J
Jay S. Reidler
Researcher at Harvard University
Publications - 11
Citations - 3006
Jay S. Reidler is an academic researcher from Harvard University. The author has contributed to research in topics: Transcranial direct-current stimulation & Brain stimulation. The author has an hindex of 6, co-authored 9 publications receiving 2570 citations. Previous affiliations of Jay S. Reidler include Spaulding Rehabilitation Hospital.
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Journal ArticleDOI
Functional-Anatomic Fractionation of the Brain's Default Network
Jessica R. Andrews-Hanna,Jay S. Reidler,Jorge Sepulcre,Jorge Sepulcre,Renee Poulin,Randy L. Buckner +5 more
TL;DR: The anatomy and function of the default network is explored across three studies to resolve divergent hypotheses about its contributions to spontaneous cognition and active forms of decision making.
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Evidence for the Default Network's Role in Spontaneous Cognition
TL;DR: In this paper, a set of brain regions known as the default network increases its activity when focus on the external world is relaxed and during such moments, participants change their focus of external attention and engage in spontaneous cognitive processes including remembering the past and imagining the future.
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Effects of Motor Cortex Modulation and Descending Inhibitory Systems on Pain Thresholds in Healthy Subjects
Jay S. Reidler,Mariana E. Mendonca,Marcus B. Santana,Xiaoen Wang,Robert E. Lenkinski,Andrea F. Motta,Andrea F. Motta,Serge Marchand,Lydia Abdul Latif,Felipe Fregni,Felipe Fregni +10 more
TL;DR: It is demonstrated that both noninvasive motor cortex modulation and a descending noxious inhibitory controls paradigm significantly increase pain thresholds in healthy subjects and appear to have an additive effect when combined.
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Investigation of Central Nervous System Dysfunction in Chronic Pelvic Pain Using Magnetic Resonance Spectroscopy and Noninvasive Brain Stimulation
Marcel Simis,Marcel Simis,Jay S. Reidler,Debora Duarte Macea,Ingrid Moreno Duarte,Xiaoen Wang,Robert E. Lenkinski,John C. Petrozza,Felipe Fregni,Felipe Fregni +9 more
TL;DR: This work investigated the contributions of critical pain‐related neural circuits using single‐voxel proton magnetic resonance spectroscopy (MRS) and transcranial direct current stimulation (tDCS) to better understand the central changes associated with chronic pelvic pain.
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Can Natural Language Processing and Artificial Intelligence Automate The Generation of Billing Codes From Operative Note Dictations?
Juno Kim,Andrew Vivas,Varun Arvind,Joseph M. Lombardi,Jay S. Reidler,Scott L. Zuckerman,Nathan J. Lee,Meghana Vulapalli,Eric Geng,Brian Cho,Kazuaki Morizane,Samuel K. Cho,Ronald A. Lehman,Lawrence G. Lenke,K. Daniel Riew +14 more
TL;DR: Combining natural language processing with machine learning is a valid approach for automatic generation of CPT billing codes and the random forest machine learning model outperformed the LSTM deep learning model in this case.