Neural Correlates of Evidence and Urgency During Human Perceptual Decision-Making in Dynamically Changing Conditions

Differences in Anatomical Structures and Resting-State Brain Networks Between Elite Wrestlers and Handball Athletes

BACKGROUND/OBJECTIVES

Advancements in biomedical imaging technologies over the past few decades have made it increasingly possible to measure the long-term effects of exercise on the central nervous system. This study aims to compare the brain morphology and functional connectivity of wrestlers and handball players, exploring sport-specific neural adaptations.

METHODS

Here, we examined 26 elite male athletes (13 wrestlers and 13 handball players) using anatomical and resting-state functional magnetic resonance imaging (fMRI) measurements. Connectivity maps are derived using the seed-based correlation analysis of resting-state fMRI, while voxel-based morphometry (VBM) is employed to identify anatomical differences. Additionally, the cortical thickness and global volumetric values of the segmented images are examined to determine the distinctions between elite wrestlers and handball players using non-parametric statistical tests.

RESULTS

Wrestlers exhibited greater grey matter volume (GMV) in the right middle temporal gyrus, left middle frontal gyrus, and right posterior cingulate gyrus (uncorr., p < 0.001). On the other hand, wrestlers showed increased functional connectivity in the left superior temporal gyrus, left parahippocampal gyrus, the left anterior orbital gyrus, and right superior frontal gyrus-medial frontal region (P(FWE) < 0.05). In addition, wrestlers showed greater cortical thickness in several brain regions.

CONCLUSIONS

The increased GMV, cortical thickness, and functional connectivity observed in wrestlers highlight the presence of sport-specific neural adaptations. While this research provides valuable insights into the neuroplastic effects of various athletic disciplines, further studies involving additional sports and control groups are needed for a more comprehensive understanding.

The role of human intraparietal sulcus in evidence accumulation revealed by EEG and model-informed fMRI: IPS accumulates evidence during decision-making

Sequential sampling models propose that the repeated sampling of sensory information is a fundamental component of perceptual decision-making. Electroencephalographic investigations in humans have demonstrated motor-independent representations of evidence accumulation, but such observations have seldom been made in neuroimaging studies exploring the neuroanatomical origins of evidence accumulation. Here, we aimed to reveal the neuroanatomical locus of sensory evidence accumulation in the human brain by regressing an electrophysiological marker of evidence accumulation (centroparietal positivity, CPP) against changes in blood oxygen level-dependent (BOLD) signal during perceptual decision-making. Our cross-modal imaging approach revealed a cluster within left intraparietal sulcus (IPS), located within putative lateral intraparietal area (region hIP3), for which BOLD signals scaled in relation to the slope of the CPP. Furthermore, the drift rate parameter of a drift diffusion model parametrically modulated BOLD activity within an overlapping region of left IPS. In contrast, parametric modulation by reaction time revealed a distributed fronto-parietal network, demonstrating the utility of our approach for isolating a discrete neuroanatomical locus of evidence accumulation. Together, our findings provide strong support for intraparietal sulcus involvement in the accumulation of sensory evidence during human perceptual decision-making.

Prioritized neural processing of social threats during perceptual decision-making

Emotional signals, notably those signaling threat, benefit from prioritized processing in the human brain. Yet, it remains unclear whether perceptual decisions about the emotional, threat-related aspects of stimuli involve specific or similar neural computations compared to decisions about their non-threatening/non-emotional components. We developed a novel behavioral paradigm in which participants performed two different detection tasks (emotion vs. color) on the same, two-dimensional visual stimuli. First, electroencephalographic (EEG) activity in a cluster of central electrodes reflected the amount of perceptual evidence around 100 ms following stimulus onset, when the decision concerned emotion, not color. Second, participants' choice could be predicted earlier for emotion (240 ms) than for color (380 ms) by the mu (10 Hz) rhythm, which reflects motor preparation. Taken together, these findings indicate that perceptual decisions about threat-signaling dimensions of facial displays are associated with prioritized neural coding in action-related brain regions, supporting the motivational value of socially relevant signals.

