#neuroimaging — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #neuroimaging, aggregated by home.social.
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DATE: September 12, 2026 at 10:00AM
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: Tracking brain waves reveals a surprising twist in how different generations form social bonds
Getting to know someone across multiple encounters can ease feelings of loneliness, and new research indicates that these budding relationships physically synchronize brain activity in unexpected ways. A new study, published in PLOS Biology, suggests that when younger and older adults regularly participate in creative activities together, their brains coordinate differently over time compared to pairs of the same age. Over six weeks of collaborative drawing, people of different generations showed decreasing neural synchronization, while same-age peers showed increasing synchronization, even as both groups reported feeling closer to their partners.
People of all ages experience perceived social isolation, and community programs that mix generations are a popular way to combat these feelings of loneliness. These programs rely on the idea that repeated interactions foster meaningful social bonds. However, the physical brain changes that happen as these relationships form are mostly unknown to scientists.
“As the global population ages, and with social isolation acknowledged as a global health risk, it is critical to understand how social bonds form between people from the same and different generations,” Ryssa Moffat, a postdoctoral researcher at ETH Zurich’s Social Brain Sciences Lab, told PsyPost. “My motivation to study social interactions between seniors and young adults grew from positive experiences getting to know seniors around the world. The idea for this project really gained momentum when I read statistics about the growing proportion of older adults globally and learned about the risks of loneliness and social isolation.”
To study these physical changes in real time, scientists use a technique called functional near-infrared spectroscopy. This involves participants wearing a flexible cap embedded with sensors that shine safe levels of light through the scalp to measure changes in blood flow in specific brain areas. This tool allows researchers to track interpersonal neural synchrony, which is the extent to which two people’s brain activity aligns in time while they interact.
Researchers pay special attention to two specific brain regions during social tasks. The first is the temporoparietal junction, an area near the ears that helps people process social information and understand others’ perspectives. The second is the inferior frontal gyrus, an area near the temples involved in paying attention to the same thing as a partner.
A progression of recent research provides evidence that social bonds shift brain-to-brain dynamics as relationships unfold. For instance, a 2022 meta-analysis found that working together on a cooperative task consistently synchronizes the frontal and temporoparietal brain regions. This aligns with research covered by PsyPost in 2024, which found that brain synchronization between humans and dogs increases as they become more familiar with each other over several days.
In human relationships, a 2024 experiment indicated that brain synchrony between two people naturally shifts over the course of a conversation depending on whether they are friends or strangers. Building on this evidence, the authors of a 2024 review proposed that using mobile brain scanning to track neural alignment across repeated sessions is essential for understanding how social bonds develop across generations. The new research, led by Moffat and Emily S. Cross, put this concept into practice.
The researchers recruited 61 pairs of strangers from the community. They formed 31 intergenerational pairs, consisting of one younger adult and one adult aged 69 or older, and 30 same-generation pairs made up of two younger adults. The pairs met once a week for six weeks to complete a creative drawing program.
At the start of each session, the participants filled out surveys measuring their current feelings of loneliness, their sense of closeness to their drawing partner, and their attitudes toward people of different age groups. After completing the surveys, researchers fitted the participants with the sensor caps.
The pairs then completed three separate drawing tasks using oil pastels, lasting five minutes each. They were instructed not to talk during the drawing portion. For the first drawing, they worked independently, separated by a visual divider. For the next two drawings, the divider was removed and the pair worked together on a single piece of paper. The sessions concluded with a short puzzle or game.
“It is very exciting to have mapped how synchrony emerges among younger and older adults for the first time,” Moffat said. She noted that they were able “to show how patterns of synchrony change across repeated encounters with information from each encounter, instead of just the first and the last encounter.”
Over the six weeks, feelings of loneliness dropped by about 1 percent per session for both groups. Feelings of social closeness increased by about 4 percent per session, indicating that the program successfully fostered social bonds. “These small but robust changes were observed for same-generation pairs and intergenerational pairs alike,” Moffat noted. The intergenerational pairs generally reported feeling less lonely than the same-generation pairs, and they held more positive attitudes toward other generations.
When analyzing the brain data from all the sessions combined, the researchers found that interpersonal neural synchrony was greater when the pairs drew together compared to when they drew alone. This brain alignment was especially high in the temporoparietal junction and inferior frontal gyrus.
The findings are in line with research covered by PsyPost earlier in 2026, which found that engaging in shared activities together produces greater interpersonal neural synchrony than doing them alone, though that study measured brain alignment during shared music listening among friends rather than interactive drawing across different generations.
