Functional brain networks involved in decision-making under certain and uncertain conditions

Insular and prelimbic cortices control behavioral accuracy and precision in a temporal decision-making task in rats

The anterior insular cortex (AIC) comprises a region of sensory integration. It appears to detect salient events in order to guide goal-directed behavior, code tracking errors, and estimate the passage of time. Temporal processing in the AIC may be instantiated by the integration of representations of interoception. Projections between the AIC and the medial prefrontal cortex (mPFC) - found both in rats and humans - also suggest a possible role for these structures in the integration of autonomic responses during ongoing behavior. Few studies, however, have investigated the role of AIC and mPFC in decision-making and time estimation tasks. Moreover, their findings are not consistent, so the relationship between temporal decision-making and those areas remains unclear. The present study employed bilateral inactivations to explore the role of AIC and prelimbic cortex (PL) in rats during a temporal decision-making task. In this task, two levers are available simultaneously (but only one is active), one predicting reinforcement after a short, and the other after a long-fixed interval. Optimal performance requires a switch from the short to the long lever after the short-fixed interval elapsed and no reinforcement was delivered. Switch behavior from the short to the long lever was dependent on AIC and PL. During AIC inactivation, switch latencies became more variable, while during PL inactivation switch latencies became both more variable and less accurate. These findings point to a dissociation between AIC and PL in temporal decision-making, suggesting that the AIC is important for temporal precision, and PL is important for both temporal accuracy and precision.

Functional dysconnectivity and microstructural impairment of the cortico-thalamo-cortical network in women with rheumatoid arthritis: A multimodal MRI study

Background

Cognitive deficits are common in rheumatoid arthritis (RA) patients, but the mechanisms remain unclear. We investigated the effective connectivity and structural alterations of the core brain regions in RA patients with cognitive impairment.

Methods

Twenty-four female patients with RA and twenty-four healthy controls were enrolled. We analyzed abnormal brain activity patterns using functional MRI during the Iowa gambling task (IGT) and core regions effective connectivity using dynamic causal model (DCM). Structural alterations of white matter volume (WMV) and gray matter volume (GMV) were detected using voxel-based morphometry (VBM).

Results

RA patients showed altered activation patterns of the cortico-thalamo-cortical network, increased coupling strength from the left ventromedial prefrontal gyrus to the anterior cingulate cortex (ACC), the ACC to the right thalamus, and decreased connectivity from the thalamus to left hippocampus. VBM structural analysis showed increased GMV in the bilateral orbital frontal gyrus, bilateral hippocampus and right putamen, and reduced GMV and WMV in the bilateral thalamus in RA patients. Right thalamic GMV and WMV were positively correlated with the right thalamus-to-hippocampus connective strength. Additionally, the bold signal, GMV and WMV of the right thalamus were positively correlated with cognitive performance (IGT score) in RA patients.

Conclusion

Results suggest a structural and functional deficiency in the cortico-thalamo-cortical network, which is characterized by increased ACC-to-thalamus strength and reduced thalamus-to-hippocampus coupling in RA patients. The cognitive dysfunction may be the result of compensatory measures against imbalanced cortico-thalamic-cortical coupling.

The parietal cortex has a causal role in ambiguity computations in humans

Humans often face the challenge of making decisions between ambiguous options. The level of ambiguity in decision-making has been linked to activity in the parietal cortex, but its exact computational role remains elusive. To test the hypothesis that the parietal cortex plays a causal role in computing ambiguous probabilities, we conducted consecutive fMRI and TMS-EEG studies. We found that participants assigned unknown probabilities to objective probabilities, elevating the uncertainty of their decisions. Parietal cortex activity correlated with the objective degree of ambiguity and with a process that underestimates the uncertainty during decision-making. Conversely, the midcingulate cortex (MCC) encodes prediction errors and increases its connectivity with the parietal cortex during outcome processing. Disruption of the parietal activity increased the uncertainty evaluation of the options, decreasing cingulate cortex oscillations during outcome evaluation and lateral frontal oscillations related to value ambiguous probability. These results provide evidence for a causal role of the parietal cortex in computing uncertainty during ambiguous decisions made by humans.

