<p>The external population delivers stochastic activity to the local network. The local network is a recurrent Erdös-Rényi random network with homogeneous synaptic weights coupling neurons in population to neurons in population , for and same parameters for all neurons. There are neurons in both the excitatory and the inhibitory population. The connection probability is , and each neuron in population receives the same number of excitatory and inhibitory synapses. The size of the external population determines the amount of shared input received by each pair of cells in the local network. The neurons are modeled as binary units with a hard threshold .</p
<p>(<b>a</b>) Scheme of a balanced recurrent network with excitatory and inhibitory neurons driven b...
Connectivity in local cortical networks is far from random: Reciprocal connections are over-represen...
Large scale distributed systems, such as natural neuronal and artificial systems, have many local in...
<p>Each neuron in population receives randomly drawn excitatory inputs with weight , randomly dra...
<p>There are two populations of neurons, excitatory (green) and inhibitory (red). The inhibitory net...
<p>Recurrently connected excitatory (<i>E</i>) and inhibitory (<i>I</i>) populations (Erdős-Rényi ra...
(A) The local representation defines the statistics of synaptic weights Jij by starting from the mar...
<p>(A) Topology of interacting network of excitatory and inhibitory neurons. Here P<sub>e</sub> = 0....
<p><b>A:</b> Schematic of an assembly <i>i</i> consisting of an excitatory (<i>E</i><sub><i>i</i></s...
<p><b>A</b> Two neural populations with rates <i>r</i><sub>1</sub>, <i>r</i><sub>2</sub> inhibit eac...
<p>(<b>A</b>) Network illustration. A set of 3600 excitatory and 900 inhibitory recurrently connecte...
<p>(A) Network architecture with 21×6 inputs and 7×3 network neurons. The green, red and blue neuron...
We define a stochastic neuron as an element that increases its internal state with probability p unt...
AbstractWe study the role of inhibition in a nearest-neighbours-connected neural model. The state of...
<p><b>A</b> Schematic of manipulation in which additional constant current drive was added to a subp...
<p>(<b>a</b>) Scheme of a balanced recurrent network with excitatory and inhibitory neurons driven b...
Connectivity in local cortical networks is far from random: Reciprocal connections are over-represen...
Large scale distributed systems, such as natural neuronal and artificial systems, have many local in...
<p>Each neuron in population receives randomly drawn excitatory inputs with weight , randomly dra...
<p>There are two populations of neurons, excitatory (green) and inhibitory (red). The inhibitory net...
<p>Recurrently connected excitatory (<i>E</i>) and inhibitory (<i>I</i>) populations (Erdős-Rényi ra...
(A) The local representation defines the statistics of synaptic weights Jij by starting from the mar...
<p>(A) Topology of interacting network of excitatory and inhibitory neurons. Here P<sub>e</sub> = 0....
<p><b>A:</b> Schematic of an assembly <i>i</i> consisting of an excitatory (<i>E</i><sub><i>i</i></s...
<p><b>A</b> Two neural populations with rates <i>r</i><sub>1</sub>, <i>r</i><sub>2</sub> inhibit eac...
<p>(<b>A</b>) Network illustration. A set of 3600 excitatory and 900 inhibitory recurrently connecte...
<p>(A) Network architecture with 21×6 inputs and 7×3 network neurons. The green, red and blue neuron...
We define a stochastic neuron as an element that increases its internal state with probability p unt...
AbstractWe study the role of inhibition in a nearest-neighbours-connected neural model. The state of...
<p><b>A</b> Schematic of manipulation in which additional constant current drive was added to a subp...
<p>(<b>a</b>) Scheme of a balanced recurrent network with excitatory and inhibitory neurons driven b...
Connectivity in local cortical networks is far from random: Reciprocal connections are over-represen...
Large scale distributed systems, such as natural neuronal and artificial systems, have many local in...