#cognitiveperformance — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #cognitiveperformance, aggregated by home.social.
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DATE: August 11, 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: Cognitive abilities help explain regional brain aging patterns in anxiety and depression
A new study published in the Journal of Affective Disorders suggests that the advanced brain aging often seen in people with anxiety and depression is partly associated with variations in their cognitive performance. By accounting for cognitive skills like memory and processing speed, scientists observed that the apparent effect of these psychiatric conditions on brain aging decreased by roughly twenty to twenty-five percent. This indicates that cognitive differences play an important role in understanding brain health in individuals with neuropsychiatric conditions.
Biological aging of the brain can sometimes diverge from chronological aging. Using structural magnetic resonance imaging, machine learning algorithms can predict a person’s brain age by comparing their brain structure to a large dataset of healthy individuals. The difference between this predicted age and the person’s actual age is called the brain age gap. A positive gap indicates an older-appearing brain, which is linked to cognitive decline, health risks, and various neurological conditions.
Neuropsychiatric disorders like depression and anxiety are associated with increased brain age gaps. People with these conditions also frequently experience cognitive difficulties that affect their attention, executive function, and processing speed. Executive function refers to a set of mental skills that include working memory, flexible thinking, and self-control. Because cognitive decline is a common feature of mood disorders, it is often difficult to tell if brain aging differences reflect the psychiatric diagnosis itself or the accompanying cognitive variation.
Previous neuroimaging research typically looked at global brain age, which assumes aging happens uniformly across the entire brain. This approach can obscure specific regional effects.
“Our main motivation was that most previous brain-age studies summarize the entire brain using a single number,” said Owen M. Vega, a doctoral candidate in the neuroscience graduate program at the University of Southern California and a researcher at the Ethel Percy Andrus Gerontology Center in the Leonard Davis School of Gerontology.
“While useful, that approach assumes the brain ages uniformly and provides little insight into why certain disorders are associated with advanced brain aging. We wanted to move beyond prediction toward biological understanding,” Vega told PsyPost.
By mapping brain age at a regional level and accounting for cognitive performance, the researchers aimed to identify the specific neural systems affected and link them to underlying cellular processes.
“Ultimately, this brings us closer to understanding the biological mechanisms that contribute to psychiatric brain aging rather than simply measuring that it exists,” Vega explained.
The authors analyzed data from 21,424 older adult participants in the UK Biobank. Participants were classified into four mutually exclusive groups based on their diagnostic status. The sample included 12,285 individuals with no psychiatric diagnosis, 1,746 with anxiety only, 4,267 with depression only, and 1,563 with comorbid anxiety and depression. Comorbidity means the individual met the criteria for both conditions.
To estimate regional brain ages, the scientists processed structural brain scans through a deep neural network, breaking the brain down into 187 distinct cortical and subcortical regions. Participants also completed several cognitive assessments measuring fluid intelligence, reaction time, and symbol substitution. These test results were statistically combined into a single principal component score representing general cognitive performance. The models also controlled for participant sex, years of education, and socioeconomic deprivation to isolate the variables of interest.
The researchers first ran a statistical model that did not account for cognitive performance. They found widespread regional brain age gap elevations across the psychiatric groups compared to the diagnosis-free participants. On average, brains in the anxiety group appeared about 1.01 years older than chronological age. Brains in the depression group appeared 1.05 years older, and brains in the comorbid group appeared 1.14 years older.
These elevated brain ages were widely distributed but particularly pronounced in specific areas. The largest gaps were observed in the anterior frontal and orbitofrontal regions, as well as the temporal pole. These areas are heavily involved in emotion regulation and reward processing.
Vega noted that while the overall increases are relatively small, they provide a starting point for exploring the biology of mental health.
“The effects are statistically robust but modest in size, with average differences of about one year. However, they should not be interpreted as the whole story,” Vega told PsyPost. “Averaging across the entire brain masks much larger regional differences. The real significance of this work lies in identifying where these changes occur.”
By pinpointing these spatial patterns, scientists can relate them to specific genes and molecular pathways, moving the field past simple summary measures.
“This moves brain-age research beyond a single summary measure toward understanding the mechanisms that may contribute to psychiatric illness and cognitive vulnerability,” Vega added.
Next, the authors ran a second model that included the participants’ general cognitive performance scores. Factoring in cognition reduced the magnitude of the brain age gaps by approximately twenty to twenty-five percent. The mean gap dropped to 0.80 years for the anxiety group, 0.84 years for the depression group, and 0.78 years for the comorbid group. Despite this reduction, the effects remained present, indicating that diagnostic status contributes to brain aging independent of cognitive ability.
