#neuralmarkers — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #neuralmarkers, aggregated by home.social.
-
DATE: August 14, 2026 at 09:00AM
SOURCE: PSYPOST.ORG** Research quality varies widely from fantastic to small exploratory studies. Please check research methods when conclusions are very important to you. **
-------------------------------------------------TITLE: Neuroscientists uncover a universal mechanism for human decision making
When humans learn new rules to make decisions, our brains appear to use the exact same information-gathering process that they use to process basic physical sensations. A recent study shows that a specific brain wave associated with collecting evidence readily adapts to track arbitrary, newly learned categories. The research was published as a preprint in The Journal of Neuroscience.
To understand how we make choices, neuroscientists often rely on a concept called evidence accumulation. This theory suggests that the brain acts like a bucket collecting drops of water. As sensory information comes in, the brain continuously gathers this evidence until it reaches a specific threshold, triggering a final decision.
Researchers can observe this accumulation process in real time using an electroencephalogram, or EEG. By placing sensors on a person’s scalp, scientists track electrical patterns known as brain waves. One specific pattern, called the centro-parietal positivity, reliably mirrors the evidence accumulation process.
The centro-parietal positivity presents as a gradual buildup of positive electrical voltage in the brain. This voltage climbs steadily while a person weighs their options. The electrical signal peaks just before the individual executes a response, like pressing a button.
Prior studies have shown that this brain wave tracks evidence from physical stimuli, such as a group of dots moving across a screen. As more dots move in the same direction, the electrical signal climbs faster. It also tracks information pulled from memory, like recalling trivia facts, or basic semantic knowledge.
Other research has found that the brain can accumulate evidence based on fixed, universally shared visual concepts. For instance, people naturally distinguish between vertical lines and diagonal lines. The brain uses these permanent visual frameworks to sort out incoming information.
Scientists did not know if the brain could apply this accumulation mechanism to entirely arbitrary rules. If a rule is newly invented and highly specific to one person, the evidence does not actually exist in the visual environment. Instead, the brain must compute the evidence internally by comparing what it sees against a newly learned, imaginary standard.
University of Nevada, Reno researchers Arianna Thoksakis and Edward F. Ester designed a study to test this question. They wanted to see if the brain’s decision-making machinery is truly flexible across different types of information. If so, the centro-parietal positivity should respond to abstract, newly learned rules just as it responds to direct sensory input.
The researchers recruited volunteers to complete a visual categorization task while hooked up to an EEG machine. Data from 38 participants was ultimately included in the analysis. The participants viewed circular images filled with hundreds of parallel lines.
During a training phase, participants had to categorize these images into two distinct groups by pressing specific keys on a keyboard. The researchers assigned a hidden, arbitrary dividing line for each participant. For example, a boundary might be set at exactly 73 degrees, completely invisible to the individual.
Any lines tilted counterclockwise to this specific angle belonged to the first category, while clockwise lines belonged to the second category. Through trial and error, guided by correct or incorrect feedback after every choice, the participants had to figure out their unique boundary. Most volunteers learned the invisible rule within a few short rounds.
Once the participants understood the rule, they moved on to the main task. The researchers presented lines tilted at specific angles relative to the participant’s hidden boundary. Some images featured lines tilted 45 degrees away from the boundary, making them easy to categorize. Other images were much harder, featuring lines tilted just two degrees away from the dividing line.
Behavioral results showed that participants were faster and more accurate when the lines were rotated further from their learned boundary. To connect this performance to the brain’s internal processes, the researchers used a mathematical framework called a drift-diffusion model. This approach separates the raw speed of a physical reaction from the cognitive process of weighing options.
The mathematical model estimates a specific metric known as the drift rate, which represents the speed of information gathering. The calculations confirmed that drift rates increased steadily as the lines moved further from the boundary. Essentially, the larger the angular distance from the hidden rule, the stronger the evidence became. This stronger evidence allowed the brain to accumulate information at a much faster pace, leading to quicker choices.
Next, the researchers examined the EEG data to see if the brain’s electrical signals matched this behavioral pattern. They measured the centro-parietal positivity buildup during the moments leading up to each participant’s button press. The electrical slope grew much steeper for images that were further from the category boundary.
The team then compared the behavioral math to the electrical brain recordings. They found a strong correlation across the participants. Individuals who showed a high behavioral sensitivity to the visual categories also displayed a highly sensitive electrical buildup in their brain waves.
This correlation suggests that the electrical signal is a direct reflection of the underlying decision variable. The brain’s machinery for accumulating physical sensations and its machinery for accumulating computed, abstract evidence are not separate systems. They appear to be a single, highly adaptable mechanism.
