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In the simulation examples, this is accomplished by changing the strength of input correlation and bidirectional interaction and observing the corresponding change in the phase-lag.
Unlike simulated models, neither the strength of input correlation nor the strength of feed-forward/feed-back interaction can be manipulated to infer their influences on phase-lag.
For actual data, while Geweke's theorem allows the extraction of various causal influences through the decomposition of synchrony, the strength of input correlation and bidirectional interaction is not easily manipulated.
The response of this model is easily understood in terms of the strength of input at a given time.
When visual contrast is manipulated, the frequency of gamma oscillations covaries with the strength of input (Ray and Maunsell 2010).
This indicates that the intrinsic noise in the steady-state behavior of intrinsic apoptosis response at single cell level can be suppressed by enhancing the strength of input signal.
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The strength of input-output stability theory is that it provides a method for anticipating the qualitative behavior of a feedback system with only rough information as regards the feedback components [1].
The inhibitory weight does not affect the operational mode, but increasing (w^{mathrm{I}}) increases the range of q, resulting in a larger range of the relative strength of inputs ((b_{mathrm{pk}}^{1}-b_{mathrm{pk}}^{2})) for which there are two co-stable activity bumps (Type IV dynamics).
The peak of the single fiber-evoked EPSC (SF current) was used to gauge the strength of inputs from single HVC or LMAN neurons.
Between 4.8 and 8.6 months after the lesion, a terminal experiment was carried out to assess the strength of inputs via the intact (ipsilateral) pyramidal tract and the medial brainstem pathways to upper limb motor neurons.
However, the strength of inputs from the neighboring barrels was significantly higher for pyramidal neurons in lower LII/III (0.08 ± 0.02 mV s; n = 12) than for those in upper LII/III (0.03 ± 0.005 mV s; n = 14, p = 0.05).
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Justyna Jupowicz-Kozak
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