Stochastic sampling provides a unifying account of visual working memory limits.

Research into human working memory limits has been shaped by the competition between different formal models, with a central point of contention being whether internal representations are continuous or discrete. Here we describe a sampling approach derived from principles of neural coding as a framework to understand working memory limits. Reconceptualizing existing models in these terms reveals strong commonalities between seemingly opposing accounts, but also allows us to identify specific points of difference. We show that the discrete versus continuous nature of sampling is not critical to model fits, but that, instead, random variability in sample counts is the key to reproducing human performance in both single- and whole-report tasks. A probabilistic limit on the number of items successfully retrieved is an emergent property of stochastic sampling, requiring no explicit mechanism to enforce it. These findings resolve discrepancies between previous accounts and establish a unified computational framework for working memory that is compatible with neural principles.

Swap errors in visual working memory are fully explained by cue-feature variability.

In cue-based recall from working memory, incorrectly reporting features of an uncued item may be referred to as a "swap" error. One account of these errors ascribes them to variability in memory for the cue features leading to erroneous selection of a non-target item, especially if it is similar to the target in the cue-feature dimension. However, alternative accounts of swap errors include cue-independent misbinding, and strategic guessing when the cued item is not in memory. Here we investigated the cause of swap errors by manipulating the variability with which either cue or report features (orientations in Exp 1; motion directions in Exp 2) were encoded. We found that swap errors increased with increasing variability in memory for the cue features, and their changing frequency could be quantitatively predicted based on recall variability when the same feature was used for report. These results are inconsistent with the hypothesis that swaps are a strategic response to forgotten items, and suggest that swap errors could be wholly accounted for by confusions due to cue-dimension variability. In a third experiment we examined whether spatial configuration of memory arrays in tasks with spatial cueing has an influence on swap error frequency. We observed a specific tendency to make swap errors to non-targets located precisely opposite to the cued location, suggesting that stimulus positions are partially encoded in a non-metric format.

Consequence of stroke for feature recall and binding in visual working memory.

Visual memory for objects involves the integration, or binding, of individual features into a coherent representation. We used a novel approach to assess feature binding, using a delayed-reproduction task in combination with computational modeling and lesion analysis. We assessed stroke patients and neurotypical controls on a visual working memory task in which spatial arrays of colored disks were presented. After a brief delay, participants either had to report the color of one disk cued by its location or the location of one disk cued by its color. Our results demonstrate that, in the controls, report imprecision and swap errors (non-target reports) can be explained by a single source of variability. Stroke patients showed an overall decrease in memory precision for both color and location, with only limited evidence for deviations from the predicted relationship between report precision and swap errors. These deviations were primarily deficits in reporting items rather than selecting items based on the cue. Atlas-based lesion-symptom mapping showed that selection and reporting deficits, precision in reporting color, and precision in reporting location were associated with different lesion profiles. Deficits in binding are associated with lesions in the left somatosensory cortex, deficits in the precision of reporting color with bilateral fronto-parietal regions, and no anatomical substrates were identified for precision in reporting location. Our results converge with previous reports that working memory representations are widely distributed in the brain and can be found across sensory, parietal, temporal, and prefrontal cortices. Stroke patients demonstrate mostly subtle impairments in visual working memory, perhaps because representations from different areas in the brain can partly compensate for impaired encoding in lesioned areas. These findings contribute to understanding of the relation between memorizing features and their bound representations.

Mechanisms of feature binding in visual working memory are stable over long delays.

