Page 18 - GHES-3-2
P. 18

Global Health Economics and
            Sustainability
                                                                        Flow states in neurodivergence: Cognitive integration


            Picó-Pérez,  M.,  Fullana,  M.A.,  Albajes-Eizagirre,  A.,  Vega,  D.,      https://doi.org/10.31234/osf.io/5j4wy
               Marco-Pallarés, J., Vilar, A., et al. (2023). Neural predictors   Uddin, L., Kelly, A., Biswal, B., Castellanos, F., Milham, M., &
               of cognitive-behavior therapy outcome in anxiety-related   Castellanos, X. (2009). Functional connectivity of default
               disorders:  A  meta-analysis  of task-based fMRI  studies.   mode network components: Correlation, anticorrelation,
               Psychological Medicine, 53(8):3387-3395.
                                                                  and causality. Human Brain Mapping, 30:625-637.
            Raichle, M. (2015). The brain’s default mode network.  Annual      https://doi.org/10.1002/hbm.20531
               Review of Neuroscience, 38:433-447.
                                                               van den Engh, M. (2024). “I’ma fish!” Deepening receptivity to
               https://doi.org/10.1146/annurev-neuro-071013-014030
                                                                  neurodiversity: A  neuroscientifically informed integration
            Ramot, M., Kimmich, S., Gonzalez-Castillo, J., Roopchansingh,  V.,   of psychoanalytic psychotherapy, reciprocal prediction, and
               Popal, H., White, E., et al. (2017). Direct modulation of   mindfulness. Neuropsychoanalysis, 26:1-15.
               aberrant  brain  network  connectivity  through  real-time   Vatansever, D., Menon, D., Manktelow, A., Sahakian, B., &
               NeuroFeedback. eLife, 6:e28974.
                                                                  Stamatakis, E. (2015). Default mode network connectivity
               https://doi.org/10.1101/139824                     during task execution. NeuroImage, 122:96-104.
            Rządeczka, M., Wodziński, M., & Moskalewicz, M. (2023).      https://doi.org/10.1016/j.neuroimage.2015.07.053
               Cognitive biases as an adaptive strategy in autism and   Vinogradov, S., Fisher, M., & De Villers-Sidani, E. (2012). Cognitive
               schizophrenia spectrum: The compensation perspective on
               neurodiversity. Frontiers in Psychiatry, 14:1291854.  training for impaired neural systems in neuropsychiatric
                                                                  illness. Neuropsychopharmacology, 37(1):43-76.
            Santarnecchi, E., Momi, D., Sprugnoli, G., Neri, F., Pascual‐
               Leone, A., Rossi, A., et al. (2018). Modulation of network‐  Volkow, N.D., Fowler, J.S., Wang, G.J., Baler, R., & Telang,  F.
               to‐network connectivity via spike‐timing‐dependent   (2009). Imaging dopamine’s role in drug abuse and
               noninvasive brain stimulation.  Human Brain Mapping,   addiction. Neuropharmacology, 56:3-8.
               39(12):4870-4883.                               Wang, Q., Li, H., Li, Y., Lv, Y., Ma, H., Xiang, A., et al. (2021).
                                                                  Resting-state abnormalities in functional connectivity of the
            Savickaite, S. (2024). Using Virtual Reality to Explore Individual
               Differences in Perception Due to Neurodiversity (Doctoral   default mode network in autism spectrum disorder: A meta-
               Dissertation, University of Glasgow).              analysis. Brain Imaging and Behavior, 15:2583-2592.
                                                                  https://doi.org/10.1007/s11682-021-00460-5
            Schauder,  K.B.,  Muller,  C.L.,  Veenstra-VanderWeele,  J.,  &
               Cascio,  C.J. (2015). Genetic variation in serotonin   Wassner, J. (2024). Acceptance and Commitment Therapy
               transporter modulates tactile hyperresponsiveness in ASD.   with  Children:  Applications and  Strategies  for  Anxiety,
               Research in Autism Spectrum Disorders, 10:93-100.  Depression, Autism, ADHD, OCD and More. United States:
                                                                  Jessica Kingsley Publishers.
            Seeburger, D.T., Xu, N., Ma, M., Larson, S., Godwin, C.,
               Keilholz,  S.D.,  et al. (2024). Time-varying functional   Wotruba, D., Michels, L., Buechler, R., Metzler, S., Theodoridou, A.,
               connectivity predicts fluctuations in sustained attention in   Gerstenberg, M., et al. (2014). Aberrant coupling within and
               a serial tapping task.  Cognitive, Affective, and Behavioral   across the default mode, task-positive, and salience network
               Neuroscience, 24(1):111-125.                       in subjects at risk for psychosis.  Schizophrenia  Bulletin,
                                                                  40(5):1095-1104.
            Senkowski, D., Ziegler, T., Singh, M., Heinz, A., He, J., Silk, T.,
               et al. (2024). Assessing inhibitory control deficits in adult      https://doi.org/10.1093/schbul/sbt161
               ADHD: A systematic review and meta-analysis of the stop-  Yoshida, K., Sawamura, D., Ogawa, K., Ikoma, K., Asakawa,  K.,
               signal task. Neuropsychology Review, 34(2):548-567.
                                                                  Yamauchi,  T.,  et al.  (2014).  Flow experience  during
            Spreng, R. (2012). The fallacy of a “task-negative” network.   attentional training improves cognitive functions in patients
               Frontiers in Psychology, 3:145.                    with traumatic brain injury: An exploratory case study.
                                                                  Hong Kong Journal of Occupational Therapy, 24:81-87.
               https://doi.org/10.3389/fpsyg.2012.00145
                                                                  https://doi.org/10.1016/j.hkjot.2015.01.001
            Tondelli, M., Manigrasso, M., & Zamboni, G. (2024). Impaired self-
               awareness in Parkinson’s and Huntington’s diseases: A literature   Yuan, Y., Pan, X., & Wang, R. (2021). Biophysical mechanism of
               review of neuroimaging correlates. Brain Sciences, 14(3):204.  the interaction between default mode network and working
                                                                  memory network. Cognitive Neurodynamics, 15(6):1101-1124.
            Trambaiolli, L., Kohl, S., Linden, D., & Mehler, D. (2020).
               Neurofeedback training in major depressive disorder:   Zhuang, K., Zeitlen, D.C., Beaty, R.E., Vatansever, D., Chen, Q.,
               A  systematic review of clinical efficacy, study quality and   & Qiu, J. (2023). Diverse functional interaction driven by
               reporting practices. Neuroscience and Biobehavioral Reviews,   control-default  network  hubs  supports  creative  thinking.
               125:33-56.                                         Cerebral Cortex, 33(23):11206-11224.





            Volume 3 Issue 2 (2025)                         10                       https://doi.org/10.36922/ghes.4345
   13   14   15   16   17   18   19   20   21   22   23