Resting-state network predicts the decision-making behaviors of the proposer during the ultimatum game

Objective. The decision-making behavior of the proposer is a key factor in achieving effective and equitable maintenance of social resources, particularly in economic interactions, and thus understanding the neurocognitive basis of the proposer's decision-making is a crucial issue. Yet the neural substrate of the proposer's decision behavior, especially from the resting-state network perspective, remains unclear.Approach. In this study, we investigated the relationship between the resting-state network and decision proposals and further established a multivariable model to predict the proposers' unfair offer rates in the ultimatum game.Main results.The results indicated the unfair offer rates of proposers are significantly related to the resting-state frontal-occipital and frontal-parietal connectivity in the delta band, as well as the network properties. And compared to the conservative decision group (low unfair offer rate), the risk decision group (high unfair offer rate) exhibited stronger resting-state long-range linkages. Finally, the established multivariable model did accurately predict the unfair offer rates of the proposers, along with a correlation coefficient of 0.466 between the actual and predicted behaviors.Significance. Together, these findings demonstrated that related resting-state frontal-occipital and frontal-parietal connectivity may serve as a dispositional indicator of the risky behaviors for the proposers and subsequently predict a highly complex decision-making behavior, which contributed to the development of artificial intelligence decision-making system with biological characteristics as well.

Event-related Potentials Corresponding to Decision-making Under Uncertain Conditions

BACKGROUND

Decision-making is essential to human functioning, and resolving uncertainty is an essential part of decision-making. Impaired decision-making is present in many pathological conditions, and identifying markers of decision-making under uncertainty will provide a measure of clinical impact in future studies of therapeutic intervention for impaired decision-making.

OBJECTIVE

To describe EEG event-related potentials (ERPs) correlating with decision-making under uncertain conditions when compared with certain conditions.

METHOD

We used a novel card-matching task based on the Wisconsin Card Sorting Test to describe the neural correlates of uncertainty, as measured by EEG, in a group of 27 neurotypical individuals. We evaluated 500-ms intervals in the 2 seconds after card presentation to identify ERPs that are associated with maximal uncertainty compared with maximal certainty.

RESULTS

After correcting for multiple comparisons, we identified an ERP in the 500-1000-ms time frame (certain > uncertain, max amplitude 12.73 µV, latency 914 ms) in the left posterior inferior region of the scalp. We also found a P300-like ERP in the left frontal and parietal regions in the 0-500-ms time frame when the individuals received correct versus incorrect feedback (incorrect feedback > correct feedback, max amplitude 1.625 µV, latency 339 ms).

CONCLUSION

We identified an ERP in the 500-1000-ms time frame (certain > uncertain) that may reflect the resolution of uncertainty, as well as a P300-like ERP when feedback is presented (incorrect feedback > correct feedback). These findings can be used in future studies to improve decision-making and resolve uncertainty on the described markers.

A Role for Uncertainty in the Neural Distinction Between Social and Nonsocial Thought

Neuroimaging research has identified a network of brain regions that is consistently more engaged when people think about the minds of other people than when they engage in nonsocial tasks. Activations in this "mentalizing network" are sometimes interpreted as evidence for the domain-specificity of cognitive processes supporting social thought. Here, we examine the alternative possibility that at least some activations in the mentalizing network may be explained by uncertainty. A reconsideration of findings from existing functional MRI studies in light of new data from independent raters suggests that (a) social tasks used in past studies have higher levels of uncertainty than their nonsocial comparison tasks and (b) activation in a key brain region associated with social cognition, the dorsomedial prefrontal cortex (DMPFC), may track with the degree of uncertainty surrounding both social and nonsocial inferences. These observations suggest that the preferential DMPFC response observed consistently in social scenarios may reflect the engagement of domain-general processes of uncertainty reduction, which points to avenues for future research into the core cognitive mechanisms supporting typical and atypical social thought.

