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.

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.

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.

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.

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.

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.

Theoretical distinction between functional states in working memory and their corresponding neural states

Working memory (WM) is important for guiding behaviour, but not always for the next possible action. Here we define a WM item that is currently relevant for guiding behaviour as the functionally "active" item; whereas items maintained in WM, but not immediately relevant to behaviour, are defined as functionally "latent". Traditional neurophysiological theories of WM proposed that content is maintained via persistent neural activity (e.g., stable attractors); however, more recent theories have highlighted the potential role for "activity-silent" mechanisms (e.g., short-term synaptic plasticity). Given these somewhat parallel dichotomies, functionally active and latent cognitive states of WM have been associated with storage based on persistent-activity and activity-silent neural mechanisms, respectively. However, in this article we caution against a one-to-one correspondence between functional and activity states. We argue that the principal theoretical requirement for active and latent WM is that the corresponding neural states play qualitatively different functional roles. We consider a number of candidate solutions, and conclude that the neurophysiological mechanisms for functionally active and latent WM items are theoretically independent of the distinction between persistent activity-based and activity-silent forms of WM storage.

Attentional Control in Subclinical Anxiety and Depression: Depression Symptoms Are Associated With Deficits in Target Facilitation, Not Distractor Inhibition

Mood and anxiety disorders are associated with deficits in attentional control involving emotive and non-emotive stimuli. Current theories focus on impaired attentional inhibition of distracting stimuli in producing these deficits. However, standard attention tasks struggle to separate distractor inhibition from target facilitation. Here, we investigate whether distractor inhibition underlies these deficits using neutral stimuli in a behavioral task specifically designed to tease apart these two attentional processes. Healthy participants performed a four-location Posner cueing paradigm and completed self-report questionnaires measuring depressive symptoms and trait anxiety. Using regression analyses, we found no relationship between distractor inhibition and mood symptoms or trait anxiety. However, we find a relationship between target facilitation and depression. Specifically, higher depressive symptoms were associated with reduced target facilitation in a task-version in which the target location repeated over a block of trials. We suggest this may relate to findings previously linking depression with deficits in predictive coding in clinical populations.

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.

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.

Premembering Experience: A Hierarchy of Time-Scales for Proactive Attention

Memories are about the past, but they serve the future. Memory research often emphasizes the former aspect: focusing on the functions that re-constitute (re-member) experience and elucidating the various types of memories and their interrelations, timescales, and neural bases. Here we highlight the prospective nature of memory in guiding selective attention, focusing on functions that use previous experience to anticipate the relevant events about to unfold-to "premember" experience. Memories of various types and timescales play a fundamental role in guiding perception and performance adaptively, proactively, and dynamically. Consonant with this perspective, memories are often recorded according to expected future demands. Using working memory as an example, we consider how mnemonic content is selected and represented for future use. This perspective moves away from the traditional representational account of memory toward a functional account in which forward-looking memory traces are informationally and computationally tuned for interacting with incoming sensory signals to guide adaptive behavior.

Concurrent visual and motor selection during visual working memory guided action

Visual working memory enables us to hold onto past sensations in anticipation that these may become relevant for guiding future actions. Yet laboratory tasks have treated visual working memories in isolation from their prospective actions and have focused on the mechanisms of memory retention rather than utilization. To understand how visual memories become used for action, we linked individual memory items to particular actions and independently tracked the neural dynamics of visual and motor selection when memories became used for action. This revealed concurrent visual-motor selection, engaging appropriate visual and motor brain areas at the same time. Thus we show that items in visual working memory can invoke multiple, item-specific, action plans that can be accessed together with the visual representations that guide them, affording fast and precise memory-guided behavior.

