Task functional networks predict individual differences in the speed of emotional facial discrimination.

Every individual experiences negative emotions, such as fear and anger, significantly influencing how external information is perceived and processed. With the gradual rise in brain-behavior relationship studies, analyses investigating individual differences in negative emotion processing and a more objective measure such as the response time (RT) remain unexplored. This study aims to address this gap by establishing that the individual differences in the speed of negative facial emotion discrimination can be predicted from whole-brain functional connectivity when participants were performing a face discrimination task. Employing the connectome predictive modeling (CPM) framework, we demonstrated this in the young healthy adult group from the Human Connectome Project-Young Adults (HCP-YA) dataset and the healthy group of the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) dataset. We identified distinct network contributions in the adult and adolescent predictive models. The highest represented brain networks involved in the adult model predictions included representations from the motor, visual association, salience, and medial frontal networks. Conversely, the adolescent predictive models showed substantial contributions from the cerebellum-frontoparietal network interactions. Finally, we observed that despite the successful within-dataset prediction in healthy adults and adolescents, the predictive models failed in the cross-dataset generalization. In conclusion, our study shows that individual differences in the speed of emotional facial discrimination can be predicted in healthy adults and adolescent samples using their functional connectivity during negative facial emotion processing. Future research is needed in the derivation of more generalizable models.

Meta-analysis of experimental factors influencing single-pulse TMS effects on the early visual cortex.

Background: Single-pulse transcranial magnetic stimulation (spTMS) applied to the Early Visual Cortex (EVC) has demonstrated the ability to suppress the perception on visual targets, akin to the effect of visual masking. However, the reported spTMS suppression effects across various studies have displayed inconsistency. Objective: We aim to test if the heterogeneity of the spTMS effects can be attributable to variations in experimental factors. Methods: We conducted a meta-analysis using data collected from the PubMed and Web of Science databases spanning from 1995 to March 2024. The meta-analysis encompassed a total of 40 independent experiments drawn from 33 original articles. Results: The findings unveiled an overall significant spTMS suppression effect on visual perception. Nevertheless, there existed substantial heterogeneity among the experiments. Univariate analysis elucidated that the spTMS effects could be significantly influenced by TMS intensity, visual angle of the stimulus, coil type, and TMS stimulators from different manufacturers. Reliable spTMS suppression effects were observed within the time windows of -80 to 0 ms and 50 to 150 ms. Multivariate linear regression analyses, which included SOA, TMS intensity, visual angle of the stimulus, and coil type, identified SOA as the key factor influencing the spTMS effects. Within the 50 to 150 ms time window, optimal SOAs were identified as 112 ms and 98 ms for objective and subjective performance, respectively. Collectively, multiple experimental factors accounted for 22.9% (r = 0.3353) and 39.9% (r = 0.3724) of the variance in objective and subjective performance, respectively. Comparing univariate and multivariate analyses, it was evident that experimental factors had different impacts on objective performance and subjective performance. Conclusion: The present study provided quantitative recommendations for future experiments involving the spTMS effects on visual targets, offering guidance on how to configure experimental factors to achieve the optimal masking effect.

The Important Role of the Right Dorsolateral Prefrontal Cortex in Conflict Adaptation: A Combined Voxel-Based Morphometry and Continuous Theta Burst Stimulation Study.

Humans can flexibly adjust their executive control to resolve conflicts. Conflict adaptation and conflict resolution are crucial aspects of conflict processing. Functional neuroimaging studies have associated the dorsolateral prefrontal cortex (DLPFC) with conflict processing, but its causal role remains somewhat controversial. Moreover, the neuroanatomical basis of conflict processing has not been thoroughly examined. In this study, the Stroop task, a well-established measure of conflict, was employed to investigate (1) the neuroanatomical basis of conflict resolution and conflict adaptation with the voxel-based morphometry analysis, (2) the causal role of DLPFC in conflict processing with the application of the continuous theta burst stimulation to DLPFC. The results revealed that the Stroop effect was correlated to the gray matter volume of the precuneus, postcentral gyrus, and cerebellum, and the congruency sequence effect was correlated to the gray matter volume of superior frontal gyrus, postcentral gyrus, and lobule paracentral gyrus. These findings indicate the neuroanatomical basis of conflict resolution and adaptation. In addition, the continuous theta burst stimulation over the right DLPFC resulted in a significant reduction in the Stroop effect of RT after congruent trials compared with vertex stimulation and a significant increase in the Stroop effect of accuracy rate after incongruent trials than congruent trials, demonstrating the causal role of right DLPFC in conflict adaptation. Moreover, the DLPFC stimulation did not affect the Stroop effect of RT and accuracy rate. Overall, our study offers further insights into the neural mechanisms underlying conflict resolution and adaptation.