Movement characteristics impact decision-making and vice versa

Previous studies suggest that humans are capable of coregulating the speed of decisions and movements if promoted by task incentives. It is unclear however whether such behavior is inherent to the process of translating decisional information into movements, beyond posing a valid strategy in some task contexts. Therefore, in a behavioral online study we imposed time constraints to either decision- or movement phases of a sensorimotor task, ensuring that coregulating decisions and movements was not promoted by task incentives. We found that participants indeed moved faster when fast decisions were promoted and decided faster when subsequent finger tapping movements had to be executed swiftly. These results were further supported by drift diffusion modelling and inspection of psychophysical kernels: Sensorimotor delays related to initiating the finger tapping sequence were shorter in fast-decision as compared to slow-decision blocks. Likewise, the decisional speed-accuracy tradeoff shifted in favor of faster decisions in fast-tapping as compared to slow-tapping blocks. These findings suggest that decisions not only impact movement characteristics, but that properties of movement impact the time taken to decide. We interpret these behavioral results in the context of embodied decision-making, whereby shared neural mechanisms may modulate decisions and movements in a joint fashion.

An EEG-Based Neuromarketing Approach for Analyzing the Preference of an Electric Car

This study evaluates consumer preference from the perspective of neuroscience when a choice is made among a number of cars, one of which is an electric car. Consumer neuroscience contributes to a systematic understanding of the underlying information processing and cognitions involved in choosing or preferring a product. This study aims to evaluate whether neural measures, which were implicitly extracted from brain activities, can be reliable or consistent with self-reported measures such as preference or liking. In an EEG-based experiment, the participants viewed images of automobiles and their specifications. Emotional and attentional stimuli and the participants' responses, in the form of decisions made, were meticulously distinguished and analyzed via signal processing techniques, statistical tests, and brain mapping tools. Long-range temporal correlations (LRTCs) were also calculated to investigate whether the preference of a product could affect the dynamic of neuronal fluctuations. Statistically significant spatiotemporal dynamical differences were then evaluated between those who select an electric car (which seemingly demands specific memory and long-term attention) and participants who choose other cars. The results showed increased PSD and central-parietal and central-frontal coherences at the alpha frequency band for those who selected the electric car. In addition, the findings showed the emergence of LRTCs or the ability of this group to integrate information over extended periods. Furthermore, the result of clustering subjects into two groups, using statistically significant discriminative EEG measures, was associated with the self-report data. The obtained results highlighted the promising role of intrinsically extracted measures on consumers' buying behavior.

Value-based cognition and drug dependency

Value-based decision-making is thought to play an important role in drug dependency. Achieving elevated levels of euphoria or ameliorating dysphoria/pain may motivate goal-directed drug consumption in both drug-naïve and long-time users. In other words, drugs become viewed as the preferred means of attaining a desired internal state. The bias towards choosing drugs may affect one's cognition. Observed biases in learning, attention and memory systems within the brain gradually focus one's cognitive functions towards drugs and related cues to the exclusion of other stimuli. In this narrative review, the effects of drug use on learning, attention and memory are discussed with a particular focus on changes across brain-wide functional networks and the subsequent impact on behaviour. These cognitive changes are then incorporated into the cycle of addiction, an established model outlining the transition from casual drug use to chronic dependency. If drug use results in the elevated salience of drugs and their cues, the studies highlighted in this review strongly suggest that this salience biases cognitive systems towards the motivated pursuit of addictive drugs. This bias is observed throughout the cycle of addiction, possibly contributing to the persistent hold that addictive drugs have over the dependent. Taken together, the excessive valuation of drugs as the preferred means of achieving a desired internal state affects more than just decision-making, but also learning, attentional and mnemonic systems. This eventually narrows the focus of one's thoughts towards the pursuit and consumption of addictive drugs.

Neural responses to rapidly selecting color names with different novelty

It is well known that different names of color can lead to distinct attractions to people. To study the neural mechanism underlying this phenomenon, an implicit association test task was designed for color names, in which participants were required to select the possible meanings of a Greek phrase from two color names (in Chinese). The behavioral results showed that the participants were more likely to select novel names for long Greek phrases and dates names for short Greek phrases. The EEG results showed that the mean amplitude of N1 was greater for selections of novel color names than selections of dates names for Greek phrases. Meanwhile, the mean amplitude of N3 for novel color names was more negative than that of dates color names. Significant interaction effect of N3 was also found for the four kinds of selections between Greek phrases and Chinese color names. Moreover, a frontal-positive and occipital-negative distribution for scalp topography of N1 was found, while the scalp topography of N3 was opposite as frontal-negative and occipital-positive distribution, suggesting the importance of visual cortex for perception of the color names and prefrontal cortex for integration and decision of selection. In summary, the results here indicated that colors with novel names could easily attract people's attention than colors with dates names, which might shed light on the usage of color names in real life.

