Neural and Behavioral Psychology Studies

Model-based EEG phenotyping uncovers distinct neurocomputational mechanisms underlying learning impairments across psychopathologies

This paper uses model-based EEG analysis to identify distinct neurocomputational mechanisms of learning impairments in MDD, BP, and SCZ compared to controls.

The Role of Attention in Multi Attribute Decision Making

The paper investigates how attention influences multi-attribute decision-making in monkeys by analyzing neural activity in the pre-supplementary motor area.

Exploring brain dynamics within the Approach-Avoidance Bias

This study uses EEG to examine neural correlates of approach-avoidance bias in a non-clinical population, finding early visual processing and motor preparation effects but no significant condition differences.

A nonlinear code for event probability in the human brain

The paper identifies a nonlinear neural code for event probability in the human brain using fMRI, showing distinct tuning curves in prefrontal and parietal cortices.

Effect of dependency and tail behavior on a probability inequality occurring in modeling cognitive processes

The paper investigates general forms of stochastic dependence that imply a probability inequality in race models of cognitive tasks, using copulas and heavy-tailed distributions.

Distributed activity in the human posterior putamen distinguishes goal-directed from habitual control

The paper uses fMRI decoding to show that neural activity in the posterior putamen during learning predicts individual differences in habit versus goal-directed behavior across multiple cohorts.

A flexible coding scheme underlying working memory generalization in human parietal and frontal cortices

This study investigates how working memory generalization occurs across tasks in human parietal and frontal cortices using functional MRI experiments.

Evidence for flexible regulation of movement and decision vigor in a reward-oriented task

The paper tests whether movement and decision vigor are co-regulated or decoupled in a reward task, finding they are mostly decoupled and driven by distinct time-cost signals.

Early Arousal Signals Drive Reward Learning and Subsequent Choice Behaviour

The paper examines EEG and pupillometry signals during reward learning, showing that an early neural signal following negative feedback is linked to uncertainty and improved learning through network resets.

Neural representation of the decisional reference point in monkeys

This study identifies neural encoding of the decisional reference point in macaques, showing that only the ventral bank of the anterior cingulate cortex encodes it at the population level.

Dissociable Pupil and Oculomotor Markers of Attention Allocation and Distractor Suppression during listening

The paper examines how pupil dilation, blinks, and microsaccades differ during attention and distractor suppression in an auditory task, revealing distinct cognitive mechanisms.

Betrayal and unfairness are linked through insula-valuation network dynamics

The paper investigates how neural responses to betrayal and unfairness are linked through insula-valuation network dynamics in social exchange tasks.

Subliminal beauty engages the brain's valuation circuits

This study shows that subjective value signals in the brain's valuation circuits can be computed without conscious awareness of the stimuli.

Selective engagement of the primate orbitofrontal cortex during value-based but not perceptual decisions

This study shows that the primate orbitofrontal cortex is specifically involved in value-based decisions but not perceptual decisions, indicating functional specialization.

The orbitofrontal cortex updates beliefs for state inference

This study shows that rat orbitofrontal cortex updates beliefs about hidden reward states during a temporal wagering task, with neural signatures of state inference identified through electrophysiology and population analysis.

Reactive suppression of distractor representations resolves multidimensional interference

The paper shows that multidimensional attentional control involves reactive suppression of distractor representations in human EEG, guided by a structured multivariate conflict signal.

Mixture-models for stimulus-selective stopping

The paper develops mixture-model classes for stimulus-selective stopping and applies them to a published dataset.

Interpretable and Brain-Inspired Recurrent Model of Hierarchical Decision-Making Capturing Trial-by-Trial Variability

The paper develops a neurocomputational model of hierarchical decision-making that captures trial-by-trial variability and reproduces human behavioral patterns.

Is the whole the sum of its parts? Neural computation of consumer bundle valuation in humans

This study investigates how the human brain computes value for individual items and bundles, finding sub-additive discounting and context-dependent normalization in prefrontal cortex value representations.

A Common Neural Signal of Evidence Accumulation for Perceptual and Mnemonic Decisions

The paper investigates whether the centro-parietal positivity (CPP) EEG component reflects evidence accumulation in perceptual and mnemonic decisions, finding it scales with evidence strength, response time, and confidence across tasks.

Neural dynamics of covert habit activation and control in humans

This study uses EEG to investigate covert habit activation and control in humans, finding that the lateralized readiness potential tracks habitual responses and frontal midline theta power scales with habit override.

Continuous theta-burst stimulation of the ventromedial prefrontal cortex reduces Pavlovian go-invigoration and enhances thalamo-striatal reward prediction error signals

This study uses cTBS to inhibit the vmPFC and shows reduced Go responses, slower reaction times, and increased reward prediction error signals in subcortical regions.

The temporal and perceptual characteristics of emotion-induced blindness

This study investigates how temporal and perceptual factors influence emotion-induced blindness in RSVP paradigms, finding that emotional distractors persistently affect target detection even without conscious recall.

Identifying Neural Biomarkers of Risk-Taking from Intracranial EEG Recordings

This study identifies neural biomarkers of risk-taking using intracranial EEG data from a single patient, achieving 68.5% classification accuracy.

Medial Frontal Theta Reduction Impairs Rule Switching via Prediction Error

This study shows that reducing medial frontal theta oscillations impairs rule switching in a probabilistic reversal learning task, supporting the role of prediction error signaling in cognitive flexibility.

Unraveling the Neurocognitive Mechanisms of Delayed Punishment in Second- and Third-Party Contexts

This study investigates how second-party and third-party punishment decisions change with delayed punishment using fMRI, finding distinct neural mechanisms and severity effects in third-party contexts.

Ventromedial prefrontal cortex shields value computations from bodily arousal in decision making

This study shows that ventromedial prefrontal cortex (vmPFC) excitability decouples value computations from physiological arousal during normative decision making, increasing selfishness in social interactions.

The role of attention in the generation of anticipatory potentials to affective stimuli: an ERP and source analysis study

This study investigates anticipatory EEG signals to affective stimuli, finding that negativity reflects attentional resource allocation rather than emotional content.

Choosing the best or avoiding the worst: complementary and opponent value signals in the human brain

The paper investigates how the brain encodes value signals for pleasant and unpleasant scenarios, showing distinct neural systems in vmPFC and aIns that guide decision-making.

Distinct contributions of anterior and posterior orbitofrontal cortex to outcome-guided behavior

This study shows that anterior and posterior orbitofrontal cortex subregions support different aspects of outcome-guided behavior: learning stimulus-outcome associations and inferring current option values.