K
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Kevin S. Holly's research investigates the use of rodent models to characterize relationships among neurological conditions, sleep patterns, and memory. He has developed automated methods for detecting sleep spindles in rodents, utilizing MATLAB applications with complementary search algorithms. His work also includes multimodal classification of mild traumatic brain injury, examining the coupling between structural and functional connectomes. Dr. Holly has published 12 works, with 161 citations, and holds an h-index of 5. He collaborates with Aaron S. Kemp, Linda Larson‐Prior, Sadie A. Villarrubia, and Allison C. Kumler at the University of Arkansas for Medical Sciences, with whom he has co-authored two publications each.
Metrics
- h-index: 5
- Publications: 10
- Citations: 156
Selected Publications
-
Automated rodent sleep spindle detector: MATLAB app using two complementary search algorithms (2023)
Collaboration Network
Top Collaborators
John E. Merten
Barrow Neurological Institute
2 shared publications
In database
- The use of rodent models to better characterize the relationship among epilepsy, sleep, and memory
- Automated rodent sleep spindle detector: MATLAB app using two complementary search algorithms
Sadie A. Villarrubia
Barrow Neurological Institute
2 shared publications
In database
- The use of rodent models to better characterize the relationship among epilepsy, sleep, and memory
- Automated rodent sleep spindle detector: MATLAB app using two complementary search algorithms
Aaron S. Kemp
University of Arkansas for Medical Sciences
2 shared publications
In database
- The use of rodent models to better characterize the relationship among epilepsy, sleep, and memory
- Automated rodent sleep spindle detector: MATLAB app using two complementary search algorithms
Allison C. Kumler
MathWorks (United States)
2 shared publications
In database
- The use of rodent models to better characterize the relationship among epilepsy, sleep, and memory
- Automated rodent sleep spindle detector: MATLAB app using two complementary search algorithms
Linda Larson‐Prior
MathWorks (United States)
2 shared publications
In database
- The use of rodent models to better characterize the relationship among epilepsy, sleep, and memory
- Automated rodent sleep spindle detector: MATLAB app using two complementary search algorithms
Teresa A. Murray
Barrow Neurological Institute (US)
2 shared publications
- The use of rodent models to better characterize the relationship among epilepsy, sleep, and memory
- Automated rodent sleep spindle detector: MATLAB app using two complementary search algorithms
Ajay Peddada
Rutgers, The State University of New Jersey (US)
1 shared publication
- Multimodal Classification of Mild Traumatic Brain Injury Reveals Local Coupling Between Structural and Functional Connectomes
Tejaswi Sudhakar
Rutgers, The State University of New Jersey (US)
1 shared publication
- Multimodal Classification of Mild Traumatic Brain Injury Reveals Local Coupling Between Structural and Functional Connectomes
Christina Ledbetter
Louisiana State University in Shreveport (US)
1 shared publication
- Multimodal Classification of Mild Traumatic Brain Injury Reveals Local Coupling Between Structural and Functional Connectomes
Christopher Talbot
Johnson University (US)
1 shared publication
- Multimodal Classification of Mild Traumatic Brain Injury Reveals Local Coupling Between Structural and Functional Connectomes
Daniel Valdivia
Johnson University (US)
1 shared publication
- Multimodal Classification of Mild Traumatic Brain Injury Reveals Local Coupling Between Structural and Functional Connectomes
Piyush Kalakoti
Johns Hopkins University (US)
1 shared publication
- Multimodal Classification of Mild Traumatic Brain Injury Reveals Local Coupling Between Structural and Functional Connectomes
Elizabeth E. Ginalis
Rutgers, The State University of New Jersey (US)
1 shared publication
- Multimodal Classification of Mild Traumatic Brain Injury Reveals Local Coupling Between Structural and Functional Connectomes
Travis R. Quinoa
Rutgers, The State University of New Jersey (US)
1 shared publication
- Multimodal Classification of Mild Traumatic Brain Injury Reveals Local Coupling Between Structural and Functional Connectomes
Benjamin J. Barker
Louisiana State University in Shreveport (US)
1 shared publication
- Multimodal Classification of Mild Traumatic Brain Injury Reveals Local Coupling Between Structural and Functional Connectomes
Similar Researchers
Based on overlapping research topics
Tatiana Wolfe
University of Arkansas for Medical Sciences
Neuroscience and Neuropharmacology Research
Neurological disorders and treatments
Behavioral and Psychological Studies
James Hyde
Southern Arkansas University
Neuroscience and Neuropharmacology Research
Neurological disorders and treatments
Behavioral and Psychological Studies
Claudia Mercedes Reyes Fuentes
Arkansas Agricultural Experiment Station
Neuroscience and Neuropharmacology Research
Neurological disorders and treatments
Medical Imaging Techniques and Applications
Annamarie Stehli Nguyen
University of Arkansas at Fayetteville
Neuroscience and Neuropharmacology Research
Sleep and related disorders
Behavioral and Psychological Studies
Clint Kilts
University of Arkansas for Medical Sciences
Neuroscience and Neuropharmacology Research
Neurological disorders and treatments
Behavioral and Psychological Studies
Timothy J. Flanigan
National Center for Toxicological Research
Neuroscience and Neuropharmacology Research
Neurological disorders and treatments
Behavioral and Psychological Studies