The cerebellum

Kristi Brogden
Mind Map by Kristi Brogden, updated more than 1 year ago
Kristi Brogden
Created by Kristi Brogden over 5 years ago
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Undergraduate BMS236 Building Nervous Systems (The cerebellum) Mind Map on The cerebellum, created by Kristi Brogden on 07/25/2014.

Resource summary

The cerebellum
1 40% of brain surface area
2 >50% of the brains neurons
2.1 10 to the 11 granule cells alone
3 Competitive advantage
3.1 Evolutionary (darwinian) perspective
3.1.1 Population characteristics are selected if they convey an evolutionary advantage
3.1.1.1 I.e. for a given individual showing that characteristic, there is an increased probability of surviving and producing offspring
3.1.2 Evolutionary pedigree of cerebellum
3.1.2.1 Killer organ for vertebrates
3.1.2.2 Fish and reptiles
3.1.2.2.1 left-right movement controller
3.1.2.2.2 Adaptation of movement to different environments
3.1.2.3 Sensorimotor stabilization
3.1.2.3.1 Vestibular-occular reflex
3.1.2.3.2 N.B senses are directly linked to actions
3.1.2.3.2.1 whisking
3.1.2.3.2.2 Ear pricking
3.1.2.3.2.3 Eye moving and focusing
3.2 Individual (developmental) perspective
3.2.1 Individuals need to compete for the best mates etc and so will strive to attain skills that will give them a competitive advantage
3.2.2 And the propensity to acquire such skills (via epigenetic programming) can be passed down to the next generation
3.3 Potential evolutionary advantages
3.3.1 Adaptive behaviour - different situations
3.3.2 Speed of action - the real time constraint on cognition
3.3.2.1 Enormous evolutionary pressure to respond faster and better
3.3.2.1.1 Enhance sophistication of sensory analysis
3.3.2.1.2 Increased speed of action
3.3.2.1.3 Synchronise sensory analysis with appropriate action
3.3.2.1.4 Both between and within species
3.3.2.2 Most species have fixed action patterns (reflexes)
3.3.2.3 Primates manage to create automatic actions through appropriate experience and practice
3.3.3 Socialisation - Important characteristic for social primates
4 10-15% of brain weight
5 Connections everywhere
5.1 Body as well as brain
6 Learning mechanisms and the brain
6.1 All regions of the brain support unsupervised learning (statistical learning)
6.2 Only the basal ganglia support reinforcement learning (i.e. success based)
6.3 Only cerebellum supports supervised learning (target and error signal)
6.4 Hence brain regions need to work together through networks
6.5 Cerebellum and skill
6.5.1 Tool use and the cerebellum
6.5.1.1 While human subjects learned to use a new tool (a computer mouse with a novel rotational transformation), cerebellar activity was measured by functional magnetic resonance imaging
6.5.1.1.1 Two types of activity were observed
6.5.1.1.1.1 One was spread over wide areas of the cerebellum and was precisely proportional to the error signal that guides the acquisition of internal models during learning
6.5.1.1.1.2 The other was confined to the area near the posterior superior fissure and remained even after learning, when the error levels had been equalized
6.5.1.1.1.2.1 Thus probably reflecting an acquired internal model of the new tool
6.5.1.2 Imamizu et al (2000)
6.5.2 Co-ordinator
6.5.2.1 sequential
6.5.2.2 Parallel
6.5.3 Adaptive timer
6.5.3.1 Response optimisation
6.5.4 Bricolage
6.5.4.1 Building blocks
6.5.5 Encapsulation and stimulation
6.5.5.1 Disembodied actions
6.5.5.2 Mental objects
6.5.6 Forward modeller
6.5.6.1 If execute A at t0, then predict state S at time t
6.5.7 sensorimotor context detector
6.5.7.1 In sensorimotor context C, execute action A after time T
6.5.8 Writing
6.5.8.1 A 'conspiracy' of neural circutis
6.6 Ito's (1990) CNMC concept
6.6.1 The major signal flow from a mossy fiber pathway to the nuclear group is modulated by its sidepath signal flow through the microzone, and this modulation is modified according to error signals mediated by the inferior olive neurons (1993, p.448)
6.6.2 Adaptive reflex control: The vestibular-occular reflex
6.6.2.1 Head velocity h• (monitored via vestibular system) is fed into the controller, whose task is to maintain eye velocity e• at -h• so that retinal slip is zero. Retinal slip is fed back to the CNMC via the IO. To make an effective correction the CNMC must learn the ‘inverse dynamics’ g-1 of the eye-muscle system
6.6.3 Voluntary motor learning: Finger to nose
6.6.3.1 Through practice, the CNMC learns equivalent dynamics (g’) to the dynamics g of the skeleto-muscular system. This allows a transition from feedback control to feedforward control. g’ reflects an ‘internalisation’ of the muscle dynamics system.
6.6.3.1.1 NB. Also the re-entrant loop, with precise timing, which allows sophisticated learning and prediction
7 Cerebellum and cognitive skill
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