To verify that this electrical buildup was truly about decision-making, the researchers checked another region of the brain entirely. They analyzed beta waves over the motor cortex, which specifically control the physical movement of the hands and fingers. Because the right side of the brain controls the left hand and vice versa, researchers can track exactly when the brain prepares to push a button.
They needed to ensure the decision signals were not just the result of a participant flexing their muscles to press a key. While the motor cortex did show the expected activation as participants prepared to respond, this activity did not change based on the difficulty of the image. The motor preparation remained identical whether the lines were two degrees or 45 degrees from the boundary. This confirms that the centro-parietal positivity reflects the mental act of deciding, rather than the physical act of moving.
There are a few methodological details to consider regarding the study design. When an image suddenly appears on a screen, it causes a rapid burst of visual processing in the brain. Because participants responded relatively quickly, this initial visual response could overlap temporally with the decision-making brain waves being measured.
While this visual overlap is present, it is unlikely to fully explain the strong correlation seen between individual brain waves and computational drift rates. Future studies could separate the visual onset from the decision-making period to completely rule out any sensory interference.
Additionally, this experiment relied on a very specific type of visual feature. Participants evaluated a single dimension, which was the orientation of straight lines. The rule separating the categories was also absolute, relying on a hard dividing line.
In natural environments, categories are rarely this simple. Objects belong to categories based on a mixture of shapes, colors, and textures, and the boundaries are often probabilistic rather than absolute. Testing whether the brain’s evidence accumulation mechanism works the same way for these messier, real-world categories will require additional research.
The study, “Neural Measures of Human Decision Making Track Evidence Accumulation in Learned Space,” was authored by Arianna Thoksakis and Edward F. Ester.
-------------------------------------------------
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 #Neuroscience #DecisionMaking #EvidenceAccumulation #CentroParietalPositivity #EEG #DriftDiffusionModel #AbstractReasoning #VisualCategorization #NeuralMarkers #BrainWaves
-
DATE: July 31, 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: Brain activity patterns may shape how we remember childhood trauma
URL: https://www.psypost.org/brain-activity-patterns-may-shape-how-we-remember-childhood-trauma/
Recent research suggests a person’s innate brain activity patterns might influence how they subjectively experience childhood adversity, which in turn shapes their vulnerability to depression. The findings propose a specific biological and psychological sequence that could help explain why some people develop traits that predispose them to mood disorders. The study was published in the *Journal of Affective Disorders*.
To understand mental health risks, psychology frequently looks at an individual’s basic temperament. Temperaments are innate, enduring traits that dictate how a person generally reacts to the world. A depressive temperament is considered a subclinical condition, meaning it is not a diagnosis of full-blown depression. Instead, it is a baseline personality disposition characterized by persistent seriousness, low energy, and a tendency toward sadness. Research shows that possessing these specific traits acts as a biological vulnerability marker for developing a major depressive disorder later in life.
Childhood maltreatment is another widely recognized risk factor for depression. Maltreatment includes both active abuse, like physical or emotional harm, and passive neglect, such as ignoring a child’s basic needs. Individuals who endure chronic stress during their developmental years often face a higher likelihood of long-term emotional dysregulation. However, the exact biological mechanisms that connect early life adversity to a permanent depressive temperament have remained partially obscured.
Typically, studies frame childhood trauma as an external force that alters the developing brain, which then produces a vulnerability to mood disorders. Wenjin Zou and Huiyuan Huang, researchers affiliated with Guangzhou Medical University in China, wanted to test a slightly different physiological sequence. The research team proposed that preexisting, localized brain mechanisms might actually shape how a person internally processes and remembers adverse childhood events. In this model, the brain’s innate wiring dictates the subjective severity of the trauma, and that subjective pain is what fosters a depressive temperament.
To investigate this idea, the researchers recruited 97 healthy adult participants from the general community. They screened the volunteers to ensure none had a history of psychiatric disorders, neurological conditions, or major medical illnesses. The participants then completed standard psychological questionnaires designed to capture their basic personality traits and their history of early life stress. One questionnaire measured the severity and frequency of various forms of childhood abuse and neglect based entirely on the participant’s retrospective memory. Another assessment measured the presence of a depressive temperament based on daily thoughts and behaviors.
Following the questionnaires, the participants underwent resting-state functional magnetic resonance imaging. A functional MRI scanner detects changes in blood flow within the brain, providing a map of neural activity. In a resting-state scan, the participants simply lie in the machine with their eyes closed and let their minds wander without engaging in any specific mental task. This allows researchers to observe spontaneous brain activity, reflecting the brain’s natural, default state of operation.
The team analyzed the imaging data using a metric called regional homogeneity. This analytical technique measures how synchronized the spontaneous activity is within small, clustered areas of the brain. When local groups of brain cells fire together in perfect harmony, regional homogeneity is high. When nearby cells act out of sync with one another, the local homogeneity levels are low. Alterations in these local synchronization patterns often point to specialized neural adaptations or vulnerabilities.
