Neural and Behavioral Psychology Studies

The paper shows that believing in internal control increases self-evaluative affect and neural activity in the vmPFC, leading to preferences for control.

The paper shows that higher meta-cognitive ability is linked to reduced reliance on overconfident model-free learning in variable environments.

This study examines neural correlates of cognitive planning using EEG, finding increased frontal midline theta activity during planning tasks.

This study uses ERP to test whether deliberation requires more effort than intuition, finding conflicting results at different time windows.

The paper shows that the caudate nucleus coordinates adaptive decision-making by integrating visual evidence and reward context in monkeys.

The paper investigates whether value appraisal and choice processes are temporally dissociable using EEG, finding distinct neural activity patterns for each.

The paper develops a novel Pavlovian-to-instrumental transfer (PIT) task to measure how reward-predicting cues influence behavioral activation in young adults, finding increased effort in response to such cues.

The paper shows that the brain detects stimulus features but not conflict in task-irrelevant sensory input using EEG data from humans.

The paper identifies dissociable neural circuits for resolving three distinct sources of competition during task-switching, showing partial overlap in some circuits.

This study shows aging changes how the basolateral amygdala (BLA) influences intertemporal decision making, with BLA inactivation affecting impulsivity differently in young and aged rats.

The paper shows that humans can use implicit metacognition to make decisions based on unconscious brain states, outperforming current AI in high-dimensional tasks.

This study investigates the neural correlates of transition model learning through EEG experiments, identifying fronto-midline theta and delta oscillations and the anterior midcingulate cortex's role in planning behavior.

This study investigates how decision evidence is represented in human brain signals using magnetoencephalography, identifying three distinct phases of processing in different brain regions.

This study uses multi-level MVPA with fMRI to investigate how task sets are represented in the brain, finding co-activation in prefrontal cortex and conjunctive representation in visual cortex.

This paper uses machine learning to analyze EEG data from a modified Flanker Task, revealing three levels of inhibitory control that group-level statistics miss.

The paper introduces a method using recurrent neural networks to jointly model behavioral and neuroimaging data, revealing new insights into the temporal patterns of brain activity related to decision-making.

This study identifies distinct neural ensemble patterns in the orbitofrontal cortex that differentiate successful from failed inhibition during a stop signal task in macaques.

The paper investigates how frontal action circuits adapt economic choices to context by tracking evolving preferences and integrating them with action signals.

The paper introduces an urgency requirement to the antisaccade task to study cognitive mechanisms, finding a nonlinear relationship between cue exposure duration and performance success.

The paper investigates how speed pressure affects decision-making by analyzing sensory evidence accumulation, finding that responses are triggered near the peak of evidence accumulation rather than after reaching a threshold.

The paper investigates how conflict is perceived as a cost in value-based decisions, showing that conflict can influence decision-making and learning differently depending on its source.

This study examines how depression affects goal-directed and habitual control in the prefrontal-striatal circuitry, revealing disruptions in reinforcement learning processes.

This study investigates how depressive symptoms affect reward learning in social contexts, finding a negative audience effect rather than impaired integration of social information.

This study investigates whether model-free reinforcement learning can operate on information stored in working memory using human participants in a reward learning task with sequential and simultaneous visual stimuli.

The paper shows that OFC neurons in macaques represent reward magnitude, certainty, and volatility as orthogonal dimensions during a visual stimulus-reward task.

The paper investigates neural responses in ferret dorsolateral frontal cortex during an auditory reversal task, finding that weak representation of behavioral meaning correlates with proactive interference.

The paper investigates automatic emotion regulation through implementation intention, showing it reduces negative feelings and amygdala activity without cognitive effort.

This study examines how semantic and basic encoding processes modulate self-esteem by analyzing neural interactions during feedback processing.

This study compares executive function performance between healthy and neuropsychiatric adults, finding larger cortical size correlates with better performance, more strongly in neuropsychiatric groups.

This study investigates how dopamine modulates the precision of cortical unsigned prediction errors and its impact on learning.