Motion capture studies show that American Sign Language (ASL) signers distinguish end-points in telic verb signs by means of marked hand articulator motion, which rapidly decelerates to a stop at the end of these signs, as compared to atelic signs (Malaia & Wilbur, in press). Non-signers also show sensitivity to velocity in deceleration cues for event segmentation in visual scenes (Zacks et al., 2010; Zacks et a., 2006), introducing the question of whether the neural regions used by ASL signers for sign language verb processing might be similar to those used by non-signers for event segmentation.
The present study investigated the neural substrate of predicate perception and linguistic processing in ASL. Observed patterns of activation demonstrate that Deaf signers process telic verb signs as having higher phonological complexity as compared to atelic verb signs. These results, together with previous neuroimaging data on spoken and sign languages (Shetreet, Friedmann, & Hadar, 2010; Emmorey et al., 2009), illustrate a route for how a prominent perceptual-kinematic feature used for non-linguistic event segmentation might come to be processed as an abstract linguistic feature due to sign language exposure.
sign language; ASL; fMRI; event structure; verb; neuroplasticity; motion
Deficits in visual perception and working memory are commonly observed in neuropsychiatric disorders and have been investigated using functional MRI. However, interpretation of differences in brain activation may be confounded with differences in task performance between groups. Differences in task difficulty across conditions may also pose interpretative issues in studies of visual processing in healthy subjects.
In order to address these concerns, the present study characterized brain activation in tasks which were psychometrically matched for difficulty. Functional magnetic resonance imaging (fMRI) was used to assess brain activation in ten healthy subjects during discrimination and working memory judgments for static and moving stimuli. For all task conditions, performance accuracy was matched at 70.7%.
Areas associated with V2 and V5 in the dorsal stream were activated during motion processing tasks and V4 in the ventral stream were activated during form processing tasks. Frontoparietal areas associated with working memory were also statistically significant during the working memory tasks.
Application of psychophysical methods to equate task demands provides a practical method to equate performance levels across conditions in fMRI studies, and to compare healthy and cognitively impaired groups at comparable levels of effort. These psychometrically matched tasks can be applied to patients with a variety of cognitive disorders to investigate dysfunction of multiple a priori defined brain regions. Measuring the changes in typical activation patterns in patients with these diseases can be useful for monitoring disease progression, evaluating new drug treatments, and possibly for developing methods for early diagnosis.
visual processing; fMRI; working memory; form; motion
To evaluate effects of combining functional MRI data acquired from different field strengths on group analysis as a function of the number of subjects at each field strength.
Materials and Methods
28 subjects (18 at 3T) participated in an auditory task of passively listening to a 0.75s segment of jazz music in an event-related design. Results of single-subject analysis were combined to create all possible subject combinations for a group size of 8 subjects from each of the 3T and 1.5T pools, comprising subject mixtures of (3T/1.5T) 0/8, 2/6, 4/4, 6/2 and 8/0. Group analysis performance of each subject permutation was measured by receiver operating characteristic (ROC) curves and activation overlap maps.
While area under ROC curves, extent of activation in the gold standard region and reliability of activation increased with the number of 3T subjects, marginal gain decreased. ROC performance overlap across mixtures was observed, indicating that some combinations of subjects markedly outperformed others. For detection of activation, 4/4 was arguably the minimum mixture level that was comparable to 3T-only group results.
Inclusion of 1.5T data does not necessarily reduce the validity of group analysis. Lower field strength data was found only to limit detection power, but did not affect specificity. Within the limits of realignment error, these results should also extend to group longitudinal analyses of subject mixtures from different field strengths.
fMRI; 1.5T; 3T; data analysis; ROC analysis
This paper describes the development of a patient-specific spine model through use of active contour segmentation and registration of intraoperative imaging of porcine vertebra augmented with kinematic constraints. The geometric active contours are fully automated and lead to a discrete representation of the image segmentation results. After determining errors within the segmentations, application of reliability theory allows the selection of active contour parameters to obtain best-fit segmentations from a stack of 2D images. The segmented images are then used in conjunction with C-arm fluoroscope images to simulate the result of intraoperative patient-specific model registration including patient and/or structure motion between preoperative and intraoperative scans. The results are validated through comparison of the error within the patient-specific model generated through use of the C-arm images with a model acquired directly from MRI images of the spine after motion. The results are applicable to the development of a wide variety of patient-specific geometric and biomechanical models.
Segmentation; template geometry; patient-specific model; spine; active contour; fluoroscopy; kinematic constraints; imaging; image error; registration
Reproducibility of three different aspects of fMRI activations—namely binary activation maps, effect size and spatial distribution of local maxima—was evaluated for an auditory sentence comprehension task with high attention demand on a group of 17 subjects that were scanned on five different occasions. While in the scanner subjects were asked to listen to series of six short everyday sentences from the CUNY sentence test. Comprehension and attention to the stimuli was monitored after each listen condition epoch by having subjects answer a series of multiple choice questions. Statistical maps of activation for the listen condition were computed at three different levels: overall results for all imaging sessions, group-level/single-session results for each of the five imaging occasions, and single-subject/single-session results computed for each subject and each scanning occasion independently. The experimental task recruited a distributed bilateral network with processing nodes located in lateral temporal cortex, inferior frontal cortex, medial BA6, medial occipital cortex and subcortical structures such as the putamen and the thalamus. Reproducibility of these activations at the group level was high (83.95% of the imaged volume was consistently classified as active/inactive across all five imaging sessions), indicating that sites of neuronal activity associated with auditory comprehension can reliably be detected with fMRI in healthy subjects, across repeated measures after group averaging. At the single-subject level reproducibility ranged from moderate to high, although no significant differences were found on behavioral measures across subjects or sessions. This result suggests that contextual differences—i.e., those specific to each imaging session, can modulate our ability to detect fMRI activations associated with speech comprehension in individual subjects.