“The main takeaway is that anxiety and depression are associated with subtle but measurable differences in how the brain ages, and those differences are not spread evenly across the brain,” Vega said.
By showing how these estimates change when mental skills are factored into the equations, the study refines how scientists understand brain health in clinical populations.
“We also found that part of the observed brain-age signal is associated with cognitive performance, showing that cognition is an important piece of the picture,” Vega explained. “More broadly, our work suggests that brain aging in psychiatric disorders reflects specific biological patterns rather than a single, uniform process, which may ultimately help researchers develop more biologically meaningful biomarkers.”
Higher cognitive performance was associated with a younger-looking brain, suggesting a protective effect. This association was noticeably stronger in all three psychiatric groups compared to the diagnosis-free participants. Interestingly, the brain regions most strongly associated with cognitive performance differed from the regions most affected by the psychiatric diagnoses.
Cognitive associations were strongest in subcortical and ventral regions of the brain. These included the thalamus, pallidum, and hippocampus, which are structures located deep beneath the cerebral cortex that are essential for memory formation and information integration. This dissociation suggests that psychiatric status and cognition exert distinct but overlapping influences on different neural systems.
The researchers also looked beyond the magnetic resonance imaging scans to see if their regional brain age maps aligned with other biological data, such as transcriptomics. Transcriptomics is the study of RNA molecules in cells, which reveals how specific genes are turned on or off to drive cellular activity.
“One of the most striking findings was that several independent biological analyses converged on the same underlying systems,” Vega said. “Regional brain-aging patterns identified from MRI aligned with transcriptomic enrichment and biological pathways in a remarkably consistent way.”
This overlap suggests that the structural differences visible on brain scans are directly tied to cellular and genetic changes.
“That convergence gives us greater confidence that these patterns reflect meaningful biology rather than isolated statistical findings, and suggests that regional brain age can serve as a bridge between neuroimaging and molecular neuroscience,” Vega added.
The cross-sectional design of the study relies on data collected at a single point in time. This prevents researchers from establishing the sequence of events.
“A key caveat is that these results are not causal. Our findings do not demonstrate that anxiety or depression directly accelerate brain aging,” Vega said. “Instead, they identify patterns of brain-aging vulnerability associated with psychiatric illness and cognitive performance.”
Tracking individuals over multiple years is necessary to determine if cognitive differences precede advanced brain aging or reflect the downstream consequences of an aging brain. Bidirectional influences are highly likely in these conditions.
“Longitudinal studies will be needed to determine how these relationships evolve over time and whether they predict future cognitive decline,” Vega explained. “The goal was to refine the interpretation of previous brain-age findings and pave the way to clinical research, not to claim a direct mechanism.”
The diagnostic classifications were derived from a combination of self-reported surveys and clinician-confirmed records. The available data lacked details regarding symptom severity, illness duration, and the age of onset. The researchers were unable to determine if the older brain ages were linked to more severe, chronic, or recurrent forms of mental illness. Residual misclassification or reporting bias might also introduce variability into the data.
The UK Biobank predominantly consists of White European participants who are often healthier than the general population. This demographic makeup limits how well these findings apply to more diverse groups worldwide. Environmental factors, cultural differences, and early-life stressors that influence brain aging were not fully captured in the dataset. Future research should prioritize replicating these findings in more ethnically diverse cohorts.
Future research will continue to explore the genetic and molecular factors that drive these localized brain changes.
“Our next step is to relate regional brain-age maps to other spatially organized biological data,” Vega said. “We are now integrating regional brain-age maps with transcriptomic, genetic, and cellular datasets to identify the biological pathways associated with vulnerability to psychiatric brain aging.”
By building a more comprehensive biological profile, the team aims to improve risk assessments for aging adults.
“Ultimately, we hope this work will improve biologically informed risk stratification, help identify individuals at greatest risk for later cognitive decline, and reveal biological systems that may become targets for future therapeutic interventions,” Vega concluded.
The study, “Cognitive performance modulates regional brain age differences in clinical anxiety and depression,” was authored by Owen M. Vega, Phoebe Imms, Nikhil N. Chaudhari, Wendy J. Mack, Nahian F. Chowdhury, and Andrei Irimia.
