Optimal information loading into working memory explains dynamic coding in the prefrontal cortex.

Working memory involves the short-term maintenance of information and is critical in many tasks. The neural circuit dynamics underlying working memory remain poorly understood, with different aspects of prefrontal cortical (PFC) responses explained by different putative mechanisms. By mathematical analysis, numerical simulations, and using recordings from monkey PFC, we investigate a critical but hitherto ignored aspect of working memory dynamics: information loading. We find that, contrary to common assumptions, optimal loading of information into working memory involves inputs that are largely orthogonal, rather than similar, to the late delay activities observed during memory maintenance, naturally leading to the widely observed phenomenon of dynamic coding in PFC. Using a theoretically principled metric, we show that PFC exhibits the hallmarks of optimal information loading. We also find that optimal information loading emerges as a general dynamical strategy in task-optimized recurrent neural networks. Our theory unifies previous, seemingly conflicting theories of memory maintenance based on attractor or purely sequential dynamics and reveals a normative principle underlying dynamic coding.

Neural signature of flexible coding in prefrontal cortex.

The ability of prefrontal cortex to quickly encode novel associations is crucial for adaptive behavior and central to working memory. Fast Hebbian changes in synaptic strength permit forming new associations, but neuronal signatures of this have been elusive. We devised a trialwise index of pattern similarity to look for rapid changes in population codes. Based on a computational model of working memory, we hypothesized that synaptic strength-and consequently, the tuning of neurons-could change if features of a subsequent stimulus need to be "reassociated," i.e., if bindings between features need to be broken to encode the new item. As a result, identical stimuli might elicit different neural responses. As predicted, neural response similarity dropped following rebinding, but only in prefrontal cortex. The history-dependent changes were expressed on top of traditional, fixed selectivity and were not explainable by carryover of previous firing into the current trial or by neural adaptation.

Multiple and Dissociable Effects of Sensory History on Working-Memory Performance.

Behavioral reports of sensory information are biased by stimulus history. The nature and direction of such serial-dependence biases can differ between experimental settings; both attractive and repulsive biases toward previous stimuli have been observed. How and when these biases arise in the human brain remains largely unexplored. They could occur either via a change in sensory processing itself and/or during postperceptual processes such as maintenance or decision-making. To address this, we tested 20 participants (11 female) and analyzed behavioral and magnetoencephalographic (MEG) data from a working-memory task in which participants were sequentially presented with two randomly oriented gratings, one of which was cued for recall at the end of the trial. Behavioral responses showed evidence for two distinct biases: (1) a within-trial repulsive bias away from the previously encoded orientation on the same trial, and (2) a between-trial attractive bias toward the task-relevant orientation on the previous trial. Multivariate classification of stimulus orientation revealed that neural representations during stimulus encoding were biased away from the previous grating orientation, regardless of whether we considered the within-trial or between-trial prior orientation, despite opposite effects on behavior. These results suggest that repulsive biases occur at the level of sensory processing and can be overridden at postperceptual stages to result in attractive biases in behavior.SIGNIFICANCE STATEMENT Recent experience biases behavioral reports of sensory information, possibly capitalizing on the temporal regularity in our environment. It is still unclear at what stage of stimulus processing such serial biases arise. Here, we recorded behavior and neurophysiological [magnetoencephalographic (MEG)] data to test whether neural activity patterns during early sensory processing show the same biases seen in participants' reports. In a working-memory task that produced multiple biases in behavior, responses were biased toward previous targets, but away from more recent stimuli. Neural activity patterns were uniformly biased away from all previously relevant items. Our results contradict proposals that all serial biases arise at an early sensory processing stage. Instead, neural activity exhibited mostly adaptation-like responses to recent stimuli.

A recurrent neural network model of prefrontal brain activity during a working memory task.

