Sentence examples for example the synaptic from inspiring English sources
For example, the synaptic clearance of GABA and glutamate by these cells is known to influence locomotion.
For example, the synaptic change (learning rate) is currently discretized into only two possible levels (± Δ w, see Eqn 3).
For example, the synaptic signal from neurons may influence the potassium channels of NG2 cells during the cell cycle and/or via the control of other intracellular signal cascades [ 89].
For example, the synaptic connections of axons that arise within the same cortical column in the neocortex preferentially innervate the proximal basal dendrites of pyramidal cells (Markram et al., 1997; Feldmeyer et al., 2002).
For example, the synaptic activation of TrkB, a receptor for brain-derived neurotrophic factor (BDNF), leads to phosphorylation of TSCs in the dendritic spine and thus the localized activation of cap-dependent translation (Takei et al., 2004).
[For example, the synaptic weights of the projections from ventral premotor cortex to superior temporal cortex ('auditory error map'), encoding the auditory targets for each speech-sound cell, are conveniently ordered in 'spatio-temporal' matrices, in which each column represents the target at one point in time, and there is a different column for every 1 ms of the duration of the speech sound.
This behavior is probably a by-product of a photoreceptor regulating its ion homeostasis and, as such, may contribute only indirectly to the coding of temporal input patterns, for example at the synaptic level [5], [14].
For example, at the synaptic ribbon in retinal bipolar cells large vesicles and invaginations are observed after stimulation and are thought to represent fusion between synaptic vesicles preceding exocytosis (Matthews and Sterling, 2008).
For example, increasing the synaptic conductance by a factor of 12, which maximizes information transmission through the synapse, more than halved the number of bits of information transmitted per ATP used.
The neural network learns the training examples by adjusting the synaptic weight according to the error occurred on the output layer.
For example, the extent of synaptic loss that begins prior to the appearance of tangles, plaques or neuronal loss is an excellent correlate of dementia.
