#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
-------------------------------------------------
#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: September 18, 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: Do antidepressants actually alter brain structure? A massive neuroscience study weighs in
A massive brain imaging study has found that subtle differences in the brain structure of people taking antidepressants are largely explained by the severity of their depression, rather than the medications themselves. The research also suggests that the relationship between depression, medication use, and brain anatomy changes across a person’s lifespan, with younger patients showing distinct structural patterns. The findings were published in Molecular Psychiatry.
Major depressive disorder is a severe and persistent form of depression that ranks among the leading causes of disability worldwide. To treat it, doctors frequently prescribe antidepressant medications, yet the exact biological mechanisms by which these drugs alter the brain remain somewhat elusive.
A 2006 theoretical framework proposed that chronic stress and depression might damage brain cells, and that antidepressants could stimulate the growth of new cells in deep brain regions. Supporting this idea, a study covered by PsyPost in 2026 indicated that treatments like duloxetine could help normalize the microscopic structure of brain tissue in depressed patients, whereas those given a placebo saw their brain tissue drift further from healthy levels.
To investigate these effects on a larger scale, researchers needed massive datasets. In prior work, the ENIGMA consortium, an international network of brain researchers, mapped how depression physically alters the brain. For instance, a 2015 study from the group found that people with major depression tend to have a smaller hippocampus, which is a seahorse-shaped structure deep in the brain that plays a primary role in memory and emotion.
Building on this lineage, researchers analyzed data from this same international network to see if antidepressant use actually counteracts these structural brain changes, and whether those effects differ depending on a patient’s age and sex.
“In several of our previous large international ENIGMA studies of depression, we kept seeing an intriguing pattern: the most widespread brain differences were often found in people with depression who were taking antidepressants at the time of their brain scan,” Lianne Schmaal, head of Mood & Anxiety Disorders Research and chair of the ENIGMA MDD consortium at Orygen and the Centre for Youth Mental Health at The University of Melbourne, told PsyPost.
“We wanted to understand that pattern better,” Schmaal explained. “Our earlier studies did not have sufficiently detailed information about how long people had been taking antidepressants or which type they were taking, and they could not tell us whether the differences we observed were related to the medication itself or to the reasons people were taking medication in the first place.”
To answer these questions, Schmaal, lead author Chaira Serrarens, and their colleagues pooled data from 32 different international cohorts, yielding a total sample of 8,696 individuals. This massive group was divided into three categories: 2,076 people with major depressive disorder who were currently taking antidepressants, 1,495 people with the disorder who were not taking antidepressants, and 5,125 healthy controls with no history of the condition.
“One of the strengths of this study is its scale,” Schmaal said. “By bringing together almost 8,700 people from 32 research cohorts around the world and analyzing their brain scans using harmonized methods, we could identify subtle patterns that smaller studies would struggle to detect reliably.”
All participants underwent structural magnetic resonance imaging (MRI), a technique that uses strong magnetic fields and radio waves to create highly detailed, three-dimensional pictures of brain anatomy. The researchers processed these brain scans using automated software to measure three main things. First, they measured the thickness of the cerebral cortex, which is the wrinkled outer layer of the brain responsible for higher-level thinking and processing. Second, they measured the total surface area of this outer layer. Third, they measured the volume of subcortical structures, which are the specialized hubs located deep beneath the outer cortex.
To ensure a fair comparison, the statistical models accounted for the participants’ age, sex, and total head size. The researchers also gathered clinical data from the depressed patients, including the severity of their current symptoms based on standard psychological questionnaires, their number of past depressive episodes, and, for a smaller subset, the specific type of antidepressant they were taking.
The brain scans revealed a complex relationship between age, medication status, and brain structure. For example, younger individuals in the medicated group (those under 50 years old) showed a thinner middle temporal gyrus compared to both the unmedicated patients and the healthy controls. The middle temporal gyrus is a ridge on the side of the brain involved in processing sensory information and emotional cues. In older individuals, this difference between the groups disappeared, with the lines crossing over around age 50.
“One of the most interesting findings was that age seemed to matter,” Schmaal noted. “Some of the differences associated with antidepressant use were most apparent in younger people and were not seen in the same way in older adults. That suggests we should not necessarily assume that the relationship between antidepressant treatment and the brain is the same across the lifespan.”
When looking at the overall effects of medication regardless of age, the researchers found that patients currently taking antidepressants had a smaller hippocampus and a thinner inferior temporal gyrus compared to patients who were not taking the drugs. The researchers ran extra tests to see if these differences were simply due to the medicated patients having a longer or more stubborn history of depression. The structural differences held true even when adjusting for the number of past depressive episodes or whether the patient was currently in remission.
However, the researchers caution that these alterations are not glaringly obvious on an individual level. “The differences were small,” Schmaal told PsyPost. “They are detectable because we were able to combine data from thousands of people, but they are nowhere near large enough to look at an individual person’s brain scan and determine whether they have taken antidepressants, or to use these measures in clinical decision-making.”
The differences between the medicated and unmedicated groups also vanished when the researchers accounted for the severity of current depressive symptoms. The people in the medicated group generally reported feeling worse at the time of the scan than the unmedicated group. This indicates that the structural differences in the temporal lobe and hippocampus might be tied more to how severely depressed a person is currently feeling, rather than being a direct physical result of the medication itself.
“We tried to account for factors such as current symptoms, number of previous depressive episodes and whether someone had recurrent depression, but it is impossible to completely separate medication use from illness severity in this kind of study,” Schmaal explained.
“Despite exploring every possible difference between those taking and those not taking antidepressants, there were only very small differences in very few brain areas which disappeared when taking into account other important differences between these groups,” Roland Zahn, a professor of Mood Disorders and Cognitive Neuroscience at King’s College London’s Centre for Affective Disorders who was not involved in the research, told PsyPost.
Zahn, who also serves as co-programme lead for the MSc Affective Disorders and shares research updates via his lab blog, added: “One important difference between the groups was that people taking antidepressants had much higher levels of depressive symptoms as measured on a gold standard observer-rated scale known to correlate with subtle changes in brain structure from other studies. When accounting for this crucial difference between the groups, the subtle differences in thickness of some of the brain areas in those taking antidepressants disappeared.”
The study also highlighted brain changes that seem driven by the depression diagnosis itself rather than the medication. Younger patients with depression, regardless of whether they took medication, had a smaller thalamus compared to healthy controls. The thalamus acts as a central relay station for sensory and motor signals in the brain. These younger patients also exhibited a thinner cortex in several regions across the frontal, occipital, and parietal lobes when compared to healthy individuals, a gap that was not present in the older participants.
In a smaller exploratory analysis, the researchers looked at specific types of antidepressants, comparing selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), and mirtazapine. They found an age-specific pattern here as well. Older adults (over the age of 40) taking mirtazapine had a thicker rostral anterior cingulate cortex compared to older adults taking SSRIs or SNRIs.
This brain region sits in the frontal lobe and is heavily involved in emotional regulation and reward processing. The authors suggest that mirtazapine might trigger a distinct neuroplastic response in this area, though they also note that mirtazapine is often prescribed for specific symptoms like insomnia or after other drugs have failed, which might influence the results.
“The authors acknowledge that they cannot establish causal relationships and particularly their comparison of different antidepressants is exploratory and based on a much smaller group, based on a single time point,” Zahn noted. “The problem is that there are several factors influencing the reason why someone is taking one antidepressant rather than another and the authors acknowledge, they were not able to account for that as this is a large study with limited clinical background information.”
