Priority-based transformations of stimulus representation in visual working memory

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.

Representing Context and Priority in Working Memory

The ability to prioritize among contents in working memory (WM) is critical for successful control of thought and behavior. Recent work has demonstrated that prioritization in WM can be implemented by representing different states of priority in different representational formats. Here, we explored the mechanisms underlying WM prioritization by simulating the double serial retrocuing task with recurrent neural networks. Visualization of stimulus representational dynamics using principal component analysis revealed that the network represented trial context (order of presentation) and priority via different mechanisms. Ordinal context, a stable property lasting the duration of the trial, was accomplished by segregating representations into orthogonal subspaces. Priority, which changed multiple times during a trial, was accomplished by separating representations into different strata within each subspace. We assessed the generality of these mechanisms by applying dimensionality reduction and multiclass decoding to fMRI and EEG data sets and found that priority and context are represented differently along the dorsal visual stream and that behavioral performance is sensitive to trial-by-trial variability of priority coding, but not context coding.

Internal Representations Are Prioritized by Frontoparietal Theta Connectivity and Suppressed by alpha Oscillation Dynamics: Evidence from Concurrent Transcranial Magnetic Stimulation EEG and Invasive EEG

Control over internal representations requires the prioritization of relevant information and suppression of irrelevant information. The frontoparietal network exhibits prominent neural oscillations during these distinct cognitive processes. Yet, the causal role of this network-scale activity is unclear. Here, we targeted theta-frequency frontoparietal coherence and dynamic alpha oscillations in the posterior parietal cortex using online rhythmic transcranial magnetic stimulation (TMS) in women and men while they prioritized or suppressed internally maintained working memory (WM) representations. Using concurrent high-density EEG, we provided evidence that we acutely drove the targeted neural oscillation and TMS improved WM capacity only when the evoked activity corresponded with the desired cognitive process. To suppress an internal representation, we increased the amplitude of lateralized alpha oscillations in the posterior parietal cortex contralateral to the irrelevant visual field. For prioritization, we found that TMS to the prefrontal cortex increased theta-frequency connectivity in the prefrontoparietal network contralateral to the relevant visual field. To understand the spatial specificity of these effects, we administered the WM task to participants with implanted electrodes. We found that theta connectivity during prioritization was directed from the lateral prefrontal to the superior posterior parietal cortex. Together, these findings provide causal evidence in support of a model where a frontoparietal theta network prioritizes internally maintained representations and alpha oscillations in the posterior parietal cortex suppress irrelevant representations.

Distinct neural signatures underlying information maintenance and manipulation in working memory

Previous working memory research has demonstrated robust stimulus representations during memory maintenance in both voltage and alpha-band activity in electroencephalography. However, the exact functions of these 2 neural signatures have remained controversial. Here we systematically investigated their respective contributions to memory manipulation. Human participants either maintained a previously seen spatial location, or manipulated the location following a mental rotation cue over a delay. Using multivariate decoding, we observed robust location representations in low-frequency voltage and alpha-band oscillatory activity with distinct spatiotemporal dynamics: location representations were most evident in posterior channels in alpha-band activity, but were most prominent in the more anterior, central channels in voltage signals. Moreover, the temporal emergence of manipulated representation in central voltage preceded that in posterior alpha-band activity, suggesting that voltage might carry stimulus-specific source signals originated internally from anterior cortex, whereas alpha-band activity might reflect feedback signals in posterior cortex received from higher-order cortex. Lastly, while location representations in both signals were coded in a low-dimensional neural subspace, location representation in central voltage was higher-dimensional and underwent a representational transformation that exclusively predicted memory behavior. Together, these results highlight the crucial role of central voltage in working memory, and support functional distinctions between voltage and alpha-band activity.

Investigating the Roles of the Visual and Parietal Cortex in Representing Content versus Context in Visual Working Memory