Association of Amyloid-β Pathology with Decision Making and Scam Susceptibility

BACKGROUND

Recent findings suggest that poor decision making and increased scam susceptibility are harbingers of Alzheimer's disease (AD) dementia and may be among the earliest behavioral manifestations of pathologic cognitive aging. However, the degree to which poor decision making and scam susceptibility reflect accumulating Alzheimer's disease (AD) pathology remains unclear.

OBJECTIVE

To investigate the associations of AD pathology with decision making and scam susceptibility in older adults without dementia.

METHODS

Data came from 198 deceased participants without clinical dementia (mean age at death = 90 years; 69%women) from two ongoing studies of aging. All underwent annual clinical evaluations, completed assessments of healthcare and financial decision making and scam susceptibility, and brain donation. Neuropathologic evaluations quantified pathologic hallmarks of AD, amyloid-β and tau-tangles, Lewy body pathology, and TDP-43 proteinopathy.

RESULTS

In linear regression models adjusted for demographics, amyloid-β pathology was associated with lower decision making (estimate = -0.35; SE = 0.16, p = 0.03), particularly healthcare decision making (estimate = -0.20; SE = 0.09, p = 0.03), as well as greater scam susceptibility (estimate = 0.12; SE = 0.04, p = 0.003); tau-tangle pathology was not related. Further, TDP-43 pathology was associated with greater scam susceptibility (estimate = 0.10; SE = 0.04; p = 0.02).

CONCLUSION

Accumulating AD pathology, particularly amyloid-β, is associated with poor decision making and increased scam susceptibility among older persons without overt cognitive impairment. These findings provide compelling evidence that decision making and scam susceptibility are sensitive to the earliest pathological changes of AD.

The role of the medial prefrontal cortex in cognition, ageing and dementia

Humans require a plethora of higher cognitive skills to perform executive functions, such as reasoning, planning, language and social interactions, which are regulated predominantly by the prefrontal cortex. The prefrontal cortex comprises the lateral, medial and orbitofrontal regions. In higher primates, the lateral prefrontal cortex is further separated into the respective dorsal and ventral subregions. However, all these regions have variably been implicated in several fronto-subcortical circuits. Dysfunction of these circuits has been highlighted in vascular and other neurocognitive disorders. Recent advances suggest the medial prefrontal cortex plays an important regulatory role in numerous cognitive functions, including attention, inhibitory control, habit formation and working, spatial or long-term memory. The medial prefrontal cortex appears highly interconnected with subcortical regions (thalamus, amygdala and hippocampus) and exerts top-down executive control over various cognitive domains and stimuli. Much of our knowledge comes from rodent models using precise lesions and electrophysiology readouts from specific medial prefrontal cortex locations. Although, anatomical disparities of the rodent medial prefrontal cortex compared to the primate homologue are apparent, current rodent models have effectively implicated the medial prefrontal cortex as a neural substrate of cognitive decline within ageing and dementia. Human brain connectivity-based neuroimaging has demonstrated that large-scale medial prefrontal cortex networks, such as the default mode network, are equally important for cognition. However, there is little consensus on how medial prefrontal cortex functional connectivity specifically changes during brain pathological states. In context with previous work in rodents and non-human primates, we attempt to convey a consensus on the current understanding of the role of predominantly the medial prefrontal cortex and its functional connectivity measured by resting-state functional MRI in ageing associated disorders, including prodromal dementia states, Alzheimer's disease, post-ischaemic stroke, Parkinsonism and frontotemporal dementia. Previous cross-sectional studies suggest that medial prefrontal cortex functional connectivity abnormalities are consistently found in the default mode network across both ageing and neurocognitive disorders such as Alzheimer's disease and vascular cognitive impairment. Distinct disease-specific patterns of medial prefrontal cortex functional connectivity alterations within specific large-scale networks appear to consistently feature in the default mode network, whilst detrimental connectivity alterations are associated with cognitive impairments independently from structural pathological aberrations, such as grey matter atrophy. These disease-specific patterns of medial prefrontal cortex functional connectivity also precede structural pathological changes and may be driven by ageing-related vascular mechanisms. The default mode network supports utility as a potential biomarker and therapeutic target for dementia-associated conditions. Yet, these associations still require validation in longitudinal studies using larger sample sizes.