Decoding the influence of anticipatory states on visual perception in the presence of temporal distractors

Anticipatory states help prioritise relevant perceptual targets over competing distractor stimuli and amplify early brain responses to these targets. Here we combine electroencephalography recordings in humans with multivariate stimulus decoding to address whether anticipation also increases the amount of target identity information contained in these responses, and to ask how targets are prioritised over distractors when these compete in time. We show that anticipatory cues not only boost visual target representations, but also delay the interference on these target representations caused by temporally adjacent distractor stimuli—possibly marking a protective window reserved for high-fidelity target processing. Enhanced target decoding and distractor resistance are further predicted by the attenuation of posterior 8–14 Hz alpha oscillations. These findings thus reveal multiple mechanisms by which anticipatory states help prioritise targets from temporally competing distractors, and they highlight the potential of non-invasive multivariate electrophysiology to track cognitive influences on perception in temporally crowded contexts.

Anticipation helps to prioritise the processing of task-relevant sensory targets over irrelevant distractors. Here the authors analyse visual EEG responses and show that anticipation may do so by enhancing the neural representation of the target and by delaying the interference caused by distractors that follow closely in time.

Benefits of flexible prioritization in working memory can arise without costs

Most recent models conceptualize working memory (WM) as a continuous resource, divided up according to task demands. When an increasing number of items need to be remembered, each item receives a smaller chunk of the memory resource. These models predict that the allocation of attention to high-priority WM items during the retention interval should be a zero-sum game: improvements in remembering cued items come at the expense of uncued items because resources are dynamically transferred from uncued to cued representations. The current study provides empirical data challenging this model. Four precision retrocueing WM experiments assessed cued and uncued items on every trial. This permitted a test for trade-off of the memory resource. We found no evidence for trade-offs in memory across trials. Moreover, robust improvements in WM performance for cued items came at little or no cost to uncued items that were probed afterward, thereby increasing the net capacity of WM relative to neutral cueing conditions. An alternative mechanism of prioritization proposes that cued items are transferred into a privileged state within a response-gating bottleneck, in which an item uniquely controls upcoming behavior. We found evidence consistent with this alternative. When an uncued item was probed first, report of its orientation was biased away from the cued orientation to be subsequently reported. We interpret this bias as competition for behavioral control in the output-driving bottleneck. Other items in WM did not bias each other, making this result difficult to explain with a shared resource model.

This study challenges the dominant model for how we remember and prioritize pieces of information over short intervals (working memory). The dominant view is that all items in working memory share a single resource, and that we can prioritize one item by redistributing resources in its favor. This view predicts that nonprioritized memories become lost or impoverished. By testing how well participants remember both prioritized and nonprioritized items, we show that this is not the case. Our findings suggest that memories can be prioritized flexibly without necessarily jeopardizing others that may still become relevant.

Prioritizing Information during Working Memory: Beyond Sustained Internal Attention

Working memory (WM) has limited capacity. This leaves attention with the important role of allowing into storage only the most relevant information. It is increasingly evident that attention is equally crucial for prioritizing representations within WM as the importance of individual items changes. Retrospective prioritization has been proposed to result from a focus of internal attention highlighting one of several representations. Here, we suggest an updated model, in which prioritization acts in multiple steps: first orienting towards and selecting a memory, and then reconfiguring its representational state in the service of upcoming task demands. Reconfiguration sets up an optimized perception-action mapping, obviating the need for sustained attention. This view is consistent with recent literature, makes testable predictions, and links WM with task switching and action preparation.

Testing sensory evidence against mnemonic templates

Most perceptual decisions require comparisons between current input and an internal template. Classic studies propose that templates are encoded in sustained activity of sensory neurons. However, stimulus encoding is itself dynamic, tracing a complex trajectory through activity space. Which part of this trajectory is pre-activated to reflect the template? Here we recorded magneto- and electroencephalography during a visual target-detection task, and used pattern analyses to decode template, stimulus, and decision-variable representation. Our findings ran counter to the dominant model of sustained pre-activation. Instead, template information emerged transiently around stimulus onset and quickly subsided. Cross-generalization between stimulus and template coding, indicating a shared neural representation, occurred only briefly. Our results are compatible with the proposal that template representation relies on a matched filter, transforming input into task-appropriate output. This proposal was consistent with a signed difference response at the perceptual decision stage, which can be explained by a simple neural model.