Content-to-context binding is crucial for working memory performance. Using a dual-serial retrocueing (DSR) task on oriented gratings, Yu et al. (2020) found that content (orientation) of both prioritized and unprioritized memory items (PMI; UMI) was represented simultaneously in visual cortex, while their context (location) was represented in intraparietal sulcus (IPS), with a priority-based remapping of the representation of content and context of the UMI in each region, respectively. This registered report acquired fMRI of 24 healthy adults while they performed a DSR task with location as the to-be-reported content and orientation as the task-relevant context. We contrasted three accounts: domain-dependent, the engagement of visual and parietal regions depends on the feature domain (orientation vs location); functional, the engagement of these regions depends on their function (content vs context); and hybrid-a combination of the domain-dependent account and the additional stipulation that IPS encodes context regardless of domain. Delay-period activity in early visual cortex conformed most closely with functional predictions: robust priority-sensitive representation of stimulus location (content), but no evidence for the active representation of stimulus orientation (context). Delay-period activity in IPS, in contrast, conformed most closely to predictions of the hybrid account: active representation of content (location) and of prioritized context (orientation). Exploratory analyses further supported the hybrid account of IPS, revealing univariate sensitivity to variation in both content and context load, the latter in a manner that predicted individual differences in behavior. The representation of visual information in working memory is highly dependent on behavioral context.

Neural population dynamics of human working memory

The activity of neurons in macaque prefrontal cortex (PFC) persists during working memory (WM) delays, providing a mechanism for memory.1,2,3,4,5,6,7,8,9,10,11 Although theory,11,12 including formal network models,13,14 assumes that WM codes are stable over time, PFC neurons exhibit dynamics inconsistent with these assumptions.15,16,17,18,19 Recently, multivariate reanalyses revealed the coexistence of both stable and dynamic WM codes in macaque PFC.20,21,22,23 Human EEG studies also suggest that WM might contain dynamics.24,25 Nonetheless, how WM dynamics vary across the cortical hierarchy and which factors drive dynamics remain unknown. To elucidate WM dynamics in humans, we decoded WM content from fMRI responses across multiple cortical visual field maps.26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48 We found coexisting stable and dynamic neural representations of WM during a memory-guided saccade task. Geometric analyses of neural subspaces revealed that early visual cortex exhibited stronger dynamics than high-level visual and frontoparietal cortex. Leveraging models of population receptive fields, we visualized and made the neural dynamics interpretable. We found that during WM delays, V1 population initially encoded a narrowly tuned bump of activation centered on the peripheral memory target. Remarkably, this bump then spread inward toward foveal locations, forming a vector along the trajectory of the forthcoming memory-guided saccade. In other words, the neural code transformed into an abstraction of the stimulus more proximal to memory-guided behavior. Therefore, theories of WM must consider both sensory features and their task-relevant abstractions because changes in the format of memoranda naturally drive neural dynamics.

Strategic control of location and ordinal context in visual working memory

Working memory (WM) requires encoding stimulus identity and context (e.g. where or when stimuli were encountered). To explore the neural bases of the strategic control of context binding in WM, we acquired fMRI while subjects performed delayed recognition of 3 orientation patches presented serially and at different locations. The recognition probe was an orientation patch with a superimposed digit, and pretrial instructions directed subjects to respond according to its location ("location-relevant"), to the ordinal position corresponding to its digit ("order-relevant"), or to just its orientation (relative to all three samples; "context-irrelevant"). Delay period signal in PPC was greater for context-relevant than for "context-irrelevant" trials, and multivariate decoding revealed strong sensitivity to context binding requirements (relevant vs. "irrelevant") and to context domain ("location-" vs. "order-relevant") in both occipital cortex and PPC. At recognition, multivariate inverted encoding modeling revealed markedly different patterns in these 2 regions, suggesting different context-processing functions. In occipital cortex, an active representation of the location of each of the 3 samples was reinstated regardless of the trial type. The pattern in PPC, by contrast, suggested a trial type-dependent filtering of sample information. These results indicate that PPC exerts strategic control over the representation of stimulus context in visual WM.

A Transient High-dimensional Geometry Affords Stable Conjunctive Subspaces for Efficient Action Selection

Flexible action selection requires cognitive control mechanisms capable of mapping the same inputs to diverse output actions depending on goals and contexts. How the brain encodes information to enable this capacity remains one of the longstanding and fundamental problems in cognitive neuroscience. From a neural state-space perspective, solving this problem requires a control representation that can disambiguate similar input neural states, making task-critical dimensions separable depending on the context. Moreover, for action selection to be robust and time-invariant, control representations must be stable in time, thereby enabling efficient readout by downstream processing units. Thus, an ideal control representation should leverage geometry and dynamics that maximize the separability and stability of neural trajectories for task computations. Here, using novel EEG decoding methods, we investigated how the geometry and dynamics of control representations constrain flexible action selection in the human brain. Specifically, we tested the hypothesis that encoding a temporally stable conjunctive subspace that integrates stimulus, response, and context (i.e., rule) information in a high-dimensional geometry achieves the separability and stability needed for context-dependent action selection. Human participants performed a task that requires context-dependent action selection based on pre-instructed rules. Participants were cued to respond immediately at varying intervals following stimulus presentation, which forced responses at different states in neural trajectories. We discovered that in the moments before successful responses, there was a transient expansion of representational dimensionality that separated conjunctive subspaces. Further, we found that the dynamics stabilized in the same time window, and that the timing of entry into this stable and high-dimensional state predicted the quality of response selection on individual trials. These results establish the neural geometry and dynamics the human brain needs for flexible control over behavior.

