Assessment on interoceptive awareness on alcohol use and gambling disorders reveals dissociable interoceptive abilities linked to external and internal dependencies: Practical use of Body Perception Questionnaire Very Short Form (BPQ-VSF) in clinical settings.

Interoception is one of the pivotal cognitive functions for mechanisms of our body awareness, and malfunction of the interoceptive network is thought to be associated with mental illness, including addiction. Within addictive disorders, substance-based and non-substance-based addictions are known to hold dissociable reward systems. However, little is known about how interoceptive awareness between these addiction sub-types would differ. Subjective interoceptive awareness was assessed among patients with alcohol use disorder (n = 50) who were subsequently hospitalized or remained out-patient and gambling addiction (n = 41) by the Body Awareness component of the Japanese version of the Body Perception Questionnaire (BPQ-VSFBA-J) and compared them against healthy control (n = 809). Both addiction groups showed significantly lower BPQ than the control, with no substantial differences between inpatients and outpatients for alcohol samples. Notably, BPQ scores for gambling patients were significantly lower than those for the alcohol group. This evidence may suggest a putative role of interoceptive ability on the severity of behavioral addiction over substance-based addiction.

Behavioral and Neural Correlates of Visual Working Memory Reveal Metacognitive Aspects of Mental Imagery.

Mental imagery (MI) is the ability to generate visual phenomena in the absence of sensory input. MI is often likened to visual working memory (VWM): the ability to maintain and manipulate visual representations. How MI is recruited during VWM is yet to be established. In a modified orientation change-discrimination task, we examined how behavioral (proportion correct) and neural (contralateral delay activity [CDA]) correlates of precision and capacity map onto subjective ratings of vividness and number of items in MI within a VWM task. During the maintenance period, 17 participants estimated the vividness of their MI or the number of items held in MI while they were instructed to focus on either precision or capacity of their representation and to retain stimuli at varying set sizes (1, 2, and 4). Vividness and number ratings varied over set sizes; however, subjective ratings and behavioral performance correlated only for vividness rating at set size 1. Although CDA responded to set size as was expected, CDA did not reflect subjective reports on high and low vividness and on nondivergent (reported the probed number of items in mind) or divergent (reported number of items diverged from probed) rating trials. Participants were more accurate in low set sizes compared with higher set sizes and in coarse (45°) orientation changes compared with fine (15°) orientation changes. We failed to find evidence for a relationship between the subjective sensory experience of precision and capacity of MI and the precision and capacity of VWM.

oFVSD: a Python package of optimized forward variable selection decoder for high-dimensional neuroimaging data.

The complexity and high dimensionality of neuroimaging data pose problems for decoding information with machine learning (ML) models because the number of features is often much larger than the number of observations. Feature selection is one of the crucial steps for determining meaningful target features in decoding; however, optimizing the feature selection from such high-dimensional neuroimaging data has been challenging using conventional ML models. Here, we introduce an efficient and high-performance decoding package incorporating a forward variable selection (FVS) algorithm and hyper-parameter optimization that automatically identifies the best feature pairs for both classification and regression models, where a total of 18 ML models are implemented by default. First, the FVS algorithm evaluates the goodness-of-fit across different models using the k-fold cross-validation step that identifies the best subset of features based on a predefined criterion for each model. Next, the hyperparameters of each ML model are optimized at each forward iteration. Final outputs highlight an optimized number of selected features (brain regions of interest) for each model with its accuracy. Furthermore, the toolbox can be executed in a parallel environment for efficient computation on a typical personal computer. With the optimized forward variable selection decoder (oFVSD) pipeline, we verified the effectiveness of decoding sex classification and age range regression on 1,113 structural magnetic resonance imaging (MRI) datasets. Compared to ML models without the FVS algorithm and with the Boruta algorithm as a variable selection counterpart, we demonstrate that the oFVSD significantly outperformed across all of the ML models over the counterpart models without FVS (approximately 0.20 increase in correlation coefficient, r, with regression models and 8% increase in classification models on average) and with Boruta variable selection algorithm (approximately 0.07 improvement in regression and 4% in classification models). Furthermore, we confirmed the use of parallel computation considerably reduced the computational burden for the high-dimensional MRI data. Altogether, the oFVSD toolbox efficiently and effectively improves the performance of both classification and regression ML models, providing a use case example on MRI datasets. With its flexibility, oFVSD has the potential for many other modalities in neuroimaging. This open-source and freely available Python package makes it a valuable toolbox for research communities seeking improved decoding accuracy.