A Feature-Based Network Analysis and fMRI Meta-Analysis Reveal Three Distinct Types of Prosocial Decisions

Tasks that measure correlates of prosocial decision-making share one common feature: agents can make choices that increase the welfare of a beneficiary. However, prosocial decisions vary widely as a function of other task features. The diverse ways that prosociality is defined and the heterogeneity of prosocial decisions have created challenges for interpreting findings across studies and identifying their neural correlates. To overcome these challenges, we aimed to organize the prosocial decision-making task space of neuroimaging studies. We conducted a systematic search for studies in which participants made decisions to increase the welfare of others during functional magnetic resonance imaging. We identified shared and distinct features of these tasks and employed an unsupervised graph-based approach to assess how various forms of prosocial decision-making are related in terms of their low-level components (e.g. task features like potential cost to the agent or potential for reciprocity). Analyses uncovered three clusters of prosocial decisions, which we labeled as cooperation, equity and altruism. This feature-based representation of the task structure was supported by results of a neuroimaging meta-analysis that each type of prosocial decisions recruited diverging neural systems. Results clarify some of the existing heterogeneity in how prosociality is conceptualized and generate insight for future research and task paradigm development.

Decision making under ambiguity and risk in adolescent-onset schizophrenia

OBJECTIVE

Numerous studies have identified impaired decision making (DM) under both ambiguity and risk in adult patients with schizophrenia. However, the assessment of DM in patients with adolescent-onset schizophrenia (AOS) has been challenging as a result of the instability and heterogeneity of manifestations. The Iowa Gambling Task (IGT) and Game of Dice Task (GDT), which are frequently used to evaluate DM respectively under ambiguity and risk, are sensitive to adolescents and neuropsychiatric patients. Our research intended to examine the performance of DM in a relatively large sample of patients with AOS using the above-mentioned two tasks. We also aimed to take a closer look at the relationship between DM and symptom severity of schizophrenia.

METHODS

We compared the performance of DM in 71 patients with AOS and 53 well-matched healthy controls using IGT for DM under ambiguity and GDT for DM under risk through net scores, total scores and feedback ration. Neuropsychological tests were conducted in all participants. Clinical symptoms were evaluated by using Positive and Negative Syndrome Scale (PANSS) in 71 patients with AOS. Pearson's correlation revealed the relationship among total score of DM and clinical and neuropsychological data.

RESULTS

Compared to healthy controls, patients with AOS failed to show learning effect and had a significant difference on the 5th block in IGT and conducted more disadvantageous choices as well as exhibited worse negative feedback rate in GDT. Apart from DM impairment under risk, diminished DM abilities under ambiguity were found related to poor executive function in AOS in the present study.

CONCLUSIONS

Our findings unveiled the abnormal pattern of DM in AOS, mainly reflected under the risky condition, extending the knowledge on the performance of DM under ambiguity and risk in AOS. Inefficient DM under risk may account for the lagging impulse control and the combined effects of developmental disease. In addition, our study demonstrated that the performance on IGT was related to executive function in AOS.

Neurophysiological correlates of purchase decision-making

Economic decisions are characterized by their uncertainty and the lack of explicit feedback that indicates the correctness of decisions at the time they are made. Nevertheless, very little is known about the neural mechanisms involved in this process. Our study sought to identify the neurophysiological correlates of purchase decision-making in situations where the optimal purchase time is not known. EEG was recorded in 24 healthy subjects while they were performing a new experimental paradigm that simulates real economic decisions. At the time of price presentation, we found an increase in the P3 Event-Related Potential and induced theta and alpha oscillatory activity when participants chose to buy compared to when they decided to wait for a better price. These results reflect the engagement of attention and executive function in purchase decision-making and might help in the understanding of brain mechanisms underlying economic decisions in uncertain scenarios.