DOI:http://dx.doi.org/10.7554/eLife.09000.001

Imagine searching for your house keys on a cluttered desk. Your eyes scan different items until they eventually find the keys you are looking for. How the brain represents an internal template of the target of your search (the keys, in this example) has been a much-debated topic in neuroscience for the past 30 years. Previous research has indicated that neurons specialized for detecting the sought-after object when it is in view are also pre-activated when we are seeking it. This would mean that these ‘template’ neurons are active the entire time that we are searching.

Myers et al. recorded brain activity from human volunteers using a non-invasive technique called magnetoencephalography (MEG) as they tried to detect when a particular shape appeared on a computer screen. The patterns of brain activity could be analyzed to identify the template that observers had in mind, and to trace when it became active. This revealed that the template was only activated around the time when a target was likely to appear, after which the activation pattern quickly subsided again.

Myers et al. also found that holding a template in mind largely activated different groups of neurons to those activated when seeing the same shape appear on a computer screen. This is contrary to the idea that the same cells are responsible both for maintaining a template and for perceiving its presence in our surroundings.

The brief activation of the template suggests that templates may come online mainly to filter new sensory evidence to detect targets. This mechanism could be advantageous because it lowers the amount of neural activity (and hence energy) needed for the task. Although this points to a more efficient way in which the brain searches for targets, these findings need to be replicated using other methods and task settings to confirm whether the brain generally uses templates in this way.

DOI:http://dx.doi.org/10.7554/eLife.09000.002

Decoding Rich Spatial Information with High Temporal Resolution

New research suggests that magnetoencephalography (MEG) contains rich spatial information for decoding neural states. Even small differences in the angle of neighbouring dipoles generate subtle, but statistically separable field patterns. This implies MEG (and electroencephalography: EEG) is ideal for decoding neural states with high-temporal resolution in the human brain.

Revealing hidden states in visual working memory using electroencephalography

It is often assumed that information in visual working memory (vWM) is maintained via persistent activity. However, recent evidence indicates that information in vWM could be maintained in an effectively "activity-silent" neural state. Silent vWM is consistent with recent cognitive and neural models, but poses an important experimental problem: how can we study these silent states using conventional measures of brain activity? We propose a novel approach that is analogous to echolocation: using a high-contrast visual stimulus, it may be possible to drive brain activity during vWM maintenance and measure the vWM-dependent impulse response. We recorded electroencephalography (EEG) while participants performed a vWM task in which a randomly oriented grating was remembered. Crucially, a high-contrast, task-irrelevant stimulus was shown in the maintenance period in half of the trials. The electrophysiological response from posterior channels was used to decode the orientations of the gratings. While orientations could be decoded during and shortly after stimulus presentation, decoding accuracy dropped back close to baseline in the delay. However, the visual evoked response from the task-irrelevant stimulus resulted in a clear re-emergence in decodability. This result provides important proof-of-concept for a promising and relatively simple approach to decode "activity-silent" vWM content using non-invasive EEG.

'Activity-silent' working memory in prefrontal cortex: a dynamic coding framework

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WM is thought to depend on persistent maintenance of stationary activity states.

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However, population-level analyses reveal that brain activity is highly dynamic.

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Accumulating evidence implicates activity-silent neural states for WM.

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Dynamic coding suggests that WM is encoded in patterns of functional connectivity.

Working memory (WM) provides the functional backbone to high-level cognition. Maintenance in WM is often assumed to depend on the stationary persistence of neural activity patterns that represent memory content. However, accumulating evidence suggests that persistent delay activity does not always accompany WM maintenance but instead seems to wax and wane as a function of the current task relevance of memoranda. Furthermore, new methods for measuring and analysing population-level patterns show that activity states are highly dynamic. At first glance, these dynamics seem at odds with the very nature of WM. How can we keep a stable thought in mind while brain activity is constantly changing? This review considers how neural dynamics might be functionally important for WM maintenance.

