Nicole M. Long

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

How do individuals decide to act based on a rewarding status quo versus an unexplored choice that might yield a better outcome? Recent evidence suggests that individuals may strategically explore as a function of the relative uncertainty about the expected value of options. However, the neural mechanisms supporting uncertainty-driven exploration remain underspecified. The present fMRI study scanned a reinforcement learning task in which participants stop a rotating clock hand in order to win points. Reward schedules were such that expected value could increase, decrease, or remain constant with respect to time. We fit several mathematical models to subject behavior to generate trial-by-trial estimates of exploration as a function of relative uncertainty. These estimates were used to analyze our fMRI data. Results indicate that rostrolateral prefrontal cortex tracks trial-by-trial changes in relative uncertainty, and this pattern distinguished individuals who rely on relative uncertainty for their exploratory decisions versus those who do not.

Separable Prefrontal Cortex Contributions to Free Recall

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 (Öztekin 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.

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

Noninvasive neuroimaging studies have revealed a network of brain regions that activate during human memory encoding; however, the relative timing of such activations remains unknown. Here we used intracranially recorded high-frequency activity (HFA) to first identify regions that activate during successful encoding. Then, we leveraged the high-temporal precision of HFA to investigate the timing of such activations. We found that memory encoding invokes two spatiotemporally distinct activations: early increases in HFA that involve the ventral visual pathway as well as the medial temporal lobe and late increases in HFA that involve the left inferior frontal gyrus, left posterior parietal cortex, and left ventrolateral temporal cortex. We speculate that these activations reflect higher-order visual processing and top-down modulation of attention/semantic information, respectively.

Subsequent memory effect in intracranial and scalp EEG

Successful memory encoding is marked by increases in 30-100Hz gamma-band activity in a broad network of brain regions. Activity in the 3-8Hz theta band has also been shown to modulate memory encoding, but this effect has been found to vary in direction across studies. Because of the diversity in memory tasks, and in recording and data-analytic methods, our knowledge of the theta frequency modulations remains limited. The difference in the directionality of these theta effects could arise from a distinction between global cortical and deeper subcortical effects. To address this issue, we examined the spectral correlates of successful memory encoding using intracranial EEG recordings in neurosurgical patients and scalp EEG recordings in healthy controls. We found significant theta (3-8Hz) power modulations (both increases and decreases) and high gamma (44-100Hz) power increases in both samples of participants. These results suggest that (1) there are two separate theta mechanisms supporting memory success, a broad theta decrease present across both the cortex and hippocampus as well as a theta power increase in the frontal cortex, (2) scalp EEG is capable of resolving high frequency gamma activity, and (3) iEEG theta effects are likely not the result of epileptic pathology.

Spatio-Spectral Mixed-Effects Model for Functional Magnetic Resonance Imaging Data

The goal of this article is to model cognitive control related activation among predefined regions of interest (ROIs) of the human brain while properly adjusting for the underlying spatio-temporal correlations. Standard approaches to fMRI analysis do not simultaneously take into account both the spatial and temporal correlations that are prevalent in fMRI data. This is primarily due to the computational complexity of estimating the spatio-temporal covariance matrix. More specifically, they do not take into account multiscale spatial correlation (between-ROIs and within-ROI). To address these limitations, we propose a spatio-spectral mixed-effects model. Working in the spectral domain simplifies the temporal covariance structure because the Fourier coefficients are approximately uncorrelated across frequencies. Additionally, by incorporating voxel-specific and ROI-specific random effects, the model is able to capture the multiscale spatial covariance structure: distance-dependent local correlation (within an ROI), and distance-independent global correlation (between-ROIs). Building on existing theory on linear mixed-effects models to conduct estimation and inference, we applied our model to fMRI data to study activation in prespecified ROIs in the prefontal cortex and estimate the correlation structure in the network. Simulation studies demonstrate that ignoring the multiscale correlation leads to higher false positive error rates.

Ventral striatum and the evaluation of memory retrieval strategies

Adaptive memory retrieval requires mechanisms of cognitive control that facilitate the recovery of goal-relevant information. Frontoparietal systems are known to support control of memory retrieval. However, the mechanisms by which the brain acquires, evaluates, and adapts retrieval strategies remain unknown. Here, we provide evidence that ventral striatal activation tracks the success of a retrieval strategy and correlates with subsequent reliance on that strategy. Human participants were scanned with fMRI while performing a lexical decision task. A rule was provided that indicated the likely semantic category of a target word given the category of a preceding prime. Reliance on the rule improved decision-making, as estimated within a drift diffusion framework. Ventral striatal activation tracked the benefit that relying on the rule had on decision-making. Moreover, activation in ventral striatum correlated with a participants subsequent reliance on the rule. Taken together, these results support a role for ventral striatum in learning and evaluating declarative retrieval strategies.