Alterations of Cerebral Hemodynamics and Network Properties Induced by Newsvendor Problem in the Human Prefrontal Cortex

While many publications have reported brain hemodynamic responses to decision-making under various conditions of risk, no inventory management scenarios, such as the newsvendor problem (NP), have been investigated in conjunction with neuroimaging. In this study, we hypothesized (I) that NP stimulates the dorsolateral prefrontal cortex (DLPFC) and the orbitofrontal cortex (OFC) joined with frontal polar area (FPA) significantly in the human brain, and (II) that local brain network properties are increased when a person transits from rest to the NP decision-making phase. A 77-channel functional near infrared spectroscopy (fNIRS) system with wide field-of-view (FOV) was employed to measure frontal cerebral hemodynamics in response to NP in 27 healthy human subjects. NP-induced changes in oxy-hemoglobin concentration, Δ[HbO], were investigated using a general linear model (GLM) and graph theory analysis (GTA). Significant activation induced by NP was shown in both DLPFC and OFC+FPA across all subjects. Specifically, higher risk NP with low-profit margins (LM) activated left-DLPFC but deactivated right-DLPFC in 14 subjects, while lower risk NP with high-profit margins (HM) stimulated both DLPFC and OFC+FPA in 13 subjects. The local efficiency, clustering coefficient, and path length of the network metrics were significantly enhanced under NP decision making. In summary, multi-channel fNIRS enabled us to identify DLPFC and OFC+FPA as key cortical regions of brain activations when subjects were making inventory-management risk decisions. We demonstrated that challenging NP resulted in the deactivation within right-DLPFC due to higher levels of stress. Also, local brain network properties were increased when a person transitioned from the rest phase to the NP decision-making phase.

The protective effect of daytime sleep on planning and risk-related decision-making in emerging adults

We assessed the effect of a daytime sleep opportunity on planning and risk-related decision-making in emerging adults using multiple neurobehavioral assessments. A total of 136 healthy emerging adults (20.0 ± 1.5 years), 65% female, performed the Risky-Gains Task and the Tower of London test twice. Between these assessments, they were randomized to either have a sleep opportunity monitored by polysomnography (Sleep group, n = 101) or to stay awake (Wake group, n = 35). During Test 2, in comparison to the Sleep group, the Wake group showed increased sleepiness, worse planning ability and more decrease in reaction times when selecting risky choices. Changes in Tower of London test steps used and Risky-Gains Task response time correlated with the number of central and frontal fast sleep spindles, respectively. These results indicate that among emerging adults who commonly have poor sleep patterns, a daytime sleep opportunity was related to better planning ability, better psychomotor vigilance and stable response speeds in risk-related decision-making. Changes in planning and risk-related decision-making correlated with the number of sleep spindles during the nap, supporting a specific role for sleep in modulating planning and potentially other higher-order cognitive functions.

Can neuromodulation techniques optimally exploit cerebello-thalamo-cortical circuit properties to enhance motor learning post-stroke?

Individuals post-stroke sustain motor deficits years after the stroke. Despite recent advancements in the applications of non-invasive brain stimulation techniques and Deep Brain Stimulation in humans, there is a lack of evidence supporting their use for rehabilitation after brain lesions. Non-invasive brain stimulation is already in use for treating motor deficits in individuals with Parkinson's disease and post-stroke. Deep Brain Stimulation has become an established treatment for individuals with movement disorders, such as Parkinson's disease, essential tremor, epilepsy, cerebral palsy and dystonia. It has also been utilized for the treatment of Tourette's syndrome, Alzheimer's disease and neuropsychiatric conditions such as obsessive-compulsive disorder, major depression and anorexia nervosa. There exists growing scientific knowledge from animal studies supporting the use of Deep Brain Stimulation to enhance motor recovery after brain damage. Nevertheless, these results are currently not applicable to humans. This review details the current literature supporting the use of these techniques to enhance motor recovery, both from human and animal studies, aiming to encourage development in this domain.