When comparing the brain scans to the survey results, the researchers found a direct association between the severity of recalled childhood maltreatment and regional homogeneity in three specific brain areas. The first region was the right hippocampus, a structure deeply involved in forming memories and managing emotions. People who reported higher levels of childhood trauma showed increased synchronization in this area. This heightened activity might reflect a neural adaptation that makes a person more sensitive to encoding traumatic memories.
The second area showing increased synchronization was the left insular cortex. This region acts as a hub for internal bodily awareness and detecting environmental threats. Elevated synchronization here could indicate a persistent state of physical hypervigilance developed in response to early life stress. Conversely, the researchers noted a decrease in regional homogeneity in the right lingual gyrus, an area dedicated to visual processing. A drop in synchronization here might suggest the brain is adaptively disengaging from trauma-related visual cues.
To test the strength of these brain markers, the researchers employed a machine learning technique known as support vector regression. They fed the localized brain activity data into a computer algorithm to see if it could predict an individual’s childhood trauma score without looking at the actual questionnaire results. The algorithm successfully matched the brain patterns to the severity of the maltreatment reported by the subjects. This demonstrated a tight mathematical relationship between localized spontaneous brain activity and the memory of early life adversity.
The primary focus of the study involved a statistical technique called mediation analysis. Mediation analysis tests whether a middle variable acts as an explanatory bridge connecting a starting variable to a final outcome. The researchers wanted to know if subjective childhood trauma bridges the gap between spontaneous brain activity and a depressive temperament. They set up mathematical models to calculate the flow of these relationships across all 97 participants.
The analysis revealed a specific, one-way path connecting the three factors. Spontaneous brain activity in the hippocampus and the insular cortex was associated with how severely the participants rated their childhood trauma. That subjective severity rating was then directly associated with the intensity of their depressive temperament. When the researchers tested an alternative model assuming trauma caused the brain changes which then caused the temperament, the statistical relationships were not statistically significant.
This pathway suggests that innate neural activity influences an individual’s psychological appraisal of their environment. Rather than just being a passive record of historical events, the brain’s baseline synchronization might dictate how intensely a person feels and remembers their past trauma. The subjective weight of those memories then appears to nurture the development of a lifelong depressive disposition. By acting as a perceptive filter, the brain’s original state plays an active role in translating the environment into a clinical vulnerability.
The authors noted several limitations in their research design. The study relied on cross-sectional data, meaning all the information was gathered at a single point in time. Because the researchers did not follow the participants from childhood into adulthood, they cannot definitively prove the chronological order of these biological and psychological changes. They can only point out that the variables are statistically linked in the present.
Additionally, the measurement of childhood trauma relied exclusively on retrospective self-reporting. Questionnaires inherently capture a person’s subjective memory of an event rather than an objective historical record. There is a possibility that people who already possess a depressive temperament simply remember their childhoods more negatively than others. Relying on self-reporting makes it difficult to separate true environmental exposure from the influence of current mood states.
The machine learning analysis also utilized a process that can sometimes generate overly optimistic results. The algorithm learned from the same overall dataset that it was ultimately tested on. In predictive statistics, this can inflate the apparent accuracy of the mathematical model. Future studies will need to train algorithms on one group of people and test them on an entirely separate group to verify the strength of the brain signatures.
Future research will also need to expand beyond healthy community samples. Investigating individuals actively diagnosed with major depressive disorder could reveal whether these same pathways operate differently during a clinical mental health crisis. Following a group of people over many years, while keeping objective records of their early life environments, would help clarify exactly how the brain and childhood adversity interact over an entire lifespan.
The study, “Childhood maltreatment mediates the effect of spontaneous brain activity on depressive temperament,” was authored by Wenjin Zou, Huiyuan Huang, Liangda Zhong, Sha Liu, Zezhi Li, Ruiwang Huang, Shufei Zhang, and Huawang Wu.
URL: https://www.psypost.org/brain-activity-patterns-may-shape-how-we-remember-childhood-trauma/
-------------------------------------------------
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 #BrainActivity #ChildhoodTrauma #DepressiveTemperament #MediationAnalysis #RestingStatefMRI #NeuralMarkers #HippocampusFunction #InsularCortex #DepressionRisk #EarlyLifeAdversity
-
Largest brain connectivity study of youth depression reveals key network disruptions https://www.psypost.org/largest-brain-connectivity-study-of-youth-depression-reveals-key-network-disruptions/?utm_source=dlvr.it&utm_medium=mastodon #youthdepression #brainconnectivity #mentalhealth #neuralmarkers #introspection