This title appears in the Scientific Report :
2019
State-dependent sequence processing in Spiking Neural Networks
State-dependent sequence processing in Spiking Neural Networks
Several organizational principles of the neocortex appear to imply a strong predisposition to acquire temporal structure in a completely incidental/unsupervised manner, a process that iscentral to many core aspects of cognition. In the work I will present, we explore the processesinvolved in implici...
| Personal Name(s): | Duarte, Renato (Corresponding author) |
|---|---|
| Contributing Institute: |
Computational and Systems Neuroscience; INM-6 Jara-Institut Brain structure-function relationships; INM-10 Computational and Systems Neuroscience; IAS-6 |
| Imprint: |
2019
|
| Conference: | NII Shonan Meeting: "Language as goal-directed sequential behavior", Kanagawa (Japan), 2019-05-19 - 2019-05-23 |
| Document Type: |
Conference Presentation |
| Research Program: |
Supercomputing and Modelling for the Human Brain W2/W3 Professorinnen Programm der Helmholtzgemeinschaft Theory, modelling and simulation |
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| 100 | 1 | |a Duarte, Renato |0 P:(DE-Juel1)165640 |b 0 |e Corresponding author |u fzj | |
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| 245 | |a State-dependent sequence processing in Spiking Neural Networks | ||
| 260 | |c 2019 | ||
| 520 | |a Several organizational principles of the neocortex appear to imply a strong predisposition to acquire temporal structure in a completely incidental/unsupervised manner, a process that iscentral to many core aspects of cognition. In the work I will present, we explore the processesinvolved in implicit, structured sequence learning in biologically-inspired architectures,systems where the current state continuously interacts with and modifies the processingcharacteristics. We demonstrate a prominent role of synaptic plasticity (particularly of inhibitorysynapses) in representational and rule-guided learning, an effect achieved by maintainingcompact dynamic representations and sparse, distributed activity patterns. We highlight a formof sequential metastability as a potential mechanism for sequence processing in neocorticalcircuits. In addition, I will discuss how innate constraints in the patterning of the synapticmachinery throughout the neocortex may bias a circuit’s intrinsic timescales and memorycapacity, while the high degree of complexity and heterogeneity may serve importantcomputational purposes by expanding the circuit’s functional space. | ||
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