High cognitive violation of expectations is compromised in cerebellar ataxia

Traditionally, the cerebellum has been primarily recognized as a motor structure. However, evidence indicates its involvement in various cognitive processes (Strick et al., 2009; Saban et al., 2024; Middleton and Strick, 2000; Guell et al., 2018; Ravizza et al., 2006; Hull, 2020). Yet, the underlying cognitive mechanisms through which the cerebellum contributes to higher cognitive abilities remain unknown. In addition, since the anatomy of the cerebellum is relatively uniform throughout its structure, it was suggested that its function may be consistent (Guell et al., 2018; Stoodley et al., 2012) (i.e. ‘universal cerebellar transform’). This led to the hypothesis that a cerebellar lesion will result in a core ubiquitous impairment across domains (Guell et al., 2018; Stoodley et al., 2012; Stoodley, 2012; Schmahmann, 2004). Despite these theoretical proposals, direct evidence for the cerebellum’s contribution to a core unifying mechanism across non-motor domains is lacking.

A substantial body of neuropsychological, modeling, and imaging evidence supports the notion that the cerebellum is involved in motor control (Hull, 2020; Stoodley et al., 2012; Heffley et al., 2018; Debas et al., 2010; Imamizu et al., 2000; Ito, 2008; Wolpert and Miall, 1996). According to the forward model framework (Ito, 2008; Wolpert and Miall, 1996), the cerebellum encodes a predictive model (Wolpert et al., 1998) (i.e. ‘internal model’). Specifically, the cerebellum is involved in prediction error (Wolpert et al., 1998), such that processing of the deviation between the predicted and the perceived information (i.e. error signal) leads to an internal model. Research shows that individuals with cerebellar pathology exhibit impairments in a range of sensorimotor tasks (Saban and Ivry, 2021a; Taylor et al., 2014). For example, in visuomotor rotation tasks, people with CA exhibit a reduced ability to process experimental perturbations, where the participant’s predicted outcome is different from the perceived stimuli. This is consistent with the idea (Hull, 2020; Fiez et al., 1992; Moberget et al., 2014; Sokolov et al., 2017) that an intact cerebellum is required to process VE. However, it is not fully understood how the concept of VE should be applied in cognitive domains (Ito, 2008; McDougle et al., 2022).

The cerebellum is involved in many cognitive abilities, such as sequence learning, executive function, and even math and language processes (Strick et al., 2009; Saban et al., 2024; Ravizza et al., 2006; Schmahmann, 2004; Sokolov et al., 2017; Lesage et al., 2016; Lesage et al., 2017; Saban and Gabay, 2023; Caligiore et al., 2017; Bostan and Strick, 2018; Barth et al., 2010; Nicolson et al., 2010). This is evidenced by cognitive deficits in individuals with cerebellar pathology (Saban et al., 2024; Saban and Ivry, 2021a; McDougle et al., 2022), bidirectional connectivity with the neocortex (Caligiore et al., 2017; Bostan and Strick, 2018; Watson et al., 2014), developmental studies (Riva and Giorgi, 2000), and neuroimaging studies showing cerebellar activation in cognitive tasks (Stoodley et al., 2012; Lesage et al., 2016; Walz et al., 2015). While existing studies support a cerebellar role in nonmotor functions (Strick et al., 2009; Ravizza et al., 2006; Fiez et al., 1992; Riva and Giorgi, 2000; Schmahmann, 2019; Buckner, 2013; Nicholas et al., 2024), direct evidence and stronger theoretical constraints on the region’s specific function in higher cognition are needed (Saban and Gabay, 2023). In addition, despite the broad evidence in many cognitive domains, how this structure contributes to a fundamental, unifying cognitive mechanism remains an open question (Stoodley, 2012; Guell et al., 2017).