The ability to accurately retain the binding between the features of different objects is a critical element of visual working memory. The underlying mechanism can be elucidated by analyzing correlations of response errors in dual-report experiments, in which participants have to report two features of a single item from a previously viewed stimulus array. Results from separate previous studies using different cueing conditions have indicated that location takes a privileged role in mediating binding between other features, in that largely independent response errors have been observed when location was used as a cue, but errors were highly correlated when location was one of the reported features. Earlier results from change detection tasks likewise support such a special role of location, but they also suggest that this role is substantially reduced for longer retention intervals in favor of object-based representation. In the present study, we replicated the findings of previous dual-report tasks with different cueing conditions, using matched stimuli and procedures. Moreover, we show that the observed patterns of error correlations remain qualitatively unchanged with longer retention intervals. Fits with neural population models demonstrate that the behavioral results at long, as well as short, delays are best explained by memory representations in independent feature maps, in which an item's features are bound to each other only via their shared location.

Transsaccadic integration relies on a limited memory resource.

Saccadic eye movements cause large-scale transformations of the image falling on the retina. Rather than starting visual processing anew after each saccade, the visual system combines post-saccadic information with visual input from before the saccade. Crucially, the relative contribution of each source of information is weighted according to its precision, consistent with principles of optimal integration. We reasoned that, if pre-saccadic input is maintained in a resource-limited store, such as visual working memory, its precision will depend on the number of items stored, as well as their attentional priority. Observers estimated the color of stimuli that changed imperceptibly during a saccade, and we examined where reports fell on the continuum between pre- and post-saccadic values. Bias toward the post-saccadic color increased with the set size of the pre-saccadic display, consistent with an increased weighting of the post-saccadic input as precision of the pre-saccadic representation declined. In a second experiment, we investigated if transsaccadic memory resources are preferentially allocated to attentionally prioritized items. An arrow cue indicated one pre-saccadic item as more likely to be chosen for report. As predicted, valid cues increased response precision and biased responses toward the pre-saccadic color. We conclude that transsaccadic integration relies on a limited memory resource that is flexibly distributed between pre-saccadic stimuli.

Drift in Neural Population Activity Causes Working Memory to Deteriorate Over Time.

Short-term memories are thought to be maintained in the form of sustained spiking activity in neural populations. Decreases in recall precision observed with increasing number of memorized items can be accounted for by a limit on total spiking activity, resulting in fewer spikes contributing to the representation of each individual item. Longer retention intervals likewise reduce recall precision, but it is unknown what changes in population activity produce this effect. One possibility is that spiking activity becomes attenuated over time, such that the same mechanism accounts for both effects of set size and retention duration. Alternatively, reduced performance may be caused by drift in the encoded value over time, without a decrease in overall spiking activity. Human participants of either sex performed a variable-delay cued recall task with a saccadic response, providing a precise measure of recall latency. Based on a spike integration model of decision making, if the effects of set size and retention duration are both caused by decreased spiking activity, we would predict a fixed relationship between recall precision and response latency across conditions. In contrast, the drift hypothesis predicts no systematic changes in latency with increasing delays. Our results show both an increase in latency with set size, and a decrease in response precision with longer delays within each set size, but no systematic increase in latency for increasing delay durations. These results were quantitatively reproduced by a model based on a limited neural resource in which working memories drift rather than decay with time.SIGNIFICANCE STATEMENT Rapid deterioration over seconds is a defining feature of short-term memory, but what mechanism drives this degradation of internal representations? Here, we extend a successful population coding model of working memory by introducing possible mechanisms of delay effects. We show that a decay in neural signal over time predicts that the time required for memory retrieval will increase with delay, whereas a random drift in the stored value predicts no effect of delay on retrieval time. Testing these predictions in a multi-item memory task with an eye movement response, we identified drift as a key mechanism of memory decline. These results provide evidence for a dynamic spiking basis for working memory, in contrast to recent proposals of activity-silent storage.

Neural Architecture for Feature Binding in Visual Working Memory.

