Task structure tailors the geometry of neural representations in human lateral prefrontal cortex.

How do human brains represent tasks of varying structure? The lateral prefrontal cortex (lPFC) flexibly represents task information. However, principles that shape lPFC representational geometry remain unsettled. We use fMRI and pattern analyses to reveal the structure of lPFC representational geometries as humans perform two distinct categorization tasks- one with flat, conjunctive categories and another with hierarchical, context-dependent categories. We show that lPFC encodes task-relevant information with task-tailored geometries of intermediate dimensionality. These geometries preferentially enhance the separability of task-relevant variables while encoding a subset in abstract form. Specifically, in the flat task, a global axis encodes response-relevant categories abstractly, while category-specific local geometries are high-dimensional. In the hierarchy task, a global axis abstractly encodes the higher-level context, while low-dimensional, context-specific local geometries compress irrelevant information and abstractly encode the relevant information. Comparing these task geometries exposes generalizable principles by which lPFC tailors representations to different tasks.

Policy abstraction as a predictor of cognitive effort avoidance.

Consistent evidence has established that people avoid cognitively effortful tasks. However, the features that make a task cognitively effortful are still not well understood. Multiple hypotheses have been proposed regarding which task demands underlie cognitive effort costs, such as time-on-task, error likelihood, and the general engagement of cognitive control. In this study, we test the novel hypothesis that tasks requiring behavior according to higher degrees of policy abstraction are experienced as more effortful. Accordingly, policy abstraction, operationalized as the levels of contextual contingency required by task rules, drives task avoidance over and above the effects of task performance, such as time-on-task or error likelihood. To test this hypothesis, we combined two previously established cognitive control tasks that parametrically manipulated policy abstraction with the demand selection task procedure. The design of these tasks allowed us to test whether people avoided tasks with higher order policy abstraction while controlling for the contribution of factors such as time-on-task and expected error rate (ER). Consistent with our hypothesis, we observed that policy abstraction was the strongest predictor of cognitive effort choices, followed by ER. This was evident across both studies and in a within-subject cross-study analysis. These results establish at least one task feature independent of performance, which is predictive of task avoidance behavior. We interpret these results within an opportunity cost framework for understanding aversive experiences of cognitive effort while performing a task. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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.

A rapid theta network mechanism for flexible information encoding.

Flexible behavior requires gating mechanisms that encode only task-relevant information in working memory. Extant literature supports a theoretical division of labor whereby lateral frontoparietal interactions underlie information maintenance and the striatum enacts the gate. Here, we reveal neocortical gating mechanisms in intracranial EEG patients by identifying rapid, within-trial changes in regional and inter-regional activities that predict subsequent behavioral outputs. Results first demonstrate information accumulation mechanisms that extend prior fMRI (i.e., regional high-frequency activity) and EEG evidence (inter-regional theta synchrony) of distributed neocortical networks in working memory. Second, results demonstrate that rapid changes in theta synchrony, reflected in changing patterns of default mode network connectivity, support filtering. Graph theoretical analyses further linked filtering in task-relevant information and filtering out irrelevant information to dorsal and ventral attention networks, respectively. Results establish a rapid neocortical theta network mechanism for flexible information encoding, a role previously attributed to the striatum.

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.

The role of conjunctive representations in prioritizing and selecting planned actions.

For flexible goal-directed behavior, prioritizing and selecting a specific action among multiple candidates are often important. Working memory has long been assumed to play a role in prioritization and planning, while bridging cross-temporal contingencies during action selection. However, studies of working memory have mostly focused on memory for single components of an action plan, such as a rule or a stimulus, rather than management of all of these elements during planning. Therefore, it is not known how post-encoding prioritization and selection operate on the entire profile of representations for prospective actions. Here, we assessed how such control processes unfold over action representations, highlighting the role of conjunctive representations that nonlinearly integrate task-relevant features during maintenance and prioritization of action plans. For each trial, participants prepared two independent rule-based actions simultaneously, then they were retro-cued to select one as their response. Prior to the start of the trial, one rule-based action was randomly assigned to be high priority by cueing that it was more likely to be tested. We found that both full action plans were maintained as conjunctive representations during action preparation, regardless of priority. However, during output selection, the conjunctive representation of the high-priority action plan was more enhanced and readily selected as an output. Furthermore, the strength of the high-priority conjunctive representation was associated with behavioral interference when the low-priority action was tested. Thus, multiple alternate upcoming actions were maintained as integrated representations and served as the target of post-encoding attentional selection mechanisms to prioritize and select an action from within working memory.

Abstract task representations for inference and control.

