Continuous manipulation of mental representations is compromised in cerebellar degeneration

Multisensory approach in Mental Imagery: ALE meta-analyses comparing Motor, Visual and Auditory Imagery

Mental Imagery is a topic of longstanding and widespread scientific interest. Individual studies have typically focused on a single modality (e.g. Motor, Visual, Auditory) of Mental Imagery. Relatively little work has considered directly comparing and contrasting the brain networks associated with these different modalities of Imagery. The present study integrates data from 439 neuroimaging experiments to identify both modality-specific and shared neural networks involved in Mental Imagery. Comparing the networks involved in Motor, Visual, and Auditory Imagery identified a pattern whereby each form of Imagery preferentially recruited 'higher level' associative brain regions involved in the associated 'real' experience. Results also indicate significant overlap in a left-lateralized network including the pre-supplementary motor area, ventral premotor cortex and inferior parietal lobule. This pattern of results supports the existence of a 'core' network that supports the attentional, spatial, and decision-making demands of Mental Imagery. Together these results offer new insights into the brain networks underlying human imagination.

The relational bottleneck as an inductive bias for efficient abstraction

A central challenge for cognitive science is to explain how abstract concepts are acquired from limited experience. This has often been framed in terms of a dichotomy between connectionist and symbolic cognitive models. Here, we highlight a recently emerging line of work that suggests a novel reconciliation of these approaches, by exploiting an inductive bias that we term the relational bottleneck. In that approach, neural networks are constrained via their architecture to focus on relations between perceptual inputs, rather than the attributes of individual inputs. We review a family of models that employ this approach to induce abstractions in a data-efficient manner, emphasizing their potential as candidate models for the acquisition of abstract concepts in the human mind and brain.

No Evidence for Semantic Prediction Deficits in Individuals With Cerebellar Degeneration

Cerebellar involvement in language processing has received considerable attention in the neuroimaging and neuropsychology literatures. Building off the motor control literature, one account of this involvement centers on the idea of internal models. In the context of language, this hypothesis suggests that the cerebellum is essential for building semantic models that, in concert with the cerebral cortex, help anticipate or predict linguistic input. To date, supportive evidence has primarily come from neuroimaging studies showing that cerebellar activation increases in contexts in which semantic predictions are generated and violated. Taking a neuropsychological approach, we put the internal model hypothesis to the test, asking if individuals with cerebellar degeneration (n = 14) show reduced sensitivity to semantic prediction. Using a sentence verification task, we compare reaction time to sentences that vary in terms of cloze probability. We also evaluated a more constrained variant of the prediction hypothesis, asking if the cerebellum facilitates the generation of semantic predictions when the content of a sentence refers to a dynamic rather than static mental transformation. The results failed to support either hypothesis: Compared to matched control participants (n = 17), individuals with cerebellar degeneration showed a similar reduction in reaction time for sentences with high cloze probability and no selective impairment in predictions involving dynamic transformations. These results challenge current theorizing about the role of the cerebellum in language processing, pointing to a misalignment between neuroimaging and neuropsychology research on this topic.

The Role of the Cerebellum in Learning to Predict Reward: Evidence from Cerebellar Ataxia

Recent findings in animals have challenged the traditional view of the cerebellum solely as the site of motor control, suggesting that the cerebellum may also be important for learning to predict reward from trial-and-error feedback. Yet, evidence for the role of the cerebellum in reward learning in humans is lacking. Moreover, open questions remain about which specific aspects of reward learning the cerebellum may contribute to. Here we address this gap through an investigation of multiple forms of reward learning in individuals with cerebellum dysfunction, represented by cerebellar ataxia cases. Nineteen participants with cerebellar ataxia and 57 age- and sex-matched healthy controls completed two separate tasks that required learning about reward contingencies from trial-and-error. To probe the selectivity of reward learning processes, the tasks differed in their underlying structure: while one task measured incremental reward learning ability alone, the other allowed participants to use an alternative learning strategy based on episodic memory alongside incremental reward learning. We found that individuals with cerebellar ataxia were profoundly impaired at reward learning from trial-and-error feedback on both tasks, but retained the ability to learn to predict reward based on episodic memory. These findings provide evidence from humans for a specific and necessary role for the cerebellum in incremental learning of reward associations based on reinforcement. More broadly, the findings suggest that alongside its role in motor learning, the cerebellum likely operates in concert with the basal ganglia to support reinforcement learning from reward.

Fundamental processes in sensorimotor learning: Reasoning, refinement, and retrieval

Motor learning is often viewed as a unitary process that operates outside of conscious awareness. This perspective has led to the development of sophisticated models designed to elucidate the mechanisms of implicit sensorimotor learning. In this review, we argue for a broader perspective, emphasizing the contribution of explicit strategies to sensorimotor learning tasks. Furthermore, we propose a theoretical framework for motor learning that consists of three fundamental processes: reasoning, the process of understanding action-outcome relationships; refinement, the process of optimizing sensorimotor and cognitive parameters to achieve motor goals; and retrieval, the process of inferring the context and recalling a control policy. We anticipate that this '3R' framework for understanding how complex movements are learned will open exciting avenues for future research at the intersection between cognition and action.