EEG correlates to perceived urgency elicited by vibration stimulation of the upper body

Conveying information effectively while minimizing user distraction is critical to human-computer interaction. As the proliferation of audio-visual communication pushes human information processing capabilities to the limit, researchers are turning their attention to haptic interfaces. Haptic feedback has the potential to create a desirable sense of urgency that allows users to selectively focus on events/tasks or process presented information with minimal distraction or annoyance. There is a growing interest in understanding the neural mechanisms associated with haptic stimulation. In this study, we aim to investigate the EEG correlates associated with the perceived urgency elicited by vibration stimuli on the upper body using a haptic vest. A total of 31 participants enrolled in this experiment and were exposed to three conditions: no vibration pattern (NVP), urgent vibration pattern (UVP), and very urgent vibration pattern (VUVP). Through self-reporting, participants confirmed that the vibration patterns elicited significantly different levels of perceived urgency (Friedman test, Holm-Bonferroni correction, p < 0.01). Furthermore, neural analysis revealed that the power spectral density of the delta, theta, and alpha frequency bands in the middle central area (C1, Cz, and C2) significantly increased for the UVP and VUVP conditions as compared to the NVP condition (One-way ANOVA test, Holm-Bonferroni correction, p < 0.01). While the perceptual experience of haptic-induced urgency is well studied with self-reporting and behavioral evidence, this is the first effort to evaluate the neural correlates to haptic-induced urgency using EEG. Further research is warranted to identify unique correlates to the cognitive processes associated with urgency from sensory feedback correlates.

Boosting Serotonin Increases Information Gathering by Reducing Subjective Cognitive Costs

Serotonin is implicated in the valuation of aversive costs, such as delay or physical effort. However, its role in governing sensitivity to cognitive effort, for example, deliberation costs during information gathering, is unclear. We show that treatment with a serotonergic antidepressant in healthy human individuals of either sex enhances a willingness to gather information when trying to maximize reward. Using computational modeling, we show this arises from a diminished sensitivity to subjective deliberation costs during the sampling process. This result is consistent with the notion that serotonin alleviates sensitivity to aversive costs in a domain-general fashion, with implications for its potential contribution to a positive impact on motivational deficits in psychiatric disorders.SIGNIFICANCE STATEMENT Gathering information about the world is essential for successfully navigating it. However, sampling information is costly, and we need to balance between gathering too little and too much information. The neurocomputational mechanisms underlying this arbitration between a putative gain, such as reward, and the associated costs, such as allocation of cognitive resources, remain unclear. In this study, we show that week-long daily treatment with a serotonergic antidepressant enhances a willingness to gather information when trying to maximize reward. Computational modeling indicates this arises from a reduced perception of aversive costs, rendering information gathering less cognitively effortful. This finding points to a candidate mechanism by which serotonergic treatment might help alleviate motivational deficits in a range of mental illnesses.

Pupillary dynamics reflect the impact of temporal expectation on detection strategy

Everyday life's perceptual decision-making is informed by experience. In particular, temporal expectation can ease the detection of relevant events in noisy sensory streams. Here, we investigated if humans can extract hidden temporal cues from the occurrences of probabilistic targets and utilize them to inform target detection in a complex acoustic stream. To understand what neural mechanisms implement temporal expectation influence on decision-making, we used pupillometry as a proxy for underlying neuromodulatory activity. We found that participants' detection strategy was influenced by the hidden temporal context and correlated with sound-evoked pupil dilation. A model of urgency fitted on false alarms predicted detection reaction time. Altogether, these findings suggest that temporal expectation informs decision-making and could be implemented through neuromodulatory-mediated urgency signals.

