Memory Meets Control in Hippocampal and Striatal Binding of Stimuli, Responses, and Attentional Control States

Binding of response-independent task rules

Binding theories claim that features of an episode are bound to each other and can be retrieved once these features are re-encountered. Binding effects have been shown in task-switching studies with a strong focus on bindings of observable features such as responses. In this study, we aimed to investigate whether task rules, translating stimulus information into motor output can be bound and subsequently retrieved even if they act independently from specific response codes. To address this question, we utilized a task-switching paradigm with varying visual context features. Unlike previous studies, tasks in the present study did not differ in their response options, and sequential response repetitions were eliminated by design. In three experiments, we observed larger task-switch costs on trials repeating the context of the previous trial than on context-change trials. According to binding accounts, this suggests that response-independent task rules adopted in the previous trial became bound to the context feature and were retrieved upon re-encountering the context feature in the current trial. The results of this study generalize previous findings indicating that binding processes can include response-independent control to task-switching situations.

Task switch costs scale with dissimilarity between task rules

Cognitive flexibility enables humans to voluntarily switch tasks. Task switching requires replacing the previously active task representation with a new one, an operation that typically results in a switch cost. Thus, understanding cognitive flexibility requires understanding how tasks are represented in the brain. We hypothesize that task representations are cognitive map-like, such that the magnitude of the difference between task representations reflects their conceptual differences: The greater the distinction between the two task representations, the more updating is required. This hypothesis predicts that switch costs should increase with between task dissimilarity. To test this hypothesis, we use an experimental design that parametrically manipulates the similarity between task rules. We observe that response time scales with the dissimilarity between the task rules. The findings shed light on the organizational principles of task representations and extend the conventional binary task-switch effect (task repeat vs. switch) to a theoretical framework with parametric task switches. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Transfer of cognitive control adjustments within and between speakers

Congruency effects in conflict tasks are typically larger after congruent compared to incongruent trials. This congruency sequence effect (CSE) indicates that top-down adjustments of cognitive control transfer between processing episodes, at least when controlling for bottom-up memory processes by alternating between stimulus-response (S-R) sets in confound-minimised designs. According to the control-retrieval account, cognitive control is bound to task-irrelevant context features (e.g., stimulus position or modality) and retrieved upon subsequent context feature repetitions. A confound-minimised CSE should therefore be larger when context features repeat rather than change between two trials. This study tested this prediction for a more abstract contextual stimulus feature, speaker gender. In two preregistered auditory prime-probe task experiments, participants classified colour words spoken by a female or male voice. Across both experiments, we found confound-minimised CSEs that were not reliably affected by whether the speaker gender repeated or changed. This indicates that speaker transitions have virtually no influence on the transfer of control adjustments in the absence of S-R repetitions. By contrast, when allowing for bottom-up memory processes by repeating the S-R set, CSEs were consistently larger when the speaker gender repeated compared to changed. This suggests that speaker transitions can in principle influence transfer between processing episodes. The discrepancy also held true when considering learning and test episodes separated by an intervening episode. Thus, the present findings call for a refinement of the control-retrieval account to accommodate the role of more abstract contextual stimulus features for the maintenance of memory traces in auditory conflict processing.

Is implicit memory associated with the hippocampus?

According to the traditional memory-systems view, the hippocampus is critical during explicit (conscious) long-term memory, whereas other brain regions support implicit (nonconscious) memory. In the last two decades, some fMRI studies have reported hippocampal activity during implicit memory tasks. The aim of the present discussion paper was to identify whether any implicit memory fMRI studies have provided convincing evidence that the hippocampus is associated with nonconscious processes without being confounded by conscious processes. Experimental protocol and analysis parameters included the stimulus type(s), task(s), measures of subjective awareness, explicit memory accuracy, the relevant fMRI contrast(s) or analysis, and confound(s). A systematic review was conducted to identify implicit memory studies that reported fMRI activity in the hippocampus. After applying exclusion criteria, 13 articles remained for analysis. We found that there were no implicit memory fMRI studies where subjective awareness was absent, explicit memory performance was at chance, and there were no confounds that could have driven the observed hippocampal activity. The confounds included explicit memory (including false memory), imbalanced attentional states between conditions (yielding activation of the default-mode network), imbalanced stimuli between conditions, and differential novelty. As such, not a single fMRI study provided convincing evidence that implicit memory was associated with the hippocampus. Neuropsychological evidence was also considered, and implicit memory deficits were caused by factors known to disrupt brain regions beyond the hippocampus, such that the behavioral effects could not be attributed to this region. The present results indicate that implicit memory is not associated with the hippocampus.

