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We propose Quantum Brain Networks (QBraiNs) as a new interdisciplinary field integratingknowledge and methods from neurotechnology, artificial intelligence, and quantum computing. Theobjective is to develop an enhanced connectivity between the human brain and quantum computersfor a variety of disruptive applications. We foresee the emergence of hybrid classical-quantumnetworks of wetware and hardware nodes, mediated by machine learning techniques and brain–machine interfaces. QBraiNs will harness and transform in unprecedented ways arts, science,technologies, and entrepreneurship, in particular activities related to medicine, Internet of Humans,intelligent devices, sensorial experience, gaming, Internet of Things, crypto trading, and business. ; European Union (EU) QMiCS (820505) and OpenSuperQ (820363) projects ; Spanish GovernmentPGC2018-095113-B-I00, PID2019-104002GB-C21, PID2019-104002GB-C22 (MCIU/AEI/FEDER, UE) ; Basque Government IT986-16 ; Junta de Andalucía (P20-00617 andUS-1380840) ; National Natural Science Foundation of China (NSFC)(12075145), STCSM (2019SHZDZX01-ZX04, 18010500400 and 18ZR1415500)

AbstractFostering creative minds has always been a premise to ensure adaptation to new challenges of human civilization. While some alternative educational settings (i.e., Montessori) were shown to nurture creative skills, it is unknown how they impact underlying brain mechanisms across the school years. This study assessed creative thinking and resting‐state functional connectivity via fMRI in 75 children (4–18 y.o.) enrolled either in Montessori or traditional schools. We found that pedagogy significantly influenced creative performance and underlying brain networks. Replicating past work, Montessori‐schooled children showed higher scores on creative thinking tests. Using static functional connectivity analysis, we found that Montessori‐schooled children showed decreased within‐network functional connectivity of the salience network. Moreover, using dynamic functional connectivity, we found that traditionally‐schooled children spent more time in a brain state characterized by high intra‐default mode network connectivity. These findings suggest that pedagogy may influence brain networks relevant to creative thinking—particularly the default and salience networks. Further research is needed, like a longitudinal study, to verify these results given the implications for educational practitioners. A video abstract of this article can be viewed at https://www.youtube.com/watch?v=xWV_5o8wB5g .Research Highlights
Most executive jobs are prospected to be obsolete within several decades, so creative skills are seen as essential for the near future.
School experience has been shown to play a role in creativity development, however, the underlying brain mechanisms remained under‐investigated yet.
Seventy‐five 4–18 years‐old children, from Montessori or traditional schools, performed a creativity task at the behavioral level, and a 6‐min resting‐state MR scan.
We uniquely report preliminary evidence for the impact of pedagogy on functional brain networks.

Interneurons play a critical role in precise control of network operation. Indeed, higher brain capabilities such as working memory, cognitive flexibility, attention, or social interaction rely on the action of GABAergic interneurons. Evidence from excitatory neurons and synapses has revealed astrocytes as integral elements of synaptic transmission. However, GABAergic interneurons can also engage astrocyte signaling; therefore, it is tempting to speculate about different scenarios where, based on particular interneuron cell type, GABAergic-astrocyte interplay would be involved in diverse outcomes of brain function. In this review, we will highlight current data supporting the existence of dynamic GABAergic-astrocyte communication and its impact on the inhibitory-regulated brain responses, bringing new perspectives on the ways astrocytes might contribute to efficient neuronal coding. ; The authors are grateful to Dr. C. Sánchez-Puelles and C. GonzálezArias for helpful comments. NB Revisions was used for manuscript editing. This work was supported by the PhD fellowship program (MINECO, BES-2014-067594) to SM; and MINECO grant (BFU2016- 75107-P), and and Cajal Blue Brain Project (Spanish partner of the Blue Brain Project initiative from EPFL) and the European Union Horizon 2020 research and innovation program under grant agreement No. 720270 (Human Brain Project, https://www.humanbrainproject.eu/) to GP.