Binding refers to the operation that groups different features together into objects. We propose a neural architecture for feature binding in visual working memory that employs populations of neurons with conjunction responses. We tested this model using cued recall tasks, in which subjects had to memorize object arrays composed of simple visual features (color, orientation, and location). After a brief delay, one feature of one item was given as a cue, and the observer had to report, on a continuous scale, one or two other features of the cued item. Binding failure in this task is associated with swap errors, in which observers report an item other than the one indicated by the cue. We observed that the probability of swapping two items strongly correlated with the items' similarity in the cue feature dimension, and found a strong correlation between swap errors occurring in spatial and nonspatial report. The neural model explains both swap errors and response variability as results of decoding noisy neural activity, and can account for the behavioral results in quantitative detail. We then used the model to compare alternative mechanisms for binding nonspatial features. We found the behavioral results fully consistent with a model in which nonspatial features are bound exclusively via their shared location, with no indication of direct binding between color and orientation. These results provide evidence for a special role of location in feature binding, and the model explains how this special role could be realized in the neural system.SIGNIFICANCE STATEMENT The problem of feature binding is of central importance in understanding the mechanisms of working memory. How do we remember not only that we saw a red and a round object, but that these features belong together to a single object rather than to different objects in our environment? Here we present evidence for a neural mechanism for feature binding in working memory, based on encoding of visual information by neurons that respond to the conjunction of features. We find clear evidence that nonspatial features are bound via space: we memorize directly where a color or an orientation appeared, but we memorize which color belonged with which orientation only indirectly by virtue of their shared location.

Restoration of fMRI Decodability Does Not Imply Latent Working Memory States.

Recent imaging studies have challenged the prevailing view that working memory is mediated by sustained neural activity. Using machine learning methods to reconstruct memory content, these studies found that previously diminished representations can be restored by retrospective cueing or other forms of stimulation. These findings have been interpreted as evidence for an activity-silent working memory state that can be reactivated dependent on task demands. Here, we test the validity of this conclusion by formulating a neural process model of working memory based on sustained activity and using this model to emulate a spatial recall task with retro-cueing. The simulation reproduces both behavioral and fMRI results previously taken as evidence for latent states, in particular the restoration of spatial reconstruction quality following an informative cue. Our results demonstrate that recovery of the decodability of an imaging signal does not provide compelling evidence for an activity-silent working memory state.

Dynamic interactions between visual working memory and saccade target selection.

Recent psychophysical experiments have shown that working memory for visual surface features interacts with saccadic motor planning, even in tasks where the saccade target is unambiguously specified by spatial cues. Specifically, a match between a memorized color and the color of either the designated target or a distractor stimulus influences saccade target selection, saccade amplitudes, and latencies in a systematic fashion. To elucidate these effects, we present a dynamic neural field model in combination with new experimental data. The model captures the neural processes underlying visual perception, working memory, and saccade planning relevant to the psychophysical experiment. It consists of a low-level visual sensory representation that interacts with two separate pathways: a spatial pathway implementing spatial attention and saccade generation, and a surface feature pathway implementing color working memory and feature attention. Due to bidirectional coupling between visual working memory and feature attention in the model, the working memory content can indirectly exert an effect on perceptual processing in the low-level sensory representation. This in turn biases saccadic movement planning in the spatial pathway, allowing the model to quantitatively reproduce the observed interaction effects. The continuous coupling between representations in the model also implies that modulation should be bidirectional, and model simulations provide specific predictions for complementary effects of saccade target selection on visual working memory. These predictions were empirically confirmed in a new experiment: Memory for a sample color was biased toward the color of a task-irrelevant saccade target object, demonstrating the bidirectional coupling between visual working memory and perceptual processing.

Representation and computation in visual working memory.

The ability to sustain internal representations of the sensory environment beyond immediate perception is a fundamental requirement of cognitive processing. In recent years, debates regarding the capacity and fidelity of the working memory (WM) system have advanced our understanding of the nature of these representations. In particular, there is growing recognition that WM representations are not merely imperfect copies of a perceived object or event. New experimental tools have revealed that observers possess richer information about the uncertainty in their memories and take advantage of environmental regularities to use limited memory resources optimally. Meanwhile, computational models of visuospatial WM formulated at different levels of implementation have converged on common principles relating capacity to variability and uncertainty. Here we review recent research on human WM from a computational perspective, including the neural mechanisms that support it.

