Research
Neural mechanisms of goal selection
Humans are constantly faced with decisions between different goals. For example, should you work late tonight to meet a deadline or should you go to the store to cook yourself a healthy meal? My ongoing research investigates how rewards influence these decisions: you may be more likely to choose to cook a healthy meal if a month of this behavior has lead to rewarding improvements in health. The influence of reward on goal selection can be adaptive when it reinforces beneficial behaviors (as in the case of healthy eating) or maladaptive when it impairs the flexibility to adopt better goals (as in substance use disorder). I use a multimodal approach to study the neural mechanisms linking rewards to goal selection. The figure on the left depicts a new approach, real-time fMRI neurotriggering, for targeting reward delivery to specific neural representations of goals.
Radulescu, A., Niv, Y., Ballard, I.C. Holistic Reinforcement Learning: The Role of Structure and Attention. Trends in Cognitive Sciences, 23(4): 278–92 (2019).
Diehl, M., Steele, V., Lempert, L., Parr, A., Ballard, I.C., Smith, D. Toward an Integrative Perspective on the Neural Mechanisms Underlying Persistent Maladaptive Behaviors. European Journal of Neuroscience, 48(3): 1870–83 (2018).
Interacting Brain Systems Supporting Learning
Our brain contains multiple systems for representing different kinds of relationships in the world. I study how these systems interact with the brain's associative learning system to support learning about these different kinds of relationships. For example, the hippocampus (depicted in purple on the left) is adept at forming conjunctive representations of multiple features in the world, and I found that its interactions with the striatum (depicted in blue) allows for learning the reward values of these conjunctions. This research makes use of multivariate tools to probe the nature of brain representations and computational models to link brain to behavior.
A New Role for the Hippocampus During Learning. Press Release.
Ballard, I.C., Wagner, A.D., McClure, S.M. Hippocampal Pattern Separation Supports Reinforcement Learning. Nature Communications, 10(1): 1073 (2019). Analysis Code. OpenNeuro Dataset.
Ballard, I.C., Miller, E., Piantadosi, S.T., Goodman, N., McClure, S.M. Beyond Reward Prediction Errors: Human Striatum Represents Rule Values During Categorization Learning. Cerebral Cortex, 19(3), 1-11 (2017).
Ballard, I.C., McClure, S.M. Joint Modeling of Choice and Reaction Times Improves Parameter Identifiability in Reinforcement Learning Models. Journal of Neuroscience Methods, 317(4): 37–44 (2019). Analysis Code and Data.
Murty, V. P., Ballard, I. C., Macduffie, K. E., Krebs, R. M. & Adcock, R. A. Hippocampal networks habituate as novelty accumulates. Learning & Memory, 20, 229–235 (2013).
Goal-directed decision making
How do we decide to pursue long-term goals instead of short-term gratification? I use computational modeling of decision-making in combination with brain imaging and transcranial magnetic stimulation to isolate the neural mechanisms underlying self-control in decision making. A key finding from this line of research is that a region of prefrontal cortex called the inferior frontal sulcus (IFS, red region on the left) is causally involved in deciding to pursue long-term goals.
Ballard, I. C. Kim, B., Aydogan, G., Liatsis, A., Cohen, J.D., McClure, S.M. More Is Meaningful: The Magnitude Effect in Intertemporal Choice Depends on Self-Control. Psychological Science, 28(10), 1443–1454 (2017). Analysis Code. OpenNeuro Dataset.
Ballard, I. C., Aydogan, G., Kim, B. & McClure, S.M. Causal Evidence for the Dependence of the Magnitude Effect on Dorsolateral Prefrontal Cortex. Scientific Reports, 8(1), 16545 (2018). Analysis Code and Data.
Samanez-Larkin, G.R., Mata, R., Radu, P.T., Ballard, I.C., Carstensen, L.L., McClure, S.M. Age differences in striatal delay sensitivity during intertemporal choice in healthy adults. Frontiers in Neuroscience, 5, 126. (2011).
Goal-directed control of motivation
When humans are motivated to accomplish a goal, multiple aspects of cognition change: they are better at maintaining focus, their actions are faster and more vigorous, and they are more likely to retain memories. However, motivation is fickle and subject to failure. I study the brain mechanisms responsible for creating a motivational state in order to better understand how and when motivation occurs. A key finding from this line of research is that the prefrontal cortex (DLPFC, left) influences the ventral tegmental area (VTA), a major source of the brain's dopamine, in order to accomplish high-value goals.
Ballard, I.C.*, Murty, V.P.*, Carter R.M., MacInnes J.J., Huettel S.A., Adcock R.A. Dorsolateral prefrontal cortex drives mesolimbic dopaminergic regions to initiate motivated behavior. Journal of Neuroscience, 31(28), 10340-6. (2011).
Murty, V.P*., Ballard, I.C*., Adcock, R.A. Hippocampus and Prefrontal Cortex Predict Distinct Timescales of Activation in the Human Ventral Tegmental Area. Cerebral Cortex, 27(2), 1660-1669 (2017).
Ballard, I.C., Hennigan, K., McClure, S.M. (2017) Mere Exposure: Preference for Novel Drinks Reflected in Human Ventral Tegmental Area. Journal of Cognitive Neuroscience, 29, 793–804 (2017).