AbstractNovel and valuable objects are motivationally attractive for animals including primates. However, little is known about how novelty and value processing is organized across the brain. We used fMRI in macaques to map brain responses to visual fractal patterns varying in either novelty or value dimensions and compared the results with the structure of functionally connected brain networks determined at rest. The results show that different brain networks possess unique combinations of novelty and value coding. One network identified in the ventral temporal cortex preferentially encoded object novelty, whereas another in the parietal cortex encoded the learned value. A third network, broadly composed of temporal and prefrontal areas (TP network), along with functionally connected portions of the striatum, amygdala, and claustrum, encoded both dimensions with similar activation dynamics. Our results support the emergence of a common currency signal in the TP network that may underlie the common attitudes toward novel and valuable objects.

AbstractThere is a growing need to understand the global impact of poverty on early brain and behavioural development, particularly with regard to key cognitive processes that emerge in early development. Although the impact of adversity on brain development can trap children in an intergenerational cycle of poverty, the massive potential for brain plasticity is also a source of hope: reliable, accessible, culturally agnostic methods to assess early brain development in low resource settings might be used to measure the impact of early adversity, identify infants for timely intervention and guide the development and monitor the effectiveness of early interventions. Visual working memory (VWM) is an early marker of cognitive capacity that has been assessed reliably in early infancy and is predictive of later academic achievement in Western countries. Here, we localized the functional brain networks that underlie VWM in early development in rural India using a portable neuroimaging system, and we assessed the impact of adversity on these brain networks. We recorded functional brain activity as young children aged 4–48 months performed a VWM task. Brain imaging results revealed localized activation in the frontal cortex, replicating findings from a Midwestern US sample. Critically, children from families with low maternal education and income showed weaker brain activity and poorer distractor suppression in canonical working memory areas in the left frontal cortex. Implications of this work are far‐reaching: it is now cost‐effective to localize functional brain networks in early development in low‐resource settings, paving the way for novel intervention and assessment methods.

Functional connectivity MRI (fcMRI) has become instrumental in facilitating research of human brain network organization in terms of coincident interactions between positive and negative synchronizations of large-scale neuronal systems. Although there is a common agreement concerning the interpretation of positive couplings between brain areas, a major debate has been made in disentangling the nature of negative connectivity patterns in terms of its emergence in several methodological approaches and its significance/meaning in specific neuropsychiatric diseases. It is still not clear what information the functional negative correlations or connectivity provides or how they relate to the positive connectivity. Through implementing stepwise functional connectivity (SFC) analysis and studying the causality of functional topological patterns, this study aims to shed light on the relationship between positive and negative connectivity in the human brain functional connectome. We found that the strength of negative correlations between voxel-pairs relates to their positive connectivity path-length. More importantly, our study describes how the spatio-temporal patterns of positive connectivity explain the evolving changes of negative connectivity over time, but not the other way around. This finding suggests that positive and negative connectivity do not display equivalent forces but shows that the positive connectivity has a dominant role in the overall human brain functional connectome. This phenomenon provides novel insights about the nature of positive and negative correlations in fcMRI and will potentially help new developments for neuroimaging biomarkers. ; This research was supported by grants from the National Institutes of Health K23EB019023 to JS, T32EB013180-06 to LO-T, Postdoctoral Fellowship Program from the Basque Country Government to ID and R01EB022574, R01MH108467 to JG, and Indiana Clinical and Translational Sciences Institute (UL1TR001108) to JG.

Abstract
Intracranial EEG (iEEG) studies have suggested that the conscious perception of pain builds up from successive contributions of brain networks in less than 1 s. However, the functional organization of cortico-subcortical connections at the multisecond time scale, and its accordance with iEEG models, remains unknown. Here, we used graph theory with modular analysis of fMRI data from 60 healthy participants experiencing noxious heat stimuli, of whom 36 also received audio stimulation. Brain connectivity during pain was organized in four modules matching those identified through iEEG, namely: 1) sensorimotor (SM), 2) medial fronto-cingulo-parietal (default mode-like), 3) posterior parietal-latero-frontal (central executive-like), and 4) amygdalo-hippocampal (limbic). Intrinsic overlaps existed between the pain and audio conditions in high-order areas, but also pain-specific higher small-worldness and connectivity within the sensorimotor module. Neocortical modules were interrelated via "connector hubs" in dorsolateral frontal, posterior parietal, and anterior insular cortices, the antero-insular connector being most predominant during pain. These findings provide a mechanistic picture of the brain networks architecture and support fractal-like similarities between the micro-and macrotemporal dynamics associated with pain. The anterior insula appears to play an essential role in information integration, possibly by determining priorities for the processing of information and subsequent entrance into other points of the brain connectome.

