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The sensory recruitment hypothesis conceptualizes information in working memory as being activated representations of information in long-term memory. Accordingly, changes made to an item in working memory would be expected to influence its subsequent retention. Here, we tested the hypothesis that suppressing information from working memory, which can reduce short-term access to that information, may also alter its long-term neural representation. We obtained fMRI data (n = 25; 13 female / 12 male participants) while participants completed a working memory removal task with scene images as stimuli, followed by a final surprise recognition test of the examined items. We applied a multivariate pattern analysis to the data to quantify the engagement of suppression on each trial, to track the contents of working memory during suppression, and to assess representational changes afterward. Our analysis confirms previous reports that suppression of information in working memory involves focused attention to target and remove unwanted information. Furthermore, our findings provide new evidence that even a single dose of suppression of an item in working memory can (if engaged with sufficient strength) produce lasting changes in its neural representation, particularly weakening the unique, item-specific features, which leads to forgetting. Our study sheds light on the underlying mechanisms that contribute to the suppression of unwanted thoughts and highlights the dynamic interplay between working memory and long-term memory. [ABSTRACT FROM AUTHOR]

Serial dependence has shown seemingly contradictory effects on visual perception and working memory. While serial dependence promotes perpetual and mnemonic stability, it biases behavioral reports toward prior information. The neural mechanisms that drive both biasing and adaptive stabilizing effects are not well understood. We proposed and tested a reactivation and integration mechanism that can account for these contradictory effects. We used multivariate pattern analyses of EEG data (26 human participants, 17 females, 9 males) to examine the reactivation of prior reported orientation during the delay period of a visual working memory task. The reactivation strength of prior reports, but not prior sensory items, was predictive of the magnitude of serial dependency biases. These reactivated representations integrated with the representation of the current memory item and improved the ability to decode the current contents of memory. Overall, our data provide convergent evidence suggesting that prior reports in a visual working memory task are reactivated on the subsequent trial and become integrated with current memory representations. This similarity-dependent reactivation mechanism drives both report biasing and stabilization effects attributed to serial dependence in working memory. [ABSTRACT FROM AUTHOR]

Recently, multi-voxel pattern analysis has verified that information can be removed from working memory (WM) via three distinct operations replacement, suppression, or clearing compared to information being maintained (Kim et al., 2020). While univariate analyses and classifier importance maps in Kim et al. (2020) identified brain regions that contribute to these operations, they did not elucidate whether these regions represent the operations similarly or uniquely. Using Leiden-community-detection on a sample of 55 humans (17 male), we identified four brain networks, each of which has a unique configuration of multi-voxel activity patterns by which it represents these WM operations. The visual network (VN) shows similar multi-voxel patterns for maintain and replace, which are highly dissimilar from suppress and clear, suggesting this network differentiates whether an item is held in WM or not. The somatomotor network (SMN) shows a distinct multi-voxel pattern for clear relative to the other operations, indicating the uniqueness of this operation. The default mode network (DMN) has distinct patterns for suppress and clear, but these two operations are more similar to each other than to maintain and replace, a pattern intermediate to that of the VN and SMN. The frontoparietal control network (FPCN) displays distinct multi-voxel patterns for each of the four operations, suggesting that this network likely plays an important role in implementing theseWMoperations. These results indicate that the operations involved in removing information fromWMcan be performed in parallel by distinct brain networks, each of which has a particular configuration by which they represent these operations. [ABSTRACT FROM AUTHOR]

