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• Cerebellar ataxia: lessons from research
  Graziella Quattrocchi
  Published on: 4 March 2015

• Published on: 4 March 2015

  Cerebellar ataxia: lessons from research

  • Graziella Quattrocchi, MD, Clinical Research Associate

  I read with interest the review by Tada et al. [1], which, based on the current knowledge on the cerebellar systems, propose an interesting framework to interpret cerebellar ataxias in clinical settings. The Authors classify cerebellar ataxias into two main categories: those with a loss of Purkinje cells, translating into a malformation of internal models; and those with a disturbance of afferent systems, causing a mis- s...

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  I read with interest the review by Tada et al. [1], which, based on the current knowledge on the cerebellar systems, propose an interesting framework to interpret cerebellar ataxias in clinical settings. The Authors classify cerebellar ataxias into two main categories: those with a loss of Purkinje cells, translating into a malformation of internal models; and those with a disturbance of afferent systems, causing a mis- selection of internal models. From a clinical point of view, the first type of deficit, as observed in SCA31 and SCA6, results in decomposition and dysmetria. In addition, the loss of Purkinje cells may initially affect just the quality, and not the quantity, of internal models, and new internal models could be reconstructed using the residual circuits. This could explain why patients with pure cerebellar ataxia initially respond well to rehabilitation. Concerning the second category, a further classification differentiates the disturbances of the corticopontocerebellar system, such as in MSA-C and SCA2, from those of the spinocerebellar system, such as in SCA1, SCA3, FRDA and AOA1. In all of them there is dysmetria and dysrhythmia but, while the pontocerebellar disturbance affects the internal model selection for well-trained limb movements, such as writing or playing an instrument; disturbances of the spinocerebellar system affect actions requiring continuous feedback from the periphery, such as stance and gait. Finally, a third type of ataxia, such as the DRPLA, involves the efferent system (deep nuclei), resulting in a deficit of the overall cerebellar function.

  This classification has the great value of building a bridge between basic research and clinical knowledge, and it's simple enough to be implemented in everyday clinical practice, but it deserves some comments.

  First, as already acknowledged by the Authors, the pathology of degenerative ataxias is much more complex than the proposed schematization, as there is usually a combined degeneration of various systems and the very initial pathological alterations in many cases are still controversial [2].

  Second, the proposed classification is based on the classical view that the cerebellar cortex has a uniform structure and that a unique neural computation (the so called "cerebellar transform") is performed throughout it [3]. This implies that the functional role of the different cerebellar areas is dictated by its input and output connections and that, once known these connections, the impact of a lesion can be predicted relatively easily. Nowadays, it looks that this traditional concept requires sophistication. In fact, as underlined in a recent review by Cerminara et al. [4], cytoarchitectural and physiological variations have been identified in the cerebellar cortex, supporting the non-orthodox hypothesis that the cerebellar cortex, and therefore its information processing, is not uniform. In this case, classifying ataxias just on the basis of the anatomical regions affected could not be enough to predict the functional deficit. Interestingly, it seems that, the configuration of Purkinje cells death in neurodegeneration is not random, being probably genetically determined [4]. Therefore, a deeper knowledge of these patterns and at the same time of the cerebellar cortex computations could lead to a more accurate phenotypic classification of ataxias.

  Third, Tada et al. [1] focused their observations on motor symptoms. As the cerebellum is nowadays known to have also non-motor roles, a similar classification regarding cognitive functions in ataxias would be of interest, even if, again, the complexity of neurodegeneration would make this task quite arduous [5].

  Finally, formally exploring the motor differences between these categories, with an accurate registration of movement kinematics and a motor learning task, would be of interest. This would require testing subjects in an early stage of disease, to evaluate if motor performance and motor learning vary across the different neurodegeneration patterns and with disease progression. This approach could finally lead to development of new rating scales but also to an improvement of actual neurorehabilitation approaches.

  References

  1. Tada M, Nishiwaza M, Onodera O. Journal of Neurology Neurosurgery and Psychiatry 2015; 0:1-7. doi: 10.1136/jnnp-2013-307225

  2. Fratkin JD and Vig PJS. Handbook of Clinical Neurology 2012; 103:111-125.

  3. D'Angelo E, Casali S. Frontiers in Neural Circuits 2013; 10:116. doi: 10.3389/fncir.2012.00116. eCollection 2012.

  4. Cerminara NL, Lang EJ, Sillitoe RV, Apps R. Nature Reviews Neuroscience 2015; 16:79-93.

  5. Burk K. Cerebellum 2007; 6(3):280-6.

  Conflict of Interest:

  None declared

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  Conflict of Interest:
  None declared.

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