Overrepresentation of bidirectional connections in local cortical networks has been repeatedly reported and is a focus of the ongoing discussion of nonrandom connectivity. Here we show in a brief mathematical analysis that in a network in which connection probabilities are symmetric in pairs, Pij = Pji, the occurrences of bidirectional connections and nonrandom structures are inherently linked; an overabundance of reciprocally connected pairs emerges necessarily when some pairs of neurons are more likely to be connected than others. Our numerical results imply that such overrepresentation can also be sustained when connection probabilities are only approximately symmetric
This study examines the relationship between population coding and spatial connection statistics in ...
<p>The figures on the left hand side column show the typical probabilities of a synapse from a neuro...
Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits no...
<div><p>How different is local cortical circuitry from a random network? To answer this question, we...
<div><p>(A) Null hypothesis is generated by assuming independent probabilities of connection.</p> ...
How different is local cortical circuitry from a random network? To answer this question, we probed ...
Modern anatomical tracing and imaging techniques are beginning to reveal the structural anatomy of n...
Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits no...
<div><p>(A) Synaptic connections in bidirectionally connected pairs are on average stronger than tho...
Lately the problem of connectivity in brain networks is being approached frequently by graph theoret...
Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits no...
Uniform random sparse network architectures are ubiquitous in computational neuroscience, but the im...
The local cortical network connectivity significantly deviates from a random network, giving rise to...
Network models are routinely downscaled because of a lack of computational resources, often without ...
Balanced networks offer an appealing theoretical framework for studying neural variability since the...
This study examines the relationship between population coding and spatial connection statistics in ...
<p>The figures on the left hand side column show the typical probabilities of a synapse from a neuro...
Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits no...
<div><p>How different is local cortical circuitry from a random network? To answer this question, we...
<div><p>(A) Null hypothesis is generated by assuming independent probabilities of connection.</p> ...
How different is local cortical circuitry from a random network? To answer this question, we probed ...
Modern anatomical tracing and imaging techniques are beginning to reveal the structural anatomy of n...
Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits no...
<div><p>(A) Synaptic connections in bidirectionally connected pairs are on average stronger than tho...
Lately the problem of connectivity in brain networks is being approached frequently by graph theoret...
Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits no...
Uniform random sparse network architectures are ubiquitous in computational neuroscience, but the im...
The local cortical network connectivity significantly deviates from a random network, giving rise to...
Network models are routinely downscaled because of a lack of computational resources, often without ...
Balanced networks offer an appealing theoretical framework for studying neural variability since the...
This study examines the relationship between population coding and spatial connection statistics in ...
<p>The figures on the left hand side column show the typical probabilities of a synapse from a neuro...
Cognitive functions are stored in the connectome, the wiring diagram of the brain, which exhibits no...