Postsynaptic signal transduction models for long-term potentiation and depression
More than a hundred biochemical species, activated by neurotransmitters binding to
transmembrane receptors, are important in long-term potentiation (LTP) and long-term …
transmembrane receptors, are important in long-term potentiation (LTP) and long-term …
Unsupervised learning to overcome catastrophic forgetting in neural networks
Continual learning is the ability to acquire a new task or knowledge without losing any
previously collected information. Achieving continual learning in artificial intelligence (AI) is …
previously collected information. Achieving continual learning in artificial intelligence (AI) is …
Learning in large-scale spiking neural networks
T Bekolay - 2011 - uwspace.uwaterloo.ca
Learning is central to the exploration of intelligence. Psychology and machine learning
provide high-level explanations of how rational agents learn. Neuroscience provides low …
provide high-level explanations of how rational agents learn. Neuroscience provides low …
Spike-timing–dependent synaptic plasticity and synaptic democracy in dendrites
A Gidon, I Segev - Journal of neurophysiology, 2009 - journals.physiology.org
We explored in a computational study the effect of dendrites on excitatory synapses
undergoing spike-timing–dependent plasticity (STDP), using both cylindrical dendritic …
undergoing spike-timing–dependent plasticity (STDP), using both cylindrical dendritic …
Behavioral analysis of differential hebbian learning in closed-loop systems
Understanding closed loop behavioral systems is a non-trivial problem, especially when
they change during learning. Descriptions of closed loop systems in terms of information …
they change during learning. Descriptions of closed loop systems in terms of information …
Self-influencing synaptic plasticity: Recurrent changes of synaptic weights can lead to specific functional properties
Recent experimental results suggest that dendritic and back-propagating spikes can
influence synaptic plasticity in different ways (Holthoff, 2004; Holthoff et al., 2005). In this …
influence synaptic plasticity in different ways (Holthoff, 2004; Holthoff et al., 2005). In this …
[PDF][PDF] Learning and memory in chaotic spiking neural models
MOI Alhawarat - 2007 - researchgate.net
Chaos has some useful properties that can be exploited in information processing such as:
sensitive dependence on initial conditions, space filling, synchronization, control, and a wide …
sensitive dependence on initial conditions, space filling, synchronization, control, and a wide …
[책][B] Mixed signal VLSI circuit implementation of the cortical microcircuit models
J Wijekoon - 2011 - search.proquest.com
This thesis proposes a novel set of generic and compact biologically plausible VLSI (Very
Large Scale Integration) neural circuits, suitable for implementing a parallel VLSI network …
Large Scale Integration) neural circuits, suitable for implementing a parallel VLSI network …
Location-specific activity of signaling molecules underlying STDP in a model CA1 pyramidal neuron
G Slivko, A Saudargienė - BMC Neuroscience, 2010 - Springer
Spike-timing-dependent plasticity (STDP) is a form of bidirectional change in synaptic
strength that depends on the temporal order and temporal difference of the pre-and …
strength that depends on the temporal order and temporal difference of the pre-and …
Modelling closed-loop receptive fields: On the formation and utility of receptive fields in closed-loop behavioural systems
T Kulvicius - 2010 - ediss.uni-goettingen.de
Bei höher entwickelten Tieren nimmt die Komplexität der visuellen rezeptiven Felder mit
dem hierarchischen Aufbau von den visuellen Eingangsarealen zu den höheren …
dem hierarchischen Aufbau von den visuellen Eingangsarealen zu den höheren …