Identifying individual's distractor suppression using functional connectivity between anatomical large-scale brain regions.

Distractor suppression (DS) is crucial in goal-oriented behaviors, referring to the ability to suppress irrelevant information. Current evidence points to the prefrontal cortex as an origin region of DS, while subcortical, occipital, and temporal regions are also implicated. The present study aimed to examine the contribution of communications between these brain regions to visual DS. To do it, we recruited two independent cohorts of participants for the study. One cohort participated in a visual search experiment where a salient distractor triggering distractor suppression to measure their DS and the other cohort filled out a Cognitive Failure Questionnaire to assess distractibility in daily life. Both cohorts collected resting-state functional magnetic resonance imaging (rs-fMRI) data to investigate function connectivity (FC) underlying DS. First, we generated predictive models of the DS measured in visual search task using resting-state functional connectivity between large anatomical regions. It turned out that the models could successfully predict individual's DS, indicated by a significant correlation between the actual and predicted DS (r = 0.32, p < 0.01). Importantly, Prefrontal-Temporal, Insula-Limbic and Parietal-Occipital connections contributed to the prediction model. Furthermore, the model could also predict individual's daily distractibility in the other independent cohort (r = -0.34, p < 0.05). Our findings showed the efficiency of the predictive models of distractor suppression encompassing connections between large anatomical regions and highlighted the importance of the communications between attention-related and visual information processing regions in distractor suppression. Current findings may potentially provide neurobiological markers of visual distractor suppression.

cTBS to Right DLPFC Modulates Physiological Correlates of Conflict Processing: Evidence from a Stroop task.

Conflict typically occurs when goal-directed processing competes with more automatic responses. Though previous studies have highlighted the importance of the right dorsolateral prefrontal cortex (rDLPFC) in conflict processing, its causal role remains unclear. In the current study, the behavioral experiment, the continuous theta burst stimulation (cTBS), and the electroencephalography (EEG) were combined to explore the effects of behavioral performance and physiological correlates during conflict processing, after the cTBS over the rDLPFC and vertex (the control condition). Twenty-six healthy participants performed the Stroop task which included congruent and incongruent trials. Although the cTBS did not induce significant changes in the behavioral performance, the cTBS over the rDLPFC reduced the Stroop effects of conflict monitoring-related frontal-central N2 component and theta oscillation, and conflict resolution-related parieto-occipital alpha oscillation, compared to the vertex stimulation. Moreover, a significant hemispheric difference in alpha oscillation was exploratively observed after the cTBS over the rDLPFC. Interestingly, we found the rDLPFC stimulation resulted in significantly reduced Stroop effects of theta and gamma oscillation after response, which may reflect the adjustment of cognitive control for the next trial. In conclusion, our study not only demonstrated the critical involvement of the rDLPFC in conflict monitoring, conflict resolution processing, and conflict adaptation but also revealed the electrophysiological mechanism of conflict processing mediated by the rDLPFC.

The role of middle frontal gyrus in working memory retrieval by the effect of target detection tasks: a simultaneous EEG-fMRI study.