Tracking the brain alignment across the six weeks presented an unexpected pattern. For the same-generation pairs, neural synchrony in the right temporoparietal junction increased as the weeks went on. For the intergenerational pairs, neural synchrony in this same area actually decreased over the six weeks.
“I was initially surprised to see synchrony levels decrease for intergenerational dyads,” Moffat explained. “My assumption that we would see increases in synchrony was based on the existing studies comparing strangers, friends, and romantic partners who attend a single session. In these studies, the closer people are to one another, the more synchrony they tend to show.”
The authors suggest that this divergence might reflect how different age pairs integrate social information. “The main takeaway from our study is that the way in which people’s brains synchronize during cooperation depends on who they’re interacting with and the common ground shared by the interacting people,” Moffat said. Because synchrony is believed to reflect how fluently people can predict each other, it is amplified when prediction is less fluent.
Younger pairs might monitor each other’s attention more closely as they become familiar, leading to higher synchrony. As Moffat noted, “they may engage in unpredictable behaviors to keep the interactions interesting and engaging.” In contrast, mixed-generation pairs might require less active monitoring of their partner’s attention once they establish a comfortable routine. “As older and younger people become better acquainted and form more common ground, they can predict each other more fluently and we see reductions in synchrony between brains in certain brain regions,” she added.
The researchers also noticed relationships between the physical brain data and the survey responses. Across all the pairs, reporting higher social closeness predicted an increase in synchrony between the inferior frontal gyrus and the temporoparietal junction. Pairs with more similar levels of loneliness showed greater synchrony in the inferior frontal gyrus when drawing together, which might indicate that sharing a similar social mindset shapes how easily two people coordinate their attention.
One common misconception to avoid is the assumption that more synchrony is always better. “If we start from the standpoint that synchrony increases when predicting another person’s actions is more challenging, it’s probable that excessively high levels of synchrony indicate excessive challenge and that very low levels may indicate a lack of engagement,” Moffat explained. Instead, a “happy medium might be optimal,” where navigating different levels of predictability keeps people socially fit.
There are a few other things to keep in mind about this study. The brain scans targeted specific areas associated with social processing and attention, so the results do not capture activity across the entire brain. The experiment also specifically restricted verbal communication during the drawing tasks, meaning brain alignment might look different if the pairs were talking freely.
Additionally, the study only compared mixed-generation pairs to young-adult pairs. The researchers did not include a group of two older adults, which means some of the differences observed between the groups might relate to general age-related brain changes rather than the specific dynamic of mixing generations. Technical issues also caused a few sensors to fail during the experiment, slightly reducing the amount of data available for the right side of the brain.
Future studies could explore whether other types of common ground, such as shared cultural backgrounds or long-term hobbies, shape brain synchronization over time. Expanding this research into larger group settings could also provide a better understanding of how community arts programs physically benefit participants.
Moffat and her colleagues plan to expand on these findings by analyzing the other behavioral data they collected. “Alongside the recordings of brain activity, we also recorded a multitude of other signals including motion capture of body movements, performance on collaborative games and puzzles, the actual drawings that the participants co-created, as well as participants’ subjective experiences,” she said. “Our next steps are to analyze the other signals and to bring them together to understand how social connections form from a holistic perspective.”
The study, “Social interactions between people of same and different generations shape longitudinal changes in interpersonal neural synchrony, loneliness, and social connection,” was authored by Ryssa Moffat, Guillaume Dumas, and Emily S. Cross.
-------------------------------------------------
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 #IntergenerationalBonds #BrainSynchrony #SocialNeuroscience #LonelinessReduction #GenerationalBridge #Neuroimaging #InterpersonalNeuralSynchrony #CreativeCollaboration #DTMBrainResearch #PLOSBiology
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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
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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
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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
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DATE: August 23, 2026 at 10:00AM
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: Survival of the wittiest: How humor and cleverness shaped human evolution
URL: https://www.psypost.org/survival-of-the-wittiest-how-humor-and-cleverness-shaped-human-evolution/
A new theoretical paper suggests that human cognitive and linguistic evolution was driven by early humans’ ability to be clever and humorous, an idea dubbed the “survival of the wittiest.” The analysis argues that the earliest stages of grammar provided a platform for verbal competition and sexual selection, gradually replacing physical violence with verbal agility. The research was published in PNAS Nexus.
For decades, discussions of human evolution have revolved around two dominant ideas. The first is Charles Darwin’s original concept of the survival of the fittest, which is often narrowly interpreted as physical strength or health. The second is the more recent hypothesis of the survival of the friendliest. This newer idea proposes that humans evolved primarily through selection for prosocial behavior and cooperation, which allowed early humans to form alliances and outcompete other groups.
