Alison R. Preston - US grants

DESCRIPTION (provided by applicant): A fundamental principle of human memory known as encoding specificity states that the way in which an event is experienced determines how memory for that event is stored and later retrieved. In terms of neural systems, encoding specificity predicts that brain regions active during encoding will be re-activated during episodic retrieval reflecting the recapitulation of an original experience as it is remembered. A second principle of human memory know as transfer appropriate processing states that memory performance is facilitated when the same processing is evoked at both encoding and retrieval. In terms of neural systems, this principle would predict that re-activation of encoding specific brain regions during episodic retrieval will be greater when encoding and retrieval processing is matched relative to when processing is mismatched. The aim of this proposal is find evidence for encoding-specific re-activation during episodic retrieval and to test the predictions made by each of these principles using event-related fMRI. In addition, we will investigate how the phenomenon of encoding-specific reactivation is related to successful episodic memory retrieval.

[unreadable] DESCRIPTION (provided by applicant): A central question in memory research is how component structures of medial temporal lobe (MTL) differentially contribute to acquisition, retention, and retrieval of long-term memories. Using a combination of high-resolution fMRI and cortical flattening techniques that make differentiation of these small, adjacent structures possible, the proposed research investigates hypotheses regarding functional specialization within MTL. The proposed experiments specifically investigate hypotheses based on the connectional anatomy of MTL, both in terms of its connectivity to sensory cortical regions and its intrinsic hierarchical connectivity. The segregation of cortical information entering MTL suggests that different MTL subregions may maintain different types of memory representations since each region has a unique set of inputs allowing for a distinctive pattern of sensory convergence and integration that support different types of representational capabilities. In addition, the hierarchical nature of processing in MTL suggests that structures at different hierarchical levels play distinct roles in declarative memory. First, we will test whether encoding responses and subsequent memory prediction of MTL subregions depend on cortical information that each subregion receives. Second, we will examine how different MTL subregions are involved in item and relational memory at encoding and retrieval. Finally, we will consider how MTL subregions contribute to acquisition and use of conjunctive information. [unreadable] [unreadable]

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. Episodic memory[unreadable]memory for individual events[unreadable]permits an organism to bridge the past with the present, providing information about prior events that serves to inform present decisions and action. Episodic memory critically depends on the medial temporal lobe (MTL) circuit, which is composed of multiple structures, including the hippocampal formation [dentate gyrus (DG), CA fields, and subiculum (SUB)] and the surrounding entorhinal (ERc), perirhinal (PRc), and parahippocampal (PHc) cortices. Though decades of research have aimed to characterize the role of MTL in episodic memory, fundamental questions remain regarding the functional contributions of specific MTL substructures. Recent advances in functional imaging methods have made it possible to address these questions in humans. Our research uses high-resolution fMRI to delineate the role of hippocampal subfields and MTL cortical structures in the encoding and retrieval of episodic memories. The experiments test anatomically-informed theory-driven hypotheses regarding the nature of episodic memory and its dependence on MTL function. The research further examines optimal learning parameters to promote the flexible, generative use of episodic memory, and the potential impact of motivational salience and attention on episodic memory processing and MTL function.