Maintained working memory (WM) representations have been shown to influence visual target detection selection, while the effect of the visual target detection process on WM retrieval remains largely unknown. In the current research, we used the dual-paradigm of the visual target detection task and the delayed matching task (DMT), which contained the following four conditions: the match condition: the DMT target contained the detection target; the mismatch condition: the DMT target contained the detection distractor; the neutral condition: only the detection target was presented; the catch condition: only the DMT target was presented. Twenty-six subjects were recruited in the experiment with simultaneous EEG-fMRI data. Behaviorally, faster responses were found in the mismatch condition than in the match and neutral conditions. The EEG data found a greater parieto-occipital N1 component in the mismatch condition compared to the neutral condition, and a greater frontal N2 component in the match condition than in the mismatch condition. Moreover, compared to the match and neutral conditions, weaker activations of the bilateral middle frontal gyrus (MFG) were observed in the mismatch condition. And the representational similarity analysis (RSA) revealed significant differences in the representational patterns of the bilateral MFG between mismatch and match conditions, as well as in the representational patterns of the left MFG between mismatch and neutral conditions. Additionally, the left MFG may be the brain source of the N1 component in the mismatch condition. These findings suggest that the mismatch between the DMT target and detection target affects early attention allocation and attentional control in WM retrieval, and the MFG may play an important role in WM retrieval by the effect of the target detection task. In conclusion, our work deepens the understanding of the neural mechanisms by which visual target detection affects WM retrieval.

Structural and functional neural substrates underlying the concreteness effect.

The concreteness effect refers to the advantage in speed and accuracy of processing concrete words over abstract words. Previous studies have shown that the processing of the two types of words is mediated by distinct neural mechanisms, but these studies were mainly conducted with task-based functional magnetic resonance imaging. This study investigates the associations between the concreteness effect and grey matter volume (GMV) of brain regions as well as resting-state functional connectivity (rsFC) of these identified regions. The results show that the GMV of left inferior frontal gyrus (IFG), right middle temporal gyrus (MTG), right supplementary motor area and right anterior cingulate cortex (ACC) negatively correlates with the concreteness effect. The rsFC of the left IFG, the right MTG and the right ACC with the nodes, mainly in default mode network, frontoparietal network and dorsal attention network positively correlates with the concreteness effect. The GMV and rsFC jointly and respectively predict the concreteness effect in individuals. In conclusion, stronger connectivity amongst functional networks and higher coherent engagement of the right hemisphere predict a greater difference in the verbal memory of abstract and concrete words.

Using modular connectome-based predictive modeling to reveal brain-behavior relationships of individual differences in working memory.

Working memory plays a crucial role in our daily lives, and brain imaging has been used to predict working memory performance. Here, we present an improved connectome-based predictive modeling approach for building a predictive model of individual working memory performance from whole-brain functional connectivity. The model was built using n-back task-based fMRI and resting-state fMRI data from the Human Connectome Project. Compared to prior models, our model was more interpretable, demonstrated a closer connection to the known anatomical and functional network. The model also demonstrates strong generalization on nine other cognitive behaviors from the HCP database and can well predict the working memory performance of healthy individuals in external datasets. By comparing the differences in prediction effects of different brain networks and anatomical feature analysis on n-back tasks, we found the essential role of some networks in differentiating between high and low working memory loads conditions.

Selective Enhancement of Frontal-Posterior Functional Connectivity by Anodal tDCS Over the Right Posterior Parietal Cortex During Temporal Attention.

Temporal attention is the concentration of perceptual resources at a specific point in time, which can help individuals get prepared to improve their behavioral performance, whereas the neural mechanism of temporal attention is yet to be well understood. In this study, behavioral measurement, transcranial direct current stimulation (tDCS), and electroencephalography (EEG) were combined to explore the effects of task performance and whole-brain functional connectivities (FCs) during temporal attention with different time intervals after applying anodal and sham tDCS over the right posterior parietal cortex (PPC). Although anodal tDCS, compared with sham tDCS, did not induce a significant effect on the task performance of temporal attention, it could effectively increase long-range FCs of gamma rhythms between the right frontal and parieto-occipital regions during temporal attention, and most of the increased FCs were in the right hemisphere with certain hemispheric laterality. Meanwhile, there were intensively more increased long-range FCs at short-time intervals than those at long-time intervals, and the increased FCs at neutral long-time intervals were the least and mainly inter-hemispheric FCs. The current study not only further enriched the evidence on the key role of the right PPC during temporal attention but also proved that anodal tDCS could indeed enhance whole-brain functional connectivity architecture involving intra- and inter-hemispheric long-range FCs, which would provide ideas and references for subsequent studies of temporal attention as well as attention deficit disorder.

