Oliver Josephs

Event-related fMRI: Characterizing differential responses

We present an approach to characterizing the differences among event-related hemodynamic responses in functional magnetic resonance imaging that are evoked by different sorts of stimuli. This approach is predicated on a linear convolution model and standard inferential statistics as employed by statistical parametric mapping. In particular we model evoked responses, and their differences, in terms of basis functions of the peri-stimulus time. This facilitates a characterization of the temporal response profiles that has a high effective temporal resolution relative to the repetition time. To demonstrate the technique we examined differential responses to visually presented words that had been seen prior to scanning or that were novel. The form of these differences involved both the magnitude and the latency of the response components. In this paper we focus on bilateral ventrolateral prefrontal responses that show deactivations for previously seen words and activations for novel words.

A method for removing imaging artifact from continuous EEG recorded during functional MRI

Combined EEG/fMRI recording has been used to localize the generators of EEG events and to identify subject state in cognitive studies and is of increasing interest. However, the large EEG artifacts induced during fMRI have precluded simultaneous EEG and fMRI recording, restricting study design. Removing this artifact is difficult, as it normally exceeds EEG significantly and contains components in the EEG frequency range. We have developed a recording system and an artifact reduction method that reduce this artifact effectively. The recording system has large dynamic range to capture both low-amplitude EEG and large imaging artifact without distortion (resolution 2 microV, range 33.3 mV), 5-kHz sampling, and low-pass filtering prior to the main gain stage. Imaging artifact is reduced by subtracting an averaged artifact waveform, followed by adaptive noise cancellation to reduce any residual artifact. This method was validated in recordings from five subjects using periodic and continuous fMRI sequences. Spectral analysis revealed differences of only 10 to 18% between EEG recorded in the scanner without fMRI and the corrected EEG. Ninety-nine percent of spike waves (median 74 microV) added to the recordings were identified in the corrected EEG compared to 12% in the uncorrected EEG. The median noise after artifact reduction was 8 microV. All these measures indicate that most of the artifact was removed, with minimal EEG distortion. Using this recording system and artifact reduction method, we have demonstrated that simultaneous EEG/fMRI studies are for the first time possible, extending the scope of EEG/fMRI studies considerably.

Event-related f MRI.

We present a method for detecting event‐related responses in functional magnetic resonance imaging (fMRI). The occurrence of time‐locked activations is formulated in terms of the general linear model, i.e., multiple linear regression. This permits the use of established statistical techniques that correct for multiple comparisons in the context of spatially smooth and serially correlated data. Responses are modelled using event‐related temporal basis functions. Inferences are then made about all components of the model, using the F‐ratio at all voxels in the image, to produce a statistical parametric map (SPM{F}). This method allows for the experimental design to relate the timing of events to the acquisition of data to give a temporal resolution (with respect to the event‐related response) far better than the scanning repeat time. Hum. Brain Mapping 5:243–248, 1997.

Image Distortion Correction in fMRI: A Quantitative Evaluation

A well-recognized problem with the echo-planar imaging (EPI) technique most commonly used for functional magnetic resonance imaging (fMRI) studies is geometric distortion caused by magnetic field inhomogeneity. This makes it difficult to achieve an accurate registration between a functional activation map calculated from an EPI time series and an undistorted, high resolution anatomical image. A correction method based on mapping the spatial distribution of field inhomogeneities can be used to reduce these distortions. This approach is attractive in its simplicity but requires postprocessing to improve the robustness of the acquired field map and reduce any secondary artifacts. Furthermore, the distribution of the internal magnetic field throughout the head is position dependent resulting in an interaction between distortion and head motion. Therefore, a single field map may not be sufficient to correct for the distortions throughout a whole fMRI time series. In this paper we present a quantitative evaluation of image distortion correction for fMRI at 2T. We assess (i) methods for the acquisition and calculation of field maps, (ii) the effect of image distortion correction on the coregistration between anatomical and functional images, and (iii) the interaction between distortion and head motion, assessing the feasibility of using field maps to reduce this effect. We propose that field maps with acceptable noise levels can be generated easily using a dual echo-time EPI sequence and demonstrate the importance of distortion correction for anatomical coregistration, even for small distortions. Using a dual echo-time series to generate a unique field map at each time point, we characterize the interaction between head motion and geometric distortion. However, we suggest that the variance between successively measured field maps introduces additional unwanted variance in the voxel time-series and is therefore not adequate to correct for time-varying distortions.

Concurrent TMS-fMRI and Psychophysics Reveal Frontal Influences on Human Retinotopic Visual Cortex

BACKGROUND Regions in human frontal cortex may have modulatory top-down influences on retinotopic visual cortex, but to date neuroimaging methods have only been able to provide indirect evidence for such functional interactions between remote but interconnected brain regions. Here we combined transcranial magnetic stimulation (TMS) with concurrent functional magnetic resonance imaging (fMRI), plus psychophysics, to show that stimulation of the right human frontal eye-field (FEF) produced a characteristic topographic pattern of activity changes in retinotopic visual areas V1-V4, with functional consequences for visual perception. RESULTS FEF TMS led to activity increases for retinotopic representations of the peripheral visual field, but to activity decreases for the central field, in areas V1-V4. These frontal influences on visual cortex occurred in a top-down manner, independently of visual input. TMS of a control site (vertex) did not elicit such visual modulations, and saccades, blinks, or pupil dilation could not account for our results. Finally, the effects of FEF TMS on activity in retinotopic visual cortex led to a behavioral prediction that we confirmed psychophysically by showing that TMS of the frontal site (again compared with vertex) enhanced perceived contrast for peripheral relative to central visual stimuli. CONCLUSIONS Our results provide causal evidence that circuits originating in the human FEF can modulate activity in retinotopic visual cortex, in a manner that differentiates the central and peripheral visual field, with functional consequences for perception. More generally, our study illustrates how the new approach of concurrent TMS-fMRI can now reveal causal interactions between remote but interconnected areas of the human brain.