Working memory is a vital, but capacity-limited, cognitive instrument that requires frequent updating as our goals and environment change. Individuals diagnosed with depression have a reduced capacity compared with the general population, as they have a propensity to fixate on negative information, even when it is not relevant for the task at hand. Here we investigated how characteristics of psychiatric illnesses, such as rumination, affect a person's ability to efficiently update emotional information in mind. We used both neutral and negative pictures of scenes in a working memory updating task that required participants to occasionally replace items held in mind during a brief delay period. Participants were presented with a probe item at the end of each trial and asked to report whether that item was in their current memory set. Responses were slowest and least accurate for images that had been replaced (i.e., "lures"), indicating there was some difficulty in successfully updating working memory in this paradigm. Participants who have both a high propensity to ruminate and a low working memory capacity were significantly more likely to false alarm to these lures. While emotional valence did not impact accuracy for these participants, their false alarms were faster for negative stimuli compared with neutral stimuli, indicating that task-irrelevant emotional information was more difficult to remove from working memory. These results demonstrate how rumination impairs goal-directed behavior by obscuring the boundary between relevant and irrelevant information in working memory. [ABSTRACT FROM AUTHOR]

Prospective memory (PM) describes the ability to remember to perform goal-relevant actions at an appropriate time in the future amid concurrent demands. A key contributor to PM performance is thought to be the effortful monitoring of the environment for PM-related cues, a process whose existence is typically inferred from a behavioral interference measure of reaction times. This measure, referred to as "PM costs," is an informative but indirect proxy for monitoring, and it may not be sufficient to understand PM behaviors in all situations. In this study, we asked participants to perform a visual search task with arrows that varied in difficulty while concurrently performing a delayed-recognition PM task with pictures of faces and scenes. To gain a precise measurement of monitoring behavior, we used eye-tracking to record fixations to all task-relevant stimuli and related these fixation measures to both PM costs and PM accuracy. We found that PM costs reflected dissociable monitoring strategies: higher costs were associated with early and frequent monitoring while lower costs were associated with delayed and infrequent monitoring. Moreover, the link between fixations and PM costs varied with cognitive load, and the inclusion of fixation data yielded better predictions of PM accuracy than using PM costs alone. This study demonstrates the benefit of eye-tracking to disentangle the nature of PM costs and more precisely describe strategies involved in prospective remembering. [ABSTRACT FROM AUTHOR]

Neurobiological evidence in rodents indicates that threat extinction incorporates reward neurocircuitry. Consequently, incorporating reward associations with an extinction memory may be an effective strategy to persistently attenuate threat responses. Moreover, while there is considerable research on the short-term effects of extinction strategies in humans, the long-term effects of extinction are rarely considered. In a within-subjects fMRI study with both female and male participants, we compared counterconditioning (CC; a form of rewarded-extinction) to standard extinction at recent (24 h) and remote (approximately one month) retrieval tests. Relative to standard extinction, rewarded extinction diminished 24-h relapse of arousal and threat expectancy, and reduced activity in brain regions associated with the appraisal and expression of threat (e.g., thalamus, insula, periaqueductal gray). The retrieval of reward-associated extinction memory was accompanied by functional connectivity between the amygdala and the ventral striatum, whereas the retrieval of standard-extinction memories was associated with connectivity between the amygdala and ventromedial prefrontal cortex (vmPFC). One month later, the retrieval of both standard-extinction and rewarded-extinction was associated with amygdala-vmPFC connectivity. However, only rewarded extinction created a stable memory trace in the vmPFC, identified through overlapping multivariate patterns of fMRI activity from extinction to 24-h and one-month retrieval. These findings provide new evidence that reward may generate a more stable and enduring memory trace of attenuated threat in humans. [ABSTRACT FROM AUTHOR]

Working memory is an essential component of cognition that facilitates goal-directed behavior. Famously, it is severely limited and performance suffers when memory load exceeds an individual's capacity. Modeling of visual working memory responses has identified two likely types of errors: guesses and swaps. Swap errors may arise from a misbinding between the features of different items. Alternatively, these errors could arise from memory noise in the feature dimension used for cueing a to-be-tested memory item, resulting in the wrong item being selected. Finally, it is possible that so-called swap errors actually reflect informed guessing, which could occur at the time of a cue, or alternatively, at the time of the response. Here, we combined behavioral response modeling and fMRI pattern analysis to test the hypothesis that swap errors involve the active maintenance of an incorrect memory item. After the encoding of six spatial locations, a retro-cue indicated which location would be tested after memory retention. On accurate trials, we could reconstruct a memory representation of the cued location in both early visual cortex and intraparietal sulcus. On swap error trials identified with mixture modeling, we were able to reconstruct a representation of the swapped location, but not of the cued location, suggesting the maintenance of the incorrect memory item before response. Moreover, participants subjectively responded with some level of confidence, rather than complete guessing, on a majority of swap error trials. Together, these results suggest that swap errors are not mere response-phase guesses, but instead result from failures of selection in working memory, contextual binding errors, or informed guesses, which produce active maintenance of incorrect memory representations. [ABSTRACT FROM AUTHOR]