Furthermore, we observed that imaging and neuropsychological literature do not always converge, with the latter mainly showing mixed results. For instance, one language paradigm that activates the cerebellum is semantic processing, focusing on right cerebellar activation (Stoodley, 2012; Moberget et al., 2014; Lesage et al., 2017; Fiez et al., 1996; Murdoch, 2010). However, while some studies did not find that patients with cerebellar pathology have impairments in semantic processing tasks (Gasparini et al., 1999; Riva, 1998; King et al., 2024), others found significant impairment (Moberget et al., 2014), specifically related to the processing of errors (Fiez et al., 1992) or sequential processing (Riva, 1998). Another example is working memory. The neuroimaging literature demonstrated the association of cerebellar activity with working memory tasks (Stoodley et al., 2012; E et al., 2014). However, again, the results are not consistent in the neuropsychology literature. While some studies report impairments in individuals with cerebellar pathology on working memory tasks (Ziemus et al., 2007), others report null effects (McDougle et al., 2022; Appollonio et al., 1993). These mixed results may reflect the heterogeneity in the cerebellar patient samples, or it may be that the chosen cognitive tasks are not consistently sensitive to cerebellar pathology. To address these two challenges, we proposed to examine a homogenous sample of individuals with a single type of spinocerebellar ataxia (SCA6). Additionally, we suggested utilizing tasks designed to be more reliably sensitive in capturing the specific cognitive impairments associated with cerebellar dysfunction.

Additionally, in the motor domain, models of cerebellar function emphasize the importance of this structure in VE (Miall et al., 2007; Wolpert and Flanagan, 2001). Expectations, which are based on top-down knowledge, are compared with visual feedback, with the difference between the two serving as an error signal (Wolpert et al., 1998). However, given that violation of expectations is a general feature of brain function (Friston, 2018), a key challenge is to specify constraints on the cerebellum’s specific role. When we examined previously used tasks, we noticed that many of them required procedure-based sequential processing (Strick et al., 2009; Saban et al., 2024; Fiez et al., 1992; Moberget et al., 2014; Riva, 1998; Elyoseph et al., 2020; Morgan et al., 2021; Pascual-Leone et al., 1993; Molinari et al., 1997; Heleven et al., 2021). People with CA show selective impairments in procedure-based tasks (Saban et al., 2024; Saban and Ivry, 2021a; Elyoseph et al., 2020; Heleven et al., 2021; Knowlton et al., 2017; Knowlton et al., 2016; Adamaszek and Kirkby, 2016), requiring an algorithm of a sequence of discrete steps to solve (Saban and Ivry, 2021a; Riva, 1998; Elyoseph et al., 2020; Morgan et al., 2021).

Herein, we proposed investigating the cognitive mechanisms by which the cerebellum contributes to tasks requiring sequential processing. Although defining the distinct cerebellum’s role in cognition is challenging (Saban and Gabay, 2023; Parvizi, 2009), we anticipate that a successful theory will likely build on its well-established role in motor control (Hull, 2020; Ito, 2008; Wolpert and Miall, 1996; Wolpert et al., 1998; Lesage et al., 2017). Our logic is straightforward. VE is involved in almost every human function, from basic ones, such as motor control, to more complex ones, such as language and math. Evidence suggests that the cerebellum contributes to motor and cognitive tasks through the processing of VE (Hull, 2020; Fiez et al., 1992; Elyoseph et al., 2020; Morgan et al., 2021; Molinari et al., 1997; Saywell and Taylor, 2008). Motivated by the biological and evolutionary principle of neural reuse (Rozin, 1976; Anderson, 2010), we propose and test the hypothesis that the cerebellum also contributes to higher cognition through cognitive VE.

