Contextual inference in learning and memory

Contextualizing predictive minds

The structure of human memory seems to be optimized for efficient prediction, planning, and behavior. We propose that these capacities rely on a tripartite structure of memory that includes concepts, events, and contexts-three layers that constitute the mental world model. We suggest that the mechanism that critically increases adaptivity and flexibility is the tendency to contextualize. This tendency promotes local, context-encoding abstractions, which focus event- and concept-based planning and inference processes on the task and situation at hand. As a result, cognitive contextualization offers a solution to the frame problem-the need to select relevant features of the environment from the rich stream of sensorimotor signals. We draw evidence for our proposal from developmental psychology and neuroscience. Adopting a computational stance, we present evidence from cognitive modeling research which suggests that context sensitivity is a feature that is critical for maximizing the efficiency of cognitive processes. Finally, we turn to recent deep-learning architectures which independently demonstrate how context-sensitive memory can emerge in a self-organized learning system constrained by cognitively-inspired inductive biases.

CA1 ensembles expressing immediate-early genes are driven by context switch, shrink with sustained presence, and show no effect of change of task demands

The hippocampus (HPC) is essential for navigation and memory, tracking environmental continuity and change, including navigation relative to moving targets. CA1 ensembles expressing immediate-early gene (IEG) Arc and Homer1a RNA are contextually specific. While IEG expression correlates with HPC-dependent task demands, the effects of behavioral demands on IEG-expressing ensembles remain unclear. In three experiments, we investigated the effects of context switch, sustained presence, and task demands on dorso-proximal CA1 IEG+ ensembles in rats. Experiment 1 showed that the size of IEG+ (Arc, Homer1a RNA) ensembles dropped to baseline during uninterrupted 30-minute exploration, reflecting familiarization, unless a context switch was present. Context-specificity of the ensembles depended on both environment identity and timing of the context switch. Experiment 2 found no effect of HPC-dependent mobile robot avoidance or HPC-independent avoidance of a stationary robot on IEG+ ensembles beyond mere exploration. Experiment 3 replicated these findings for c-Fos protein. The data suggest that IEG+ ensembles are driven by a context switch and shrink over time during sustained presence in the same environment. We found no evidence of task demands or their change affecting the size, stability over time, or task-specificity of IEG+ ensembles. These results shed light on the temporal dynamics of CA1 IEG+ ensembles, and their control by contextual and behavioral factors.

Partially dissociable roles of the orbitofrontal cortex and dorsal hippocampus in context-dependent hierarchical associations

Reward cues are often ambiguous; what is good in one context is not necessarily good in another. To solve this ambiguity, animals form hierarchical associations in which the context gates the retrieval of appropriate cue-evoked memories. These hierarchical associations regulate cue-elicited behavior and influence subsequent learning, promoting the inference of context-dependency. The orbitofrontal cortex (OFC) and dorsal hippocampus (DH) are both proposed to encode a "cognitive map" encompassing hierarchical, context-dependent associations. However, OFC- and DH-specific contributions to the different functional properties of hierarchical associations remain controversial. Using chemogenetic inactivation in rats, we show that the OFC is essential to both properties of hierarchical associations (performance regulation and learning bias). In contrast, DH's role appears limited to the contextual learning bias conferred by hierarchical associations. This work establishes the OFC as a critical orchestrator of hierarchical associations and provides insights into the extended circuits mediating the functional properties of these associations.

Kernels of Motor Memory Formation: Temporal Generalization in Bimanual Adaptation

In daily life, we coordinate both simultaneous and sequential bimanual movements to manipulate objects. Our ability to rapidly account for different object dynamics suggests there are neural mechanisms to quickly deal with them. Here we investigate how actions of one arm can serve as a contextual cue for the other arm and facilitate adaptation. Specifically, we examine the temporal characteristics that underlie motor memory formation and recall, by testing the contextual effects of prior, simultaneous, and post contralateral arm movements in both male and female human participants. To do so, we measure their temporal generalization in three bimanual interference tasks. Importantly, the timing context of the learned action plays a pivotal role in the temporal generalization. While motor memories trained with post adaptation contextual movements generalize broadly, motor memories trained with prior contextual movements exhibit limited generalization, and motor memories trained with simultaneous contextual movements do not generalize to prior or post contextual timings. This highlights temporal tuning in sensorimotor plasticity: different training conditions yield substantially different temporal generalization characteristics. Since these generalizations extend far beyond any variability in training times, we suggest that the observed differences may stem from inherent differences in the use of prior, current, and post adaptation contextual information in the generation of natural behavior. This would imply differences in the underlying neural circuitry involved in learning and executing the corresponding coordinated bimanual movements.