When multiple items are held in short-term memory, cues that retrospectively prioritise one item over another (retro-cues) can facilitate subsequent recall. However, the neural and computational underpinnings of this effect are poorly understood. One recent study recorded neural signals in the macaque lateral prefrontal cortex (LPFC) during a retro-cueing task, contrasting delay-period activity before (pre-cue) and after (post-cue) retrocue onset. They reported that in the pre-cue delay, the individual stimuli were maintained in independent subspaces of neural population activity, whereas in the post-cue delay, the prioritised items were rotated into a common subspace, potentially allowing a common readout mechanism. To understand how such representational transitions can be learnt through error minimisation, we trained recurrent neural networks (RNNs) with supervision to perform an equivalent cued-recall task. RNNs were presented with two inputs denoting conjunctive colour-location stimuli, followed by a pre-cue memory delay, a location retrocue, and a post-cue delay. We found that the orthogonal-to-parallel geometry transformation observed in the macaque LPFC emerged naturally in RNNs trained to perform the task. Interestingly, the parallel geometry only developed when the cued information was required to be maintained in short-term memory for several cycles before readout, suggesting that it might confer robustness during maintenance. We extend these findings by analysing the learning dynamics and connectivity patterns of the RNNs, as well as the behaviour of models trained with probabilistic cues, allowing us to make predictions for future studies. Overall, our findings are consistent with recent theoretical accounts which propose that retrocues transform the prioritised memory items into a prospective, action-oriented format.

Integrating Reward Information for Prospective Behavior.

Value-based decision-making is often studied in a static context, where participants decide which option to select from those currently available. However, everyday life often involves an additional dimension: deciding when to select to maximize reward. Recent evidence suggests that agents track the latent reward of an option, updating changes in their latent reward estimate, to achieve appropriate selection timing (latent reward tracking). However, this strategy can be difficult to distinguish from one in which the optimal selection time is estimated in advance, allowing an agent to wait a predetermined amount of time before selecting, without needing to monitor an option's latent reward (distance-to-goal tracking). Here, we show that these strategies can in principle be dissociated. Human brain activity was recorded using electroencephalography (EEG), while female and male participants performed a novel decision task. Participants were shown an option and decided when to select it, as its latent reward changed from trial-to-trial. While the latent reward was uncued, it could be estimated using cued information about the option's starting value and value growth rate. We then used representational similarity analysis (RSA) to assess whether EEG signals more closely resembled latent reward tracking or distance-to-goal tracking. This approach successfully dissociated the strategies in this task. Starting value and growth rate were translated into a distance-to-goal signal, far in advance of selecting the option. Latent reward could not be independently decoded. These results demonstrate the feasibility of using high temporal resolution neural recordings to identify internally computed decision variables in the human brain.SIGNIFICANCE STATEMENT Reward-seeking behavior involves acting at the right time. However, the external world does not always tell us when an action is most rewarding, necessitating internal representations that guide action timing. Specifying this internal neural representation is challenging because it might stem from a variety of strategies, many of which make similar predictions about brain activity. This study used a novel approach to test whether alternative strategies could be dissociated in principle. Using representational similarity analysis (RSA), we were able to distinguish between candidate internal representations for selection timing. This shows how pattern analysis methods can be used to measure latent decision information in noninvasive neural data.

Drifting codes within a stable coding scheme for working memory.

Working memory (WM) is important to maintain information over short time periods to provide some stability in a constantly changing environment. However, brain activity is inherently dynamic, raising a challenge for maintaining stable mental states. To investigate the relationship between WM stability and neural dynamics, we used electroencephalography to measure the neural response to impulse stimuli during a WM delay. Multivariate pattern analysis revealed representations were both stable and dynamic: there was a clear difference in neural states between time-specific impulse responses, reflecting dynamic changes, yet the coding scheme for memorised orientations was stable. This suggests that a stable subcomponent in WM enables stable maintenance within a dynamic system. A stable coding scheme simplifies readout for WM-guided behaviour, whereas the low-dimensional dynamic component could provide additional temporal information. Despite having a stable subspace, WM is clearly not perfect-memory performance still degrades over time. Indeed, we find that even within the stable coding scheme, memories drift during maintenance. When averaged across trials, such drift contributes to the width of the error distribution.

A Hierarchy of Functional States in Working Memory.