-------------------------------------------------
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 #BrainAging #AnxietyDepression #CognitivePerformance #RegionalBrainAge #Neuroimaging #MentalHealthBiology #BrainAgeGap #CognitionAndBrain #Transcriptomics #BiomarkersInMentalHealth
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DATE: August 11, 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: Cognitive abilities help explain regional brain aging patterns in anxiety and depression
A new study published in the Journal of Affective Disorders suggests that the advanced brain aging often seen in people with anxiety and depression is partly associated with variations in their cognitive performance. By accounting for cognitive skills like memory and processing speed, scientists observed that the apparent effect of these psychiatric conditions on brain aging decreased by roughly twenty to twenty-five percent. This indicates that cognitive differences play an important role in understanding brain health in individuals with neuropsychiatric conditions.
Biological aging of the brain can sometimes diverge from chronological aging. Using structural magnetic resonance imaging, machine learning algorithms can predict a person’s brain age by comparing their brain structure to a large dataset of healthy individuals. The difference between this predicted age and the person’s actual age is called the brain age gap. A positive gap indicates an older-appearing brain, which is linked to cognitive decline, health risks, and various neurological conditions.
Neuropsychiatric disorders like depression and anxiety are associated with increased brain age gaps. People with these conditions also frequently experience cognitive difficulties that affect their attention, executive function, and processing speed. Executive function refers to a set of mental skills that include working memory, flexible thinking, and self-control. Because cognitive decline is a common feature of mood disorders, it is often difficult to tell if brain aging differences reflect the psychiatric diagnosis itself or the accompanying cognitive variation.
Previous neuroimaging research typically looked at global brain age, which assumes aging happens uniformly across the entire brain. This approach can obscure specific regional effects.
“Our main motivation was that most previous brain-age studies summarize the entire brain using a single number,” said Owen M. Vega, a doctoral candidate in the neuroscience graduate program at the University of Southern California and a researcher at the Ethel Percy Andrus Gerontology Center in the Leonard Davis School of Gerontology.
“While useful, that approach assumes the brain ages uniformly and provides little insight into why certain disorders are associated with advanced brain aging. We wanted to move beyond prediction toward biological understanding,” Vega told PsyPost.
By mapping brain age at a regional level and accounting for cognitive performance, the researchers aimed to identify the specific neural systems affected and link them to underlying cellular processes.
“Ultimately, this brings us closer to understanding the biological mechanisms that contribute to psychiatric brain aging rather than simply measuring that it exists,” Vega explained.
The authors analyzed data from 21,424 older adult participants in the UK Biobank. Participants were classified into four mutually exclusive groups based on their diagnostic status. The sample included 12,285 individuals with no psychiatric diagnosis, 1,746 with anxiety only, 4,267 with depression only, and 1,563 with comorbid anxiety and depression. Comorbidity means the individual met the criteria for both conditions.
To estimate regional brain ages, the scientists processed structural brain scans through a deep neural network, breaking the brain down into 187 distinct cortical and subcortical regions. Participants also completed several cognitive assessments measuring fluid intelligence, reaction time, and symbol substitution. These test results were statistically combined into a single principal component score representing general cognitive performance. The models also controlled for participant sex, years of education, and socioeconomic deprivation to isolate the variables of interest.
The researchers first ran a statistical model that did not account for cognitive performance. They found widespread regional brain age gap elevations across the psychiatric groups compared to the diagnosis-free participants. On average, brains in the anxiety group appeared about 1.01 years older than chronological age. Brains in the depression group appeared 1.05 years older, and brains in the comorbid group appeared 1.14 years older.
These elevated brain ages were widely distributed but particularly pronounced in specific areas. The largest gaps were observed in the anterior frontal and orbitofrontal regions, as well as the temporal pole. These areas are heavily involved in emotion regulation and reward processing.
Vega noted that while the overall increases are relatively small, they provide a starting point for exploring the biology of mental health.
“The effects are statistically robust but modest in size, with average differences of about one year. However, they should not be interpreted as the whole story,” Vega told PsyPost. “Averaging across the entire brain masks much larger regional differences. The real significance of this work lies in identifying where these changes occur.”
By pinpointing these spatial patterns, scientists can relate them to specific genes and molecular pathways, moving the field past simple summary measures.
“This moves brain-age research beyond a single summary measure toward understanding the mechanisms that may contribute to psychiatric illness and cognitive vulnerability,” Vega added.
