Ian C. Ballard

983 total citations
20 papers, 589 citations indexed

About

Ian C. Ballard is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Experimental and Cognitive Psychology. According to data from OpenAlex, Ian C. Ballard has authored 20 papers receiving a total of 589 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Cognitive Neuroscience, 5 papers in Cellular and Molecular Neuroscience and 3 papers in Experimental and Cognitive Psychology. Recurrent topics in Ian C. Ballard's work include Neural and Behavioral Psychology Studies (12 papers), Neural dynamics and brain function (9 papers) and Functional Brain Connectivity Studies (8 papers). Ian C. Ballard is often cited by papers focused on Neural and Behavioral Psychology Studies (12 papers), Neural dynamics and brain function (9 papers) and Functional Brain Connectivity Studies (8 papers). Ian C. Ballard collaborates with scholars based in United States, Switzerland and France. Ian C. Ballard's co-authors include Samuel M. McClure, R. Alison Adcock, Vishnu P. Murty, Scott A. Huettel, Ronald Carter, Jeff MacInnes, Yael Niv, Angela Radulescu, Anthony D. Wagner and Gregory R. Samanez‐Larkin and has published in prestigious journals such as Nature Communications, Journal of Neuroscience and Trends in Cognitive Sciences.

In The Last Decade

Ian C. Ballard

17 papers receiving 578 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ian C. Ballard United States 12 405 123 97 93 46 20 589
Michael J. Frank United States 4 513 1.3× 184 1.5× 63 0.6× 93 1.0× 21 0.5× 5 761
Nicole C. Wright United Kingdom 10 344 0.8× 149 1.2× 46 0.5× 121 1.3× 26 0.6× 22 540
Lea K. Krugel Germany 10 363 0.9× 63 0.5× 80 0.8× 54 0.6× 26 0.6× 12 523
A. M. Owen United Kingdom 2 438 1.1× 127 1.0× 118 1.2× 82 0.9× 37 0.8× 4 675
Irma T. Kurniawan United Kingdom 6 358 0.9× 67 0.5× 93 1.0× 89 1.0× 18 0.4× 11 492
Katharina Paul Germany 17 538 1.3× 178 1.4× 48 0.5× 71 0.8× 21 0.5× 35 751
Jacqueline Scholl United Kingdom 13 599 1.5× 138 1.1× 83 0.9× 63 0.7× 12 0.3× 25 759
Irene van de Vijver Netherlands 10 508 1.3× 129 1.0× 75 0.8× 41 0.4× 26 0.6× 20 687
Reka Daniel United States 8 582 1.4× 142 1.2× 73 0.8× 64 0.7× 12 0.3× 9 757
Paul Faulkner United Kingdom 15 262 0.6× 172 1.4× 145 1.5× 38 0.4× 22 0.5× 29 667

Countries citing papers authored by Ian C. Ballard

Since Specialization
Citations

This map shows the geographic impact of Ian C. Ballard'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 Ian C. Ballard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ian C. Ballard more than expected).

Fields of papers citing papers by Ian C. Ballard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ian C. Ballard. 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 Ian C. Ballard. The network helps show where Ian C. Ballard may publish in the future.

