Jesse Rissman

Top-down suppression deficit underlies working memory impairment in normal aging.

In this study, we assess the impact of normal aging on top-down modulation, a cognitive control mechanism that supports both attention and memory by the suppression and enhancement of sensory processing in accordance with task goals. Using fMRI (functional magnetic resonance imaging), we show that healthy older adults demonstrated a prominent deficit in the suppression of cortical activity associated with task-irrelevant representations, whereas enhancement of task-relevant activity was preserved. Moreover, this suppression-specific attention deficit correlated with impaired working memory performance.

Measuring functional connectivity during distinct stages of a cognitive task

The inherently multivariate nature of functional brain imaging data affords the unique opportunity to explore how anatomically disparate brain areas interact during cognitive tasks. We introduce a new method for characterizing inter-regional interactions using event-related functional magnetic resonance imaging (fMRI) data. This methods principle advantage over existing analytical techniques is its ability to model the functional connectivity between brain regions during distinct stages of a cognitive task. The method is implemented by using separate covariates to model the activity evoked during each stage of each individual trial in the context of the general linear model (GLM). The resulting parameter estimates (beta values) are sorted according to the stage from which they were derived to form a set of stage-specific beta series. Regions whose beta series are correlated during a given stage are inferred to be functionally interacting during that stage. To validate the assumption that correlated fluctuations in trial-to-trial beta values imply functional connectivity, we applied the method to an event-related fMRI data set in which subjects performed two sequence-tapping tasks. In concordance with previous electrophysiological and fMRI coherence studies, we found that the task requiring greater bimanual coordination induced stronger correlations between motor regions of the two hemispheres. The method was then applied to an event-related fMRI data set in which subjects performed a delayed recognition task. Distinct functional connectivity maps were generated during the component stages of this task, illustrating how important and novel observations of neural networks within the isolated stages of a cognitive task can be obtained.

Functional connectivity during working memory maintenance.

Neurophysiological experiments with monkeys have demonstrated that working memory (WM) is associated with persistent neural activity in multiple brain regions, such as the prefrontal cortex (PFC), the parietal cortex, and posterior unimodal association areas. WM maintenance is believed to require the coordination of these brain regions, which do not function in isolation but, rather, interact to maintain visual percepts that are no longer present in the environment. However, single-unit physiology studies and traditional univariate analyses of functional brain imaging data cannot evaluate interactions between distant brain regions, and so evidence of regional integration during WM maintenance is largely indirect. In this study, we utilized a recently developed multivariate analysis method that allows us to explore functional connectivity between brain regions during the distinct stages of a delayed face recognition task. To characterize the neural network mediating the on-line maintenance of faces, the fusiform face area (FFA) was defined as a seed and was then used to generate whole-brain correlation maps. A random effects analysis of the correlation data revealed a network of brain regions exhibiting significant correlations with the FFA seed during the WM delay period. This maintenance network included the dorsolateral and ventrolateral PFC, the premotor cortex, the intraparietal sulcus, the caudate nucleus, the thalamus, the hippocampus, and occipitotemporal regions. These findings support the notion that the coordinated functional interaction between nodes of a widely distributed network underlies the active maintenance of a perceptual representation.

An Event-Related fMRI Investigation of Implicit Semantic Priming

The neural basis underlying implicit semantic priming was investigated using event-related fMRI. Prime-target pairs were presented auditorily for lexical decision (LD) on the target stimulus, which was either semantically related or unrelated to the prime, or was a nonword. A tone task was also administered as a control. Behaviorally, all participants demonstrated semantic priming in the LD task. fMRI results showed that for all three conditions of the LD task, activation was seen in the superior temporal gyrus (STG), the middle temporal gyrus (MTG), and the inferior parietal lobe, with greater activation in the unrelated and nonword conditions than in the related condition. Direct comparisons of the related and unrelated conditions revealed foci in the left STG, left precentral gyrus, left and right MTGs, and right caudate, exhibiting significantly lower activation levels in the related condition. The reduced activity in the temporal lobe suggests that the perception of the prime word activates a lexical semantic network that shares common elements with the target word, and, thus, the target can be recognized with enhanced neural efficiency. The frontal lobe reductions most likely reflect the increased efficiency in monitoring the activation of lexical representations in the temporal lobe, making a decision, and planning the appropriate motor response.

Distributed Representations in Memory: Insights from Functional Brain Imaging

Forging new memories for facts and events, holding critical details in mind on a moment-to-moment basis, and retrieving knowledge in the service of current goals all depend on a complex interplay between neural ensembles throughout the brain. Over the past decade, researchers have increasingly utilized powerful analytical tools (e.g., multivoxel pattern analysis) to decode the information represented within distributed functional magnetic resonance imaging activity patterns. In this review, we discuss how these methods can sensitively index neural representations of perceptual and semantic content and how leverage on the engagement of distributed representations provides unique insights into distinct aspects of memory-guided behavior. We emphasize that, in addition to characterizing the contents of memories, analyses of distributed patterns shed light on the processes that influence how information is encoded, maintained, or retrieved, and thus inform memory theory. We conclude by highlighting open questions about memory that can be addressed through distributed pattern analyses.