Wayne State University linguist Ljiljana Progovac authored the new paper to offer an alternative viewpoint. Progovac argues that physical fitness and friendliness fail to capture the unique role that language played in human development. Being physically strong or socially cooperative are traits shared with many other animals, including bonobos and other primates. These traits alone do not explain the rapid and unique expansion of human cognition.
According to Progovac, focusing entirely on friendliness misses the competitive nature of human interaction. Evolution involves both cooperation and ruthless competition. To fully understand how our ancestors evolved into modern humans, researchers must account for the biological advantage of eloquence, imagination, and the ability to outwit rivals. This perspective centers on sexual selection, where traits that make an individual attractive to mates are passed down through successive generations.
To build this argument, Progovac analyzed linguistic structures that represent the earliest stages of grammar. Language leaves no physical bones behind, so researchers must rely on a process called reverse engineering. By peeling back the complex layers of modern syntax, linguists can reconstruct the most foundational building blocks of language. These foundational structures are referred to as living fossils.
In modern languages, these fossils appear as simple two-word combinations consisting of one verb and one noun. Examples in English include words like “killjoy,” “crybaby,” “pickpocket,” and “scatterbrain.” These basic compounds do not rely on complex grammatical rules. They lack the structural layers required to distinguish between subjects and objects or to establish tense.
These simple word pairs are remarkably consistent across entirely different language families. Progovac notes that similar verb-noun compounds exist in languages ranging from Serbian to Berber to Twi. Historically, these basic constructions have been used to create highly vivid, metaphorical nicknames. Often, these nicknames are derogatory or humorous, describing a person based on a prominent action or physical trait.
Progovac proposes that as early humans developed these two-word abilities, a new form of social competition emerged. Individuals who could quickly invent clever, insulting, or amusing names had a distinct social advantage. They could demean rivals and impress potential mates without resorting to physical combat. This quick-wittedness represented an enormous cognitive leap, showing that early language was not just for sharing information but for social maneuvering.
The biological benefits of this verbal agility are still visible in human populations today. In many traditional oral societies across the globe, the most eloquent speakers hold the highest social status. Individuals who can manipulate words effectively gain access to political power and better reproductive success. The ability to charm a mate through humor and metaphorical language proved to be highly adaptive over time.
The paper also reviews experimental evidence from neuroimaging to support this evolutionary timeline. In a prior functional magnetic resonance imaging experiment, researchers tracked brain activity while participants read ancient verb-noun combinations compared to more modern, complex words. The older compounds evoked a more visceral reaction in the brain than modern words.
The experimenters found that processing the older, fossil-like compounds activated the right side of the fusiform gyrus in the brain. This specific brain region is directly involved in face perception and face recognition. Finding that the same brain area handles both face recognition and basic verb-noun processing supports the idea that the earliest grammar was closely tied to naming individuals and attaching linguistic labels to faces.
A related brain imaging experiment looked at how the brain processes simple sentences compared to hierarchical, modern sentences. The simpler sentences resulted in less activity in the Broca’s area and the basal ganglia. The basal ganglia are deep brain structures involved in motor control and learning.
Over the course of human evolution, the connections between the Broca’s area and the basal ganglia became much denser. The gradual mastery of more complex language likely drove the physical evolution of these brain networks. This aligns with genetic changes unique to humans and Neanderthals, including variations in the FOXP2 gene, which is associated with speech and language development.
By replacing physical fighting with verbal dueling, quick-wittedness played a direct role in reducing physical aggression among early humans. Humor and laughter act as natural stress antagonists, lowering cortisol levels in the body. This biological response connects the survival of the wittiest with the concept of human self-domestication. Over time, societies selected for individuals who could use words to defuse tension or assert dominance, leading to a species that prizes cognitive contests over lethal battles.
While this perspective offers a robust framework for understanding language origins, measuring the evolutionary impact of humor and wit relies heavily on reconstructing the past. Researchers must reverse-engineer modern languages and rely on brain imaging proxies, which cannot definitively prove how ancient ancestors behaved in their daily lives. Brain scans of modern humans only provide an approximation of ancient cognitive processes.
Future studies could test this hypothesis by examining how individual variations in cognitive conditions process these fossil grammars. By observing how brains with different neurological setups handle early grammatical structures, scientists can better map the exact neural pathways that allowed language to flourish.
The study, “Survival of the wittiest (not friendliest): The art and science behind human linguistic and cognitive evolution,” was authored by Ljiljana Progovac.