Evolutionarily novel cognitive abilities, such as arithmetic and language, also rely on the processing of VE (Fiez et al., 1992; Moberget et al., 2014; Lesage et al., 2017; Berger et al., 2006; Argyropoulos, 2016). For instance, based on known rules, a person predicts the correct answer to an equation, the next word in a sentence, or the next letter in a word. The expectations in these sequential processes are sometimes accurate and sometimes not. We suggest that through a VE mechanism, the cerebellum contributes not only to motor abilities but also to the cognitive procedures necessary for solving symbolic arithmetic and alphabet transformation problems (Saban et al., 2024; Fiez et al., 1992; Lesage et al., 2017).

Notably, these higher cognitive sequential problems are probably not solved by one continuous mental computation, and multi-step discrete computations are needed (Dietrich and Markman, 2003; Logan and Klapp, 1991; Ashcraft, 1992; Verhaeghen et al., 1997). It is more likely that mental arithmetic and alphabet transformation problems are solved using discrete mental procedures by breaking down these complex cognitive computations into smaller steps (Dietrich and Markman, 2003; Verhaeghen et al., 1997; Cohen-Kadosh and Dowker, 2015; LeFevre et al., 1996; DeStefano and LeFevre, 2004; Grabner and De Smedt, 2011; Taatgen, 2013; Fias et al., 2021; Tiberghien et al., 2019). For instance, when solving a simple subtraction problem (e.g. 9–5=3), a person typically follows a series of mental steps. For instance, first, they represent the stimuli mentally, understanding the need to subtract 5 from 9. They then retrieve relevant arithmetic facts from long-term memory or apply subtraction rules (Cohen-Kadosh and Dowker, 2015; Grabner et al., 2009). After arriving at a potential answer, they compare their expected computation (e.g. 4) with the actual visual information presented on the screen (e.g. 3). This algorithmic procedure highlights how sequential cognitive steps are used to solve even a simple arithmetic problem and how VE is a process needed for higher cognition as well.

Interestingly, in a sequential task requiring a series of discrete steps to solve, expectations are formed within each trial rather than between trials. During the operation of these mental steps, participants develop a prediction model (i.e. ‘internal model’), predicting the correct outcome. When an incorrect answer is presented, it leads to a violation of the participant’s expectation within that specific trial. This process allows for the investigation of VE within the context of a single trial, providing valuable insights into the underlying cognitive mechanism for each problem. Taken together, rather than being restricted to continuous transformations as suggested before (McDougle et al., 2022), we propose that the cerebellum is necessary for solving sequential higher cognitive problems via VE.

In three experiments, patients with CA and neurotypical (NT) healthy participants solved symbolic arithmetic, alphabet transformation, and grammar sequential problems. These sequential problems required a series of discrete steps to be completed in a specific order to reach a solution. In Experiment 1, the CA group demonstrated impairment in a subtraction task, providing novel evidence of the cerebellum’s contribution to symbolic arithmetic reasoning. In addition, we found a selective impairment of the CA group compared to the NT group. The CA group exhibited a disproportionate expectancy effect only (no difference in the complexity effect). Consistent with Experiment 1, in Experiment 2, using the alphabet transformation task, we found a distinct disproportionate expectancy effect (no difference in the complexity effect). Transforming alphabetic letters by an arithmetic operator is a less commonly used cognitive operation than subtracting digits. This allowed us to reduce the potential effects of top-down processes and show that CA’s impairment also appears when there are fewer top-down effects. Rather, this probably increased the need to develop algorithmic procedures during the task.

In Experiments 1 and 2, participants identified if a given problem was correct or not based on their previous knowledge; however, in Experiment 3, we probed novel cognitive VE under uncertainty. We formed a new scenario where prior lifetime knowledge is absent, and participants are required to learn a new grammatical rule within the task. The participants' expectations were novel and were not based on previous top-down processes. Utilizing an AGL task Pothos, 2007, participants needed to learn a new Markovian grammar, regarding how to organize a sequence of letters in a specific order. To assess the effect of the participant’s uncertainty, we manipulated the level of similarity between grammatical and nongrammatical problems. We found that the CA group showed selective impairment only in the low similarity condition (higher sensitivity), probably where expectations are higher. Although it was not a causal finding and no behavioral evidence was found, an fMRI study (Lesage et al., 2017Lesage et al., 2017) revealed that activity in the right posterolateral cerebellum correlated with the predictability of the upcoming target word. Together with our current findings and others (Fiez et al., 1992; Moberget et al., 2014), this pattern of results might indicate that the cerebellum is necessary for higher cognition through a VE mechanism.

