麻豆传媒

LOS ANGELES (Dec. 17, 2024) -- 

Brain Cells in Social Situations

News — Cedars-Sinai investigators have identified the brain cells responsible for navigating everyday social situations, such as understanding which topics are best avoided in a conversation or gauging the emotions or motives of someone we are talking to. The study, published in the peer-reviewed journal , identified brain circuits that could be targeted to treat social impairments associated with conditions such as autism.

“Recording the activity of individual neurons in the brains of study participants, we found that distinct populations of neurons were dedicated to these tasks, which we call social inferences,” said , director of the Center for Neural Science and Medicine and professor of Neurosurgery, Neurology and Biomedical Sciences at Cedars-Sinai, and senior author of the study. “The ability to make decisions about these types of social situations is immensely important and frequently impaired by neurological disease, but the mechanisms behind it have been poorly understood.”

Investigators found that the neurons supporting social inferences were different than those supporting inferences based on nonsocial situations, such as noticing that the sidewalk is wet and inferring that it recently rained. They also found that separate neurons are dedicated to processing social information provided by hands versus that from faces and facial expressions.

AI Predicts Postpartum Depression Risk

Cedars-Sinai investigators have created machine learning (ML) models, a type of artificial intelligence, that can use patients’ electronic health records to predict—independent of racial minority biases—the risk of postpartum depression.

The ML models, described in the peer-reviewed journal , were more likely to correctly identify postpartum depression in racial minorities compared to non-Hispanic white patients. Because many postpartum women who are Black or Hispanic are not properly diagnosed with postpartum depression, the use of these models could help improve early detection across all racial groups, potentially leading to more equitable healthcare outcomes.

“Prior models assumed that all women evaluated for postpartum depression received the same treatment and often did not account for racial disparities,” said , senior author of the study and the co-director of the Center for Artificial Intelligence Research and Education and research assistant professor in the Department of Computational Biomedicine at Cedars-Sinai. “We were able to create models that did not perpetuate the same biases often seen in prior prediction models, suggesting the critical role of equity-centered modeling decisions in ensuring equitable patient care.”

Improving Diversity in Clinical Trials

Investigators can increase racial and ethnic diversity in clinical trials by updating language used in promotional materials, demonstrating cultural sensitivity and employing digital tools, a new study from Cedars-Sinai shows.

The study, published in the peer-reviewed , identified multiple strategies to address low participation rates of non-Hispanic Black and Hispanic patients in a National Institutes of Health-funded trial investigating virtual reality for chronic lower back pain. 

“Traditional recruitment strategies have not been effective in reaching these communities,” said , assistant professor of Neurosurgery at Cedars-Sinai and first author of the study. “We conducted focus groups with Black and Hispanic patients to understand their concerns and preferences, highlighting barriers to participation such as mistrust, lack of interest, cultural differences and ineffective communication. The insights we gained allowed us to revise our recruitment materials to be more culturally responsive, updating language, imagery and outreach methods. We also used advanced digital tools to scan electronic medical records and micro-target eligible Black and Hispanic patients for the trial.” 

After these changes were implemented, recruitment of Hispanic participants into the trial more than quadrupled, and recruitment of Black participants showed a notable upward trend. Ross said these results demonstrate that culturally adapted recruitment strategies and digital targeting tools can play a critical role in improving clinical trial diversity, and offer actionable insights for researchers aiming to bridge the gap in clinical trial representation of diverse communities.

A New Brain ‘Traffic Map’

Bringing together structural and functional brain imaging data, Cedars-Sinai investigators have created a “traffic map” to illustrate which pathways are most frequently used for interactions between different regions of the brain and enable the regions to communicate with each other. The new model, which also can help predict cognitive performance, is described in the peer-reviewed journal .

“Our model, called the Unified Structural and Functional Connectivity model, provides a first step toward mapping how different parts of the brain functionally communicate,” said , director of Neuroimaging Research and professor of Biomedical Sciences at Cedars-Sinai and senior author of the study. “The model shows that certain structural pathways, especially in networks related to emotions, self-awareness, and sensory processing, are heavily used for brain communications. The model also enhances our understanding of how these interactions relate to cognitive function.”

The investigative team—led by Gao, study co-author Pascal Sati, PhD, director of the Neuroimaging Program and associate professor of Neurology, and first author Arzu Silemek, PhD, a postdoctoral fellow supervised by Gao and Sati—found that certain areas serve as crucial hubs, with a significant corridor facilitating overall brain connectivity. They believe this mapping of brain communication could inform future research on cognitive processes and neurodevelopmental disorders. Clinically, they suggested it could improve physicians’ diagnostic tools by providing insights into how structural changes affect brain function, potentially leading to better-targeted interventions for conditions such as Alzheimer’s disease and other cognitive disorders.