URL: https://www.psypost.org/survival-of-the-wittiest-how-humor-and-cleverness-shaped-human-evolution/
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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #SurvivaloftheWittiest #HumorEvolution #LanguageOrigins #EarlyGrammar #VerbalCompetition #SexualSelection #Neuroimaging # FOXP2 #SocialManeuvering #EvolutionOfCognition
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DATE: August 19, 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: Childhood ADHD is linked to distinct developmental changes in brain white matter
An analysis of ABCD study data found that children with ADHD showed signs of reduced glial cellularity (measured as reduced restricted normalized isotropic diffusion) in 20 white matter tracts at 9 years of age. They also noticed signs of reduced axonal organization (measured as reduced restricted normalized directional diffusion) of nerve fibers in 16 white matter tracts between ages 9 and 14. The paper was published in Biological Psychiatry: Cognitive Neuroscience and Neuroimaging.
Attention-deficit/hyperactivity disorder, or ADHD, is a neurodevelopmental condition that affects attention, impulse control, and activity levels. It usually begins in childhood, although many people continue to experience symptoms in adolescence and adulthood. Some people with ADHD mainly struggle with distractibility, forgetfulness, and organization, while others are more affected by restlessness and impulsive behavior. Many experience a combination of both patterns.
ADHD symptoms are persistent and interfere with everyday functioning. They can affect school or work performance, relationships, time management, and the ability to complete routine tasks. In fact, ADHD is frequently diagnosed when a child starts school because its symptoms often conflict with classroom expectations. It is estimated to affect approximately 3-10% of children.
Study author L. Nate Overholtzer and his colleagues note that white matter—the tissue in the brain made mainly of nerve fibers—facilitates efficient communication between brain regions, thereby supporting higher-order cognitive processes. These processes are commonly impaired in ADHD. With this in mind, they conducted a study aiming to characterize the relationship between ADHD and white matter microarchitecture across early adolescence. They also evaluated how these associations were affected by three classes of ADHD medications: amphetamine-based, methylphenidate-based, and nonstimulant medications.
They analyzed data from the Adolescent Brain and Cognitive Development Study (ABCD Study). The ABCD study is a large, long-term U.S. research project following thousands of children into adulthood to understand how brain development relates to health, behavior, and life experiences.
The analyses used data collected at enrollment (2016-2018), 2 years (2018-2020), and 4 years (2020-2022) after the start of the study. The total number of participants for whom data were available at the start of the study was 9,426. In year 2, it was 6,745, and it was down to 2,483 participants in year 4. At the start of the study, 1,150 participants (12.2%) had ADHD (658 of whom were taking ADHD medication). In year 2, there were 763 participants with ADHD (11.3%), and in year 4, there were 294 (11.8%).
The researchers used advanced diffusion magnetic resonance imaging (MRI) scans of the participants’ brains. Participants who were using non-ADHD psychiatric medications were excluded from the analysis to prevent pharmacological confounds. The study authors identified whether participants had ADHD based on caregiver responses to the computerized Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS) and the Medication Inventory Survey (MIS). The latter assessment also served to identify the type of ADHD medication participants were taking.
Results indicated that children with ADHD tended to show decreased restricted normalized isotropic diffusion in 20 white matter tracts at age 9, indicating reduced glial cellularity. The analyses also showed that ADHD was associated with enduring decreases in restricted normalized directional diffusion in 16 white matter tracts between the ages of 9 and 14, indicating reduced axonal organization. Additionally, an exploratory analysis indicated that the narrowing of isotropic diffusion differences between children with and without ADHD across early adolescence paralleled an overall age-related drop in ADHD symptoms across the participants.
Restricted normalized isotropic diffusion (RNI) and restricted normalized directional diffusion (RND) are advanced MRI measures that describe how water movement is restricted within brain tissue.
RNI reflects restriction that is similar in all directions and serves as an indicator of glial cellularity—the presence and morphology of support cells like astrocytes, microglia, and myelin-producing cells.
RND reflects restriction along a particular direction and, in brain white matter, provides information about the organization, packing, and alignment of nerve fibers (axons).
“Altogether, ADHD was robustly associated with reductions in isotropic diffusion in white matter tracts, suggestive of atypical glial cellularity during late childhood. Complementary reductions in directional diffusion of select tracts may suggest atypical axonal organization enduring across early adolescence,” the study authors concluded.
The study contributes to the scientific knowledge about the neural basis of ADHD. However, the study was limited by smaller sample sizes in later waves—partially because Year 4 data collection was still ongoing at the time of the data release, and because children with ADHD had higher exclusion rates due to factors like moving during MRI scans or taking other psychiatric medications. This could limit the generalizability of the results to the broader ADHD population.
