Risk-taking bias in human decision-making is encoded via a right-left brain push-pull system

An EEG Dataset of Neural Signatures in a Competitive Two-Player Game Encouraging Deceptive Behavior

Studying deception is vital for understanding decision-making and social dynamics. Recent EEG research has deepened insights into the brain mechanisms behind deception. Standard methods in this field often rely on memory, are vulnerable to countermeasures, yield false positives, and lack real-world relevance. Here, we present a comprehensive dataset from an EEG-monitored competitive, two-player card game designed to elicit authentic deception behavior. Our extensive dataset contains EEG data from 12 pairs (N = 24 participants with role switching), controlled for age, gender, and risk-taking, with detailed labels and annotations. The dataset combines standard event-related potential and microstate analyses with state-of-the-art decoding approaches of four scenarios: spontaneous/instructed truth-telling and lying. This demonstrates game-based methods' efficacy in studying deception and sets a benchmark for future research. Overall, our dataset represents a unique resource with applications in cognitive neuroscience and related fields for studying deception, competitive behavior, decision-making, inter-brain synchrony, and benchmarking of decoding frameworks in a difficult, high-level cognitive task.

Internal states as a source of subject-dependent movement variability are represented by large-scale brain networks

Humans' ability to adapt and learn relies on reflecting on past performance. These experiences form latent representations called internal states that induce movement variability that improves how we interact with our environment. Our study uncovered temporal dynamics and neural substrates of two states from ten subjects implanted with intracranial depth electrodes while they performed a goal-directed motor task with physical perturbations. We identified two internal states using state-space models: one tracking past errors and the other past perturbations. These states influenced reaction times and speed errors, revealing how subjects strategize from trial history. Using local field potentials from over 100 brain regions, we found large-scale brain networks such as the dorsal attention and default mode network modulate visuospatial attention based on recent performance and environmental feedback. Notably, these networks were more prominent in higher-performing subjects, emphasizing their role in improving motor performance by regulating movement variability through internal states.

Individual risk attitudes arise from noise in neurocognitive magnitude representations

Humans are generally risk averse, preferring smaller certain over larger uncertain outcomes. Economic theories usually explain this by assuming concave utility functions. Here, we provide evidence that risk aversion can also arise from relative underestimation of larger monetary payoffs, a perceptual bias rooted in the noisy logarithmic coding of numerical magnitudes. We confirmed this with psychophysics and functional magnetic resonance imaging, by measuring behavioural and neural acuity of magnitude representations during a magnitude perception task and relating these measures to risk attitudes during separate risky financial decisions. Computational modelling indicated that participants use similar mental magnitude representations in both tasks, with correlated precision across perceptual and risky choices. Participants with more precise magnitude representations in parietal cortex showed less variable behaviour and less risk aversion. Our results highlight that at least some individual characteristics of economic behaviour can reflect capacity limitations in perceptual processing rather than processes that assign subjective values to monetary outcomes.

Association between vmPFC gray matter volume and smoking initiation in adolescents

Smoking of cigarettes among young adolescents is a pressing public health issue. However, the neural mechanisms underlying smoking initiation and sustenance during adolescence, especially the potential causal interactions between altered brain development and smoking behaviour, remain elusive. Here, using large longitudinal adolescence imaging genetic cohorts, we identify associations between left ventromedial prefrontal cortex (vmPFC) gray matter volume (GMV) and subsequent self-reported smoking initiation, and between right vmPFC GMV and the maintenance of smoking behaviour. Rule-breaking behaviour mediates the association between smaller left vmPFC GMV and smoking behaviour based on longitudinal cross-lagged analysis and Mendelian randomisation. In contrast, smoking behaviour associated longitudinal covariation of right vmPFC GMV and sensation seeking (especially hedonic experience) highlights a potential reward-based mechanism for sustaining addictive behaviour. Taken together, our findings reveal vmPFC GMV as a possible biomarker for the early stages of nicotine addiction, with implications for its prevention and treatment.

