AbstractGain modulation is a prominent feature of neuronal activity recorded in behaving animals, but the mechanism by which it occurs is unknown. By introducing a barrage of excitatory and inhibitory synaptic conductances that mimics conditions encountered in vivo into pyramidal neurons in slices of rat somatosensory cortex, we show that the gain of a neuronal response to excitatory drive can be modulated by varying the level of “background” synaptic input. Simultaneously increasing both excitatory and inhibitory background firing rates in a balanced manner results in a divisive gain modulation of the neuronal response without appreciable signal-independent increases in firing rate or spike-train variability. These results suggest that, wi...
The modulation of the sensitivity, or gain, of neural responses to input is an important component o...
The cortex is sensitive to weak stimuli, but responds to stronger inputs without saturating. The mec...
AbstractOne of the more prosaic but necessary features of almost any information processing system i...
AbstractGain modulation is a prominent feature of neuronal activity recorded in behaving animals, bu...
SummaryGain modulation is a widespread neuronal phenomenon that modifies response amplitude without ...
The modulation of the sensitivity, or gain, of neural responses to input is an important component o...
The cerebral cortex is organized so that an important component of feedback input from higher to low...
To act as computational devices, neurons must perform mathematical operations as they transform syna...
Stimulus properties, attention, and behavioral context influence correlations between the spike time...
4th NAMASEN Training Workshop - Dendrites 2014Neurons use the rate of action potentials to encode se...
<div><p>Gain modulation is a key feature of neural information processing, but underlying mechanisms...
The output of individual neurons is dependent on both synaptic and intrinsic membrane properties. Wh...
SummaryChanging gain in a neuronal system has important functional consequences, but the underlying ...
This is the final published version. It first appeared at http://journals.plos.org/plosone/article?i...
SummaryNeurons possess elaborate dendritic arbors which receive and integrate excitatory synaptic si...
The modulation of the sensitivity, or gain, of neural responses to input is an important component o...
The cortex is sensitive to weak stimuli, but responds to stronger inputs without saturating. The mec...
AbstractOne of the more prosaic but necessary features of almost any information processing system i...
AbstractGain modulation is a prominent feature of neuronal activity recorded in behaving animals, bu...
SummaryGain modulation is a widespread neuronal phenomenon that modifies response amplitude without ...
The modulation of the sensitivity, or gain, of neural responses to input is an important component o...
The cerebral cortex is organized so that an important component of feedback input from higher to low...
To act as computational devices, neurons must perform mathematical operations as they transform syna...
Stimulus properties, attention, and behavioral context influence correlations between the spike time...
4th NAMASEN Training Workshop - Dendrites 2014Neurons use the rate of action potentials to encode se...
<div><p>Gain modulation is a key feature of neural information processing, but underlying mechanisms...
The output of individual neurons is dependent on both synaptic and intrinsic membrane properties. Wh...
SummaryChanging gain in a neuronal system has important functional consequences, but the underlying ...
This is the final published version. It first appeared at http://journals.plos.org/plosone/article?i...
SummaryNeurons possess elaborate dendritic arbors which receive and integrate excitatory synaptic si...
The modulation of the sensitivity, or gain, of neural responses to input is an important component o...
The cortex is sensitive to weak stimuli, but responds to stronger inputs without saturating. The mec...
AbstractOne of the more prosaic but necessary features of almost any information processing system i...