Multivariate analysis differentiates intertemporal choices in both value and cognitive control network

Choices between immediate smaller reward and long-term larger reward are referred to as intertemporal choice. Numerous functional magnetic resonance imaging (fMRI) studies have investigated the neural substrates of intertemporal choice via conventional univariate analytical approaches, revealing dissociable activations of decisions involving immediately available rewards and decisions involving delayed rewards in value network. With the help of multivariate analyses, which is more sensitive for evaluating information encoded in spatially distributed patterns, we showed that fMRI activity patterns represent viable signatures of intertemporal choice, as well as individual differences while controlling for age. Notably, in addition to value network, regions from cognitive control network play prominent roles in differentiating between different intertemporal choices as well as individuals with distinct discount rates. These findings provide clear evidence that substantiates the important role of value and cognitive control networks in the neural representation of one's intertemporal decisions.

Investigation of Involvement between Specific Brain Regions and Evaluation Criteria Elements in a Two-Selections Task

It is essential to understand the neural mechanisms underlying human decision-making. Several studies using traditional analysis have attempted to explain the neural mechanisms associated with decision-making based on abstract rewards. However, brain-decoding research that utilizes the multivoxel pattern analysis (MVPA) method, especially research focusing on decision-making, remains limited. In brain analysis, decoding strategies for multivoxels are required for various decision-making evaluation criteria. This is because in daily life, the human decision-making process makes use of many evaluation criteria. In the present study, we investigated the representation of evaluation criterion categories in a decision-making process using functional magnetic resonance imaging and MVPA. Participants performed a decision-making task that involved choosing a smartphone by referring to four types of evaluation criteria. The regions of interest (ROIs) were the ventromedial prefrontal cortex (vmPFC), nucleus accumbens (NAcc), and insula. Each combination of the four evaluation criteria was analyzed based on a binary classification using MVPA. From the binary classification accuracy obtained from MVPA, the regions that reflected differences in the evaluation criteria among the ROIs were evaluated. The results of the binary classification in the vmPFC and NAcc indicated that these regions can express evaluation criteria in decision-making processes.

Do sparse brain activity patterns underlie human cognition?

Accumulating multivariate pattern analysis (MVPA) results from fMRI studies suggest that information is represented in fingerprint patterns of activations and deactivations during perception, emotions, and cognition. We postulate that these fingerprint patterns might reflect neuronal-population level sparse code documented in two-photon calcium imaging studies in animal models, i.e., information represented in specific and reproducible ensembles of a few percent of active neurons amidst widespread inhibition in neural populations. We suggest that such representations constitute a fundamental organizational principle via interacting across multiple levels of brain hierarchy, thus giving rise to perception, emotions, and cognition.

Dorsal striatum coding for the timely execution of action sequences

The automatic initiation of actions can be highly functional. But occasionally these actions cannot be withheld and are released at inappropriate times, impulsively. Striatal activity has been shown to participate in the timing of action sequence initiation and it has been linked to impulsivity. Using a self-initiated task, we trained adult male rats to withhold a rewarded action sequence until a waiting time interval has elapsed. By analyzing neuronal activity we show that the striatal response preceding the initiation of the learned sequence is strongly modulated by the time subjects wait before eliciting the sequence. Interestingly, the modulation is steeper in adolescent rats, which show a strong prevalence of impulsive responses compared to adults. We hypothesize this anticipatory striatal activity reflects the animals’ subjective reward expectation, based on the elapsed waiting time, while the steeper waiting modulation in adolescence reflects age-related differences in temporal discounting, internal urgency states, or explore–exploit balance.

Magnitude-sensitivity: rethinking decision-making

Magnitude-sensitivity refers to the result that performance in decision-making, across domains and organisms, is affected by the total value of the possible alternatives. This simple result offers a window into fundamental issues in decision-making and has led to a reconsideration of ecological decision-making, prominent computational models of decision-making, and optimal decision-making. Moreover, magnitude-sensitivity has inspired the design of new robotic systems that exploit natural solutions and apply optimal decision-making policies. In this article, we review the key theoretical and empirical results about magnitude-sensitivity and highlight the importance that this phenomenon has for the understanding of decision-making. Furthermore, we discuss open questions and ideas for future research.

