#neuroimaging — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #neuroimaging, aggregated by home.social.
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DATE: September 21, 2026 at 09:00AM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Brain structure, function, and behavior show independent patterns of sex differences
Men and women show distinct biological differences in how their brains activate during various tasks, the physical size of specific brain regions, and their behavioral traits. A new study published in Nature Communications reveals that while each of these factors can accurately predict a person’s sex, an individual’s degree of sex typicality in one domain is entirely unrelated to the others. These results suggest that sex differences in the human brain are highly context-dependent and operate independently across structure, function, and behavior.
Biological sex differences appear in the prevalence of various neuropsychiatric conditions, such as autism and mood disorders. They also manifest in specific aspects of cognition and physical behavior. Past neuroimaging research has attempted to map out how male and female brains differ in their physical structure and functional activity.
Functional magnetic resonance imaging, or fMRI, allows researchers to observe which brain regions activate when a person performs specific mental tasks. Structural MRI measures the physical volume and shape of brain tissue. Many previous fMRI studies on sex differences have relied on small numbers of participants completing single tasks. This reliance on limited data has led to intense debate about the true extent and relevance of sex differences in human brain function.
To address this gap, researchers Siyuan Liu and Armin Raznahan at the National Institute of Mental Health led a comprehensive analysis of brain activity, anatomy, and behavior. The research team aimed to determine if sex differences in brain function are tied to specific tasks, if they align with physical brain volume, and how they relate to behavior.
The researchers analyzed data from nearly 1,000 healthy young adults. The participants underwent fMRI scans while completing seven different tasks. These tasks were designed to measure emotion processing, gambling, relational reasoning, social cognition, language processing, working memory, and motor skills. By scanning participants during this wide array of activities, the team could observe both task-specific brain activation and general activation patterns.
The analysis revealed widespread sex differences in brain activation across 85 percent of the outer layer of the brain, known as the cerebral cortex. These differences were highly reproducible but mostly specific to individual tasks. For instance, certain brain regions showed more activation in females during a language task but more activation in males during a gambling task.
A small number of regions, particularly those involved in motor control and physical sensation, showed a general tendency for higher activation in females across all seven tasks. Across the board, the effect sizes for these functional differences were small to moderate.
Next, the researchers examined whether these functional differences matched up with anatomical differences. They used structural MRI scans from the same participants to measure the volume of gray matter, which is the tissue containing the main bodies of nerve cells. The team found reproducible sex differences in gray matter volume across various regions of the cerebral cortex.
They then mapped the areas with functional activation differences over the areas with physical volume differences. The spatial patterns did not overlap in a coordinated way. Brain regions that exhibited sex differences in volume were generally not the same regions that showed sex differences in task activation. This lack of alignment suggests that sex differences in brain structure and brain function represent distinct biological phenomena.
The team then incorporated behavioral data, analyzing participant scores across 86 different behavioral traits. These traits ranged from physical grip strength and visual judgment to tendencies toward anxiety and psychological distress. Using a machine learning framework, the researchers tested whether an individual’s combined profile of brain activity, brain volume, or behavior could predict their biological sex.
The machine learning models accurately predicted a participant’s sex based on any of the three categories alone. Task-specific brain activation predicted sex with 88 percent accuracy, regional brain volume with 86 percent accuracy, and behavior with 91 percent accuracy. The models also generated a sex typicality score for each person within each category, rating how closely their data matched the average male or female profile.
Despite the high predictive accuracy of all three categories, a participant’s sex typicality score in one domain did not correlate with their score in another. An individual might have a highly male-typical brain volume, but a strongly female-typical pattern of brain activation during a language task. Only a tiny fraction of individuals exhibited consistently male-typical or female-typical profiles across all measurements of brain and behavior.
In their final analysis, the researchers looked for interactions between sex, brain activation, and behavior. They conducted a brain-wide association study to see if variations in brain activation between individuals correlated with variations in behavior. They first confirmed that measurable links exist between task-induced brain activation and specific behavioral traits within each sex group.