The dead salmon strikes again: Reports of unconscious processing in the hippocampus may reflect Type-I error

Steinkrauss and Slotnick (2024) reviewed neuroimaging studies linking the hippocampus with implicit memory. They conclude that there is no convincing evidence that the hippocampus is associated with implicit memory because prior studies are confounded by explicit memory (among other factors). Here, we ask a different yet equally important question: do reports of unconscious hippocampal activity reflect a Type-I error (i.e. a false positive)? We find that 39% of studies linking the hippocampus with implicit memory (7 of 18) do not report correcting for multiple comparisons. These results indicate that many unconscious hippocampal effects may reflect a Type-I error.

Memory for abstract control states does not decay with increasing retrieval delays

Recent studies have suggested that abstract control states (i.e., internal attentional states independent from concrete stimuli and responses) can be stored in episodic memory and retrieved subsequently. However, the duration of such a control state memory remains unclear. Previous research has found a quick and complete decay for stimulus-response bindings after 2000-5000 ms. Here, we tested a possible decay of control state bindings with retrieval delays of 2000, 3000, or 5000 ms. Five preregistered experiments used a confound-minimized prime-target task to measure the congruency sequence effect (CSE) separately for trials in which a nominally irrelevant context feature changed or repeated across trials. Analyses of the individual experiments did not result in conclusive evidence. A mega-analysis integrating the data of all experiments (Ntotal = 326) replicated evidence for binding and retrieval of control states, in that larger CSEs were found for context repetition trials. Importantly, Bayesian analysis indicated that this effect was not modulated by the length of retrieval delay. While this finding suggests that bindings of abstract control states can be relatively robust, we also discuss possible limitations of the present research.

Exploring behavioral adjustments of proportion congruency manipulations in an Eriksen flanker task with visual and auditory distractor modalities

The present study investigated global behavioral adaptation effects to conflict arising from different distractor modalities. Three experiments were conducted using an Eriksen flanker paradigm with constant visual targets, but randomly varying auditory or visual distractors. In Experiment 1, the proportion of congruent to incongruent trials was varied for both distractor modalities, whereas in Experiments 2A and 2B, this proportion congruency (PC) manipulation was applied to trials with one distractor modality (inducer) to test potential behavioral transfer effects to trials with the other distractor modality (diagnostic). In all experiments, mean proportion congruency effects (PCEs) were present in trials with a PC manipulation, but there was no evidence of transfer to diagnostic trials in Experiments 2A and 2B. Distributional analyses (delta plots) provided further evidence for distractor modality-specific global behavioral adaptations by showing differences in the slope of delta plots with visual but not auditory distractors when increasing the ratio of congruent trials. Thus, it is suggested that distractor modalities constrain global behavioral adaptation effects due to the learning of modality-specific memory traces (e.g., distractor-target associations) and/or the modality-specific cognitive control processes (e.g., suppression of modality-specific distractor-based activation). Moreover, additional analyses revealed partial transfer of the congruency sequence effect across trials with different distractor modalities suggesting that distractor modality may differentially affect local and global behavioral adaptations.

Flexible integration and segregation of large-scale networks during adaptive control

Adaptive control characterizes the dynamic adjustment of cognitive control to changing environmental demand, and has obtained growing interests in its neural mechanism for the past two decades. Recent years, interpreting network reconfiguration in terms of integration and segregation has been proved to shed light on neural structure underlying various cognitive tasks. However, the relationship between network architecture and adaptive control remains unclear. Here, we quantified the network integration (global efficiency, participation coefficient, inter-subnetwork efficiency) and segregation (local efficiency, modularity) in the whole-brain and analyzed how these graph theory metrics were modulated by adaptive control. The results showed that the integration of the cognitive control network (the fronto-parietal network, FPN), the visual network (VIN) and the sensori-motor network (SMN) was significantly improved when conflict was rare, so as to cope with the incongruent trials of high cognitive control demands. Additionally, as the conflict proportion increased, the segregation of the cingulo-opercular network (CON) and the default mode network (DMN) significantly enhanced, which may contribute to specialized functioning or automatic processing, and help to solve conflict in a less resource-intensive mode. Finally, using graph metrics as features, the multivariate classifier reliably predicted the context condition. These results demonstrate how large-scale brain networks support adaptive control through flexible integration and segregation.

Conflict Experience Regulates the Neural Encoding of Cognitive Conflict

Cognitive control is adaptive in that it rapidly adjusts attention in response to changing contexts and shifting goals. Research provides evidence that cognitive control can rapidly adjust attention to focus on task-relevant information based on prior conflict experience. Neural encoding of goal-related information is critical for goal-directed behaviour; however, the empirical evidence on how conflict experience affects the encoding of cognitive conflict in the brain is rather weak. In the present fMRI study, a Stroop task with different proportions of incongruent trial was used to investigate the neural encoding of cognitive conflict in the environment with changing conflict experience. The results showed that the anterior cingulate cortex, dorsolateral prefrontal cortex, and intraparietal sulcus played a pivotal role in the neural encoding of cognitive conflict. The classification in anterior cingulate cortex was significantly above chance in the high-proportion, moderate-proportion, and low-proportion conflict conditions conducted separately, suggesting that neural encoding of cognitive conflict in this region was not altered based on proportion of conflict. The dorsolateral prefrontal cortex and intraparietal sulcus showed significant above-chance classification in the moderate-proportion and low-proportion conflict conditions, but not in the high-proportion conflict condition. These findings provide direct evidence that conflict experience modulates the neural encoding of cognitive conflict.