Impaired sensory evidence accumulation and network function in Lewy body dementia

Deficits in attention underpin many of the cognitive and neuropsychiatric features of Lewy body dementia. These attention-related symptoms remain difficult to treat and there are many gaps in our understanding of their neurobiology. An improved understanding of attention-related impairments can be achieved via mathematical modelling approaches, which identify cognitive parameters to provide an intermediate level between observed behavioural data and its underlying neural correlate. Here, we apply this approach to identify the role of impaired sensory evidence accumulation in the attention deficits that characterize Lewy body dementia. In 31 people with Lewy body dementia (including 13 Parkinson's disease dementia and 18 dementia with Lewy bodies cases), 16 people with Alzheimer's disease, and 23 healthy controls, we administered an attention task whilst they underwent functional 3 T MRI. Using hierarchical Bayesian estimation of a drift-diffusion model, we decomposed task performance into drift rate and decision boundary parameters. We tested the hypothesis that the drift rate-a measure of the quality of sensory evidence accumulation-is specifically impaired in Lewy body dementia, compared to Alzheimer's disease. We further explored whether trial-by-trial variations in the drift rate related to activity within the default and dorsal attention networks, to determine whether altered activity in these networks was associated with slowed drift rates in Lewy body dementia. Our results revealed slower drift rates in the Lewy body dementia compared to the Alzheimer's disease group, whereas the patient groups were equivalent for their decision boundaries. The patient groups were reduced relative to controls for both parameters. This highlights sensory evidence accumulation deficits as a key feature that distinguishes attention impairments in Lewy body dementia, consistent with impaired ability to efficiently process information from the environment to guide behaviour. We also found that the drift rate was strongly related to activity in the dorsal attention network across all three groups, whereas the Lewy body dementia group showed a divergent relationship relative to the Alzheimer's disease and control groups for the default network, consistent with altered default network modulation being associated with impaired evidence accumulation. Together, our findings reveal impaired sensory evidence accumulation as a specific marker of attention problems in Lewy body dementia, which may relate to large-scale network abnormalities. By identifying impairments in a specific sub-process of attention, these findings will inform future exploratory and intervention studies that aim to understand and treat attention-related symptoms that are a key feature of Lewy body dementia.

Evidence and Urgency Related EEG Signals during Dynamic Decision-Making in Humans

A successful class of models link decision-making to brain signals by assuming that evidence accumulates to a decision threshold. These evidence accumulation models have identified neuronal activity that appears to reflect sensory evidence and decision variables that drive behavior. More recently, an additional evidence-independent and time-variant signal, called urgency, has been hypothesized to accelerate decisions in the face of insufficient evidence. However, most decision-making paradigms tested with fMRI or EEG in humans have not been designed to disentangle evidence accumulation from urgency. Here we use a face-morphing decision-making task in combination with EEG and a hierarchical Bayesian model to identify neural signals related to sensory and decision variables, and to test the urgency-gating model. Forty females and 34 males took part (mean age, 23.4 years). We find that an evoked potential time locked to the decision, the centroparietal positivity, reflects the decision variable from the computational model. We further show that the unfolding of this signal throughout the decision process best reflects the product of sensory evidence and an evidence-independent urgency signal. Urgency varied across subjects, suggesting that it may represent an individual trait. Our results show that it is possible to use EEG to distinguish neural signals related to sensory evidence accumulation, decision variables, and urgency. These mechanisms expose principles of cognitive function in general and may have applications to the study of pathologic decision-making such as in impulse control and addictive disorders.SIGNIFICANCE STATEMENT Perceptual decisions are often described by a class of models that assumes that sensory evidence accumulates gradually over time until a decision threshold is reached. In the present study, we demonstrate that an additional urgency signal impacts how decisions are formed. This endogenous signal encourages one to respond as time elapses. We found that neural decision signals measured by EEG reflect the product of sensory evidence and an evidence-independent urgency signal. A nuanced understanding of human decisions, and the neural mechanisms that support it, can improve decision-making in many situations and potentially ameliorate dysfunction when it has gone awry.