When the team compared these brain-behavior associations between men and women, they found striking similarities. The overall topography of how brain activity relates to behavior is broadly consistent across both sexes. The researchers detected a few isolated instances where the relationship between brain activity and behavior diverged between males and females. However, these rare differences did not preferentially involve behaviors that were themselves heavily sex-biased.
The study relies on observational data, meaning it can only identify associations rather than establish direct biological causes. Finding a sex difference in brain activation or structure does not mean that sex directly dictates how the brain operates, nor does it guarantee that the physical difference has a functional consequence. The research is focused exclusively on the biological construct of sex based on self-identification as male or female, rather than the psychosocial concept of gender.
The findings are also limited to specific types of neuroimaging. Functional MRI during tasks and structural gray matter measurements capture only a portion of the brain’s complex organization. Other techniques, such as resting-state fMRI or imaging that tracks the brain’s white matter connections, could reveal different patterns of sex-based variation. Future research will need to explore how these independent traits develop over a person’s lifespan and whether they fluctuate during different stages of brain development and aging.
The study, “Robust but independent sex differences in human brain function, structure, and behavior,” was authored by Siyuan Liu, Bridget W. Mahony, Ethan T. Whitman, Stephen J. Gotts, Dustin Moraczewski, Adam Thomas, Alex Martin, and Armin Raznahan.
-------------------------------------------------
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #BrainSexDifferences #SexDifferencesInBrain #fMRI activation #StructuralMRI #GrayMatterVolume #Neuroimaging #Sextypicality #BrainBehaviorLinks #CortexActivation #NatureCommunicationsStudy
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DATE: September 21, 2026 at 09:00AM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Brain structure, function, and behavior show independent patterns of sex differences
Men and women show distinct biological differences in how their brains activate during various tasks, the physical size of specific brain regions, and their behavioral traits. A new study published in Nature Communications reveals that while each of these factors can accurately predict a person’s sex, an individual’s degree of sex typicality in one domain is entirely unrelated to the others. These results suggest that sex differences in the human brain are highly context-dependent and operate independently across structure, function, and behavior.
Biological sex differences appear in the prevalence of various neuropsychiatric conditions, such as autism and mood disorders. They also manifest in specific aspects of cognition and physical behavior. Past neuroimaging research has attempted to map out how male and female brains differ in their physical structure and functional activity.
Functional magnetic resonance imaging, or fMRI, allows researchers to observe which brain regions activate when a person performs specific mental tasks. Structural MRI measures the physical volume and shape of brain tissue. Many previous fMRI studies on sex differences have relied on small numbers of participants completing single tasks. This reliance on limited data has led to intense debate about the true extent and relevance of sex differences in human brain function.
To address this gap, researchers Siyuan Liu and Armin Raznahan at the National Institute of Mental Health led a comprehensive analysis of brain activity, anatomy, and behavior. The research team aimed to determine if sex differences in brain function are tied to specific tasks, if they align with physical brain volume, and how they relate to behavior.
The researchers analyzed data from nearly 1,000 healthy young adults. The participants underwent fMRI scans while completing seven different tasks. These tasks were designed to measure emotion processing, gambling, relational reasoning, social cognition, language processing, working memory, and motor skills. By scanning participants during this wide array of activities, the team could observe both task-specific brain activation and general activation patterns.
The analysis revealed widespread sex differences in brain activation across 85 percent of the outer layer of the brain, known as the cerebral cortex. These differences were highly reproducible but mostly specific to individual tasks. For instance, certain brain regions showed more activation in females during a language task but more activation in males during a gambling task.
A small number of regions, particularly those involved in motor control and physical sensation, showed a general tendency for higher activation in females across all seven tasks. Across the board, the effect sizes for these functional differences were small to moderate.
Next, the researchers examined whether these functional differences matched up with anatomical differences. They used structural MRI scans from the same participants to measure the volume of gray matter, which is the tissue containing the main bodies of nerve cells. The team found reproducible sex differences in gray matter volume across various regions of the cerebral cortex.