Working memory constraints for visuomotor retrieval strategies

Recent work has shown the fundamental role that cognitive strategies play in visuomotor adaptation. Although algorithmic strategies, such as mental rotation, are flexible and generalizable, they are computationally demanding. To avoid this computational cost, people can instead rely on memory retrieval of previously successful visuomotor solutions. However, such a strategy is likely subject to stimulus-response associations and rely heavily on working memory. In a series of five experiments, we sought to estimate the constraints in terms of capacity and precision of working memory retrieval for visuomotor adaptation. This was accomplished by leveraging different variations of visuomotor item-recognition and visuomotor rotation tasks where we associated unique rotations with specific targets in the workspace and manipulated the set size (i.e., number of rotation-target associations). Notably, from experiment 1 to 4, we found key signatures of working memory retrieval and not mental rotation. In particular, participants were less accurate and slower for larger set sizes and less recent items. Using a Bayesian latent-mixture model, we found that such decrease in performance was the result of increasing guessing behavior and less precise memories. In addition, we estimated that participants' working memory capacity was limited to two to five items, after which guessing increasingly dominated performance. Finally, in experiment 5, we showed how the constraints observed across experiments 1 to 4 can be overcome when relying on long-term memory retrieval. Our results point to the opportunity of studying other sources of memories where visuomotor solutions can be stored (e.g., episodic memories) to achieve successful adaptation.NEW & NOTEWORTHY We show that humans can adapt to feedback perturbations in different variations of the visuomotor rotation task by retrieving the successful solutions from working memory. In addition, using a Bayesian latent-mixture model, we reveal that guessing and low-precision memories are both responsible for the decrease in participants' performance as the number of solutions to memorize increases. These constraints can be overcome by relying on long-term memory retrieval resulting from extended practice with the visuomotor solutions.

Selective recruitment of the cerebellum evidenced by task-dependent gating of inputs

Functional magnetic resonance imaging (fMRI) studies have documented cerebellar activity across a wide array of tasks. However, the functional contribution of the cerebellum within these task domains remains unclear because cerebellar activity is often studied in isolation. This is problematic, as cerebellar fMRI activity may simply reflect the transmission of neocortical activity through fixed connections. Here, we present a new approach that addresses this problem. Rather than focus on task-dependent activity changes in the cerebellum alone, we ask if neocortical inputs to the cerebellum are gated in a task-dependent manner. We hypothesize that input is upregulated when the cerebellum functionally contributes to a task. We first validated this approach using a finger movement task, where the integrity of the cerebellum has been shown to be essential for the coordination of rapid alternating movements but not for force generation. While both neocortical and cerebellar activity increased with increasing speed and force, the speed-related changes in the cerebellum were larger than predicted by an optimized cortico-cerebellar connectivity model. We then applied the same approach in a cognitive domain, assessing how the cerebellum supports working memory. Enhanced gating was associated with the encoding of items in working memory, but not with the manipulation or retrieval of the items. Focusing on task-dependent gating of neocortical inputs to the cerebellum offers a promising approach for using fMRI to understand the specific contributions of the cerebellum to cognitive function.

Emergence of syntax and word prediction in an artificial neural circuit of the cerebellum

The cerebellum, interconnected with the cerebral neocortex, plays a vital role in human-characteristic cognition such as language processing, however, knowledge about the underlying circuit computation of the cerebellum remains very limited. To gain a better understanding of the computation underlying cerebellar language processing, we developed a biologically constrained cerebellar artificial neural network (cANN) model, which implements the recently identified cerebello-cerebellar recurrent pathway. We found that while cANN acquires prediction of future words, another function of syntactic recognition emerges in the middle layer of the prediction circuit. The recurrent pathway of the cANN was essential for the two language functions, whereas cANN variants with further biological constraints preserved these functions. Considering the uniform structure of cerebellar circuitry across all functional domains, the single-circuit computation, which is the common basis of the two language functions, can be generalized to fundamental cerebellar functions of prediction and grammar-like rule extraction from sequences, that underpin a wide range of cerebellar motor and cognitive functions. This is a pioneering study to understand the circuit computation of human-characteristic cognition using biologically-constrained ANNs.