The brain stimulation of DLPFC regulates choice preference in intertemporal choice self-other differences.

Intertemporal choice requires to make decision by evaluating the value of two options consisting of different times and benefits. The dorsolateral prefrontal cortex (DLPFC) is a key brain region for modulating intertemporal choice. The aim of this study is to investigate the effect of non-invasive brain stimulation over DLPFC on intertemporal choice behavior for self and others. We used transcranial direct current stimulation (tDCS) and continuous theta burst stimulation (cTBS) to stimulate bilateral DLPFC in two experiments respectively. After stimulation, subjects made a choice between a Smaller-Sooner (SS) reward and a Larger-Later (LL) reward in intertemporal choice task. The results showed that cTBS stimulation on the left DLPFC reduced the choice preference for SS reward when individuals made choices for themselves. The cTBS stimulation caused preference difference between choosing for self and parents. But tDCS stimulation had no effect on regulating choice preference. In addition, subjects preferred SS reward for self than strangers. Time-types and monetary difference of rewards affected the choice preference. The presence of immediate time increased the choice preference of SS reward. As the monetary difference increased, the choice proportion of SS reward decreased. Our study demonstrates that brain stimulation on the left DLPFC can regulate choice preference behavior in intertemporal choice.

Working memory biases early object discrimination and parietal activity during attentional selection.

The contents of working memory (WM) guide visual attention, but the neural mechanisms underlying WM biases remains unclear. Here, we used simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) approaches to characterize the timing and location of the neural response underlying WM guidance during a visual search task. Behaviorally, we observed faster search performance when the WM contents matching targets (valid) compared to when WM contents did not reappear (neutral). The EEG data showed similar benefit effects of posterior N1 component, in which targets induced larger N1 amplitudes in the valid condition than in the neutral condition. Interestingly, the fMRI activation in left supramarginal gyrus (SMG)/inferior parietal lobule (IPL) and bilateral occipital cortex was lower in the valid compared to neutral conditions. Importantly, the magnitude of the increased N1 activity and the decreased fMRI activity in the left SMG/IPL predicted the extent of search improvement at an individual subject level. These results suggest that information held in WM enhances early object discrimination during attentional selection, and the left SMG/IPL may be a critical region in mediating goal-directed processing under WM biases in human visual attention.

Visual Selective Attention P300 Source in Frontal-Parietal Lobe: ERP and fMRI Study.

Visual selective attention can be achieved into bottom-up and top-down attention. Different selective attention tasks involve different attention control ways. The pop-out task requires more bottom-up attention, whereas the search task involves more top-down attention. P300, which is the positive potential generated by the brain in the latency of 300 ~ 600 ms after stimulus, reflects the processing of attention. There is no consensus on the P300 source. The aim of present study is to study the source of P300 elicited by different visual selective attention. We collected thirteen participants' P300 elicited by pop-out and search tasks with event-related potentials (ERP). We collected twenty-six participants' activation brain regions in pop-out and search tasks with functional magnetic resonance imaging (fMRI). And we analyzed the sources of P300 using the ERP and fMRI integration with high temporal resolution and high spatial resolution. ERP results indicated that the pop-out task induced larger P300 than the search task. P300 induced by the two tasks distributed at frontal and parietal lobes, with P300 induced by the pop-out task mainly at the parietal lobe and that induced by the search task mainly at the frontal lobe. Further ERP and fMRI integration analysis showed that neural difference sources of P300 were the right precentral gyrus, left superior frontal gyrus (medial orbital), left middle temporal gyrus, left rolandic operculum, right postcentral gyrus, and left angular gyrus. Our study suggests that the frontal and parietal lobes contribute to the P300 component of visual selective attention.

The critical role of the orbitofrontal cortex for regret in an economic decision-making task.