Previous work has shown that functional magnetic resonance imaging (fMRI) activity patterns associated with individual fingers can be shifted by temporary impairment of the hand. Here, we investigated whether these neural activity patterns could be modulated endogenously and whether any behavioral changes result from this modulation. We used decoded neurofeedback in healthy individuals to encourage participants to shift the neural activity pattern in sensorimotor cortex of the middle finger toward the index finger, and the ring finger toward the little finger. We first mapped the neural activity patterns for all fingers of the right hand in an fMRI pattern localizer session. Then, in three subsequent neurofeedback sessions, participants were rewarded after middle/ring finger presses according to their activity pattern overlap during each trial. A force-sensitive keyboard was used to ensure that participants were not altering their physical finger coordination patterns. We found evidence that participants could learn to shift the activity pattern of the ring finger but not of the middle finger. Increased variability of these activity patterns during the localizer session was associated with the ability of participants to modulate them using neurofeedback. Participants also showed an increased preference for the ring finger but not for the middle finger in a postneurofeedback motor task. Our results show that neural activity and behaviors associated with the ring finger are more readily modulated than those associated with the middle finger. These results have broader implications for rehabilitation of individual finger movements, which may be limited or enhanced by individual finger plasticity after neurological injury. NEW & NOTEWORTHY It may be possible to remobilize fingers after neurological injury by altering neural activity patterns. Toward this end, we examined whether finger-related neural activity patterns could be modified in healthy individuals without physical intervention, using fMRI neurofeedback. Our findings show that greater variability of neural patterns at baseline predicted a participant’s ability to successfully shift these patterns. Because neural variability is common in individuals poststroke, this illustrates a potential clinical benefit of this procedure. [ABSTRACT FROM AUTHOR]

The inability to individuate finger movements is a common impairment following stroke. Conventional physical therapy ignores underlying neural changes with recovery, leaving it unclear why sensorimotor function often remains impaired. Functional MRI neurofeedback can monitor neural activity and reinforce it towards a healthy template to restore function. However, identifying an individualized training template may not be possible depending on the severity of impairment. In this study, we investigated the use of functional alignment of brain data across healthy participants to create an idealized neural template to be used as a training target for new participants. We employed multi-voxel pattern analyses to assess the prediction accuracy and robustness to missing data of pre-trained functional templates corresponding to individual finger presses. We found a significant improvement in classification accuracy (p < 0.001) of individual finger presses when group data was aligned based on function (88%) rather than anatomy (46%). Importantly, we found no significant drop in performance when aligning a new participant to a pre-established template as compared to including this new participant in the creation of a new template. These results indicate that functionally aligned templates could provide an effective surrogate training target for patients following neurological injury. [ABSTRACT FROM AUTHOR]

Working memory capacity is incredibly limited and thus it is important to use this resource wisely. Prior knowledge in long-term memory can aid in efficient encoding of information by allowing for the prioritization of novel stimuli over familiar ones. Here we used a full-report procedure in a visual working memory paradigm, where participants reported the location of six colored circles in any order, to examine the influence of prior information on resource allocation in working memory. Participants learned that one of the items appeared in a restricted range of locations, whereas the remaining items could appear in any location. We found that participants' memory performance benefited from learning this prior information. Specifically, response precision increased for all items when prior information was available for one of the items. Responses for both familiar and novel items were systematically ordered from highest to lowest precision. Participants tended to report the familiar item in the second half of the six responses and did so with greater precision than for novel items. Moreover, novel items that appeared near the center of the prior location were reported with worse precision than novel items that appeared elsewhere. This shows that people strategically allocated working memory resources by ignoring information that appeared in predictable locations and prioritizing the encoding of information that appeared in unpredictable locations. Together these findings demonstrate that people rely on long-term memory not only for remembering familiar items, but also for the strategic allocation of their limited capacity working memory resources. [ABSTRACT FROM AUTHOR]

