Neocerebellar Emulation in Language Processing
Giorgos P. Argyropoulos
Language Evolution and Computation Research Unit, University of Edinburgh
giorgos@ling.ed.ac.uk
1. Introduction
3. Language comprehension in the
cerebellum
Despite the ample evidence gathered during the last decades in support of
the involvement of the cerebellum in language processing, there has been
little attention paid to the identity of the computations underlying such
involvement, especially given that the cerebellum seems to perform a 3.1. What is a Kalman filter?
unitary computation for a wide range of behavioral repertoires.
Emphasizing language comprehension here, I attempt the grounding of a
The Kalman filter (Kalman, 1960) is a dynamical state estimator testing incoming
recently proposed psycholinguistic processor (Pickering & Garrod, 2007) in
data against expectations, compensating for delays and filtering out noise in the
the cortico-cerebellar circuit.
sensory feedback, if the signal can be modeled as the output of a known dynamical
system. A Kalman regulator uses the sensory error to correct the estimate resulting
from the forward model. The Kalman gain determines the extent to which the
sensory residual influences the a priori estimate (i.e., whether emulation tramps the
actual sensory feedback or not).
2. The cerebellum
3.2. The reception of the Kalman filter in cognitive
psychology and psycholinguistics
2.1. The unitary cerebellar computation
4. The cerebellar pseudosyntax
1)
Townsend & Bever (2001): Sentence comprehension
employs both algorithmic (the actual “syntax”) and faster,
preemptive heuristic computations (the “pseudosyntax”); the
latter pertains to “semantic associations” and “syntactic habits”.

Ito (2000): A CNMC might connect to the cerebral loop as
a reliable copy of the thought/language model in the
temporoparietal areas, with the thought/language process being
alternatively conducted by the frontal areas acting on the CNMC
rather than on the temporoparietal areas, adaptively avoiding the
conscious effort needed for the exploration of cortical loci.
2)
McRae et al. (2005): Predictive top-down processing in
sentence comprehension relies on associative lexical relations,
not captured by spreading activation in lexical networks, but by
expectancy-generation mechanisms.

Expectancy-generation is ideally captured by the internal
model computations (e.g., Wolpert et al., 1998)

Cerebellar patients seem to be particularly impaired in the
noun-verb generation task (Fiez et al., 1992; Gebhart et al., 2002), a
lexical association that McRae et al. (2005) particularly
emphasize for expectation-based sentence comprehension.
• Cytoarchitectural (computational) homogeneity, functional heterogeneity
(e.g., Kawato & Gomi, 1992; Wolpert et al., 1998).
• “a unitary principle of architecture, but a localizationist principle of the
connectivity” (Schmahmann, 2000; 206).
3)
Kempson & Cann (2007): “… a natural subsequent step
of routinization… would be to call up the actions associated with
the verb together with those associated with the clitic with a
single lexical look-up mechanism” (Kempson & Cann, 2007)
Doya (1999): “… a cerebellar mapping can work as a
short-cut circuit or a look-up table for a mapping that was
originally developed by the time-consuming cortico-cortical
processing” (Doya, 1999, 970).


The posterolateral cerebellum is involved in constrained
search space in language tasks:
3.3. The neocerebellar KF linguistic processor
• Increased cerebellar activation in FEW condition in stem
completion task (Desmond et al., 1998)
• Spared performance in subordinate category generation
VS poor performance in superordinate category and
antonym generation for posterolateral cerebellars (Gebhart et al.,
The computations of a Cerebellar Cortico-Nuclear Micro-Complex (Ito, 1989). Figure
taken from Ito (2002, p. 281). Long-term depression (LTD) occurs at parallel fiber-toPurkinje cell synapses after conjunctive activation of these synapses together with
climbing fiber-to-Purkinje cell synapses (Ito et al., 1982).
2002; Fiez et al., 1992)
PC: Purkinje Cell. GR: Granule Cell. CC: Cerebellar Cortex. IO: Climbing Fiber.
MF: Mossy Fiber. CN: Cerebellar Nucleus CF: Climbing Fiber. LTD: Long Term
Depression. Hollow circle: Excitatory synapse. Filled circle: Inhibitory synapse.
5. Conclusion
The posterolateral cerebellum might be involved in language
perception processes by implementing Kalman Filter
computations in a way that makes language perception noiseresistant, and automatic, triggering covert, imitative
involvement of production mechanisms in language perception.
Acknowledgments
I am grateful to my supervisors, Prof. Jim Hurford, Dr. Patrick Sturt and Dr. Thomas Bak, as well as to the Pavlos and Elissavet
Papagiannopoulou Foundation for the financial support in my PhD studies.
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