Functional differentiation of the dorsal striatum: a coordinate-based neuroimaging meta-analysis

Background

The dorsal striatum, a nucleus in the basal ganglia, plays a key role in the execution of cognitive functions in the human brain. Recent studies have focused on how the dorsal striatum participates in a single cognitive function, whereas the specific roles of the caudate and putamen in performing multiple cognitive functions remain unclear. In this paper we conducted a meta-analysis of the relevant neuroimaging literature to understand the roles of subregions of the dorsal striatum in performing different functions.

Methods

PubMed, Web of Science, and BrainMap Functional Database were searched to find original functional magnetic resonance imaging (fMRI) studies conducted on healthy adults under reward, memory, emotion, and decision-making tasks, and relevant screening criteria were formulated. Single task activation, contrast activation, and conjunction activation analyses were performed using the activation likelihood estimation (ALE) method for the coordinate-based meta-analysis to evaluate the differences and linkages.

Results

In all, 112 studies were included in this meta-analysis. Analysis revealed that, of the 4 single activation tasks, reward, memory, and emotion tasks all activated the putamen more, whereas decision-making tasks activated the caudate body. Contrast analysis showed that the caudate body played an important role in the 2 cooperative activation tasks, but conjunction activation results found that more peaks appeared in the caudate head.

Discussion

Different subregions of the caudate and putamen assume different roles in processing complex cognitive behaviors. Functional division of the dorsal striatum identified specific roles of 15 different subregions, reflecting differences and connections between the different subregions in performing different cognitive behaviors.

Transfer of learned cognitive control settings within and between tasks

Cognitive control is modulated based on learned associations between conflict probability and stimulus features such as color. We investigated whether such learning-guided control transfers to novel stimuli and/or a novel task. In Experiments 1 and 2, participants experienced an item-specific proportion congruence (ISPC) manipulation in a Stroop (Experiment 1) or Flanker (Experiment 2) task with mostly congruent (MC) and mostly incongruent (MI) colors in training blocks. During a transfer block, participants performed the same task and encountered novel transfer stimuli paired with MC or MI colors. Evidencing within-task transfer, in both experiments, responses were faster to incongruent transfer stimuli comprising an MI color compared with an MC color. In Experiment 3, we investigated between-task transfer from Stroop to Flanker. After training with an ISPC manipulation in the Stroop task, a Flanker task was completed with the same colors but without an ISPC manipulation (i.e., 50% congruent). Responses were faster to incongruent transfer stimuli paired with the previously-MI colors compared with the previously-MC colors. Additionally, transfer was evident in the first half of the Flanker task but not the second half. The evidence for within-task transfer, in combination with the novel evidence for between-task transfer, suggests learned control settings are flexibly retrieved and executed when predictive cues signaling these control settings are encountered in novel stimuli or a novel task. Theoretical implications are discussed alongside potential neural mechanisms mediating transfer of learning-guided control.

Assessing the Durability of One-Shot Stimulus-Control Bindings

It has been proposed that cognitive control processes may be implemented in a contextually appropriate manner through the encoding, and cued retrieval, of associations between stimuli and the control processes that were active during their encoding, forming "stimulus-control bindings" as part of episodic event files. Prior work has found strong evidence for such a mechanism by observing behavioral effects of stimulus-control bindings based on a single pairing (one-shot learning). Here, we addressed the important question of how durable these one-shot stimulus-control bindings are. Over three experiments, we investigated the durability of one-shot stimulus-control bindings in relation to both the passage of time and the number of intervening events between the encoding (prime) and retrieval (probe) of the stimulus-control bindings. We found that stimulus-control bindings are quite robust to temporal decay, lasting at least up to 5 minutes in the absence of similar intervening events. By contrast, binding effects were more short-lived in the face of interference from the encoding of similar events between the prime and probe, with a maximum duration of ~2 minutes. Together, these results shed new light on the characteristics of the binding mechanisms underlying the integration of internal control processes in episodic event files and highlight that interference, rather than temporal decay, may be the main limiting factor on long-term effects of item-specific one-shot control learning.