Co-authorship network of co-authors of Ian C. Ballard

This figure shows the co-authorship network connecting the top 25 collaborators of Ian C. Ballard. A scholar is included among the top collaborators of Ian C. Ballard 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 Ian C. Ballard. Ian C. Ballard 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.
Kim, Haena, Ian C. Ballard, & Yuan Chang Leong. (2025). A neurocomputational account of motivated seeing. Trends in Cognitive Sciences. 30(1). 80–94.
2.
Ballard, Ian C., et al.. (2025). Willing to wait: Anorexia nervosa symptomatology is associated with higher future orientation and reduced intertemporal discounting. Scientific Reports. 15(1). 4508–4508. 1 indexed citations
3.
Ballard, Ian C., et al.. (2024). In vivo structural connectivity of the reward system along the hippocampal long axis. Hippocampus. 34(7). 327–341.
4.
Ballard, Ian C., et al.. (2024). Reward Reinforcement Creates Enduring Facilitation of Goal-directed Behavior. Journal of Cognitive Neuroscience. 36(12). 2847–2862. 2 indexed citations
5.
Ballard, Ian C., et al.. (2022). Decision uncertainty during hypothesis testing enhances memory accuracy for incidental information. Learning & Memory. 29(4). 93–99. 2 indexed citations
6.
Lapate, Regina C., et al.. (2021). Emotional Context Sculpts Action Goal Representations in the Lateral Frontal Pole. Journal of Neuroscience. 42(8). 1529–1541. 15 indexed citations
7.
McDougle, Samuel D., Ian C. Ballard, Beth Baribault, Sonia J. Bishop, & Anne Collins. (2021). Executive Function Assigns Value to Novel Goal-Congruent Outcomes. Cerebral Cortex. 32(1). 231–247. 13 indexed citations
8.
Ballard, Ian C. & Samuel M. McClure. (2019). Joint modeling of reaction times and choice improves parameter identifiability in reinforcement learning models. Journal of Neuroscience Methods. 317. 37–44. 29 indexed citations
9.
Ballard, Ian C., Anthony D. Wagner, & Samuel M. McClure. (2019). Hippocampal pattern separation supports reinforcement learning. Nature Communications. 10(1). 1073–1073. 40 indexed citations
10.
Radulescu, Angela, Yael Niv, & Ian C. Ballard. (2019). Holistic Reinforcement Learning: The Role of Structure and Attention. Trends in Cognitive Sciences. 23(4). 278–292. 64 indexed citations
11.
Ballard, Ian C., et al.. (2018). Causal Evidence for the Dependence of the Magnitude Effect on Dorsolateral Prefrontal Cortex. Scientific Reports. 8(1). 16545–16545. 12 indexed citations
12.
Diehl, María M., Karolina M. Lempert, Ashley C. Parr, et al.. (2018). Toward an integrative perspective on the neural mechanisms underlying persistent maladaptive behaviors. European Journal of Neuroscience. 48(3). 1870–1883. 11 indexed citations
13.
Ballard, Ian C., et al.. (2017). Beyond Reward Prediction Errors: Human Striatum Updates Rule Values During Learning. Cerebral Cortex. 28(11). 3965–3975. 24 indexed citations
14.
Ballard, Ian C., et al.. (2017). Mere Exposure: Preference Change for Novel Drinks Reflected in Human Ventral Tegmental Area. Journal of Cognitive Neuroscience. 29(5). 793–804. 8 indexed citations
15.
Ballard, Ian C., et al.. (2017). More Is Meaningful: The Magnitude Effect in Intertemporal Choice Depends on Self-Control. Psychological Science. 28(10). 1443–1454. 47 indexed citations
16.
Murty, Vishnu P., Ian C. Ballard, & R. Alison Adcock. (2016). Hippocampus and Prefrontal Cortex Predict Distinct Timescales of Activation in the Human Ventral Tegmental Area. Cerebral Cortex. 27(2). bhw005–bhw005. 18 indexed citations
17.
Murty, Vishnu P., Ian C. Ballard, Katherine E. MacDuffie, Ruth M. Krebs, & R. Alison Adcock. (2013). Hippocampal networks habituate as novelty accumulates. Learning & Memory. 20(4). 229–235. 33 indexed citations
18.
Ballard, Ian C., Vishnu P. Murty, Ronald Carter, et al.. (2011). Dorsolateral Prefrontal Cortex Drives Mesolimbic Dopaminergic Regions to Initiate Motivated Behavior. Journal of Neuroscience. 31(28). 10340–10346. 199 indexed citations
19.
Samanez‐Larkin, Gregory R., et al.. (2011). Age Differences in Striatal Delay Sensitivity During Intertemporal Choice in Healthy Adults. SSRN Electronic Journal.
20.
Samanez‐Larkin, Gregory R., et al.. (2011). Age Differences in Striatal Delay Sensitivity during Intertemporal Choice in Healthy Adults. Frontiers in Neuroscience. 5. 126–126. 71 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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