Travis D. Goode
Impact in
- Behavioral Neuroscience top 2%
- Stress Responses and Cortisol
- Cognitive Neuroscience top 5%
- Memory and Neural Mechanisms
- Neural dynamics and brain function
Papers in
-
- Memory and Neural Mechanisms 15
- Sleep and Wakefulness Research 3
-
- Neuroscience and Neuropharmacology Research 10
- Co-authors
- Stephen Maren (12 shared papers)Gillian M. Acca (4 shared papers)Reed L. Ressler (3 shared papers)Amar Sahay (3 shared papers)Thomas J. McHugh (1 shared paper)Kazumasa Z. Tanaka (1 shared paper)Paul J. Fitzgerald (2 shared papers)Thomas F. Giustino (2 shared papers)
- Journals
- Learning & Memory (3 papers)Neurobiology of Learning and Memory (3 papers)Nature Neuroscience (2 papers)Neuron (2 papers)eNeuro (1 paper)
- Partner nations
- United StatesJapanAustralia
In The Last Decade
Travis D. Goode
16 papers receiving 762 citations
Peers
Comparison fields: 5 of 65
- Behavioral Neuroscience 241
- Cognitive Neuroscience 563
- Cellular and Molecular Neuroscience 422
- Developmental Neuroscience 40
- Social Psychology 205
Countries citing papers authored by Travis D. Goode
This map shows the geographic impact of Travis D. Goode'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 Travis D. Goode with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Travis D. Goode more than expected).
Fields of papers citing papers by Travis D. Goode
This network shows the impact of papers produced by Travis D. Goode. 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 Travis D. Goode. The network helps show where Travis D. Goode may publish in the future.
Co-authors
The 25 scholars most cited alongside Travis D. Goode, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 166 | |
| 2 | 2017 | 101 | |
| 3 | 2020 | 94 | |
| 4 | 2019 | 80 | |
| 5 | 2014 | 73 | |
| 6 | 2018 | 55 | |
| 7 | 2017 | 35 | |
| 8 | 2021 | 33 | |
| 9 | 2016 | 29 | |
| 10 | 2019 | 28 | |
| 11 | 2015 | 22 | |
| 12 | 2017 | 17 | |
| 13 | 2018 | 14 | |
| 14 | 2016 | 13 | |
| 15 | 2020 | 12 | |
| 16 | 2015 | 6 | |
| 17 | 2026 | 0 | |
| 18 | 2023 | 0 |
About Travis D. Goode
Travis D. Goode is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience, Behavioral Neuroscience, Social Psychology and Developmental Neuroscience, having authored 18 papers that have together received 778 indexed citations. Recurring topics across this work include Memory and Neural Mechanisms (15 papers), Neuroscience and Neuropharmacology Research (10 papers), Stress Responses and Cortisol (7 papers), Neuroendocrine regulation and behavior (6 papers), Sleep and Wakefulness Research (3 papers), Glaucoma and retinal disorders (1 paper), Neurogenesis and neuroplasticity mechanisms (1 paper) and Biochemical Analysis and Sensing Techniques (1 paper). The work is most often cited by research in Behavioral Neuroscience (241 citations), Cognitive Neuroscience (563 citations), Cellular and Molecular Neuroscience (422 citations), Developmental Neuroscience (40 citations) and Social Psychology (205 citations). Travis D. Goode has collaborated with scholars based in United States, Japan and Australia. Frequent co-authors include Stephen Maren, Gillian M. Acca, Reed L. Ressler, Amar Sahay, Thomas J. McHugh, Kazumasa Z. Tanaka, Paul J. Fitzgerald, Thomas F. Giustino, Olivia W. Miles and Roger Marek. Their work appears in journals such as Learning & Memory, Neurobiology of Learning and Memory, Nature Neuroscience, Neuron and eNeuro.
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.