Separable amygdala activation patterns in the evaluations of robots.

Given the increasing presence of robots in everyday environments and the significant challenge posed by social interactions with robots, it is crucial to gain a deeper understanding into the social evaluations of robots. One potentially effective approach to comprehend the fundamental processes underlying controlled and automatic evaluations of robots is to probe brain response to different perception levels of robot-related stimuli. Here, we investigate controlled and automatic evaluations of robots based on brain responses during viewing of suprathreshold (duration: 200 ms) and subthreshold (duration: 17 ms) humanoid robot stimuli. Our behavioral analysis revealed that despite participants' self-reported positive attitudes, they held negative implicit attitudes toward humanoid robots. Neuroimaging analysis indicated that subthreshold presentation of humanoid robot stimuli elicited significant activation in the left amygdala, which was associated with negative implicit attitudes. Conversely, no significant left amygdala activation was observed during suprathreshold presentation. Following successful attenuation of negative attitudes, the left amygdala response to subthreshold presentation of humanoid robot stimuli decreased, and this decrease correlated positively with the reduction in negative attitudes. These findings provide evidence for separable patterns of amygdala activation between controlled and automatic processing of robots, suggesting that controlled evaluations may influence automatic evaluations of robots.

Impulsivity-related right superior frontal gyrus as a biomarker of internet gaming disorder.

Background: Internet gaming disorder (IGD) is a mental health issue that affects individuals worldwide. However, the lack of knowledge about the biomarkers associated with the development of IGD has restricted the diagnosis and treatment of this disorder. Aims: We aimed to reveal the biomarkers associated with the development of IGD through resting-state brain network analysis and provide clues for the diagnosis and treatment of IGD. Methods: Twenty-six patients with IGD, 23 excessive internet game users (EIUs) who recurrently played internet games but were not diagnosed with IGD and 29 healthy controls (HCs) performed delay discounting task (DDT) and Iowa gambling task (IGT). Resting-state functional magnetic resonance imaging (fMRI) data were also collected. Results: Patients with IGD exhibited significantly lower hubness in the right medial orbital part of the superior frontal gyrus (ORBsupmed) than both the EIU and the HC groups. Additionally, the hubness of the right ORBsupmed was found to be positively correlated with the highest excessive internet gaming degree during the past year in the EIU group but not the IGD group; this might be the protective mechanism that prevents EIUs from becoming addicted to internet games. Moreover, the hubness of the right ORBsupmed was found to be related to the treatment outcome of patients with IGD, with higher hubness of this region indicating better recovery when undergoing forced abstinence. Further modelling analysis of the DDT and IGT showed that patients with IGD displayed higher impulsivity during the decision-making process, and impulsivity-related parameters were negatively correlated with the hubness of right ORBsupmed. Conclusions: Our findings revealed that the impulsivity-related right ORBsupmed hubness could serve as a potential biomarker of IGD and provide clues for the diagnosis and treatment of IGD.

Reduced loss aversion in value-based decision-making and edge-centric functional connectivity in patients with internet gaming disorder.

Background and aims: Impaired value-based decision-making is a feature of substance and behavioral addictions. Loss aversion is a core of value-based decision-making and its alteration plays an important role in addiction. However, few studies explored it in internet gaming disorder patients (IGD). Methods: In this study, IGD patients (PIGD) and healthy controls (Con-PIGD) performed the Iowa gambling task (IGT), under functional magnetic resonance imaging (fMRI). We investigated group differences in loss aversion, brain functional networks of node-centric functional connectivity (nFC) and the overlapping community features of edge-centric functional connectivity (eFC) in IGT. Results: PIGD performed worse with lower average net score in IGT. The computational model results showed that PIGD significantly reduced loss aversion. There was no group difference in nFC. However, there were significant group differences in the overlapping community features of eFC1. Furthermore, in Con-PIGD, loss aversion was positively correlated with the edge community profile similarity of the edge2 between left IFG and right hippocampus at right caudate. This relationship was suppressed by response consistency3 in PIGD. In addition, reduced loss aversion was negatively correlated with the promoted bottom-to-up neuromodulation from the right hippocampus to the left IFG in PIGD. Discussion and conclusions: The reduced loss aversion in value-based decision making and their related edge-centric functional connectivity support that the IGD showed the same value-based decision-making deficit as the substance use and other behavioral addictive disorders. These findings may have important significance for understanding the definition and mechanism of IGD in the future.

Internet gaming disorder and tobacco use disorder share neural connectivity patterns between the subcortical and the motor network.