Changes in behavioral priority influence the accessibility of working memory content

Evolving behavioral goals require the existence of selection mechanisms that prioritize task-relevant working memory (WM) content for action. Selecting an item stored in WM is known to blunt and/or reverse information loss in stimulus-specific representations of that item reconstructed from human brain activity, but extant studies have focused on all-or-none circumstances that allow or disallow an agent to select one of several items stored in WM. Conversely, behavioral studies suggest that humans can flexibly assign different levels of priority to different items stored in WM, but how doing so influences neural representations of WM content is unclear. One possibility is that assigning different levels of priority to items in WM influences the quality of those representations, resulting in more robust neural representations of high- vs. low-priority WM content. A second - and non-exclusive - possibility is that asymmetries in behavioral priority influence how rapidly neural representations of high- vs. low-priority WM content can be selected and reported. We tested these possibilities in two experiments by decoding high- and low-priority WM content from EEG recordings obtained while human volunteers performed a retrospectively cued WM task. Probabilistic changes in the behavioral relevance of a remembered item had no effect on our ability to decode it from EEG signals; instead, these changes influenced the latency at which above-chance decoding performance was reached. Thus, our results indicate that probabilistic changes in the behavioral relevance of WM content influence the ease with which memories can be selected independently of their strength.

Predicted utility modulates working memory fidelity in the brain

The predicted utility of information stored in working memory (WM) is hypothesized to influence the strategic allocation of WM resources. Prior work has shown that when information is prioritized, it is remembered with greater precision relative to other remembered items. However, these paradigms often complicate interpretation of the effects of predicted utility on item fidelity due to a concurrent memory load. Likewise, no fMRI studies have examined whether the predicted utility of an item modulates fidelity in the neural representation of items during the memory delay without a concurrent load. In the current study, we used fMRI to investigate whether predicted utility influences fidelity of WM representations in the brain. Using a generative model multivoxel analysis approach to estimate the quality of remembered representations across predicted utility conditions, we observed that items with greater predicted utility are maintained in memory with greater fidelity, even when they are the only item being maintained. Further, we found that this pattern follows a parametric relationship where more predicted utility corresponded to greater fidelity. These precision differences could not be accounted for based on a redistribution of resources among already-remembered items. Rather, we interpret these results in terms of a gating mechanism that allows for pre-allocation of resources based on predicted value alone. This evidence supports a theoretical distinction between resource allocation that occurs as a result of load and resource pre-allocation that occurs as a result of predicted utility.

Temporal expectation based on the duration variability modulates alpha oscillations during working memory retention

While maintaining information over a delay of time, working memory (WM) also allows individuals to prepare the mnemonic contents for prospective utilisation. However, it remains unclear whether the expectation of the time of WM test could modulate neural responses during the retention interval of WM and subsequent performance. Here, we investigated whether temporal expectations based on the variability of delay duration can modulate 9-13 Hz alpha oscillations during WM retention and whether the expectation-induced alpha activity was associated with WM performance. Participants performed a retro-cueing WM task with magnetoencephalography (MEG) (Experiment 1) and a standard WM task with electroencephalography (EEG) (Experiment 2). The expectation of the timing of the WM test was manipulated by the temporal structure of the tasks with small or large variability in the delay durations. We showed that alpha oscillations during retention interval and WM performance varied with duration variability in both of the MEG and EEG experiments. The novel finding was greater alpha-power attenuation over the left frontal and parietal regions during WM retention when the duration variability was small and the test onset was predictable, compared to when the duration variability was large and the test onset was less predictable. Importantly, we observed a positive relationship in variability difference between the response benefit and alpha-power attenuation in the left posterior parietal regions at both MEG-source and EEG-electrode levels. Finally, we confirmed the behavioural benefit when a condition with a fixed delay-duration was included in a behavioural experiment (Experiment 3). When conjoined, the delay duration enables individuals to anticipate when the relevant information would be put to work, and alpha oscillations track the anticipatory states during WM maintenance.