Results 1  10
of
144
RealTime Computing Without Stable States: A New Framework for Neural Computation Based on Perturbations
"... A key challenge for neural modeling is to explain how a continuous stream of multimodal input from a rapidly changing environment can be processed by stereotypical recurrent circuits of integrateandfire neurons in realtime. We propose a new computational model for realtime computing on timevar ..."
Abstract

Cited by 469 (38 self)
 Add to MetaCart
be implemented on generic evolved or found recurrent circuitry. It is shown that the inherent transient dynamics of the highdimensional dynamical system formed by a sufficiently large and heterogeneous neural circuit may serve as universal analog fading memory. Readout neurons can learn to extract in real
Perspectives of the high dimensional dynamics of neural microcircuits from the point of view of low dimensional readouts
 Complexity
, 2003
"... We investigate generic models for cortical microcircuits, i.e., recurrent circuits of integrateandfire neurons with dynamic synapses. These complex dynamic systems subserve the amazing information processing capabilities of the cortex, but are at the present time very little understood. We analyze ..."
Abstract

Cited by 11 (2 self)
 Add to MetaCart
analyze the transient dynamics of models for neural microcircuits from the point of view of one or two readout neurons that collapse the highdimensional transient dynamics of a neural circuit into a one or twodimensional output stream. This stream may for example represent the information
and a Delay&Sum Readout
, 2008
"... Echo state networks (ESNs) are a novel approach to recurrent neural network training with the advantage of a very simple and linear learning algorithm. It has been demonstrated that ESNs outperform other methods on a number of benchmark tasks. Although the approach is appealing, there are still so ..."
Abstract
 Add to MetaCart
and signals at different timescales, which is especially important for modeling realworld time series. Second, a delay&sum readout is introduced, which adds trainable delays in the synaptic connections of output neurons and therefore vastly improves the memory capacity of echo state networks
Readout of visual information from inferior temporal cortex for object recognition
"... We are studying the properties of local field potentials (LFPs) in inferior temporal (IT) cortex of the macaque monkey. LFPs are thought to constitute an average mostly of excitatory postsynaptic potentials over large numbers of neurons. Therefore we ask whether the LFPs showed selective responses ..."
Abstract
 Add to MetaCart
built a classifier to be able to readout information about the visual stimuli presented to the monkey from the neural responses recorded in IT cortex. Motivation: After several decades of work trying to understand how IT cortex neurons respod to presentation of visual stimuli, some of the most basic
Belief propagation in networks of spiking neurons
 Neural Comput
, 2009
"... From a theoretical point of view, statistical inference is an attractive model of brain operation. However, it is unclear how to implement these inferential processes in neuronal networks. We offer a solution to this problem by showing in detailed simulations how the BeliefPropagation algorithm on ..."
Abstract

Cited by 19 (5 self)
 Add to MetaCart
messages to be transmitted over the edges of the graph are each computed by a group of readout neurons that feed in their respective destination pools. We use this approach to implement two examples of factor graphs. The first example is drawn from coding theory. It models the transmission of signals
Perceptual ‘‘ReadOut’ ’ of Conjoined Direction and Disparity Maps in Extrastriate Area MT
"... Cortical neurons are frequently tuned to several stimulus dimensions, and many cortical areas contain intercalated maps of multiple variables. Relatively little is known about how information is ‘‘read out’ ’ of these multidimensional maps. For example, how does an organism extract information relev ..."
Abstract

Cited by 6 (1 self)
 Add to MetaCart
Cortical neurons are frequently tuned to several stimulus dimensions, and many cortical areas contain intercalated maps of multiple variables. Relatively little is known about how information is ‘‘read out’ ’ of these multidimensional maps. For example, how does an organism extract information
Uncorrected Proof
, 1703
"... The brain faces the problem of inferring reliable hidden causes from large populations of noisy neurons, for example, the direction of a moving object from spikes in area MT. It is known that a theoretically optimal likelihood decoding could be carried out by simple linear readout neurons if weights ..."
Abstract
 Add to MetaCart
The brain faces the problem of inferring reliable hidden causes from large populations of noisy neurons, for example, the direction of a moving object from spikes in area MT. It is known that a theoretically optimal likelihood decoding could be carried out by simple linear readout neurons
ARTICLE Communicated by Mark van Rossum Emergence of Optimal Decoding of Population Codes Through STDP
"... The brain faces the problem of inferring reliable hidden causes from large populations of noisy neurons, for example, the direction of a moving object from spikes in area MT. It is known that a theoretically optimal likelihood decoding could be carried out by simple linear readout neurons if weigh ..."
Abstract
 Add to MetaCart
The brain faces the problem of inferring reliable hidden causes from large populations of noisy neurons, for example, the direction of a moving object from spikes in area MT. It is known that a theoretically optimal likelihood decoding could be carried out by simple linear readout neurons
unknown title
, 2003
"... We investigate generic models for cortical microcircuits, i.e. recurrent circuits of integrateand fire neurons with dynamic synapses. These complex dynamic systems subserve the amazing information processing capabilities of the cortex, but are at the present time very little understood. We analyze ..."
Abstract
 Add to MetaCart
the transient dynamics of models for neural microcircuits from the point of view of one or two readout neurons that collapse 2 the high dimensional transient dynamics of a neural circuit into a 1 or 2dimensional output stream. This stream may for example represent the information that is projected from
unknown title
, 2004
"... We investigate generic models for cortical microcircuits, i.e. recurrent circuits of integrateand fire neurons with dynamic synapses. These complex dynamic systems subserve the amazing information processing capabilities of the cortex, but are at the present time very little understood. We analyze ..."
Abstract
 Add to MetaCart
the transient dynamics of models for neural microcircuits from the point of view of one or two readout neurons that collapse the high dimensional transient dynamics of a neural circuit into a 1 or 2dimensional output stream. This stream may for example represent the information that is projected from
Results 1  10
of
144