Universal Transform or Multiple Functionality? Understanding the Contribution of the Human Cerebellum across Task Domains

Abstract

An impressive body of research over the past 30 years has implicated the human cerebellum in a broad range of functions, including motor control, perception, language, working memory, cognitive control, and social cognition. The relatively uniform anatomy and physiology of the cerebellar cortex has given rise to the idea that this structure performs the same computational function across diverse domains. Here we highlight evidence from the human neuroimaging literature that documents the striking functional heterogeneity of the cerebellum, both in terms of task-evoked activity patterns and, as measured under task-free conditions, functional connectivity with the neocortex. Building on these observations, we discuss the theoretical challenges these results present to the idea of a universal cerebellar computation and consider the alternative concept of multiple functionality, the idea that the same underlying circuit implements functionally distinct computations.

Keywords: cerebellum; cognition; fMRI; functional magnetic resonance imaging; review; universal transform.

Figure 1

Cerebellar circuitry. (a) The main connections of the cortico-cerebellar loop. Numbers indicate rough estimates of the number of projections, or cells in the human brain in millions (M). (b) Local circuit in the cerebellum. Every granule cell receives 4–5 mossy fibers and gives rise to a single parallel fiber. Each Purkinje cell receives input from ~175,000 parallel fibers, as well as from a single climbing fiber that originates in the inferior olive. Purkinje cells send inhibitory projection to cells in the deep cerebellar nuclei (DCN). The inhibitory interneurons (mainly Golgi, Stellate, and Basket cells) complete the circuit.

Figure 2

Schematic of the universal transform and multiple functionality hypotheses, considered across Marr’s three levels of analysis. At the computational level, each task demands a different computational description. At the implementation level, the cerebellar circuitry is remarkably uniform. The idea of a universal transform holds that at the algorithmic level we can formulate a general idea of how cerebellar circuits contributes to diverse functions. In contrast, the multiple functionality models posits that different task rely on variable contributions from a number of cerebellar functional modules, each of which requires a distinct algorithmic description.

Figure 3

Surface of cerebellar cortex. (a) A section showing inferior lobules VIIIa, VIIIb and IX of the left hemisphere of a human cerebellum scanned at 150μm resolution. The scan clearly visualizes the granular cell layer in medium gray and the molecular layer in white. The superimposed grid indicates a typical sampling of a functional scan at 1.5mm resolution. (b) Unfolded representation of an entire human cerebellum (Sereno et al., 2014). For flattening, the surface is cut into 4 pieces. Color indicates local curvature, with green indicating the crest of a folia. (c) Simplified surface at the level of cerebellar lobules for the display of volume-averaged function data (Diedrichsen and Zotow, 2015).

Figure 4

Functional organization of the human cerebellum. (a) Somatotopic representation of foot (blue), hand (red) and tongue (green) movement in the cerebellum (Diedrichsen & Zotow, 2015). (b) Functional parcellation of the cerebellum based on multi-domain task battery (King et al., 2018). Parcellation and underlying task contrasts are available at diedrichsenlab.org/imaging/mdtb.htm.

Figure 5

Functional connectivity between neocortex and cerebellar cortex, using a cortical parcellation into 17 regions (Buckner et al., 2011). It has been proposed that the neocortex is “represented” 3 times in the cerebellum, with each representation running from motor to more cognitive regions.