Internet gaming disorder (IGD) and tobacco use disorder (TUD) are globally common, non-substance-related disorders and substance-related disorders worldwide, respectively. Recognizing the commonalities between IGD and TUD will deepen understanding of the underlying mechanisms of addictive behavior and excessive online gaming. Using node strength, 141 resting-state data were collected in this study to compute network homogeneity. The participants included participants with IGD (PIGD: n = 34, male = 29, age: 15-25 years), participants with TUD (PTUD: n = 33, male = 33, age: 19-42 years), and matched healthy controls (control-for-IGD: n = 41, male = 38, age: 17-32 years; control-for-TUD: n = 33, age: 21-27 years). PIGD and PTUD exhibited common enhanced node strength between the subcortical and motor networks. Additionally, a common enhanced resting-state functional connectivity (RSFC) was found between the right thalamus and right postcentral gyrus in PIGD and PTUD. Node strength and RSFC were used to distinguish PIGD and PTUD from their respective healthy controls. Interestingly, models trained on PIGD versus controls could classify PTUD versus controls and vice versa, suggesting that these disorders share common neurological patterns. Enhanced connectivity may indicate a greater association between rewards and behaviors, inducing addiction behaviors without flexible and complex regulation. This study discovered that the connectivity between the subcortical and motor networks is a potential biological target for developing addiction treatment in the future.

Altered white matter functional network in nicotine addiction.

Nicotine addiction is a neuropsychiatric disorder with dysfunction in cortices as well as white matter (WM). The nature of the functional alterations in WM remains unclear. The small-world model can well characterize the structure and function of the human brain. In this study, we utilized the small-world model to compare the WM functional connectivity between 62 nicotine addiction participants (called the discovery sample) and 66 matched healthy controls (called the control sample). We also recruited an independent sample comprising 32 nicotine addicts (called the validation sample) for clinical application. The WM functional network data at the network level showed that the nicotine addiction group revealed decreased small-worldness index (σ) and normalized clustering coefficient (γ) compared with healthy controls. For clinical application, the small-world topology of WM functional connectivity could distinguish nicotine addicts from healthy controls (classification accuracy=0.59323, p = 0.0464). We trained abnormal small-world properties on the discovery sample to identify the severity of nicotine addiction, and the identification was successfully applied to the validation sample (classification accuracy=0.65625, p = 0.0106). Our neuroimaging findings provide direct evidence for WM functional changes in nicotine addiction and suggest that the small-world properties of WM function could be qualified as potential biomarkers in nicotine addiction.

Smoking related attention alteration in chronic obstructive pulmonary disease-smoking comorbidity.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a respiratory disease that causes a wide range of cognitive impairments. Although COPD-Smoking comorbidity is common, the relationship between smoking and cognitive function in COPD-Smoking comorbidity remains unclear. This study aimed to investigate the effect of smoking on cognitive function like attention in COPD-Smoking patients. METHODS: In this study, we used the Montreal Cognitive Assessment (MoCA) scale and resting-state functional magnetic resonance imaging (fMRI) to explore the effect of smoking on attention in patients with COPD. RESULTS: Behavioral analysis revealed that among patients with COPD the smokers had a shorter course of COPD and showed a worse attention performance than the non-smokers. Resting-state fMRI analysis revealed that among patients with COPD smokers showed lower regional homogeneity (ReHo) value of the fusiform gyrus than non-smokers. Importantly, the ReHo of the fusiform gyrus is positively associated with attention and mediates the effect of smoking on attention in COPD. CONCLUSIONS: In summary, our study provides behavioral and neurobiological evidence supporting the positive effect of smoking on attention in COPD. This may be helpful for understanding and treating COPD and even other diseases comorbid with smoking.

The orbitofrontal cortex represents advantageous choice in the Iowa gambling task.

A good-based model, the central neurobiological model of economic decision-making, proposes that the orbitofrontal cortex (OFC) represents binary choice outcome, that is, the chosen good. A good is defined by a group of determinants characterizing the conditions in which the commodity is offered, including commodity type, cost, risk, time delay, and ambiguity. Previous studies have found that the OFC represents the binary choice outcome in decision-making tasks involving commodity type, cost, risk, and delay. Real-life decisions are often complex and involve uncertainty, rewards, and penalties; however, whether the OFC represents binary choice outcomes in a complex decision-making situation, for example, Iowa gambling task (IGT), remains unclear. Here, we propose that the OFC represents binary choice outcome, that is, advantageous choice versus disadvantageous choice, in the IGT. We propose two hypotheses: first, the activity pattern in the human OFC represents an advantageous choice; and second, choice induces an OFC-related functional network. Using functional magnetic resonance imaging and advanced machine-learning tools, we found that the OFC represented an advantageous choice in the IGT. The OFC representation of advantageous choice was related to decision-making performance. Choice modulated the functional connectivity between the OFC and the superior medial gyrus. In conclusion, the OFC represents an advantageous choice during the IGT. In the framework of a good-based model, the results extend the role of the OFC to complex decision-making situation when making a binary choice.