The researchers also investigated how long patients had been on their current medication, finding no clear association between duration of use and structural changes. “We also did not find evidence that a longer duration of current antidepressant use was associated with greater brain differences,” Schmaal said. “That is reassuring in one sense, but it needs to be interpreted cautiously because detailed information on duration was available for only a subset of participants, and importantly we did not have people’s complete lifetime history of antidepressant exposure.”
The findings are in tension with research covered by PsyPost earlier this year, which found that patients taking the antidepressant escitalopram experienced increases in right hippocampal volume during their treatment. Both studies measure hippocampal volume via MRI in depressed patients taking antidepressants, but that earlier study tracked longitudinal within-person volume changes over weeks of treatment, whereas the new study assessed cross-sectional volume differences between different groups of medicated and unmedicated patients at a single point in time.
However, the ENIGMA study’s immense size adds significant weight to its findings. “This is a very important study in that it was able to merge data from thousands of people and therefore had the ability to detect very small differences,” Zahn said. “It thereby challenged findings from non-human animals as well as findings in smaller studies.”
As with all research, there are a few things to keep in mind. The study relies on a cross-sectional design, meaning the participants were only scanned once. Because the researchers did not track the same individuals over time, they cannot definitively say whether the antidepressants caused the observed brain differences, or if people with certain brain shapes and symptom severities are simply more likely to be prescribed antidepressants.
“The main misinterpretation I would want to avoid is that this study shows antidepressants cause the brain to shrink or cause brain damage. It does not,” Schmaal said. “Imagine taking a photograph of two groups of people today: one group taking antidepressants and another group not taking them. Even if their brains differ on average, that photograph cannot tell you what caused the difference or what their brains looked like before treatment.”
Zahn echoed this caution, emphasizing that brain anatomy is highly variable. “It is also important to note that the structure of our brains constantly changes and the biggest driver of such change is age,” he said. “It is also important to note that large individual differences in brain structure exist with little impact on functioning.”
Because of this limitation, the findings should not alter how patients currently manage their condition. “That is why these results should not be used to make decisions about starting or stopping antidepressants,” Schmaal added. “Those decisions need to be based on the balance of benefits and risks for an individual person and discussed with their treating clinician.”
The researchers also lacked data on the participants’ lifetime history of medication use, meaning some people in the “unmedicated” group might have taken antidepressants in the past. Other factors that shape brain anatomy over a lifespan, such as education, lifestyle habits, or early signs of neurodegenerative diseases in older adults, could not be fully accounted for across all 32 international sites.
“The next critical step is longitudinal research,” Schmaal told PsyPost. “Ideally, we need to follow people from before, or very soon after, they first start an antidepressant and repeatedly assess both their mental health and their brain over several years.”
“The next step as the authors acknowledge is to investigate multiple time points in datasets which contain more detail about other relevant factors, such as other conditions, and response to previous treatments,” Zahn added.
“Ultimately, the goal is not simply to ask whether antidepressants affect the brain,” Schmaal concluded. “We want to understand how they affect the developing and adult brain, whether those effects differ between individuals and across different ages, and whether any brain changes relate to treatment benefit, side effects or longer-term outcomes.”
The study, “Regional brain morphology and current antidepressant use: findings from 32 international cohorts from the ENIGMA major depressive disorder working group,” was authored by Chaira Serrarens, Yara J. Toenders, Elena Pozzi, André Aleman, Nina Alexander, Zeynep Başgöze, Vladimir Belov, Klaus Berger, Katharina Brosch, Robin Bülow, Geraldo Filho Busatto, Liliana P. Capitão, Colm G. Connolly, Baptiste Couvy-Duchesne, Kathryn R. Cullen, Udo Dannlowski, Christopher G. Davey, Greig I. de Zubicaray, Danai Dima, Katharina Dohm, Verena Enneking, Tracy Erwin-Grabner, Ulrika Evermann, Cynthia H. Y. Fu, Paola Fuentes-Claramonte, Beata R. Godlewska, Ali Saffet Gonul, Ian H. Gotlib, Roberto Goya-Maldonado, Hans J. Grabe, Nynke A. Groenewold, Dominik Grotegerd, Oliver Gruber, Tim Hahn, Geoffrey Hall, Ben J. Harrison, Walter Heindel, Marco Hermesdorf, Tiffany C. Ho, Naho Ichikawa, Eri Itai, Neda Jahanshad, Hamidreza Jamalabadi, Alec J. Jamieson, Andreas Jansen, Tilo Kircher, Bonnie Klimes-Dougan, Bernd Krämer, Axel Krug, Thomas M. Lancaster, Elisabeth J. Leehr, Meng Li, David E. J. Linden, Frank MacMaster, Katie L. McMahon, Sarah E. Medland, David M. A. Mehler, Susanne Meinert, Benson Mwangi, Igor Nenadić, Go Okada, Yasumasa Okamoto, Nils Opel, Julia-Katharina Pfarr, Edith Pomarol-Clotet, Maria J. Portella, Ronny Redlich, Liesbeth Reneman, Jonathan Repple, Kai Ringwald, Elena Rodriguez-Cano, Pedro G. P. Rosa, Matthew D. Sacchet, Philipp G. Sämann, Raymond Salvador, Anouk Schrantee, Hotaka Shinzato, Kang Sim, Egle Simulionyte, Jair C. Soares, Dan J. Stein, Frederike Stein, Benjamin Straube, Lachlan T. Strike, Florian Thomas-Odenthal, Sophia I. Thomopoulos, Paul M. Thompson, Marie-Jose van Tol, Paula Usemann, Aslihan Uyar, Nic van der Wee, Steven van der Werff, Yolanda Vives-Gilabert, Henry Völzke, Martin Walter, Sarah Whittle, Katharina Wittfeld, Adrian Wroblewski, Mon-Ju Wu, Tony T. Yang, Giovana B. Zunta-Soares, Dick J. Veltman, Lianne Schmaal, and Laura S. van Velzen.
-------------------------------------------------
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 #antidepressants #brainstructure #ENIGMA #MDD #hippocampus #neuroimaging #MolecularPsychiatry #depressionresearch #lifespan #neuroplasticity
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DATE: September 18, 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: Do antidepressants actually alter brain structure? A massive neuroscience study weighs in
A massive brain imaging study has found that subtle differences in the brain structure of people taking antidepressants are largely explained by the severity of their depression, rather than the medications themselves. The research also suggests that the relationship between depression, medication use, and brain anatomy changes across a person’s lifespan, with younger patients showing distinct structural patterns. The findings were published in Molecular Psychiatry.
Major depressive disorder is a severe and persistent form of depression that ranks among the leading causes of disability worldwide. To treat it, doctors frequently prescribe antidepressant medications, yet the exact biological mechanisms by which these drugs alter the brain remain somewhat elusive.
A 2006 theoretical framework proposed that chronic stress and depression might damage brain cells, and that antidepressants could stimulate the growth of new cells in deep brain regions. Supporting this idea, a study covered by PsyPost in 2026 indicated that treatments like duloxetine could help normalize the microscopic structure of brain tissue in depressed patients, whereas those given a placebo saw their brain tissue drift further from healthy levels.