Next, the authors ran a second model that included the participants’ general cognitive performance scores. Factoring in cognition reduced the magnitude of the brain age gaps by approximately twenty to twenty-five percent. The mean gap dropped to 0.80 years for the anxiety group, 0.84 years for the depression group, and 0.78 years for the comorbid group. Despite this reduction, the effects remained present, indicating that diagnostic status contributes to brain aging independent of cognitive ability.
“The main takeaway is that anxiety and depression are associated with subtle but measurable differences in how the brain ages, and those differences are not spread evenly across the brain,” Vega said.
By showing how these estimates change when mental skills are factored into the equations, the study refines how scientists understand brain health in clinical populations.
“We also found that part of the observed brain-age signal is associated with cognitive performance, showing that cognition is an important piece of the picture,” Vega explained. “More broadly, our work suggests that brain aging in psychiatric disorders reflects specific biological patterns rather than a single, uniform process, which may ultimately help researchers develop more biologically meaningful biomarkers.”
Higher cognitive performance was associated with a younger-looking brain, suggesting a protective effect. This association was noticeably stronger in all three psychiatric groups compared to the diagnosis-free participants. Interestingly, the brain regions most strongly associated with cognitive performance differed from the regions most affected by the psychiatric diagnoses.
Cognitive associations were strongest in subcortical and ventral regions of the brain. These included the thalamus, pallidum, and hippocampus, which are structures located deep beneath the cerebral cortex that are essential for memory formation and information integration. This dissociation suggests that psychiatric status and cognition exert distinct but overlapping influences on different neural systems.
The researchers also looked beyond the magnetic resonance imaging scans to see if their regional brain age maps aligned with other biological data, such as transcriptomics. Transcriptomics is the study of RNA molecules in cells, which reveals how specific genes are turned on or off to drive cellular activity.
“One of the most striking findings was that several independent biological analyses converged on the same underlying systems,” Vega said. “Regional brain-aging patterns identified from MRI aligned with transcriptomic enrichment and biological pathways in a remarkably consistent way.”
This overlap suggests that the structural differences visible on brain scans are directly tied to cellular and genetic changes.
“That convergence gives us greater confidence that these patterns reflect meaningful biology rather than isolated statistical findings, and suggests that regional brain age can serve as a bridge between neuroimaging and molecular neuroscience,” Vega added.
The cross-sectional design of the study relies on data collected at a single point in time. This prevents researchers from establishing the sequence of events.
“A key caveat is that these results are not causal. Our findings do not demonstrate that anxiety or depression directly accelerate brain aging,” Vega said. “Instead, they identify patterns of brain-aging vulnerability associated with psychiatric illness and cognitive performance.”
Tracking individuals over multiple years is necessary to determine if cognitive differences precede advanced brain aging or reflect the downstream consequences of an aging brain. Bidirectional influences are highly likely in these conditions.
“Longitudinal studies will be needed to determine how these relationships evolve over time and whether they predict future cognitive decline,” Vega explained. “The goal was to refine the interpretation of previous brain-age findings and pave the way to clinical research, not to claim a direct mechanism.”
The diagnostic classifications were derived from a combination of self-reported surveys and clinician-confirmed records. The available data lacked details regarding symptom severity, illness duration, and the age of onset. The researchers were unable to determine if the older brain ages were linked to more severe, chronic, or recurrent forms of mental illness. Residual misclassification or reporting bias might also introduce variability into the data.
The UK Biobank predominantly consists of White European participants who are often healthier than the general population. This demographic makeup limits how well these findings apply to more diverse groups worldwide. Environmental factors, cultural differences, and early-life stressors that influence brain aging were not fully captured in the dataset. Future research should prioritize replicating these findings in more ethnically diverse cohorts.
Future research will continue to explore the genetic and molecular factors that drive these localized brain changes.
“Our next step is to relate regional brain-age maps to other spatially organized biological data,” Vega said. “We are now integrating regional brain-age maps with transcriptomic, genetic, and cellular datasets to identify the biological pathways associated with vulnerability to psychiatric brain aging.”
By building a more comprehensive biological profile, the team aims to improve risk assessments for aging adults.
“Ultimately, we hope this work will improve biologically informed risk stratification, help identify individuals at greatest risk for later cognitive decline, and reveal biological systems that may become targets for future therapeutic interventions,” Vega concluded.
The study, “Cognitive performance modulates regional brain age differences in clinical anxiety and depression,” was authored by Owen M. Vega, Phoebe Imms, Nikhil N. Chaudhari, Wendy J. Mack, Nahian F. Chowdhury, and Andrei Irimia.