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.

Modulation of alpha power at encoding and retrieval tracks the precision of visual short-term memory

Our ability to hold information in mind is strictly limited. We sought to understand the relationship between oscillatory brain activity and the allocation of resources within visual short-term memory (VSTM). Participants attempted to remember target arrows embedded among distracters and used a continuous method of responding to report their memory for a cued target item. Trial-to-trial variability in the absolute circular accuracy with which participants could report the target was predicted by event-related alpha synchronization during initial processing of the memoranda and by alpha desynchronization during the retrieval of those items from VSTM. Using a model-based approach, we were also able to explore further which parameters of VSTM-guided behavior were most influenced by alpha band changes. Alpha synchronization during item processing enhanced the precision with which an item could be retained without affecting the likelihood of an item being represented per se (as indexed by the guessing rate). Importantly, our data outline a neural mechanism that mirrors the precision with which items are retained; the greater the alpha power enhancement during encoding, the greater the precision with which that item can be retained.

Preferential encoding of behaviorally relevant predictions revealed by EEG

Statistical regularities in the environment guide perceptual processing; however, some predictions are bound to be more important than others. In this electroencephalogram (EEG) study, we test how task relevance influences the way predictions are learned from the statistics of visual input, and exploited for behavior. We developed a novel task in which participants are simply instructed to respond to a designated target stimulus embedded in a serial stream of non-target stimuli. Presentation probabilities were manipulated such that a designated target cue stimulus predicted the target onset with 70% validity. We also included a corresponding control contingency: a pre-designated control cue predicted a specific non-target stimulus with 70% validity. Participants were not informed about these contingencies. This design allowed us to examine the neural response to task-relevant predictive (cue) and predicted stimuli (target), relative to task-irrelevant predictive (control cue) and predicted stimuli (control non-target). The behavioral results confirmed that participants learned and exploited task-relevant predictions even when not explicitly defined. The EEG results further showed that target-relevant predictions are coded more strongly than statistically equivalent regularities between non-target stimuli. There was a robust modulation of the response for predicted targets associated with learning, enhancing the response to cued stimuli just after 200 ms post-stimulus in central and posterior electrodes, but no corresponding effects for predicted non-target stimuli. These effects of target prediction were preceded by a sustained frontal negativity following presentation of the predictive cue stimulus. These results show that task relevance critically influences how the brain extracts predictive structure from the environment, and exploits these regularities for optimized behavior.

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.

Attention biases visual activity in visual short-term memory

In the current study, we tested whether representations in visual STM (VSTM) can be biased via top-down attentional modulation of visual activity in retinotopically specific locations. We manipulated attention using retrospective cues presented during the retention interval of a VSTM task. Retrospective cues triggered activity in a large-scale network implicated in attentional control and led to retinotopically specific modulation of activity in early visual areas V1-V4. Importantly, shifts of attention during VSTM maintenance were associated with changes in functional connectivity between pFC and retinotopic regions within V4. Our findings provide new insights into top-down control mechanisms that modulate VSTM representations for flexible and goal-directed maintenance of the most relevant memoranda.

Dynamic coding for cognitive control in prefrontal cortex

Cognitive flexibility is fundamental to adaptive intelligent behavior. Prefrontal cortex has long been associated with flexible cognitive function, but the neurophysiological principles that enable prefrontal cells to adapt their response properties according to context-dependent rules remain poorly understood. Here, we use time-resolved population-level neural pattern analyses to explore how context is encoded and maintained in primate prefrontal cortex and used in flexible decision making. We show that an instruction cue triggers a rapid series of state transitions before settling into a stable low-activity state. The postcue state is differentially tuned according to the current task-relevant rule. During decision making, the response to a choice stimulus is characterized by an initial stimulus-specific population response but evolves to different final decision-related states depending on the current rule. These results demonstrate how neural tuning profiles in prefrontal cortex adapt to accommodate changes in behavioral context. Highly flexible tuning could be mediated via short-term synaptic plasticity.