Extensive research has examined how information is maintained in working memory (WM), but it remains unknown how WM is used to guide behavior. We addressed this question by combining human electrophysiology (50 subjects, male and female) with pattern analyses, cognitive modeling, and a task requiring the prolonged maintenance of two WM items and priority shifts between them. This enabled us to discern neural states coding for memories that were selected to guide the next decision from states coding for concurrently held memories that were maintained for later use, and to examine how these states contribute to WM-based decisions. Selected memories were encoded in a functionally active state. This state was reflected in spontaneous brain activity during the delay period, closely tracked moment-to-moment fluctuations in the quality of evidence integration, and also predicted when memories would interfere with each other. In contrast, concurrently held memories were encoded in a functionally latent state. This state was reflected only in stimulus-evoked brain activity, tracked memory precision at longer timescales, but did not engage with ongoing decision dynamics. Intriguingly, the two functional states were highly flexible, as priority could be dynamically shifted back and forth between memories without degrading their precision. These results delineate a hierarchy of functional states, whereby latent memories supporting general maintenance are transformed into active decision circuits to guide flexible behavior.SIGNIFICANCE STATEMENT Working memory enables maintenance of information that is no longer available in the environment. Abundant neuroscientific work has examined where in the brain working memories are stored, but it remains unknown how they are represented and used to guide behavior. Our study shows that working memories are represented in qualitatively different formats, depending on behavioral priorities. Memories that are selected for guiding behavior are encoded in an active state that transforms sensory input into decision variables, whereas other concurrently held memories are encoded in a latent state that supports precise maintenance without affecting ongoing cognition. These results dissociate mechanisms supporting memory storage and usage, and open the door to reveal not only where memories are stored but also how.

Neural Reinstatement Tracks Spread of Attention between Object Features in Working Memory.

Attention can be allocated in working memory (WM) to select and privilege relevant content. It is unclear whether attention selects individual features or whole objects in WM. Here, we used behavioral measures, eye-tracking, and EEG to test the hypothesis that attention spreads between an object's features in WM. Twenty-six participants completed a WM task that asked them to recall the angle of one of two oriented, colored bars after a delay while EEG and eye-tracking data were collected. During the delay, an orthogonal "incidental task" cued the color of one item for a match/mismatch judgment. On congruent trials (50%), the cued item was probed for subsequent orientation recall; on incongruent trials (50%), the other memory item was probed. As predicted, selecting the color of an object in WM brought other features of the cued object into an attended state as revealed by EEG decoding, oscillatory α-power, gaze bias, and improved orientation recall performance. Together, the results show that attentional selection spreads between an object's features in WM, consistent with object-based attentional selection. Analyses of neural processing at recall revealed that the selected object was automatically compared with the probe, whether it was the target for recall or not. This provides a potential mechanism for the observed benefits of nonpredictive cueing in WM, where a selected item is prioritized for subsequent decision-making.

Previously Reward-Associated Stimuli Capture Spatial Attention in the Absence of Changes in the Corresponding Sensory Representations as Measured with MEG.

Studies of selective attention typically consider the role of task goals or physical salience, but attention can also be captured by previously reward-associated stimuli, even if they are currently task irrelevant. One theory underlying this value-driven attentional capture (VDAC) is that reward-associated stimulus representations undergo plasticity in sensory cortex, thereby automatically capturing attention during early processing. To test this, we used magnetoencephalography to probe whether stimulus location and identity representations in sensory cortex are modulated by reward learning. We furthermore investigated the time course of these neural effects, and their relationship to behavioral VDAC. Male and female human participants first learned stimulus-reward associations. Next, we measured VDAC in a separate task by presenting these stimuli in the absence of reward contingency and probing their effects on the processing of separate target stimuli presented at different time lags. Using time-resolved multivariate pattern analysis, we found that learned value modulated the spatial selection of previously rewarded stimuli in posterior visual and parietal cortex from ∼260 ms after stimulus onset. This value modulation was related to the strength of participants' behavioral VDAC effect and persisted into subsequent target processing. Importantly, learned value did not influence cortical signatures of early processing (i.e., earlier than ∼200 ms); nor did it influence the decodability of stimulus identity. Our results suggest that VDAC is underpinned by learned value signals that modulate spatial selection throughout posterior visual and parietal cortex. We further suggest that VDAC can occur in the absence of changes in early visual processing in cortex.SIGNIFICANCE STATEMENT Attention is our ability to focus on relevant information at the expense of irrelevant information. It can be affected by previously learned but currently irrelevant stimulus-reward associations, a phenomenon termed "value-driven attentional capture" (VDAC). The neural mechanisms underlying VDAC remain unclear. It has been speculated that reward learning induces visual cortical plasticity, which modulates early visual processing to capture attention. Although we find that learned value modulates spatial signals in visual cortical areas, an effect that correlates with VDAC, we find no relevant signatures of changes in early visual processing in cortex.