Across the three experiments, we examined the effect of VE in both established and newly learned cognitive procedures, considering varying levels of potential top-down effects. The CA group showed a disproportionate expectancy effect compared to the NT group. We found that the between-group differences in the expectancy effect are consistent across tasks. Notably, the results indicate that CA patients had both intact processing of the problems’ complexity (i.e. number of steps) and intact ability to discriminate between correct and incorrect problems when certainty decreased (i.e. sensitivity was lower). Thus, the results indicate a distinct role of the cerebellum in processing VE across these sequential cognitive tasks.

Several theories are in line with the principle of neural reuse and our hypothesis that the cerebellum contributes to many domains using the same core cognitive mechanism (Saban and Gabay, 2023). Rozin, 1976 proposed that computations that initially evolved to solve specific problems become accessible to other systems through evolution, as well as within the individual lifetime of an organism. Change or expansion of a function, because it is more generally available or accessible, ‘would have adaptive value when an area of behavioral function could profit from programs initially developed for another purpose.’ This idea has been reframed and elaborated upon in Gallese’s ‘neural exploitation’ hypothesis (Gallese and Cuccio, 2018) and Anderson’s ‘massive redeployment’ hypothesis (Anderson, 2010; Anderson, 2007). The core idea is that neural networks can acquire new uses after establishing an initial function. Decades of empirical research from human and animal experiments, including our own, support this framework (Hull, 2020; Saban and Gabay, 2023; Saban et al., 2021b; Balsters et al., 2013). The broad involvement of the cerebellum in motor and nonmotor functions supports the idea of neural reuse, indicating this specific structure’s potential ability to reuse its core function.

A few hypotheses have been proposed based on the idea that cerebellar contributions to motor control may extend to the cognitive domain (Ito, 2008; Fiez et al., 1992; McDougle et al., 2022). For example, in one recent paper (McDougle et al., 2022) it was hypothesized that the cerebellum supports dynamic continuous transformations of mental representations. However, the concrete implementation of 'continuity' in terms of higher mental representations remains an open question (Dietrich and Markman, 2003). Currently, there is no established direct evidence supporting the existence of such ‘continuous’ and ‘dynamic’ higher cognitive processes. Indeed, a recent later study by the same authors found no support for this hypothesis within the language domain (i.e. semantic processing task) (King et al., 2024). It is unclear whether the utilized problems, such as simple addition or mental rotation, are entirely solved using ‘continuous transformation’ or through previously learned procedural knowledge of the required mental steps. The constraints on the cerebellum’s role remain an open question, particularly whether its role is limited solely to tasks requiring ‘continuous mental transformation,’ as previously suggested (McDougle et al., 2022). Therefore, more consistent and well-established cerebellar parsimonious theories are still needed.

One might be concerned that if the cerebellum is involved in sequential operations, its involvement in mental letter rotation, which can be assumed as ‘continuous transformation,’ may appear contradictory. We note that the boundary between continuous and stepwise, procedural operations is not always clear-cut and may vary depending on the participant’s strategy and previous knowledge, which is not always fully known to the researchers. But this is a debatable consideration. More importantly, a careful reading of our paper suggests that our experiments were designed to examine VE within tasks that involve sequential processing. Notably, we are not claiming that the cerebellum is involved in sequential processing per se. Rather, our findings point to a more specific role for the cerebellum in processing VE that arises during the construction of multi-step procedural tasks. In fact, the results indicate that while the cerebellum may not be directly involved in the procedural process itself, it is critical when expectations are violated within such a context. This distinction is made possible in our study by the inclusion of a control condition (the complexity effect), which allows for a unique dissociation in our experimental design—one that, to our knowledge, has not been sufficiently addressed in previous studies (McDougle et al., 2022).