Distinct Contributions of the Cerebellum and Basal Ganglia to Arithmetic Procedures

Humans exhibit complex mathematical skills attributed to the exceptional enlargement of neocortical regions throughout evolution. In the current work, we initiated a novel exploration of the ancient subcortical neural network essential for mathematical cognition. Using a neuropsychological approach, we report that degeneration of two subcortical structures, the cerebellum and basal ganglia, impairs performance in symbolic arithmetic. We identify distinct computational impairments in male and female participants with cerebellar degeneration (CD) or Parkinson's disease (PD). The CD group exhibited a disproportionate cost when the arithmetic sum increased, suggesting that the cerebellum is critical for iterative procedures required for calculations. The PD group showed a disproportionate cost for equations with increasing addends, suggesting that the basal ganglia are critical for chaining multiple operations. In Experiment 2, the two patient groups exhibited intact practice gains for repeated equations at odds with an alternative hypothesis that these impairments were related to memory retrieval. Notably, we discuss how the counting and chaining operations relate to cerebellar and basal ganglia function in other task domains (e.g., motor processes). Overall, we provide a novel perspective on how the cerebellum and basal ganglia contribute to symbolic arithmetic. Our studies demonstrate the constraints on the computational role of two subcortical regions in higher cognition.

Cerebellar Degeneration Impairs Strategy Discovery but Not Strategy Recall

The cerebellum is recognized to play a critical role in the automatic and implicit process by which movement errors are used to keep the sensorimotor system precisely calibrated. However, its role in other learning processes frequently engaged during sensorimotor adaptation tasks remains unclear. In the present study, we tested the performance of individuals with cerebellar degeneration on a variant of a visuomotor adaptation task in which learning requires the use of strategic re-aiming, a process that can nullify movement errors in a rapid and volitional manner. Our design allowed us to assess two components of this learning process, the discovery of an appropriate strategy and the recall of a learned strategy. Participants were exposed to a 60° visuomotor rotation twice, with the initial exposure block assessing strategy discovery and the re-exposure block assessing strategy recall. Compared to age-matched controls, individuals with cerebellar degeneration were slower to derive an appropriate aiming strategy in the initial Discovery block but exhibited similar recall of the aiming strategy during the Recall block. This dissociation underscores the multi-faceted contributions of the cerebellum to sensorimotor learning, highlighting one way in which this subcortical structure facilitates volitional action selection.

The development of simple addition problem solving in children: Reliance on automatized counting or memory retrieval depends on both expertise and problem size

In an experiment, 98 children aged 8 to 9, 10 to 12, and 13 to 15 years solved addition problems with a sum up to 10. In another experiment, the same children solved the same calculations within a sign priming paradigm where half the additions were displayed with the "+" sign 150 ms before the addends. Therefore, size effects and priming effects could be considered conjointly within the same populations. Our analyses revealed that small problems, constructed with addends from 1 to 4, presented a linear increase of solution times as a function of problem sums (i.e., size effect) in all age groups. However, an operator priming effect (i.e., facilitation of the solving process with the anticipated presentation of the "+" sign) was observed only in the group of oldest children. These results support the idea that children use a counting procedure that becomes automatized (as revealed by the priming effect) around 13 years of age. For larger problems and whatever the age group, no size or priming effects were observed, suggesting that the answers to these problems were already retrieved from memory at 8 to 9 years of age. For this specific category of large problems, negative slopes in solution times demonstrate that retrieval starts from the largest problems during development. These results are discussed in light of a horse race model in which procedures can win over retrieval.

Neurocognitive and cerebellar function in ADHD, autism and spinocerebellar ataxia

The cerebellum plays a major role in balance, motor control and sensorimotor integration, but also in cognition, language, and emotional regulation. Several neuropsychiatric disorders such as attention deficit-hyperactivity disorder (ADHD), autism spectrum disorder (ASD), as well as neurological diseases such as spinocerebellar ataxia type 3 (SCA3) are associated with differences in cerebellar function. Morphological abnormalities in different cerebellar subregions produce distinct behavioral symptoms related to the functional disruption of specific cerebro-cerebellar circuits. The specific contribution of the cerebellum to typical development may therefore involve the optimization of the structure and function of cerebro-cerebellar circuits underlying skill acquisition in multiple domains. Here, we review cerebellar structural and functional differences between healthy and patients with ADHD, ASD, and SCA3, and explore how disruption of cerebellar networks affects the neurocognitive functions in these conditions. We discuss how cerebellar computations contribute to performance on cognitive and motor tasks and how cerebellar signals are interfaced with signals from other brain regions during normal and dysfunctional behavior. We conclude that the cerebellum plays a role in many cognitive functions. Still, more clinical studies with the support of neuroimaging are needed to clarify the cerebellum's role in normal and dysfunctional behavior and cognitive functioning.

