The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Bien que des pratiques d’intervention comme la méditation de pleine conscience se soient révélées efficaces dans le traitement de la psychose, le mécanisme de propagation de l’information dans le cerveau n’est pas clair. Dans cette étude, nous avons formulé un problème d'optimisation de réseau et recherché la solution optimale à l'aide de Digital Annealer développé par Fujitsu Ltd. Celui-ci s'inspire de l'informatique quantique et est efficace pour résoudre des problèmes d'optimisation combinatoire à grande échelle afin de trouver la voie de propagation de l'information dans le cerveau. qui contribue à la réalisation de la pleine conscience. Plus précisément, nous avons défini l’état optimal du réseau comme l’état du réseau cérébral considéré comme associé à l’état de pleine conscience. Nous avons formulé le problème en deux problèmes d'optimisation du réseau – le problème de couverture minimale des sommets et le problème de flux maximum – pour rechercher la voie de propagation de l'information qui est importante pour réaliser l'état. Dans le problème de la couverture minimale des sommets, nous avons cherché à identifier les régions du cerveau qui sont importantes pour la réalisation de l'état de pleine conscience, et avons identifié huit régions, dont quatre qui ont été suggérées comme étant cohérentes avec les études précédentes. Nous avons formulé le problème comme un problème de flux maximum pour identifier les voies de propagation de l'information dans le cerveau qui contribuent à l'activation de ces quatre régions identifiées. En conséquence, environ 30 % des connexions dans la structure du réseau cérébral de cette étude ont été identifiées, et la voie présentant le débit le plus élevé a été considérée pour caractériser la régulation ascendante des émotions pendant la pleine conscience. Les résultats de cette étude pourraient être utiles pour des interventions plus directes dans le contexte de la pleine conscience, qui sont étudiées par le neurofeedback et d'autres méthodes. En effet, les études existantes n’ont pas clarifié les voies de propagation de l’information qui contribuent à la réalisation des états du réseau cérébral qui caractérisent les états de pleine conscience. En outre, cette approche peut être utile comme méthodologie pour identifier les voies de propagation de l'information dans le cerveau qui contribuent à la réalisation d'activités cognitives humaines d'ordre supérieur, telles que la pleine conscience, au sein de réseaux cérébraux à grande échelle.
Haruka NAKAMURA
Waseda University
Yoshimasa TAWATSUJI
Waseda University
Tatsunori MATSUI
Waseda University
Makoto NAKAMURA
FUJITSU LABORATORIES LTD.
Koichi KIMURA
FUJITSU LABORATORIES LTD.
Hisanori FUJISAWA
FUJITSU LABORATORIES LTD.
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Haruka NAKAMURA, Yoshimasa TAWATSUJI, Tatsunori MATSUI, Makoto NAKAMURA, Koichi KIMURA, Hisanori FUJISAWA, "Formulation of Mindfulness States as a Network Optimization Problem and an Attempt to Identify Key Brain Pathways Using Digital Annealer" in IEICE TRANSACTIONS on Information,
vol. E105-D, no. 11, pp. 1969-1983, November 2022, doi: 10.1587/transinf.2021EDP7228.