Computed Tomography Radiomics-Based Prediction of Microvascular Invasion in Hepatocellular Carcinoma.

Background: Due to the high recurrence rate in hepatocellular carcinoma (HCC) after resection, preoperative prognostic prediction of HCC is important for appropriate patient management. Exploring and developing preoperative diagnostic methods has great clinical value in treating patients with HCC. This study sought to develop and evaluate a novel combined clinical predictive model based on standard triphasic computed tomography (CT) to discriminate microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Methods: The preoperative findings of 82 patients with HCC, including conventional clinical factors, CT imaging findings, and CT texture analysis (TA), were analyzed retrospectively. All included cases were divided into MVI-negative (n = 33; no MVI) and MVI-positive (n = 49; low or high risk of MVI) groups. TA parameters were extracted from non-enhanced, arterial, portal venous, and equilibrium phase images and subsequently calculated using the Artificial Intelligence Kit. After statistical analyses, a clinical model comprising conventional clinical and CT image risk factors, radiomics signature models, and a novel combined model (fused radiomic signature) was constructed. The area under the curve (AUC) of the receiver operating characteristics (ROC) curve was used to assess the performance of the various models in discriminating MVI. Results: We found that tumor diameter and pathological grade were effective clinical predictors in clinical model and 12 radiomics features were effective for MVI prediction of each CT phase. The AUCs of the clinical, plain, artery, venous, and delay models were 0.77 (95% CI: 0.67-0.88), 0.75 (95% CI: 0.64-0.87), 0.79 (95% CI: 0.69-0.89), 0.73 (95% CI: 0.61-0.85), and 0.80 (95% CI: 0.70-0.91), respectively. The novel combined model exhibited the best performance, with an AUC of 0.83 (95% CI: 0.74-0.93). Conclusions: Models derived from triphasic CT can preoperatively predict MVI in patients with HCC. Of the models tested here, the novel combined model was most predictive and could become a useful tool to guide subsequent personalized treatment of HCC.

Brain morphology, harm avoidance, and the severity of excessive internet use.

As the previous studies have mainly focused on the reward system and the corresponding brain regions, the relationship between brain morphology and excessive internet use (EIU) were not clear; the purpose of the study was to investigate if the brain regions other than the reward system were associated with EIU. Data were acquired from 131 excessive internet users. Psychological measures included internet use, life quality, personality, mental illness symptoms, impulsivity, and thought suppression. The brain was scanned with 3T magnetic resonance imaging (MRI) and six types of brain morphological indexes were calculated. Lasso regression methods were used to select the predictors. Stepwise linear regression methods were used to build the models and verify the model. The variables remaining in the model were left precentral (curve), left superior temporal (surface area), right cuneus (folding index), right rostral anterior cingulate (folding index), and harm avoidance. The independent variable was the EIU score of the worst week in the past year. The study found that the brain morphological indexes other than the reward system, including the left precentral (curve), the left superior temporal (surface area), the right cuneus (folding index), and the right rostral anterior cingulate (folding index), can predict the severity of EIU, suggesting an extensive change in the brain. In this study, a whole-brain data analysis was conducted and it was concluded that the changes in certain brain regions were more predictive than the reward system and psychological measures or more important for EIU.

A role of the lateral prefrontal cortex in the congruency sequence effect revealed by transcranial direct current stimulation.

Congruency effect is the increase in response time when relevant and irrelevant cues indicate incongruent rather than congruent responses. The congruency effect is smaller in the trial after an incongruent trial than after a congruent trial: this difference is known as the congruency sequence effect (CSE). Psychophysical and neural studies have suggested that the lateral prefrontal cortex (LPFC) and the medial prefrontal cortex are associated with the CSE. In the present study, we applied anodal and cathodal transcranial direct current stimulation, which is thought to result in excitation and inhibition, respectively, on the LPFC, while human participants were performing a flanker task. We found that the CSE was increased under cathodal stimulation (inhibition) of the LPFC. Moreover, the LPFC stimulation modulated the congruency effect after a congruent trial. Further analyses suggested that the results cannot be explained by any of the currently prevailing hypotheses of the CSE, including the conflict monitoring hypothesis, feature integration hypothesis, and temporal learning account. Based on our findings, we propose that a new distinct mechanism might be involved in the CSE. Specifically, the LPFC might contribute to the CSE by maintaining the attention to the task-relevant information, which is an endogenous goal-oriented function and reduces the carry-over of the task-irrelevant information after a congruent trial.