Holding information in working memory is essential for cognition, but removing unwanted thoughts is equally important. Here we use multivariate pattern analyses of brain activity to demonstrate the successful manipulation and removal of information from working memory using different strategies including suppressing a specific thought, replacing a thought with a different one, and clearing the mind of all thought. These strategies are supported by distinct brain regions and have differential consequences for allowing new information to be encoded. There are multiple methods of clearing one's mind of current thoughts. Here the authors use fMRI decoding to confirm the successful clearing of minds using different strategies, and show that these strategies have distinct neural signatures. [ABSTRACT FROM AUTHOR]

Mindfulness and compassion meditation are thought to cultivate prosocial behavior. However, the lack of diverse representation within both scientific and participant populations in contemplative neuroscience may limit generalizability and translation of prior findings. To address these issues, we propose a research framework called Intersectional Neuroscience which adapts research procedures to be more inclusive of under-represented groups. Intersectional Neuroscience builds inclusive processes into research design using two main approaches: 1) community engagement with diverse participants, and 2) individualized multivariate neuroscience methods to accommodate neural diversity. We tested the feasibility of this framework in partnership with a diverse U.S. meditation center (East Bay Meditation Center, Oakland, CA). Using focus group and community feedback, we adapted functional magnetic resonance imaging (fMRI) screening and recruitment procedures to be inclusive of participants from various under-represented groups, including racial and ethnic minorities, gender and sexual minorities, people with disabilities, neuropsychiatric disorders, and/or lower income. Using person-centered screening and study materials, we recruited and scanned 15 diverse meditators (80% racial/ethnic minorities, 53% gender and sexual minorities). The participants completed the EMBODY task – which applies individualized machine learning algorithms to fMRI data – to identify mental states during breath-focused meditation, a basic skill that stabilizes attention to support interoception and compassion. All 15 meditators' unique brain patterns were recognized by machine learning algorithms significantly above chance levels. These individualized brain patterns were used to decode the internal focus of attention throughout a 10-min breath-focused meditation period, specific to each meditator. These data were used to compile individual-level attention profiles during meditation, such as the percentage time attending to the breath, mind wandering, or engaging in self-referential processing. This study provides feasibility of employing an intersectional neuroscience approach to include diverse participants and develop individualized neural metrics of meditation practice. Through inclusion of more under-represented groups while developing reciprocal partnerships, intersectional neuroscience turns the research process into an embodied form of social action. [ABSTRACT FROM AUTHOR]

Meditation practices are often used to cultivate interoception or internally-oriented attention to bodily sensations, which may improve health via cognitive and emotional regulation of bodily signals. However, it remains unclear how meditation impacts internal attention (IA) states due to lack of measurement tools that can objectively assess mental states during meditation practice itself, and produce time estimates of internal focus at individual or group levels. To address these measurement gaps, we tested the feasibility of applying multi-voxel pattern analysis (MVPA) to single-subject fMRI data to: (1) learn and recognize internal attentional states relevant for meditation during a directed IA task; and (2) decode or estimate the presence of those IA states during an independent meditation session. Within a mixed sample of experienced meditators and novice controls (N = 16), we first used MVPA to develop single-subject brain classifiers for five modes of attention during an IA task in which subjects were specifically instructed to engage in one of five states [i.e., meditation-related states: breath attention, mind wandering (MW), and self-referential processing, and control states: attention to feet and sounds]. Using standard cross-validation procedures, MVPA classifiers were trained in five of six IA blocks for each subject, and predictive accuracy was tested on the independent sixth block (iterated until all volumes were tested, N = 2,160). Across participants, all five IA states were significantly recognized well above chance (>41% vs. 20% chance). At the individual level, IA states were recognized in most participants (87.5%), suggesting that recognition of IA neural patterns may be generalizable for most participants, particularly experienced meditators. Next, for those who showed accurate IA neural patterns, the originally trained classifiers were applied to a separate meditation run (10-min) to make an inference about the percentage time engaged in each IA state (breath attention, MW, or self-referential processing). Preliminary group-level analyses demonstrated that during meditation practice, participants spent more time attending to breath compared to MW or self-referential processing. This paradigm established the feasibility of using MVPA classifiers to objectively assess mental states during meditation at the participant level, which holds promise for improved measurement of internal attention states cultivated by meditation. [ABSTRACT FROM AUTHOR]