Towards understanding how we pay attention in naturalistic visual search settings

Research on attentional control has largely focused on single senses and the importance of behavioural goals in controlling attention. However, everyday situations are multisensory and contain regularities, both likely influencing attention. We investigated how visual attentional capture is simultaneously impacted by top-down goals, the multisensory nature of stimuli, and the contextual factors of stimuli's semantic relationship and temporal predictability. Participants performed a multisensory version of the Folk et al. (1992) spatial cueing paradigm, searching for a target of a predefined colour (e.g. a red bar) within an array preceded by a distractor. We manipulated: 1) stimuli's goal-relevance via distractor's colour (matching vs. mismatching the target), 2) stimuli's multisensory nature (colour distractors appearing alone vs. with tones), 3) the relationship between the distractor sound and colour (arbitrary vs. semantically congruent) and 4) the temporal predictability of distractor onset. Reaction-time spatial cueing served as a behavioural measure of attentional selection. We also recorded 129-channel event-related potentials (ERPs), analysing the distractor-elicited N2pc component both canonically and using a multivariate electrical neuroimaging framework. Behaviourally, arbitrary target-matching distractors captured attention more strongly than semantically congruent ones, with no evidence for context modulating multisensory enhancements of capture. Notably, electrical neuroimaging of surface-level EEG analyses revealed context-based influences on attention to both visual and multisensory distractors, in how strongly they activated the brain and type of activated brain networks. For both processes, the context-driven brain response modulations occurred long before the N2pc time-window, with topographic (network-based) modulations at ∼30 ms, followed by strength-based modulations at ∼100 ms post-distractor onset. Our results reveal that both stimulus meaning and predictability modulate attentional selection, and they interact while doing so. Meaning, in addition to temporal predictability, is thus a second source of contextual information facilitating goal-directed behaviour. More broadly, in everyday situations, attention is controlled by an interplay between one's goals, stimuli's perceptual salience, meaning and predictability. Our study calls for a revision of attentional control theories to account for the role of contextual and multisensory control.

A Representational Similarity Analysis of Cognitive Control during Color-Word Stroop

Progress in understanding the neural bases of cognitive control has been supported by the paradigmatic color-word Stroop task, in which a target response (color name) must be selected over a more automatic, yet potentially incongruent, distractor response (word). For this paradigm, models have postulated complementary coding schemes: dorsomedial frontal cortex (DMFC) is proposed to evaluate the demand for control via incongruency-related coding, whereas dorsolateral PFC (DLPFC) is proposed to implement control via goal and target-related coding. Yet, mapping these theorized schemes to measured neural activity within this task has been challenging. Here, we tested for these coding schemes relatively directly, by decomposing an event-related color-word Stroop task via representational similarity analysis. Three neural coding models were fit to the similarity structure of multivoxel patterns of human fMRI activity, acquired from 65 healthy, young-adult males and females. Incongruency coding was predominant in DMFC, whereas both target and incongruency coding were present with indistinguishable strength in DLPFC. In contrast, distractor information was strongly encoded within early visual cortex. Further, these coding schemes were differentially related to behavior: individuals with stronger DLPFC (and lateral posterior parietal cortex) target coding, but weaker DMFC incongruency coding, exhibited less behavioral Stroop interference. These results highlight the utility of the representational similarity analysis framework for investigating neural mechanisms of cognitive control and point to several promising directions to extend the Stroop paradigm.SIGNIFICANCE STATEMENT How the human brain enables cognitive control - the ability to override behavioral habits to pursue internal goals - has been a major focus of neuroscience research. This ability has been frequently investigated by using the Stroop color-word naming task. With the Stroop as a test-bed, many theories have proposed specific neuroanatomical dissociations, in which medial and lateral frontal brain regions underlie cognitive control by encoding distinct types of information. Yet providing a direct confirmation of these claims has been challenging. Here, we demonstrate that representational similarity analysis, which estimates and models the similarity structure of brain activity patterns, can successfully establish the hypothesized functional dissociations within the Stroop task. Representational similarity analysis may provide a useful approach for investigating cognitive control mechanisms.

Meaningful boundaries create boundary conditions for control

Recent research demonstrated that control states learned via experience in inducer locations were retrieved in novel, unbiased (i.e., diagnostic) locations positioned nearby. Such transfer has been observed even in the presence of a visual boundary (a line) separating inducer and diagnostic locations. One aim of the present study was to assess whether a meaningful boundary might disrupt retrieval of control states in diagnostic locations. Supporting this possibility, in Experiment 1 learned control states did not transfer from inducer locations superimposed on a university's quad to diagnostic locations superimposed on buildings outside the quad. Similarly, in Experiment 2 transfer was not observed for diagnostic locations positioned on a track outside of the field where inducer locations were positioned; however, transfer was also not observed for diagnostic locations on the field (inside the boundary). The latter finding helped motivate Experiments 3a and 3b, which tackled the second aim by examining whether a meaningful boundary might attenuate learning of control states for inducer locations within the boundary. Consistent with this hypothesis, a CSPC effect was observed only when a meaningful boundary was not present. Taken together, the findings provide evidence that meaningful boundaries influence how conflict experiences are organized during a task thereby impacting learning and transfer of context-specific control states.