They then mapped the areas with functional activation differences over the areas with physical volume differences. The spatial patterns did not overlap in a coordinated way. Brain regions that exhibited sex differences in volume were generally not the same regions that showed sex differences in task activation. This lack of alignment suggests that sex differences in brain structure and brain function represent distinct biological phenomena.
The team then incorporated behavioral data, analyzing participant scores across 86 different behavioral traits. These traits ranged from physical grip strength and visual judgment to tendencies toward anxiety and psychological distress. Using a machine learning framework, the researchers tested whether an individual’s combined profile of brain activity, brain volume, or behavior could predict their biological sex.
The machine learning models accurately predicted a participant’s sex based on any of the three categories alone. Task-specific brain activation predicted sex with 88 percent accuracy, regional brain volume with 86 percent accuracy, and behavior with 91 percent accuracy. The models also generated a sex typicality score for each person within each category, rating how closely their data matched the average male or female profile.
Despite the high predictive accuracy of all three categories, a participant’s sex typicality score in one domain did not correlate with their score in another. An individual might have a highly male-typical brain volume, but a strongly female-typical pattern of brain activation during a language task. Only a tiny fraction of individuals exhibited consistently male-typical or female-typical profiles across all measurements of brain and behavior.
In their final analysis, the researchers looked for interactions between sex, brain activation, and behavior. They conducted a brain-wide association study to see if variations in brain activation between individuals correlated with variations in behavior. They first confirmed that measurable links exist between task-induced brain activation and specific behavioral traits within each sex group.
When the team compared these brain-behavior associations between men and women, they found striking similarities. The overall topography of how brain activity relates to behavior is broadly consistent across both sexes. The researchers detected a few isolated instances where the relationship between brain activity and behavior diverged between males and females. However, these rare differences did not preferentially involve behaviors that were themselves heavily sex-biased.
The study relies on observational data, meaning it can only identify associations rather than establish direct biological causes. Finding a sex difference in brain activation or structure does not mean that sex directly dictates how the brain operates, nor does it guarantee that the physical difference has a functional consequence. The research is focused exclusively on the biological construct of sex based on self-identification as male or female, rather than the psychosocial concept of gender.
The findings are also limited to specific types of neuroimaging. Functional MRI during tasks and structural gray matter measurements capture only a portion of the brain’s complex organization. Other techniques, such as resting-state fMRI or imaging that tracks the brain’s white matter connections, could reveal different patterns of sex-based variation. Future research will need to explore how these independent traits develop over a person’s lifespan and whether they fluctuate during different stages of brain development and aging.
The study, “Robust but independent sex differences in human brain function, structure, and behavior,” was authored by Siyuan Liu, Bridget W. Mahony, Ethan T. Whitman, Stephen J. Gotts, Dustin Moraczewski, Adam Thomas, Alex Martin, and Armin Raznahan.
-------------------------------------------------
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #BrainSexDifferences #SexDifferencesInBrain #fMRI activation #StructuralMRI #GrayMatterVolume #Neuroimaging #Sextypicality #BrainBehaviorLinks #CortexActivation #NatureCommunicationsStudy
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DATE: September 21, 2026 at 09:00AM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Brain structure, function, and behavior show independent patterns of sex differences
Men and women show distinct biological differences in how their brains activate during various tasks, the physical size of specific brain regions, and their behavioral traits. A new study published in Nature Communications reveals that while each of these factors can accurately predict a person’s sex, an individual’s degree of sex typicality in one domain is entirely unrelated to the others. These results suggest that sex differences in the human brain are highly context-dependent and operate independently across structure, function, and behavior.
Biological sex differences appear in the prevalence of various neuropsychiatric conditions, such as autism and mood disorders. They also manifest in specific aspects of cognition and physical behavior. Past neuroimaging research has attempted to map out how male and female brains differ in their physical structure and functional activity.