Imaging the Human Medial Temporal Lobe with High-Resolution fMRI

High-resolution functional MRI (hr-fMRI) affords unique leverage on the functional properties of human medial temporal lobe (MTL) substructures. We review initial hr-fMRI efforts to delineate (1) encoding and retrieval processes within the hippocampal circuit, (2) hippocampal subfield contributions to pattern separation and pattern completion, and (3) the representational capabilities of distinct MTL subregions. Extant data reveal functional heterogeneity within human MTL and highlight the promise of hr-fMRI for bridging human, animal, and computational approaches to understanding MTL function.

Detecting individual memories through the neural decoding of memory states and past experience

A wealth of neuroscientific evidence indicates that our brains respond differently to previously encountered than to novel stimuli. There has been an upswell of interest in the prospect that functional MRI (fMRI), when coupled with multivariate data analysis techniques, might allow the presence or absence of individual memories to be detected from brain activity patterns. This could have profound implications for forensic investigations and legal proceedings, and thus the merits and limitations of such an approach are in critical need of empirical evaluation. We conducted two experiments to investigate whether neural signatures of recognition memory can be reliably decoded from fMRI data. In Exp. 1, participants were scanned while making explicit recognition judgments for studied and novel faces. Multivoxel pattern analysis (MVPA) revealed a robust ability to classify whether a given face was subjectively experienced as old or new, as well as whether recognition was accompanied by recollection, strong familiarity, or weak familiarity. Moreover, a participants subjective mnemonic experiences could be reliably decoded even when the classifier was trained on the brain data from other individuals. In contrast, the ability to classify a faces objective old/new status, when holding subjective status constant, was severely limited. This important boundary condition was further evidenced in Exp. 2, which demonstrated that mnemonic decoding is poor when memory is indirectly (implicitly) probed. Thus, although subjective memory states can be decoded quite accurately under controlled experimental conditions, fMRI has uncertain utility for objectively detecting an individuals past experiences.

Fidelity of neural reactivation reveals competition between memories

Remembering an event from the past is often complicated by the fact that our memories are cluttered with similar events. Though competition is a fundamental part of remembering, there is little evidence of how mnemonic competition is neurally represented. Here, we assessed whether competition between visual memories is captured in the relative degree to which target vs. competing memories are reactivated within the ventral occipitotemporal cortex (VOTC). To assess reactivation, we used multivoxel pattern analysis of fMRI data, quantifying the degree to which retrieval events elicited patterns of neural activity that matched those elicited during encoding. Consistent with recent evidence, we found that retrieval of visual memories was associated with robust VOTC reactivation and that the degree of reactivation scaled with behavioral expressions of target memory retrieval. Critically, competitive remembering was associated with more ambiguous patterns of VOTC reactivation, putatively reflecting simultaneous reactivation of target and competing memories. Indeed, the more weakly that target memories were reactivated, the more likely that competing memories were later remembered. Moreover, when VOTC reactivation indicated that conflict between target and competing memories was high, frontoparietal mechanisms were markedly engaged, revealing specific neural mechanisms that tracked competing mnemonic evidence. Together, these findings provide unique evidence that neural reactivation captures competition between individual memories, providing insight into how well target memories are retrieved in the present and how likely competing memories will be remembered in the future.

The Perception of Voice Onset Time: An fMRI Investigation of Phonetic Category Structure

This study explored the neural systems underlying the perception of phonetic category structure by investigating the perception of a voice onset time (VOT) continuum in a phonetic categorization task. Stimuli consisted of five synthetic speech stimuli which ranged in VOT from 0 msec ([da]) to 40 msec ([ta]). Results from 12 subjects showed that the neural system is sensitive to VOT differences of 10 msec and that details of phonetic category structure are retained throughout the phonetic processing stream. Both the left inferior frontal gyrus (IFG) and cingulate showed graded activation as a function of category membership with increasing activation as stimuli approached the phonetic category boundary. These results are consistent with the view that the left IFG is involved in phonetic decision processes, with the extent of activation influenced by increased resources devoted to resolving phonetic category membership and/or selecting between competing phonetic categories. Activation patterns in the cingulate suggest that it is sensitive to stimulus difficulty and resolving response conflict. In contrast, activation in the posterior left middle temporal gyrus and the left angular gyrus showed modulation of activation only to the best fit of the phonetic category, suggesting that these areas are involved in mapping sound structure to its phonetic representation. The superior temporal gyrus (STG) bilaterally showed weaker sensitivity to the differences in phonetic category structure, providing further evidence that the STG is involved in the early analysis of the sensory properties of speech.

Modulation of inferotemporal cortex activation during verbal working memory maintenance

Regions of the left inferotemporal cortex are involved in visual word recognition and semantics. We utilized functional magnetic resonance imaging to localize an inferotemporal language area and to demonstrate that this area is involved in the active maintenance of visually presented words in working memory. Maintenance activity in this inferotemporal area showed an effect of memory load for words, but not pseudowords. In the absence of visual input, the selective modulation of this language-related inferotemporal area for the maintenance of words is accompanied by an increased functional connectivity with left prefrontal cortex. These results demonstrate an involvement of inferotemporal cortex in verbal working memory and provide neurophysiological support for the notion that nonphonological language representations can be recruited in the service of verbal working memory. More generally, they suggest that verbal working memory should be conceptualized as the frontally guided, sustained activation of pre-existing cortical language representations.