To investigate these effects on a larger scale, researchers needed massive datasets. In prior work, the ENIGMA consortium, an international network of brain researchers, mapped how depression physically alters the brain. For instance, a 2015 study from the group found that people with major depression tend to have a smaller hippocampus, which is a seahorse-shaped structure deep in the brain that plays a primary role in memory and emotion.
Building on this lineage, researchers analyzed data from this same international network to see if antidepressant use actually counteracts these structural brain changes, and whether those effects differ depending on a patient’s age and sex.
“In several of our previous large international ENIGMA studies of depression, we kept seeing an intriguing pattern: the most widespread brain differences were often found in people with depression who were taking antidepressants at the time of their brain scan,” Lianne Schmaal, head of Mood & Anxiety Disorders Research and chair of the ENIGMA MDD consortium at Orygen and the Centre for Youth Mental Health at The University of Melbourne, told PsyPost.
“We wanted to understand that pattern better,” Schmaal explained. “Our earlier studies did not have sufficiently detailed information about how long people had been taking antidepressants or which type they were taking, and they could not tell us whether the differences we observed were related to the medication itself or to the reasons people were taking medication in the first place.”
To answer these questions, Schmaal, lead author Chaira Serrarens, and their colleagues pooled data from 32 different international cohorts, yielding a total sample of 8,696 individuals. This massive group was divided into three categories: 2,076 people with major depressive disorder who were currently taking antidepressants, 1,495 people with the disorder who were not taking antidepressants, and 5,125 healthy controls with no history of the condition.
“One of the strengths of this study is its scale,” Schmaal said. “By bringing together almost 8,700 people from 32 research cohorts around the world and analyzing their brain scans using harmonized methods, we could identify subtle patterns that smaller studies would struggle to detect reliably.”
All participants underwent structural magnetic resonance imaging (MRI), a technique that uses strong magnetic fields and radio waves to create highly detailed, three-dimensional pictures of brain anatomy. The researchers processed these brain scans using automated software to measure three main things. First, they measured the thickness of the cerebral cortex, which is the wrinkled outer layer of the brain responsible for higher-level thinking and processing. Second, they measured the total surface area of this outer layer. Third, they measured the volume of subcortical structures, which are the specialized hubs located deep beneath the outer cortex.
To ensure a fair comparison, the statistical models accounted for the participants’ age, sex, and total head size. The researchers also gathered clinical data from the depressed patients, including the severity of their current symptoms based on standard psychological questionnaires, their number of past depressive episodes, and, for a smaller subset, the specific type of antidepressant they were taking.
The brain scans revealed a complex relationship between age, medication status, and brain structure. For example, younger individuals in the medicated group (those under 50 years old) showed a thinner middle temporal gyrus compared to both the unmedicated patients and the healthy controls. The middle temporal gyrus is a ridge on the side of the brain involved in processing sensory information and emotional cues. In older individuals, this difference between the groups disappeared, with the lines crossing over around age 50.
“One of the most interesting findings was that age seemed to matter,” Schmaal noted. “Some of the differences associated with antidepressant use were most apparent in younger people and were not seen in the same way in older adults. That suggests we should not necessarily assume that the relationship between antidepressant treatment and the brain is the same across the lifespan.”
When looking at the overall effects of medication regardless of age, the researchers found that patients currently taking antidepressants had a smaller hippocampus and a thinner inferior temporal gyrus compared to patients who were not taking the drugs. The researchers ran extra tests to see if these differences were simply due to the medicated patients having a longer or more stubborn history of depression. The structural differences held true even when adjusting for the number of past depressive episodes or whether the patient was currently in remission.
However, the researchers caution that these alterations are not glaringly obvious on an individual level. “The differences were small,” Schmaal told PsyPost. “They are detectable because we were able to combine data from thousands of people, but they are nowhere near large enough to look at an individual person’s brain scan and determine whether they have taken antidepressants, or to use these measures in clinical decision-making.”
The differences between the medicated and unmedicated groups also vanished when the researchers accounted for the severity of current depressive symptoms. The people in the medicated group generally reported feeling worse at the time of the scan than the unmedicated group. This indicates that the structural differences in the temporal lobe and hippocampus might be tied more to how severely depressed a person is currently feeling, rather than being a direct physical result of the medication itself.
“We tried to account for factors such as current symptoms, number of previous depressive episodes and whether someone had recurrent depression, but it is impossible to completely separate medication use from illness severity in this kind of study,” Schmaal explained.
“Despite exploring every possible difference between those taking and those not taking antidepressants, there were only very small differences in very few brain areas which disappeared when taking into account other important differences between these groups,” Roland Zahn, a professor of Mood Disorders and Cognitive Neuroscience at King’s College London’s Centre for Affective Disorders who was not involved in the research, told PsyPost.
Zahn, who also serves as co-programme lead for the MSc Affective Disorders and shares research updates via his lab blog, added: “One important difference between the groups was that people taking antidepressants had much higher levels of depressive symptoms as measured on a gold standard observer-rated scale known to correlate with subtle changes in brain structure from other studies. When accounting for this crucial difference between the groups, the subtle differences in thickness of some of the brain areas in those taking antidepressants disappeared.”
The study also highlighted brain changes that seem driven by the depression diagnosis itself rather than the medication. Younger patients with depression, regardless of whether they took medication, had a smaller thalamus compared to healthy controls. The thalamus acts as a central relay station for sensory and motor signals in the brain. These younger patients also exhibited a thinner cortex in several regions across the frontal, occipital, and parietal lobes when compared to healthy individuals, a gap that was not present in the older participants.
In a smaller exploratory analysis, the researchers looked at specific types of antidepressants, comparing selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), and mirtazapine. They found an age-specific pattern here as well. Older adults (over the age of 40) taking mirtazapine had a thicker rostral anterior cingulate cortex compared to older adults taking SSRIs or SNRIs.
This brain region sits in the frontal lobe and is heavily involved in emotional regulation and reward processing. The authors suggest that mirtazapine might trigger a distinct neuroplastic response in this area, though they also note that mirtazapine is often prescribed for specific symptoms like insomnia or after other drugs have failed, which might influence the results.
“The authors acknowledge that they cannot establish causal relationships and particularly their comparison of different antidepressants is exploratory and based on a much smaller group, based on a single time point,” Zahn noted. “The problem is that there are several factors influencing the reason why someone is taking one antidepressant rather than another and the authors acknowledge, they were not able to account for that as this is a large study with limited clinical background information.”
The researchers also investigated how long patients had been on their current medication, finding no clear association between duration of use and structural changes. “We also did not find evidence that a longer duration of current antidepressant use was associated with greater brain differences,” Schmaal said. “That is reassuring in one sense, but it needs to be interpreted cautiously because detailed information on duration was available for only a subset of participants, and importantly we did not have people’s complete lifetime history of antidepressant exposure.”
The findings are in tension with research covered by PsyPost earlier this year, which found that patients taking the antidepressant escitalopram experienced increases in right hippocampal volume during their treatment. Both studies measure hippocampal volume via MRI in depressed patients taking antidepressants, but that earlier study tracked longitudinal within-person volume changes over weeks of treatment, whereas the new study assessed cross-sectional volume differences between different groups of medicated and unmedicated patients at a single point in time.
However, the ENIGMA study’s immense size adds significant weight to its findings. “This is a very important study in that it was able to merge data from thousands of people and therefore had the ability to detect very small differences,” Zahn said. “It thereby challenged findings from non-human animals as well as findings in smaller studies.”