Mind wandering at encoding, but not at retrieval, disrupts one-shot stimulus-control learning

The one-shot pairing of a stimulus with a specific cognitive control process, such as task switching, can bind the two together in memory. The episodic control-binding hypothesis posits that the formation of temporary stimulus-control bindings, which are held in event-files supported by episodic memory, can guide the contextually appropriate application of cognitive control. Across two experiments, we sought to examine the role of task-focused attention in the encoding and implementation of stimulus-control bindings in episodic event-files. In Experiment 1, we obtained self-reports of mind wandering during encoding and implementation of stimulus-control bindings. Results indicated that, whereas mind wandering during the implementation of stimulus-control bindings does not decrease their efficacy, mind wandering during the encoding of these control-state associations interferes with their successful deployment at a later point. In Experiment 2, we complemented these results by using trial-by-trial pupillometry to measure attention, again demonstrating that attention levels at encoding predict the subsequent implementation of stimulus-control bindings better than attention levels at implementation. These results suggest that, although encoding stimulus-control bindings in episodic memory requires active attention and engagement, once encoded, these bindings are automatically deployed to guide behavior when the stimulus recurs. These findings expand our understanding of how cognitive control processes are integrated into episodic event files.

Learning to Overexert Cognitive Control in a Stroop Task

How do people learn when to allocate how much cognitive control to which task? According to the Learned Value of Control (LVOC) model, people learn to predict the value of alternative control allocations from features of a situation. This suggests that people may generalize the value of control learned in one situation to others with shared features, even when demands for control are different. This makes the intriguing prediction that what a person learned in one setting could cause them to misestimate the need for, and potentially overexert, control in another setting, even if this harms their performance. To test this prediction, we had participants perform a novel variant of the Stroop task in which, on each trial, they could choose to either name the color (more control-demanding) or read the word (more automatic). Only one of these tasks was rewarded each trial and could be predicted by one or more stimulus features (the color and/or word). Participants first learned colors and then words that predicted the rewarded task. Then, we tested how these learned feature associations transferred to novel stimuli with some overlapping features. The stimulus-task-reward associations were designed so that for certain combinations of stimuli, transfer of learned feature associations would incorrectly predict that more highly rewarded task would be color-naming, even though the actually rewarded task was word-reading and therefore did not require engaging control. Our results demonstrated that participants overexerted control for these stimuli, providing support for the feature-based learning mechanism described by the LVOC model.

Multiple Routes to Control in the Prime-Target Task: Congruence Sequence Effects Emerge Due to Modulation of Irrelevant Prime Activity and Utilization of Temporal Order Information

In interference tasks, the magnitude of the congruency effect is reduced in trials that follow an incongruent trial. This congruence sequence effect (CSE) reflects cognitive control processes, yet accounts disagree when and how control is exerted. Here, we address these questions in the context of the prime-target task. In this task, control can either modulate early prime or late target information. Furthermore, control can utilize information specific to the stimulus (perceptual features) or relational information between stimuli (temporal order). Two experiments (N = 41 | N = 62) were conducted using a prime-target task with arrows (prime) and letters (target). We presented either the prime before the target or the target before the prime. For both trial-type transitions, the CSE was assessed. Regarding the first question, when is control exerted, results showed a larger CSE for prime→target relative to target→prime trials. This suggests that control in the prime-target task modulates prime activity. Regarding the second question, how is control exerted, a combined analysis of both experiments showed a larger CSE for repetition of the same prime and target order across two trials (e.g., previous trial: prime→target; current trial: prime→target) compared to changes (e.g., previous trial: prime→target; current trial: target→prime), suggesting that control in the prime-target task can employ temporal selection.

Performance feedback promotes proactive but not reactive adaptation of conflict-control

Cognitive control refers to the use of internal goals to guide how we process stimuli, and control can be applied proactively (in anticipation of a stimulus) or reactively (once that stimulus has been presented). The application of control can be guided by memory; for instance, people typically learn to adjust their level of attentional selectivity to changing task statistics, such as different frequencies of hard and easy trials in the Stroop task. This type of control-learning is highly adaptive, but its boundary conditions are currently not well understood. In the present study, we assessed how the presence of performance feedback shapes control-learning in the context of item-specific (reactive control, Experiments 1a and 1b) and list-wide (proactive control, Experiments 2a and 2b) proportion of congruency manipulations in a Stroop protocol. We found that performance feedback did not alter the modulation of the Stroop effect by item-specific cueing, but did enhance the modulation of the Stroop effect by a list-wide context. Performance feedback thus selectively promoted proactive, but not reactive, adaptation of cognitive control. These results have important implications for experimental designs, potential psychiatric treatment, and theoretical accounts of the mechanisms underlying control-learning. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Prefrontal reinstatement of contextual task demand is predicted by separable hippocampal patterns