Attention restores discrete items to visual short-term memory

When a memory is forgotten, is it lost forever? Our study shows that selective attention can restore forgotten items to visual short-term memory (VSTM). In our two experiments, all stimuli presented in a memory array were designed to be equally task relevant during encoding. During the retention interval, however, participants were sometimes given a cue predicting which of the memory items would be probed at the end of the delay. This shift in task relevance improved recall for that item. We found that this type of cuing improved recall for items that otherwise would have been irretrievable, providing critical evidence that attention can restore forgotten information to VSTM. Psychophysical modeling of memory performance has confirmed that restoration of information in VSTM increases the probability that the cued item is available for recall but does not improve the representational quality of the memory. We further suggest that attention can restore discrete items to VSTM.

Biophysical determinants of transcranial magnetic stimulation: effects of excitability and depth of targeted area

Safe and effective transcranial magnetic stimulation (TMS) requires accurate intensity calibration. Output is typically calibrated to individual motor cortex excitability and applied to nonmotor brain areas, assuming that it captures a site nonspecific factor of excitability. We tested this assumption by correlating the effect of TMS at motor and visual cortex. In 30 participants, we measured motor threshold (MT) and phosphene threshold (PT) at the scalp surface and at coil-scalp distances of 3.17, 5.63, and 9.03 mm. We also modeled the effect of TMS in a simple head model to test the effect of distance. Four independent tests confirmed a significant correlation between PT and MT. We also found similar effects of distance in motor and visual areas, which did not correlate across participants. Computational modeling suggests that the relationship between the effect of distance and the induced electric field is effectively linear within the range of distances that have been explored empirically. We conclude that MT-guided calibration is valid for nonmotor brain areas if coil-cortex distance is taken into account. For standard figure-of-eight TMS coils connected to biphasic stimulators, the effect of cortical distance should be adjusted using a general correction factor of 2.7% stimulator output per millimeter.

Lacking control over the trade-off between quality and quantity in visual short-term memory

Visual short-term memory (VSTM) is limited in the quantity and quality of items that can be retained over time. Importantly, these two mnemonic parameters interact: increasing the number of items in VSTM reduces the quality with which they are represented. Here, we ask whether this trade-off is under top-down control. Specifically, we test whether participants can strategically optimise the trade-off between quality and quantity for VSTM according to task demands. We manipulated strategic trade-off by varying expectations about the number of to-be-remembered items (Experiments 1-2) or the precision required for the memory-based judgement (Experiment 3). In a final experiment, we manipulated both variables in a complementary way to maximise the motivation to strategically control the balance between number and the quality of items encoded into VSTM. In different blocks, performance would benefit most either by encoding a large number of items with low precision or by encoding a small number of items with high precision (Experiment 4). In all experiments, we compared VSTM performance on trials matched for mnemonic demand, but within contexts emphasising the quality or quantity of VSTM representations. Across all four experiments, we found no evidence to suggest that participants use this contextual information to bias the balance between the number and precision of items in VSTM. Rather, our data suggest that the trade-off may be determined primarily by stimulus-driven factors at encoding.

