We studied single-event and average BOLD responses to EEG interictal epileptic discharges (IEDs) in four patients with focal epilepsy, using continuous EEG-fMRI during 80-min sessions. The detection of activated areas was performed by comparing the BOLD signal at each voxel to a model of the expected signal. Since little is known about the BOLD response to IEDs, we modeled it with the response ...

Although fMRI is increasingly used to assess language-related brain activation in patients with aphasia, few studies have examined the hemodynamic response function (HRF) in perilesional, and contralesional areas of the brain. In addition, the relationship between HRF abnormalities and other variables such as lesion size and severity of aphasia has not been explored. The objective of this study...

The thresholded t-map produced by the General Linear Model (GLM) gives an effective summary of activation patterns in functional brain images and is widely used for feature selection in fMRI related classification tasks. As part of a project to build content-based retrieval systems for fMRI images, we have investigated ways to make GLM more adaptive and more robust in dealing with fMRI data fro...

Introduction: The mapping from neuronal activation to measured blood oxygenation level dependent (BOLD) signal in fMRI involves a complex interplay between physiological and physical processes that is yet to fully elucidated. Methods that account for the variability of the hemodynamic response function (HRF) have, with few exceptions (eg.[1] and subsequent works), focused on parameterised, dete...

A linear time-invariant model based on statistical time series analysis in the Fourier domain for single subjects is further developed and applied to functional MRI (fMRI) blood-oxygen level-dependent (BOLD) multivariate data. This methodology was originally developed to analyze multiple stimulus input evoked response BOLD data. However, to analyze clinical data generated using a repeated measu...

Some efforts were done to investigate the disruption of brain causal connectivity networks involved in major depressive disorder (MDD) using Granger causality (GC) analysis. However, the homogenous hemodynamic response function (HRF) assumption over the brain may disturb the inference of temporal precedence. Here we applied a blind deconvolution approach to examine the altered HRF shape in firs...

The goal of many functional Magnetic Resonance Imaging (fMRI) studies is to infer neural activity from hemodynamic signals. Classical fMRI analysis approaches assume that the hemodynamic response function (HRF) is identical in every voxel, i.e. it is separable in voxel-space and time. This study demonstrates to our knowledge for the first time directly that although the nonseparable part is sma...

Factors such as strabismus or anisometropia during infancy can disrupt normal visual development and result in amblyopia, characterized by reduced visual function in an otherwise healthy eye and often associated with persistent suppression of inputs from the amblyopic eye by those from the dominant eye. It has become evident from fMRI studies that the cortical response to stimulation of the amb...

This paper proposes a methodology for estimating Neural Response Functions (NRFs) from fMRI data. These NRFs describe non-linear relationships between experimental stimuli and neuronal population responses. The method is based on a two-stage model comprising an NRF and a Hemodynamic Response Function (HRF) that are simultaneously fitted to fMRI data using a Bayesian optimization algorithm. This...

This paper presents the possibility of using Electroencephalograms (EEG) signals of an individual for quantitative interpretation of Cerebral Autoregulation (CA). EEG data was recorded during arm cuff inflation to induce dynamic changes in arterial blood pressure and then, Cerebral Blood Flow (CBF) was estimated from EEG using canonical hemodynamic response function (HRF). The assessment of CA ...