Assessment IS learning: developing a student-centred approach for assessment in Higher Education

Assessment and the associated feedback from those assessments are powerful factors in the development of students' learning. We have seen a shift within the Higher Education sector to conceptualise assessment as being more than summative assessment 'of' learning. Instead, there has been a greater emphasis on assessment 'as' learning, or assessment 'for' learning, through the enhanced use of formative assessments. Centralising assessment within the learning process highlights that assessment IS learning and cannot be separated from other elements of the learning process. In particular, assessment has a vital role to play in the development of students' self-regulated learning skills and the development of independence in learners. However, for assessments to effectively support learning, they need to be meaningful, engaging, well-integrated into the learning activities and 'student-focused'. Placing student skills development and personal development at the centre of assessment design has the potential to empower students through assessment. This review focuses on the potential of assessment to support student learning and development, using the 'Equity, Agency, Transparency' ('EAT') framework as a lens for effective assessment and feedback practices. We suggest ways in which we can make our assessment and feedback practices more inclusive, meaningful and authentic to the students' learning needs.

Identifying Transfer Learning in the Reshaping of Inductive Biases

Transfer learning, the reuse of newly acquired knowledge under novel circumstances, is a critical hallmark of human intelligence that has frequently been pitted against the capacities of artificial learning agents. Yet, the computations relevant to transfer learning have been little investigated in humans. The benefit of efficient inductive biases (meta-level constraints that shape learning, often referred as priors in the Bayesian learning approach), has been both theoretically and experimentally established. Efficiency of inductive biases depends on their capacity to generalize earlier experiences. We argue that successful transfer learning upon task acquisition is ensured by updating inductive biases and transfer of knowledge hinges upon capturing the structure of the task in the inductive bias that can be reused in novel tasks. To explore this, we trained participants on a non-trivial visual stimulus sequence task (Alternating Serial Response Times, ASRT); during the Training phase, participants were exposed to one specific sequence for multiple days, then on the Transfer phase, the sequence changed, while the underlying structure of the task remained the same. Our results show that beyond the acquisition of the stimulus sequence, our participants were also able to update their inductive biases. Acquisition of the new sequence was considerably sped up by earlier exposure but this enhancement was specific to individuals showing signatures of abandoning initial inductive biases. Enhancement of learning was reflected in the development of a new internal model. Additionally, our findings highlight the ability of participants to construct an inventory of internal models and alternate between them based on environmental demands. Further, investigation of the behavior during transfer revealed that it is the subjective internal model of individuals that can predict the transfer across tasks. Our results demonstrate that even imperfect learning in a challenging environment helps learning in a new context by reusing the subjective and partial knowledge about environmental regularities.

Attention defines the context for implicit sensorimotor adaptation

Movement errors are used to continuously recalibrate the sensorimotor map, a process known as sensorimotor adaptation. Here we examined how attention influences this automatic and obligatory learning process. Focusing first on spatial attention, we compared conditions in which the visual feedback that provided information about the movement outcome was either attended or unattended. Surprisingly, this manipulation had no effect on the rate of adaptation. We next used a dual-task methodology to examine the influence of attentional resources on adaptation. Here, again, we found no effect of attention, with the rate of adaptation similar under focused or divided attention conditions. Interestingly, we found that attention modulates adaptation in an indirect manner: Attended stimuli serve as cues that define the context for learning. The rate of adaptation was significantly attenuated when the attended stimulus changed from the end of one trial to the start of the next trial. In contrast, similar changes to unattended stimuli had no impact on adaptation. Together, these results suggest that visual attention defines the cues that establish the context for sensorimotor learning.

