The human brain can infer one's own and other individuals' mental states through metacognition and mentalizing, respectively. A new study in PLOS Biology has implicated distinct brain regions of the ...medial prefrontal cortex (PFC) in metacognition and mentalizing.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The valuation of food is a fundamental component of our decision-making. Yet little is known about how value signals for food and other rewards are constructed by the brain. Using a food-based ...decision task in human participants, we found that subjective values can be predicted from beliefs about constituent nutritive attributes of food: protein, fat, carbohydrates and vitamin content. Multivariate analyses of functional MRI data demonstrated that, while food value is represented in patterns of neural activity in both medial and lateral parts of the orbitofrontal cortex (OFC), only the lateral OFC represents the elemental nutritive attributes. Effective connectivity analyses further indicate that information about the nutritive attributes represented in the lateral OFC is integrated within the medial OFC to compute an overall value. These findings provide a mechanistic account for the construction of food value from its constituent nutrients.
Cytotoxic effects of radiation play an important role in the treatment of head and neck cancer. However, irradiation is known to lead to the migration of various cancer cells, including those of head ...and neck cancer. Recently, fibroblasts in the cancer microenvironment have been reported to be involved in this mechanism. Nevertheless, the mechanism underlying migration of head and neck cancer cells remains unclear. Herein, we aimed to elucidate this migration mechanism induced by irradiation in terms of the interaction of head and neck cancer cells with fibroblasts.
We used the head and neck squamous cell carcinoma (HNSCC) cell lines SAS and FaDu as well as fibroblast cell lines. These cells were irradiated and their viability was compared. In fibroblasts, changes in interleukin-6 (IL-6) secretion caused by irradiation were measured by enzyme-linked immunosorbent assay (ELISA). The cell migration ability of cancer cells was evaluated via a migration assay using a semipermeable membrane. HNSCC cells were cocultured with irradiated and nonirradiated fibroblasts, and their migration ability under each condition was compared. We also examined the effect of IL-6 on the migration of HNSCC cells. Furthermore, to investigate the effect of fibroblast-derived IL-6 on the migration ability of HNSCC cells, we conducted a coculture study using IL-6 neutralizing antibody.
Irradiation reduced the survival of HNSCC cells, whereas fibroblasts were resistant to irradiation. Irradiation also increased IL-6 secretion by fibroblasts. Migration of HNSCC cells was enhanced by coculture with fibroblasts and further enhanced by coculture with irradiated fibroblasts. We also confirmed that the migration of HNSCC cells was induced by IL-6. The enhanced migration of cancer cells caused by coculturing with fibroblasts was canceled by the IL-6 neutralizing antibody.
These results show that fibroblasts survive irradiation and induce the migration ability of HNSCC cells through increased secretion of IL-6.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Body-image disturbance comprises two components. The first is perceptual in nature, and is measured by a discrepancy between one's actual body and perceived self-image ("perceived-actual ...discrepancy"). The other component is affective, and is measured by a discrepancy between one's perceived self-image and ideal body image ("perceived-ideal discrepancy"). The present study evaluated the relationships between body-image disturbance and characteristics of eating disorders such as symptoms and related personality traits. In a psychophysiological experiment, female university students (mean ± SD age = 21.0 ± 1.38 years) were presented with silhouette images of their own bodies that were distorted in terms of width. The participants were asked whether each silhouette image was more overweight than their actual or ideal body images. Eating-disorder characteristics were assessed using six factors from the Japanese version of the Eating Disorder Inventory 2 (EDI2). We found that perceived-actual discrepancies correlated with negative self-evaluation (i.e., factor 3 of the EDI2), whereas perceived-ideal discrepancies correlated with dissatisfaction with one's own body (i.e., factor 2 of EDI2). These results imply that distinct psychological mechanisms underlie the two components of body-image disturbance.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Our preferences are influenced by the opinions of others. The past human neuroimaging studies on social conformity have identified a network of brain regions related to social conformity that ...includes the posterior medial frontal cortex (pMFC), anterior insula, and striatum. Since these brain regions are also known to play important roles in reinforcement learning (i.e., processing prediction error), it was previously hypothesized that social conformity and reinforcement learning have a common neural mechanism. However, although this view is currently widely accepted, these two processes have never been directly compared; therefore, the extent to which they shared a common neural mechanism had remained unclear. This study aimed to formally test the hypothesis. The same group of participants (n = 25) performed social conformity and reinforcement learning tasks inside a functional magnetic resonance imaging (fMRI) scanner. Univariate fMRI data analyses revealed activation overlaps in the pMFC and bilateral insula between social conflict and unsigned prediction error and in the striatum between social conflict and signed prediction error. We further conducted multivoxel pattern analysis (MVPA) for more direct evidence of a shared neural mechanism. MVPA did not reveal any evidence to support the hypothesis in any of these regions but found that activation patterns between social conflict and prediction error in these regions were largely distinct. Taken together, the present study provides no clear evidence of a common neural mechanism between social conformity and reinforcement learning.
The present study tested the hypothesis that social conformity would share the same neural mechanism as reinforcement learning. While univariate results showed large activation overlaps in the posterior medial frontal cortex (pMFC), anterior insula, and striatum between social conflict and prediction error, multi‐voxel pattern analysis (MVPA) showed that their activation patterns within each of these regions were largely distinct rather than similar. The results suggest that the idea that social conformity and reinforcement learning share common neural mechanisms may be too simplistic.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Retrospective epidemiological study.