-------------------------------------------------
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 #BrainAging #AnxietyDepression #CognitivePerformance #RegionalBrainAge #Neuroimaging #MentalHealthBiology #BrainAgeGap #CognitionAndBrain #Transcriptomics #BiomarkersInMentalHealth
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DATE: July 26, 2026 at 06:00PM
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: Scientists reveal what is actually happening to your body when you let out a random sigh
A recent study published in the journal Psychophysiology suggests that spontaneous sighs act as a physical reset button for our breathing patterns during prolonged tasks. The research provides evidence that sighing helps regulate both breathing variability and physiological alertness when people are engaged in monotonous activities. These findings suggest that an occasional deep breath plays a basic role in maintaining physical balance during sustained attention.
The research team, consisting of Ralph W. G. Andrews, Michael C. Melnychuk, and Paul M. Dockree, sought to understand how spontaneous deep breaths relate to human attention. Everyday breathing is rarely perfectly steady or completely uniform. It contains natural variations in speed and depth, which scientists refer to as respiratory variability.
This variability is thought to keep the respiratory system flexible. A flexible system is better equipped to adapt to sudden changes in physical effort or emotional states. Over time, however, this variability can build up and become too chaotic or disorganized. Previous work suggests that a spontaneous sigh acts to reset this system, bringing chaotic breathing patterns back into a healthy and balanced range.
The scientists also wanted to test if sighs help reset mental alertness during tedious tasks. A specific brain network, known as the noradrenaline system, regulates general alertness and arousal in mammals. It acts as a chemical messenger network originating deep in the brain, sending signals to the rest of the nervous system to wake up or pay attention.
Activity in this system causes the pupil of the eye to expand or contract. The authors suspected that sighing might be intimately linked to this alertness network. They predicted that during boring tasks, a sigh might trigger a physical shift in brain arousal to help a person stay focused. When the body becomes too relaxed or disengaged, a deep breath could act as an internal alarm clock.
To test these predictions, the researchers analyzed data from two separate experiments. The first dataset included seventy-two adults who completed a visual attention test. Participants watched a computer screen for eight blocks of eight minutes each. They were instructed to click a mouse whenever a circular visual pattern slightly faded in contrast.
Throughout this visual test, the software randomly interrupted the task with thought probes. A probe would temporarily pause the experiment and ask participants to rate whether they were actively thinking about the visual task or if they were distracted by unrelated daydreams. This allowed the research team to track subjective engagement.
The second dataset involved fifty-seven participants engaging in a rhythmic listening task for twenty-one minutes. These individuals clicked a mouse in time with a continuous cycle of high and low audio tones. This group was split into two separate conditions. Thirty-two participants breathed normally without any specific instructions. Twenty-five participants were instructed to match their breathing to the changing audio tones, resulting in a slow and controlled breathing pattern.
In both experiments, the scientists measured breathing dynamics using a specialized effort belt worn around the participant’s lower chest. A sigh was specifically defined as any breath that was at least twice as deep as the participant’s average breath volume. The team also used high-speed tracking cameras to record the exact diameter of the participants’ pupils throughout the sessions.
The scientists found that people who breathed normally tended to sigh more frequently as the tasks wore on. As the minutes ticked by, their regular breathing patterns showed an increase in total variability. This means their breathing speed and depth became increasingly irregular over time. Immediately after a sigh occurred, this accumulated variability decreased.
The researchers distinguished between random breathing variability and structured breathing variability. Structured variability means that consecutive breaths are similar to one another, following a predictable sequence. The authors noted that sighs tended to occur when breathing lacked this predictable structure. Following a sigh, the variability in breathing depth became more structured and predictable again.
In the listening task, the group instructed to breathe slowly and steadily showed a completely different pattern. Their sighing dropped dramatically compared to the normal breathing group. Because they were intentionally controlling their breath, their respiratory variability was severely restricted. This suggests that intentional, controlled breathing overrides the body’s natural need to generate a deep sigh.
The visual test dataset revealed an interesting phenomenon known as phase-locking. Phase-locking is a behavior where the brain subconsciously matches biological rhythms to external events. In this context, participants subconsciously synchronized their natural breathing rhythms to the random timing of the fading visual targets on the screen.
The researchers found that the stronger a participant synchronized their breath to the screen, the more chaotic their general breathing became. Forcing the body to match an unpredictable external event seems to disrupt the natural respiratory rhythm. This high degree of synchronization was associated with a significantly higher number of sighs.