The paper, “Developmental Differences in White Matter Microarchitecture in Youth with ADHD: Longitudinal Findings from the ABCD Study,” was authored by L. Nate Overholtzer, Katherine L. Bottenhorn, Hedyeh Ahmadi, Sarah L. Karalunas, Bradley S. Peterson, and Megan M. Herting.
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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #ADHD #WhiteMatter #BrainDevelopment #ABCDStudy #Neuroimaging #DiffusionMRI #GlialCells #AxonalOrganization #ChildhoodADHD #NeuroscienceResearch
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DATE: August 18, 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: The human brain reorganizes itself at four distinct ages
URL: https://www.psypost.org/the-human-brain-reorganizes-itself-at-four-distinct-ages/
The structural organization of the human brain changes non-linearly over a person’s life, shifting at four distinct ages. A large study identified major transitions in brain network architecture around ages nine, 32, 66, and 83. The research was published in Nature Communications.
The brain is essentially a network of connected regions. The architecture of this network, known as its topology, dictates how well different areas communicate. Researchers measure this topology using mathematical concepts like integration, segregation, and centrality. Different topological structures have different strengths related to cognition and behavior.
Integration describes how easily information travels across the entire brain. A highly integrated network has many short paths connecting distant regions, optimizing it for rapid communication. Segregation refers to how the network divides into specialized local groups. A highly segregated network has dense local connections that support specialized processing tasks, like vision or motor control. Centrality identifies specific regions that act as highly active hubs for information transfer, making the network more resilient to damage.
Past research has linked brain topology to cognitive function and mental health during specific life stages. But the underlying principles of how this organization shifts across an entire human life have remained unmapped. Alexa Mousley, a researcher at the University of Cambridge, wanted to identify if there are specific turning points when the brain enters a new phase of developmental change.
To map these lifespan changes, the researchers gathered brain imaging data from nine different datasets. The combined data included 4,216 participants ranging in age from zero to 90 years old. Because the sample exceeded 2,000 individuals, this qualifies as a large study.
The team used a specific type of magnetic resonance imaging that tracks the movement of water molecules to map the physical wiring of the brain. They then harmonized the data from the different sources to account for variations in scanning equipment. From there, the scientists calculated 12 different metrics to describe the topology of each participant’s brain network. The network densities were strictly controlled to allow for fair comparisons across different ages.
To make sense of this highly detailed data, the team used a mathematical technique to project the network metrics into three-dimensional spaces. This machine learning approach filters out overlapping information to reveal the fundamental mathematical structure of complex data. By tracing the average trajectory of brain development through these spaces, the researchers could pinpoint where the trajectory abruptly changed direction. They defined these spots as turning points.
The analysis revealed four major turning points in the human lifespan. These occur around ages nine, 32, 66, and 83. These four points separate human life into five distinct epochs of brain development, with each epoch featuring its own unique pattern of structural change.
The first epoch spans from birth to age nine. During this childhood phase, the brain’s global integration decreases while local segregation increases. The extent to which neighboring regions connect to each other is the strongest predictor of a child’s age during this period. The end of this epoch coincides roughly with the onset of puberty and a known biological phase where the brain actively eliminates unused neural connections.
The second epoch lasts from age nine to 32. This phase encompasses adolescence and early adulthood. Over these years, the brain network becomes increasingly integrated and less segregated on a global scale. The balance between global efficiency and local specialization becomes the most defining feature of brain development during this time.
The turning point at age 32 represents the largest structural shift in the entire lifespan. It aligns with the known peak of white matter volume, which is the insulated wiring that connects brain regions. Following this peak, the third epoch stretches across three decades of adulthood, from age 32 to 66.
This middle adulthood epoch is a relatively stable period characterized by slower changes in network architecture. During these years, global integration begins to decline while local efficiency increases. Changes in network segregation drive the relationship between age and brain topology during this long phase.
The fourth turning point arrives at age 66, marking the transition into older age. From 66 to 83, the brain network shows a distinct shift toward increasing modularity. Modularity means the network separates into highly interconnected subgroups. The researchers note this pattern suggests a simplification of the brain’s structural network, which corresponds with expected age-related degradation in white matter.
The final epoch covers ages 83 to 90. In this late stage of life, the relationship between age and brain topology is quite weak. The only metric that tracks with age during this period is the centrality of individual nodes, meaning certain localized hubs become increasingly important for connectivity.
The study has some limitations that affect how the results should be interpreted. The data is cross-sectional, meaning it compares different people of different ages rather than following the same individuals over their entire lives. This design makes it impossible to establish causality or temporal dynamics within a single person. It prevents researchers from tracking how an individual’s specific brain topology changes over time.
