منابع مشابه
Polychronization: Computation with Spikes
We present a minimal spiking network that can polychronize, that is, exhibit reproducible time-locked but not synchronous firing patterns with millisecond precision, as in synfire braids. The network consists of cortical spiking neurons with axonal conduction delays and spike-timing-dependent plasticity (STDP); a ready-to-use MATLAB code is included. It exhibits sleeplike oscillations, gamma (4...
متن کاملDelay learning and polychronization for reservoir computing
We propose a multi-timescale learning rule for spiking neuron networks, in the line of the recently emerging field of reservoir computing. The reservoir is a network model of spiking neurons, with random topology and driven by STDP (Spike-TimeDependent Plasticity), a temporal Hebbian unsupervised learning mode, biologically observed. The model is further driven by a supervised learning algorith...
متن کاملLearning through Viable Knowledge Creation
The idea that learners can have styles of learning derives from the work of Kolb, which stems from an inadequate theory of learning behaviour. Learning might better be placed within the context such as the knowledge creation cycle of Nonaka and Takeuchi. However this too has its epistemological problems. An alternative knowledge creation cycle is proposed that results in an alternative conceptu...
متن کاملEnhanced polychronization in a spiking network with metaplasticity
Computational models of metaplasticity have usually focused on the modeling of single synapses (Shouval et al., 2002). In this paper we study the effect of metaplasticity on network behavior. Our guiding assumption is that the primary purpose of metaplasticity is to regulate synaptic plasticity, by increasing it when input is low and decreasing it when input is high. For our experiments we adop...
متن کاملEvaluating the Effect of Spiking Network Parameters on Polychronization
Spiking neural networks (SNNs) are considered to be more biologically realistic compared to typical rate-coded networks as they can model closely different types of neurons and their temporal dynamics. Typical spiking models use a number of fixed parameters such as the ratio between excitatory and inhibitory neurons. However, the parameters that are used in these models focus almost exclusively...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: AVANT. The Journal of the Philosophical-Interdisciplinary Vanguard
سال: 2017
ISSN: 2082-6710
DOI: 10.26913/80s02017.0111.0015