The research also revealed a direct connection between sighs and eye pupil size. During a sigh, participants’ pupils consistently dilated in a specific pattern. The pupil size began to increase at the start of the deep inhalation, peaked in size shortly after the breath reached its maximum depth, and then steadily contracted during the exhalation.
Because pupil dilation is a widely accepted proxy for the brain’s alertness system, this precise timing provides evidence that a sigh involves a rapid, coordinated change in physiological arousal. The scientists propose that sighs might help regulate arousal during prolonged tasks.
Interestingly, these physical resets did not translate into immediate behavioral improvements. Reaction times to the visual and auditory targets remained completely unchanged immediately after a sigh. Additionally, the participants’ self-reported focus on the task did not improve after a deep breath. The authors noted that this lack of behavioral change highlights a disconnect between bodily states and cognitive output in this specific context. The tasks were designed to be monotonous, which might explain why cognitive performance remained flat regardless of breathing changes.
It is necessary to acknowledge a few limitations regarding how the study was conducted. The method used to detect sighs relied entirely on breath volume. The respiratory equipment could not tell the difference between a natural sigh and a yawn. Because people tend to yawn when they are subjected to a monotonous task, yawning could have inflated the total number of deep breaths recorded in the datasets.
The attention tasks used in these experiments were relatively easy and undemanding. More difficult mental tasks might draw out different results, perhaps showing a stronger link between sighing and actual cognitive performance. In a high-stress scenario, a sigh might produce a measurable improvement in reaction time that was mostly invisible in a low-stress setting.
The single breathing belt only measured movement in the lower chest and abdomen. This setup might miss subtle changes in how the upper chest expands during respiratory shifts. The study also acknowledges that individual differences in emotional baseline states or daily stress levels were not entirely controlled, which might introduce slight variations in the data. Future studies could explore how different types of guided breathing exercises affect the natural urge to sigh. Additional research should also test whether the physical resets provided by sighing can be directly manipulated to help people stay focused in demanding environments.
The study, “Sighs Shape Respiratory Variability and Pupil Dynamics and Adapt to Sustained Attention Demands,” was authored by Ralph W. G. Andrews, Michael C. Melnychuk, and Paul M. Dockree.
-------------------------------------------------
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 #SighsInBreathing #RespiratoryVariability #PupilDynamics #SustainedAttention #BrainArousal #NoradrenergicSystem #PhaseLocking #BreathingReset #VisualAttention #CognitivePerformance
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DATE: July 26, 2026 at 06:00PM
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: Scientists reveal what is actually happening to your body when you let out a random sigh
A recent study published in the journal Psychophysiology suggests that spontaneous sighs act as a physical reset button for our breathing patterns during prolonged tasks. The research provides evidence that sighing helps regulate both breathing variability and physiological alertness when people are engaged in monotonous activities. These findings suggest that an occasional deep breath plays a basic role in maintaining physical balance during sustained attention.
The research team, consisting of Ralph W. G. Andrews, Michael C. Melnychuk, and Paul M. Dockree, sought to understand how spontaneous deep breaths relate to human attention. Everyday breathing is rarely perfectly steady or completely uniform. It contains natural variations in speed and depth, which scientists refer to as respiratory variability.
This variability is thought to keep the respiratory system flexible. A flexible system is better equipped to adapt to sudden changes in physical effort or emotional states. Over time, however, this variability can build up and become too chaotic or disorganized. Previous work suggests that a spontaneous sigh acts to reset this system, bringing chaotic breathing patterns back into a healthy and balanced range.
The scientists also wanted to test if sighs help reset mental alertness during tedious tasks. A specific brain network, known as the noradrenaline system, regulates general alertness and arousal in mammals. It acts as a chemical messenger network originating deep in the brain, sending signals to the rest of the nervous system to wake up or pay attention.
Activity in this system causes the pupil of the eye to expand or contract. The authors suspected that sighing might be intimately linked to this alertness network. They predicted that during boring tasks, a sigh might trigger a physical shift in brain arousal to help a person stay focused. When the body becomes too relaxed or disengaged, a deep breath could act as an internal alarm clock.
To test these predictions, the researchers analyzed data from two separate experiments. The first dataset included seventy-two adults who completed a visual attention test. Participants watched a computer screen for eight blocks of eight minutes each. They were instructed to click a mouse whenever a circular visual pattern slightly faded in contrast.