Abstract: Although intervention practices like mindfulness meditation have proven effective in treating psychosis, there is no clarity on the mechanism of information propagation in the brain. In this study, we formulated a network optimization problem and searched for the optimal solution using Digital Annealer developed by Fujitsu Ltd. This is inspired by quantum computing and is effective in solving large-scale combinatorial optimization problems to find the information propagation pathway in the brain that contributes to the realization of mindfulness. Specifically, we defined the optimal network state as the state of the brain network that is considered to be associated with the mindfulness state. We formulated the problem into two network optimization problems — the minimum vertex-cover problem and the maximum-flow problem — to search for the information propagation pathway that is important for realizing the state. In the minimum vertex-cover problem, we aimed to identify brain regions that are important for the realization of the mindfulness state, and identified eight regions, including four that were suggested to be consistent with previous studies. We formulated the problem as a maximum-flow problem to identify the information propagation pathways in the brain that contribute to the activation of these four identified regions. As a result, approximately 30% of the connections in the brain network structure of this study were identified, and the pathway with the highest flow rate was considered to characterize the bottom-up emotion regulation during mindfulness. The findings of this study could be useful for more direct interventions in the context of mindfulness, which are being investigated by neurofeedback and other methods. This is because existing studies have not clarified the information propagation pathways that contribute to the realization of the brain network states that characterize mindfulness states. In addition, this approach may be useful as a methodology to identify information propagation pathways in the brain that contribute to the realization of higher-order human cognitive activities, such as mindfulness, within large-scale brain networks.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2021EDP7228/_p
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@ARTICLE{e105-d_11_1969,
author={Haruka NAKAMURA, Yoshimasa TAWATSUJI, Tatsunori MATSUI, Makoto NAKAMURA, Koichi KIMURA, Hisanori FUJISAWA, },
journal={IEICE TRANSACTIONS on Information},
title={Formulation of Mindfulness States as a Network Optimization Problem and an Attempt to Identify Key Brain Pathways Using Digital Annealer},
year={2022},
volume={E105-D},
number={11},
pages={1969-1983},
abstract={Although intervention practices like mindfulness meditation have proven effective in treating psychosis, there is no clarity on the mechanism of information propagation in the brain. In this study, we formulated a network optimization problem and searched for the optimal solution using Digital Annealer developed by Fujitsu Ltd. This is inspired by quantum computing and is effective in solving large-scale combinatorial optimization problems to find the information propagation pathway in the brain that contributes to the realization of mindfulness. Specifically, we defined the optimal network state as the state of the brain network that is considered to be associated with the mindfulness state. We formulated the problem into two network optimization problems — the minimum vertex-cover problem and the maximum-flow problem — to search for the information propagation pathway that is important for realizing the state. In the minimum vertex-cover problem, we aimed to identify brain regions that are important for the realization of the mindfulness state, and identified eight regions, including four that were suggested to be consistent with previous studies. We formulated the problem as a maximum-flow problem to identify the information propagation pathways in the brain that contribute to the activation of these four identified regions. As a result, approximately 30% of the connections in the brain network structure of this study were identified, and the pathway with the highest flow rate was considered to characterize the bottom-up emotion regulation during mindfulness. The findings of this study could be useful for more direct interventions in the context of mindfulness, which are being investigated by neurofeedback and other methods. This is because existing studies have not clarified the information propagation pathways that contribute to the realization of the brain network states that characterize mindfulness states. In addition, this approach may be useful as a methodology to identify information propagation pathways in the brain that contribute to the realization of higher-order human cognitive activities, such as mindfulness, within large-scale brain networks.},
keywords={},
doi={10.1587/transinf.2021EDP7228},
ISSN={1745-1361},
month={November},}
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TY - JOUR
TI - Formulation of Mindfulness States as a Network Optimization Problem and an Attempt to Identify Key Brain Pathways Using Digital Annealer
T2 - IEICE TRANSACTIONS on Information
SP - 1969
EP - 1983
AU - Haruka NAKAMURA
AU - Yoshimasa TAWATSUJI
AU - Tatsunori MATSUI
AU - Makoto NAKAMURA
AU - Koichi KIMURA
AU - Hisanori FUJISAWA
PY - 2022
DO - 10.1587/transinf.2021EDP7228
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E105-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2022
AB - Although intervention practices like mindfulness meditation have proven effective in treating psychosis, there is no clarity on the mechanism of information propagation in the brain. In this study, we formulated a network optimization problem and searched for the optimal solution using Digital Annealer developed by Fujitsu Ltd. This is inspired by quantum computing and is effective in solving large-scale combinatorial optimization problems to find the information propagation pathway in the brain that contributes to the realization of mindfulness. Specifically, we defined the optimal network state as the state of the brain network that is considered to be associated with the mindfulness state. We formulated the problem into two network optimization problems — the minimum vertex-cover problem and the maximum-flow problem — to search for the information propagation pathway that is important for realizing the state. In the minimum vertex-cover problem, we aimed to identify brain regions that are important for the realization of the mindfulness state, and identified eight regions, including four that were suggested to be consistent with previous studies. We formulated the problem as a maximum-flow problem to identify the information propagation pathways in the brain that contribute to the activation of these four identified regions. As a result, approximately 30% of the connections in the brain network structure of this study were identified, and the pathway with the highest flow rate was considered to characterize the bottom-up emotion regulation during mindfulness. The findings of this study could be useful for more direct interventions in the context of mindfulness, which are being investigated by neurofeedback and other methods. This is because existing studies have not clarified the information propagation pathways that contribute to the realization of the brain network states that characterize mindfulness states. In addition, this approach may be useful as a methodology to identify information propagation pathways in the brain that contribute to the realization of higher-order human cognitive activities, such as mindfulness, within large-scale brain networks.
ER -