As with all research, there are a few things to keep in mind. The study relies on a cross-sectional design, meaning the participants were only scanned once. Because the researchers did not track the same individuals over time, they cannot definitively say whether the antidepressants caused the observed brain differences, or if people with certain brain shapes and symptom severities are simply more likely to be prescribed antidepressants.
“The main misinterpretation I would want to avoid is that this study shows antidepressants cause the brain to shrink or cause brain damage. It does not,” Schmaal said. “Imagine taking a photograph of two groups of people today: one group taking antidepressants and another group not taking them. Even if their brains differ on average, that photograph cannot tell you what caused the difference or what their brains looked like before treatment.”
Zahn echoed this caution, emphasizing that brain anatomy is highly variable. “It is also important to note that the structure of our brains constantly changes and the biggest driver of such change is age,” he said. “It is also important to note that large individual differences in brain structure exist with little impact on functioning.”
Because of this limitation, the findings should not alter how patients currently manage their condition. “That is why these results should not be used to make decisions about starting or stopping antidepressants,” Schmaal added. “Those decisions need to be based on the balance of benefits and risks for an individual person and discussed with their treating clinician.”
The researchers also lacked data on the participants’ lifetime history of medication use, meaning some people in the “unmedicated” group might have taken antidepressants in the past. Other factors that shape brain anatomy over a lifespan, such as education, lifestyle habits, or early signs of neurodegenerative diseases in older adults, could not be fully accounted for across all 32 international sites.
“The next critical step is longitudinal research,” Schmaal told PsyPost. “Ideally, we need to follow people from before, or very soon after, they first start an antidepressant and repeatedly assess both their mental health and their brain over several years.”
“The next step as the authors acknowledge is to investigate multiple time points in datasets which contain more detail about other relevant factors, such as other conditions, and response to previous treatments,” Zahn added.
“Ultimately, the goal is not simply to ask whether antidepressants affect the brain,” Schmaal concluded. “We want to understand how they affect the developing and adult brain, whether those effects differ between individuals and across different ages, and whether any brain changes relate to treatment benefit, side effects or longer-term outcomes.”
The study, “Regional brain morphology and current antidepressant use: findings from 32 international cohorts from the ENIGMA major depressive disorder working group,” was authored by Chaira Serrarens, Yara J. Toenders, Elena Pozzi, André Aleman, Nina Alexander, Zeynep Başgöze, Vladimir Belov, Klaus Berger, Katharina Brosch, Robin Bülow, Geraldo Filho Busatto, Liliana P. Capitão, Colm G. Connolly, Baptiste Couvy-Duchesne, Kathryn R. Cullen, Udo Dannlowski, Christopher G. Davey, Greig I. de Zubicaray, Danai Dima, Katharina Dohm, Verena Enneking, Tracy Erwin-Grabner, Ulrika Evermann, Cynthia H. Y. Fu, Paola Fuentes-Claramonte, Beata R. Godlewska, Ali Saffet Gonul, Ian H. Gotlib, Roberto Goya-Maldonado, Hans J. Grabe, Nynke A. Groenewold, Dominik Grotegerd, Oliver Gruber, Tim Hahn, Geoffrey Hall, Ben J. Harrison, Walter Heindel, Marco Hermesdorf, Tiffany C. Ho, Naho Ichikawa, Eri Itai, Neda Jahanshad, Hamidreza Jamalabadi, Alec J. Jamieson, Andreas Jansen, Tilo Kircher, Bonnie Klimes-Dougan, Bernd Krämer, Axel Krug, Thomas M. Lancaster, Elisabeth J. Leehr, Meng Li, David E. J. Linden, Frank MacMaster, Katie L. McMahon, Sarah E. Medland, David M. A. Mehler, Susanne Meinert, Benson Mwangi, Igor Nenadić, Go Okada, Yasumasa Okamoto, Nils Opel, Julia-Katharina Pfarr, Edith Pomarol-Clotet, Maria J. Portella, Ronny Redlich, Liesbeth Reneman, Jonathan Repple, Kai Ringwald, Elena Rodriguez-Cano, Pedro G. P. Rosa, Matthew D. Sacchet, Philipp G. Sämann, Raymond Salvador, Anouk Schrantee, Hotaka Shinzato, Kang Sim, Egle Simulionyte, Jair C. Soares, Dan J. Stein, Frederike Stein, Benjamin Straube, Lachlan T. Strike, Florian Thomas-Odenthal, Sophia I. Thomopoulos, Paul M. Thompson, Marie-Jose van Tol, Paula Usemann, Aslihan Uyar, Nic van der Wee, Steven van der Werff, Yolanda Vives-Gilabert, Henry Völzke, Martin Walter, Sarah Whittle, Katharina Wittfeld, Adrian Wroblewski, Mon-Ju Wu, Tony T. Yang, Giovana B. Zunta-Soares, Dick J. Veltman, Lianne Schmaal, and Laura S. van Velzen.
-------------------------------------------------
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-------------------------------------------------
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-
DATE: September 18, 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: Do antidepressants actually alter brain structure? A massive neuroscience study weighs in
A massive brain imaging study has found that subtle differences in the brain structure of people taking antidepressants are largely explained by the severity of their depression, rather than the medications themselves. The research also suggests that the relationship between depression, medication use, and brain anatomy changes across a person’s lifespan, with younger patients showing distinct structural patterns. The findings were published in Molecular Psychiatry.
Major depressive disorder is a severe and persistent form of depression that ranks among the leading causes of disability worldwide. To treat it, doctors frequently prescribe antidepressant medications, yet the exact biological mechanisms by which these drugs alter the brain remain somewhat elusive.
A 2006 theoretical framework proposed that chronic stress and depression might damage brain cells, and that antidepressants could stimulate the growth of new cells in deep brain regions. Supporting this idea, a study covered by PsyPost in 2026 indicated that treatments like duloxetine could help normalize the microscopic structure of brain tissue in depressed patients, whereas those given a placebo saw their brain tissue drift further from healthy levels.
To investigate these effects on a larger scale, researchers needed massive datasets. In prior work, the ENIGMA consortium, an international network of brain researchers, mapped how depression physically alters the brain. For instance, a 2015 study from the group found that people with major depression tend to have a smaller hippocampus, which is a seahorse-shaped structure deep in the brain that plays a primary role in memory and emotion.
Building on this lineage, researchers analyzed data from this same international network to see if antidepressant use actually counteracts these structural brain changes, and whether those effects differ depending on a patient’s age and sex.
“In several of our previous large international ENIGMA studies of depression, we kept seeing an intriguing pattern: the most widespread brain differences were often found in people with depression who were taking antidepressants at the time of their brain scan,” Lianne Schmaal, head of Mood & Anxiety Disorders Research and chair of the ENIGMA MDD consortium at Orygen and the Centre for Youth Mental Health at The University of Melbourne, told PsyPost.
“We wanted to understand that pattern better,” Schmaal explained. “Our earlier studies did not have sufficiently detailed information about how long people had been taking antidepressants or which type they were taking, and they could not tell us whether the differences we observed were related to the medication itself or to the reasons people were taking medication in the first place.”
To answer these questions, Schmaal, lead author Chaira Serrarens, and their colleagues pooled data from 32 different international cohorts, yielding a total sample of 8,696 individuals. This massive group was divided into three categories: 2,076 people with major depressive disorder who were currently taking antidepressants, 1,495 people with the disorder who were not taking antidepressants, and 5,125 healthy controls with no history of the condition.
