Joseph C. Griffis

1.5k total citations
30 papers, 1.0k citations indexed

About

Joseph C. Griffis is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging and Neurology. According to data from OpenAlex, Joseph C. Griffis has authored 30 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Cognitive Neuroscience, 13 papers in Radiology, Nuclear Medicine and Imaging and 6 papers in Neurology. Recurrent topics in Joseph C. Griffis's work include Functional Brain Connectivity Studies (16 papers), Neural dynamics and brain function (10 papers) and Advanced Neuroimaging Techniques and Applications (10 papers). Joseph C. Griffis is often cited by papers focused on Functional Brain Connectivity Studies (16 papers), Neural dynamics and brain function (10 papers) and Advanced Neuroimaging Techniques and Applications (10 papers). Joseph C. Griffis collaborates with scholars based in United States, Italy and Spain. Joseph C. Griffis's co-authors include Jerzy P. Szaflarski, Jane B. Allendorfer, Maurizio Corbetta, Gordon L. Shulman, Nicholas V. Metcalf, Rodolphe Nenert, Kristina Visscher, Lawrence Ver Hoef, Jennifer Vannest and Gustavo Deco and has published in prestigious journals such as Nature Communications, NeuroImage and Brain.

In The Last Decade

Joseph C. Griffis

29 papers receiving 1000 citations

Peers

Joseph C. Griffis
Nicholas V. Metcalf United States
Christoph Sperber Germany
Rose Bosnell United Kingdom
Nicholas B. Dadario United States
Tibor Auer United Kingdom
Rose Bruffaerts Belgium
Isabella M. Young Australia
Borna Bonakdarpour United States
Lenny Ramsey United States
Yohan Attal France
Nicholas V. Metcalf United States
Joseph C. Griffis
Citations per year, relative to Joseph C. Griffis Joseph C. Griffis (= 1×) peers Nicholas V. Metcalf

Countries citing papers authored by Joseph C. Griffis

Since Specialization
Citations

This map shows the geographic impact of Joseph C. Griffis's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Joseph C. Griffis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joseph C. Griffis more than expected).

Fields of papers citing papers by Joseph C. Griffis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Joseph C. Griffis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Joseph C. Griffis. The network helps show where Joseph C. Griffis may publish in the future.

Co-authorship network of co-authors of Joseph C. Griffis

This figure shows the co-authorship network connecting the top 25 collaborators of Joseph C. Griffis. A scholar is included among the top collaborators of Joseph C. Griffis based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Joseph C. Griffis. Joseph C. Griffis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bruss, Joel, Joseph C. Griffis, Hiroto Kawasaki, et al.. (2024). Lesion and lesion network localization of dysnomia after epilepsy surgery. Brain. 148(3). 776–787.
2.
Allegra, Michele, Jakub Vohryzek, Yonatan Sanz Perl, et al.. (2024). Generative whole-brain dynamics models from healthy subjects predict functional alterations in stroke at the level of individual patients. Brain Communications. 6(4). fcae237–fcae237. 3 indexed citations
3.
4.
Metcalf, Nicholas V., et al.. (2022). Inferring the dynamical effects of stroke lesions through whole-brain modeling. NeuroImage Clinical. 36. 103233–103233. 13 indexed citations
5.
Pirondini, Elvira, Nawal Kinany, Joseph C. Griffis, et al.. (2022). Post-stroke reorganization of transient brain activity characterizes deficits and recovery of cognitive functions. NeuroImage. 255. 119201–119201. 16 indexed citations
6.
Adhikari, Mohit H., Joseph C. Griffis, Joshua S. Siegel, et al.. (2021). Effective connectivity extracts clinically relevant prognostic information from resting state activity in stroke. Brain Communications. 3(4). fcab233–fcab233. 16 indexed citations
7.
Griffis, Joseph C., Nicholas V. Metcalf, Maurizio Corbetta, & Gordon L. Shulman. (2021). Lesion Quantification Toolkit: A MATLAB software tool for estimating grey matter damage and white matter disconnections in patients with focal brain lesions. NeuroImage Clinical. 30. 102639–102639. 87 indexed citations
8.
Griffis, Joseph C., et al.. (2021). Mental health in the UK Biobank: A roadmap to self‐report measures and neuroimaging correlates. Human Brain Mapping. 43(2). 816–832. 27 indexed citations
9.
Griffis, Joseph C., Nicholas V. Metcalf, Maurizio Corbetta, & Gordon L. Shulman. (2020). Damage to the shortest structural paths between brain regions is associated with disruptions of resting-state functional connectivity after stroke. NeuroImage. 210. 116589–116589. 47 indexed citations
10.
Griffis, Joseph C., Nicholas V. Metcalf, Maurizio Corbetta, & Gordon L. Shulman. (2019). Structural Disconnections Explain Brain Network Dysfunction after Stroke. Cell Reports. 28(10). 2527–2540.e9. 127 indexed citations
11.
Griffis, Joseph C., et al.. (2018). Cortical excitability and seizure control influence attention performance in patients with idiopathic generalized epilepsies (IGEs). Epilepsy & Behavior. 89. 135–142. 13 indexed citations
12.
Griffis, Joseph C., et al.. (2018). Cortical excitability affects mood state in patients with idiopathic generalized epilepsies (IGEs). Epilepsy & Behavior. 90. 84–89. 7 indexed citations
13.
Griffis, Joseph C., Rodolphe Nenert, Jane B. Allendorfer, & Jerzy P. Szaflarski. (2017). Damage to white matter bottlenecks contributes to language impairments after left hemispheric stroke. NeuroImage Clinical. 14. 552–565. 66 indexed citations
14.
Griffis, Joseph C., Rodolphe Nenert, Jane B. Allendorfer, & Jerzy P. Szaflarski. (2017). Linking left hemispheric tissue preservation to fMRI language task activation in chronic stroke patients. Cortex. 96. 1–18. 26 indexed citations
15.
Griffis, Joseph C., et al.. (2016). Retinotopic patterns of functional connectivity between V1 and large-scale brain networks during resting fixation. NeuroImage. 146. 1071–1083. 21 indexed citations
16.
Griffis, Joseph C., Rodolphe Nenert, Dawn K. DeCarlo, et al.. (2016). Cortical thickness in human V1 associated with central vision loss. Scientific Reports. 6(1). 23268–23268. 40 indexed citations
17.
Griffis, Joseph C., et al.. (2016). Age-Dependent Cortical Thinning of Peripheral Visual Field Representations in Primary Visual Cortex. Frontiers in Aging Neuroscience. 8. 248–248. 7 indexed citations
18.
Griffis, Joseph C., Jane B. Allendorfer, & Jerzy P. Szaflarski. (2015). Voxel-based Gaussian naïve Bayes classification of ischemic stroke lesions in individual T1-weighted MRI scans. Journal of Neuroscience Methods. 257. 97–108. 120 indexed citations
19.
Allendorfer, Jane B., Tyler E. Gaston, Joseph C. Griffis, et al.. (2015). White matter diffusion abnormalities in patients with psychogenic non-epileptic seizures. Brain Research. 1620. 169–176. 57 indexed citations
20.
Griffis, Joseph C., et al.. (2015). Retinotopic patterns of background connectivity between V1 and fronto-parietal cortex are modulated by task demands. Frontiers in Human Neuroscience. 9. 338–338. 25 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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