Regret affects decision-making behavior, which is mediated by a cognitive process known as counterfactual thinking in economic science. Several studies indicate that orbitofrontal cortex (OFC) plays a crucial role in decision-making behavior. However, the neural correlates of regret trait and the function of the OFC in decision-making remain unclear. In this study, we employed a typical monetary decision-making task, a modified 'Wheel of Fortune gamble' paradigm, to investigate decision-making behavior and its neural mechanism. We combined voxel-based morphometry (VBM) and task-evoked functional magnetic resonance imaging (fMRI) analyses to explore the neural substrates of regret trait. VBM analyses revealed that individual Regret Scale Score was negatively associated with the gray-matter volume (GMV) in the frontal and temporal areas, including the bilateral OFC. These results indicate that individuals with high regret trait have smaller GMV in these areas. Moreover, we found stronger task-evoked activation of the left OFC in high regret trait individuals during the decision-maker's choice (choose conditions) phase, whereas we did not find this relationship in computer-selected's (follow conditions) choice phase. Using generalized psychophysiological interactions (PPI) analysis, we further found that the functional connectivity of the left OFC to right inferior frontal gyrus and left cerebellum was stronger in the complete feedback choose condition (under regret theoretical framework) than partial feedback choose condition (under disappointment theoretical framework). These findings verify the critical role of the OFC in the decision-making, more importantly, provide novel insights into the morphological and functional substrates of individual regret trait.

Structural and functional MRI evidence for significant contribution of precentral gyrus to flexible oculomotor control: evidence from the antisaccade task.

Antisaccade task requires inhibition of a prepotent prosaccade to a peripheral target and initiation of a saccade to the opposite location, and, therefore, is used as a tool to investigate behavioral adjustment. The frontal and parietal cortices are both known for their activation during saccade generation, but it is unclear whether their neuroanatomical characteristics also contribute to antisaccades. Here, we took antisaccade cost (antisaccade latency minus prosaccade latency) as an index for additional time for generating antisaccades. Fifty-eight participants conducted pro and antisaccade tasks outside the magnetic resonance imaging (MRI) scanner and their structural MRI (sMRI) data were also collected to explore brain regions neuroanatomically related to antisaccade cost. Then, twelve participants performed saccade tasks in the scanner and their task-state functional MRI (fMRI) data were collected to verify the activation of structurally identified brain regions during the saccade generation. Voxel-based morphometry (VBM) results revealed that gray matter volume (GMV) of the left precentral gyrus and the left insula were positively correlated with the antisaccade cost, which was validated by the prediction analysis. Brain activation results showed the activation of the precentral during both pro and antisaccade execution period, but not the insula. Our results suggest that precentral gyrus and insula play vital roles to antisaccade cost, but possibly in different ways. The insula, a key node of the salience network, possibly regulates the saliency processing of the target, while the precentral gyrus possibly mediates the generation of saccades. Our study especially highlights an outstanding role of the precentral gyrus in flexible oculomotor control.

Aberrant Whole-Brain Resting-State Functional Connectivity Architecture in Obsessive-Compulsive Disorder: An EEG Study.

Obsessive-compulsive disorder (OCD) is a common neuropsychiatric disorder characterized by intrusive thoughts (obsessions) and repetitive behaviors (compulsions), and few studies have assessed the whole-brain functional connectivity architecture of OCD with electroencephalogram (EEG) during different resting states. Graph theory and network-based statistics (NBS) were employed to examine the neural synchronization and the whole-brain functional connectivity (FC) based on the phase-locking value (PLV) of OCD patients and healthy controls (HCs) during eyes-closed (EC) and eyes-open (EO) states. Compared with HCs, OCD patients exhibited not only decreased global synchronization in terms of phase synchrony but also aberrant global topological properties (decreased average shortest path lengths and normalized shortest path lengths together with increased global efficiencies and normalized clustering coefficients) together with inhibited intra-hemispheric and interhemispheric FCs during rest, which suggested an imbalance between functional integration and segregation of brain networks for OCD patients. Meanwhile, OCD patients had increased global efficiencies and normalized clustering coefficients, but decreased average clustering coefficients and normalized shortest path lengths together with significantly decreased FCs in the alpha band from EC to EO states, which suggested a dynamic switch between highly integrated (EC state) and highly specialized (EO state) modes of information processing. Moreover, the decreased FCs of OCD patients showed obvious hemispheric asymmetry within or between groups during EC and EO states, which might serve as a potential biomarker to classify OCD patients from HCs.

