Brice Alan Kuhl, Ph.D. - US grants

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Declarative memory formation is known to be influenced both by interference from competing memories as well as motivational factors such as the anticipation of reward. While interference has a deleterious effect on episodic encoding and frequently elicits activation in left ventrolateral prefrontal cortex (VLPFC), reward anticipation has recently been shown to facilitate encoding through engagement of mesolimbic structures. Although reward anticipation and the presence of interference have distinct effects, the extent of interactions between the neural systems engaged by each remains unclear. In the present study, we used functional MRI to characterize neural responses related to reward anticipation and mnemonic interference in the context of a paired associate memory task. During scanning, each paired associate encoding trial was preceded by a cue indicating the potential reward if the pair could be later remembered (either 'high'or 'low'reward trials). Moreover, while some pairs were entirely novel, others contained elements previously associated with other stimuli (no interference vs. interference trials, respectively).

DESCRIPTION (provided by applicant): Fundamental to an efficient episodic memory system is the ability to remember selectively-to be able to focus attention on relevant memories at the exclusion of irrelevant memories. While it is thought that prefrontal cortex (PFC) plays a critical role in selecting among competing memories, there remains considerable ambiguity concerning how competition is represented at a neural level and how PFC interacts with posterior cortical sites to achieve selection. This proposal seeks to advance understanding of how competition impacts processing in the cortical regions that support 'reactivation'of memories and how signals from these regions relate to engagement of specific PFC subregions. The first experiment will assess the representation of memory competition in regions that process perceptual elements of events and are reactivated during retrieval. It is hypothesized that the fidelity of signals in these perceptual regions will be related to PFC engagement. The second experiment will assess the generality of PFC mechanisms that resolve competition by formally testing for overlap between mechanisms that govern competitive retrieval and those that govern perceptual decision-making. Finally, the third experiment will assess the adaptive qualities of retrieval, probing the biases in reactivation that come about as a consequence of prior acts of retrieval. Across each of these experiments, experimental paradigms will be structured such that relevant (target) and irrelevant (distracter) memories are always from visual categories that are processed by distinct perceptual cortical regions (i.e., Faces and Scenes). This approach will allow for direct comparison of reactivation that is related to targets vs. distractors and will therefore be essential for gauging the relationship between PFC engagement and the signals propagating from perceptual cortical regions. These experimental pursuits are intended to form the basis for more applied experimental questions related to the memory failures that are frequently observed in a variety of clinical and non-clinical states. Summary: The present proposal seeks to use functional MRI to better understand how, at a neural level, competition between episodic memories is experienced and resolved. This work underscores the fact that memory often fails not because information is not learned in the first place, but because retrieval operations are overwhelmed by competition. The insights to be gained are of obvious and critical relevance to memory disorders and impairments associated with aging and dementia, particularly of the Alzheimer's type.

DESCRIPTION (provided by applicant): One of the biggest challenges to successful remembering is the potential for confusion or interference between similar memories. For every password, name, or parking space that we store in memory, there are many other passwords, names or parking spaces that we have already learned or will learn in the future. While interference is a factor in relatively benign-yet annoying-examples of 'normal' forgetting, it is aso a major factor in clinically significant examples of forgetting that occur with aging and/or dementia. Thus, there is a fundamental need to understand the neural mechanisms that support the acquisition/retrieval of similar memories while minimizing interference and corresponding forgetting. Computational models of episodic memory have proposed two core mechanisms that are thought to reduce interference-related forgetting: integration and pattern separation. Integration involves 'fusing' overlapping memories into a common representation such that the relationship between these memories is more complementary than competitive. Pattern separation involves the orthogonalization of similar memories such that differences between memories are exaggerated and the potential for interference minimized. While there is general agreement that these mechanisms are theoretically appealing and offer clear computational advantages, clear evidence for how and when these learning mechanisms are invoked- particularly in humans-remains surprisingly limited? In particular, there remains ambiguity as far as (a) the learning contexts in which each mechanism might be recruited, (b) what the corresponding neural signatures of each mechanism are, and (c) the specific behavioral consequences associated with the engagement of each mechanism. We propose a systematic investigation of the contexts in which integration and pattern separation occur with the goal of using sophisticated, cutting-edge neuroimaging (fMRI) techniques to identify distributed patterns of neural activity that are diagnostic of each mechanism. Critically, we also plan to use these observed patterns of neural activity-that is, neural evidence for integration vs. separation-to predict behavioral memory phenomena, including interference-related forgetting. The research represents a strong synthesis of psychology and neuroscience questions with an emphasis on learning mechanisms inspired by computational models and analysis approaches that draw from the fields of machine learning and data mining.

The hippocampus is essential for forming long-lasting episodic memories. Yet, patterns of hippocampal activity associated with an individual event continue to change with experience and learning. What consequence do these changes have for the underlying memory representations? In rodents, the phenomenon of hippocampal pattern change has been termed `remapping' and has most typically been reported in place cells. This allows for remapping to be directly related to spatial coding of the environment. In humans, however, it is less clear how reconfiguration of hippocampal activity patterns (remapping-like phenomena) translates to specific changes in memory representations. Potentially, changes in hippocampal activity patterns reflect changes in the specific features that, when bound together, comprise a memory. The goal of the proposed research is to gain insight into how and why hippocampal activity patterns (and memories more generally) change with learning. We will address this by developing and leveraging innovative and highly-sensitive pattern-based fMRI methods that map specific features of a memory to patterns of cortical activity. In particular, we will use these methods to reconstruct images from memory and to read out the semantic components of memories. This will allow us to measure how individual features of a memory change with learning and to test whether cortically-expressed feature changes are predicted by remapping-like phenomena in the hippocampus. We will specifically target feature representations in lateral parietal cortex, motivated by accumulating evidence that lateral parietal cortex actively represents the contents of memory and is functionally coupled with the hippocampus. The proposed research will bridge rodent and human models of memory while introducing conceptual approaches and analysis methods that have the potential to significantly advance the field. Because the specific brain regions that will be targeted in the research (the hippocampus and lateral parietal cortex) are frequently implicated in disease- and stroke-related memory impairments, the proposed research will also support critical foundational knowledge that has the potential to guide clinical interventions.