated whether psychiatric disorders share common brain networks. ”
The researchers studied a series of structural brains from over 15,000 healthy controls, as well as patients diagnosed with schizophrenia, bipolar disorder, depression, addiction, obsessive-compulsive disorder, or anxiety. We started by analyzing the data. They found decreased gray matter in the anterior cingulate gyrus and insula, two brain regions commonly associated with mental illness.
However, only one-third of the studies showed reductions in gray matter in these brain regions. Moreover, neurodegenerative diseases also showed a reduction in gray matter in these same areas.
To address these shortcomings, the team used the human connectome (the wiring diagram of the human brain) to show that gray matter changes in psychiatric illness affect common brain networks more effectively than common brain regions. I tested if it is mapped.
Researchers found a trans-diagnostic network in which up to 85% of studies showed gray matter reduction. This network was specific for gray matter reduction in psychiatric and neurodegenerative diseases.
We then performed the same analysis, excluding data for one psychiatric diagnosis at a time. The trans-diagnostic network remains robust, suggesting that the identified network causes are not biased towards a single psychiatric disorder.
In a subsequent analysis of a dataset containing brain images from 194 veterans with and without a psychiatric diagnosis with and without head trauma, the researchers superimposed the lesions onto an interdiagnostic network and compared lesions within the network. We found that induced injury correlated with a higher likelihood of multiple psychiatric disorders. disease.
They also used veteran data to independently derive a cross-diagnostic network based on brain lesions associated with psychiatric disorders. They found that this lesion-based psychiatric network was very similar to the atrophy-based psychiatric network, even though it was derived from a completely different dataset.
Finally, the team used data from neurosurgical ablation for patients with extreme, incurable psychiatric disorders. These ablation targets coincide with transdiagnostic networks.
Most strikingly, their findings seem to challenge the notion that decreased gray matter in the anterior cingulate gyrus and insula is causally linked to mental illness.
“Lesions to these areas the following Shingles and islet atrophy may be a consequence or compensation rather than the cause of mental illness,” Taylor said.
Instead, their analysis points to the posterior parietal cortex as the brain network node most likely to be causally linked to mental illness.
By identifying an important, sensitive and specific trans-diagnostic network in psychiatric disorders, the team will analyze existing fMRI datasets to see if neural activation patterns follow the same circuit and to investigate the circuit. and have opened up many new directions for follow-up research. Based on differences across mental disorders. Taylor also plans to tune the network using transcranial magnetic stimulation (TMS), specifically targeting the occipital parietal region.
“Psychiatric disorders are brain disorders, and we are just beginning to have tools to study and modulate the underlying circuitry,” says Taylor. “These diseases may have more in common than we originally thought.”
About this Psychiatric and Mental Health Research News
author: press office
sauce: Brigham and Women’s Hospital
contact: Press Office – Brigham and Women’s Hospital
image: image is public domain
Original research: closed access.
“Trans-Diagnostic Network for Psychiatric Disorders Derived from Atrophy and Lesion” by Joseph Taylor et al. nature human behavior
Trans-diagnostic network for psychiatric disorders derived from atrophy and lesions
Psychiatric disorders share neurobiology and frequently coexist. This neurobiological and clinical overlap highlights trans-diagnostic therapeutic opportunities.
This study used coordinate and lesion network mapping to test shared brain networks across psychiatric disorders. A meta-analysis of 193 studies found that atrophy across six psychiatric disorders was linked to a common brain network defined by positive connections to the anterior cingulate gyrus and insula, and negative connections to the posterior parietal and lateral occipital lobes. mapped.
The network was robust to leave-one-diagnosis-out cross-validation and specific for atrophy coordinates due to psychiatric and neurodegenerative disorders (72 studies). In her 194 patients with penetrating head trauma, lesional damage to this network correlated with the number of postlesional psychiatric diagnoses. Neurosurgical ablation targets for psychiatric disorders (four targets) are also linked with the network.
This convergent brain network for psychiatric disorders may partially explain the high comorbidity of psychiatric disorders and may highlight targets for neuromodulation in patients with multiple psychiatric disorders.