Goal-directed behavior requires the representation of a task-set that defines the task-relevance of stimuli and guides stimulus-action mappings. Past experience provides one source of knowledge about likely task demands in the present, with learning enabling future predictions about anticipated demands. We examine whether spatial contexts serve to cue retrieval of associated task demands (e.g., context A and B probabilistically cue retrieval of task demands X and Y, respectively), and the role of the hippocampus and dorsolateral prefrontal cortex (dlPFC) in mediating such retrieval. Using 3D virtual environments, we induce context-task demand probabilistic associations and find that learned associations affect goal-directed behavior. Concurrent fMRI data reveal that, upon entering a context, differences between hippocampal representations of contexts (i.e., neural pattern separability) predict proactive retrieval of the probabilistically dominant associated task demand, which is reinstated in dlPFC. These findings reveal how hippocampal-prefrontal interactions support memory-guided cognitive control and adaptive behavior.

Spatial contexts are often predictive of the tasks to be performed in them (e.g., a kitchen predicts cooking). Here the authors show that the retrieval of task demand when encountering a spatial context depends on hippocampal-prefrontal interactions.

Memories of control: One-shot episodic learning of item-specific stimulus-control associations

The repeated pairing of a particular stimulus with a specific cognitive control process, such as task switching, can bind the two together in memory, resulting in the formation of stimulus-control associations. These bindings are thought to guide the context-sensitive application of cognitive control, but it is not presently known whether such stimulus-control associations are only acquired through slow, incremental learning or could also be mediated by episodic memories of a single experience, so-called one-shot learning. Here, we tested this episodic control-binding hypothesis by probing whether a single co-occurrence of a stimulus and the control process of task switching would lead to significant performance benefits (reduced task switch cost) when that stimulus later re-occurred under the same as opposed to different control demands. Across three experiments, we demonstrate that item-specific stimulus-control associations can be formed based on a single exposure, providing the first strong evidence for episodic memory guidance of cognitive control.

Measuring Adaptive Control in Conflict Tasks

The past two decades have witnessed an explosion of interest in the cognitive and neural mechanisms of adaptive control processes that operate in selective attention tasks. This has spawned not only a large empirical literature and several theories but also the recurring identification of potential confounds and corresponding adjustments in task design to create confound-minimized metrics of adaptive control. The resulting complexity of this literature can be difficult to navigate for new researchers entering the field, leading to suboptimal study designs. To remediate this problem, we present here a consensus view among opposing theorists that specifies how researchers can measure four hallmark indices of adaptive control (the congruency sequence effect, and list-wide, context-specific, and item-specific proportion congruency effects) while minimizing easy-to-overlook confounds.

Cortical and subcortical contributions to context-control learning

"Cognitive control" describes our ability to strategically bias information processing in line with internal goals. Traditionally, research has focused on delineating the sources of top-down biasing, implicating the lateral prefrontal cortex. The past two decades, however, have seen increasing interest in the regulation of control, that is, how learning processes guide the context-sensitive application of top-down biasing. Here, we review and synthesize recent research into the cognitive and neural mechanisms of this type of "context-control learning". We first discuss a fast-growing cognitive psychology literature documenting how specific cognitive control states can become associated with, and subsequently triggered by, contextual cues. We then review neuroimaging studies that speak to the neural substrates of contextual adjustments in control, with a particular focus on recent work that explicitly modeled context-control learning processes. We conclude that these studies suggest an important subcortical extension of the traditional frontal control network, as they indicate a key role for the caudate nucleus in forming associations between contextual cues and appropriate control settings.

Repetition priming in amnesia: Distinguishing associative learning at different levels of abstraction

Learned associations between stimuli and responses make important contributions to priming. The current study aimed to determine whether medial temporal lobe (MTL) binding mechanisms mediate this learning. Prior studies implicating the MTL in stimulus-response (S-R) learning have not isolated associative learning at the response level from associative learning at other levels of representation (e.g., task sets or decisions). The current study investigated whether the MTL is specifically involved in associative learning at the response level by testing a group of amnesic patients with MTL damage on a priming paradigm that isolates associative learning at the response level. Patients demonstrated intact priming when associative learning was isolated to the stimulus-response level. In contrast, their priming was reduced when associations between stimuli and more abstract representations (e.g., stimulus-task or stimulus-decision associations) could contribute to performance. These results provide novel neuropsychological evidence that S-R contributions to priming can be supported by regions outside the MTL, and suggest that the MTL may play a critical role in linking stimuli to more abstract tasks or decisions during priming.