Decision uncertainty as a context for motor memory

The current view of perceptual decision-making suggests that once a decision is made, only a single motor programme associated with the decision is carried out, irrespective of the uncertainty involved in decision making. In contrast, we show that multiple motor programmes can be acquired on the basis of the preceding uncertainty of the decision, indicating that decision uncertainty functions as a contextual cue for motor memory. The actions learned after making certain (uncertain) decisions are only partially transferred to uncertain (certain) decisions. Participants were able to form distinct motor memories for the same movement on the basis of the preceding decision uncertainty. Crucially, this contextual effect generalizes to novel stimuli with matched uncertainty levels, demonstrating that decision uncertainty is itself a contextual cue. These findings broaden the understanding of contextual inference in motor memory, emphasizing that it extends beyond direct motor control cues to encompass the decision-making process.

Different mechanisms of contextual inference govern associatively learned and sensory-evoked postural responses

Human standing balance relies on the continuous monitoring and integration of sensory signals to infer our body's motion and orientation within the environment. However, when sensory information is no longer contextually relevant to balancing the body (e.g., when sensory and motor signals are incongruent), sensory-evoked balance responses are rapidly suppressed, much earlier than any conscious perception of changes in balance control. Here, we used a robotic balance simulator to assess whether associatively learned postural responses are similarly modulated by sensorimotor incongruence and contextual relevance to postural control. Twenty-nine participants in three groups were classically conditioned to generate postural responses to whole-body perturbations when presented with an initially neutral sound cue. During catch and extinction trials, participants received only the auditory stimulus but in different sensorimotor states corresponding to their group: 1) during normal active balance, 2) while immobilized, and 3) throughout periods where the computer subtly removed active control over balance. In the balancing and immobilized states, conditioned responses were either evoked or suppressed, respectively, according to the (in)ability to control movement. Following the immobilized state, conditioned responses were renewed when balance was restored, indicating that conditioning was retained but only expressed when contextually relevant. In contrast, conditioned responses persisted in the computer-controlled state even though there was no causal relationship between motor and sensory signals. These findings suggest that mechanisms responsible for sensory-evoked and conditioned postural responses do not share a single, central contextual inference and assessment of their relevance to postural control, and may instead operate in parallel.

Elemental and configural representation of a conditioned context

A context can be conceptualized as a stable arrangement of elements or as the sum of single elements. Both configural and elemental representations play a role in associative processes. This study aimed to explore the respective contributions of these two representations of a context in the acquisition of conditioned anxiety in humans. Virtual reality (VR) can be an ecologically valid tool to investigate context-related mechanisms, yet the influence of the sense of presence within the virtual environment remains unclear. Forty-eight healthy individuals participated in a VR-based context conditioning wherein electric shocks (unconditioned stimulus, US) were unpredictably delivered in one virtual office (CTX+), but not in the other (CTX-). During the test phase, nine elements from each context were presented singularly. We found a cluster of participants, who exhibited heightened anticipation of the US for anxiety-related elements as compared to the other group. In contrast to their clear elemental representation, these individuals showed diminished discriminative responses between the two context's configurations. Discriminative responses to the contexts were boosted in those individuals, who had a weaker elemental representation. Importantly, the individual sense of presence significantly influenced the conditioned responses. These findings align with the dual-representation view of context and provide insights into the role of presence in eliciting (conditioned) anxiety responses.

Sleep and quiet wakefulness signify an idling brain hub for creative insights

Long-term potentiation of synaptic strength is a fundamental aspect of learning and memory. Memories are believed to be stored within specific populations of neurons known as engram cells, which are subsequently reactivated during sleep, facilitating the consolidation of stored information. However, sleep and offline reactivations are associated not only with past experiences but also with anticipation of future events. During periods of offline reactivation, which occur during sleep and quiet wakefulness, the brain exhibits a capability to form novel connections. This process links various past experiences, often leading to the emergence of qualitatively new information that was not initially available. Brain activity during sleep and quiet wakefulness is referred to as the 'idling brain'. Idling brain activity is believed to play a pivotal role in abstracting essential information, comprehending underlying rules, generating creative ideas and fostering insightful thoughts. In this review, we will explore the current state of research and future directions in understanding how sleep and idling brain activity are interconnected with various cognitive functions, especially creative insights. These insights have profound implications for our daily lives, impacting our ability to process information, make decisions and navigate complex situations effectively. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.