Since the causes and incidences of traumatic spinal cord injury (TSCI) in each country change over time, up-to-date epidemiological studies are required for ...countermeasures against TSCI. However, no nationwide survey in Japan has been conducted for about 30 years. The purpose of this study was therefore to investigate the recent incidence and characteristics of TSCI in Japan.
Japan METHODS: Survey sheets were sent to all hospitals (emergency and acute care hospitals) that treated TSCI persons in Japan in 2018 and case notes were retrospectively reviewed. Frankel grade E cases were excluded from analysis.
The response rate was 74.4% (2804 of 3771 hospitals). The estimated annual incidence of TSCI excluding Frankel E was 49 per million, with a median age of 70.0 years and individuals in their 70s as the largest age group. Male-to-female ratio was 3:1. Cervical cord injuries occurred in 88.1%. Frankel D was the most frequent grade (46.3%), followed by Frankel C (33.0%). The most frequent cause was fall on level surface (38.6%), followed by traffic accident (20.1%). The proportion of fall on level surface increased with age. TSCI due to sports was the most frequent cause in teenagers (43.2%).
This nationwide survey in Japan showed that estimated incidence of TSCI, rate of cervical cord injury, and incomplete injury by falls appear to be increasing with the aging of the population.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
During competitive interactions, humans have to estimate the impact of their own actions on their opponent's strategy. Here we provide evidence that neural computations in the right temporoparietal ...junction (rTPJ) and interconnected structures are causally involved in this process. By combining inhibitory continuous theta-burst transcranial magnetic stimulation with model-based functional MRI, we show that disrupting neural excitability in the rTPJ reduces behavioral and neural indices of mentalizing-related computations, as well as functional connectivity of the rTPJ with ventral and dorsal parts of the medial prefrontal cortex. These results provide a causal demonstration that neural computations instantiated in the rTPJ are neurobiological prerequisites for the ability to integrate opponent beliefs into strategic choice, through system-level interaction within the valuation and mentalizing networks.
Subjective values for food rewards guide our dietary choices. There is growing evidence that value signals are constructed in the brain by integrating multiple types of information about flavour, ...taste, and nutritional attributes of the foods. However, much less is known about the influence of food-extrinsic factors such as labels, brands, prices, and packaging designs. In this mini review, we outline recent findings in decision neuroscience, consumer psychology, and food science with regard to the effect of extrinsic factors on food value computations in the human brain. To date, studies have demonstrated that, while the integrated value signal is encoded in the ventromedial prefrontal cortex, information on the extrinsic factors of the food is encoded in diverse brain regions previously implicated in a wide range of functions: cognitive control, memory, emotion and reward processing. We suggest that a comprehensive understanding of food valuation requires elucidation of the mechanisms behind integrating extrinsic factors in the brain to compute an overall subjective value signal.
Aim
Psychiatric symptoms are often accompanied by impairments in decision‐making to attain rewards and avoid losses. However, due to the complex nature of mental disorders (e.g., high comorbidity), ...symptoms that are specifically associated with deficits in decision‐making remain unidentified. Furthermore, the influence of psychiatric symptoms on computations underpinning reward‐seeking and loss‐avoidance decision‐making remains elusive. Here, we aim to address these issues by leveraging a large‐scale online experiment and computational modeling.
Methods
In the online experiment, we recruited 1900 non‐diagnostic participants from the general population. They performed either a reward‐seeking or loss‐avoidance decision‐making task, and subsequently completed questionnaires about psychiatric symptoms.
Results
We found that one trans‐diagnostic dimension of psychiatric symptoms related to compulsive behavior and intrusive thought (CIT) was negatively correlated with overall decision‐making performance in both the reward‐seeking and loss‐avoidance tasks. A deeper analysis further revealed that, in both tasks, the CIT psychiatric dimension was associated with lower preference for the options that recently led to better outcomes (i.e. reward or no‐loss). On the other hand, in the reward‐seeking task only, the CIT dimension was associated with lower preference for recently unchosen options.
Conclusion
These findings suggest that psychiatric symptoms influence the two types of decision‐making, reward‐seeking and loss‐avoidance, through both common and distinct computational processes.
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DOBA, FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UILJ, UKNU, UL, UM, UPUK
Many food decisions are made rapidly and without reflective processing. The ability to determine nutritional information accurately is a precursor of food decisions and is important for a healthy ...diet and weight management. However, little is known about the cognitive evaluation of food attributes based on visual information in relation to assessing nutritional content. We investigated the accuracy of visual encoding of nutritional information after brief and extended time exposures to food images. The following questions were addressed: (1) how accurately do people estimate energy and macronutrients after brief exposure to food images, and (2) how does estimation accuracy change with time exposure and the type of nutritional information? Participants were first asked to rate the energy density (calories) and macronutrient content (carbohydrates/fat/protein) of different sets of food images under three time conditions (97, 500 or 1000 ms) and then asked to perform the task with no time constraints. We calculated estimation accuracy by computing the correlations between estimated and actual nutritional information for each time exposure and compared estimation accuracy with respect to the type of nutritional information and the exposure time. The estimated and actual energy densities and individual macronutrient content were significantly correlated, even after a brief exposure time (97 ms). The degree of accuracy of the estimations did not differ with additional time exposure, suggesting that <100 ms was sufficient to predict the energy and macronutrients from food images. Additionally, carbohydrate estimates were less accurate than the estimates of other nutritional variables (proteins, fat and calories), regardless of the exposure time. These results revealed rapid and accurate assessment of food attributes based on visual information and the accuracy of visual encoding of nutritional information after brief and extended time exposure to food imagery.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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