Sensorimotor learning biases choice behavior: a learning neural field model for decision making.

According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making) should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action selection required for decision making in ambiguous choice situations.

Role of time in binding features in visual working memory.

Previous research on feature binding in visual working memory has supported a privileged role for location in binding an object's nonspatial features. However, humans are able to correctly recall feature conjunctions of objects that occupy the same location at different times. In a series of behavioral experiments, we investigated binding errors under these conditions, and specifically tested whether ordinal position can take the role of location in mediating feature binding. We performed two dual report experiments in which participants had to memorize three colored shapes presented sequentially at the screen center. When participants were cued with the ordinal position of one item and had to report its shape and color, report errors for the two features were largely uncorrelated. In contrast, when participants were cued, for example, with an item's shape and reported an incorrect ordinal position, they had a high chance of making a corresponding error in the color report. This pattern of error correlations closely matched the predictions of a model in which color and shape are bound to each other only indirectly via an item's ordinal position. In a third experiment, we directly compared the roles of location and sequential position in feature binding. Participants viewed a sequence of colored disks displayed at different locations and were cued either by a disk's location or its ordinal position to report its remaining properties. The pattern of errors supported a mixed strategy with individual variation, suggesting that binding via either time or space could be used for this task. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A neural mechanism for coordinate transformation predicts pre-saccadic remapping.

Whenever we shift our gaze, any location information encoded in the retinocentric reference frame that is predominant in the visual system is obliterated. How is spatial memory retained across gaze changes? Two different explanations have been proposed: Retinocentric information may be transformed into a gaze-invariant representation through a mechanism consistent with gain fields observed in parietal cortex, or retinocentric information may be updated in anticipation of the shift expected with every gaze change, a proposal consistent with neural observations in LIP. The explanations were considered incompatible with each other, because retinocentric update is observed before the gaze shift has terminated. Here, we show that a neural dynamic mechanism for coordinate transformation can also account for retinocentric updating. Our model postulates an extended mechanism of reference frame transformation that is based on bidirectional mapping between a retinocentric and a body-centered representation and that enables transforming multiple object locations in parallel. The dynamic coupling between the two reference frames generates a shift of the retinocentric representation for every gaze change. We account for the predictive nature of the observed remapping activity by using the same kind of neural mechanism to generate an internal representation of gaze direction that is predictively updated based on corollary discharge signals. We provide evidence for the model by accounting for a series of behavioral and neural experimental observations.

Location-independent feature binding in visual working memory for sequentially presented objects.

Spatial location is believed to have a privileged role in binding features held in visual working memory. Supporting this view, Pertzov and Husain (Attention, Perception, & Psychophysics, 76(7), 1914-1924, 2014) reported that recall of bindings between visual features was selectively impaired when items were presented sequentially at the same location compared to sequentially at different locations. We replicated their experiment, but additionally tested whether the observed impairment could be explained by perceptual interference during encoding. Participants viewed four oriented bars in highly discriminable colors presented sequentially either at the same or different locations, and after a brief delay were cued with one color to reproduce the associated orientation. When we used the same timing as the original study, we reproduced its key finding of impaired binding memory in the same-location condition. Critically, however, this effect was significantly modulated by the duration of the inter-stimulus interval, and disappeared if memoranda were presented with longer delays between them. In a second experiment, we tested whether the effect generalized to other visual features, namely reporting of colors cued by stimulus shape. While we found performance deficits in the same-location condition, these did not selectively affect binding memory. We argue that the observed effects are best explained by encoding interference, and that memory for feature binding is not necessarily impaired when memoranda share the same location.

Scene memory and spatial inhibition in visual search : A neural dynamic process model and new experimental evidence.