Throughout this visual test, the software randomly interrupted the task with thought probes. A probe would temporarily pause the experiment and ask participants to rate whether they were actively thinking about the visual task or if they were distracted by unrelated daydreams. This allowed the research team to track subjective engagement.
The second dataset involved fifty-seven participants engaging in a rhythmic listening task for twenty-one minutes. These individuals clicked a mouse in time with a continuous cycle of high and low audio tones. This group was split into two separate conditions. Thirty-two participants breathed normally without any specific instructions. Twenty-five participants were instructed to match their breathing to the changing audio tones, resulting in a slow and controlled breathing pattern.
In both experiments, the scientists measured breathing dynamics using a specialized effort belt worn around the participant’s lower chest. A sigh was specifically defined as any breath that was at least twice as deep as the participant’s average breath volume. The team also used high-speed tracking cameras to record the exact diameter of the participants’ pupils throughout the sessions.
The scientists found that people who breathed normally tended to sigh more frequently as the tasks wore on. As the minutes ticked by, their regular breathing patterns showed an increase in total variability. This means their breathing speed and depth became increasingly irregular over time. Immediately after a sigh occurred, this accumulated variability decreased.
The researchers distinguished between random breathing variability and structured breathing variability. Structured variability means that consecutive breaths are similar to one another, following a predictable sequence. The authors noted that sighs tended to occur when breathing lacked this predictable structure. Following a sigh, the variability in breathing depth became more structured and predictable again.
In the listening task, the group instructed to breathe slowly and steadily showed a completely different pattern. Their sighing dropped dramatically compared to the normal breathing group. Because they were intentionally controlling their breath, their respiratory variability was severely restricted. This suggests that intentional, controlled breathing overrides the body’s natural need to generate a deep sigh.
The visual test dataset revealed an interesting phenomenon known as phase-locking. Phase-locking is a behavior where the brain subconsciously matches biological rhythms to external events. In this context, participants subconsciously synchronized their natural breathing rhythms to the random timing of the fading visual targets on the screen.
The researchers found that the stronger a participant synchronized their breath to the screen, the more chaotic their general breathing became. Forcing the body to match an unpredictable external event seems to disrupt the natural respiratory rhythm. This high degree of synchronization was associated with a significantly higher number of sighs.
The research also revealed a direct connection between sighs and eye pupil size. During a sigh, participants’ pupils consistently dilated in a specific pattern. The pupil size began to increase at the start of the deep inhalation, peaked in size shortly after the breath reached its maximum depth, and then steadily contracted during the exhalation.
Because pupil dilation is a widely accepted proxy for the brain’s alertness system, this precise timing provides evidence that a sigh involves a rapid, coordinated change in physiological arousal. The scientists propose that sighs might help regulate arousal during prolonged tasks.
Interestingly, these physical resets did not translate into immediate behavioral improvements. Reaction times to the visual and auditory targets remained completely unchanged immediately after a sigh. Additionally, the participants’ self-reported focus on the task did not improve after a deep breath. The authors noted that this lack of behavioral change highlights a disconnect between bodily states and cognitive output in this specific context. The tasks were designed to be monotonous, which might explain why cognitive performance remained flat regardless of breathing changes.
It is necessary to acknowledge a few limitations regarding how the study was conducted. The method used to detect sighs relied entirely on breath volume. The respiratory equipment could not tell the difference between a natural sigh and a yawn. Because people tend to yawn when they are subjected to a monotonous task, yawning could have inflated the total number of deep breaths recorded in the datasets.
The attention tasks used in these experiments were relatively easy and undemanding. More difficult mental tasks might draw out different results, perhaps showing a stronger link between sighing and actual cognitive performance. In a high-stress scenario, a sigh might produce a measurable improvement in reaction time that was mostly invisible in a low-stress setting.
The single breathing belt only measured movement in the lower chest and abdomen. This setup might miss subtle changes in how the upper chest expands during respiratory shifts. The study also acknowledges that individual differences in emotional baseline states or daily stress levels were not entirely controlled, which might introduce slight variations in the data. Future studies could explore how different types of guided breathing exercises affect the natural urge to sigh. Additional research should also test whether the physical resets provided by sighing can be directly manipulated to help people stay focused in demanding environments.
The study, “Sighs Shape Respiratory Variability and Pupil Dynamics and Adapt to Sustained Attention Demands,” was authored by Ralph W. G. Andrews, Michael C. Melnychuk, and Paul M. Dockree.
