The assumption of linear time-invariance (LTI) in the human primary somatosensory cortex (SI) is assessed for fMRI signals generated by variable-duration vibrotactile stimuli. Predictions based on time-shifted summati...
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The assumption of linear time-invariance (LTI) in the human primary somatosensory cortex (SI) is assessed for fMRI signals generated by variable-duration vibrotactile stimuli. Predictions based on time-shifted summation (TSS) of responses to 2 s stimuli overestimate observed BOLD signal amplitudes in response to longer-duration stimuli, in agreement with previous findings in other primary sensory cortices. To interpret these results, we undertook an alternative approach for LTI assessment by characterizing BOLD signals using two biophysical models. The first model assumes that the input stimulus envelope is proportional to neural activity. The second assumes that neural activity exhibits both transient and steady-state components, consistent with extensive electrophysiological data, and fits the experimental data better. Although nonlinearity remains evident for short stimulus durations, the latter model shows that the TSS procedure to assess LTI overestimates the BOLD signal because the temporal characteristics of neural activity have not been considered adequately. Further research to investigate the BOLD response to time-varying neural activity is required. (C) 2005 Wiley-Liss, Inc.
This study achieves superior multi-channel output gain margin (MOGM), compensation of continuous-time, lineartime-invariant (LTI), non-minimum-phase, unstable, multi-input-multi-output (MIMO) plants by first input-ou...
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This study achieves superior multi-channel output gain margin (MOGM), compensation of continuous-time, lineartime-invariant (LTI), non-minimum-phase, unstable, multi-input-multi-output (MIMO) plants by first input-output decoupling these in open-loop and then effecting zero placements of the decoupled loops using single-input-single-output (SISO) periodic feedback. The condition that allows this controller to yield arbitrarily large MOGM is also found out. An example is considered to illustrate the design procedure and the capability of this controller.
Characterizing the neurovascular coupling between hemodynamic signals and their neural origins is crucial to functional neuroimaging research, even more so as new methods become available for integrating results from ...
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Characterizing the neurovascular coupling between hemodynamic signals and their neural origins is crucial to functional neuroimaging research, even more so as new methods become available for integrating results from different functional neuroimaging modalities. We present a novel method to relate magnetoencephalography (MEG) and BOLD fMRI data from primary somatosensory cortex within the context of the linear convolution model. This model, which relates neural activity to BOLD signal change, has been widely used to predict BOLD signals but typically lacks experimentally derived measurements of neural activity. In this study, an fMRI experiment is performed using variable-duration (<= 1 s) vibrotactile stimuli applied at 22 Hz, analogous to a previously published MEG study (Nangini et al., [2006]: Neuroimage 33:252-262), testing whether MEG source waveforms from the previous study can inform the convolution model and improve BOLD signal estimates across all stimulus durations. The typical formulation of the convolution model in which the input is given by the stimulus profile is referred to as Model 1. Model 2 is based on an energy argument relating metabolic demand to the postsynaptic currents largely responsible for the MEG current dipoles, and uses the energy density of the estimated MEG source waveforms as input to the convolution model. It is shown that Model 2 improves the BOLD signal estimates compared to Model 1 under the experimental conditions implemented, suggesting that MEG energy density can be a useful index of hemodynamic activity.
We introduce the W-CALCULUS, an extension of the call-by-value lambda-calculus with synchronous semantics, designed to be flexible enough to capture different implementation forms of Digital Signal Processing algorith...
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ISBN:
(纸本)9781450386135
We introduce the W-CALCULUS, an extension of the call-by-value lambda-calculus with synchronous semantics, designed to be flexible enough to capture different implementation forms of Digital Signal Processing algorithms, while permitting a direct embedding into the Coq proof assistant for mechanized formal verification. In particular, we are interested in the different implementations of classical DSP algorithms such as audio filters and resonators, and their associated high-level properties such as linear time-invariance. We describe the syntax and denotational semantics of the W-CALCULUS, providing a Coq implementation. As a first application of the mechanized semantics, we prove that every program expressed in a restricted syntactic subset of W is lineartime-invariant, by means of a characterization of the property using logical relations. This first semantics, while convenient for mechanized reasoning, is still not useful in practice as it requires re-computation of previous steps. To improve on that, we develop an imperative version of the semantics that avoids recomputation of prior stream states. We empirically evaluate the performance of the imperative semantics using a staged interpreter written in OCaml, which, for an input program in W, produces a specialized OCaml program, which is then fed to the optimizing OCaml compiler. The approach provides a convenient path from the high-level semantical description to low-level efficient code.
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