Zobrazeno 1 - 10
of 54
pro vyhledávání: '"David S Wack"'
Publikováno v:
PLoS ONE, Vol 10, Iss 9, p e0137326 (2015)
It is unclear whether attention deficit hyperactive disorder (ADHD) is a hypodopaminergic or hyperdopaminergic condition. Different sets of data suggest either hyperactive or hypoactive dopamine system. Since indirect methods used in earlier studies
Externí odkaz:
https://doaj.org/article/67f2f9f623834e0e83eff3ae675504c2
Publikováno v:
PLoS ONE, Vol 9, Iss 2, p e88466 (2014)
In our previous study we investigated Masking Level Differences (MLD) using functional Magnetic Resonance Imaging (fMRI), but were unable to confirm neural correlations for the MLD within the auditory cortex and inferior colliculus. Here we have dupl
Externí odkaz:
https://doaj.org/article/203f2a653a2c4056b9ed89933024208b
Autor:
David S Wack, Jennifer L Cox, Claudiu V Schirda, Christopher R Magnano, Joan E Sussman, Donald Henderson, Robert F Burkard
Publikováno v:
PLoS ONE, Vol 7, Iss 7, p e41263 (2012)
INTRODUCTION: Masking level differences (MLDs) are differences in the hearing threshold for the detection of a signal presented in a noise background, where either the phase of the signal or noise is reversed between ears. We use N0/Nπ to denote noi
Externí odkaz:
https://doaj.org/article/29588bf88d3349cfa8d495df8969a991
Publikováno v:
Journal of the American Academy of Audiology. 33(3)
Background The cervical vestibular evoked myogenic potential (cVEMP) is a vestibular response that is produced by the saccule in response to intense, often low-frequency, short-duration auditory stimuli, and is typically recorded from a contracted st
Autor:
David S. Wack, Jean M. Vettel, Sarah F. Muldoon, Henry E. Baidoo-Williams, Matthew Cieslak, Konstantinos Slavakis, Shiva Salsabilian, Scott T. Grafton
Publikováno v:
IEEE Transactions on Signal and Information Processing over Networks. 4:519-533
This paper advocates Riemannian multi-manifold modeling for network-wide time-series analysis: Dynamic brain-network data yield features which are viewed as points in or close to a union of a finite number of submanifolds of a Riemannian manifold. Di
Autor:
Henry E. Baidoo-Williams, Scott T. Grafton, Konstantinos Slavakis, Jean M. Vettel, Shiva Salsabilian, Matthew Cieslak, Sarah F. Muldoon, David S. Wack
Publikováno v:
Wavelets and Sparsity XVII.
This paper introduces Riemannian multi-manifold modeling in the context of brain-network analytics: Brainnetwork time-series yield features which are modeled as points lying in or close to a union of a finite number of submanifolds within a known Rie
Publikováno v:
Current Medical Imaging Reviews. 10:155-162
Publikováno v:
Anesthesia & Analgesia. 119:550-553
Reports of memory impairment after cardiac surgery are controversial. To address this controversy, we used positron emission tomography to examine changes in regional cerebral blood flow (rCBF) during memory processing before and after elective coron
Autor:
Edward D. Huey, A. Donati, Maria Eriksdotter, Jean Paul G. Vonsattel, Alexander Wutzler, Nicole M. Armstrong, T. Rune Nielsen, Charlotte Niederländer, Robert S. Miletich, Vesna Jelic, S. Petrillo, Hanne Gottrup, Elisabeth Steinhagen-Thiessen, Lawrence S. Honig, David S. Wack, Peter L. Kolominsky-Rabas, Eva Baillés, Abel López-Bermejo, Geir Selbæk, Wilhelm Haverkamp, Regine Becker, Amy J. Williams, Jordan Grafman, Philip Wahlster, J. Studer, Birgitte Bo Andersen, Nicole Schupf, Janne Røsvik, Hiroshi Yoshizawa, Gernot Lämmler, Knut Engedal, Milica G. Kramberger, J. Popp, Øyvind Kirkevold, C. Pocnet, Sandra Schaller, John G. Baker, Christine Kriza, Anne Marie Mork Rokstad, Jan H. Lützhøft, Bengt Winblad, Peter Høgh, J. Rossier, Ingemar Kåreholt, Druck Reinhardt Druck Basel, Jurate Saltyte Benth, Gunhild Waldemar, Thomas Andersson, Carme Carrion, Marta Aymerich, A. Von Gunten
Publikováno v:
Dementia and Geriatric Cognitive Disorders. 36:I-IV
Autor:
Matthew Cieslak, Sarah F. Muldoon, Shiva Salsabilian, Konstantinos Slavakis, David S. Wack, JeanM. Vettel, Henry E. Baidoo-Williams, Scott T. Grafton
Publikováno v:
ACSSC
In response to the demand on data-analytic tools that monitor time-varying connectivity patterns within brain networks, the present paper extends the framework of [Slavakis et al., SSP'16] to include kernel-based partial correlations as a tool for cl