The mechanism behind memory is one of the mysteries in neuroscience. Here we unravel part of the mechanism by showing that cultured neuronal networks develop an activity connectivity balance. External inputs disturb this balance and induce connectivity changes. The new connectivity is no longer disrupted by reapplication of the input, indicating that a network memorizes the input. A different input again induces connectivity changes, but returning to the first input no longer affects connectivity, showing that memory traces are stored in parallel. Computer modeling supports these findings, and shows that spike timing dependent plasticity enables neuronal networks to store memory traces of different inputs in parallel
Learning, or more generally, plasticity may be studied using cultured networks of rat cortical neuro...
The ability to associate some stimuli while differentiating between others is an essential character...
We applied a training protocol to cultured cortical networks, adapted from Shahaf and Marom [1]. Lik...
The mechanisms behind memory have been studied mainly in artificial neural networks. Several mechani...
During systems consolidation, memories are spontaneously replayed favoring information transfer from...
The growth of civilization stems from our collective ability to encode, store and retrieve more fact...
Learning, or more generally, plasticity may be studied using cultured neuronal networks on multi ele...
SummaryThe ability to associate some stimuli while differentiating between others is an essential ch...
Neurons are the computational building blocks of our brains. They form complicated net- works that p...
Learning, or more generally, plasticity may be studied using cultured neuronal networks on multi ele...
Although already William James and, more explicitly, Donald Hebb's theory of cell assemblies have su...
Despite significant progress in our understanding of the brain at both microscopic and macroscopic s...
Cellular level learning is vital to almost all brain function, and extensive homeostatic plasticity ...
Learning, or more generally, plasticity may be studied using cultured networks of rat cortical neuro...
Cell assemblies are thought to be the substrate of memory in the brain. Theoretical studies have pre...
Learning, or more generally, plasticity may be studied using cultured networks of rat cortical neuro...
The ability to associate some stimuli while differentiating between others is an essential character...
We applied a training protocol to cultured cortical networks, adapted from Shahaf and Marom [1]. Lik...
The mechanisms behind memory have been studied mainly in artificial neural networks. Several mechani...
During systems consolidation, memories are spontaneously replayed favoring information transfer from...
The growth of civilization stems from our collective ability to encode, store and retrieve more fact...
Learning, or more generally, plasticity may be studied using cultured neuronal networks on multi ele...
SummaryThe ability to associate some stimuli while differentiating between others is an essential ch...
Neurons are the computational building blocks of our brains. They form complicated net- works that p...
Learning, or more generally, plasticity may be studied using cultured neuronal networks on multi ele...
Although already William James and, more explicitly, Donald Hebb's theory of cell assemblies have su...
Despite significant progress in our understanding of the brain at both microscopic and macroscopic s...
Cellular level learning is vital to almost all brain function, and extensive homeostatic plasticity ...
Learning, or more generally, plasticity may be studied using cultured networks of rat cortical neuro...
Cell assemblies are thought to be the substrate of memory in the brain. Theoretical studies have pre...
Learning, or more generally, plasticity may be studied using cultured networks of rat cortical neuro...
The ability to associate some stimuli while differentiating between others is an essential character...
We applied a training protocol to cultured cortical networks, adapted from Shahaf and Marom [1]. Lik...