Functional magnetic resonance imaging, or fMRI, allows researchers to observe which brain regions activate when a person performs specific mental tasks. Structural MRI measures the physical volume and shape of brain tissue. Many previous fMRI studies on sex differences have relied on small numbers of participants completing single tasks. This reliance on limited data has led to intense debate about the true extent and relevance of sex differences in human brain function.
To address this gap, researchers Siyuan Liu and Armin Raznahan at the National Institute of Mental Health led a comprehensive analysis of brain activity, anatomy, and behavior. The research team aimed to determine if sex differences in brain function are tied to specific tasks, if they align with physical brain volume, and how they relate to behavior.
The researchers analyzed data from nearly 1,000 healthy young adults. The participants underwent fMRI scans while completing seven different tasks. These tasks were designed to measure emotion processing, gambling, relational reasoning, social cognition, language processing, working memory, and motor skills. By scanning participants during this wide array of activities, the team could observe both task-specific brain activation and general activation patterns.
The analysis revealed widespread sex differences in brain activation across 85 percent of the outer layer of the brain, known as the cerebral cortex. These differences were highly reproducible but mostly specific to individual tasks. For instance, certain brain regions showed more activation in females during a language task but more activation in males during a gambling task.
A small number of regions, particularly those involved in motor control and physical sensation, showed a general tendency for higher activation in females across all seven tasks. Across the board, the effect sizes for these functional differences were small to moderate.
Next, the researchers examined whether these functional differences matched up with anatomical differences. They used structural MRI scans from the same participants to measure the volume of gray matter, which is the tissue containing the main bodies of nerve cells. The team found reproducible sex differences in gray matter volume across various regions of the cerebral cortex.
They then mapped the areas with functional activation differences over the areas with physical volume differences. The spatial patterns did not overlap in a coordinated way. Brain regions that exhibited sex differences in volume were generally not the same regions that showed sex differences in task activation. This lack of alignment suggests that sex differences in brain structure and brain function represent distinct biological phenomena.
The team then incorporated behavioral data, analyzing participant scores across 86 different behavioral traits. These traits ranged from physical grip strength and visual judgment to tendencies toward anxiety and psychological distress. Using a machine learning framework, the researchers tested whether an individual’s combined profile of brain activity, brain volume, or behavior could predict their biological sex.
The machine learning models accurately predicted a participant’s sex based on any of the three categories alone. Task-specific brain activation predicted sex with 88 percent accuracy, regional brain volume with 86 percent accuracy, and behavior with 91 percent accuracy. The models also generated a sex typicality score for each person within each category, rating how closely their data matched the average male or female profile.
Despite the high predictive accuracy of all three categories, a participant’s sex typicality score in one domain did not correlate with their score in another. An individual might have a highly male-typical brain volume, but a strongly female-typical pattern of brain activation during a language task. Only a tiny fraction of individuals exhibited consistently male-typical or female-typical profiles across all measurements of brain and behavior.
In their final analysis, the researchers looked for interactions between sex, brain activation, and behavior. They conducted a brain-wide association study to see if variations in brain activation between individuals correlated with variations in behavior. They first confirmed that measurable links exist between task-induced brain activation and specific behavioral traits within each sex group.
When the team compared these brain-behavior associations between men and women, they found striking similarities. The overall topography of how brain activity relates to behavior is broadly consistent across both sexes. The researchers detected a few isolated instances where the relationship between brain activity and behavior diverged between males and females. However, these rare differences did not preferentially involve behaviors that were themselves heavily sex-biased.
The study relies on observational data, meaning it can only identify associations rather than establish direct biological causes. Finding a sex difference in brain activation or structure does not mean that sex directly dictates how the brain operates, nor does it guarantee that the physical difference has a functional consequence. The research is focused exclusively on the biological construct of sex based on self-identification as male or female, rather than the psychosocial concept of gender.