Shared and distinct structure-function substrates of heterogenous distractor suppression ability between high and low working memory capacity individuals.

Salient stimuli can capture attention in a bottom-up manner; however, this attentional capture can be suppressed in a top-down manner. It has been shown that individuals with high working memory capacity (WMC) can suppress salient­but-irrelevant distractors better than those with low WMC; however, neural substrates underlying this difference remain unclear. To examine this, participants with high or low WMC (high-/low-WMC, n = 44/44) performed a visual search task wherein a color singleton item served as a salient distractor, and underwent structural and resting-state functional magnetic resonance imaging scans. Behaviorally, the color singleton distractor generally reduced the reaction time (RT). This RT benefit (ΔRT) was higher in the high-WMC group relative to the low-WMC group, indicating the superior distractor suppression ability of the high-WMC group. Moreover, leveraging voxel-based morphometry analysis, gray matter morphology (volume and deformation) in the ventral attention network (VAN) was found to show the same, positive associations with ΔRT in both WMC groups. However, correlations of the opposite sign were found between ΔRT and gray matter morphology in the frontoparietal (FPN)/default mode network (DMN) in the two WMC groups. Furthermore, resting-state functional connectivity analysis centering on regions with a structural-behavioral relationship found that connections between the left orbital and right superior frontal gyrus (hubs of DMN and VAN, respectively) was correlated with ΔRT in the high-WMC group (but not in the low-WMC group). Collectively, our work present shared and distinct neuroanatomical substrates of distractor suppression in high- and low-WMC individuals. Furthermore, intrinsic connectivity of the brain network hubs in high-WMC individuals may account for their superior ability in suppressing salient distractors.

Enhancing Visuospatial Working Memory Performance Using Intermittent Theta-Burst Stimulation Over the Right Dorsolateral Prefrontal Cortex.

Noninvasive brain stimulation provides a promising approach for the treatment of neuropsychiatric conditions. Despite the increasing research on the facilitatory effects of this kind of stimulation on the cognitive processes, the majority of the studies have used the standard stimulation approaches such as the transcranial direct current stimulation and the conventional repetitive transcranial magnetic stimulation (rTMS) which seem to be limited in robustness and the duration of the transient effects. However, a recent specialized type of rTMS, theta-burst stimulation (TBS), patterned to mimic the natural cross-frequency coupling of the human brain, may induce robust and longer-lasting effects on cortical activity. Here, we aimed to investigate the effects of the intermittent TBS (iTBS), a facilitatory form of TBS, over the right DLPFC (rDLPFC), a brain area implicated in higher-order cognitive processes, on visuospatial working memory (VSWM) performance. Therefore, iTBS was applied over either the rDLPFC or the vertex of 24 healthy participants, in two separate sessions. We assessed VSWM performance using 2-back and 4-back visuospatial tasks before iTBS (at the baseline (BL), and after the iTBS. Our results indicate that the iTBS over the rDLPFC significantly enhanced VSWM performance in the 2-back task, as measured by the discriminability index and the reaction time. However, the 4-back task performance was not significantly modulated by iTBS. These findings demonstrate that the rDLPFC plays a critical role in VSWM and that iTBS is a safe and effective approach for investigating the causal role of the specific brain areas.

Differential involvement of frontoparietal network and insula cortex in emotion regulation.