Inferring task-related networks using independent component analysis in magnetoencephalography

A novel framework for analysing task-positive data in magnetoencephalography (MEG) is presented that can identify task-related networks. Techniques that combine beamforming, the Hilbert transform and temporal independent component analysis (ICA) have recently been applied to resting-state MEG data and have been shown to extract resting-state networks similar to those found in fMRI. Here we extend this approach in two ways. First, we systematically investigate optimisation of time-frequency windows for connectivity measurement. This is achieved by estimating the distribution of functional connectivity scores between nodes of known resting-state networks and contrasting it with a distribution of artefactual scores that are entirely due to spatial leakage caused by the inverse problem. We find that functional connectivity, both in the resting-state and during a cognitive task, is best estimated via correlations in the oscillatory envelope in the 8–20 Hz frequency range, temporally down-sampled with windows of 1–4 s. Second, we combine ICA with the general linear model (GLM) to incorporate knowledge of task structure into our connectivity analysis. The combination of ICA with the GLM helps overcome problems of these techniques when used independently: namely, the interpretation and separation of interesting independent components from those that represent noise in ICA and the correction for multiple comparisons when applying the GLM. We demonstrate the approach on a 2-back working memory task and show that this novel analysis framework is able to elucidate the functional networks involved in the task beyond that which is achieved using the GLM alone. We find evidence of localised task-related activity in the area of the hippocampus, which is difficult to detect reliably using standard methods. Task-positive ICA, coupled with the GLM, has the potential to be a powerful tool in the analysis of MEG data.

Stimulating deep cortical structures with the batwing coil: how to determine the intensity for transcranial magnetic stimulation using coil-cortex distance

Transcranial magnetic stimulation (TMS) is increasingly used in cognitive neuroscience to probe non-motor cortical regions. A key question for such studies is the choice of stimulation intensity. Early studies used a simple metric such as 115% of motor threshold (MT) for non-motor regions; where MT is the stimulation intensity required to elicit a particular amplitude of motor evoked potential or visible muscle twitch when the coil is placed over primary motor cortex. Recently, however, it was demonstrated that this simple metric for stimulation of non-motor regions is inadequate - it could lead to over or under-stimulation depending on the distance between the coil and the cortex. Instead, a method was developed to scale the motor threshold based on coil-cortex distance, at least for standard figure-of-eight stimulating coils. Here we validate the same method for a 'batwing coil', which is designed to stimulate deeper cortical structures such as the medial frontal cortex. We modulated coil-cortex distance within-participant by inserting spacers of different thickness between coil and scalp. We then measured MT at each spacer. We show that for every millimeter between coil and scalp an additional 1.4% of TMS output is required to induce an equivalent level of brain stimulation at the motor cortex. Using this parameter we describe a linear function to adjust MT for future studies of non-motor regions-of-interest using the batwing coil. This is the first study to demonstrate the effects of coil-cortical distance on stimulation efficiency via a monophasic system using a batwing coil.

Reliability of the 'observation of movement' method for determining motor threshold using transcranial magnetic stimulation

The aim of this study was to establish the reliability of the observation of movement (OM) method for obtaining motor threshold (MT) in transcranial magnetic stimulation (TMS). MTs were obtained on separate days, following separate hunting procedures, for both left and right motor cortex (M1), with one or multiple estimates obtained from the same hemisphere within a single session. MTs obtained using the OM method were highly reliable and reproducible on different days (left M1: r=.98, p<.0001; right M1: r=.97, p<.0001). MTs were not influenced by the order of acquisition when two hemispheres were stimulated in the same session [F(1,22)=.12, p=.73] or by the collection of additional MTs as part of the distance-adjusted procedure [F(1,23)=.74, p=.40]. The results verify the reliability of the OM method and confirm its viability for the safe and efficient application of TMS to the left and right M1. The OM method is a reliable technique for obtaining MT and is relatively simple and quick to run. It therefore provides an effective procedure for research and clinical applications.