Insula neuroanatomical networks predict interoceptive awareness.

Interoceptive awareness (IA), the subjective and conscious perception of visceral and physiological signals from the body, has been associated with functions of cortical and subcortical neural systems involved in emotion control, mood and anxiety disorders. We recently hypothesized that IA and its contributions to mental health are realized by a brain interoception network (BIN) linking brain regions that receive ascending interoceptive information from the brainstem, such as the amygdala, insula and anterior cingulate cortex (ACC). However, little evidence exists to support this hypothesis. In order to test this hypothesis, we used a publicly available dataset that contained both anatomical neuroimaging data and an objective measure of IA assessed with a heartbeat detection task. Whole-brain Voxel-Based Morphometry (VBM) was used to investigate the association of IA with gray matter volume (GMV) and the structural covariance network (SCN) of the amygdala, insula and ACC. The relationship between IA and mental health was investigated with questionnaires that assessed depressive symptoms and anxiety. We found a positive correlation between IA and state anxiety, but not with depressive symptoms. In the VBM analysis, only the GMV of the left anterior insula showed a positive association with IA. A similar association was observed between the parcellated GMV of the left dorsal agranular insula, located in the anterior insula, and IA. The SCN linking the right dorsal agranular insula with the left dorsal agranular insula and left hyper-granular insula were positively correlated with IA. No association between GMV or SCN and depressive symptoms or anxiety were observed. These findings revealed a previously unknown association between IA, insula volume and intra-insula SCNs. These results may support development of non-invasive neuroimaging interventions, e.g., neurofeedback, seeking to improve IA and to prevent development of mental health problems, such anxiety disorders.

The neuroanatomy of social trust predicts depression vulnerability.

Trust attitude is a social personality trait linked with the estimation of others' trustworthiness. Trusting others, however, can have substantial negative effects on mental health, such as the development of depression. Despite significant progress in understanding the neurobiology of trust, whether the neuroanatomy of trust is linked with depression vulnerability remains unknown. To investigate a link between the neuroanatomy of trust and depression vulnerability, we assessed trust and depressive symptoms and employed neuroimaging to acquire brain structure data of healthy participants. A high depressive symptom score was used as an indicator of depression vulnerability. The neuroanatomical results observed with the healthy sample were validated in a sample of clinically diagnosed depressive patients. We found significantly higher depressive symptoms among low trusters than among high trusters. Neuroanatomically, low trusters and depressive patients showed similar volume reduction in brain regions implicated in social cognition, including the dorsolateral prefrontal cortex (DLPFC), dorsomedial PFC, posterior cingulate, precuneus, and angular gyrus. Furthermore, the reduced volume of the DLPFC and precuneus mediated the relationship between trust and depressive symptoms. These findings contribute to understanding social- and neural-markers of depression vulnerability and may inform the development of social interventions to prevent pathological depression.

Suppression of Neuroinflammation Attenuates Persistent Cognitive and Neurogenic Deficits in a Rat Model of Cardiopulmonary Bypass.

Post-operative cognitive dysfunction (POCD) can be a serious surgical complication, and patients undergoing cardiac procedures are at particular risk for POCD. This study examined the effect of blocking neuroinflammation on behavioral and neurogenic deficits produced in a rat model of cardiopulmonary bypass (CPB). Minocycline, a drug with established anti-inflammatory activity, or saline was administered daily for 30 days post-CPB. Treatment with minocycline reduced the number of activated microglia/macrophages observed in the dentate gyrus of the hippocampus at 6 months post-CPB, consistent with an anti-inflammatory action in this CPB model. Behavioral testing was conducted at 6 months post-CPB utilizing a win-shift task on an 8-arm radial maze. Minocycline-treated animals performed significantly better than saline-treated animals on this task after CPB. In addition, the CPB-induced reduction in adult neurogenesis was attenuated in the minocycline-treated animals. Together, these findings indicate that suppressing neuroinflammation during the early post-surgical phase can limit long-term deficits in both behavioral and neurogenic outcomes after CPB.

Resting-state brain activity can predict target-independent aptitude in fMRI-neurofeedback training.