Risk and aversion coding in human habenula high gamma activity

Neurons in the primate lateral habenula fire in response to punishments and are inhibited by rewards. Through its modulation of midbrain monoaminergic activity, the habenula is believed to play an important role in adaptive behavioural responses to punishment and underlie depressive symptoms and their alleviation with ketamine. However, its role in value-based decision-making in humans is poorly understood due to limitations with non-invasive imaging methods which measure metabolic, not neural, activity with poor temporal resolution. Here, we overcome these limitations to more closely bridge the gap between species by recording local field potentials directly from the habenula in 12 human patients receiving deep brain stimulation treatment for bipolar disorder (n = 4), chronic pain (n = 3), depression (n = 3) and schizophrenia (n = 2). This allowed us to record neural activity during value-based decision-making tasks involving monetary rewards and losses. High-frequency gamma (60-240 Hz) activity, a proxy for population-level spiking involved in cognitive computations, increased during the receipt of loss and decreased during receipt of reward. Furthermore, habenula high gamma also encoded risk during decision-making, being larger in amplitude for high compared to low risk. For both risk and aversion, differences between conditions peaked approximately between 400 and 750 ms after stimulus onset. The findings not only demonstrate homologies with the primate habenula but also extend its role to human decision-making, showing its temporal dynamics and suggesting revisions to current models. The findings suggest that habenula high gamma could be used to optimize real-time closed-loop deep brain stimulation treatment for mood disturbances and impulsivity in psychiatric disorders.

Decomposing Executive Function into Distinct Processes Underlying Human Decision Making

Executive function (EF) consists of higher level cognitive processes including working memory, cognitive flexibility, and inhibition which together enable goal-directed behaviors. Many neurological disorders are associated with EF dysfunctions which can lead to suboptimal behavior. To assess the roles of these processes, we introduce a novel behavioral task and modeling approach. The gamble-like task, with sub-tasks targeting different EF capabilities, allows for quantitative assessment of the main components of EF. We demonstrate that human participants exhibit dissociable variability in the component processes of EF. These results will allow us to map behavioral outcomes to EEG recordings in future work in order to map brain networks associated with EF deficits. Clinical relevance- This work will allow us to quantify EF deficits and corresponding brain activity in patient populations in future work.

Neural mass model-based study of frontal-temporal theta oscillations in human subjects during the performance of a cognitive control task

Cognitive control, the ability to rapidly shift one's attention and behavioral strategy in response to environmental changes, is often compromised across psychiatric disorders. One of the well-validated behavioral paradigms for tapping into the cognitive control circuits is a cognitive interference task, where subjects must suppress a natural response to follow a less intuitive rule. Slower response times on these tasks indicate difficulty exerting control to overcome response conflict. Conflict evokes robust electrophysiological signatures, such as theta (4-8 Hz) oscillations in the prefrontal cortex (PFC). However, the underlying neural mechanisms of conflict-evoked theta oscillations in the PFC are not clear. The objective of this work is to use a neural mass model (NMM) to find feasible cortical networks generating theta oscillations during conflict processing in human subjects. We used intracranial EEG (iEEG) recorded from dorsolateral PFC (dIPFC) and lateral temporal lobe (LTL) of human subjects with intractable epilepsy undergoing invasive monitoring, while they performed a multi-source interference task (MSIT). We used a dynamic causal modeling (DCM) framework to simulate dIPFC-LTL theta using a Jansen-Rit NMM. We found significant evidence for an LTL input into the dlPFC during the initial 500 ms of conflict processing compared to a bidirectional connection between the dlPFC and LTL. We conclude that a neural mass modeling framework can be used to elucidate candidate mechanisms of neural oscillations underlying conflict resolution in human subjects. Clinical Relevance- This can be used to find feasible target mechanisms for designing therapy in patients with compromised cognitive control. This framework can also be expanded to serve as an in-silico test bed for designing and testing neuromodulatory interventions such as electrical stimulation for improving cognitive control in mood/anxiety disorders.

Structure-function coupling within the reward network in preschool children predicts executive functioning in later childhood

Early differences in reward behavior have been linked to executive functioning development. The nucleus accumbens (NAc) and orbitofrontal cortex (OFC) are activated by reward-related tasks and identified as key nodes of the brain circuit that underlie reward processing. We aimed to investigate the relation between NAc-OFC structural and functional connectivity in preschool children, as well as associations with future reward sensitivity and executive function. We showed that NAc-OFC structural and functional connectivity were not significantly associated in preschool children, but both independently predicted sensitivity to reward in males in a left-lateralized manner. Moreover, significant NAc-OFC structure-function coupling was only found in individuals who performed poorly on executive function tasks in later childhood, but not in the middle- and high-performing groups. As structure-function coupling is proposed to measure functional specialization, this finding suggests premature functional specialization within the reward network, which may impede dynamic communication with other regions, affects executive function development. Our study also highlights the utility of multimodal imaging data integration when studying the effects of reward network functional flexibility in the preschool age, a critical period in brain and executive function development.