Working memory persists in the face of distraction, yet not without consequence. Previous research has shown that memory for low-level visual features is systematically influenced by the maintenance or presentation of a similar distractor stimulus. Responses are frequently biased in stimulus space towards a perceptual distractor, though this has yet to be determined for high-level stimuli. We investigated whether these influences are shared for complex visual stimuli such as faces. To quantify response accuracies for these stimuli, we used a delayed-estimation task with a computer-generated "face space" consisting of 80 faces that varied continuously as a function of age and sex. In a set of three experiments, we found that responses for a target face held in working memory were biased towards a distractor face presented during the maintenance period. The amount of response bias did not vary as a function of distance between target and distractor. Our data suggest that, similar to low-level visual features, high-level face representations in working memory are biased by the processing of related but task-irrelevant information. [ABSTRACT FROM AUTHOR]

The human brain constantly anticipates the future based on memories of the past. Encountering a familiar situation reactivates memory of previous encounters, which can trigger a prediction of what comes next to facilitate responsiveness. However, a prediction error can lead to pruning of the offending memory, a process that weakens its representation in the brain and leads to forgetting. Our goal in this study was to evaluate whether memories are spared from such pruning in situations that allow for accurate predictions at the categorical level, despite prediction errors at the item level. Participants viewed a sequence of objects, some of which reappeared multiple times ("cues"), followed always by novel items. Half of the cues were followed by new items from different (unpredictable) categories, while others were followed by new items from a single (predictable) category. Pattern classification of fMRI data was used to identify category-specific predictions after each cue. Pruning was observed only in unpredictable contexts, while encoding of new items was less robust in predictable contexts. These findings demonstrate that how associative memories are updated is influenced by the reliability of abstract-level predictions in familiar contexts. [ABSTRACT FROM AUTHOR]

The intention to forget can produce long-lasting effects. This ability has been linked to suppression of both rehearsal and retrieval of unwanted memories, processes mediated by the prefrontal cortex and hippocampus. Here, we describe an alternative account in which the intention to forget is associated with increased engagement with the unwanted information. We used pattern classifiers to decode human functional magnetic resonance imaging data from a task in which male and female participants viewed a series of pictures and were instructed to remember or forget each one. Pictures followed by a forget instruction elicited higher levels of processing in the ventral temporal cortex compared with those followed by a remember instruction. This boost in processing led to more forgetting, particularly for items that showed moderate (vs weak or strong) activation. This result is consistent with the nonmonotonic plasticity hypothesis, which predicts weakening and forgetting of memories that are moderately activated. [ABSTRACT FROM AUTHOR]

Abstract: What happens to goal‐relevant information in working memory after it is no longer needed? Here, we review evidence for a selective removal process that operates on outdated information to limit working memory load and hence facilitates the maintenance of goal‐relevant information. Removal alters the representations of irrelevant content so as to reduce access to it, thereby improving access to the remaining relevant content and also facilitating the encoding of new information. Both behavioral and neural evidence support the existence of a removal process that is separate from forgetting due to decay or interference. We discuss the potential mechanisms involved in removal and characterize the time course and duration of the process. In doing so, we propose the existence of two forms of removal: one is temporary, and reversible, which modifies working memory content without impacting content‐to‐context bindings, and another is permanent, which unbinds the content from its context in working memory (without necessarily impacting long‐term forgetting). Finally, we discuss limitations on removal and prescribe conditions for evaluating evidence for or against this process. [ABSTRACT FROM AUTHOR]