-------------------------------------------------
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 #SighsInBreathing #RespiratoryVariability #PupilDynamics #SustainedAttention #BrainArousal #NoradrenergicSystem #PhaseLocking #BreathingReset #VisualAttention #CognitivePerformance
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Vitamin D3 During Pregnancy and Cognitive Performance at 10 Years
https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2849122
#HackerNews #VitaminD3 #Pregnancy #CognitivePerformance #HealthResearch #ScienceNews
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Vitamin D3 During Pregnancy and Cognitive Performance at 10 Years
https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2849122
#HackerNews #VitaminD3 #Pregnancy #CognitivePerformance #HealthResearch #ScienceNews
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The Cognitive Elite: Top 3 Nootropic Supplements for Brain Health and Performance
If there's one supplement that consistently garners praise for its elegant formulation and broad-spectrum benefits, it's Mind Lab Pro.
Save 25% when you buy a 4-month supply! Shop online!
https://sites.google.com/view/mind-lab-pro-nootropic/home?authuser=1
#nootropics #brainhealth #supplements #biohacking #mentalclarity #focus #neuroscience #wellness #productivity #brainpower #healthylifestyle #memory #cognitiveperformance
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The Cognitive Elite: Top 3 Nootropic Supplements for Brain Health and Performance
If there's one supplement that consistently garners praise for its elegant formulation and broad-spectrum benefits, it's Mind Lab Pro.
Save 25% when you buy a 4-month supply! Shop online!
https://sites.google.com/view/mind-lab-pro-nootropic/home?authuser=1
#nootropics #brainhealth #supplements #biohacking #mentalclarity #focus #neuroscience #wellness #productivity #brainpower #healthylifestyle #memory #cognitiveperformance
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Unlock Your Brain's Potential: The Power of Posture!
#PostureMatters #CognitivePerformance #BrainHealth #GoodPosture #MentalFocus #CerebralBloodFlow #HealthyHabits #MindBodyConnection #WellnessTips #BoostYourBrain #AttentionControl #Neuroscience #HealthyLiving #ProductivityTips
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Unlocking the Brain’s Secrets: Pain, Performance, and the Power of Substance P!
#BrainScience #PainManagement #Neuroplasticity #CognitiveBehavioralTherapy #Mindfulness #NeuropathicPain #SubstanceP #RehabilitationMedicine #MentalHealthMatters #Neuroscience #PainPerception #CognitivePerformance #MindBodyConnection #HealthAndWellness #EmotionalWellbeing
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Brief exercise sessions linked to small but consistent boosts in brain performance https://www.psypost.org/brief-exercise-sessions-linked-to-small-but-consistent-boosts-in-brain-performance/?utm_source=dlvr.it&utm_medium=mastodon #Exercise #BrainHealth #CognitivePerformance #FitnessTips #HealthyLiving
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Are night owls really smarter? 🦉
In my latest article on Medium, I dive into new research from Imperial College London that explores the link between chronotypes and cognitive performance. 🌟 It turns out that night owls might outperform early risers in areas like memory and logical reasoning! But does staying up late make you smarter? 🧐
Find out what science says about your natural sleep-wake cycle and how it can impact your productivity and well-being.
🚀 Check it out on Medium:
https://gisiger.medium.com/are-night-owls-smarter-new-insights-into-chronotypes-and-cognitive-performance-a00b9068af63#Productivity #SleepScience #NightOwls #CognitivePerformance
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Are night owls really smarter? 🦉
In my latest article on Medium, I dive into new research from Imperial College London that explores the link between chronotypes and cognitive performance. 🌟 It turns out that night owls might outperform early risers in areas like memory and logical reasoning! But does staying up late make you smarter? 🧐
Find out what science says about your natural sleep-wake cycle and how it can impact your productivity and well-being.
🚀 Check it out on Medium:
https://gisiger.medium.com/are-night-owls-smarter-new-insights-into-chronotypes-and-cognitive-performance-a00b9068af63#Productivity #SleepScience #NightOwls #CognitivePerformance
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https://pubmed.ncbi.nlm.nih.gov/38926480/ Cognitive functioning associated with acute and subacute effects of classic psychedelics and MDMA - a systematic review and meta-analysis (Basedow, et al, 2024) #mdma #psychedelics #fda #psychedelicresearch #psychedelic in which acute MDMA effect found to affect memory, leaving executive functions and attention unaffected. #brains #neuroscience #MDMAtherapy #ptsd #trauma #cognitiveperformance #cognition #psychedelictherapy