S Davis Headshot
Principal Investigator
Assistant Professor in Neurology
Assistant Professor in Pathology
Assistant Professor in Psychiatry and Behavioral Sciences
Member of the Center for Cognitive Neuroscience
Contact Information

Campus mail: B243q LSRC, Durham, NC 27708

Phone: (919) 668-2299

Email: simon.davis@duke.edu

Twitter: @woodforbrains

Location
227E Bryan Research Building, 311 Research Dr

Volunteer for a Study

The Duke-UNC Alzheimer’s Disease Research Center’s Memory & Aging Study works to identify the biological factors involved in normal brain aging and disease with the help of a diverse group of young and older people with and without memory impairments. 

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About us

Our lab focuses on three kinds of research: memory studies, white matter in the brain, and brain stimulation.

Our first research focus examines our ability to form abstract representations of objects in semantic memory is crucial to language and thought. However, it's unclear how semantic memory influences and is influenced by the organization of complex representational structures. We have shown how feature similarity across a wide set of items predicts distinct forms of episodic memory performance. 

Second, the integrity of cerebral white matter is critical for efficient cognitive functioning. Our lab finds interesting ways to use diffusion weighted imaging (DWI) to ask novel questions about how white matter supports healthy cognitive function. DWI measures the directional displacement of molecular water, and as a result can characterize the properties of white matter that combine to restrict diffusivity in a spatially coherent manner.

Thirdly, over the past few decades, transcranial magnetic stimulation (TMS) has developed into a powerful tool to causally establish brain-behavior relationships. The goal of our work here is to understand how differences in stimulation parameters map onto these global network dynamics, or how cognitive states can be selectively targeted using dynamic spatiotemporal signals distributed over large-scale networks of the brain.

We are located in Durham, North Carolina and are a part of both the Duke Neurology Department and the Center for Cognitive Neuroscience at Duke University. 

Our Research

Our primary focus is investigating white matter changes in the aging brain, examining representations of semantic memory networks, and probing the effects of TMS on older adults. We are located in Durham, North Carolina and are a part of the Department of Neurology and the Center for Cognitive Neuroscience at Duke University.

White matter changes in Normal Aging and ADBlue Painted Brain

The integrity of cerebral white matter is critical for efficient cognitive functioning. Our lab finds interesting ways to use diffusion weighted imaging (DWI) to ask novel questions about how white matter supports healthy cognitive function. DWI measures the directional displacement of molecular water and as a result can characterize the properties of white matter that combine to restrict diffusivity in a spatially coherent manner.

Semantic Memory Networks

Our ability to form abstract representations of objects in semantic memory is crucial to language and thought. The utility of this information relies both on the representations of sensory-motor feature knowledge stored in long-term memory and the executive processes required to retrieve, manipulate, and evaluate this semantic knowledge in a task-relevant manner.Semantic connections illustration

The explosion of fMRI-based representational similarity analyses (RSA) have helped to elucidate the functional correlates of object representation. What is less clear is how memory influences and is influenced by the organization of complex representational structures. We have shown how feature similarity across a wide set of items predicts distinct forms of episodic memory performance. Subjects named everyday objects during fMRI and returned a day later to make old/new judgments on either conceptual (old/new words) or perceptual information (same/exemplar images).

Brain Stimulation Effects on Networks in AgingBrain with connections within

As populations experience a rapid growth of its older segments, a major neuroscientific research goal is to increase our knowledge about mechanisms that sustain healthy brain aging, as well as to promote projects that may help to prevent neuropsychiatric age-associated disorders. Over the past few decades, transcranial magnetic stimulation (TMS) has developed into a powerful tool to causally establish brain-behavior relationships. The goal of our work here is to understand how differences in stimulation parameters map onto these global network dynamics, or how cognitive states can be selectively targeted using dynamic spatiotemporal signals distributed over large-scale networks of the brain.

Our Team

JT Galla

Undergraduate Researcher

JT Galla is an undergraduate senior at Duke University majoring in Neuroscience with minors in Chemistry and Computational Biology & Bioinformatics. At Duke, he has conducted research on clinical trials involving rTMS as a therapeutic for PTSD and smoking cessation with veterans, and has also assisted in fMRI data analysis for a study on TMS-coupled Cognitive Behavioral Therapy.

