Sentence examples for correlation between neurons from inspiring English sources
In this report we show that the observed inter-neuronal correlation reflects a superposition of correlations associated with the intrinsic correlation between neurons, and correlations associated with variability in the stimuli presented to, or the actions performed by, the subject.
The sensitivity of a population of neurons, and therefore the amount of sensory information available to an animal, is limited by the sensitivity of single neurons in the population and by noise correlation between neurons.
SC describes the correlation between neurons in the intra-cycle interval and quantifies common changes in the activity of the neurons in relation to movement.
But the prediction of the optimal ratio here also varies over a wide range, depending on the assumption on the decoding scheme (and probably the shape of the tuning curves, assumption on the correlation between neurons etc).
We are not convinced that they make a very convincing case here, because they provide average data, and so it could be that on average the change in Rin is small, but that there is a good correlation between neurons that show a change in firing rate and neurons that show a change in Rin.
Romo et al. (2003) observed a loss in accuracy caused by positive correlations (with an average correlation coefficient of 0.12) between neurons tuned to the same frequency, but this was partially offset by an improvement caused by positive correlation between neurons tuned to different frequencies.
The results of NeuN and TUNEL double staining showed a negative correlation between neuron apoptosis and E-64-d, indicating that inhibition of calpain 1 at least partly rescued neurons from apoptosis in the lesion and may be therefore beneficial to recovery of SCI.
We find that the pattern of pairwise correlations between neurons has a strength that is well within the strongly correlated regime and does not require fine tuning, suggesting that this state is generic for populations of 100+ neurons.
For the 'selective decoding' model, noise among neurons within each pool was correlated in the same manner as described above, but there were no correlations between neurons in different pools.
Also, when correlations between neurons are introduced for each stimuli class, the advantage the MDA has over the PCA method is increased (data now shown).
In particular, levels of synergy and redundancy amongst three variables can be quantified in a principled manner, and have recently been formulated in the context of analyzing correlations between neurons [29], [30].