One Thing Leads to Another: Anticipating Visual Object Identity Based on Associative-Memory Templates.

Probabilistic associations between stimuli afford memory templates that guide perception through proactive anticipatory mechanisms. A great deal of work has examined the behavioral consequences and human electrophysiological substrates of anticipation following probabilistic memory cues that carry spatial or temporal information to guide perception. However, less is understood about the electrophysiological substrates linked to anticipating the sensory content of events based on recurring associations between successive events. Here, we demonstrate behavioral and electrophysiological signatures of using associative-memory templates to guide perception, while equating spatial and temporal anticipation (experiments 1 and 2), as well as target probability and response demands (experiment 2). By recording the electroencephalogram in the two experiments (N = 55; 24 females), we show that two markers in human electrophysiology implicated in spatial and temporal anticipation also contribute to the anticipation of perceptual identity, as follows: attenuation of alpha-band oscillations and the contingent negative variation (CNV). Together, our results show that memory-guided identity templates proactively impact perception and are associated with anticipatory states of attenuated alpha oscillations and the CNV. Furthermore, by isolating object-identity anticipation from spatial and temporal anticipation, our results suggest a role for alpha attenuation and the CNV in specific visual content anticipation beyond general changes in neural excitability or readiness.SIGNIFICANCE STATEMENT Probabilistic associations between stimuli afford memory templates that guide perception through proactive anticipatory mechanisms. The current work isolates the behavioral benefits and electrophysiological signatures of memory-guided identity-based anticipation, while equating anticipation of space, time, motor responses, and task relevance. Our results show that anticipation of the specific identity of a forthcoming percept impacts performance and is associated with states of attenuated alpha oscillations and the contingent negative variation, extending previous work implicating these neural substrates in spatial and temporal preparatory attention. Together, this work bridges fields of attention, memory, and perception, providing new insights into the neural mechanisms that support complex attentional templates.

Unimodal and Bimodal Access to Sensory Working Memories by Auditory and Visual Impulses.

It is unclear to what extent sensory processing areas are involved in the maintenance of sensory information in working memory (WM). Previous studies have thus far relied on finding neural activity in the corresponding sensory cortices, neglecting potential activity-silent mechanisms, such as connectivity-dependent encoding. It has recently been found that visual stimulation during visual WM maintenance reveals WM-dependent changes through a bottom-up neural response. Here, we test whether this impulse response is uniquely visual and sensory-specific. Human participants (both sexes) completed visual and auditory WM tasks while electroencephalography was recorded. During the maintenance period, the WM network was perturbed serially with fixed and task-neutral auditory and visual stimuli. We show that a neutral auditory impulse-stimulus presented during the maintenance of a pure tone resulted in a WM-dependent neural response, providing evidence for the auditory counterpart to the visual WM findings reported previously. Interestingly, visual stimulation also resulted in an auditory WM-dependent impulse response, implicating the visual cortex in the maintenance of auditory information, either directly or indirectly, as a pathway to the neural auditory WM representations elsewhere. In contrast, during visual WM maintenance, only the impulse response to visual stimulation was content-specific, suggesting that visual information is maintained in a sensory-specific neural network, separated from auditory processing areas.SIGNIFICANCE STATEMENT Working memory is a crucial component of intelligent, adaptive behavior. Our understanding of the neural mechanisms that support it has recently shifted: rather than being dependent on an unbroken chain of neural activity, working memory may rely on transient changes in neuronal connectivity, which can be maintained efficiently in activity-silent brain states. Previous work using a visual impulse stimulus to perturb the memory network has implicated such silent states in the retention of line orientations in visual working memory. Here, we show that auditory working memory similarly retains auditory information. We also observed a sensory-specific impulse response in visual working memory, while auditory memory responded bimodally to both visual and auditory impulses, possibly reflecting visual dominance of working memory.