Matthew Slayton

Graduate Student

Matthew Slayton is a PhD Student in the Psychology and Neuroscience program at Duke University. He studies neural representation of concepts, memory, and Alzheimer’s Disease. He earned his BA in Neurolinguistics at Duke, an MA in Philosophy of Biology at the University of Chicago, and an MM in Music Composition at San Francisco Conservatory of Music.

Margaret (Mags) McAllister

Clinical Research Coordinator

Margaret (Mags) McAllister is Clinical Research Coordinator in the Electric Dinosaur Lab. She graduated from UNC-Chapel Hill in 2018 with a B.A. in Psychology and Neuroscience. Mags is generally interested in using neuroimaging tools to better understand how the developing brain learns over the lifespan. She previously worked on research in early detection and intervention of disordered development including ASD, ADHD, and Anxiety. She's a harpist who loves baking and dabbling in amateur triathlons.  

Lifu Deng

Graduate Student

Lifu Deng is a graduate student in the CNAP program. He graduated from Shanghai Jiao Tong University with B.S. in Biomedical Engineering & Applied Mathematics, and M.S. in Biomedical Engineering. Lifu is interested in the dynamics of functional networks in the brain, and how it is influenced by structural connectivity and stimulation. Lifu enjoys outdoor activities and playing music. He’s an amateur in botanics who used to own a collection of bizarre-looking cacti, succulents, and orchids before coming to Duke.

Lab Alumni

  • Amanda Szymanski – Research Technician
  • Daisy Banta - Research Technician
  • Courtney Crowell - Research Technician
  • Devi Lakhlani - Undergraduate Researcher
  • Mariam Hovhannisyan - Research Technician
  • Olga Lucia Gamboa Arana, PhD - Post Doctorate

Publications

Preprints

Hovhannisyan M, Geib B, Clarke A, Cicchinelli R, Cabeza R, Davis SWin review. The Visual and Semantic Features that Predict Object Memory: Concept Property Norms for 1000 Object Images. preprinthttps://psyarxiv.com/nqmjt/

Cooper RA, Kurkela KA, Davis SW, Ritchey M. in review. Mapping the organization and dynamics of the posterior medial network during movie watching. preprint: https://www.biorxiv.org/content/10.1101/2020.10.21.348953v1.

Beynel L, Campbell E, Naclerio N, Galla JT, Ghosal A, Michael AM, Kimbrel NA, Davis SW, Appelbaum LG. in review. The effect of functionally-guided-connectivity-based rTMS on amygdala activation
preprint: https://www.biorxiv.org/content/10.1101/2020.10.13.338483v1.


Journal Articles

2020

Davis SW, Geib BR, Wing EA, Wang W-C, Hovhannisyan M, Monge Z, Cabeza R. Visual and semantic representations predict subsequent memory in perceptual and conceptual memory tests. 2020. Cerebral Cortex. 

Beynel L*, Deng L*, Crowell CA, Dannhauer M, Palmer H, Hilbig SA, Peterchev AV, Luber B, Lisanby SH, Cabeza R, Appelbaum LG, Davis SW. 2020. Structural Controllability Predicts Functional Patterns and Brain Stimulation Benefits Associated with Working Memory.” J Neurosci 40(35): 6770-6778. 

Cabeza R, Becker M, Davis SW. Are the hippocampus and its network necessary for creativity? 2020. PNAS. 117 (25), 13870-13872. 

Davis SW*, Crowell CA*, Beynel L, Deng L, Lakhlani D, Hilbig SA, Palmer H, Peterchev A, Luber BL, Lisanby SH, Appelbaum LG, Cabeza R. 2020. Older adults benefit from more widespread brain network integration during working memory. Neuroimage, 116959. 

Gamboa OL, Brito A, Abzug Z, D’Arbeloff T, Beynel L, Wing EA, Dannhauer M, Palmer H, Hilbig SA, Crowell CA, Liu S, Donaldson R, Cabeza R, Davis SW, Peterchev AV, Sommer MA, Appelbaum LG. 2020. Application of long-interval paried-pulse transcranial magnetic stimulation to motion-sensitive visual cortex does not lead to changes in motion discrimination. Neuroscience Letters.

Beynel L*, Davis SW*, Crowell CA, Hilbig SA, Dannhauer M, Lim W, Palmer H , Hilbig SA, Brito A, Hile C, Luber B, Lisanby SH, Peterchev AV, Cabeza R, Appelbaum LG. 2020. Site-specific effects of online rTMS during a working memory task in healthy older adults. Brain Sciences. 10 (5), 255. 