Additionally, the researchers used fixed network density thresholds for their main analysis to allow for fair comparisons between different ages. While they conducted secondary tests to verify their choices, this thresholding process might obscure some smaller individual differences in total brain connectivity. The analysis also did not separate the data by biological sex, leaving it unknown whether these major turning points happen at different ages for men and women.
Finally, the oldest age group contained just 93 participants, which lowered the statistical power of the analysis for that specific epoch. The associations in this late-aging epoch were mostly not statistically significant. It is also highly possible that the people in their late 80s who participated in these imaging studies are exceptionally healthy compared to their peers. This selection bias could skew the results for the oldest epoch, making their brains look more resilient than average.
The study, “Topological turning points across the human lifespan,” was authored by Alexa Mousley, Richard A. I. Bethlehem, Fang-Cheng Yeh, and Duncan E. Astle.
URL: https://www.psypost.org/the-human-brain-reorganizes-itself-at-four-distinct-ages/
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DATE: August 17, 2026 at 06:00AM
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 scans reveal two distinct biological profiles of migraine
URL: https://www.psypost.org/brain-scans-reveal-two-distinct-biological-profiles-of-migraine/
A recent analysis of brain scans has revealed that people who experience migraines can be grouped into two distinct biological categories. These categories are based on how the brain is wired and physically structured, offering a new way to understand the disorder beyond traditional symptom checklists. The findings were published in the journal Cephalalgia.
Migraine is a neurological condition that causes severe head pain, sensitivity to light, and other debilitating symptoms. Doctors currently classify the disorder based on how often attacks occur and whether a patient experiences an aura, which refers to visual or sensory disturbances preceding the headache. This symptom-based approach, outlined in the International Classification of Headache Disorders, often fails to predict which treatments will work best for individual patients.
The biological differences between people with migraines remain largely unmapped. Researchers suspect that categorizing patients based on brain biology, rather than just symptom frequency, might eventually improve treatment strategies. Stanford University researchers Jaiashre Sridhar and Danielle D. DeSouza led a team to investigate whether patterns in brain imaging could identify hidden biological subgroups.
To do this, the research team used two types of magnetic resonance imaging, or MRI. Structural MRI measures the physical dimensions of the brain, such as the volume and thickness of the outer layer known as the cerebral cortex, as well as deeper subcortical structures. Functional MRI tracks blood flow to observe how different brain regions communicate when a person is at rest, a metric called functional connectivity.
The researchers first analyzed combined structural and functional brain scan data from 111 individuals with migraines and 51 healthy controls. They used a mathematical algorithm to simplify the massive amount of data and group the patients based on shared biological patterns. This exploratory approach was designed to let the data dictate the groups rather than relying on prior clinical labels.
This combined analysis identified two biological subgroups with distinct brain profiles and clinical experiences. One group tended to be older, had lived with migraines longer, and reported higher levels of daily disability. This higher-burden group also experienced longer individual headache durations and lower confidence in their ability to manage pain.
In this higher-burden group, functional MRI scans showed elevated connectivity between deeper brain structures and cortical networks responsible for attention, movement, and visual processing. Structurally, these individuals also exhibited reduced brain volume across several cortical regions, including the frontal, parietal, and temporal lobes, compared with the other subgroup. Many of these heightened functional connections were also elevated relative to the healthy control group.
The second subgroup presented a milder biological profile. Their brain structure was largely preserved in comparison to the first group. Their functional connectivity patterns and brain volumes were not statistically significant when compared to the healthy control group.
After identifying the combined groups, the researchers conducted a secondary analysis using only the functional connectivity data. They applied the same mathematical grouping process to see how the patients would cluster based solely on how different brain regions communicate.
This functional-only model produced two subgroups that closely matched the groups found in the initial combined analysis. Patients with higher clinical burden again clustered together, exhibiting similar patterns of elevated brain connectivity. When grouped this way, the resulting clusters did not display any differences in brain structure, indicating that functional connectivity drove most of the initial subgroupings.
Next, the team ran a third clustering model using exclusively structural MRI data. They grouped the same patients based entirely on the thickness and volume of their brain tissue.
This structural-only analysis generated two entirely different patient clusters that had almost no overlap with the groups formed by the combined or functional data. While these two new groups showed widespread differences in brain volume, they exhibited no differences in functional connectivity. This divergence indicates that structural variations represent a completely separate dimension of migraine biology than functional variations.
To verify the stability of their findings, the researchers performed a final sensitivity analysis. Instead of looking at broad functional networks, they repeated the combined analysis using a much more detailed map that divided the brain into over a hundred smaller, specific regions.