Attention modulates maintenance of representations in visual short-term memory

Recent studies have shown that selective attention is of considerable importance for encoding task-relevant items into visual short-term memory (VSTM) according to our behavioral goals. However, it is not known whether top-down attentional biases can continue to operate during the maintenance period of VSTM. We used ERPs to investigate this question across two experiments. Specifically, we tested whether orienting attention to a given spatial location within a VSTM representation resulted in modulation of the contralateral delay activity (CDA), a lateralized ERP marker of VSTM maintenance generated when participants selectively encode memory items from one hemifield. In both experiments, retrospective cues during the maintenance period could predict a specific item (spatial retrocue) or multiple items (neutral retrocue) that would be probed at the end of the memory delay. Our results revealed that VSTM performance is significantly improved by orienting attention to the location of a task-relevant item. The behavioral benefit was accompanied by modulation of neural activity involved in VSTM maintenance. Spatial retrocues reduced the magnitude of the CDA, consistent with a reduction in memory load. Our results provide direct evidence that top-down control modulates neural activity associated with maintenance in VSTM, biasing competition in favor of the task-relevant information.

Markers of preparatory attention predict visual short-term memory performance

Visual short-term memory (VSTM) is limited in capacity. Therefore, it is important to encode only visual information that is most likely to be relevant to behaviour. Here we asked which aspects of selective biasing of VSTM encoding predict subsequent memory-based performance. We measured EEG during a selective VSTM encoding task, in which we varied parametrically the memory load and the precision of recall required to compare a remembered item to a subsequent probe item. On half the trials, a spatial cue indicated that participants only needed to encode items from one hemifield. We observed a typical sequence of markers of anticipatory spatial attention: early attention directing negativity (EDAN), anterior attention directing negativity (ADAN), late directing attention positivity (LDAP); as well as of VSTM maintenance: contralateral delay activity (CDA). We found that individual differences in preparatory brain activity (EDAN/ADAN) predicted cue-related changes in recall accuracy, indexed by memory-probe discrimination sensitivity (d′). Importantly, our parametric manipulation of memory-probe similarity also allowed us to model the behavioural data for each participant, providing estimates for the quality of the memory representation and the probability that an item could be retrieved. We found that selective encoding primarily increased the probability of accurate memory recall; that ERP markers of preparatory attention predicted the cue-related changes in recall probability.

Distance-adjusted motor threshold for transcranial magnetic stimulation

OBJECTIVE

To examine the relationship between coil-cortex distance and effective cortical stimulation using transcranial magnetic stimulation (TMS) in the left and right motor cortex. We also compare the effect of coil-cortex distance using 50 and 70 mm figure-eight stimulating coils.

METHODS

Coil-cortex distance was manipulated within each participant using 5 and 10 mm acrylic separators placed between the coil and scalp surface. The effect of cortical stimulation was indexed by resting motor threshold (MT).

RESULTS

Increasing distance between the coil and underlying cortex was associated with a steep linear increase in MT. For each additional millimetre separating the stimulating coil from the scalp surface, an additional approximately 2.8% of absolute stimulator output (approximately 0.062 T) was required to reach MT. The gradient of the observed distance effect did not differ between hemispheres, and no differences were observed between the 50 and 70 mm TMS coils.

CONCLUSIONS

Coil-cortex distance directly influences the magnitude of cortical stimulation in TMS. The relationship between TMS efficacy and coil-cortex distance is well characterised by a linear function, providing a simple and effective method for scaling stimulator output to a distance adjusted MT.

SIGNIFICANCE

MT measured at the scalp-surface is dependent on the underlying scalp-cortex distance, and therefore does not provide an accurate index of cortical excitability. Distance-adjusted MT provides a more accurate index of cortical excitability, and improves the safety and efficacy of MT-calibrated TMS.

Executive "brake failure" following deactivation of human frontal lobe

In the course of daily living, humans frequently encounter situations in which a motor activity, once initiated, becomes unnecessary or inappropriate. Under such circumstances, the ability to inhibit motor responses can be of vital importance. Although the nature of response inhibition has been studied in psychology for several decades, its neural basis remains unclear. Using transcranial magnetic stimulation, we found that temporary deactivation of the pars opercularis in the right inferior frontal gyrus selectively impairs the ability to stop an initiated action. Critically, deactivation of the same region did not affect the ability to execute responses, nor did it influence physiological arousal. These findings confirm and extend recent reports that the inferior frontal gyrus is vital for mediating response inhibition.