High Gamma and Beta Temporal Interference Stimulation in the Human Motor Cortex Improves Motor Functions.

Background: Temporal interference (TI) stimulation is a new technique of non-invasive brain stimulation. Envelope-modulated waveforms with two high-frequency carriers can activate neurons in target brain regions without stimulating the overlying cortex, which has been validated in mouse brains. However, whether TI stimulation can work on the human brain has not been elucidated. Objective: To assess the effectiveness of the envelope-modulated waveform of TI stimulation on the human primary motor cortex (M1). Methods: Participants attended three sessions of 30-min TI stimulation during a random reaction time task (RRTT) or a serial reaction time task (SRTT). Motor cortex excitability was measured before and after TI stimulation. Results: In the RRTT experiment, only 70 Hz TI stimulation had a promoting effect on the reaction time (RT) performance and excitability of the motor cortex compared to sham stimulation. Meanwhile, compared with the sham condition, only 20 Hz TI stimulation significantly facilitated motor learning in the SRTT experiment, which was significantly positively correlated with the increase in motor evoked potential. Conclusion: These results indicate that the envelope-modulated waveform of TI stimulation has a significant promoting effect on human motor functions, experimentally suggesting the effectiveness of TI stimulation in humans for the first time and paving the way for further explorations.

Transforming brain signals related to value evaluation and self-control into behavioral choices.

The processes involved in value evaluation and self-control are critical when making behavioral choices. However, the evidence linking these two types of processes to behavioral choices in intertemporal decision-making remains elusive. As the ventromedial prefrontal cortex (vmPFC), striatum, and dorsolateral prefrontal cortex (dlPFC) have been associated with these two processes, we focused on these three regions. We employed functional magnetic resonance imaging during a delayed discounting task (DDT) using a relatively large sample size, three independent samples. We evaluated how much information about a specific choice could be decoded from local patterns in each brain area using multivoxel pattern analysis (MVPA). To investigate the relationship between the dlPFC and vmPFC/striatum regions, we performed a psychophysiological interaction (PPI) analysis. In Experiment I, we found that the vmPFC and dlPFC, but not the striatum, could determine choices in healthy participants. Furthermore, we found that the dlPFC showed significant functional connectivity with the vmPFC, but not the striatum, when making decisions. These results could be replicated in Experiment II with an independent sample of healthy participants. In Experiment III, the choice-decoding accuracy in the vmPFC and dlPFC was lower in patients with addiction (smokers and participants with Internet gaming disorder) than in healthy participants, and decoding accuracy in the dlPFC was related to impulsivity in addicts. Taken together, our findings may provide neural evidence supporting the hypothesis that value evaluation and self-control processes both guide the intertemporal choices, and might provide potential neural targets for the diagnosis and treatment of impulsivity-related brain disorders.

Chronic nicotine exposure impairs uncertainty modulation on reinforcement learning in anterior cingulate cortex and serotonin system.

Deficits in the computational processes of reinforcement learning have been suggested to underlie addiction. Additionally, environmental uncertainty, which is encoded in the anterior cingulate cortex (ACC), modulates reward prediction errors (RPEs) during reinforcement learning and exacerbates addiction. The present study tested whether and how the ACC would have an essential role in drug addiction by failing to use uncertainty to modulate the RPEs during reinforcement learning. In Experiment I, we found that the ACC/medial prefrontal cortex (MPFC) did not modulate RPE learning according to uncertainty in smokers. The effect of uncertainty × RPE in the ACC/MPFC was correlated with the learning rate of RPEs and the duration of nicotine use. Experiment II demonstrated that serotonin, but not dopamine, receptor mRNA expression significantly decreased in the ACC of the nicotine exposed compared to the control rats. Furthermore, there was a positive correlation between learning rate and serotonin receptor mRNA expression in the ACC. Therefore, all present results suggest that impairments in uncertainty modulation in the ACC disrupt reinforcement learning processes in chronic nicotine users and contribute to maladaptive decision-making. These findings support interventions for pathological decision-making in drug addiction that strongly focus on the serotonin system in ACC.

Neural substrates of updating the prediction through prediction error during decision making.