The results of this fine-grained analysis strongly mirrored the original combined model. Between 90 and 95 percent of the participants were assigned to the exact same subgroups as before. This consistency suggests that the biological groups are robust, regardless of the scale used to map the brain.
While these biological groupings provide a new perspective on migraines, the research relies on data collected at a single point in time. It is not possible to know whether prolonged migraines alter the brain over the years, or if these brain differences exist first and influence how the condition develops. The clinical differences between the two subgroups were also relatively subtle, and the groups did not align with traditional categories like chronic or episodic migraine.
The researchers noted that this was a modestly sized study, meaning the results will need to be verified in larger populations. The study also did not track the exact phase of the patients’ migraine cycle during the brain scans, such as whether they were actively having a migraine or in a resting phase. Additionally, the researchers did not account for all preventive medications the participants might have been taking at the time.
Future research will need to track larger groups of patients over extended periods to see how these biological profiles evolve and whether they can eventually guide medical care.
The study, “Neuroimaging-based subtyping of migraine identifies clinically distinct phenotypes,” was authored by Jaiashre Sridhar, Mahsa Babaei, Bharati M. Sanjanwala, Robert P. Cowan, and Danielle D. DeSouza.
URL: https://www.psypost.org/brain-scans-reveal-two-distinct-biological-profiles-of-migraine/
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#psychology #counseling #socialwork #psychotherapy @psychotherapist @psychotherapists @psychology @socialpsych @socialwork @psychiatry #mentalhealth #psychiatry #healthcare #depression #psychotherapist #MigraineBiology #Neuroimaging #BrainConnectivity #StructuralFunctionalMRI #MigraineSubtypes #CephalalgiaStudy #BrainNetworks #PersonalizedMedicine #NeurologyResearch #MigrainePhenotypes
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On the Emergence of Neuroforecasting
Knowledge in the neurosciences, theory and methodology, is increasingly applied to improve and deepen our understanding of consumer decision processes, affect and cognition, and behaviours, in a young field known as consumer neuroscience; practical implementation of this knowledge on consumers in marketing management is known as neuromarketing. Relevant specialisitations in the neurosciences include neuropsychology, neuroeconomics, and neurobiology. The research has largely focused on […]https://consumergateway.org/2026/07/13/on-the-emergence-of-neuroforecasting/
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NeuroVFM trains a medical AI on 5 million uncurated brain scans without human labels
https://1ban.news/neurovfm-neuroimaging-foundation-model-vol-jepa/
#1ban #neurovfm #neuroimaging #foundation #model #tech -
A neuroimaging study revealed that a small subpopulation of individuals with schizophrenia who have a history of severe physical violence display heightened brain activity when anticipating punishment, rather than when receiving a reward or an actual punishment.
#Neuroscience #Psychiatry #Neuroimaging #Schizophrenia #sflorg
https://www.sflorg.com/2026/07/ns07062601.html -
Neuroimaging-derived biotypes of self-reported insomnia symptoms are differentially associated with affective symptoms
https://1ban.news/neuroimaging-biotypes-insomnia-affective-risk/
#1ban #neuroimaging #biotypes #insomnia #affective #sleep -
ggseg now draws brains without sf.
It installs without needing compiled GDAL, GEOS, or PROJ — so it runs on locked-down laptops, HPC clusters, and in the browser (webR/shinylive). Same geom_brain(), identical figures.
How & why 👉
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At booth #39-40 today, Artinis & @NIRx Medical Technologies are demoing #fNIRS + #TMS, a powerful combination for brain stimulation research that gives you both the trigger and the response. Come, join us at 1 PM!
Visit booth #44 for:
🔹 APEX EEG + Brite fNIRS
🔹 SAGA EEG + NIRSport2 demos!https://www.artinis-nirx.com/ohbm-2026-bordeaux #🧠 #OHBM2026 #BrainStimulation #Neuroscience #Neuroimaging
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🧠 Could the brain reveal vision loss more accurately than traditional eye tests?
🔗 Using Steady-State Visual Evoked Potentials to Characterize Wide-Ranging Retinopathy Linked to CRB1: Implications for Clinical Trials. Computational and Structural Biotechnology Journal (CSBJ). DOI: https://doi.org/10.34133/csbj.0042
📚 CSBJ - A Science Partner Journal: https://spj.science.org/journal/csbj
#Neuroscience #Ophthalmology #RetinalDiseases #GeneTherapy #EEG #BrainResearch #DigitalHealth #PrecisionMedicine #Neuroimaging
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Cerebellar flatmaps now in #ggsegverse!