Statistical learning shapes pain perception and prediction independently of external cues

The placebo and nocebo effects highlight the importance of expectations in modulating pain perception, but in everyday life we don't need an external source of information to form expectations about pain. The brain can learn to predict pain in a more fundamental way, simply by experiencing fluctuating, non-random streams of noxious inputs, and extracting their temporal regularities. This process is called statistical learning. Here, we address a key open question: does statistical learning modulate pain perception? We asked 27 participants to both rate and predict pain intensity levels in sequences of fluctuating heat pain. Using a computational approach, we show that probabilistic expectations and confidence were used to weigh pain perception and prediction. As such, this study goes beyond well-established conditioning paradigms associating non-pain cues with pain outcomes, and shows that statistical learning itself shapes pain experience. This finding opens a new path of research into the brain mechanisms of pain regulation, with relevance to chronic pain where it may be dysfunctional.

A cerebellar population coding model for sensorimotor learning

The cerebellum is crucial for sensorimotor adaptation, using error information to keep the sensorimotor system well-calibrated. Here we introduce a population-coding model to explain how cerebellar-dependent learning is modulated by contextual variation. The model consists of a two-layer network, designed to capture activity in both the cerebellar cortex and deep cerebellar nuclei. A core feature of the model is that within each layer, the processing units are tuned to both movement direction and the direction of movement error. The model captures a large range of contextual effects including interference from prior learning and the influence of error uncertainty and volatility. While these effects have traditionally been taken to indicate meta learning or context-dependent memory within the adaptation system, our results show that they are emergent properties that arise from the population dynamics within the cerebellum. Our results provide a novel framework to understand how the nervous system responds to variable environments.

Latent-state and model-based learning in PTSD

Post-traumatic stress disorder (PTSD) is characterized by altered emotional and behavioral responding following a traumatic event. In this article, we review the concepts of latent-state and model-based learning (i.e., learning and inferring abstract task representations) and discuss their relevance for clinical and neuroscience models of PTSD. Recent data demonstrate evidence for brain and behavioral biases in these learning processes in PTSD. These new data potentially recast excessive fear towards trauma cues as a problem in learning and updating abstract task representations, as opposed to traditional conceptualizations focused on stimulus-specific learning. Biases in latent-state and model-based learning may also be a common mechanism targeted in common therapies for PTSD. We highlight key knowledge gaps that need to be addressed to further elaborate how latent-state learning and its associated neurocircuitry mechanisms function in PTSD and how to optimize treatments to target these processes.

Quantifying motor adaptation in a sport-specific table tennis setting

Studies on motor adaptation aim to better understand the remarkable, largely implicit capacity of humans to adjust to changing environmental conditions. So far, this phenomenon has mainly been investigated in highly controlled laboratory setting, allowing only limited conclusions and consequences for everyday life scenarios. Natural movement tasks performed under externally valid conditions would provide important support on the transferability of recent laboratory findings. Therefore, one major goal of the current study was to create and assess a new table tennis paradigm mapping motor adaptation in a more natural and sport-specific setting. High-speed cinematographic measurements were used to determine target accuracy in a motor adaptation table tennis paradigm in 30 right-handed participants. In addition, we investigated if motor adaptation was affected by temporal order of perturbations (serial vs. random practice). In summary, we were able to confirm and reproduce typical motor adaptation effects in a sport-specific setting. We found, according to previous findings, an increase in target errors with perturbation onset that decreased during motor adaptation. Furthermore, we observed an increase in target errors with perturbation offset (after-effect) that decrease subsequently during washout phase. More importantly, this motor adaptation phenomenon did not differ when comparing serial vs. random perturbation conditions.

Application of "immersive contextualization based-learning teaching" mode in the orthopaedic musculoskeletal disorder module of clinical medicine education

OBJECTIVE

To evaluate the effect and influence of the "immersive contextualization-based learning" teaching mode (ICBLT) in the orthopaedic musculoskeletal disorder module of clinical medicine education.

METHODS

Undergraduate students in five consecutive semesters of clinical medicine in West China Hospital, Sichuan University were enrolled in this study. During the teaching process in each semester, a cross-over design was applied, and students were randomly divided into two classes (Class A and Class B) to receive the designated experimental courses with different routes. After they took the final exams, the scores of the selected chapters (sports injury chapter and osteoarthritis chapter) were extracted to conduct Tests of Between-Subjects Effects. Q-Q plot was drawn to test whether the distribution of the scores follows normal distribution. The part of the feedback questionnaires to assess these two teaching modes were also extracted for comparison.