We often reflect on our past to understand current experience or predict future events. For example, in choosing a birthday gift for a friend, we can look to past birthdays for help in deciding what gift would elicit the greatest joy for the friend this year. In this way, memory is not merely retrospective, but also intrinsically prospective. With funding from the National Science Foundation, Alison Preston, Ph.D., and colleagues at the University of Texas at Austin are using functional magnetic resonance imaging (fMRI) to understand how the brain supports predictions about the present and future based on memories of the past. Despite decades of neuroscience research focused on retrospective memory, very little is known about the neurobiological mechanisms that enable the prospective use of experience. However, a rich history of research suggests that the brain's medial temporal lobe structures are important for learning and remembering individual experiences. One goal of this project is to learn how these brain structures reactivate existing memories in the face of new experiences. In one set of studies, participants learn sequences of events while undergoing fMRI. The researchers are seeking evidence in the fMRI data for reactivation of prior memories during prediction of upcoming events in the sequence. A second goal of this project is to discover how remembering influences new learning. To be maximally adaptive for future use, memories do not simply consist of individual records of directly experienced events but also include memories built by integrating knowledge across different events. The researchers are learning how remembering past events during new situations provides an opportunity for new memories to be formed that connect present experience with existing memories. For example, if today one sees an unfamiliar man walking a familiar Great Dane, the sight of the dog may trigger a memory for a previous occasion on which one saw that same dog being walked by a woman. By recalling the previous experience with the Great Dane, a new memory can be formed that not only represents the relationship between the man and the dog, and the woman and the dog, but also connects the man and the woman, despite ones never having seen them together. Such integrated memories are a means by which individual experiences are combined to anticipate future judgments and actions. In related fMRI experiments, participants study events that share content and make judgments about the relationship between those experiences. These studies are allowing the researchers to understand how the brain builds a rich, cohesive record of experience by incorporating new events into existing memories.

A core mission of this project is to combine research efforts with teaching, mentorship, and outreach. Unique training and educational activities are being carried out at the high school, undergraduate, and graduate levels. Students are participating in hands-on training with state-of-the-art fMRI techniques and advanced quantitative methods. This training provides students with the necessary tools to address critical questions in cognitive neuroscience with an increased level of sophistication. To ensure that these training opportunities are available to a broad range of students, the research program forms the basis of a public outreach effort encouraging minority students outside of academic research centers to become involved in neuroscience research. This outreach program includes classroom demonstrations of neuroscience concepts at high schools and community colleges that serve underrepresented minority groups, organized tours for learning about research in the lab, and summer assistantships for students to gain research experience. Public lectures to the general community are engaging the public's interest in basic science and communicating how discoveries in neuroscience can influence many aspects of society, such as educational and clinical practices.

DESCRIPTION (provided by applicant): Judging a person as a friend or foe, a mushroom as edible or poisonous, or a sound as an \l\ or \r\ are examples of categorization problems. One key aspect of learning is discerning the relevant stimulus dimensions that determine category membership and the value and costs (in terms of time, cognitive efort, and dollars) associated with gathering such information. Many category learning models employ selective attention mechanisms that learn which stimulus dimensions are most critical to performance. However, these models make the unrealistic assumption that all stimulus dimensions will be encoded, and, thus, fail to address challenges that arise from limited processing resources, both cognitive and neural. Improved models are required to understand the interplay between attentional allocation and memory. By recasting category learning as a dynamic decision process, we develop a model that selectively encodes information during learning as a function of the learner's goals, task demands, and knowledge state. To capture the required interplay between attention, memory, and executive function, our model consists of two primary components: one that determines the value of potential sources of information based on the decision maker's goals and assumptions about the world and a second component that reflects the decision maker's current knowledge. Current knowledge represented by the second learning component is utilized by the first value component to direct information gathering. The learning component of the model is updated by the information selected by the first component, completing the cycle of mutual influence. A central goal of the proposal is to develop models that make realistic assumptions about human capacity limitations and to characterize how individuals' mental machinery and behavioral outcomes deviate from rational principles. A second goal is to combine our novel model-based approach with eye tracking and functional magnetic resonance imaging (fMRI) to determine the neural mechanisms that support goal-directed attention and learning. Model-based analyses of fMRI data have the power to go beyond conventional analysis methods to reveal complex dynamics between neural systems that give rise to cognitive competencies. In two proposed studies, participants must decide which information sources to sample, taking into account the conflicting needs of (1) minimizing information cost, (2) making the correct decision, and (3) learning more about the categories and information sources with the aim of increasing performance on future trials. By fitting our model to individuals' information seeking and classification behavior, we can calculate a number of regressors that track unobservable mental states that are predictive of subsequent behavior and critical for determining the brain basis of the dynamic decision making processes that support category learning. Advancing our knowledge of the brain processes that underlie these powerful aspects of cognition may have real-world consequences by providing knowledge about optimal learning strategies as well as providing insight into disorders that affect learning and memory. PUBLIC HEALTH RELEVANCE: Impairments in learning, memory, and attention deficits accompany a number of psychiatric (e.g., schizophrenia, major depression, ADHD) and neurological disorders (e.g., Alzheimer's disease, epilepsy). Accordingly, understanding the neural mechanisms of attention and memory in the healthy brain promises to advance neurobiological theory and may lead to new developments that bear on the diagnosis and treatment of such conditions.

