Decreases in ADC observed in tissue areas during activation in the cat visual cortex at 9.4 T using high diffusion sensitization

Recent studies in the human visual cortex using diffusion-weighted functional magnetic resonance imaging (fMRI) have suggested that the apparent diffusion coefficient (ADC) decreases, in contrast to earlier studies that consistently reported ADC increases during neuronal activation. The changes, in either case, are hypothesized to provide the ability to improve the spatial specificity of fMRI over conventional blood-oxygenation-level-dependent (BOLD) methods. Most recently, the ADC decreases have been suggested as originating from transient cell swelling caused by either shrinkage of the extracellular space or some intracellular neuronal process that precedes the hemodynamic response. All of these studies have been conducted in humans and at lower magnetic fields, which can be limited by the signal-to-noise ratio (SNR). The low SNR can lead to significant partial-volume effects because of the lower spatial resolutions required to attain sufficient SNR in diffusion-weighted images. Human studies also have the potential confound of motion. At high magnetic fields and in animal model studies, these limitations are alleviated. At high fields, SNR increases, tissue signals are enhanced and signal changes inside the blood are significantly reduced compared to lower fields. In this work, we were able to measure a small but significant ADC decrease in tissue areas, in conjunction with brain activation in the cat visual cortex at 9.4 T when using highly diffusion-weighted images (b>1200 s/mm2) where intravascular effects are minimal. When using low b-values, delayed increases in the tissue ADC during activation were observed. No significant changes in ADC were observed in surface vessels for any diffusion weighting. Furthermore, we did not observe any temporal differences in the highly diffusion-weighted data compared to BOLD; however, although the changes may likely be vascular in nature, they are highly localized to the tissue areas.     

Spatial normalization, bulk motion correction and coregistration for functional magnetic resonance imaging of the human cervical spinal cord and brainstem

Functional magnetic resonance imaging (fMRI) of the cortex is a powerful tool for neuroscience research, and its use has been extended into the brainstem and spinal cord as well. However, there are significant technical challenges with extrapolating the developments that have been achieved in the cortex to their use in the brainstem and spinal cord. Here, we develop a normalized coordinate system for the cervical spinal cord and brainstem, demonstrating a semiautomated method for spatially normalizing and coregistering fMRI data from these regions. fMRI data from 24 experiments in eight volunteers are normalized and combined to create the first anatomical reference volume, and based on this volume, we define a standardized region-of-interest (ROI) mask, as well as a map of 52 anatomical regions, which can be applied automatically to fMRI results. The normalization is demonstrated to have an accuracy of less than 2 mm in 93% of anatomical test points. The reverse of the normalization procedure is also demonstrated for automatic alignment of the standardized ROI mask and region-label map with fMRI data in its original (unnormalized) format. A reliable method for spatially normalizing fMRI data is essential for analyses of group data and for assessing the effects of spinal cord injury or disease on an individual basis by comparing with results from healthy subjects.     

Distributed analysis of simultaneous EEG-fMRI time-series: modeling and interpretation issues

Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) represent brain activity in terms of a reliable anatomical localization and a detailed temporal evolution of neural signals. Simultaneous EEG-fMRI recordings offer the possibility to greatly enrich the significance and the interpretation of the single modality results because the same neural processes are observed from the same brain at the same time. Nonetheless, the different physical nature of the measured signals by the two techniques renders the coupling not always straightforward, especially in cognitive experiments where spatially localized and distributed effects coexist and evolve temporally at different temporal scales.     

Nonlinear statistical properties of fMRI signals in human visual cortex during resting-state

The purpose of the current work is to study nonlinear dynamics in neuronal activity within human brain visual cortex based on blood-oxygen-level dependent (BOLD) contrast imaging. In particular, based on functional magnetic resonance imaging (fMRI) signals, measures of fractality, complexity, and state disorder are estimated from central and peripheral eccentricity bands across three visual areas. Statistical results from analysis of 48750 resting-state fMRI signals show evidence that nonlinear dynamics of neuronal activity in resting-state in central and peripheral eccentricity bands of human visual cortex are persistent. However, they exhibit heterogeneous variability across eccentricity bands and visual areas. Also, information content in first visual area is more ordered than in the second one, whilst information content in the third visual area is the least ordered. These interesting nonlinear statistical properties are a further step toward understanding neuronal activity and nonlinear dynamics in human brain visual cortex.     

A new approach to estimating the signal dimension of concatenated resting-state functional MRI data sets

Estimating the effective signal dimension of resting-state functional MRI (fMRI) data sets (i.e., selecting an appropriate number of signal components) is essential for data-driven analysis. However, current methods are prone to overestimate the dimensions, especially for concatenated group data sets. This work aims to develop improved dimension estimation methods for group fMRI data generated by data reduction and grouping procedure at multiple levels. We proposed a “noise-blurring” approach to suppress intragroup signal variations and to correct spectral alterations caused by the data reduction, which should be responsible for the group dimension overestimation. This technique was evaluated on both simulated group data sets and in vivo resting-state fMRI data sets acquired from 14 normal human subjects during five different scan sessions. Reduction and grouping procedures were repeated at three levels in either “scan–session–subject” or “scan–subject–session” order. Compared with traditional estimation methods, our approach exhibits a stronger immunity against intragroup signal variation, less sensitivity to group size and a better agreement on the dimensions at the third level between the two grouping orders.     