Behavioral flexibility depends on our capacity to build and leverage abstract knowledge about tasks. Recently, two separate lines of research have implicated distinct brain networks in representing abstract task information: a frontoparietal cortical network, and a network involving the medial temporal lobe (MTL), medial prefrontal, and orbitofrontal cortex (OMPFC). These observations have mostly been made in parallel, with little attempt to understand their relationship. Here, we hypothesize that abstract task representations in these networks differ primarily in format, not content. Namely, that the MTL-OMPFC network maintains task knowledge in a flexible cognitive map, while the frontoparietal network formats this knowledge as productions that facilitate action selection. We discuss novel implications and predictions for behavioral flexibility arising from this hypothesis.

Differential assessment of frontally-mediated behaviors between self- and informant-report in patients with obsessive-compulsive disorder following gamma ventral capsulotomy.

Obsessive-Compulsive Disorder (OCD) is a debilitating disorder causing marked distress and functional impairment. While advances in behavioral and pharmacotherapies have been effective for a majority of patients with OCD, 10-30% remain treatment refractory and severely impaired. For a subset of treatment-resistant individuals with the most severe and disabling (intractable) illness, gamma ventral capsulotomy (GVC) appears effective in reducing OCD symptoms and functional impairment. However, the effects of the ventral internal capsule lesion via GVC surgery on executive function in everyday life have been minimally investigated. Examining behavioral outcomes of GVC also provides a rare opportunity to probe the functional importance of the ventral prefrontal-subcortical connections of the internal capsule white matter tract in a relatively homogenous sample of patients with comparable white matter lesions. The present study investigated changes in frontally-mediated behaviors, measured by the Frontal Systems Behavior Scale (FrSBe), following GVC in 45 individuals with severe and otherwise intractable OCD, as rated by patients themselves and family members. Linear mixed effects models revealed a significant improvement in patient self-ratings on the FrSBe after surgery, while family ratings did not significantly change. Interestingly, improvement on the FrSBe for both self and family raters was significantly correlated with improvement in OCD symptomatology post-surgery, as measured by the Yale-Brown Obsessive Compulsive Scale (Y-BOCS). At the group level, we found no evidence of decline in frontally-mediated behaviors assessed by the FrSBe as a result of focal white matter disconnection via GVC. However, we cannot rule out the possibility that placebo effects or compromised patient self-awareness or insight contributed to the significant improvement in self ratings. Our measures may also have limited sensitivity to more selective impairments that could result from a small lesion to the ventral internal capsule. The present study demonstrates the need for detailed investigation of cognitive and behavioral changes as important factors when considering GVC as a viable treatment option for patients with refractory OCD.

Neural systems underlying the learning of cognitive effort costs.

People balance the benefits of cognitive work against the costs of cognitive effort. Models that incorporate prospective estimates of the costs of cognitive effort into decision making require a mechanism by which these costs are learned. However, it remains an open question what brain systems are important for this learning, particularly when learning is not tied explicitly to a decision about what task to perform. In this fMRI experiment, we parametrically manipulated the level of effort a task requires by increasing task switching frequency across six task contexts. In a scanned learning phase, participants implicitly learned about the task switching frequency in each context. In a subsequent test phase, participants made selections between pairs of these task contexts. We modeled learning within a reinforcement learning framework, and found that effort expectations that derived from task-switching probability and response time (RT) during learning were the best predictors of later choice behavior. Prediction errors (PE) from these two models were associated with FPN during distinct learning epochs. Specifically, PE derived from expected RT was most correlated with the fronto-parietal network early in learning, whereas PE derived from expected task switching frequency was correlated with the fronto-parietal network late in learning. These results suggest that multiple task-related factors are tracked by the brain while performing a task that can drive subsequent estimates of effort costs.

Neural representation of abstract task structure during generalization.

Cognitive models in psychology and neuroscience widely assume that the human brain maintains an abstract representation of tasks. This assumption is fundamental to theories explaining how we learn quickly, think creatively, and act flexibly. However, neural evidence for a verifiably generative abstract task representation has been lacking. Here, we report an experimental paradigm that requires forming such a representation to act adaptively in novel conditions without feedback. Using functional magnetic resonance imaging, we observed that abstract task structure was represented within left mid-lateral prefrontal cortex, bilateral precuneus, and inferior parietal cortex. These results provide support for the neural instantiation of the long-supposed abstract task representation in a setting where we can verify its influence. Such a representation can afford massive expansions of behavioral flexibility without additional experience, a vital characteristic of human cognition.

