Effect of diverse recoding of granule cells on optokinetic response in a cerebellar ring network with synaptic plasticity. (February 2021)
- Record Type:
- Journal Article
- Title:
- Effect of diverse recoding of granule cells on optokinetic response in a cerebellar ring network with synaptic plasticity. (February 2021)
- Main Title:
- Effect of diverse recoding of granule cells on optokinetic response in a cerebellar ring network with synaptic plasticity
- Authors:
- Kim, Sang-Yoon
Lim, Woochang - Abstract:
- Abstract: We consider a cerebellar ring network for the optokinetic response (OKR), and investigate the effect of diverse recoding of granule (GR) cells on OKR by varying the connection probability p c from Golgi to GR cells. For an optimal value of p c ∗ ( = 0 . 06 ), individual GR cells exhibit diverse spiking patterns which are in-phase, anti-phase, or complex out-of-phase with respect to their population-averaged firing activity. Then, these diversely-recoded signals via parallel fibers (PFs) from GR cells are effectively depressed by the error-teaching signals via climbing fibers from the inferior olive which are also in-phase ones. Synaptic weights at in-phase PF-Purkinje cell (PC) synapses of active GR cells are strongly depressed via strong long-term depression (LTD), while those at anti-phase and complex out-of-phase PF-PC synapses are weakly depressed through weak LTD. This kind of "effective" depression (i.e., strong/weak LTD) at the PF-PC synapses causes a big modulation in firings of PCs, which then exert effective inhibitory coordination on the vestibular nucleus (VN) neuron (which evokes OKR). For the firing of the VN neuron, the learning gain degree L g, corresponding to the modulation gain ratio, increases with increasing the learning cycle, and it saturates at about the 300th cycle. By varying p c from p c ∗, we find that a plot of saturated learning gain degree L g ∗ versus p c forms a bell-shaped curve with a peak at p c ∗ (where the diversity degree inAbstract: We consider a cerebellar ring network for the optokinetic response (OKR), and investigate the effect of diverse recoding of granule (GR) cells on OKR by varying the connection probability p c from Golgi to GR cells. For an optimal value of p c ∗ ( = 0 . 06 ), individual GR cells exhibit diverse spiking patterns which are in-phase, anti-phase, or complex out-of-phase with respect to their population-averaged firing activity. Then, these diversely-recoded signals via parallel fibers (PFs) from GR cells are effectively depressed by the error-teaching signals via climbing fibers from the inferior olive which are also in-phase ones. Synaptic weights at in-phase PF-Purkinje cell (PC) synapses of active GR cells are strongly depressed via strong long-term depression (LTD), while those at anti-phase and complex out-of-phase PF-PC synapses are weakly depressed through weak LTD. This kind of "effective" depression (i.e., strong/weak LTD) at the PF-PC synapses causes a big modulation in firings of PCs, which then exert effective inhibitory coordination on the vestibular nucleus (VN) neuron (which evokes OKR). For the firing of the VN neuron, the learning gain degree L g, corresponding to the modulation gain ratio, increases with increasing the learning cycle, and it saturates at about the 300th cycle. By varying p c from p c ∗, we find that a plot of saturated learning gain degree L g ∗ versus p c forms a bell-shaped curve with a peak at p c ∗ (where the diversity degree in spiking patterns of GR cells is also maximum). Consequently, the more diverse in recoding of GR cells, the more effective in motor learning for the OKR adaptation. Highlights: A cerebellar ring network for the optokinetic response (OKR) is considered. Effect of diverse recoding of granule (GR) cells on the learning for the OKR adaptation is studied. Diverse spiking patterns of GR cells appear relative to their population-averaged firing activity. Diverse recoding of the GR cells leads to effective long-term depression and motor learning. The more diverse in recoding of the GR cells, the more effective in learning for the OKR adaptation. … (more)
- Is Part Of:
- Neural networks. Volume 134(2021)
- Journal:
- Neural networks
- Issue:
- Volume 134(2021)
- Issue Display:
- Volume 134, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 134
- Issue:
- 2021
- Issue Sort Value:
- 2021-0134-2021-0000
- Page Start:
- 173
- Page End:
- 204
- Publication Date:
- 2021-02
- Subjects:
- Optokinetic response -- Cerebellar ring network -- Diverse recoding -- Effective long-term depression -- Effective motor learning
Neural computers -- Periodicals
Neural networks (Computer science) -- Periodicals
Neural networks (Neurobiology) -- Periodicals
Nervous System -- Periodicals
Ordinateurs neuronaux -- Périodiques
Réseaux neuronaux (Informatique) -- Périodiques
Réseaux neuronaux (Neurobiologie) -- Périodiques
Neural computers
Neural networks (Computer science)
Neural networks (Neurobiology)
Periodicals
006.32 - Journal URLs:
- http://www.sciencedirect.com/science/journal/08936080 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.neunet.2020.11.014 ↗
- Languages:
- English
- ISSNs:
- 0893-6080
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 6081.280800
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