Learning of prediction error (PE), including reward PE and risk PE, is crucial for updating the prediction in reinforcement learning (RL). Neurobiological and computational models of RL have reported extensive brain activations related to PE. However, the occurrence of PE does not necessarily predict updating the prediction, e.g., in a probability-known event. Therefore, the brain regions specifically engaged in updating the prediction remain unknown. Here, we conducted two functional magnetic resonance imaging (fMRI) experiments, the probability-unknown Iowa Gambling Task (IGT) and the probability-known risk decision task (RDT). Behavioral analyses confirmed that PEs occurred in both tasks but were only used for updating the prediction in the IGT. By comparing PE-related brain activations between the two tasks, we found that the rostral anterior cingulate cortex/ventral medial prefrontal cortex (rACC/vmPFC) and the posterior cingulate cortex (PCC) activated only during the IGT and were related to both reward and risk PE. Moreover, the responses in the rACC/vmPFC and the PCC were modulated by uncertainty and were associated with reward prediction-related brain regions. Electric brain stimulation over these regions lowered the performance in the IGT but not in the RDT. Our findings of a distributed neural circuit of PE processing suggest that the rACC/vmPFC and the PCC play a key role in updating the prediction through PE processing during decision making.

Resting-state functional connectivity between the dorsal anterior cingulate cortex and thalamus is associated with risky decision-making in nicotine addicts.

Nicotine addiction is associated with risky behaviors and abnormalities in local brain areas related to risky decision-making such as the dorsal anterior cingulate cortex (dACC), anterior insula (AI), and thalamus. Although these brain abnormalities are anatomically separated, they may in fact belong to one neural network. However, it is unclear whether circuit-level abnormalities lead to risky decision-making in smokers. In the current study, we used task-based functional magnetic resonance imaging (fMRI) and examined resting-state functional connectivity (RSFC) to study how connectivity between the dACC, insula, and thalamus influence risky decision-making in nicotine addicts. We found that an increase in risky decision-making was associated with stronger nicotine dependence and stronger RSFC of the dACC-rAI (right AI), the dACC-thalamus, the dACC-lAI (left AI), and the rAI-lAI, but that risky decision-making was not associated with risk level-related activation. Furthermore, the severity of nicotine dependence positively correlated with RSFC of the dACC-thalamus but was not associated with risk level-related activation. Importantly, the dACC-thalamus coupling fully mediated the effect of nicotine-dependent severity on risky decision-making. These results suggest that circuit-level connectivity may be a critical neural link between risky decision-making and severity of nicotine dependence in smokers.

Novelty seeking is related to individual risk preference and brain activation associated with risk prediction during decision making.

Novelty seeking (NS) is a personality trait reflecting excitement in response to novel stimuli. High NS is usually a predictor of risky behaviour such as drug abuse. However, the relationships between NS and risk-related cognitive processes, including individual risk preference and the brain activation associated with risk prediction, remain elusive. In this fMRI study, participants completed the Tridimensional Personality Questionnaire to measure NS and performed a probabilistic decision making task. Using a mathematical model, we estimated individual risk preference. Brain regions associated with risk prediction were determined via fMRI. The NS score showed a positive correlation with risk preference and a negative correlation with the activation elicited by risk prediction in the right posterior insula (r-PI), left anterior insula (l-AI), right striatum (r-striatum) and supplementary motor area (SMA). Within these brain regions, only the activation associated with risk prediction in the r-PI showed a correlation with NS after controlling for the effect of risk preference. Resting-state functional connectivity between the r-PI and r-striatum/l-AI was negatively correlated with NS. Our results suggest that high NS may be associated with less aversion to risk and that the r-PI plays an important role in relating risk prediction to NS.

Cerebral activity to opposite-sex voices reflected by event-related potentials.

Human voice is a gender discriminating cue and is important to mate selection. This study employed electrophysiological recordings to examine whether there is specific cerebral activity when presented with opposite-sex voices as compared to same-sex voices. Male voices and female voices were pseudo-randomly presented to male and female participants. In Experiment 1, participants were instructed to determine the gender of each voice. A late positivity (LP) response around 750 ms after voice onset was elicited by opposite-sex voices, as reflected by a positive deflection of the ERP to opposite-sex voices than that to same-sex voices. This LP response was prominent around parieto-occipital recording sites, and it suggests an opposite-sex specific process, which may reflect emotion- and/or reward-related cerebral activity. In Experiment 2, participants were instructed to press a key when hearing a non-voice pure tone and not give any response when they heard voice stimuli. In this task, no difference were found between the ERP to same-sex voices and that to opposite-sex voices, suggesting that the cerebral activity to opposite-sex voices may disappear without gender-related attention. These results provide significant implications on cognitive mechanisms with regard to opposite-sex specific voice processing.