“One of the strengths of this study is its scale,” Schmaal said. “By bringing together almost 8,700 people from 32 research cohorts around the world and analyzing their brain scans using harmonized methods, we could identify subtle patterns that smaller studies would struggle to detect reliably.”
All participants underwent structural magnetic resonance imaging (MRI), a technique that uses strong magnetic fields and radio waves to create highly detailed, three-dimensional pictures of brain anatomy. The researchers processed these brain scans using automated software to measure three main things. First, they measured the thickness of the cerebral cortex, which is the wrinkled outer layer of the brain responsible for higher-level thinking and processing. Second, they measured the total surface area of this outer layer. Third, they measured the volume of subcortical structures, which are the specialized hubs located deep beneath the outer cortex.
To ensure a fair comparison, the statistical models accounted for the participants’ age, sex, and total head size. The researchers also gathered clinical data from the depressed patients, including the severity of their current symptoms based on standard psychological questionnaires, their number of past depressive episodes, and, for a smaller subset, the specific type of antidepressant they were taking.
The brain scans revealed a complex relationship between age, medication status, and brain structure. For example, younger individuals in the medicated group (those under 50 years old) showed a thinner middle temporal gyrus compared to both the unmedicated patients and the healthy controls. The middle temporal gyrus is a ridge on the side of the brain involved in processing sensory information and emotional cues. In older individuals, this difference between the groups disappeared, with the lines crossing over around age 50.
“One of the most interesting findings was that age seemed to matter,” Schmaal noted. “Some of the differences associated with antidepressant use were most apparent in younger people and were not seen in the same way in older adults. That suggests we should not necessarily assume that the relationship between antidepressant treatment and the brain is the same across the lifespan.”
When looking at the overall effects of medication regardless of age, the researchers found that patients currently taking antidepressants had a smaller hippocampus and a thinner inferior temporal gyrus compared to patients who were not taking the drugs. The researchers ran extra tests to see if these differences were simply due to the medicated patients having a longer or more stubborn history of depression. The structural differences held true even when adjusting for the number of past depressive episodes or whether the patient was currently in remission.
However, the researchers caution that these alterations are not glaringly obvious on an individual level. “The differences were small,” Schmaal told PsyPost. “They are detectable because we were able to combine data from thousands of people, but they are nowhere near large enough to look at an individual person’s brain scan and determine whether they have taken antidepressants, or to use these measures in clinical decision-making.”
The differences between the medicated and unmedicated groups also vanished when the researchers accounted for the severity of current depressive symptoms. The people in the medicated group generally reported feeling worse at the time of the scan than the unmedicated group. This indicates that the structural differences in the temporal lobe and hippocampus might be tied more to how severely depressed a person is currently feeling, rather than being a direct physical result of the medication itself.
“We tried to account for factors such as current symptoms, number of previous depressive episodes and whether someone had recurrent depression, but it is impossible to completely separate medication use from illness severity in this kind of study,” Schmaal explained.
“Despite exploring every possible difference between those taking and those not taking antidepressants, there were only very small differences in very few brain areas which disappeared when taking into account other important differences between these groups,” Roland Zahn, a professor of Mood Disorders and Cognitive Neuroscience at King’s College London’s Centre for Affective Disorders who was not involved in the research, told PsyPost.
Zahn, who also serves as co-programme lead for the MSc Affective Disorders and shares research updates via his lab blog, added: “One important difference between the groups was that people taking antidepressants had much higher levels of depressive symptoms as measured on a gold standard observer-rated scale known to correlate with subtle changes in brain structure from other studies. When accounting for this crucial difference between the groups, the subtle differences in thickness of some of the brain areas in those taking antidepressants disappeared.”
The study also highlighted brain changes that seem driven by the depression diagnosis itself rather than the medication. Younger patients with depression, regardless of whether they took medication, had a smaller thalamus compared to healthy controls. The thalamus acts as a central relay station for sensory and motor signals in the brain. These younger patients also exhibited a thinner cortex in several regions across the frontal, occipital, and parietal lobes when compared to healthy individuals, a gap that was not present in the older participants.
In a smaller exploratory analysis, the researchers looked at specific types of antidepressants, comparing selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), and mirtazapine. They found an age-specific pattern here as well. Older adults (over the age of 40) taking mirtazapine had a thicker rostral anterior cingulate cortex compared to older adults taking SSRIs or SNRIs.
This brain region sits in the frontal lobe and is heavily involved in emotional regulation and reward processing. The authors suggest that mirtazapine might trigger a distinct neuroplastic response in this area, though they also note that mirtazapine is often prescribed for specific symptoms like insomnia or after other drugs have failed, which might influence the results.
“The authors acknowledge that they cannot establish causal relationships and particularly their comparison of different antidepressants is exploratory and based on a much smaller group, based on a single time point,” Zahn noted. “The problem is that there are several factors influencing the reason why someone is taking one antidepressant rather than another and the authors acknowledge, they were not able to account for that as this is a large study with limited clinical background information.”
The researchers also investigated how long patients had been on their current medication, finding no clear association between duration of use and structural changes. “We also did not find evidence that a longer duration of current antidepressant use was associated with greater brain differences,” Schmaal said. “That is reassuring in one sense, but it needs to be interpreted cautiously because detailed information on duration was available for only a subset of participants, and importantly we did not have people’s complete lifetime history of antidepressant exposure.”
The findings are in tension with research covered by PsyPost earlier this year, which found that patients taking the antidepressant escitalopram experienced increases in right hippocampal volume during their treatment. Both studies measure hippocampal volume via MRI in depressed patients taking antidepressants, but that earlier study tracked longitudinal within-person volume changes over weeks of treatment, whereas the new study assessed cross-sectional volume differences between different groups of medicated and unmedicated patients at a single point in time.
However, the ENIGMA study’s immense size adds significant weight to its findings. “This is a very important study in that it was able to merge data from thousands of people and therefore had the ability to detect very small differences,” Zahn said. “It thereby challenged findings from non-human animals as well as findings in smaller studies.”
As with all research, there are a few things to keep in mind. The study relies on a cross-sectional design, meaning the participants were only scanned once. Because the researchers did not track the same individuals over time, they cannot definitively say whether the antidepressants caused the observed brain differences, or if people with certain brain shapes and symptom severities are simply more likely to be prescribed antidepressants.
“The main misinterpretation I would want to avoid is that this study shows antidepressants cause the brain to shrink or cause brain damage. It does not,” Schmaal said. “Imagine taking a photograph of two groups of people today: one group taking antidepressants and another group not taking them. Even if their brains differ on average, that photograph cannot tell you what caused the difference or what their brains looked like before treatment.”
Zahn echoed this caution, emphasizing that brain anatomy is highly variable. “It is also important to note that the structure of our brains constantly changes and the biggest driver of such change is age,” he said. “It is also important to note that large individual differences in brain structure exist with little impact on functioning.”
Because of this limitation, the findings should not alter how patients currently manage their condition. “That is why these results should not be used to make decisions about starting or stopping antidepressants,” Schmaal added. “Those decisions need to be based on the balance of benefits and risks for an individual person and discussed with their treating clinician.”
The researchers also lacked data on the participants’ lifetime history of medication use, meaning some people in the “unmedicated” group might have taken antidepressants in the past. Other factors that shape brain anatomy over a lifespan, such as education, lifestyle habits, or early signs of neurodegenerative diseases in older adults, could not be fully accounted for across all 32 international sites.