Decoding visual colour from scalp electroencephalography measurements.

Recent advances have made it possible to decode various aspects of visually presented stimuli from patterns of scalp EEG measurements. As of recently, such multivariate methods have been commonly used to decode visual-spatial features such as location, orientation, or spatial frequency. In the current study, we show that it is also possible to track visual colour processing by using Linear Discriminant Analysis on patterns of EEG activity. Building on other recent demonstrations, we show that colour decoding: (1) reflects sensory qualities (as opposed to, for example, verbal labelling) with a prominent contribution from posterior electrodes contralateral to the stimulus, (2) conforms to a parametric coding space, (3) is possible in multi-item displays, and (4) is comparable in magnitude to the decoding of visual stimulus orientation. Through subsampling our data, we also provide an estimate of the approximate number of trials and participants required for robust decoding. Finally, we show that while colour decoding can be sensitive to subtle differences in luminance, our colour decoding results are primarily driven by measured colour differences between stimuli. Colour decoding opens a relevant new dimension in which to track visual processing using scalp EEG measurements, while bypassing potential confounds associated with decoding approaches that focus on spatial features.

Reward Boosts Neural Coding of Task Rules to Optimize Cognitive Flexibility.

Cognitive flexibility is critical for intelligent behavior. However, its execution is effortful and often suboptimal. Recent work indicates that flexible behavior can be improved by the prospect of reward, which suggests that rewards optimize flexible control processes. Here we investigated how different reward prospects influence neural encoding of task rule information to optimize cognitive flexibility. We applied representational similarity analysis to human electroencephalograms, recorded while female and male participants performed a rule-guided decision-making task. During the task, the prospect of reward varied from trial to trial. Participants made faster, more accurate judgements on high-reward trials. Critically, high reward boosted neural coding of the active task rule, and the extent of this increase was associated with improvements in task performance. Additionally, the effect of high reward on task rule coding was most pronounced on switch trials, where rules were updated relative to the previous trial. These results suggest that reward prospect can promote cognitive performance by strengthening neural coding of task rule information, helping to improve cognitive flexibility during complex behavior.SIGNIFICANCE STATEMENT The importance of motivation is evident in the ubiquity with which reward prospect guides adaptive behavior and the striking number of neurological conditions associated with motivational impairments. In this study, we investigated how dynamic changes in motivation, as manipulated through reward, shape neural coding for task rules during a flexible decision-making task. The results of this work suggest that motivation to obtain reward modulates the encoding of task rules needed for flexible behavior. The extent to which reward increased task rule coding also tracked improvements in behavioral performance under high-reward conditions. These findings help to inform how motivation shapes neural processing in the healthy human brain.

Comparing the prioritization of items and feature-dimensions in visual working memory.

Selective attention can be directed not only to external sensory inputs, but also to internal sensory representations held within visual working memory (VWM). To date, this phenomenon has been studied predominantly following retrospective cues directing attention to particular items, or their locations in memory. In addition to item-level attentional prioritization, recent studies have shown that selectively attending to feature dimensions in VWM can also improve memory recall performance. However, no study to date has directly compared item-based and dimension-based attention in VWM, nor their neural bases. Here, we compared the benefits of retrospective cues (retro-cues) that were directed either at a multifeature item or at a feature dimension that was shared between two spatially segregated items. Behavioral results revealed qualitatively similar attentional benefits in both recall accuracy and response time, but also showed that cueing benefits were larger after item cues. Concurrent electroencephalogram measurements further revealed a similar attenuation of posterior alpha oscillations following both item and dimension retro-cues when compared with noninformative, neutral retro-cues. We argue that attention can act flexibly to prioritize the most relevant information-at either the item or the dimension level-to optimize ensuing memory-based task performance, and we discuss the implications of the observed commonalities and differences between item-level and dimension-level prioritization in VWM.

Stable and Dynamic Coding for Working Memory in Primate Prefrontal Cortex.