Abstract: How we attend to our thoughts affects how we attend to our environment. Holding information in working memory can automatically bias visual attention toward matching information. By observing attentional biases on reaction times to visual search during a memory delay, it is possible to reconstruct the source of that bias using machine learning techniques and thereby behaviorally decode the content of working memory. Can this be done when more than one item is held in working memory? There is some evidence that multiple items can simultaneously bias attention, but the effects have been inconsistent. One explanation may be that items are stored in different states depending on the current task demands. Recent models propose functionally distinct states of representation for items inside versus outside the focus of attention. Here, we use behavioral decoding to evaluate whether multiple memory items—including temporarily irrelevant items outside the focus of attention—exert biases on visual attention. Only the single item in the focus of attention was decodable. The other item showed a brief attentional bias that dissipated until it returned to the focus of attention. These results support the idea of dynamic, flexible states of working memory across time and priority. [ABSTRACT FROM AUTHOR]

Direct manipulation of brain activity can be used to investigate causal brain-behavior relationships. Current noninvasive neural stimulation techniques are too coarse to manipulate behaviors that correlate with fine-grained spatial patterns recorded by fMRI. However, these activity patterns can be manipulated by having people learn to self-regulate their own recorded neural activity. This technique, known as fMRI neurofeedback, faces challenges as many participants are unable to self-regulate. The causes of this non-responder effect are not well understood due to the cost and complexity of such investigation in the MRI scanner. Here, we investigated the temporal dynamics of the hemodynamic response measured by fMRI as a potential cause of the non-responder effect. Learning to self-regulate the hemodynamic response involves a difficult temporal credit-assignment problem because this signal is both delayed and blurred over time. Two factors critical to this problem are the prescribed self-regulation strategy (cognitive or automatic) and feedback timing (continuous or intermittent). Here, we sought to evaluate how these factors interact with the temporal dynamics of fMRI without using the MRI scanner. We first examined the role of cognitive strategies by having participants learn to regulate a simulated neurofeedback signal using a unidimensional strategy: pressing one of two buttons to rotate a visual grating that stimulates a model of visual cortex. Under these conditions, continuous feedback led to faster regulation compared to intermittent feedback. Yet, since many neurofeedback studies prescribe implicit self-regulation strategies, we created a computational model of automatic reward-based learning to examine whether this result held true for automatic processing. When feedback was delayed and blurred based on the hemodynamics of fMRI, this model learned more reliably from intermittent feedback compared to continuous feedback. These results suggest that different self-regulation mechanisms prefer different feedback timings, and that these factors can be effectively explored and optimized via simulation prior to deployment in the MRI scanner. [ABSTRACT FROM AUTHOR]

Emerging evidences have shown that one form of mental training--mindfulness meditation, can improve attention, emotion regulation and cognitive performance through changing brain activity and structural connectivity. However, whether and how the short-term mindfulness meditation alters large-scale brain networks are not well understood. Here, we applied a novel data-driven technique, the multivariate pattern analysis (MVPA) to resting-state fMRI (rsfMRI) data to identify changes in brain activity patterns and assess the neural mechanisms induced by a brief mindfulness training--integrative body-mind training (IBMT), which was previously reported in our series of randomized studies. Whole brain rsfMRI was performed on an undergraduate group who received 2 weeks of IBMT with 30 min per session (5 h training in total). Classifiers were trained on measures of functional connectivity in this fMRI data, and they were able to reliably differentiate (with 72% accuracy) patterns of connectivity from before vs. after the IBMT training. After training, an increase in positive functional connections (60 connections) were detected, primarily involving bilateral superior/middle occipital gyrus, bilateral frontale operculum, bilateral superior temporal gyrus, right superior temporal pole, bilateral insula, caudate and cerebellum. These results suggest that brief mental training alters the functional connectivity of large-scale brain networks at rest that may involve a portion of the neural circuitry supporting attention, cognitive and affective processing, awareness and sensory integration and reward processing. [ABSTRACT FROM AUTHOR]