The value of proactive goal setting and choice in 3- to 7-year-olds' use of working memory gating strategies in a naturalistic task.

Rule-guided behavior depends on the ability to strategically update and act on content held in working memory. Proactive and reactive control strategies were contrasted across two experiments using an adapted input/output gating paradigm (Neuron, 81, 2014 and 930). Behavioral accuracies of 3-, 5-, and 7-year-olds were higher when a contextual cue appeared at the beginning of the task (input gating) rather than at the end (output gating). This finding supports prior work in older children, suggesting that children are better when input gating but rely on the more effortful output gating strategy for goal-oriented action selection (Cognition, 155, 2016 and 8). A manipulation was added to investigate whether children's use of working memory strategies becomes more flexible when task goals are specified internally rather than externally provided by the experimenter. A shift toward more proactive control was observed when children chose the task goal among two alternatives. Scan path analyses of saccadic eye movement indicated that giving children agency and choice over the task goal resulted in less use of a reactive strategy than when the goal was determined by the experimenter.

The dimensionality of neural representations for control.

Cognitive control allows us to think and behave flexibly based on our context and goals. At the heart of theories of cognitive control is a control representation that enables the same input to produce different outputs contingent on contextual factors. In this review, we focus on an important property of the control representation's neural code: its representational dimensionality. Dimensionality of a neural representation balances a basic separability/generalizability trade-off in neural computation. We will discuss the implications of this trade-off for cognitive control. We will then briefly review current neuroscience findings regarding the dimensionality of control representations in the brain, particularly the prefrontal cortex. We conclude by highlighting open questions and crucial directions for future research.

Augmenting Frontal Dopamine Tone Enhances Maintenance over Gating Processes in Working Memory.

The contents of working memory must be maintained in the face of distraction, but updated when appropriate. To manage these competing demands of stability and flexibility, maintained representations in working memory are complemented by distinct gating mechanisms that selectively transmit information into and out of memory stores. The operations of such dopamine-dependent gating systems in the midbrain and striatum and their complementary dopamine-dependent memory maintenance operations in the cortex may therefore be dissociable. If true, selective increases in cortical dopamine tone should preferentially enhance maintenance over gating mechanisms. To test this hypothesis, tolcapone, a catechol-O-methyltransferase inhibitor that preferentially increases cortical dopamine tone, was administered in a randomized, double-blind, placebo-controlled, within-subject fashion to 49 participants who completed a hierarchical working memory task that varied maintenance and gating demands. Tolcapone improved performance in a condition with higher maintenance requirements and reduced gating demands, reflected in a reduction in the slope of RTs across the distribution. Resting-state fMRI data demonstrated that the degree to which tolcapone improved performance in individual participants correlated with increased connectivity between a region important for stimulus response mappings (left dorsal premotor cortex) and cortical areas implicated in visual working memory, including the intraparietal sulcus and fusiform gyrus. Together, these results provide evidence that augmenting cortical dopamine tone preferentially improves working memory maintenance.

A Virtual Reality Memory Palace Variant Aids Knowledge Retrieval from Scholarly Articles.

We present exploratory research of virtual reality techniques and mnemonic devices to assist in retrieving knowledge from scholarly articles. We used abstracts of scientific publications to represent knowledge in scholarly articles; participants were asked to read, remember, and retrieve knowledge from a set of abstracts. We conducted an experiment to compare participants' recall and recognition performance in three different conditions: a control condition without a pre-specified strategy to test baseline individual memory ability, a condition using an image-based variant of a mnemonic called a "memory palace," and a condition using a virtual reality-based variant of a memory palace. Our analyses show that using a virtual reality-based memory palace variant greatly increased the amount of knowledge retrieved and retained over the baseline, and it shows a moderate improvement over the other image-based memory palace variant. Anecdotal feedback from participants suggested that personalizing a memory palace variant would be appreciated. Our results support the value of virtual reality for some high-level cognitive tasks and help improve future applications of virtual reality and visualization.

Neural Systems for Memory-based Value Judgment and Decision-making.

Real-life choices often require that we draw inferences about the value of options based on structured, schematic knowledge about their utility for our current goals. Other times, value information may be retrieved directly from a specific prior experience with an option. In an fMRI experiment, we investigated the neural systems involved in retrieving and assessing information from different memory sources to support value-based choice. Participants completed a task in which items could be conferred positive or negative value based on schematic associations (i.e., schema value) or learned directly from experience via deterministic feedback (i.e., experienced value). We found that ventromedial pFC (vmPFC) activity correlated with the influence of both experience- and schema-based values on participants' decisions. Connectivity between the vmPFC and middle temporal cortex also tracked the inferred value of items based on schematic associations on the first presentation of ingredients, before any feedback. In contrast, the striatum responded to participants' willingness to bet on ingredients as a function of the unsigned strength of their memory for those options' values. These results argue that the striatum and vmPFC play distinct roles in memory-based value judgment and decision-making. Specifically, the vmPFC assesses the value of options based on information inferred from schematic knowledge and retrieved from prior direct experience, whereas the striatum controls a decision to act on options based on memory strength.

