Journal Article

FZJ-2020-02860

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Firing rate homeostasis counteracts changes in stability of recurrent neural networks caused by synapse loss in Alzheimer’s disease

Bachmann, C. (Corresponding author)FZJ* ; Tetzlaff, T.FZJ* ; Duarte, R.FZJ* ; Morrison, A.FZJ*

2020
Public Library of Science San Francisco, Calif.

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Please use a persistent id in citations: http://hdl.handle.net/2128/25883  doi:10.1371/journal.pcbi.1007790

Abstract: The impairment of cognitive function in Alzheimer’s disease is clearly correlated to synapse loss. However, the mechanisms underlying this correlation are only poorly understood. Here, we investigate how the loss of excitatory synapses in sparsely connected random networks of spiking excitatory and inhibitory neurons alters their dynamical characteristics. Beyond the effects on the activity statistics, we find that the loss of excitatory synapses on excitatory neurons reduces the network’s sensitivity to small perturbations. This decrease in sensitivity can be considered as an indication of a reduction of computational capacity. A full recovery of the network’s dynamical characteristics and sensitivity can be achieved by firing rate homeostasis, here implemented by an up-scaling of the remaining excitatory-excitatory synapses. Mean-field analysis reveals that the stability of the linearised network dynamics is, in good approximation, uniquely determined by the firing rate, and thereby explains why firing rate homeostasis preserves not only the firing rate but also the network’s sensitivity to small perturbations.

Note: Additional grants: Helmholtz Association Initiative and Networking Fund (project no. SO-092 [Advanced Computing Architectures] and Helmholtz Portfolio Theme "Supercomputing and Modeling for the Human Brain"),

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Contributing Institute(s):

1. Computational and Systems Neuroscience (INM-6)
2. Theoretical Neuroscience (IAS-6)
3. Jara-Institut Brain structure-function relationships (INM-10)
4. JARA - HPC (JARA-HPC)
5. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 571 - Connectivity and Activity (POF3-571) (POF3-571)
2. 572 - (Dys-)function and Plasticity (POF3-572) (POF3-572)
3. 574 - Theory, modelling and simulation (POF3-574) (POF3-574)
4. HBP SGA1 - Human Brain Project Specific Grant Agreement 1 (720270) (720270)
5. HBP SGA2 - Human Brain Project Specific Grant Agreement 2 (785907) (785907)
6. DFG project 233510988 - Mathematische Modellierung der Entstehung und Suppression pathologischer Aktivitätszustände in den Basalganglien-Kortex-Schleifen (233510988) (233510988)
7. Advanced Computing Architectures (aca_20190115) (aca_20190115)
8. Functional Neural Architectures (jinm60_20190501) (jinm60_20190501)

Appears in the scientific report 2020

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