DESCRIPTION (provided by applicant): Leading memory theories emphasize that new learning occurs on the background of existing knowledge. Retrieving prior knowledge during new experiences allows new information to be integrated into existing memories, resulting in the formation of rich, cohesive memory networks that relate discrete events. This integration process is proposed to facilitate new learning and enable memories to extend beyond direct experience to anticipate the relationships among events. However, memory for evidence neurobiological inability to directly measure the contents of reactivated memories during new experiences. To address this critical gap, the proposed studies employ a new experimental paradigm that uses highly sensitive pattern classifier algorithms applied to functional neuroimaging data to quantify incidental memory reactivation during new event encoding. Quantifying memory reactivation allows us to test mechanistic predictions about how past memories influence learning in the present. Aim 1 will use this paradigm to test the hypothesis that hippocampus and ventromedial prefrontal cortex (VMPFC) work in concert to support memory integration during new learning. We propose that by linking new information with well-established memories, this hippocampal-VMPFC mediated encoding process improves new learning and enables novel judgments about relationships among distinct events. Aim 2 will examine how temporal context and memory strength influence the formation of integrated memory traces for related events. We propose that learning overlapping events within the same temporal context facilitates memory integration by enhancing memory reactivation and recruiting hippocampal-VMPFC encoding processes. We will also adjudicate between opposing theoretical perspectives of learning that make competing predictions for whether strong or weak memories lead to enhanced memory integration. Aim 3 will use high- resolution fMRI focused on the medial temporal lobe to determine the precise hippocampal computations and coding strategies that underlie memory integration. We will determine the relationship between memory reactivation and hippocampal mismatch responses that signal differences between current events and existing memories to test the hypothesis that mismatch responses trigger memory integration. We will also use pattern- information analysis to test the hypothesis that the hippocampus creates integrated memories by forming overlapping neural codes for related events. Collectively, this work will determine how internally generated content influences new learning and will isolate the precise neural networks, computations, and coding strategies that underlie memory integration. Understanding how the brain uses prior experience to make sense of new information will lay the foundation for translational work onintegration and its functional significance is sorely lacking due primarily to an effective for interventions therapeutic psychiatric and neurological disorders that require acquisition and maintenance of new behaviors.

? DESCRIPTION (provided by applicant): Every day, our brains face the challenge of combining information across discrete experiences to answer novel questions. This central ability emerges early in childhood and retains a high degree of importance throughout the lifespan. Yet, the mechanisms and brain regions that support the integration of information across distinct episodes have only recently become the subject of empirical study-even in adult populations. How the neural processes underlying this faculty develop throughout childhood and adolescence remains virtually unstudied. Recent work suggests that in the mature brain, both the medial temporal lobes (MTL) and ventromedial prefrontal cortex (VMPFC) are important for building and using knowledge that spans experiences. The proposed research will use high-resolution structural and functional magnetic resonance imaging in children, adolescents, and young adults to investigate how the ability to link memories across time changes as the brain matures. The key hypothesis is that despite extant notions that the MTL-based episodic memory system is fully developed early in childhood, memory integration-which requires dynamic interactions between MTL and VMPFC-does not emerge until adulthood. This hypothesis is consistent with the protracted structural development of MTL, VMPFC, and the white matter pathways connecting these regions. Furthermore, we hypothesize that the development of memory integration is critical for other important cognitive behaviors such as inferential reasoning. Aim 1 will determine how existing knowledge influences the ability to encode new, related information and will characterize the neural processes that support memory integration and inferential reasoning at different ages. Aim 2 will test the hypothesis that offline mechanisms demonstrated to support consolidation of individual memories also support strengthening of integrated memories that span experiences. We predict that evidence for offline consolidation of integrated memories will be observed only in the mature brain. Aim 3 will employ structural MRI and high-resolution diffusion-weighted imaging to determine how VMPFC, MTL subregions, and their associated white matter pathways develop to support behavior, thus providing a wealth of neuroanatomical data to inform memory theories. We anticipate that our findings will advance understanding of both typical and atypical development. Reasoning ability is predictive of both math and reading success; testing the link between memory and reasoning may thus provide new insights into the neural predictors of real-world academic achievement. Moreover, a number of clinical conditions are associated with marked memory deficits and structural abnormalities in MTL and prefrontal areas (e.g., autism, schizophrenia, depression). Understanding how these regions develop to reach adult-like functionality is critical for creating effective treatment interventions for these mental health disorders throughout the lifespan.