AbstractPrior work has extensively studied neural deficits in children with reading impairment (RI) in their native language but has rarely examined those of RI children in their second language (L2). A recent study revealed that the function of the local brain regions was disrupted in children with RI in L2, but it is not clear whether the disruption also occurs at a large‐scale brain network level. Using fMRI and graph theoretical analysis, we explored the topology of the whole‐brain functional network during a phonological rhyming task and network reconfigurations across task and short resting phases in Chinese children with English reading impairment versus age‐matched typically developing (TD) children. We found that, when completing the phonological task, the RI group exhibited higher local network efficiency and network modularity compared with the TD group. When switching between the phonological task and the short resting phase, the RI group showed difficulty with network reconfiguration, as reflected in fewer changes in the local efficiency and modularity properties and less rearrangement of the modular communities. These findings were reproducible after controlling for the effects of in‐scanner accuracy, participant gender, and L1 reading performance. The results from the whole‐brain network analyses were largely replicated in the task‐activated network. These findings provide preliminary evidence supporting that RI in L2 is associated with not only abnormal functional network organization but also poor flexibility of the neural system in responding to changing cognitive demands.

Only Vanderbilt University affiliated authors are listed on VUIR. For a full list of authors, access the version of record at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6751331/ ; The annual deep brain stimulation (DBS) Think Tank aims to create an opportunity for a multidisciplinary discussion in the field of neuromodulation to examine developments, opportunities and challenges in the field. The proceedings of the Sixth Annual Think Tank recapitulate progress in applications of neurotechnology, neurophysiology, and emerging techniques for the treatment of a range of psychiatric and neurological conditions including Parkinson's disease, essential tremor, Tourette syndrome, epilepsy, cognitive disorders, and addiction. Each section of this overview provides insight about the understanding of neuromodulation for specific disease and discusses current challenges and future directions. This year's report addresses key issues in implementing advanced neurophysiological techniques, evolving use of novel modulation techniques to deliver DBS, ans improved neuroimaging techniques. The proceedings also offer insights into the new era of brain network neuromodulation and connectomic DBS to define and target dysfunctional brain networks. The proceedings also focused on innovations in applications and understanding of adaptive DBS (closed-loop systems), the use and applications of optogenetics in the field of neurostimulation and the need to develop databases for DBS indications. Finally, updates on neuroethical, legal, social, and policy issues relevant to DBS research are discussed. ; AR-Z serves as a consultant for the National Parkinson Foundation, and has received consulting honoraria from Medtronic, Boston Scientific, and Wilson Therapeutics and has participated as a site PI and/or co-PI for several NIH, foundation, and industry sponsored trials over the years but has not received honoraria. JG work was supported in part by the European Union's Horizon 2020 Research and Innovation Programme under grant agreement 720270: HBP SGA1; by federal funds UL1TR001409 from the National Center for Advancing Translational Sciences (NCATS), National Institutes of Health, through the Clinical and Translational Science Awards Program (CTSA), a trademark of the Department of Health and Human Services, part of the Roadmap Initiative, "ReEngineering the Clinical Research Enterprise"; by funding from the AEHS Foundation, in conjunction with Project NeuroHOPE; and from the Austin and Ann O'Malley Visiting Chair in Bioethics of Loyola Marymount University. EB was supported by J. Doerr, the HHMI-Simons Faculty Scholars Program, the Open Philanthropy Project, Human Frontier Science Program (RGP0015/2016), US Army Research Laboratory and the US Army Research Office (W911NF1510548), US-Israel Binational Science Foundation (2014509), and NIH (2R01-DA029639 and 1R01-GM104948). VG work was primarily supported by the National Institutes of Health (NIH) Director's New Innovator grant DP2NS087949 and