Additionally, in the case of arithmetic problem solving—such as the tasks used in prior studies (McDougle et al., 2022)—there is substantial evidence that these problems are typically solved through stepwise, procedural operations. Arithmetic reasoning, used in our Experiments 1 and 2, has been robustly associated with procedural, multi-step strategies, which may be more clearly aligned with traditional views of cerebellar involvement in sequential operations. Thus, we propose that the role of the cerebellum in continuous transformations should be further examined.

We suggest a more parsimonious theory – the cerebellum contributes to VE, a field that was highly examined before. Yet, to reconcile these findings, we propose that the cerebellum’s contribution may not be limited to either continuous or stepwise, procedural operations per se, but rather to a domain-general process: the processing of VE. This theoretical framework can explain performance patterns across mental rotation tasks, grammar learning, and procedural arithmetic.

Another concern is related to oculomotor deficits (e.g. downbeat nystagmus), which are common in CA and could have influenced participants' performance. While the SARA scale does not assess oculomotor function, our experimental design – in all three experiments – has control conditions that help account for general processing differences, including those that could arise from oculomotor deficits. These conditions, such as the correct trials and the complexity effects, allow us to isolate effects specifically related to VE while minimizing the influence of broader performance factors, such as eye movement abnormalities. We also note that, while some patients can experience oculomotor symptoms such as downbeat nystagmus, none of our tasks required precise visual tracking or gaze shifts. In our experimental tasks, stimuli were centrally presented, and no visual tracking or saccadic responses were required.

Our study is subject to two main limitations. First, information about anatomical-behavioral relationships can provide valuable data and will certainly be important in the long run for understanding how the cerebellum contributes to cognition. For example, one can ask if performance is related to gross measures such as total cerebellar volume or finer measures such as whether the observed deficits are associated with atrophy in particular regions. These analyses typically require large sample sizes, especially when dealing with atrophic processes (where the pathology tends to be relatively diffuse). Relatedly, we could not perform brain connectivity analysis, which limits our ability to examine the interactions between the cerebellum and other brain regions, such as the basal ganglia (BG) and the frontal lobe. This lack of brain connectivity data also restricts our ability to compare the cerebellum’s functional contributions to those of other regions. For example, in a recently published paper (2024), we found that the BG plays a distinct role in mathematical complexity processes (Saban et al., 2024). Unfortunately, we do not have imaging data for many of the patients.

Yet, there is added value in studies that include behavioral results from neurological groups defined based on clinical diagnosis. This is common in the literature, as seen in other recently published studies (Saban et al., 2024; McDougle et al., 2022) in high-impact journals (PNAS, Journal of Neuroscience, Brain). In addition, the current experimental design is already complex, with two groups and three experiments, including control conditions. However, future work should use lesion analysis or connectivity methods to identify the specific anatomical-behavioral relationships critical for arithmetic and language operations.

A few important questions remain open in the literature concerning the cerebellum’s role in expectation-related processes. The first is whether the cerebellum contributes to the formation of expectations or the processing of their violations. In Experiments 1 and 2, the CA group did not show impairments in the complexity manipulation. Solving these problems requires the formation of expectations during the reasoning process. Given the intact performance of the CA group, these results suggest that they are not impaired in forming expectations. However, in both Experiments 1 and 2, patients exhibited selective impairments in solving incorrect problems compared to correct problems. Since expectation formation is required in both conditions, but only incorrect problems involve a VE, we hypothesize that the cerebellum is involved in VE processes. We suggest that the CA group can form expectations in familiar tasks, but are impaired in processing unexpected compared to expected outcomes. This supports the notion that the cerebellum contributes to VE, rather than to forming expectations.