Neural substrates of global perception are modulated by local element grouping

THE GLOBAL PERCEPTION OF HIERARCHICALLY ORGANIZED STIMULI CAN BE DIFFERENT FROM THE LOCAL PERCEPTION IN THAT GLOBAL RESPONSES ARE FASTER THAN LOCAL RESPONSES AND THE GLOBAL-TO-LOCAL INTERFERENCE IS STRONGER THAN THE RE-VERSE[1]. THIS GLOBAL PRECEDENCE EFF…     

Developments in active noise control sound systems for magnetic resonance imaging

Magnetic resonance imaging (MRI) scanners can produce noise measuring over 130 dB SPL. This noise stimulates the auditory nervous system, limiting the dynamic range for stimulus driven activity in functional MRI (fMRI) experiments and can influence other brain functions. Even for structural scans it causes subject anxiety and discomfort in addition to the impediment to communications. Here we describe the realization and validation of a sound system for sound presentation inside an MRI scanner and the modifications to a standard active noise control technique for use in the noisy and compact environment of the scanner. This paper provides a review of the technology available for the presentation of audio stimuli in an MRI environment and the modifications required for the active control of scanner noise. Some of the content has been previously published [Chambers J, Akeroyd MA, Summerfield AQ, Palmer AR. Active control of the volume acquisition noise in functional magnetic resonance imaging: method and psychoacoustical evaluation. J Acoust Soc Am 2001;110(6):3041-54; Levitt H. Transformed up-down methods in psychoacoustics. J Acoust Soc Am 1971;49:467-77], but this paper goes further in describing the stages of development as the system performance was optimised. The performance of the system and both the objective and subjective reduction of the scanner noise are reported. Finally, we discuss recent improvements to the system that are currently being evaluated and describe the theory of opto-acoustical transducers that operate on the principle of light modulation. These are immune from, and do not create, electro-magnetic interference (EMI) and radio-frequency interference (RFI).     

Finer discrimination of brain activation with local multivariate distance

The organization of human brain function is diverse on different spatial scales. Various cognitive states are always represented as distinct activity patterns across the specific brain region on fine scales. Conventional univariate analysis of functional MRI data seeks to determine how a particular cognitive state is encoded in brain activity by analyzing each voxel separately without considering the fine-scale patterns information contained in the local brain regions. In this paper, a local multivariate distance mapping (LMDM) technique is proposed to detect the brain activation and to map the fine-scale brain activity patterns. LMDM directly represents the local brain activity with the patterns across multiple voxels rather than individual voxels, and it employs the multivariate distance between different patterns to discriminate the brain state on fine scales. Experiments with simulated and real fMRI data demonstrate that LMDM technique can dramatically increase the sensitivity of the detection for the fine-scale brain activity patterns which contain the subtle information of the experimental conditions.     

一种用于fMRI的温度觉刺激装置的设计与验证

介绍了一种用于功能磁共振成像(f MRI)的温度觉刺激装置的设计与验证,该装置能够用于f MRI温度觉的脑功能研究,满足温度觉f MRI实验的自动化刺激要求.整个刺激装置设计了以微控制器为核心的控制电路,通过数据采集卡能够与上位机Lab VIEW软件进行数据通讯,并将获取的数据通过特定的串口协议传递给数字PID温控模块,实现对刺激端温度的精确调控.最后,使用该刺激装置对多名被试进行了温度觉的脑功能实验,实验结果验证了该设计的可行性.     

BOLD functional MRI in disease and pharmacological studies: room for improvement?

In the past decade the use of blood oxygen level-dependent (BOLD) fMRI to investigate the effect of diseases and pharmacological agents on brain activity has increased greatly. BOLD fMRI does not measure neural activity directly, but relies on a cascade of physiological events linking neural activity to the generation of MRI signal. However, most of the disease and pharmacological studies performed so far have interpreted changes in BOLD fMRI as "brain activation," ignoring the potential confounds that can arise through drug- or disease-induced modulation of events downstream of the neural activity. This issue is especially serious in diseases (like multiple sclerosis, brain tumours and stroke) and drugs (like anaesthetics or those with a vascular action) that are known to influence these physiological events. Here we provide evidence that, to extract meaningful information on brain activity in patient and pharmacological BOLD fMRI studies, it is important to identify, characterise and possibly correct these influences that potentially confound the results. We suggest a series of experimental measures to improve the interpretability of BOLD fMRI studies. We have ranked these according to their potential information and current practical feasibility. First-line, necessary improvements consist of (1) the inclusion of one or more control tasks, and (2) the recording of physiological parameters during scanning and subsequent correction of possible between-group differences. Second-line, highly recommended important aim to make the results of a patient or drug BOLD study more interpretable and include the assessment of (1) baseline brain perfusion, (2) vascular reactivity, (3) the inclusion of stimulus-related perfusion fMRI and (4) the recording of electrophysiological responses to the stimulus of interest. Finally, third-line, desirable improvements consist of the inclusion of (1) simultaneous EEG-fMRI, (2) cerebral blood volume and (3) rate of metabolic oxygen consumption measurements and, when relevant, (4) animal studies investigating signalling between neural cells and blood vessels.