Behavioral facilitation and increased brain responses from a high interference working memory context

Many real-life situations require flexible behavior in changing environments. Evidence suggests that anticipation of conflict or task difficulty results in behavioral and neural allocation of task-relevant resources. Here we used a high- and low-interference version of an item-recognition task to examine the neurobehavioral underpinnings of context-sensitive adjustment in working memory (WM). We hypothesized that task environments that included high-interference trials would require participants to allocate neurocognitive resources to adjust to the more demanding task context. The results of two independent behavioral experiments showed enhanced WM performance in the high-interference context, which indicated that a high-interference context improves performance on non-interference trials. A third behavioral experiment showed that when WM load was increased, this effect was no longer significant. Neuroimaging results further showed greater engagement of inferior frontal gyrus, striatum, parietal cortex, hippocampus, and midbrain in participants performing the task in the high- than in the low-interference context. This effect could arise from an active or dormant mode of anticipation that seems to engage fronto-striatal and midbrain regions to flexibly adjust resources to task demands. Our results extend the model of conflict adaptation beyond trial-to-trial adjustments by showing that a high interference context affects both behavioral and biological aspects of cognition.

Integrated externally and internally generated task predictions jointly guide cognitive control in prefrontal cortex

Cognitive control proactively configures information processing to suit expected task demands. Predictions of forthcoming demand can be driven by explicit external cues or be generated internally, based on past experience (cognitive history). However, it is not known whether and how the brain reconciles these two sources of information to guide control. Pairing a probabilistic task-switching paradigm with computational modeling, we found that external and internally generated predictions jointly guide task preparation, with a bias for internal predictions. Using model-based neuroimaging, we then show that the two sources of task prediction are integrated in dorsolateral prefrontal cortex, and jointly inform a representation of the likelihood of a change in task demand, encoded in frontoparietal cortex. Upon task-stimulus onset, dorsomedial prefrontal cortex encoded the need for reactive task-set adjustment. These data reveal how the human brain integrates external cues and cognitive history to prepare for an upcoming task.

The Complex Nature of Hippocampal-Striatal Interactions in Spatial Navigation

Decades of research have established the importance of the hippocampus for episodic and spatial memory. In spatial navigation tasks, the role of the hippocampus has been classically juxtaposed with the role of the dorsal striatum, the latter of which has been characterized as a system important for implementing stimulus-response and action-outcome associations. In many neuroimaging paradigms, this has been explored through contrasting way finding and route-following behavior. The distinction between the contributions of the hippocampus and striatum to spatial navigation has been supported by extensive literature. Convergent research has also underscored the fact that these different memory systems can interact in dynamic ways and contribute to a broad range of navigational scenarios. For example, although familiar routes may often be navigable based on stimulus-response associations, hippocampal episodic memory mechanisms can also contribute to egocentric route-oriented memory, enabling recall of context-dependent sequences of landmarks or the actions to be made at decision points. Additionally, the literature has stressed the importance of subdividing the striatum into functional gradients—with more ventral and medial components being important for the behavioral expression of hippocampal-dependent spatial memories. More research is needed to reveal how networks involving these regions process and respond to dynamic changes in memory and control demands over the course of navigational events. In this Perspective article, we suggest that a critical direction for navigation research is to further characterize how hippocampal and striatal subdivisions interact in different navigational contexts.

The Caudate Nucleus Mediates Learning of Stimulus-Control State Associations

A longstanding dichotomy in cognitive psychology and neuroscience pits controlled, top-down driven behavior against associative, bottom-up driven behavior, where cognitive control processes allow us to override well-learned stimulus-response (S-R) associations. By contrast, some previous studies have raised the intriguing possibility of an integration between associative and controlled processing in the form of stimulus-control state (S-C) associations, the learned linkage of specific stimuli to particular control states, such as high attentional selectivity. The neural machinery mediating S-C learning remains poorly understood, however. Here, we combined human functional magnetic resonance imaging (fMRI) with a previously developed Stroop protocol that allowed us to dissociate reductions in Stroop interference based on S-R learning from those based on S-C learning. We modeled subjects' acquisition of S-C and S-R associations using an associative learning model and then used trial-by-trial S-C and S-R prediction error (PE) estimates in model-based behavioral and fMRI analyses. We found that PE estimates derived from S-C and S-R associations accounted for the reductions in behavioral Stroop interference effects in the S-C and S-R learning conditions, respectively. Moreover, model-based fMRI analyses identified the caudate nucleus as the key structure involved in selectively updating stimulus-control state associations. Complementary analyses also revealed a greater reliance on parietal cortex when using the learned S-R versus S-C associations to minimize Stroop interference. These results support the emerging view that generalizable control states can become associated with specific bottom-up cues, and they place the caudate nucleus of the dorsal striatum at the center of the neural stimulus-control learning machinery.