“The next critical step is longitudinal research,” Schmaal told PsyPost. “Ideally, we need to follow people from before, or very soon after, they first start an antidepressant and repeatedly assess both their mental health and their brain over several years.”
“The next step as the authors acknowledge is to investigate multiple time points in datasets which contain more detail about other relevant factors, such as other conditions, and response to previous treatments,” Zahn added.
“Ultimately, the goal is not simply to ask whether antidepressants affect the brain,” Schmaal concluded. “We want to understand how they affect the developing and adult brain, whether those effects differ between individuals and across different ages, and whether any brain changes relate to treatment benefit, side effects or longer-term outcomes.”
The study, “Regional brain morphology and current antidepressant use: findings from 32 international cohorts from the ENIGMA major depressive disorder working group,” was authored by Chaira Serrarens, Yara J. Toenders, Elena Pozzi, André Aleman, Nina Alexander, Zeynep Başgöze, Vladimir Belov, Klaus Berger, Katharina Brosch, Robin Bülow, Geraldo Filho Busatto, Liliana P. Capitão, Colm G. Connolly, Baptiste Couvy-Duchesne, Kathryn R. Cullen, Udo Dannlowski, Christopher G. Davey, Greig I. de Zubicaray, Danai Dima, Katharina Dohm, Verena Enneking, Tracy Erwin-Grabner, Ulrika Evermann, Cynthia H. Y. Fu, Paola Fuentes-Claramonte, Beata R. Godlewska, Ali Saffet Gonul, Ian H. Gotlib, Roberto Goya-Maldonado, Hans J. Grabe, Nynke A. Groenewold, Dominik Grotegerd, Oliver Gruber, Tim Hahn, Geoffrey Hall, Ben J. Harrison, Walter Heindel, Marco Hermesdorf, Tiffany C. Ho, Naho Ichikawa, Eri Itai, Neda Jahanshad, Hamidreza Jamalabadi, Alec J. Jamieson, Andreas Jansen, Tilo Kircher, Bonnie Klimes-Dougan, Bernd Krämer, Axel Krug, Thomas M. Lancaster, Elisabeth J. Leehr, Meng Li, David E. J. Linden, Frank MacMaster, Katie L. McMahon, Sarah E. Medland, David M. A. Mehler, Susanne Meinert, Benson Mwangi, Igor Nenadić, Go Okada, Yasumasa Okamoto, Nils Opel, Julia-Katharina Pfarr, Edith Pomarol-Clotet, Maria J. Portella, Ronny Redlich, Liesbeth Reneman, Jonathan Repple, Kai Ringwald, Elena Rodriguez-Cano, Pedro G. P. Rosa, Matthew D. Sacchet, Philipp G. Sämann, Raymond Salvador, Anouk Schrantee, Hotaka Shinzato, Kang Sim, Egle Simulionyte, Jair C. Soares, Dan J. Stein, Frederike Stein, Benjamin Straube, Lachlan T. Strike, Florian Thomas-Odenthal, Sophia I. Thomopoulos, Paul M. Thompson, Marie-Jose van Tol, Paula Usemann, Aslihan Uyar, Nic van der Wee, Steven van der Werff, Yolanda Vives-Gilabert, Henry Völzke, Martin Walter, Sarah Whittle, Katharina Wittfeld, Adrian Wroblewski, Mon-Ju Wu, Tony T. Yang, Giovana B. Zunta-Soares, Dick J. Veltman, Lianne Schmaal, and Laura S. van Velzen.
-------------------------------------------------
Private, vetted email list for mental health professionals: https://www.clinicians-exchange.org
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-------------------------------------------------
#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #antidepressants #brainstructure #ENIGMA #MDD #hippocampus #neuroimaging #MolecularPsychiatry #depressionresearch #lifespan #neuroplasticity
-
DATE: September 11, 2026 at 12:00PM
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: Brain scans reveal how recurrent depression leaves a lasting mark on the amygdala
Brain scans reveal that elevated activity in the emotion-processing center is tied to a person’s history of recurrent depression, rather than their current mood. The large study, published in Psychological Medicine, suggests that each major depressive episode may leave a lasting biological mark that increases future vulnerability to the disease.
Major depressive disorder is a common psychiatric condition that affects millions of people worldwide. Currently, psychiatrists diagnose the condition based on clinical interviews and patient history. There are no biological markers, like a blood test or a brain scan, to guide treatment choices.
Functional magnetic resonance imaging, or fMRI, allows researchers to observe the brain in action by tracking blood-oxygen levels. When a brain region becomes active, it requires more oxygen, leading to localized changes in blood flow. The scanner detects these magnetic differences to map out neural activity.
Scientists often use this technology to study the amygdala, an almond-shaped structure deep inside the brain that processes fear and negative emotions. Early brain imaging research suggested that people with clinical depression have hyperactive amygdalae when looking at negative images. But a recent analysis of a massive dataset called the UK Biobank found no association between amygdala activity and current depression symptoms.
Jerke J. van den Berg, a biomedical researcher at the University of Amsterdam, and his colleagues designed a new study to better understand this discrepancy. They suspected that previous research might have missed the broader picture by only looking at a patient’s current mood. The researchers focused on a concept called the kindling theory.
The kindling theory proposes that an initial depressive episode makes the brain more sensitive to stress. After the brain has been sensitized by that first experience, it takes progressively less trauma to trigger a relapse. To test if the amygdala reflects this effect, the research team decided to look at a person’s lifetime history of depression, known as a trait, rather than their current symptoms, known as a state.
The researchers utilized data from the UK Biobank, a long-term population health study. They analyzed functional MRI scans from a subset of participants, totaling more than 11,000 individuals. While inside the scanner, participants completed a visual exercise called the Hariri task.
During the task, participants were shown a target image of an angry or fearful face at the top of a screen. They were then asked to select the matching face from two options at the bottom. This specific visual matching exercise is known to reliably stimulate the amygdala.
Brain activity can vary widely from person to person based on age, gender, and head movement during a scan. To account for this natural variation, the research team used a statistical technique called normative modeling. They analyzed scans from over 6,400 healthy participants to establish a baseline of expected amygdala activity. This works much like a pediatric growth chart, which maps out normal ranges for a child’s height and weight.
Next, the researchers evaluated how much the brain activity of nearly 5,000 other participants deviated from this baseline model. They categorized these individuals based on their self-reported mental health histories. The groups included healthy controls, people who had experienced a single depressive episode, those with moderate recurrence involving two to five episodes, and those with a high recurrence of six or more episodes.
For this initial cross-sectional analysis, the team focused strictly on participants who were currently in remission from their depression. The initial results were not statistically significant when the team analyzed the unaltered brain scans. However, once they applied the normative modeling technique to account for age and gender variations, a distinct pattern emerged.
The analysis revealed a measurable association between an individual’s history of depression and their amygdala response. Participants with a high recurrence of depressive episodes showed a heightened amygdala reaction to negative faces compared to healthy controls.
When the researchers looked at individuals actively experiencing a depressive episode, they found no distinct increase in brain activity compared to controls. This suggested that amygdala reactivity represents a long-term biological trait, rather than a temporary state reflecting current mood.