In traditional fMRI, individuals respond to exogenous stimuli and are naïve to the effects of the stimuli on their neural activity patterns. Changes arising in the fMRI signal are analyzed post-hoc to elucidate the spatial and temporal activation of brain regions associated with the tasks performed. The advent of real-time fMRI has enabled a new method to systematically alter brain activity across space and time using neurofeedback training (NFT), providing a new tool to study internally-driven processes such as neuroplasticity. In this work, we combined n-back practice with fMRI-NFT of the left dorsolateral prefrontal cortex (DLPFC) to better understand the relationship between open- and closed-loop neuromodulation. FMRI data were acquired during both traditional n-back and NFT across five imaging sessions. Region-of-interest (ROI) and voxel-wise 2 ? 2 within subjects ANOVAs were carried out to determine the effects of, and interaction between, training session and neuromodulation type. A main effect of training session was identified for only a single, highly focused cluster that shared spatial properties with the fMRI-NFT target region (left DLPFC). This finding indicates that combined open- and closed-loop neuroplastic enhancement techniques result in focal changes that are confined to the target area of NFT, and do not affect up- or down-stream network components that are normally engaged during working memory. Additionally, we identified a main effect of neuromodulation type for 15 clusters with significantly different activation between open- and closed-loop neuromodulation during training, 12 of which demonstrated higher activity during the open-loop neuromodulation. Our results, taken together with previous reports, indicate that fMRI-NFT combined with n-back practice leads to a highly focal volume exhibiting neuroplasticity without additional network effects. [ABSTRACT FROM AUTHOR]

The capacity of long-term memory is thought to be virtually unlimited. However, our memory bank may need to be pruned regularly to ensure that the information most important for behavior can be stored and accessed efficiently. Using functional magnetic resonance imaging of the human brain, we report the discovery of a context-based mechanism for determining which memories to prune. Specifically, when a previously experienced context is reencountered, the brain automatically generates predictions about which items should appear in that context. If an item fails to appear when strongly expected, its representation in memory is weakened, and it is more likely to be forgotten. We find robust support for this mechanism using multivariate pattern classification and pattern similarity analyses. The results are explained by a model in which context-based predictions activate item representations just enough for them to be weakened during a misprediction. These findings reveal an ongoing and adaptive process for pruning unreliable memories. [ABSTRACT FROM AUTHOR]

Short-term memory (STM) refers to the capacity-limited retention of information over a brief period of time, and working memory (WM) refers to the manipulation and use of that information to guide behavior. In recent years it has become apparent that STM and WM interact and overlap with other cognitive processes, including attention (the selection of a subset of information for further processing) and long-term memory (LTM— the encoding and retention of an effectively unlimited amount of information for a much longer period of time). Broadly speaking, there have been two classes of memory models: systems models, which posit distinct stores for STM and LTM (Atkinson and Shiffrin, 1968; Baddeley and Hitch, 1974); and state-based models, which posit a common store with different activation states corresponding to STM and LTM (Cowan, 1995; McElree, 1996; Oberauer, 2002). In this paper, we will focus on state-based accounts of STM. First, we will consider several theoretical models that postulate, based on considerable behavioral evidence, that information in STM can exist in multiple representational states. We will then consider how neural data from recent studies of STM can inform and constrain these theoretical models. In the process we will highlight the inferential advantage of multivariate, information-based analyses of neuroimaging data (fMRI and electroencephalography (EEG)) over conventional activation-based analysis approaches (Postle, in press). We will conclude by addressing lingering questions regarding the fractionation of STM, highlighting differences between the attention to information vs. the retention of information during brief memory delays. [ABSTRACT FROM AUTHOR]