Effects of working memory load and CS-US intervals on delay eyeblink conditioning

Eyeblink conditioning is used in many species to study motor learning and make inferences about cerebellar function. However, the discrepancies in performance between humans and other species combined with evidence that volition and awareness can modulate learning suggest that eyeblink conditioning is not merely a passive form of learning that relies on only the cerebellum. Here we explored two ways to reduce the influence of volition and awareness on eyeblink conditioning: (1) using a short interstimulus interval, and (2) having participants do working memory tasks during the conditioning. Our results show that participants trained with short interstimulus intervals (150 ms and 250 ms) produce very few conditioned responses after 100 trials. Participants trained with a longer interstimulus interval (500 ms) who simultaneously did working memory tasks produced fewer conditioned responses than participants who watched a movie during the training. Our results suggest that having participants perform working memory tasks during eyeblink conditioning can be a viable strategy for studying cerebellar learning that is absent of influences from awareness and volition. This could enhance the comparability of the results obtained in human studies with those in animal models.

Inhibition, Shifting and Updating: Inter and intra-domain commonalities and differences from an executive functions activation likelihood estimation meta-analysis

Executive functions are higher-order mental processes that support goal-directed behavior. Among these processes, Inhibition, Updating, and Shifting have been considered core executive domains. In this meta-analysis, we comprehensively investigate the neural networks of these executive domains and we synthesize for the first time the neural convergences and divergences among the most frequently used executive paradigms within those domains. A systematic search yielded 1055 published neuroimaging studies (including 26,191 participants in total). Our study revealed that a fronto-parietal network was shared by the three main domains. Furthermore, we executed conjunction analyses among the paradigms of the same domain to extract the core distinctive components of the main executive domains. This approach showed that Inhibition and Shifting are characterized by a strongly lateralized neural activation in the right and left hemisphere, respectively. In addition, both networks overlapped with the Updating network but not with each other. Remarkably, our study detected heterogeneity among the paradigms from the same domain. More specifically, analysis of Inhibition tasks revealed differing activations for Response Inhibition compared to Interference Control paradigms, suggesting that Inhibition encompasses relatively heterogeneous sub-functions. Shifting analyses revealed a bilateral overlap of the Wisconsin Card Sorting Task with the Updating network, but this pattern was absent for Rule Switching and Dual Task paradigms. Moreover, our Updating meta-analyses revealed the neural signatures associated with the specific modules of the Working Memory model from Baddeley and Hitch. To our knowledge, this is the most comprehensive meta-analysis of executive functions to date. Its paradigm-driven analyses provide a unique contribution to a better understanding of the neural convergences and divergences among executive processes that are relevant for clinical applications, such as cognitive enhancement and neurorehabilitation interventions.

Mental arithmetic modulates temporal variabilities of finger-tapping tasks in a tempo-dependent manner

Background

Several psychiatric diseases impair temporal processing. Temporal processing is thought to be based on two domains: supra-second intervals and sub-second intervals. Studies show that temporal processing in sub-second intervals is mainly an automated process. However, the brain functions involved in temporal processing at each time scale remain unclear. We hypothesized that temporal processing in supra-second intervals requires several brain areas, such as the ventrolateral prefrontal cortex, intraparietal sulcus (IPS), and inferior parietal lobe, corresponding to various cognitions in a time scale-dependent manner. We focused on a dual-task paradigm (DTP) involving simultaneous performance of cognitive and motor tasks, which is an effective method for screening psychomotor functions; we then designed a DTP comprising finger tapping at various tempi as the temporal processing task and two cognitive tasks (mental arithmetic and reading) that might affect temporal processing. We hoped to determine whether task-dependent interferences on temporal processing in supra-second intervals differed depending on the cognitive tasks involved.

Methods

The study included 30 participants with no history of neuromuscular disorders. Participants were asked to perform a DTP involving right index finger tapping at varying tempi (0.33, 0.5, 1, 2, 3, and 4 s inter-tapping intervals). Cognitive tasks comprised mental arithmetic (MA) involving three-digit addition, mental reading (MR) of three- to four-digit numbers, and a control (CTL) task without any cognitive loading. For comparison between tasks, we calculated the SDs of the inter-tapping intervals. Participants' MA abilities in the three-digit addition task were evaluated.

Results

The MA and MR tasks significantly increased the SDs of the inter-tapping intervals compared to those of the CTL task in 2-3 s and 3-4 s for the MA and MR tasks, respectively. Furthermore, SD peaks in the finger-tapping tasks involving MA were normalized by those in the CTL task, which were moderately correlated with the participants' MA ability (r = 0.462, P = 0.010).

Discussion

Our results established that DTP involving the temporal coordination of finger-tapping and cognitive tasks increased temporal variability in a task- and tempo-dependent manner. Based on the behavioral aspects, we believe that these modulations of temporal variability might result from the interaction between finger function, arithmetic processing, and temporal processing, especially during the "pre-semantic period". Our findings may help in understanding the temporal processing deficits in various disorders such as dementia, Parkinson's disease, and autism.