Neurofeedback (NF) aptitude, which refers to an individual's ability to change brain activity through NF training, has been reported to vary significantly from person to person. The prediction of individual NF aptitudes is critical in clinical applications to screen patients suitable for NF treatment. In the present study, we extracted the resting-state functional brain connectivity (FC) markers of NF aptitude, independent of NF-targeting brain regions. We combined the data from fMRI-NF studies targeting four different brain regions at two independent sites (obtained from 59 healthy adults and six patients with major depressive disorder) to collect resting-state fMRI data associated with aptitude scores in subsequent fMRI-NF training. We then trained the multiple regression models to predict the individual NF aptitude scores from the resting-state fMRI data using a discovery dataset from one site and identified six resting-state FCs that predicted NF aptitude. Subsequently, the reproducibility of the prediction model was validated using independent test data from another site. The identified FC model revealed that the posterior cingulate cortex was the functional hub among the brain regions and formed predictive resting-state FCs, suggesting that NF aptitude may be involved in the attentional mode-orientation modulation system's characteristics in task-free resting-state brain activity.

The Shape of a Vehicle Windshield Affects Reaction Time and Brain Activity During a Target Detection Task.

Background: Achieving clear visibility through a windshield is one of the crucial factors in manufacturing a safe and comfortable vehicle. The optic flow (OF) through the windshield has been reported to divert attention and could impair visibility. Although a growing number of behavioral and neuroimaging studies have assessed drivers' attention in various driving scenarios, there is still little evidence of a relationship between OF, windshield shape, and driver's attentional efficacy. The purpose of this research was to examine this relationship. Methods: First, we quantified the OF across the windshield in a simulated driving scenario with either of two types of the windshield (a tilted or vertical pillar) at different speeds (60 km/h or 160 km/h) and found more upward OF along the tilted pillar than along the vertical pillar. Therefore, we hypothesized that the predominance of upward OF around the windshield along a tilted pillar could distract a driver and that we could observe the corresponding neural activity. Magnetic resonance scans were then obtained while the subjects performed a visual detection task while watching the driving scene used in the OF analysis. The subjects were required to press a button as rapidly as possible when a target appeared at one of five positions (leftmost, left, center, right, and rightmost). Results: We found that the reaction time (RT) on exposure to a tilted pillar was longer than that on exposure to a vertical pillar in the leftmost and rightmost conditions. Furthermore, there was more brain activity in the precuneus when the pillar was tilted than when it was vertical in the rightmost condition near the pillar. In a separate analysis, activation in the precuneus was found to reflect relative changes in the amount of upward OF when the target was at the rightmost position. Conclusions: Overall, these observations suggest that activation in the precuneus may reflect extraneous cognitive load driven by upward OF along the pillar and could distract visual attention. The findings of this study highlight the value of a cognitive neuroscientific approach to research and development in the motor vehicle manufacturing industry.

Gray Matter Volume in Different Cortical Structures Dissociably Relates to Individual Differences in Capacity and Precision of Visual Working Memory.

Visual working memory (VWM) refers to our ability to selectively maintain visual information in a mental representation. While cognitive limits of VWM greatly influence a variety of mental operations, it remains controversial whether the quantity or quality of representations in mind constrains VWM. Here, we examined behavior-to-brain anatomical relations as well as brain activity to brain anatomy associations with a "neural" marker specific to the retention interval of VWM. Our results consistently indicated that individuals who maintained a larger number of items in VWM tended to have a larger gray matter (GM) volume in their left lateral occipital region. In contrast, individuals with a superior ability to retain with high precision tended to have a larger GM volume in their right parietal lobe. These results indicate that individual differences in quantity and quality of VWM may be associated with regional GM volumes in a dissociable manner, indicating willful integration of information in VWM may recruit separable cortical subsystems.

Quantification of anticipation of excitement with a three-axial model of emotion with EEG.