The researchers also wanted to know how medication might influence these brain signals. They noticed that a higher percentage of people in the severe recurrence group were taking antidepressants compared to those with a single past episode. They repeated their cross-sectional analysis, this time removing any participants who were actively taking antidepressant medications.
Excluding medicated individuals strengthened the observed differences between the healthy controls and the recurrent depression groups. The findings indicated that antidepressants might dampen the hyperactive amygdala signal associated with a history of recurrent depression. Because the medication reduced amygdala reactivity, including these participants in the initial data pool slightly masked the true extent of the brain changes.
To see how the brain changes over time, the team conducted a longitudinal analysis. They focused on a smaller group of participants who returned for a second brain scan roughly two and a half years after their initial visit. The researchers categorized these individuals based on whether they had suffered new depressive episodes between the two scans.
For this longitudinal evaluation, the team specifically analyzed people who were in remission during both of their imaging sessions. Participants who began the study with a history of just one depressive episode, but then experienced multiple new episodes before their second scan, exhibited an increase in amygdala reactivity over time.
This brain change supported the kindling theory. It suggests that new depressive episodes incrementally alter how the brain processes negative emotional information, leaving a biological mark even after symptoms fade.
The study relied on a large dataset, but the researchers noted that the effect sizes were relatively small. These findings do not mean that a functional MRI scan can be used to diagnose depression in a clinical setting right now. The results are not robust enough to predict an individual’s exact risk of a relapse based on a single brain scan.
The data collection methods also presented certain limitations. The study depended on participants accurately recalling their own mental health histories, which can introduce memory biases. People might misremember exactly how many distinct depressive episodes they experienced over the course of their lives.
The mental health questionnaires also combined treatments for nerves, anxiety, and depression into a single metric. Because of this, the researchers could not strictly isolate the effects of anxiety disorders from the effects of clinical depression. Future studies will need to track larger groups of symptomatic individuals over extended periods of time to untangle these variables.
Scientists hope that advancing neuroimaging techniques will eventually reduce the normal fluctuations seen in brain scans. Over time, mapping the biology of recurrent depression could help psychiatrists tailor treatments to a patient’s individual history, moving away from the current trial-and-error approach to prescribing medication.
The study, “Normative amygdala fMRI response during emotional processing as a trait of depressive symptoms in the UK Biobank,” was authored by Jerke J. van den Berg, Henricus G. Ruhé, Henk A. Marquering, Liesbeth Reneman, and Matthan W. A. Caan.
-------------------------------------------------
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 #DepressionResearch #Amygdala #fMRI #Neuroimaging #KindlingTheory #UKBiobank #MentalHealthAwareness #BiomarkersInDepression #LongitudinalStudy #NeuroscienceAdvances
-
DATE: September 11, 2026 at 12:00PM
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: Brain scans reveal how recurrent depression leaves a lasting mark on the amygdala
Brain scans reveal that elevated activity in the emotion-processing center is tied to a person’s history of recurrent depression, rather than their current mood. The large study, published in Psychological Medicine, suggests that each major depressive episode may leave a lasting biological mark that increases future vulnerability to the disease.
Major depressive disorder is a common psychiatric condition that affects millions of people worldwide. Currently, psychiatrists diagnose the condition based on clinical interviews and patient history. There are no biological markers, like a blood test or a brain scan, to guide treatment choices.
Functional magnetic resonance imaging, or fMRI, allows researchers to observe the brain in action by tracking blood-oxygen levels. When a brain region becomes active, it requires more oxygen, leading to localized changes in blood flow. The scanner detects these magnetic differences to map out neural activity.
Scientists often use this technology to study the amygdala, an almond-shaped structure deep inside the brain that processes fear and negative emotions. Early brain imaging research suggested that people with clinical depression have hyperactive amygdalae when looking at negative images. But a recent analysis of a massive dataset called the UK Biobank found no association between amygdala activity and current depression symptoms.
Jerke J. van den Berg, a biomedical researcher at the University of Amsterdam, and his colleagues designed a new study to better understand this discrepancy. They suspected that previous research might have missed the broader picture by only looking at a patient’s current mood. The researchers focused on a concept called the kindling theory.
The kindling theory proposes that an initial depressive episode makes the brain more sensitive to stress. After the brain has been sensitized by that first experience, it takes progressively less trauma to trigger a relapse. To test if the amygdala reflects this effect, the research team decided to look at a person’s lifetime history of depression, known as a trait, rather than their current symptoms, known as a state.
The researchers utilized data from the UK Biobank, a long-term population health study. They analyzed functional MRI scans from a subset of participants, totaling more than 11,000 individuals. While inside the scanner, participants completed a visual exercise called the Hariri task.
During the task, participants were shown a target image of an angry or fearful face at the top of a screen. They were then asked to select the matching face from two options at the bottom. This specific visual matching exercise is known to reliably stimulate the amygdala.
Brain activity can vary widely from person to person based on age, gender, and head movement during a scan. To account for this natural variation, the research team used a statistical technique called normative modeling. They analyzed scans from over 6,400 healthy participants to establish a baseline of expected amygdala activity. This works much like a pediatric growth chart, which maps out normal ranges for a child’s height and weight.
Next, the researchers evaluated how much the brain activity of nearly 5,000 other participants deviated from this baseline model. They categorized these individuals based on their self-reported mental health histories. The groups included healthy controls, people who had experienced a single depressive episode, those with moderate recurrence involving two to five episodes, and those with a high recurrence of six or more episodes.
For this initial cross-sectional analysis, the team focused strictly on participants who were currently in remission from their depression. The initial results were not statistically significant when the team analyzed the unaltered brain scans. However, once they applied the normative modeling technique to account for age and gender variations, a distinct pattern emerged.
The analysis revealed a measurable association between an individual’s history of depression and their amygdala response. Participants with a high recurrence of depressive episodes showed a heightened amygdala reaction to negative faces compared to healthy controls.
When the researchers looked at individuals actively experiencing a depressive episode, they found no distinct increase in brain activity compared to controls. This suggested that amygdala reactivity represents a long-term biological trait, rather than a temporary state reflecting current mood.
The researchers also wanted to know how medication might influence these brain signals. They noticed that a higher percentage of people in the severe recurrence group were taking antidepressants compared to those with a single past episode. They repeated their cross-sectional analysis, this time removing any participants who were actively taking antidepressant medications.
Excluding medicated individuals strengthened the observed differences between the healthy controls and the recurrent depression groups. The findings indicated that antidepressants might dampen the hyperactive amygdala signal associated with a history of recurrent depression. Because the medication reduced amygdala reactivity, including these participants in the initial data pool slightly masked the true extent of the brain changes.
To see how the brain changes over time, the team conducted a longitudinal analysis. They focused on a smaller group of participants who returned for a second brain scan roughly two and a half years after their initial visit. The researchers categorized these individuals based on whether they had suffered new depressive episodes between the two scans.
For this longitudinal evaluation, the team specifically analyzed people who were in remission during both of their imaging sessions. Participants who began the study with a history of just one depressive episode, but then experienced multiple new episodes before their second scan, exhibited an increase in amygdala reactivity over time.
This brain change supported the kindling theory. It suggests that new depressive episodes incrementally alter how the brain processes negative emotional information, leaving a biological mark even after symptoms fade.
The study relied on a large dataset, but the researchers noted that the effect sizes were relatively small. These findings do not mean that a functional MRI scan can be used to diagnose depression in a clinical setting right now. The results are not robust enough to predict an individual’s exact risk of a relapse based on a single brain scan.