Working memory (WM) provides the stability necessary for high-level cognition. Influential theories typically assume that WM depends on the persistence of stable neural representations, yet increasing evidence suggests that neural states are highly dynamic. Here we apply multivariate pattern analysis to explore the population dynamics in primate lateral prefrontal cortex (PFC) during three variants of the classic memory-guided saccade task (recorded in four animals). We observed the hallmark of dynamic population coding across key phases of a working memory task: sensory processing, memory encoding, and response execution. Throughout both these dynamic epochs and the memory delay period, however, the neural representational geometry remained stable. We identified two characteristics that jointly explain these dynamics: (1) time-varying changes in the subpopulation of neurons coding for task variables (i.e., dynamic subpopulations); and (2) time-varying selectivity within neurons (i.e., dynamic selectivity). These results indicate that even in a very simple memory-guided saccade task, PFC neurons display complex dynamics to support stable representations for WM.SIGNIFICANCE STATEMENT Flexible, intelligent behavior requires the maintenance and manipulation of incoming information over various time spans. For short time spans, this faculty is labeled "working memory" (WM). Dominant models propose that WM is maintained by stable, persistent patterns of neural activity in prefrontal cortex (PFC). However, recent evidence suggests that neural activity in PFC is dynamic, even while the contents of WM remain stably represented. Here, we explored the neural dynamics in PFC during a memory-guided saccade task. We found evidence for dynamic population coding in various task epochs, despite striking stability in the neural representational geometry of WM. Furthermore, we identified two distinct cellular mechanisms that contribute to dynamic population coding.

Distinct Mechanisms for Distractor Suppression and Target Facilitation.

It is well established that preparatory attention improves processing of task-relevant stimuli. Although it is often more important to ignore task-irrelevant stimuli, comparatively little is known about preparatory attentional mechanisms for inhibiting expected distractions. Here, we establish that distractor inhibition is not under the same top-down control as target facilitation. Using a variant of the Posner paradigm, participants were cued to either the location of a target stimulus, the location of a distractor, or were provided no predictive information. In Experiment 1, we found that participants were able to use target-relevant cues to facilitate target processing in both blocked and flexible conditions, but distractor cueing was only effective in the blocked version of the task. In Experiment 2, we replicate these findings in a larger sample and leveraged the additional statistical power to perform individual differences analyses to tease apart potential underlying mechanisms. We found no evidence for a correlation between these two types of benefit, suggesting that flexible target cueing and distractor suppression depend on distinct cognitive mechanisms. In Experiment 3, we use EEG to show that preparatory distractor suppression is associated with a diminished P1, but we found no evidence to suggest that this effect was mediated by top-down control of oscillatory activity in the alpha band (8-12 Hz). We conclude that flexible top-down mechanisms of cognitive control are specialized for target-related attention, whereas distractor suppression only emerges when the predictive information can be derived directly from experience. This is consistent with a predictive coding model of expectation suppression. SIGNIFICANCE STATEMENT: If you were told to ignore a white bear, you might find it quite difficult. Holding something in working memory is thought to automatically facilitate feature processing, even if doing so is detrimental to the current task. Despite this paradox, it is often assumed that distractor suppression is controlled via similar top-down mechanisms of attention that prepare brain areas for target enhancement. In particular, low-frequency oscillations in visual cortex appear especially well suited for gating task-irrelevant information. We describe the results of a series of studies exploring distractor suppression and challenge this popular notion. We draw on behavioral and EEG evidence to show that selective distractor suppression operates via an alternative mechanism, such as expectation suppression within a predictive coding framework.

Resting GABA and glutamate concentrations do not predict visual gamma frequency or amplitude.

Gamma band oscillations arise in neuronal networks of interconnected GABAergic interneurons and excitatory pyramidal cells. A previous study found a correlation between visual gamma peak frequency, as measured with magnetoencephalography, and resting GABA levels, as measured with magnetic resonance spectroscopy (MRS), in 12 healthy volunteers. If true, this would allow studies in clinical populations testing modulation of this relationship, but this finding has not been replicated. We addressed this important question by measuring gamma oscillations and GABA, as well as glutamate, in 50 healthy volunteers. Visual gamma activity was evoked using an established gratings paradigm, and we applied a beamformer spatial filtering technique to extract source-reconstructed gamma peak frequency and amplitude from the occipital lobe. We determined gamma peak frequency and amplitude from the location with maximal activation and from the location of the MRS voxel to assess the relationship of GABA with gamma. Gamma peak frequency was estimated from the highest value of the raw spectra and by a Gaussian fit to the spectra. MRS data were acquired from occipital cortex. We did not replicate the previously found correlation between gamma peak frequency and GABA concentration. Calculation of a Bayes factor provided strong evidence in favor of the null hypothesis. We also did not find a correlation between gamma activity and glutamate or between gamma and the ratio of GABA/glutamate. Our results suggest that cortical gamma oscillations do not have a consistent, demonstrable relationship to excitatory/inhibitory network activity as proxied by MRS measurements of GABA and glutamate.