Enhancement of visual selection during transient disruption of parietal cortex

Selective attention is critical for guiding human behavior. Recent theories have described the process of attention as a biased competition between sensory inputs, but questions remain concerning the anatomical basis of these competitive mechanisms. Using transcranial magnetic stimulation, we found that disruption of the right parietal cortex improved the perception of relevant stimuli in competitive visual displays. This enhancement of selective attention is consistent with previous observations and suggests a crucial role of the superior parietal lobule and supramarginal gyrus in mediating competition between visual inputs.

Executive “Brake Failure” following Deactivation of Human Frontal Lobe

In the course of daily living, humans frequently encounter situations in which a motor activity, once initiated, becomes unnecessary or inappropriate. Under such circumstances, the ability to inhibit motor responses can be of vital importance. Although the nature of response inhibition has been studied in psychology for several decades, its neural basis remains unclear. Using transcranial magnetic stimulation, we found that temporary deactivation of the pars opercularis in the right inferior frontal gyrus selectively impairs the ability to stop an initiated action. Critically, deactivation of the same region did not affect the ability to execute responses, nor did it influence physiological arousal. These findings confirm and extend recent reports that the inferior frontal gyrus is vital for mediating response inhibition.

Simple metric for scaling motor threshold based on scalp-cortex distance: application to studies using transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is a unique method in neuroscience used to stimulate focal regions of the human brain. As TMS gains popularity in experimental and clinical domains, techniques for controlling the extent of brain stimulation are becoming increasingly important. At present, TMS intensity is typically calibrated to the excitability of the human motor cortex, a measure referred to as motor threshold (MT). Although TMS is commonly applied to nonmotor regions, most applications do not consider the effect of changes in distance between the stimulating device and underlying neural tissue. Here we show that for every millimeter from the stimulating coil, an additional 3% of TMS output is required to induce an equivalent level of brain stimulation at the motor cortex. This abrupt spatial gradient will have crucial consequences when TMS is applied to nonmotor regions because of substantial variance in scalp-cortex distances over different regions of the head. Stimulation protocols that do not account for cortical distance therefore risk substantial under- or overstimulation. We describe a simple method for adjusting MT to account for variations in cortical distance, thus providing a more accurate calibration than unadjusted MT for the safe and effective application of TMS in clinical and experimental neuroscience.

Modality-Specific Control of Strategic Spatial Attention in Parietal Cortex

The neural basis of selective spatial attention presents a significant challenge to cognitive neuroscience. Recent neuroimaging studies have suggested that regions of the parietal and temporal cortex constitute a "supramodal" network that mediates goal-directed attention in multiple sensory modalities. Here we used transcranial magnetic stimulation (TMS) to determine which cortical subregions control strategic attention in vision and touch. Healthy observers undertook an orienting task in which a central arrow cue predicted the location of a subsequent visual or somatosensory target. To determine the attentional role of cortical subregions at different stages of processing, TMS was delivered to the right hemisphere during cue or target events. Results indicated a critical role of the inferior parietal cortex in strategic orienting to visual events, but not to somatosensory events. These findings are inconsistent with the existence of a supramodal attentional network and instead provide direct evidence for modality-specific attentional processing in parietal cortex.

Fast and slow parietal pathways mediate spatial attention

Mechanisms of selective attention are vital for guiding human behavior. The parietal cortex has long been recognized as a neural substrate of spatial attention, but the unique role of distinct parietal subregions has remained unclear. Using single-pulse transcranial magnetic stimulation, we found that the angular gyrus of the right parietal cortex mediates spatial orienting during two distinct time periods after the onset of a behaviorally relevant event. The biphasic involvement of the angular gyrus suggests that both fast and slow visual pathways are necessary for orienting spatial attention.