@netneurosci

MIT Press Journal devoted to brain networks at all scales - molecular, neuronal, circuit, systems

 Bloomington, IN
mitpressjournals.org/netn
Joined July 2016
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Just announced: Our 2022 Journal Impact Factor is 🔔4.7🔔 Thanks once again to all authors, reviewers, editors - and our terrific OA publisher @mitpress
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For context, this IF puts us right at, or above, several competing journals offered by commercial publishers (and our APC is much lower). We hope you will choose Network Neuroscience for your next brain-network-related article!
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Network Neuroscience (2023) 7 (1): 351–376. Sex differences in multilayer functional network topology over the course of aging in 37543 UK Biobank participants direct.mit.edu/netn/article/… @MijalkovMite
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Network Neuroscience (2023) 7 (1): 322–350. Multiclass characterization of frontotemporal dementia variants via multimodal brain network computational inference direct.mit.edu/netn/article/…
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Network Neuroscience (2023) 7 (1): 299–321. Multimodal multilayer network centrality relates to executive functioning direct.mit.edu/netn/article/… @lucasbreedt @LindaDouw
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Network Neuroscience (2023) 7 (1): 269–298. Circuit analysis of the Drosophila brain using connectivity-based neuronal classification reveals organization of key communication pathways direct.mit.edu/netn/article/…
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Network Neuroscience (2023) 7 (1): 254–268. Nonoptimal component placement of the human connectome supports variable brain dynamics direct.mit.edu/netn/article/… @ConnectomeLab
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Network Neuroscience (2023) 7 (1): 234–253. 𝓗1 persistent features of the resting-state connectome in healthy subjects direct.mit.edu/netn/article/…
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Network Neuroscience (2023) 7 (1): 213–233. Increased structural connectivity in high schizotypy direct.mit.edu/netn/article/…
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Network Neuroscience (2023) 7 (1): 184–212. The topology, stability, and instability of learning-induced brain network repertoires in schizophrenia direct.mit.edu/netn/article/…
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Network Neuroscience (2023) 7 (1): 160–183. Exploring personalized structural connectomics for moderate to severe traumatic brain injury direct.mit.edu/netn/article/… @PhoebeImms @KCaeyenberghs
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Network Neuroscience (2023) 7 (1): 148–159. Graph theoretical approach to brain remodeling in multiple sclerosis direct.mit.edu/netn/article/… @mohammadhadiara et al

Graph theoretical approach to brain remodeling in multiple sclerosis

Abstract. Multiple sclerosis (MS) is a neuroinflammatory disorder damaging structural connectivity. Natural remodeling processes of the nervous system can, to some extent, restore the damage caused....

direct.mit.edu
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Network Neuroscience (2023) 7 (1): 122–147. Classification and prediction of cognitive performance differences in older age based on brain network patterns using a machine learning approach direct.mit.edu/netn/article/…
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Network Neuroscience (2023) 7 (1): 102–121. Reconfigurations in brain networks upon awakening from slow wave sleep: Interventions and implications in neural communication direct.mit.edu/netn/article/…
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Network Neuroscience (2023) 7 (1): 86–101. Coupling of the spatial distributions between sMRI and PET reveals the progression of Alzheimer’s disease direct.mit.edu/netn/article/…
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Network Neuroscience (2023) 7 (1): 73–85. Dynamical interactions reconfigure the gradient of cortical timescales direct.mit.edu/netn/article/… @PierpaSorre @GRabuffo @eNeuroEiC @ViktorJirsa et al
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Network Neuroscience (2023) 7 (1): 48–72 Stability and dynamics of a spectral graph model of brain oscillations direct.mit.edu/netn/article/… @parulv1 @srinagarajan @ashishrajs
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Network Neuroscience (2023) 7 (1): 22–47. A transformer model for learning spatiotemporal contextual representation in fMRI data direct.mit.edu/netn/article/…
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Network Neuroscience (2023) 7 (1): 1–21. 3M_BANTOR: A regression framework for multitask and multisession brain network distance metrics direct.mit.edu/netn/article/…
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We are very happy and excited that @ImagingNeurosci will soon join the growing family of OA neuro journals (including @netneurosci and @jneurolang) at @mitpress | Again, best of luck to all involved in this important transition
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