Oscillatory brain state predicts variability in working memory.

Our capacity to remember and manipulate objects in working memory (WM) is severely limited. However, this capacity limitation is unlikely to be fixed because behavioral models indicate variability from trial to trial. We investigated whether fluctuations in neural excitability at stimulus encoding, as indexed by low-frequency oscillations (in the alpha band, 8-14 Hz), contribute to this variability. Specifically, we hypothesized that the spontaneous state of alpha band activity would correlate with trial-by-trial fluctuations in visual WM. Electroencephalography recorded from human observers during a visual WM task revealed that the prestimulus desynchronization of alpha oscillations predicts the accuracy of memory recall on a trial-by-trial basis. A model-based analysis indicated that this effect arises from a modulation in the precision of memorized items, but not the likelihood of remembering them (the recall rate). The phase of posterior alpha oscillations preceding the memorized item also predicted memory accuracy. Based on correlations between prestimulus alpha levels and stimulus-related visual evoked responses, we speculate that the prestimulus state of the visual system prefigures a cascade of state-dependent processes, ultimately affecting WM-guided behavior. Overall, our results indicate that spontaneous changes in cortical excitability can have profound consequences for higher visual cognition.

Aberrant functional connectivity in dissociable hippocampal networks is associated with deficits in memory.

In the healthy human brain, evidence for dissociable memory networks along the anterior-posterior axis of the hippocampus suggests that this structure may not function as a unitary entity. Failure to consider these functional divisions may explain diverging results among studies of memory adaptation in disease. Using task-based and resting functional MRI, we show that chronic seizures disrupting the anterior medial temporal lobe (MTL) preserve anterior and posterior hippocampal-cortical dissociations, but alter signaling between these and other key brain regions. During performance of a memory encoding task, we found reduced neural activity in human patients with unilateral temporal lobe epilepsy relative to age-matched healthy controls, but no upregulation of fMRI signal in unaffected hippocampal subregions. Instead, patients showed aberrant resting fMRI connectivity within anterior and posterior hippocampal-cortical networks, which was associated with memory decline, distinguishing memory-intact from memory-impaired patients. Our results highlight a critical role for intact hippocampo-cortical functional communication in memory and provide evidence that chronic injury-induced functional reorganization in the diseased MTL is behavioral inefficient.

Temporal dynamics of attention during encoding versus maintenance of working memory: complementary views from event-related potentials and alpha-band oscillations.

Working memory (WM) is strongly influenced by attention. In visual WM tasks, recall performance can be improved by an attention-guiding cue presented before encoding (precue) or during maintenance (retrocue). Although precues and retrocues recruit a similar frontoparietal control network, the two are likely to exhibit some processing differences, because precues invite anticipation of upcoming information whereas retrocues may guide prioritization, protection, and selection of information already in mind. Here we explored the behavioral and electrophysiological differences between precueing and retrocueing in a new visual WM task designed to permit a direct comparison between cueing conditions. We found marked differences in ERP profiles between the precue and retrocue conditions. In line with precues primarily generating an anticipatory shift of attention toward the location of an upcoming item, we found a robust lateralization in late cue-evoked potentials associated with target anticipation. Retrocues elicited a different pattern of ERPs that was compatible with an early selection mechanism, but not with stimulus anticipation. In contrast to the distinct ERP patterns, alpha-band (8-14 Hz) lateralization was indistinguishable between cue types (reflecting, in both conditions, the location of the cued item). We speculate that, whereas alpha-band lateralization after a precue is likely to enable anticipatory attention, lateralization after a retrocue may instead enable the controlled spatiotopic access to recently encoded visual information.