The goal of this research program is to advance our understanding of the functional organization of frontal cortex and the ways in which interactions among frontal regions permit internal control of thought and action, an ability termed cognitive control. The proposed experiments test the hypothesis that the rostro-caudal axis of the frontal lobes comprises a processing hierarchy whereby more anterior regions support cognitive control involving progressively more abstract goals, plans, and action representations. First, a set of fMRI experiments, using factorial logic, seek to specify the dimensions of abstraction that define regional differences along the rostro-caudal axis of the frontal lobes. Several experiments have demonstrated a functional gradient along the rostro-caudal axis as cognitive control involves more abstract representations. However, these experiments have differed in their definition of abstraction, including domain generality, temporal abstraction, and rule complexity. Though these dimensions of abstraction are not mutually exclusive, they may also be independently varied under controlled circumstances. Thus, the first set of fMRI experiments take advantage of this independence to provide a more explicit definition of abstraction as it relates to frontal lobe function. Second, a hierarchical system requires that superordinate processors can modulate subordinate processors but not vice versa. Translated to a frontal hierarchy, this asymmetry predicts that control processing by a given region of the frontal cortex should directly influence regions posterior to but not anterior to its locus. Thus, a line fMRI experiments will use effective connectivity analysis to test whether (a) cognitive control processing in anterior frontal regions can modulate processing in posterior frontal regions, (b) whether cognitive control processing in posterior frontal regions can affect concurrent control processing by anterior frontal regions. Third, a set of experiments will investigate frontal lobe function during learning and adaptation of hierarchically structured rule sets. In general, hierarchies are useful structures for supporting learning of novel tasks because they can represent the same information at multiple levels of abstraction and so can provide access points for the application of prior knowledge, such as through analogy. Thus, a set of experiments test whether the putative frontal lobe hierarchy reflects such dynamics during learning of novel rule sets, the transfer of learning to new tasks, and the application of transformational rules to existing rule sets. Hence, across its aims, this program of research triangulates the hypothesis of a hierarchical organization of the frontal lobe by testing three different classes of predictions that each arises from an assumption of a hierarchical system.
A variety of disorders impact cognitive control and frontal function, including schizophrenia, attention-deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder, major depression, autism, Alzheimer's disease, and Parkinson's disease. However, a lack of basic understanding of cognitive control and frontal function remains a persistent obstacle to directed assessment and rehabilitation of frontal lobe dysfunction (Royall et al., 2002). The proposed research seeks to fill these gaps in basic understanding of frontal lobe function, and so may form a basis for development of directed assessments that refine diagnosis and improve rehabilitation.
| Nyhus, Erika (2018) Brain Networks Related to Beta Oscillatory Activity during Episodic Memory Retrieval. J Cogn Neurosci 30:174-187 |
| Bhandari, Apoorva; Badre, David (2018) Learning and transfer of working memory gating policies. Cognition 172:89-100 |
| Sayal?, Ceyda; Badre, David (2018) Neural systems of cognitive demand avoidance. Neuropsychologia : |
| Badre, David; Nee, Derek Evan (2018) Frontal Cortex and the Hierarchical Control of Behavior. Trends Cogn Sci 22:170-188 |
| Collins, Anne G E; Ciullo, Brittany; Frank, Michael J et al. (2017) Working Memory Load Strengthens Reward Prediction Errors. J Neurosci 37:4332-4342 |
| Chatham, Christopher H; Badre, David (2015) Multiple gates on working memory. Curr Opin Behav Sci 1:23-31 |
| Kang, Hakmook; Blume, Jeffrey; Ombao, Hernando et al. (2015) Simultaneous control of error rates in fMRI data analysis. Neuroimage 123:102-13 |
| Voytek, Bradley; Kayser, Andrew S; Badre, David et al. (2015) Oscillatory dynamics coordinating human frontal networks in support of goal maintenance. Nat Neurosci 18:1318-24 |
| Frank, Michael J; Badre, David (2015) How cognitive theory guides neuroscience. Cognition 135:14-20 |
| Frank, Michael J; Gagne, Chris; Nyhus, Erika et al. (2015) fMRI and EEG predictors of dynamic decision parameters during human reinforcement learning. J Neurosci 35:485-94 |
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