Any object-oriented action requires that the object be first brought into the attentional foreground, often through visual search. Outside the laboratory, this would always take place in the presence of a scene representation acquired from ongoing visual exploration. The interaction of scene memory with visual search is still not completely understood. Feature integration theory (FIT) has shaped both research on visual search, emphasizing the scaling of search times with set size when searches entail feature conjunctions, and research on visual working memory through the change detection paradigm. Despite its neural motivation, there is no consistently neural process account of FIT in both its dimensions. We propose such an account that integrates (1) visual exploration and the building of scene memory, (2) the attentional detection of visual transients and the extraction of search cues, and (3) visual search itself. The model uses dynamic field theory in which networks of neural dynamic populations supporting stable activation states are coupled to generate sequences of processing steps. The neural architecture accounts for basic findings in visual search and proposes a concrete mechanism for the integration of working memory into the search process. In a behavioral experiment, we address the long-standing question of whether both the overall speed and the efficiency of visual search can be improved by scene memory. We find both effects and provide model fits of the behavioral results. In a second experiment, we show that the increase in efficiency is fragile, and trace that fragility to the resetting of spatial working memory.

New perspectives on binding in visual working memory.

How does visual working memory (WM) store the binding between different features of a visual object (like colour, orientation, and location), and does memorizing these bindings require additional resources beyond memorizing individual features? These questions have traditionally been addressed by comparing performance across different types of change detection task. More recently, experimental tasks such as analogue (cued) recall, combined with analysis methods including Bayesian hypothesis testing and formal model comparison, have shed new light on the properties of WM. A significant new perspective is that noise in neural representation limits the precision of recall, and several recent models incorporate this view to account for failures of binding in WM. We review the literature on feature binding with a focus on these new developments and discuss their implications for the interpretation of classical findings.

No fixed item limit in visuospatial working memory.

Investigations of working memory capacity in the visual domain have converged on the concept of a limited supply of a representational medium, flexibly distributed between objects. Current debate centers on whether this medium is continuous, or quantized into 2 or 3 memory "slots". The latter model makes the strong prediction that, if an item in memory is probed, behavioral parameters will plateau when the number of items is the same or more than the number of slots. Here we examine short-term memory for object location using a two-dimensional pointing task. We show that recall variability for items in memory increases monotonically from 1 to 8 items. Using a novel method to isolate only those trials on which a participant correctly identifies the target, we show that response latency also increases monotonically from 1 to 8 items. We argue that both these findings are incompatible with a quantized model.

The Infant Orienting With Attention task: Assessing the neural basis of spatial attention in infancy.

Infant visual attention develops rapidly over the first year of life, significantly altering the way infants respond to peripheral visual events. Here we present data from 5-, 7- and 10-month-old infants using the Infant Orienting With Attention (IOWA) task, designed to capture developmental changes in visual spatial attention and saccade planning. Results indicate rapid development of spatial attention and visual response competition between 5 and 10 months. We use a dynamic neural field (DNF) model to link behavioral findings to neural population activity, providing a possible mechanistic explanation for observed developmental changes. Together, the behavioral and model simulation results provide new insights into the specific mechanisms that underlie spatial cueing effects, visual competition, and visual interference in infancy.

A neurobehavioral model of flexible spatial language behaviors.

We propose a neural dynamic model that specifies how low-level visual processes can be integrated with higher level cognition to achieve flexible spatial language behaviors. This model uses real-word visual input that is linked to relational spatial descriptions through a neural mechanism for reference frame transformations. We demonstrate that the system can extract spatial relations from visual scenes, select items based on relational spatial descriptions, and perform reference object selection in a single unified architecture. We further show that the performance of the system is consistent with behavioral data in humans by simulating results from 2 independent empirical studies, 1 spatial term rating task and 1 study of reference object selection behavior. The architecture we present thereby achieves a high degree of task flexibility under realistic stimulus conditions. At the same time, it also provides a detailed neural grounding for complex behavioral and cognitive processes.