Recall dynamics reveal the retrieval of emotional context

Memory is often better for emotional rather than neutral stimuli. The benefit for emotional items could be the result of an associative mechanism whereby items are associated to a slowly updating context. Through this process, emotional features are integrated with context during study, and are reactivated during test. The presence of emotion in context would both provide a stronger retrieval cue, enhancing memory of emotional items, as well as lead to emotional clustering, whereby emotionally similar items are recalled consecutively. To measure whether associative mechanisms can explain the enhancement for emotional items, we conducted a free recall study in which most items were emotionally neutral to minimize effects of mood induction and to more closely reflect naturalistic settings. We found that emotional items were significantly more likely to be recalled than neutral items and that participants were more likely to transition between emotional items rather than between emotional and neutral items. Together, these results suggest that contextual encoding and retrieval mechanisms may drive the benefit for emotional items both within and outside the laboratory.

Successful memory formation is driven by contextual encoding in the core memory network

To understand how memories are successfully formed, scientists have compared neural activity during the encoding of subsequently remembered and forgotten items. Though this approach has elucidated a network of brain regions involved in memory encoding, this method cannot distinguish broad, non-specific signals from memory specific encoding processes, such as associative encoding. Associative encoding, which is a key mechanism of learning, can be seen in the tendency of participants to successively recall, or cluster, study neighbors. We assessed the electrophysiological correlates of associative processing by comparing intracranially recorded EEG activity during the encoding of items that were subsequently recalled and clustered; recalled and not clustered; or not recalled. We found that high frequency activity (HFA) in left prefrontal cortex, left temporal cortex and hippocampus increased during the encoding of subsequently recalled items. Critically, the magnitude of this effect was largest for those recalled items that were also subsequently clustered. HFA temporally dissociated across regions, with increases in left prefrontal cortex preceding those in hippocampus. Furthermore, late hippocampal HFA positively correlated with behavioral measures of clustering. These results suggest that associative processes linking items to their spatiotemporal context underlie the traditionally observed subsequent memory effect and support successful memory formation.

Hippocampal mismatch signals are modulated by the strength of neural predictions and their similarity to outcomes.

The hippocampus is thought to compare predicted events with current perceptual input, generating a mismatch signal when predictions are violated. However, most prior studies have only inferred when predictions occur without measuring them directly. Moreover, an important but unresolved question is whether hippocampal mismatch signals are modulated by the degree to which predictions differ from outcomes. Here, we conducted a human fMRI study in which subjects repeatedly studied various word–picture pairs, learning to predict particular pictures (outcomes) from the words (cues). After initial learning, a subset of cues was paired with a novel, unexpected outcome, whereas other cues continued to predict the same outcome. Critically, when outcomes changed, the new outcome was either “near” to the predicted outcome (same visual category as the predicted picture) or “far” from the predicted outcome (different visual category). Using multivoxel pattern analysis, we indexed cue-evoked reactivation (prediction) within neocortical areas and related these trial-by-trial measures of prediction strength to univariate hippocampal responses to the outcomes. We found that prediction strength positively modulated hippocampal responses to unexpected outcomes, particularly when unexpected outcomes were close, but not identical, to the prediction. Hippocampal responses to unexpected outcomes were also associated with a tradeoff in performance during a subsequent memory test: relatively faster retrieval of new (updated) associations, but relatively slower retrieval of the original (older) associations. Together, these results indicate that hippocampal mismatch signals reflect a comparison between active predictions and current outcomes and that these signals are most robust when predictions are similar, but not identical, to outcomes. SIGNIFICANCE STATEMENT Although the hippocampus is widely thought to signal “mismatches” between memory-based predictions and outcomes, previous research has not linked hippocampal mismatch signals directly to neural measures of prediction strength. Here, we show that hippocampal mismatch signals increase as a function of the strength of predictions in neocortical regions. This increase in hippocampal mismatch signals was particularly robust when outcomes were similar, but not identical, to predictions. These results indicate that hippocampal mismatch signals are driven by both the active generation of predictions and the similarity between predictions and outcomes.

Optimizing design efficiency of free recall events for fmri

Free recall is a fundamental paradigm for studying memory retrieval in the context of minimal cue support. Accordingly, free recall has been extensively studied using behavioral methods. However, the neural mechanisms that support free recall have not been fully investigated due to technical challenges associated with probing individual recall events with neuroimaging methods. Of particular concern is the extent to which the uncontrolled latencies associated with recall events can confer sufficient design efficiency to permit neural activation for individual conditions to be distinguished. The present study sought to rigorously assess the feasibility of testing individual free recall events with fMRI. We used both theoretically and empirically derived free recall latency distributions to generate simulated fMRI data sets and assessed design efficiency across a range of parameters that describe free recall performance and fMRI designs. In addition, two fMRI experiments empirically assessed whether differential neural activation in visual cortex at onsets determined by true free recall performance across different conditions can be resolved. Collectively, these results specify the design and performance parameters that can provide comparable efficiency between free recall designs and more traditional jittered event-related designs. These findings suggest that assessing BOLD response during free recall using fMRI is feasible, under certain conditions, and can serve as a powerful tool in understanding the neural bases of memory search and overt retrieval.