Emotion regulation (ER) is an essential part of our daily life. To effectively regulate emotions, different types of strategies may be adopted. Although previous neuroimaging studies have shown that the frontoparietal cortex is critical for the regulation of emotions, reports about the specific brain regions involved in each strategy remain inconsistent. Therefore, the present study recruited 32 healthy participants to directly examine three typical ER strategies (distraction, reappraisal, and suppression) with an emotional regulation paradigm using functional magnetic resonance imaging (fMRI). Our results show that the three ER strategies recruited differential activation in the frontoparietal and insular cortex. Specifically, distraction evoked stronger activation in the parietal cortex, while reappraisal triggered stronger activation in most parts of the frontal cortex. Importantly, suppression predominantly recruited the left inferior frontal gyrus (IFG), while reappraisal caused more activation than suppression in bilateral medial superior frontal gyrus and IFG. Besides, functional connectivity analysis found that the connectivity between the right insular and the right IFG was negatively correlated with reappraisal effect, while that between the left insular and the left IFG was negatively correlated with suppression effect. These results suggest that the successful implementation of distraction, reappraisal, and suppression specifically employ different parts of the frontoparietal network. Overall, our findings may have potential implications for clinical practice by providing specific neural targets for clinical intervention.

Predicting MCI to AD Conversation Using Integrated sMRI and rs-fMRI: Machine Learning and Graph Theory Approach.

BACKGROUND: Graph theory and machine learning have been shown to be effective ways of classifying different stages of Alzheimer's disease (AD). Most previous studies have only focused on inter-subject classification with single-mode neuroimaging data. However, whether this classification can truly reflect the changes in the structure and function of the brain region in disease progression remains unverified. In the current study, we aimed to evaluate the classification framework, which combines structural Magnetic Resonance Imaging (sMRI) and resting-state functional Magnetic Resonance Imaging (rs-fMRI) metrics, to distinguish mild cognitive impairment non-converters (MCInc)/AD from MCI converters (MCIc) by using graph theory and machine learning. METHODS: With the intra-subject (MCInc vs. MCIc) and inter-subject (MCIc vs. AD) design, we employed cortical thickness features, structural brain network features, and sub-frequency (full-band, slow-4, slow-5) functional brain network features for classification. Three feature selection methods [random subset feature selection algorithm (RSFS), minimal redundancy maximal relevance (mRMR), and sparse linear regression feature selection algorithm based on stationary selection (SS-LR)] were used respectively to select discriminative features in the iterative combinations of MRI and network measures. Then support vector machine (SVM) classifier with nested cross-validation was employed for classification. We also compared the performance of multiple classifiers (Random Forest, K-nearest neighbor, Adaboost, SVM) and verified the reliability of our results by upsampling. RESULTS: We found that in the classifications of MCIc vs. MCInc, and MCIc vs. AD, the proposed RSFS algorithm achieved the best accuracies (84.71, 89.80%) than the other algorithms. And the high-sensitivity brain regions found with the two classification groups were inconsistent. Specifically, in MCIc vs. MCInc, the high-sensitivity brain regions associated with both structural and functional features included frontal, temporal, caudate, entorhinal, parahippocampal, and calcarine fissure and surrounding cortex. While in MCIc vs. AD, the high-sensitivity brain regions associated only with functional features included frontal, temporal, thalamus, olfactory, and angular. CONCLUSIONS: These results suggest that our proposed method could effectively predict the conversion of MCI to AD, and the inconsistency of specific brain regions provides a novel insight for clinical AD diagnosis.

Distance Estimation in Virtual Reality Is Affected by Both the Virtual and the Real-World Environments.

The experience in virtual reality (VR) is unique, in that observers are in a real-world location while browsing through a virtual scene. Previous studies have investigated the effect of the virtual environment on distance estimation. However, it is unclear how the real-world environment influences distance estimation in VR. Here, we measured the distance estimation using a bisection (Experiment 1) and a blind-walking (Experiments 2 and 3) method. Participants performed distance judgments in VR, which rendered either virtual indoor or outdoor scenes. Experiments were also carried out in either real-world indoor or outdoor locations. In the bisection experiment, judged distance in virtual outdoor was greater than that in virtual indoor. However, the real-world environment had no impact on distance judgment estimated by bisection. In the blind-walking experiment, judged distance in real-world outdoor was greater than that in real-world indoor. On the other hand, the virtual environment had no impact on distance judgment estimated by blind-walking. Generally, our results suggest that both the virtual and real-world environments have an impact on distance judgment in VR. Especially, the real-world environment where a person is physically located during a VR experience influences the person's distance estimation in VR.