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Functional connectivity is not tethered to structural connectivity in preschool age.

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Higher degree of SC-FC coupling reflects lower plasticity in early childhood.

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Gender differences in reward sensitivity were present as early as in preschool age.

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Early reward network SC-FC coupling affects later executive function.

Alpha Power in the Cingulate Cortex reflects Accumulated Winnings During Gambling in Humans

When making bets one's level of attention determines how much they may win. The cingulate cortex is a brain region associated with attention and may influence behaviors during gambling. With data gathered from the cingulate cortex in humans implanted with depth electrodes for clinical purposes while performing a gambling task of high card, we determine a relationship between neural correlates of attention and accumulated winnings. Specifically, we analyze how changes in alpha power (8-12 Hz) in the CC relate to accumulated winnings. We compared three subjects with different betting strategies: Reflexive (betting low on cards 2, 4, and 6), Logical (varying how they bet on card 6), and Illogical (betting randomly on all cards). We found that alpha power encodes attention in the cingulate cortex and relates to their accumulated winnings, especially in the illogical subject who had the least winning.

Association of increased abdominal adiposity at birth with altered ventral caudate microstructure

BACKGROUND

Neonatal adiposity is associated with a higher risk of obesity and cardiometabolic risk factors in later life. It is however unknown if central food intake regulating networks in the ventral striatum are altered with in-utero abdominal growth, indexed by neonatal adiposity in our current study. We aim to examine the relationship between striatal microstructure and abdominal adipose tissue compartments (AATCs) in Asian neonates from the Growing Up in Singapore Toward healthy Outcomes mother-offspring cohort.

STUDY DESIGN

About 109 neonates were included in this study. Magnetic resonance imaging (MRI) was performed for the brain and abdominal regions between 5 to 17 days of life. Diffusion-weighted imaging of the brain was performed for the derivation of caudate and putamen fractional anisotropy (FA). Abdominal imaging was performed to quantify AATCs namely superficial subcutaneous adipose tissue (sSAT), deep subcutaneous adipose tissue (dSAT), and internal adipose tissue (IAT). Absolute and percentage adipose tissue of total abdominal volume (TAV) were calculated.

RESULTS

We showed that AATCs at birth were significantly associated with increased FA in bilateral ventral caudate heads which are part of the ventral striatum (sSAT: β_left = 0.56, p < 0.001; β_right = 0.65, p < 0.001, dSAT: β_left = 0.43, p < 0.001; β_right = 0.52, p < 0.001, IAT: β_left = 0.30, p = 0.005; β_right = 0.32, p = 0.002) in neonates with low birth weights adjusted for gestational age.

CONCLUSIONS

Our study provides preliminary evidence of a potential relationship between neonatal adiposity and in-utero programming of the ventral striatum, a brain structure that governs feeding behavior.

Differential functional connectivity underlying asymmetric reward-related activity in human and nonhuman primates

The orbitofrontal cortex (OFC) is a key brain region involved in complex cognitive functions such as reward processing and decision making. Neuroimaging studies have reported unilateral OFC response to reward-related variables; however, those studies rarely discussed this observation. Nevertheless, some lesion studies suggest that the left and right OFC contribute differently to cognitive processes. We hypothesized that the OFC asymmetrical response to reward could reflect underlying hemispherical difference in OFC functional connectivity. Using resting-state and reward-related functional MRI data from humans and from rhesus macaques, we first identified an asymmetrical response of the lateral OFC to reward in both species. Crucially, the subregion showing the highest reward-related asymmetry (RRA) overlapped with the region showing the highest functional connectivity asymmetry (FCA). Furthermore, the two types of asymmetries were found to be significantly correlated across individuals. In both species, the right lateral OFC was more connected to the default mode network compared to the left lateral OFC. Altogether, our results suggest a functional specialization of the left and right lateral OFC in primates.