fMRI; functional MRI; reliability; reproducibility; intraclass correlation coefficient; ratio of volume overlap; language; speech; auditory sentence comprehension
A confound for functional magnetic resonance imaging (fMRI), especially for auditory studies, is the presence of imaging acoustic noise generated mainly as a byproduct of rapid gradient switching during volume acquisition and to a lesser extent, the radio-frequency transmit. This work utilized a novel pulse sequence to present actual imaging acoustic noise for characterization of the induced hemodynamic responses and assessment of linearity in the primary auditory cortex with respect to noise duration. Results show that responses to brief duration (46ms) imaging acoustic noise is highly nonlinear while responses to longer duration (>1s) imaging acoustic noise becomes approximately linear, with the right primary auditory cortex exhibiting a higher degree of nonlinearity than the left for the investigated noise durations. This study also assessed the spatial extent of activation induced by imaging acoustic noise, showing that the use of modeled responses (specific to imaging acoustic noise) as the reference waveform revealed additional activations in the auditory cortex not observed with a canonical gamma variate reference waveform, suggesting an improvement in detection sensitivity for imaging acoustic noise-induced activity. Longer duration (1.5s) imaging acoustic noise was observed to induce activity that expanded outwards from Heschl’s gyrus to cover the superior temporal gyrus as well as parts of the middle temporal gyrus and insula, potentially affecting higher level acoustic processing.
imaging acoustic noise; functional MRI; hemodynamic response; linear systems
In this work, the architectures of three partially adaptive STAP algorithms are introduced, one of which is explored in detail, that reduce dimensionality and improve tractability over fully adaptive STAP when used in construction of brain activation maps in fMRI. Computer simulations incorporating actual MRI noise and human data analysis indicate that element space partially adaptive STAP can attain close to the performance of fully adaptive STAP while significantly decreasing processing time and maximum memory requirements, and thus demonstrates potential in fMRI analysis.
Element-space partially adaptively STAP; fMRI; image processing; space-time adaptive processing
Acoustic imaging noise produced during functional magnetic resonance imaging (fMRI) studies can hinder auditory fMRI research analysis by altering the properties of the acquired time-series data. Acoustic imaging noise can be especially confounding when estimating the time course of the hemodynamic response (HDR) in auditory event-related fMRI (fMRI) experiments. This study is motivated by the desire to establish a baseline function that can serve not only as a comparison to other quantities of acoustic imaging noise for determining how detrimental is one's experimental noise, but also as a foundation for a model that compensates for the response to acoustic imaging noise. Therefore, the amplitude and spatial extent of the HDR to the elemental unit of acoustic imaging noise (i.e., a single ping) associated with echoplanar acquisition were characterized and modeled. Results from this fMRI study at 1.5 T indicate that the group-averaged HDR in left and right auditory cortex to acoustic imaging noise (duration of 46 ms) has an estimated peak magnitude of 0.29% (right) to 0.48% (left) signal change from baseline, peaks between 3 and 5 s after stimulus presentation, and returns to baseline and remains within the noise range approximately 8 s after stimulus presentation.
Acoustic noise; auditory system; biomedical image processing; magnetic resonance imaging; modeling
To assess and model signal fluctuations induced by non-T1-related confounds in variable repetition time fMRI and to develop a compensation procedure to correct for the non-T1- related artifacts.
Materials and Methods
Radio-frequency disabled volume gradient sequences were effected at variable offsets between actual image acquisitions, enabling perturbation of the measurement system without perturbing longitudinal magnetization, allowing the study of non-T1-related confounds that may arise in variable TR experiments. Three imaging sessions utilizing a daily quality assurance (DQA) phantom were conducted to assess the signal fluctuations, which were then modeled as a second order system. A modified projection procedure was implemented to correct for signal fluctuations arising from non-T1-related confounds, and statistical analysis was performed to assess the significance of the artifacts with and without compensation.
Assessment using phantom data reveals that the signal fluctuations induced by non-T1- related confounds was consistent in shape across the phantom and well-modeled by a second order system. The phantom exhibited significant spurious detections (at p < 0.01) almost uniformly across the central slices of the phantom. Second-order system modeling and compensation of non-T1-related confounds achieves significant reduction of spurious detection of fMRI activity in a phantom.
variable TR; non-T1-related artifacts; eddy currents; gradient coil heating
Multiple sclerosis (MS) is a chronic disabling disorder histopathologically characterized by inflammation, demyelination and axonal loss. Conventional MRI has made most contributions to the diagnosis of MS. However, it is not sufficiently sensitive and specific to reveal the extent and severity of the damage in the disease. Other nuclear magnetic resonance (NMR) techniques including magnetic resonance spectroscopy, magnetization transfer imaging, diffusion weighted and diffusion tensor imaging, and functional MRI have provided additional information that improves the diagnosis and understanding of MS. Optical techniques including optical coherence tomography (OCT) and coherent anti-Stokes Raman scattering (CARS) microscopy have shown promise in diagnosis and mechanistic study of myelin diseases.
To review new imaging techniques and their potential in diagnosis of MS.
The principles of three imaging techniques (MRI, OCT and CARS) and their applications to MS studies are described. Their advantages and disadvantages are compared.
Conventional MRI remains a critical tool in the diagnosis of MS. Alternative NMR/MRI techniques have improved specificity for the detection of lesions and provided more quantitative information about MS. Optical techniques including OCT and CARS microscopy are opening up new ways for diagnosis and mechanistic study of myelin diseases.
coherent anti-Stokes Raman scattering microscopy; magnetic resonance imaging; multiple sclerosis; optical coherence tomography