RESULTS

A total of 441 students were enrolled in this study, among which, Class A teaching route was implemented to 222 students and Class B to the rest 219. The results of Tests of Between-Subjects Effects showed that ICBLT mode could lead to better scores compared to the Lecturing-based learning teaching (LBLT) mode (p < 0.0001). In terms of mastery of practical skills, help to deepen the memory of knowledge and satisfaction with the teaching mode, the ICBLT mode showed better results (p < 0.0001).

CONCLUSION

ICBLT mode had better potential in helping mastery of practical skills and deepening the memory of knowledge.

Continuous multiplexed population representations of task context in the mouse primary visual cortex

Effective task execution requires the representation of multiple task-related variables that determine how stimuli lead to correct responses. Even the primary visual cortex (V1) represents other task-related variables such as expectations, choice, and context. However, it is unclear how V1 can flexibly accommodate these variables without interfering with visual representations. We trained mice on a context-switching cross-modal decision task, where performance depends on inferring task context. We found that the context signal that emerged in V1 was behaviorally relevant as it strongly covaried with performance, independent from movement. Importantly, this signal was integrated into V1 representation by multiplexing visual and context signals into orthogonal subspaces. In addition, auditory and choice signals were also multiplexed as these signals were orthogonal to the context representation. Thus, multiplexing allows V1 to integrate visual inputs with other sensory modalities and cognitive variables to avoid interference with the visual representation while ensuring the maintenance of task-relevant variables.

Neural representations for multi-context visuomotor adaptation and the impact of common representation on multi-task performance: a multivariate decoding approach

The human brain's remarkable motor adaptability stems from the formation of context representations and the use of a common context representation (e.g., an invariant task structure across task contexts) derived from structural learning. However, direct evaluation of context representations and structural learning in sensorimotor tasks remains limited. This study aimed to rigorously distinguish neural representations of visual, movement, and context levels crucial for multi-context visuomotor adaptation and investigate the association between representation commonality across task contexts and adaptation performance using multivariate decoding analysis with fMRI data. Here, we focused on three distinct task contexts, two of which share a rotation structure (i.e., visuomotor rotation contexts with -90° and +90° rotations, in which the mouse cursor's movement was rotated 90 degrees counterclockwise and clockwise relative to the hand-movement direction, respectively) and the remaining one does not (i.e., mirror-reversal context where the horizontal movement of the computer mouse was inverted). This study found that visual representations (i.e., visual direction) were decoded in the occipital area, while movement representations (i.e., hand-movement direction) were decoded across various visuomotor-related regions. These findings are consistent with prior research and the widely recognized roles of those areas. Task-context representations (i.e., either -90° rotation, +90° rotation, or mirror-reversal) were also distinguishable in various brain regions. Notably, these regions largely overlapped with those encoding visual and movement representations. This overlap suggests a potential intricate dependency of encoding visual and movement directions on the context information. Moreover, we discovered that higher task performance is associated with task-context representation commonality, as evidenced by negative correlations between task performance and task-context-decoding accuracy in various brain regions, potentially supporting structural learning. Importantly, despite limited similarities between tasks (e.g., rotation and mirror-reversal contexts), such association was still observed, suggesting an efficient mechanism in the brain that extracts commonalities from different task contexts (such as visuomotor rotations or mirror-reversal) at multiple structural levels, from high-level abstractions to lower-level details. In summary, while illuminating the intricate interplay between visuomotor processing and context information, our study highlights the efficiency of learning mechanisms, thereby paving the way for future exploration of the brain's versatile motor ability.