The findings are also limited to specific types of neuroimaging. Functional MRI during tasks and structural gray matter measurements capture only a portion of the brain’s complex organization. Other techniques, such as resting-state fMRI or imaging that tracks the brain’s white matter connections, could reveal different patterns of sex-based variation. Future research will need to explore how these independent traits develop over a person’s lifespan and whether they fluctuate during different stages of brain development and aging.
The study, “Robust but independent sex differences in human brain function, structure, and behavior,” was authored by Siyuan Liu, Bridget W. Mahony, Ethan T. Whitman, Stephen J. Gotts, Dustin Moraczewski, Adam Thomas, Alex Martin, and Armin Raznahan.
-------------------------------------------------
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #BrainSexDifferences #SexDifferencesInBrain #fMRI activation #StructuralMRI #GrayMatterVolume #Neuroimaging #Sextypicality #BrainBehaviorLinks #CortexActivation #NatureCommunicationsStudy
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DATE: July 16, 2026 at 02:00PM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Genetic risk for cannabis use disorder linked to brain differences in youth
URL: https://www.psypost.org/genetic-risk-for-cannabis-use-disorder-linked-to-brain-differences-in-youth/
A person’s genetic risk for developing a cannabis addiction is associated with structural brain differences during adolescence, even in individuals who have never struggled with substance abuse. The finding indicates that some brain variations previously attributed to marijuana use might partly originate from an inherited biological predisposition. The study was published in the Journal of Psychopharmacology.
Bipolar disorder is a severe mental health condition characterized by dramatic shifts in mood, energy, and activity levels. People with the condition experience intense emotional states known as mood episodes, which can include periods of extreme elation or irritability, known as mania, and periods of deep sadness, known as depression. The condition often emerges during the teenage years and is a leading cause of functional disability among youth globally.
Teenagers with bipolar disorder frequently face additional psychiatric challenges throughout their schooling and home lives. Research shows that about 30 percent of youth diagnosed with bipolar disorder also have a co-occurring substance use disorder. Cannabis use disorder ranks as the most common addiction in this specific clinical group. Youth with bipolar disorder use cannabis at higher rates than the general population and face an elevated risk of developing a long-term dependency on the drug.
Heavy cannabis use has been repeatedly linked to worse outcomes for individuals with bipolar disorder. These negative impacts include a higher risk of suicide, a delayed recovery process, and an increased likelihood of experiencing psychosis. Past brain imaging studies have also noted structural differences in the brains of teenagers who regularly consume cannabis, both with and without mood disorders. The exact nature of these differences has varied across different observational reports.
Some research points to larger gray matter volume in certain brain regions among users, while other reports document smaller volumes in those same areas. Because most of these studies observe people at a single point in time, it is difficult to determine whether cannabis changes the brain or if people with preexisting brain differences are simply more likely to use the drug. To separate cause from effect in these brain measurements, scientists sometimes examine genetics. Addiction involves inherited physical traits, and modern genetic testing allows researchers to measure a person’s underlying vulnerability to an addiction before it ever develops.
Scientists do this using an advanced mathematical tool called a polygenic risk score. Unlike older tests that look for a single faulty gene, a polygenic risk score tallies up thousands of tiny genetic variations across a person’s entire DNA sequence. By comparing these variations against data from people who have a condition, researchers can calculate a customized score that estimates an individual’s overall genetic likelihood of developing that specific problem. Alysha Sultan, a researcher at the Centre for Addiction and Mental Health in Toronto, recognized an opportunity to apply this genetics tool to brain imaging.
Sultan and her colleagues set out to discover if a high polygenic risk score for cannabis use disorder correlated with brain structure in youths, regardless of their developmental history of drug use. The researchers recruited 114 teenagers and young adults between the ages of 13 and 20. The sample included 67 youths who had been diagnosed with bipolar disorder at a specialty psychiatric clinic. The remaining 47 participants were healthy controls randomly recruited from the community who had no personal or family history of major psychiatric disorders.