High Frequency Activity in the Orbital Frontal Cortex Modulates with Mismatched Expectations During Gambling in Humans

During gambling, humans often begin by making decisions based on expected rewards and expected risks. However, expectations may not match actual outcomes. As gamblers keep track of their performance, they may feel more or less lucky, which then influences future betting decisions. Studies have identified the orbitofrontal cortex (OFC) as a brain region that plays a significant role during risky decision making in humans. However, most human studies infer neural activation from functional magnetic resonance imaging (fMRI), which has a poor temporal resolution. In particular, fMRI cannot detect activity from neuronal populations in the OFC, which may encode specific information about how a subject reacts to mismatched outcomes. In this preliminary study, four human subjects participated in a gambling task while local field potentials (LFPs), captured at a millisecond resolution, were recorded from the OFC. We analyzed high-frequency activity (HFA: >70 Hz) in the LFPs, as HFA has been shown to correlate to activation of neuronal populations. In 3 out of 4 subjects, HFA in OFC modulated between matched and mismatched trials as soon as the outcome of each bet was revealed, with modulations occurring at different times and directions depending on the anatomical location within the OFC.

Correlates of Attention in the Cingulate Cortex During Gambling in Humans

People make decisions multiple times on a daily basis. However, some decisions are easier to make than others and perhaps require more attention to ensure a positive outcome. During gambling, one should attempt to compute the expected rewards and risks associated with decisions. Failing to allocate attention and neural resources to estimate these values can be costly, and in some cases can lead to bankruptcy. Alpha-band (8-12 Hz) oscillatory power in the brain is thought to reflect attention, but how this influences financial decision making is not well understood. Using local field potential recordings in nine human subjects performing a gambling task, we compared alpha-band power from the cingulate cortex (CC) during trials of low and high attention. We found that alpha-band power tended to be higher during a 2 second window after a fixation cue was shown in low attention trials.

Neural correlates and role of medication in reactive motor impulsivity in Tourette disorder

Abnormality of inhibitory control is considered to be a potential cognitive marker of tics in Tourette disorder (TD), attention deficit hyperactivity disorder (ADHD), and impulse control disorders. The results of the studies on inhibitory control in TD showed discrepant results. The aim of the present study was to assess reactive inhibitory control in adult TD patients with and without antipsychotic medication, and under emotional stimulation (visual images with positive, neutral and negative content). We assessed 31 unmedicated and 19 medicated TD patients and 26 matched healthy controls using the stop signal task as an index of reactive motor impulsivity and emotional stimulation with the aim to increase impulsivity. We performed a multimodal neuroimaging analysis using a regions of interest approach on grey matter signal, resting-state spontaneous brain activity and functional connectivity analyses. We found a higher reactive motor impulsivity in TD patients medicated with antipsychotics compared to unmedicated TD patients and controls. This propensity for reactive motor impulsivity in medicated TD patients was not influenced by ADHD or emotional stimulation. Neuroimaging results in medicated TD patients suggested that reactive motor impulsivity was underpinned by an increased grey matter signal from the right supplementary motor area and inferior frontal gyrus; decreased resting-state spontaneous activity of the left putamen; higher functional connectivity between the inferior frontal gyrus and the superior temporal gyri (bilaterally); lower functional connectivity between the cerebellum and the right subthalamic nucleus. Taken together, our data suggested (i) a deficit in reactive motor impulsivity in TD patients medicated with atypical antipsychotics that was unrelated to ADHD and (ii) that motor impulsivity was underpinned by structures and by functional connectivity of the fronto-temporo-basal ganglia-cerebellar pathway.

Infra-slow brain dynamics as a marker for cognitive function and decline

Functional magnetic resonance imaging (fMRI) enables measuring human brain activity, in vivo. Yet, the fMRI hemodynamic response unfolds over very slow timescales (<0.1-1 Hz), orders of magnitude slower than millisecond timescales of neural spiking. It is unclear, therefore, if slow dynamics as measured with fMRI are relevant for cognitive function. We investigated this question with a novel application of Gaussian Process Factor Analysis (GPFA) and machine learning to fMRI data. We analyzed slowly sampled (1.4 Hz) fMRI data from 1000 healthy human participants (Human Connectome Project database), and applied GPFA to reduce dimensionality and extract smooth latent dynamics. GPFA dimensions with slow (<1 Hz) characteristic timescales identified, with high accuracy (>95%), the specific task that each subject was performing inside the fMRI scanner. Moreover, functional connectivity between slow GPFA latents accurately predicted inter-individual differences in behavioral scores across a range of cognitive tasks. Finally, infra-slow (<0.1 Hz) latent dynamics predicted CDR (Clinical Dementia Rating) scores of individual patients, and identified patients with mild cognitive impairment (MCI) who would progress to develop Alzheimer's dementia (AD). Slow and infra-slow brain dynamics may be relevant for understanding the neural basis of cognitive function, in health and disease.