Motor cortex is required for flexible but not automatic motor sequences

How motor cortex contributes to motor sequence execution is much debated, with studies supporting disparate views. Here we probe the degree to which motor cortex's engagement depends on task demands, specifically whether its role differs for highly practiced, or 'automatic', sequences versus flexible sequences informed by external events. To test this, we trained rats to generate three-element motor sequences either by overtraining them on a single sequence or by having them follow instructive visual cues. Lesioning motor cortex revealed that it is necessary for flexible cue-driven motor sequences but dispensable for single automatic behaviors trained in isolation. However, when an automatic motor sequence was practiced alongside the flexible task, it became motor cortex-dependent, suggesting that subcortical consolidation of an automatic motor sequence is delayed or prevented when the same sequence is produced also in a flexible context. A simple neural network model recapitulated these results and explained the underlying circuit mechanisms. Our results critically delineate the role of motor cortex in motor sequence execution, describing the condition under which it is engaged and the functions it fulfills, thus reconciling seemingly conflicting views about motor cortex's role in motor sequence generation.

The Computational and Neural Bases of Context-Dependent Learning

Flexible behavior requires the creation, updating, and expression of memories to depend on context. While the neural underpinnings of each of these processes have been intensively studied, recent advances in computational modeling revealed a key challenge in context-dependent learning that had been largely ignored previously: Under naturalistic conditions, context is typically uncertain, necessitating contextual inference. We review a theoretical approach to formalizing context-dependent learning in the face of contextual uncertainty and the core computations it requires. We show how this approach begins to organize a large body of disparate experimental observations, from multiple levels of brain organization (including circuits, systems, and behavior) and multiple brain regions (most prominently the prefrontal cortex, the hippocampus, and motor cortices), into a coherent framework. We argue that contextual inference may also be key to understanding continual learning in the brain. This theory-driven perspective places contextual inference as a core component of learning.

Transdiagnostic computations of uncertainty: towards a new lens on intolerance of uncertainty

People radically differ in how they cope with uncertainty. Clinical researchers describe a dispositional characteristic known as "intolerance of uncertainty", a tendency to find uncertainty aversive, reported to be elevated across psychiatric and neurodevelopmental conditions. Concurrently, recent research in computational psychiatry has leveraged theoretical work to characterise individual differences in uncertainty processing. Under this framework, differences in how people estimate different forms of uncertainty can contribute to mental health difficulties. In this review, we briefly outline the concept of intolerance of uncertainty within its clinical context, and we argue that the mechanisms underlying this construct may be further elucidated through modelling how individuals make inferences about uncertainty. We will review the evidence linking psychopathology to different computationally specified forms of uncertainty and consider how these findings might suggest distinct mechanistic routes towards intolerance of uncertainty. We also discuss the implications of this computational approach for behavioural and pharmacological interventions, as well as the importance of different cognitive domains and subjective experiences in studying uncertainty processing.

A new understanding of the cognitive reappraisal technique: an extension based on the schema theory

Cognitive reappraisal is a widely utilized emotion regulation strategy that involves altering the personal meaning of an emotional event to enhance attention to emotional responses. Despite its common use, individual differences in cognitive reappraisal techniques and the spontaneous recovery, renewal, and reinstatement of negative responses across varying contexts may limit its effectiveness. Furthermore, detached reappraisal could cause distress for clients. According to Gross's theory, cognitive reappraisal is an effortless process that can occur spontaneously. When guided language triggers cognitive reappraisal as an emotion regulation strategy in laboratory or counseling settings, clients experience improved emotional states, but this induced strategy may not necessarily guide them in regulating emotions in similar future situations. Therefore, effectively applying cognitive reappraisal techniques in clinical practice to help clients alleviate emotional distress in daily life remains a significant concern. Exploring the mechanism of cognitive reappraisal reveals that reconstructing stimulus meaning is akin to extinction learning, which entails fostering cognitive contingency that the original stimulus provoking negative emotions will no longer result in negative outcomes in the current context. However, extinction learning is a new learning process rather than an elimination process. The activation of new learning relies on the presentation of critical cues, with contextual cues often playing a vital role, such as a safe laboratory or consulting room environment. We propose a new understanding of cognitive reappraisal based on the schema theory and the dual-system theory, emphasizing the significance of environmental interaction and feedback in constructing new experiences and updating schemata. This approach ultimately enriches the schema during training and integrates the new schema into long-term memory. Bottom-up behavioral experiences as schema enrichment training provide the foundation for top-down regulation to function. This method can assist clients in activating more suitable schemata probabilistically when encountering stimuli in real life, forming stable emotions, and achieving transfer and application across diverse contexts.