OBJECTIVE: Multiple facets of human emotion underlie diverse and sparse neural mechanisms. Among the many existing models of emotion, the two-dimensional circumplex model of emotion is an important theory. The use of the circumplex model allows us to model variable aspects of emotion; however, such momentary expressions of one's internal mental state still lacks a notion of the third dimension of time. Here, we report an exploratory attempt to build a three-axis model of human emotion to model our sense of anticipatory excitement, 'Waku-Waku' (in Japanese), in which people predictively code upcoming emotional events. APPROACH: Electroencephalography (EEG) data were recorded from 28 young adult participants while they mentalized upcoming emotional pictures. Three auditory tones were used as indicative cues, predicting the likelihood of the valence of an upcoming picture: positive, negative, or unknown. While seeing an image, the participants judged its emotional valence during the task and subsequently rated their subjective experiences on valence, arousal, expectation, and Waku-Waku immediately after the experiment. The collected EEG data were then analyzed to identify contributory neural signatures for each of the three axes. MAIN RESULTS: A three-axis model was built to quantify Waku-Waku. As expected, this model revealed the considerable contribution of the third dimension over the classical two-dimensional model. Distinctive EEG components were identified. Furthermore, a novel brain-emotion interface was proposed and validated within the scope of limitations. SIGNIFICANCE: The proposed notion may shed new light on the theories of emotion and support multiplex dimensions of emotion. With the introduction of the cognitive domain for a brain-computer interface, we propose a novel brain-emotion interface. Limitations of the study and potential applications of this interface are discussed.

Affective auditory stimulus database: An expanded version of the International Affective Digitized Sounds (IADS-E).

Using appropriate stimuli to evoke emotions is especially important for researching emotion. Psychologists have provided several standardized affective stimulus databases-such as the International Affective Picture System (IAPS) and the Nencki Affective Picture System (NAPS) as visual stimulus databases, as well as the International Affective Digitized Sounds (IADS) and the Montreal Affective Voices as auditory stimulus databases for emotional experiments. However, considering the limitations of the existing auditory stimulus database studies, research using auditory stimuli is relatively limited compared with the studies using visual stimuli. First, the number of sample sounds is limited, making it difficult to equate across emotional conditions and semantic categories. Second, some artificially created materials (music or human voice) may fail to accurately drive the intended emotional processes. Our principal aim was to expand existing auditory affective sample database to sufficiently cover natural sounds. We asked 207 participants to rate 935 sounds (including the sounds from the IADS-2) using the Self-Assessment Manikin (SAM) and three basic-emotion rating scales. The results showed that emotions in sounds can be distinguished on the affective rating scales, and the stability of the evaluations of sounds revealed that we have successfully provided a larger corpus of natural, emotionally evocative auditory stimuli, covering a wide range of semantic categories. Our expanded, standardized sound sample database may promote a wide range of research in auditory systems and the possible interactions with other sensory modalities, encouraging direct reliable comparisons of outcomes from different researchers in the field of psychology.

Overlearning hyperstabilizes a skill by rapidly making neurochemical processing inhibitory-dominant.

Overlearning refers to the continued training of a skill after performance improvement has plateaued. Whether overlearning is beneficial is a question in our daily lives that has never been clearly answered. Here we report a new important role: overlearning in humans abruptly changes neurochemical processing, to hyperstabilize and protect trained perceptual learning from subsequent new learning. Usually, learning immediately after training is so unstable that it can be disrupted by subsequent new learning until after passive stabilization occurs hours later. However, overlearning so rapidly and strongly stabilizes the learning state that it not only becomes resilient against, but also disrupts, subsequent new learning. Such hyperstabilization is associated with an abrupt shift from glutamate-dominant excitatory to GABA-dominant inhibitory processing in early visual areas. Hyperstabilization contrasts with passive and slower stabilization, which is associated with a mere reduction of excitatory dominance to baseline levels. Using hyperstabilization may lead to efficient learning paradigms.

Human visual short-term memory precision can be varied at will when the number of retained items is low.

It has been debated whether human visual working memory is limited by the number of items or the precision with which they are represented. In the research reported here, we show that the precision of working memory can be flexibly and willfully controlled, but only if the number of retained items is low. Electroencephalographic recordings revealed that a neural marker for visual working memory (contralateral delay activity, or CDA) that is known to increase in amplitude with the number of retained items was also affected by the precision with which items were retained. However, willfully enhanced precision increased CDA amplitude only when the number of retained items was low. These results show that both the number and the (willfully controlled) precision of retained items constrain visual working memory: People can enhance the precision of their visual working memory, but only for a few items.

Principal component analysis of behavioural individual differences suggests that particular aspects of visual working memory may relate to specific aspects of attention.