In Experiment 3, during training, participants learn a novel rule (grammar), forming new expectations on how strings of letters should be. Afterwards, during testing, the participants are requested to identify if a novel string following the rule or not. We examined sensitivity to distinguish between grammatical and non‐grammatical strings of letters, thus taking into account a baseline ability to identify expected strings. Additionally, both in the low‐similarity and high‐similarity conditions, there are expectations regarding whether the strings following the rule or not. However, in the high‐similarity condition, there is more uncertainty regarding which strings are following the grammatical rule, as demonstrated in a lower sensitivity (d prime). Given the group differences only in the low similarity condition, these results suggest the CA group is impaired only when the rules are more certain. Given these results, we suggest that forming cognitive expectations is not necessarily dependent on the cerebellum. Rather, we propose that the cerebellum is critical for processing VE (detection or processing of detected errors) under conditions of more certainty. One remaining question for future studies is whether the cerebellum contributes to detection of a mismatch between the expectation and sensory evidence, or the processing of a detected VE.

We suggest that these key questions are relevant to both motor and non-motor domains and were not fully addressed even in the previous, well-studied motor domain. Importantly, while previous experimental manipulations Taylor et al., 2014; Moberget et al., 2014; Riva, 1998; Butcher et al., 2017 have provided valuable insights regarding the cerebellar role in these processes, some may have confounded these two internal constructs due to task design limitations (e.g. lack of baseline conditions). Notably, some of these previous studies did not include control conditions, such as correct trials, where there was no VE. In addition, other studies did not include a control measure (e.g. complexity effect), which limits their ability to infer the specific cerebellar role in expectation manipulation.

Thus, the current experimental design used in three different experiments provides a valuable novel experimental perspective, allowing us to distinguish between some, but not all, of the processes involved in the formation of expectations and their violations. For instance, to our knowledge, this is the first study to demonstrate a selective impairment in rule-based VE processing in cerebellar patients across both numerical reasoning and artificial grammar tasks. If feasible, we propose that future studies should disentangle different forms of VE by operationalizing them in experimental tasks in an orthogonal manner. This will allow us to achieve a more detailed and well-defined cerebellar motor and non-motor mechanistic account.

All data supporting the conclusions of this study are included in the main text. The raw datasets analyzed in this study involve patients with a rare disease (prevalence < 0.01), and publishing these data poses a significant risk to patient privacy. For this reason, the patients' individual raw data cannot be made publicly available. Researchers who wish to access the raw data may contact the corresponding author (willsabanATtauex.tau.ac.il). Requests must include a project proposal outlining the intended use of the data. Proposals will be reviewed by our Institutional Review Board (IRB) and/or data access committee to ensure compliance with ethical and legal standards. If approved, access will be granted for non-commercial research purposes only. The review process typically requires 4-8 weeks. Summary data files and R code to reproduce the figures and statistical results are available on GitHub (copy archived at Saban, 2025).

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Author details

1. Leonardo Daniel

   1. Center for Accessible Neuropsychology and Sagol School of Neuroscience, Tel Aviv University, Tel aviv, Israel
   2. Department of Occupational Therapy, Gray Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv, Israel

   Contribution

   Formal analysis, Methodology, Writing – original draft, Project administration, Writing – review and editing

   Competing interests

   No competing interests declared

2. Eli Vakil

   Department of Psychology and Leslie and Susan Gonda (Goldschmied) Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat-Gan, Israel

   Contribution

   Writing – review and editing

   Competing interests

   No competing interests declared

3. William Saban

   1. Center for Accessible Neuropsychology and Sagol School of Neuroscience, Tel Aviv University, Tel aviv, Israel
   2. Department of Occupational Therapy, Gray Faculty of Medical & Health Sciences, Tel Aviv University, Tel Aviv, Israel

   Contribution

   Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   For correspondence

   williamsaban@gmail.com

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4215-2478

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