The last decade has seen dramatic technological and conceptual changes in research on episodic memory and the brain. New technologies, and increased use of more naturalistic observations, have enabled investigators to delve deeply into the structures that mediate episodic memory, particularly the hippocampus, and to track functional and structural interactions among brain regions that support it. Conceptually, episodic memory is increasingly being viewed as subject to lifelong transformations that are reflected in the neural substrates that mediate it. In keeping with this dynamic perspective, research on episodic memory (and the hippocampus) has infiltrated domains, from perception to language and from empathy to problem solving, that were once considered outside its boundaries. Using the component process model as a framework, and focusing on the hippocampus, its subfields, and specialization along its longitudinal axis, along with its interaction with other brain regions, we consider these new developments and their implications for the organization of episodic memory and its contribution to functions in other domains.

/pdf/episodic-memory-and-beyond-the-hippocampus-and-neocortex-in-20cqmrqvoe.pdf

Episodic Memory and Beyond: The Hippocampus and Neocortex in Transformation

Neural Computations Underlying Arbitration between Model-Based and Model-free Learning

Classical regression methods treat covariates as a vector and estimate a corresponding vector of regression coefficients Modern applications in medical imaging generate covariates of more complex form such as multidimensional arrays (tensors) Traditional statistical and computational methods are proving insufficient for analysis of these high-throughput data due to their ultrahigh dimensionality as well as complex structure In this article, we propose a new family of tensor regression models that efficiently exploit the special structure of tensor covariates Under this framework, ultrahigh dimensionality is reduced to a manageable level, resulting in efficient estimation and prediction A fast and highly scalable estimation algorithm is proposed for maximum likelihood estimation and its associated asymptotic properties are studied Effectiveness of the new methods is demonstrated on both synthetic and real MRI imaging data Supplementary materials for this article are available online

/pdf/tensor-regression-with-applications-in-neuroimaging-data-1qmr9yg02s.pdf

Tensor Regression with Applications in Neuroimaging Data Analysis

Thisstudy usedpositron emission tomogra- phy(PET)toinvestigate theneuroanatomical correlates of remembering previously experienced events. Twelve young healthy adults listened to"old"meaningful sentences which they hadstudied 24hrpreviously. Asacontrol task thesubjects listened tocomparable "new"sentences that theyhadnever heard before. Regional cerebral blood flowassociated with each task wasmeasured byPETscans using 150-labeled water. Cowparison (old-sentence task minus new-sentence task) ofthe PETimages revealed anextended strip ofincreased blood flow intheright dorsolateral prefrontal cortex (Brodmann's areas 10,46,and9)andtheanterior portion ofarea6.Other principal regions ofincreased blood flow weresituated around theleft anterior cingulate sulcus andbilaterally intheparietal lobes (areas 7and40). Major decreases inblood flowwere situated bilaterally inthetemporal lobes (areas 21,22,41,and 42). Ahigh proportion ofactivity changes seemed tobelocated inthedepths ofcortical sulci. Increases inblood flow areseen asreflecting theoperations ofawidely distributed neuronal network involving prefrontal andparietal cortical regions that subserves theconscious recollection ofpreviously experienced events. Decreases inblood flow inthetemporal auditory areas areinterpreted asreflecting auditory priming. Theprevalence ofsulcal blood-flow changes mayreflect extensive cortical gYrification; itmayalso indicate that memory-related processes rely onthedensely packed neuropil ofsulcal regions.

Neuroanatomical correlates ofretrieval inepisodic memory: Auditory sentence recognition

Frontal midline theta oscillations during working memory maintenance and episodic encoding and retrieval.

http://ski.cog.brown.edu/papers/BadreEtAl_explore.pdf

Rostrolateral prefrontal cortex and individual differences in uncertainty-driven exploration.

http://memory.psych.upenn.edu/files/pubs/LongEtal14.pdf

Subsequent memory effect in intracranial and scalp EEG.

http://memory.psych.upenn.edu/files/pubs/BurkEtal14.pdf

Human intracranial high-frequency activity maps episodic memory formation in space and time.

In everyday life, we often must remember the past in the absence of helpful cues in the environment. In these cases, the brain directs retrieval by relying on internally maintained cues and strategies. Free recall is a widely used behavioral paradigm for studying retrieval with minimal cue support. During free recall, individuals often recall semantically related items consecutively—an effect termed semantic clustering—and previous studies have sought to understand clustering to gain leverage on the basic mechanisms supporting strategic recall. Successful recall and semantic clustering depend on the prefrontal cortex (PFC). However, as a result of methodological limitations, few functional magnetic resonance imaging (fMRI) studies have assessed the neural mechanisms at encoding that support subsequent recall, and none have tested the event-related correlates of recall itself. Thus, it remains open whether one or several frontal control mechanisms operate during encoding and recall. Here, we applied a recently developed method (Oztekin et al., 2010) to assess event-related fMRI signal changes during free recall. During encoding, dorsolateral prefrontal cortex (DLPFC) activation was predictive of subsequent semantic clustering. In contrast, subregions of ventrolateral prefrontal cortex (VLPFC) were predictive of subsequent recall, whether clustered or nonclustered, and were inversely associated with clustering during recall. These results suggest that DLPFC supports relational processes at encoding that are sufficient to produce category clustering effects during recall. Conversely, controlled retrieval mechanisms supported by VLPFC support item-specific search during recall.

https://www.jneurosci.org/content/jneuro/30/33/10967.full.pdf

Separable prefrontal cortex contributions to free recall.

Contiguity is one of the major predictors of recall dynamics in human episodic memory. But there are many competing theories of how the memory system gives rise to contiguity. Here we provide a set of benchmark findings for which any such theory should account. These benchmarks are drawn from a review of the existing literature as well as analyses of both new and archival data. They include 34 distinct findings on how various factors including individual and group differences, task parameters, and type of stimuli influence the magnitude of the contiguity effect. We will see that contiguity is observed in a range of tasks including recognition, paired associates, and autobiographical recall and across a range of time scales including minutes, days, weeks, and years. The broad pattern of data point toward a theory in which contiguity arises from fundamental memory mechanisms that encode and search an approximately time scale invariant representation of temporal distance.

/pdf/contiguity-in-episodic-memory-2u7uw5mvpp.pdf

Nicole M. Long

Papers

Rostrolateral prefrontal cortex and individual differences in uncertainty-driven exploration.

Subsequent memory effect in intracranial and scalp EEG.

Human intracranial high-frequency activity maps episodic memory formation in space and time.

Separable prefrontal cortex contributions to free recall.

Contiguity in episodic memory.