The previously separate literatures on visual attention and on visual working memory are converging, with growing interest in how visual attention may relate to visual short-term memory, as exemplified by this special issue. We report exploratory analysis of how individual behavioural differences in separable aspects of attention may relate to particular aspects of visual working memory. Previous work with the Attention Network Test (ANT; Fan, McCandliss, Sommer, Raz, & Posner, 2002) proposed that it can measure three distinct aspects of attention: alerting, spatial orienting, plus executive control of response competition. We implemented the ANT in 50 healthy young adults, who also underwent a behavioural battery of visual working memory (WM) tests. These visual WM tests were all variations on recent paradigms, used here with the aim of measuring potential individual differences in visual WM capacity; WM precision; or WM distractor-filtering. Principal component analysis of the behavioural dataset revealed three main components. Interestingly, each component paired one aspect of ANT scores together with one aspect of WM scores, in terms of the strongest loadings. WM capacity loaded with ANT alerting; WM precision with ANT orienting; and WM filtering with ANT executive control. These results suggest that visual WM may involve separate component processes, and that different aspects of attention relate to different aspects of visual WM, in terms of behavioural individual differences. We discuss the observed pattern in relation to current issues and with respect to possible future work on the potential neural bases of individual differences in the distinct components.

The time course of ventrolateral prefrontal cortex involvement in memory formation.

Human neuroimaging studies have implicated a number of brain regions in long-term memory formation. Foremost among these is ventrolateral prefrontal cortex. Here, we used double-pulse transcranial magnetic stimulation (TMS) to assess whether the contribution of this part of cortex is crucial for laying down new memories and, if so, to examine the time course of this process. Healthy adult volunteers performed an incidental encoding task (living/nonliving judgments) on sequences of words. In separate series, the task was performed either on its own or while TMS was applied to one of two sites of experimental interest (left/right anterior inferior frontal gyrus) or a control site (vertex). TMS pulses were delivered at 350, 750, or 1,150 ms following word onset. After a delay of 15 min, memory for the items was probed with a recognition memory test including confidence judgments. TMS to all three sites nonspecifically affected the speed and accuracy with which judgments were made during the encoding task. However, only TMS to prefrontal cortex affected later memory performance. Stimulation of left or right inferior frontal gyrus at all three time points reduced the likelihood that a word would later be recognized by a small, but significant, amount (approximately 4%). These findings indicate that bilateral ventrolateral prefrontal cortex plays an essential role in memory formation, exerting its influence between > or = 350 and 1,150 ms after an event is encountered.

Electrophysiological measures of maintaining representations in visual working memory.

Visual working memory (WM) is a limited capacity system which maintains information about objects in the immediate visual environment. Recent neurophysiological and neuroimaging studies have identified sustained memory-item specific activity during the retention period of WM tasks, and this activity may be a physiological substrate of maintaining representations in WM. In the present study, we present an electrophysiological measure of delay activity using event-related potentials (ERPs). Subjects were asked to remember the items in a single hemifield presented within a bilateral display. Approximately 200 msec following the onset of the memory array, we observed a large negative wave at electrode sites that were contralateral with respect to the position of the memory items. This activity persisted throughout the retention period and appears to be an analog to delay activity observed in monkey single-unit and functional magnetic resonance imaging (fMRI) WM studies. The contralateral delay activity is modulated by the number of items in the memory array but reaches asymptote for arrays of 3 to 4 items. This activity is similar across different classes of simple objects and the amplitude is smaller on incorrect response trials relative to correct trials, suggesting that this activity is necessary for correct performance on a given trial. Together, these results appear to indicate an electrophysiological index of the maintained representations in visual WM.

Neural measures reveal individual differences in controlling access to working memory.

The capacity of visual short-term memory is highly limited, maintaining only three to four objects simultaneously. This extreme limitation necessitates efficient mechanisms to select only the most relevant objects from the immediate environment to be represented in memory and to restrict irrelevant items from consuming capacity. Here we report a neurophysiological measure of this memory selection mechanism in humans that gauges an individual's efficiency at excluding irrelevant items from being stored in memory. By examining the moment-by-moment contents of visual memory, we observe that selection efficiency varies substantially across individuals and is strongly predicted by the particular memory capacity of each person. Specifically, high capacity individuals are much more efficient at representing only the relevant items than are low capacity individuals, who inefficiently encode and maintain information about the irrelevant items present in the display. These results provide evidence that under many circumstances low capacity individuals may actually store more information in memory than high capacity individuals. Indeed, this ancillary allocation of memory capacity to irrelevant objects may be a primary source of putative differences in overall storage capacity.