The team asked all participants to provide a saliva sample. From this saliva, the scientists extracted DNA and scanned the genetic sequences to calculate a specific polygenic risk score for cannabis use disorder for every participant. To create the scoring baseline, they relied on data from a preexisting study of adults that mapped the genetic profiles of tens of thousands of people with a diagnosed cannabis dependency.
After collecting the genetic data, the researchers brought the participants in for brain imaging. They used a magnetic resonance imaging machine, commonly known as an MRI, to capture high-resolution pictures of the participants’ brains. The team focused on the cerebral cortex, the folded outer layer of the brain that manages complex thought, memory, and perception.
The researchers measured three specific physical traits of the cerebral cortex: volume, surface area, and thickness. Volume refers to the total amount of space a specific brain region takes up, while surface area measures the expanse of the folded outer layer. Thickness gauges the physical depth of the gray matter on that layer. The scientists wrote statistical models to compare these structural measurements against the participants’ genetic risk scores, accounting for variables like age, sex, and overall head size.
The neuroimaging data revealed a consistent physical pattern. Across the entire group of youths, a higher genetic risk score for cannabis use disorder matched up with localized reductions in brain size. The researchers observed lower total volume and lower surface area in a brain region called the right superior frontal gyrus. Located near the very top and front of the brain, the superior frontal gyrus is involved in higher cognitive functions such as spatial processing and working memory, which is the ability to hold and manipulate information in the mind over short periods.
The researchers also noticed a smaller surface area in a region called the left paracentral lobule. This area rests near the top center of the brain and helps process sensory information from the body. These results were evident regardless of whether the youths had bipolar disorder or whether they had ever tried cannabis. The researchers ran specialized tests that completely excluded the participants who currently or previously had a cannabis use disorder, and the structural differences remained.
When the team split the participants by diagnosis, they found similar patterns among the healthy volunteers. Healthy teenagers with a higher genetic risk for the addiction exhibited lower brain volume and surface area in both the left and the right superior frontal gyrus.
The results among the participants diagnosed with bipolar disorder were not statistically significant when analyzed on their own. The researchers suspect this outcome relates to the vast biological complexities associated with bipolar disorder itself. The youths with the condition had high rates of anxiety and attention difficulties, took various psychiatric medications, and reported different medical histories. These competing factors may alter brain structure in their own localized ways, creating statistical noise in the data that masks the subtler differences linked strictly to the cannabis risk genes.
Sultan and her colleagues pointed out a few constraints to their investigation. Addiction involves similar genetic pathways across different types of substances, meaning people with a genetic liability for cannabis use disorder often share a generalized genetic vulnerability to alcohol or nicotine. The risk scores used in the study might reflect a broader tendency toward behavioral disinhibition rather than a strict vulnerability to cannabis alone. The genetic baselines used in the study also relied on data from individuals of European ancestry, meaning the relationships might differ for people of other ethnic backgrounds.
The initial findings offer a new way to interpret past neuroimaging research. Because a genetic predisposition alone corresponds with smaller frontal brain regions, some of the brain differences previously blamed on teen marijuana use might have existed before the drug use began. The scientists suggest that longer studies following the same teenagers into adulthood could help explain how inherited vulnerabilities shape the growing brain over time.
The study, “Association of polygenic risk for cannabis use disorder with brain structure among youth with and without bipolar disorder,” was authored by Alysha A. Sultan, Clement C. Zai, Kody G. Kennedy, L. Trevor Young, Bradley J. MacIntosh, and Benjamin I. Goldstein.
URL: https://www.psypost.org/genetic-risk-for-cannabis-use-disorder-linked-to-brain-differences-in-youth/
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Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
Unofficial Psychology Today Xitter to toot feed at Psych Today Unofficial Bot @PTUnofficialBot
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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #CannabisUseDisorder #GeneticRisk #BrainStructure #AdolescentBrain #PolygenicRiskScore #BipolarDisorder #Neuroimaging #FrontalGyrus #CerebralCortex #YouthMentalHealth