Wing EA, Geib BR, Wang WC, Monge Z, Davis SW, Cabeza R. 2020. Cortical overlap and cortica-hippocampal interactions predict subsequent true and false memory. Journal of Neuroscience. 40 (9), 1920-1930. 

2019

Beynel L, Appelbaum LG, Luber B, Crowell CA, Hilbig SA, Lim W, Nguyen D, Chrapliwy NA, Davis SW, Cabeza R, Lisanby SH, Deng Z. 2019. Effects of online repetitive transcranial magnetic stimulation (TMS) on cognitive processing: A meta-analysis and recommendations for future studies. Neuroscience and Behavioral Reviews. 107, 45-58. 

Beynel L, Davis SW, Crowell CA, Hilbig SA, Lim W, Nguyen D  Palmer H , Brito A, Peterchev AV, Luber B, Lisanby SH, Cabeza R, Appelbaum LG. 2019. Online repetitive transcranial magnetic stimulation during working memory in younger and older adults: A randomized within-subject comparison. 2019. PLoS one. 14 (3), e0213707. 

2018

Wang W, Wing EA, Murphy DLK, Luber B, Lisanby SH, Cabeza R, Davis SW. 2018. Excitatory TMS Boosts Memory Representations.Cognitive Neuroscience.

Davis SW, Fink, TA, Hayes SA, Cabeza R. Cooperative Contributions of Structural and Functional Connectivity to Successful Memory in Aging. 2018. Network Neuroscience. 

Davis SW, Crowell CA, Beynel L, Deng L, Lakhlani D, Hilbig SA, Lim W, Nguyen D, Palmer H, Peterchev A, Luber BL, Lisanby SH, Appelbaum LG, Cabeza R. 2018. Complementary topology of maintenance and manipulation brain networks in working memory. 

Davis SW*, Wing EA*, Cabeza R. Contributions of the ventral parietal cortex to declarative memory. 2018. In: Vallar G and Coslett HB, eds. Handbook of Clinical Neurology: The Parietal Lobe. San Diego: Elsevier BV, 2018.

2017

Davis SW, Murphy DM, Luber BL, Lisanby SH, Cabeza R. Frequency-specific neuromodulation of local and distant connectivity in aging and episodic memory function. 2017. Human Brain Mapping

2016

Davis SW, Stanley ML, Moscovitch M, Cabeze R. Resting-state networks do not determine cognitive function networks. 2016. Language, Cognition, and Neuroscience. 32, 6: 669-673. 

2015

Davis SW & Cabeza R. Cross-Hemispheric Collaboration and Segregation Associated with Task Difficulty as Revealed by Structural and Functional Connectivity. 2015. Journal of Neuroscience. 35: 8191-8200. 

2014

Kievet RA, Davis SW, Mitchell DJ, Taylor JR, Duncan J, Henson RNA. 2014. Distinct aspects of frontal lobe structure mediate age-related differences in fluid intelligence and multitasking. in pressNature Communications. 

Madden DJ, Parks EL, Davis SW, Diaz MT, Potter GG, Chou YH, Chen NK, Cabeza R. 2014. Age mediation of frontoparietal activation during visual feature search. NeuroImage, doi: 10.1016/j.neuroimage.2014.07.053. 

Davis SW, Zhuang J, Wright P, Tyler LK. Task-related modulation of neurocognitive networks in aging. 2014. Neuropsychologia. 63:107-15. 

Hall SA, Rubin DC, Miles A, Davis SW, Wing EA, Cabeza R, Berntsen D. 2014. The Neural Basis of Involuntary Episodic Memories. J Cogn Neurosci

2013

Daselaar SM, Davis SW, Iyengar V, Eklund K, Hayes SM, Cabeza R. 2013. Less Wiring, More Firing: Low-Performing Older Adults Compensate for Impaired White Matter with Greater Neural Activity. Cerebral Cortex

Whalley MG, Kroes MC, Huntley Z, Rugg MD, Davis SW, Brewin CR. 2013. An fMRI investigation of posttraumatic flashbacks. Brain Cogn. 81:151-9. 

2012

Cantlon JF, Davis SW, Libertus M, Brannon E.M, and Pelphrey KA.  2012. Inter-parietal white matter development predicts numerical performance in young children.  Learning and Individual Differences. 21, 672-680. 