We have now shipped across the ggsegverse the possibility to visualise the cerebellum parcellations also, based on the SUIT flatmap from the Diedriksen lab.
Read more about it https://ggsegverse.github.io/news/cerebellar-support/
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Call for Papers: Human Neuroimaging Education Special Issue
Share training programs, open resources, AI in education and more.
Deadline: 31 Aug 2026
Guidelines: https://apertureneuro.org/for-authors
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#fMRT, macht die #Hirnaktivität sichtbar, doch die Interpretation wird häufig hinterfragt. Auch Forschende der @FAU ermittelten in einer #Studie eine Diskrepanz. Die Autoren sprechen jedoch nicht von Kritik an der Methode, sondern von #Erkenntnisgewinn für die fMRT-Bildgebung, wobei ein zweiter Blick neues offenbart...
Interessiert an mehr? Den #HintergrundArtikel von Larissa Tetsch findet ihr hier: https://www.laborjournal.de/editorials/3465.php
#Laborjournal #LifeSci #Neuroimaging #Neuroscience #Hirnforschung
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Thank you for the incredible response to our recent #fNIRS Introduction Courses! Our next stop is #Sydney 🇦🇺
📅 Friday, April 24
⏰ 10 AM – 5 PM
📍 University of Sydney, Camperdown/Darlington CampusJoin us for a full day of hands-on learning and expert insights. Spots are limited 👉 https://zurl.co/HYf2l
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Mind-bending visualization of brain spirals sweeping across the cortex — a stunning re-creation from Gong et al. Watch neural waves come alive and rethink how activity travels through the brain. Perfect for neuroscience lovers and visual explorers! #neuroscience #brain #neuroimaging #visualization #science #research #neuro #English
https://video.davidsterry.com/videos/watch/f4613fb1-0c22-4fb2-b95d-2505e5125204 -
New ggsegverse update!
I finally got around to pre-release new ggseg.extra (notice name change) package, for creating new atlases.
https://ggsegverse.github.io/news/ggseg.extra/
It's full of new features, and likely lots of new bugs.
I'd love folks to test how it works, I've really tried making things more robust and I hope its payed off! -
neuromapr 0.2.1 has been accepted and published on CRAN!
Very excited to get this out to users in the simplest way possible, and hope the #rstats #neuroimaging community finds it useful!
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🧠 From setup to real-time decoding: how fNIRS-BCIs actually work. In Part 1 of our #fNIRS #BCI: Methodology and (clinical) application possibilities" webinar series, Dr. Bettina Sorger from Maastricht University & Dr. Franziska Klein from OFFIS guide you through system setup, experimental design, and the fundamentals of online analysis.
They also discuss the strengths & limitations of fNIRS compared to other BCI modalities.
▶️ https://zurl.co/pemtc
#Neuroscience #Neuroimaging -
New neuromapr #rstats package is available from GitHub! Highly experimental, early adopters and bug identifiers are super welcome to report issues!
It implements the framework from Markello et al. (2022, Nature Methods) and is aligned with the neuromaps Python reference implementation. Co-developed with Claude Code.
https://netneurolab.github.io/neuromaps/index.html -
The ggseg ecosystem finally has a proper home! 🧠
For those who don't know, ggseg is an R package ecosystem for visualizing brain atlas data. Think ggplot2, but for brains. -
Hemodynamic initial-dip reflects local spiking activity.
🧠 Initial-dip: transient HbR increase.
🔍 More spatially specific than hemodynamic response.
📉 HbT decrease leads to capping HbR.
🔄 Biphasic HbR with early decrease, late rebound.#fNIRS #Neuroimaging #Hemodynamics #Neuroscience #Pub2Post https://tnyp.me/l3nndrWk/m
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Another reason why you really can't beat yourself up over mistakes in the past -
Human #brains have 5 distinct 'epochs' in a lifetime, study finds https://www.nbcnews.com/science/science-news/human-brains-5-epochs-development-rcna245663
#braindevelopment #research #neuroimaging #neuralnetwork #mentalhealth #brainarchitecture
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Moving Day! Our state-of-the-art PRISMA 3T #MRI Scanner arrived at its new home, the #CoBIC. It offers very precise #neuroimaging and is a real asset for #neuroscientific research. But this is just the beginning, more exciting news about brand new imaging infrastructure coming soon!👀 @ESI_Frankfurt
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Timely synopsis of emerging #neuroimaging evidence linking #loss anticipation in the #insula to #stimulant use relapse by Jennifer Stewart of the Laureate Institute (thanks for the shout-out! #neuroscience, #addiction)...
https://www.sciencedirect.com/science/article/pii/S0006322323016256