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Personalizing neuromodulation
Journal article   Open access   Peer reviewed

Personalizing neuromodulation

John D. Medaglia, Brian Erickson, Jared Zimmerman and Apoorva Kelkar
International journal of psychophysiology, v 154
01 Aug 2020
PMID: 30685229
url
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6824943View
Accepted (AM)Open Access (License Unspecified) Open

Abstract

Life Sciences & Biomedicine Neurosciences Neurosciences & Neurology Physiology Psychology Psychology, Biological Psychology, Experimental Science & Technology Social Sciences
In the era of "big data", we are gaining rich person-specific information about neuroanatomy, neural function, and cognitive functions. However, the optimal ways to create precise approaches to optimize individuals' mental functions in health and disease are unclear. Multimodal analysis and modeling approaches can guide neuromodulation by combining anatomical networks, functional signal analysis, and cognitive neuroscience paradigms in single subjects. Our progress could be improved by progressing from statistical fits to mechanistic models. Using transcranial magnetic stimulation as an example, we discuss how integrating methods with a focus on mechanisms could improve our predictions TMS effects within individuals, refine our models of health and disease, and improve our treatments.

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16 citations in Scopus

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

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Collaboration types
Domestic collaboration
Web of Science research areas
Neurosciences
Physiology
Psychology
Psychology, Biological
Psychology, Experimental
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