2011

Davis SW, Kragel JE, Madden DJ, Cabeza R.  2011. The architecture of cross-hemispheric communication in aging: Linking behavior to structural and functional connectivity. Cerebral Cortex, 21(4), 231-42

2010

Madden DJ, Costello MC, Dennis NA, Davis SW, Shepler AM, Spaniol J, Bucur B, Cabeza R. 2010. Adult age differences in functional connectivity during executive control. Neuroimage, 15, 643-657. 

2009

Davis SW, Dennis, NA, Buchler, NEG, Madden DJ, White LE, Cabeza R.  2009. Assessing the effects of age on long association fibers using DTI tractography.  NeuroImage. 46, 530-541. 

Madden, D.J, Spaniol, J, Costello, M, Bucur, B, White LE, Cabeza, R, Davis, S.W, Dennis, N.A, Provenzale, J.M, Huettel, S.A.  2009.  Cerebral white matter integrity mediates adult age differences in cognitive performance.  Journal of Cognitive Neuroscience. 21, 289-302. 

2008

Davis SW, Dennis NA, Daselaar, SM, Fleck, ME, Cabeza, R. 2008. Que PASA? The posterior-anterior shift in aging.  Cerebral Cortex. 18(5), 1201-1209. *Reviewed by Faculty of 1000, Medicine: Must Read 

2007

Leow AD, Yanovsky I, Chiang MC, Lee AD, Klunder AD, Lu A, Becker JT, Davis SW, Toga AW, Thompson PM. 2007. Statistical properties of Jacobian maps and the realization of unbiased large-deformation nonlinear image registration. IEEE Trans Med Imaging. 26(6), 822-832. 

2006

Simons JS, Davis SW, Gilbert SJ, Frith CD, Burgess PW. 2006. Discriminating imagined from perceived information engages brain areas implicated in schizophrenia. NeuroImage. 32, 696-703. 

Becker JT, Davis SW, Hiyashi KM, Meltzer CC, Toga AW, Lopez OL, Thompson PM. 2006. Three-dimensional patterns of hippocampal atrophy in mild cognitive impairment. Archives of Neurology. 63, 90-101. 

2005

Carmichael OT, Aizenstein HA, Davis SW, Becker JT, Thompson PM, Meltzer CC, Liu Y. 2005. Atlas-based hippocampus segmentation in Alzheimer’s disease and mild cognitive impairment. NeuroImage. 27, 979-990. 


Presentations

Cross-hemispheric Connectivity Benefits Cognition in Normal Aging & MCI (March 2020). Presented at the Cognitive Neuroscience Society 2020 Virtual Meeting.

Modulation of brain activation and functional connectivity during motion perception with concurrent TMS (March 2020) Presented at the Cognitive Neuroscience Society 2020 Virtual Meeting.

The Visual and Semantic Features that Predict Object Memory (March 2019). Presented at the North Carolina Cognition Conference. Raleigh, NC


 

Talks

APA San Francisco 2018

Come see my talk,TMS for Identifying Compensatory Patterns in Aging, at the American Psychological Association conference, Thursday @ 10am (Moscone Center, Room 156, Upper Mezzanine – South Building), in a session on Transcranial Magnetic Stimulation as an Emerging Clinical and Research Tool

Carolina Networks Research Group

November 8

Visualizing Dynamic Functional Connectivity (Speaker: Guorong Wu)

 

September 13th, 2017

Defining Architecture with DWI (Speaker: S

Collaborators

Cabeza Lab (Duke University)

Opti Lab (Duke University School of Medicine)

Cam-CAN (Cambridge University)

Rogier Kievit  (Cambridge University)

Karen Campbell  (Cambridge University)

Duke Institute for Brain Sciences (Duke’s umbrella organization for neuroscience-related research)

Bryan Alzheimer's Disease Research Center (Bryan ADRC)

Resources

The DinoLab Object Database

This database represents normative visual and semantic feature information on 1000 object images, selected to represent a wide range of real-world concepts organized by category.

Information includes:

  • Regularized (300×300) jpegs of all 1000 objects in the database
  • Normative semantic features, based on data collected on Amazon Turk
  • Memorability information for each item, for both lexical and pictoral recognition memory tests

Software

Brains

Grants

Local Duke Stuff

  • The always helpful BIAC wiki.