For decades it has been assumed that sustained, elevated neural activity--the so-called active trace--is the neural correlate of the short-term retention of information. However, a recent fMRI study has suggested that this activity may be more related to attention than to retention. Specifically, a multivariate pattern analysis failed to find evidence that information that was outside the focus of attention, but nonetheless in STM, was retained in an active state. Here, we replicate and extend this finding by querying the neural signatures of attended versus unattended information within STM with electroencephalograpy (EEG), a method sensitive to oscillatory neural activity to which the previous fMRI study was insensitive. We demonstrate that in the delay-period EEG activity, there is information only about memory items that are also in the focus of attention. Information about items outside the focus of attention is not detectable. This result converges with the fMRI findings to suggest that, contrary to conventional wisdom, an active memory trace may be unnecessary for the shortterm retention of information. [ABSTRACT FROM AUTHOR]

It is widely assumed that the short-term retention of information is accomplished via maintenance of an active neural trace. However, we demonstrate that memory can be preserved across a brief delay despite the apparent loss of sustained representations. Delay period activity may, in fact, reflect the focus of attention, rather than STM. We unconfounded attention and memory by causing external and internal shifts of attention away from items that were being actively retained. Multivariate pattern analysis of fMRI indicated that only items within the focus of attention elicited an active neural trace. Activity corresponding to representations of items outside the focus quickly dropped to baseline. Nevertheless, this information was remembered after a brief delay. Our data also show that refocusing attention toward a previously unattended memory item can reactivate its neural signature. The loss of sustained activity has long been thought to indicate a disruption of STM, but our results suggest that, even for small memory loads not exceeding the capacity limits of STM, the active maintenance of a stimulus representation may not be necessary for its short-term retention. [ABSTRACT FROM AUTHOR]

It is widely assumed that the short-term retention of information is accomplished via maintenance of an active neural trace. However, we demonstrate that memory can be preserved across a brief delay despite the apparent loss of sustained representations. Delay period activity may, in fact, reflect the focus of attention, rather than STM. We unconfounded attention and memory by causing external and internal shifts of attention away from items that were being actively retained. Multivariate pattern analysis of fMRI indicated that only items within the focus of attention elicited an active neural trace. Activity corresponding to representations of items outside the focus quickly dropped to baseline. Nevertheless, this information was remembered after a brief delay. Our data also show that refocusing attention toward a previously unattended memory item can reactivate its neural signature. The loss of sustained activity has long been thought to indicate a disruption of STM, but our results suggest that, even for small memory loads not exceeding the capacity limits of STM, the active maintenance of a stimulus representation may not be necessary for its short-term retention. [ABSTRACT FROM AUTHOR]

This study describes a functional magnetic resonance imaging study of humans engaged in long-term memory (LTM) and working memory tasks. A pattern classifier learned to identify patterns of brain activity associated with viewing and making judgments about three categories of pictures (famous people, famous locations, and common objects). The evaluation of these stimuli relied on perception and long-term semantic and/or episodic memories. We investigated whether this classifier could successfully decode brain activity from a subsequent delayed paired-associate recognition working memory task that required the short-term retention of the same stimuli. We reasoned that the LTM-trained classifier would be able to decode delay-period activity only if that activity reflected, to some extent, the temporary activation of LTM. Our results demonstrated successful decoding: delay-period activity from a distributed network of brain regions matched learned patterns of activity for task-relevant stimuli to a greater extent than for task-irrelevant stimuli. In varying degrees throughout the delay, activity reflected the target (a retrospective code) and its associate (a prospective code) with considerable variability among subjects. Although prefrontal cortex (PFC) demonstrated category-specific patterns of activity during the LTM task, these patterns were not reinstated in PFC during the working memory task. We conclude that the short-term retention of information can be supported by the temporary reactivation of LTM representations. [ABSTRACT FROM AUTHOR]