13 research outputs found
Predicting the synaptic information efficacy in cortical layer 5 pyramidal neurons using a minimal integrate-and-fire model
Synaptic information efficacy (SIE) is a statistical measure to quantify the efficacy of a synapse. It measures how much information is gained, on the average, about the output spike train of a postsynaptic neuron if the input spike train is known. It is a particularly appropriate measure for assessing the inputâoutput relationship of neurons receiving dynamic stimuli. Here, we compare the SIE of simulated synaptic inputs measured experimentally in layer 5 cortical pyramidal neurons in vitro with the SIE computed from a minimal model constructed to fit the recorded data. We show that even with a simple model that is far from perfect in predicting the precise timing of the output spikes of the real neuron, the SIE can still be accurately predicted. This arises from the ability of the model to predict output spikes influenced by the input more accurately than those driven by the background current. This indicates that in this context, some spikes may be more important than others. Lastly we demonstrate another aspect where using mutual information could be beneficial in evaluating the quality of a model, by measuring the mutual information between the modelâs output and the neuronâs output. The SIE, thus, could be a useful tool for assessing the quality of models of single neurons in preserving inputâoutput relationship, a property that becomes crucial when we start connecting these reduced models to construct complex realistic neuronal networks
Up and down states and memory consolidation across somatosensory, entorhinal, and hippocampal cortices
In the course of a day, brain states fluctuate, from conscious awake information-acquiring states to sleep states, during which previously acquired information is further processed and stored as memories. One hypothesis is that memories are consolidated and stored during "offline" states such as sleep, a process thought to involve transfer of information from the hippocampus to other cortical areas. Up and Down states (UDS), patterns of activity that occur under anesthesia and sleep states, are likely to play a role in this process, although the nature of this role remains unclear. Here we review what is currently known about these mechanisms in three anatomically distinct but interconnected cortical areas: somatosensory cortex, entorhinal cortex, and the hippocampus. In doing so, we consider the role of this activity in the coordination of "replay" during sleep states, particularly during hippocampal sharp-wave ripples. We conclude that understanding the generation and propagation of UDS may provide key insights into the cortico-hippocampal dialogue linking archi- and neocortical areas during memory formation
Analysis of the intraspinal calcium dynamics and its implications on the plasticity of spiking neurons
The influx of calcium ions into the dendritic spines through the
N-metyl-D-aspartate (NMDA) channels is believed to be the primary trigger for
various forms of synaptic plasticity. In this paper, the authors calculate
analytically the mean values of the calcium transients elicited by a spiking
neuron undergoing a simple model of ionic currents and back-propagating action
potentials. The relative variability of these transients, due to the stochastic
nature of synaptic transmission, is further considered using a simple Markov
model of NMDA receptos. One finds that both the mean value and the variability
depend on the timing between pre- and postsynaptic action-potentials. These
results could have implications on the expected form of synaptic-plasticity
curve and can form a basis for a unified theory of spike time-dependent, and
rate based plasticity.Comment: 14 pages, 10 figures. A few changes in section IV and addition of a
new figur