Hierarchical cognitive control and the frontal lobes.

Cognitive control refers to our ability to choose courses of thought and action that achieve our goals over habitual but contextually inappropriate ones. Hierarchical control problems are those in which multiple goals or contextual contingency must be managed at once and related to one another. In the open-ended complexity of the real world, hierarchical control arguably characterizes most of the problems faced by our control systems. And, it is these cases of hierarchical control where patients with damage to executive systems are most apt to fail, even those that perform well on simplified laboratory tasks. In this chapter, we consider the functional organization of frontal brain systems that support hierarchical cognitive control. We focus on two particular cases of hierarchical control. First, we discuss a line of work testing how managing multiple contingencies en route to a response relates to processing along the rostrocaudal axis of frontal cortex. Second, we consider cases of sequential tasks that require monitoring and behaving according to a series of tasks performed in time. In this latter case, we focus on the particular role of rostrolateral prefrontal cortex. We conclude with considerations of future directions of basic and clinically relevant research in this domain.

Double-wavelet transform for multisubject task-induced functional magnetic resonance imaging data.

The goal of this article is to model multisubject task-induced functional magnetic resonance imaging (fMRI) response among predefined regions of interest (ROIs) of the human brain. Conventional approaches to fMRI analysis only take into account temporal correlations, but do not rigorously model the underlying spatial correlation due to the complexity of estimating and inverting the high dimensional spatio-temporal covariance matrix. Other spatio-temporal model approaches estimate the covariance matrix with the assumption of stationary time series, which is not always feasible. To address these limitations, we propose a double-wavelet approach for modeling the spatio-temporal brain process. Working with wavelet coefficients simplifies temporal and spatial covariance structure because under regularity conditions, wavelet coefficients are approximately uncorrelated. Different wavelet functions were used to capture different correlation structures in the spatio-temporal model. The main advantages of the wavelet approach are that it is scalable and that it deals with nonstationarity in brain signals. Simulation studies showed that our method could reduce false-positive and false-negative rates by taking into account spatial and temporal correlations simultaneously. We also applied our method to fMRI data to study activation in prespecified ROIs in the prefontal cortex. Data analysis showed that the result using the double-wavelet approach was more consistent than the conventional approach when sample size decreased.

Neural systems of cognitive demand avoidance.

Cognitive effort is typically aversive, evident in people's tendency to avoid cognitively demanding tasks. The 'cost of control' hypothesis suggests that engagement of cognitive control systems of the brain makes a task costly and the currency of that cost is a reduction in anticipated rewards. However, prior studies have relied on binary hard versus easy task subtractions to manipulate cognitive effort and so have not tested this hypothesis in "dose-response" fashion. In a sample of 50 participants, we parametrically manipulated the level of effort during fMRI scanning by systematically increasing cognitive control demands during a demand-selection paradigm over six levels. As expected, frontoparietal control network (FPN) activity increased, and reward network activity decreased, as control demands increased across tasks. However, avoidance behavior was not attributable to the change in FPN activity, lending only partial support to the cost of control hypothesis. By contrast, we unexpectedly observed that the de-activation of a task-negative brain network corresponding to the Default Mode Network (DMN) across levels of the cognitive control manipulation predicted the change in avoidance. In summary, we find partial support for the cost of control hypothesis, while highlighting the role of task-negative brain networks in modulating effort avoidance behavior.

The relationship between cognitive enrichment and cognitive control: A systematic investigation of environmental influences on development through socioeconomic status.

We measured the impact of socioeconomic status (SES) on cognitive processes. We examined cognitive control, specifically working memory (WM), in a sample of N = 141 7- to 17-year-olds using rule-guided behavior tasks. Our hypothesis is based on computational modeling data that suggest that the development of flexible cognitive control requires variable experiences in which to implement rule-guided action. We found that not all experiences that correlated with SES in our sample impacted task performance, and not all experiential variables that impacted performance were associated with SES. Of the experiential variables associated with task performance, only cognitive enrichment opportunities worked indirectly through SES to affect WM as tested with rule-guided behavior tasks. We discuss the data in the context of necessary precision in SES research.