SIGNIFICANCE STATEMENT

Previous behavioral studies have demonstrated that control states, for instance, heightened attentional selectivity, can become directly associated with, and subsequently retrieved by, particular stimuli, thus breaking down the traditional dichotomy between top-down and bottom-up driven behavior. However, the neural mechanisms underlying this type of stimulus-control learning remain poorly understood. We therefore combined noninvasive human neuroimaging with a task that allowed us to dissociate the acquisition of stimulus-control associations from that of stimulus-response associations. The results revealed the caudate nucleus as the key brain structure involved in selectively driving stimulus-control learning. These data represent the first identification of the neural mechanisms of stimulus-specific control associations, and they significantly extend current conceptions of the type of learning processes mediated by the caudate.

Cueing cognitive flexibility: Item-specific learning of switch readiness

The rich behavioral repertoire of the human species derives from our ability to flexibly reconfigure processing strategies (task sets) in response to changing requirements. This updating of task sets is effortful, as reflected by longer response times when switching a task than repeating it (switch costs). However, some recent data suggest that switch costs can be reduced by cueing switch readiness bottom-up, by associating particular stimuli with frequent switch requirements. This type of "stimulus-control (S-C) learning" would be highly adaptive, as it combines the speed of automatic (bottom-up) processing with the flexibility and generalizability of controlled (top-down) processing. However, it is unclear whether S-C learning of switch readiness is truly possible, and what the underlying mechanisms are. Here we address these questions by pairing specific stimuli with a need to update task-sets either frequently or rarely. In all 3 experiments, we observe robust item-specific switch probability (ISSP) effects as revealed by smaller switch costs for frequent switch items than for rare switch items. By including a neutral condition, we also show that the ISSP effect is primarily driven by S-C learning reducing switch costs in frequent switch items. Furthermore, by employing 3 tasks in Experiment 3, we establish that the ISSP effect reflects an enhancement of general switch readiness, rather than of the readiness to switch to a specific alternate task. These results firmly establish that switch readiness is malleable by item-specific S-C learning processes, documenting that a generalizable state of cognitive flexibility can be primed by a bottom-up stimulus. (PsycINFO Database Record

Visual Prediction Error Spreads Across Object Features in Human Visual Cortex

Visual cognition is thought to rely heavily on contextual expectations. Accordingly, previous studies have revealed distinct neural signatures for expected versus unexpected stimuli in visual cortex. However, it is presently unknown how the brain combines multiple concurrent stimulus expectations such as those we have for different features of a familiar object. To understand how an unexpected object feature affects the simultaneous processing of other expected feature(s), we combined human fMRI with a task that independently manipulated expectations for color and motion features of moving-dot stimuli. Behavioral data and neural signals from visual cortex were then interrogated to adjudicate between three possible ways in which prediction error (surprise) in the processing of one feature might affect the concurrent processing of another, expected feature: (1) feature processing may be independent; (2) surprise might "spread" from the unexpected to the expected feature, rendering the entire object unexpected; or (3) pairing a surprising feature with an expected feature might promote the inference that the two features are not in fact part of the same object. To formalize these rival hypotheses, we implemented them in a simple computational model of multifeature expectations. Across a range of analyses, behavior and visual neural signals consistently supported a model that assumes a mixing of prediction error signals across features: surprise in one object feature spreads to its other feature(s), thus rendering the entire object unexpected. These results reveal neurocomputational principles of multifeature expectations and indicate that objects are the unit of selection for predictive vision.

SIGNIFICANCE STATEMENT

We address a key question in predictive visual cognition: how does the brain combine multiple concurrent expectations for different features of a single object such as its color and motion trajectory? By combining a behavioral protocol that independently varies expectation of (and attention to) multiple object features with computational modeling and fMRI, we demonstrate that behavior and fMRI activity patterns in visual cortex are best accounted for by a model in which prediction error in one object feature spreads to other object features. These results demonstrate how predictive vision forms object-level expectations out of multiple independent features.

Sex Differences in Fiber Connection between the Striatum and Subcortical and Cortical Regions

The striatum is an important subcortical structure with extensive connections to other regions of the brain. These connections are believed to play important roles in behaviors such as reward-related processes and impulse control, which show significant sex differences. However, little is known about sex differences in the striatum-projected fiber connectivity. The current study examined sex differences between 50 Chinese males and 79 Chinese females in their fiber connections between the striatum and nine selected cortical and subcortical regions. Despite overall similarities, males showed stronger fiber connections between the left caudate and rostral cingulate cortex, between the right putamen and the lateral orbitofrontal cortex, between the bilateral putamen and the ventro-lateral prefrontal cortex, and between the right caudate and the ventro-lateral prefrontal cortex, whereas females showed stronger fiber connections between the right putamen and the dorsolateral prefrontal cortex, between bilateral caudate and hippocampus, and between the left putamen and hippocampus. These findings help us to understand sex differences in the striatum-projected fiber connections and their implications for sex differences in behaviors.