The data collection methods also presented certain limitations. The study depended on participants accurately recalling their own mental health histories, which can introduce memory biases. People might misremember exactly how many distinct depressive episodes they experienced over the course of their lives.
The mental health questionnaires also combined treatments for nerves, anxiety, and depression into a single metric. Because of this, the researchers could not strictly isolate the effects of anxiety disorders from the effects of clinical depression. Future studies will need to track larger groups of symptomatic individuals over extended periods of time to untangle these variables.
Scientists hope that advancing neuroimaging techniques will eventually reduce the normal fluctuations seen in brain scans. Over time, mapping the biology of recurrent depression could help psychiatrists tailor treatments to a patient’s individual history, moving away from the current trial-and-error approach to prescribing medication.
The study, “Normative amygdala fMRI response during emotional processing as a trait of depressive symptoms in the UK Biobank,” was authored by Jerke J. van den Berg, Henricus G. Ruhé, Henk A. Marquering, Liesbeth Reneman, and Matthan W. A. Caan.
-------------------------------------------------
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 #DepressionResearch #Amygdala #fMRI #Neuroimaging #KindlingTheory #UKBiobank #MentalHealthAwareness #BiomarkersInDepression #LongitudinalStudy #NeuroscienceAdvances
-
DATE: September 11, 2026 at 12:00PM
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: Brain scans reveal how recurrent depression leaves a lasting mark on the amygdala
Brain scans reveal that elevated activity in the emotion-processing center is tied to a person’s history of recurrent depression, rather than their current mood. The large study, published in Psychological Medicine, suggests that each major depressive episode may leave a lasting biological mark that increases future vulnerability to the disease.
Major depressive disorder is a common psychiatric condition that affects millions of people worldwide. Currently, psychiatrists diagnose the condition based on clinical interviews and patient history. There are no biological markers, like a blood test or a brain scan, to guide treatment choices.
Functional magnetic resonance imaging, or fMRI, allows researchers to observe the brain in action by tracking blood-oxygen levels. When a brain region becomes active, it requires more oxygen, leading to localized changes in blood flow. The scanner detects these magnetic differences to map out neural activity.
Scientists often use this technology to study the amygdala, an almond-shaped structure deep inside the brain that processes fear and negative emotions. Early brain imaging research suggested that people with clinical depression have hyperactive amygdalae when looking at negative images. But a recent analysis of a massive dataset called the UK Biobank found no association between amygdala activity and current depression symptoms.
Jerke J. van den Berg, a biomedical researcher at the University of Amsterdam, and his colleagues designed a new study to better understand this discrepancy. They suspected that previous research might have missed the broader picture by only looking at a patient’s current mood. The researchers focused on a concept called the kindling theory.
The kindling theory proposes that an initial depressive episode makes the brain more sensitive to stress. After the brain has been sensitized by that first experience, it takes progressively less trauma to trigger a relapse. To test if the amygdala reflects this effect, the research team decided to look at a person’s lifetime history of depression, known as a trait, rather than their current symptoms, known as a state.
The researchers utilized data from the UK Biobank, a long-term population health study. They analyzed functional MRI scans from a subset of participants, totaling more than 11,000 individuals. While inside the scanner, participants completed a visual exercise called the Hariri task.
During the task, participants were shown a target image of an angry or fearful face at the top of a screen. They were then asked to select the matching face from two options at the bottom. This specific visual matching exercise is known to reliably stimulate the amygdala.
Brain activity can vary widely from person to person based on age, gender, and head movement during a scan. To account for this natural variation, the research team used a statistical technique called normative modeling. They analyzed scans from over 6,400 healthy participants to establish a baseline of expected amygdala activity. This works much like a pediatric growth chart, which maps out normal ranges for a child’s height and weight.
Next, the researchers evaluated how much the brain activity of nearly 5,000 other participants deviated from this baseline model. They categorized these individuals based on their self-reported mental health histories. The groups included healthy controls, people who had experienced a single depressive episode, those with moderate recurrence involving two to five episodes, and those with a high recurrence of six or more episodes.
For this initial cross-sectional analysis, the team focused strictly on participants who were currently in remission from their depression. The initial results were not statistically significant when the team analyzed the unaltered brain scans. However, once they applied the normative modeling technique to account for age and gender variations, a distinct pattern emerged.
The analysis revealed a measurable association between an individual’s history of depression and their amygdala response. Participants with a high recurrence of depressive episodes showed a heightened amygdala reaction to negative faces compared to healthy controls.
When the researchers looked at individuals actively experiencing a depressive episode, they found no distinct increase in brain activity compared to controls. This suggested that amygdala reactivity represents a long-term biological trait, rather than a temporary state reflecting current mood.
The researchers also wanted to know how medication might influence these brain signals. They noticed that a higher percentage of people in the severe recurrence group were taking antidepressants compared to those with a single past episode. They repeated their cross-sectional analysis, this time removing any participants who were actively taking antidepressant medications.
Excluding medicated individuals strengthened the observed differences between the healthy controls and the recurrent depression groups. The findings indicated that antidepressants might dampen the hyperactive amygdala signal associated with a history of recurrent depression. Because the medication reduced amygdala reactivity, including these participants in the initial data pool slightly masked the true extent of the brain changes.
To see how the brain changes over time, the team conducted a longitudinal analysis. They focused on a smaller group of participants who returned for a second brain scan roughly two and a half years after their initial visit. The researchers categorized these individuals based on whether they had suffered new depressive episodes between the two scans.
For this longitudinal evaluation, the team specifically analyzed people who were in remission during both of their imaging sessions. Participants who began the study with a history of just one depressive episode, but then experienced multiple new episodes before their second scan, exhibited an increase in amygdala reactivity over time.
This brain change supported the kindling theory. It suggests that new depressive episodes incrementally alter how the brain processes negative emotional information, leaving a biological mark even after symptoms fade.
The study relied on a large dataset, but the researchers noted that the effect sizes were relatively small. These findings do not mean that a functional MRI scan can be used to diagnose depression in a clinical setting right now. The results are not robust enough to predict an individual’s exact risk of a relapse based on a single brain scan.
The data collection methods also presented certain limitations. The study depended on participants accurately recalling their own mental health histories, which can introduce memory biases. People might misremember exactly how many distinct depressive episodes they experienced over the course of their lives.
The mental health questionnaires also combined treatments for nerves, anxiety, and depression into a single metric. Because of this, the researchers could not strictly isolate the effects of anxiety disorders from the effects of clinical depression. Future studies will need to track larger groups of symptomatic individuals over extended periods of time to untangle these variables.
Scientists hope that advancing neuroimaging techniques will eventually reduce the normal fluctuations seen in brain scans. Over time, mapping the biology of recurrent depression could help psychiatrists tailor treatments to a patient’s individual history, moving away from the current trial-and-error approach to prescribing medication.
The study, “Normative amygdala fMRI response during emotional processing as a trait of depressive symptoms in the UK Biobank,” was authored by Jerke J. van den Berg, Henricus G. Ruhé, Henk A. Marquering, Liesbeth Reneman, and Matthan W. A. Caan.
-------------------------------------------------
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 #DepressionResearch #Amygdala #fMRI #Neuroimaging #KindlingTheory #UKBiobank #MentalHealthAwareness #BiomarkersInDepression #LongitudinalStudy #NeuroscienceAdvances