It has recently been shown that both high-frequency and low-frequency cardiac and respiratory noise sources exist throughout the entire brain and can cause significant signal changes in fMRI data. It is also known that the brainstem, basal forebrain and spinal cord areas are problematic for fMRI because of the magnitude of cardiac-induced pulsations at these locations. In this study, the physio...

Magnetic Resonance Imaging (MRI) uses Radio waves and strong magnetic field rather than X-ray to provide clear and detailed pictures of internal organs and tissues. Functional Magnetic Resonance Imaging (fMRI) is a non-invasive brain imaging technique, which developed in the early 1990's, for determining which parts of the brain are activated by different types of physical sensation or activity...

Avalanches with power-law distributed size parameters have been observed in neuronal networks. This observation might be a manifestation of the self-organized criticality (SOC). Yet, the physiological mechanicsm of this behavior is currently unknown. Describing synaptic noise as transmission failures mainly originating from the probabilistic nature of neurotransmitter release, this study invest...

Cross-synaptic synchrony--correlations in transmitter release across output synapses of a single neuron--is a key determinant of how signal and noise traverse neural circuits. The anatomical connectivity between rod bipolar and A17 amacrine cells in the mammalian retina, specifically that neighboring A17s often receive input from many of the same rod bipolar cells, provides a rare technical opp...

There is increasing concern that human-produced ocean noise is adversely affecting marine mammals, as several recent cetacean mass strandings may have been caused by animals' interactions with naval 'mid-frequency' sonar. However, it has yet to be empirically demonstrated how sonar could induce these strandings or cause physiological effects. In controlled experimental studies, we show that mid...

Low frequency drift (0.0-0.015 Hz) has often been reported in time series fMRI data. This drift has often been attributed to physiological noise or subject motion, but no studies have been done to test this assumption. Time series T*2-weighted volumes were acquired on two clinical 1.5 T MRI systems using spiral and EPI readout gradients from cadavers, a normal volunteer, and nonhomogeneous and ...

INTRODUCTION Cardiac and respiratory fluctuations (physiological noise) are known to be confounding signals in the detection of cortical activation by fMRI. The standard correction method RETROICOR [1] has been used to perform a global correction by folding the whole time series (TS) into only one signal cycle and to use this global template to correct each individual cycle. We extended RETROIC...

A new form of image estimator, which takes account of linear features, is derived using a signal equivalent formulation. The estimator is shown to be a nonstationary linear combination of three stationary estimators. The relation of the estimator to human visual physiology is discussed. A method for estimating the nonstationary control information is described and shown to be effective when the...

K. Restom, Y. Behzadi, J. E. Perthen, T. T. Liu Center for Functional MRI, University of California, San Diego, La Jolla, CA, United States Introduction Physiological noise is a dominant source of noise in fMRI experiments, especially at higher field strengths. A previous study showed that the sensitivity of perfusion based fMRI could be significantly improved by removing physiological noise co...

Signal detection in the CNS relies on a complex interaction between the numerous synaptic inputs to the detecting cells. Two effects, stochastic resonance (SR) and coherence resonance (CR) have been shown to affect signal detection in arrays of basic neuronal models. Here, an array of simulated hippocampal CA1 neurons was used to test the hypothesis that physiological noise and electrical coupl...