To Smooth or Not to Smooth?: Bias and Efficiency in fMRI Time-Series Analysis

This paper concerns temporal filtering in fMRI time-series analysis. Whitening serially correlated data is the most efficient approach to parameter estimation. However, if there is a discrepancy between the assumed and the actual correlations, whitening can render the analysis exquisitely sensitive to bias when estimating the standard error of the ensuing parameter estimates. This bias, although not expressed in terms of the estimated responses, has profound effects on any statistic used for inference. The special constraints of fMRI analysis ensure that there will always be a misspecification of the assumed serial correlations. One resolution of this problem is to filter the data to minimize bias, while maintaining a reasonable degree of efficiency. In this paper we present expressions for efficiency (of parameter estimation) and bias (in estimating standard error) in terms of assumed and actual correlation structures in the context of the general linear model. We show that: (i) Whitening strategies can result in profound bias and are therefore probably precluded in parametric fMRI data analyses. (ii) Band-pass filtering, and implicitly smoothing, has an important role in protecting against inferential bias.

Optimal EPI parameters for reduction of susceptibility-induced BOLD sensitivity losses: a whole-brain analysis at 3 T and 1.5 T.

Most functional magnetic resonance imaging (fMRI) studies record the blood oxygen level-dependent (BOLD) signal using fast gradient-echo echo-planar imaging (GE EPI). However, GE EPI can suffer from substantial signal dropout caused by inhomogeneities in the static magnetic field. These field inhomogeneities occur near air/tissue interfaces, because they are generated by variations in magnetic susceptibilities. Thus, fMRI studies are often limited by a reduced BOLD sensitivity (BS) in inferior brain regions. Recently, a method has been developed which allows for optimizing the BS in dropout regions by specifically adjusting the slice tilt, the direction of the phase-encoding (PE), and the z-shim moment. However, optimal imaging parameters were only reported for the orbitofrontal cortex (OFC) and inferior temporal lobes. The present study determines the optimal slice tilt, PE direction, and z-shim moment at 3 T and 1.5 T, otherwise using standard fMRI acquisition parameters. Results are reported for all brain regions, yielding a whole-brain atlas of optimal parameters. At both field strengths, optimal parameters increase the BS by more than 60% in many voxels in the OFC and by at least 30% in the other dropout regions. BS gains are shown to be more widespread at 3 T, suggesting an increased benefit from the dropout compensation at higher fields. Even the mean BS of a large brain region, e.g., encompassing the medial OFC, can be increased by more than 15%. The maps of optimal parameters allow for assessing the feasibility and improving fMRI of brain regions affected by susceptibility-induced BS losses.

Auditory Processing across the Sleep-Wake Cycle: Simultaneous EEG and fMRI Monitoring in Humans

We combined fMRI and EEG recording to study the neurophysiological responses associated with auditory stimulation across the sleep-wake cycle. We found that presentation of auditory stimuli produces bilateral activation in auditory cortex, thalamus, and caudate during both wakefulness and nonrapid eye movement (NREM) sleep. However, the left parietal and, bilaterally, the prefrontal and cingulate cortices and the thalamus were less activated during NREM sleep compared to wakefulness. These areas may play a role in the further processing of sensory information required to achieve conscious perception during wakefulness. Finally, during NREM sleep, the left amygdala and the left prefrontal cortex were more activated by stimuli having special affective significance than by neutral stimuli. These data suggests that the sleeping brain can process auditory stimuli and detect meaningful events.

Event-Related fMRI with Simultaneous and Continuous EEG: Description of the Method and Initial Case Report

We report on the initial imaging findings with a new technique for the simultaneous and continuous acquisition of functional MRI data and EEG recording. Thirty-seven stereotyped interictal epileptiform discharges (spikes) were identified on EEG recorded continuously during the fMRI acquisition on a patient with epilepsy. Localization of the BOLD activation associated with the EEG events was consistent with previous findings and EEG source modeling. The time course of activation was comparable with the physiological hemodynamic response function (HRF). The new methodology could lead to novel and important applications in many areas of neuroscience.

Compensation of susceptibility-induced BOLD sensitivity losses in echo-planar fMRI imaging.

Gradient-echo echo-planar imaging is a standard technique in functional magnetic resonance imaging (fMRI) experiments based on the blood oxygenation level-dependent (BOLD) effect. A major problem is the occurrence of susceptibility gradients near air/tissue interfaces. As a consequence, the detection of neuronal activation may be greatly compromised in certain brain areas, especially in the temporal lobes and in the orbitofrontal cortex. Common approaches to overcome this problem, such as z-shimming or the use of tailored radio frequency pulses, usually compensate only for susceptibility gradients in the slice selection direction. In the present study, the influence of susceptibility gradients in the phase encoding direction is investigated both theoretically and experimentally. It is shown that these gradients influence the effective echo time TE and may reduce considerably the local BOLD sensitivity, even in the case of acceptable image intensities. A compensation method is proposed and tested in an fMRI experiment based on a hypercapnic challenge. The results suggest that the compensation method allows for the detection of activation in brain areas which are usually unavailable for BOLD studies.