PECASE, National Institute on Aging grant R01AG047664, BRAIN grant U01NS090577, SPARC grant OT2OD023848-01, and the Defense Advanced Research Projects Agency (DARPA) Biological Technologies Office. Additional funding included the NSF NeuroNex Technology Hub grant 1707316 and funds from the Curci Foundation, the Beckman Institute, and the Rosen Center at Caltech. AG is supported by the NIH/NCATS Clinical and Translational Science Awards to the University of Florida UL1TR001427, KL2TR001429, and TL1TR001428. PS is a recipient of funding from the National Institutes of Health (R01 NS090913 and UH3 NS 100544) and from the Defense Advanced Research Projects Agency (DARPA). SS acknowledges support from the DARPA Restoring Active Memory (RAM) program (Co-operative Agreement N66001-14-2-4032) and NIH Grants MH104606 and 1S10OD018211-01. CM work was supported by the National Institutes of Health Grants R01 MH106173 and R01 NS086100. CM is a paid consultant for Boston Scientific Neuromodulation and Kernel, as well as a shareholder in the following companies: Surgical Information Sciences, Autonomic Technologies, Cardionomic, Enspire DBS, and Neuros Medical. MF work was supported by the NIH National Institute of Neurological Disorders and Stroke (K23NS083741) and Dystonia Medical Research Foundation. HB-S work was supported by the NINDS Grant 5 R21 NS096398-02, the Michael J. Fox Foundation, the Robert and Ruth Halperin Foundation, the John A. Blume Foundation, the Helen M. Cahill Award for Research in Parkinson's Disease, and Medtronic, Inc., who provided the devices used in this study but no additional financial support. HM work was supported by the NIH Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative (UH3NS103550) and the Hope for Depression Research Foundation. NP reports support by grants UH3NS103549, R01NS097782, and U01NS098961 from the National Institute of Neurological Disorders and Stroke (NINDS). AHG work was supported by grants from the Brain and Behavior Research Foundation (National Alliance for Research on Schizophrenia and Depression Young Investigator Grant), the Parkinson's Disease Foundation, and the NIH Intramural Research Program. MC work was funded by a Whitehall Research grant (Grant ID#2017-12-54). GL-M work has been funded by the National Institutes of Health (NIH) grant R00HG008689. MR work has been supported by the National Institutes of Health through Grant Number UL1-TR-001857. P-FD acknowledges the National Institutes of Health (NIH) for their support of Neurotargetting LLC and their CranialSuite clinical software (R01-EB006136 and R01-NS095291). NH is a shareholder of Surgical Information Sciences, Inc. and holds a patent related to high-resolution brain image system (U.S. Patent 9600778). This study was partially supported by the National Institutes of Health (R01-NS085188, P41 EB015894, and P30 NS076408) and the University of Minnesota Udall center (P50NS098573). JW acknowledges grant support by NIH 1K01ES025436. KB reports support from NIH NINDS NS092730. AK and HC work was supported by National Institutes of Health grant T90 DA032436, National Science Foundation grant EEC-1028725, the Department of Defense through the National Defense and Engineering Graduate Fellowship program, and a donation by Medtronic. RG work was supported by NIH grants (NS090913-01 and NS100544-02) and the UC President's Postdoctoral Fellowship. MO serves as a consultant for the National Parkinson Foundation, and has received research grants from NIH, NPF, the Michael J. Fox Foundation, the Parkinson Alliance, Smallwood Foundation, the BachmannStrauss Foundation, the Tourette Syndrome Association, and the UF Foundation. MO's DBS research is supported by grants R01 NR014852 and R01NS096008 from the National Institutes of Health. MO has previously received honoraria, but in the past > 60 months has received no support from industry. MO has received royalties for publications with Demos, Manson, Amazon, Smashwords, Books4Patients, and Cambridge (movement disorders books). MO is an associate editor for New England Journal of Medicine Journal Watch Neurology. MO has participated in CME and educational activities on movement disorders (in the last 36 months) sponsored by PeerView, Prime, QuantiaMD, WebMD, Medicus, MedNet, Henry Stewart, and by Vanderbilt University. The institution and not MO receives grants from Medtronic, Abbvie, Allergan, and ANS/St. Jude, and the PI has no financial interest in these grants. MO has participated as a site PI and/or co-PI for several NIH, foundation, and industry sponsored trials over the years but has not received honoraria.