? DESCRIPTION: The Center for Learning and Memory (CLM) at the University of Texas at Austin is an organized research unit that brings together researchers whose goal is to identify the neural mechanisms of learning and memory. The CLM has grown to include fifteen faculty, all hired since its inception in 2005. Given this growth, the highly interdisciplinary and collaborative nature of the CLM faculty, and the major University commitment to this research field, we believe all key elements are in place to implement an innovative and active training program in learning and memory. The CLM faculty represent a broad range of approaches to the mechanisms of learning and memory - from the molecules of neural information processing and synaptic plasticity to cellular and systems level studies to functional neuroimaging in humans. We will leverage the strengths of this collaborative faculty along with innovative and comprehensive training activities to implement a program that prepares graduate students and postdoctoral trainees to become innovative leaders in the future of learning and memory research. The proposed training has four important components. First, we will provide our trainees with hands-on instruction in the implementation of interdisciplinary approaches to the study of learning and memory that cross levels of analysis. Second, we will provide extensive training in computational neuroscience methods that are increasingly necessary to understanding the neural mechanisms that support learning and memory. Third, the proposed activities will provide our trainees with the ability to place their research in a biomedical contet, with a particular emphasis on the role of learning and memory processes in disorders of mental health. Finally, the proposed activities and resources provide our trainees with many opportunities for career development including the skills necessary to obtain a tenure track position (e.g., presentation and grant writing skills) as well as exposure to research-related careers outside of academia. These components will prepare our trainees to be the next generation of leading edge researchers dedicated to uncovering the neural mechanisms that support our ability to acquire new information and remember past experiences.

Project Summary/Abstract How does memory guide our choices in particular locations and contexts? How does our brain accomplish this? Memory, navigation, and context dependent decision-making are essential for adaptive human behavior and are impaired in several neurological and psychiatric disorders. This proposal aims to identify the basic mechanisms mediating context dependent memory representations in the human brain towards advancing refined therapeutic tools for memory enhancement in clinical populations. More specifically, this proposal will investigate the neural basis of context dependent memory encoding and retrieval, behavior that enables us to flexibly act in the world according to particular situations. Influential human brain imaging and lesion studies have identified that the hippocampus (HPC) and the medial prefrontal cortex (mPFC), along with their interactions, are where memory and navigational computations take place. However, these studies have poor temporal resolution and do not directly measure electrical activity. Thus, we don't understand how context dependent memories are formed and retrieved in humans. The proposed experiments will utilize direct human brain recordings from HPC and mPFC in epilepsy patients undergoing invasive seizure monitoring to yield new insight into the electrophysiological basis of human memory. Patients perform a context dependent learning and memory task in which objects are associated with different rewards depending on context. The task is embedded in a virtual environment, enabling comparisons of neural signatures of both spatial navigation and associative memory. We hypothesize that synchronous, ?phase coded? oscillatory activity within and between the HPC and mPFC supports context dependent memory. Aiming to identify the unique and overlapping electrophysiological mechanisms mediating context dependent representations, this proposal is likely to transform our understanding of how the human brain coordinates its activity in the service of adaptive human behavior. This work will also shed new light on how the human brain utilizes complex, context dependent associations to provide insight into putative mechanisms mediating impairments in several clinical populations.