Design, construction, and validation of an MRI-compatible vibrotactile stimulator intended for clinical use

Chakravarty, M. Mallar; Broadbent, Scott; Rosa‐Neto, Pedro; Lambert, Casey; Collins, D. Louis

doi:10.1016/j.jneumeth.2009.07.018

Cited by 21 publications

(24 citation statements)

References 30 publications

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“…For segmentation with the ANIMAL algorithm we use the nonlinear registration parameters previously validated [Chakravarty, b] and evaluated against other nonlinear registration methods [Chakravarty, ]. Briefly, this method involves a linear registration followed by a nonlinear registration focused on a region‐of‐interest limited predominantly to the subcortical structures and other noncortical anatomical structures (such as the corpus callosum and lateral ventricles) to help guide the nonlinear transformation estimation process.…”

Section: Methodsmentioning

confidence: 99%

Performing label-fusion-based segmentation using multiple automatically generated templates

et al. 2012

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Classically, model-based segmentation procedures match magnetic resonance imaging (MRI) volumes to an expertly labeled atlas using nonlinear registration. The accuracy of these techniques are limited due to atlas biases, misregistration, and resampling error. Multi-atlas-based approaches are used as a remedy and involve matching each subject to a number of manually labeled templates. This approach yields numerous independent segmentations that are fused using a voxel-by-voxel label-voting procedure. In this article, we demonstrate how the multi-atlas approach can be extended to work with input atlases that are unique and extremely time consuming to construct by generating a library of multiple automatically generated templates of different brains (MAGeT Brain). We demonstrate the efficacy of our method for the mouse and human using two different nonlinear registration algorithms (ANIMAL and ANTs). The input atlases consist a high-resolution mouse brain atlas and an atlas of the human basal ganglia and thalamus derived from serial histological data. MAGeT Brain segmentation improves the identification of the mouse anterior commissure (mean Dice Kappa values (κ = 0.801), but may be encountering a ceiling effect for hippocampal segmentations. Applying MAGeT Brain to human subcortical structures improves segmentation accuracy for all structures compared to regular model-based techniques (κ = 0.845, 0.752, and 0.861 for the striatum, globus pallidus, and thalamus, respectively). Experiments performed with three manually derived input templates suggest that MAGeT Brain can approach or exceed the accuracy of multi-atlas label-fusion segmentation (κ = 0.894, 0.815, and 0.895 for the striatum, globus pallidus, and thalamus, respectively).

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Section: Methodsmentioning

confidence: 99%

Performing label-fusion-based segmentation using multiple automatically generated templates

et al. 2012

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“…The atlas was then customized to the unique neuroanatomy of the subjects being studied using a region-of-interest non-linear registration estimation approach (Chakravarty et al, 2008, 2009b) that has been validated against manually defined gold-standards, intra-operative recordings, and brain activations recorded using functional magnetic resonance imaging techniques (Chakravarty et al, 2008, 2009a,b). All linear and non-linear transformations were estimated using the ANIMAL algorithm (Collins et al, 1994, 1995; Collins and Evans, 1997), which is part of the MINC suite of medical image processing tools 1 .…”

Section: Methodsmentioning

confidence: 99%

DISC1 and Striatal Volume: A Potential Risk Phenotype For mental Illness

et al. 2012

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Disrupted-in-schizophrenia 1 was originally discovered in a large Scottish family with abnormally high rates of severe mental illness, including schizophrenia, bipolar disorder, and depression. An accumulating body of evidence from genetic, postmortem, and animal data supports a role for DISC1 in different forms of mental illness. DISC1 may play an important role in determining structure and function of several brain regions. One brain region of particular importance for several mental disorders is the striatum, and DISC1 mutant mice have demonstrated an increase in dopamine (D2) receptors in this structure. However, association between DISC1 functional polymorphisms and striatal structure have not been examined in humans. We, therefore hypothesized that there would be a relationship between human striatal volume and DISC1 genotype, specifically in the Leu607Phe (rs6675281) and Ser704Cys (rs821618) single nucleotide polymorphisms. We tested our hypothesis by automatically identifying the striatum in 54 healthy volunteers recruited for this study. We also performed an exploratory analysis of cortical thickness, cortical surface area, and structure volume. Our results demonstrate that Phe allele carriers have larger striatal volume bilaterally (left striatum: p = 0.017; right striatum: p = 0.016). From the exploratory analyses we found that the Phe carriers also had larger left hemisphere volumes (p = 0.0074) and right occipital lobe surface area (p = 0.014) compared to LeuLeu homozygotes. However, these exploratory findings do not survive a conservative correction for multiple comparisons. Our findings demonstrate that a functional DISC1 variant influences striatal volumes. Taken together with animal data that this gene influences D2 receptor levels in striatum, a key risk pathway for mental illnesses such as schizophrenia and bipolar disorder may be conferred via DISC1’s effects on the striatum.

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“…Thalamic activations of vibrotactile stimuli have only been reported in a few awake human studies (Chakravarty et al, 2009a, b; Li Hegner et al, 2007) but are not generally detected in anesthetized animal models. For example, a PET study in awake humans showed that passive finger movement activated only the contralateral S1 and S2, whereas active finger movement activated the contralateral M, SMA, bilateral S2, and premotor cortex, in addition to the contralateral S1 (Mima et al, 1999).…”

Section: Discussionmentioning

confidence: 99%

BOLD fMRI of visual and somatosensory–motor stimulations in baboons

Wey

Szabó

et al. 2010

NeuroImage

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Baboon, with its large brain size and extensive cortical folding compared to other non-human primates, serves as a good model for neuroscience research. This study reports the implementation of a baboon model for blood oxygenation level-dependent (BOLD) fMRI studies (1.5 × 1.5 × 4 mm resolution) on a clinical 3 T-MRI scanner. BOLD fMRI responses to hypercapnic (5% CO 2 ) challenge, 10 Hz flicker visual, and vibrotactile somatosensory-motor stimulations were investigated in baboons anesthetized sequentially with isoflurane and ketamine. Hypercapnia evoked robust BOLD increases. Paralysis was determined to be necessary to achieve reproducible functional activations within and between subjects under our experimental conditions. With optimized anesthetic doses (0.8-1.0% isoflurane or 6-8 mg/kg/h ketamine) and adequate paralysis (vecuronium, 0.2 mg/kg), robust activations were detected in the visual (V), primary (S1) and secondary (S2) somatosensory, primary motor (M cortices), supplementary motor area (SMA), lateral geniculate nucleus (LGN) and thalamus (Th). Data were tabulated for 11 trials under isoflurane and 10 trials under ketamine on 5 baboons. S1, S2, M, and V activations were detected in essentially all trials (90-100% of the time, except 82% for S2 under isoflurane and 70% for M under ketamine).LGN activations were detected 64-70% of the time under both anesthetics. SMA and Th activations were detected 36-45% of the time under isoflurane and 60% of the time under ketamine. BOLD percent changes among different structures were slightly higher under ketamine than isoflurane (0.75% versus 0.58% averaging all structures), but none was statistically different (P>0.05). This baboon model offers an opportunity to non-invasively image brain functions and dysfunctions in large non-human primates.

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Design, construction, and validation of an MRI-compatible vibrotactile stimulator intended for clinical use

Cited by 21 publications

References 30 publications

Performing label-fusion-based segmentation using multiple automatically generated templates

Performing label-fusion-based segmentation using multiple automatically generated templates

DISC1 and Striatal Volume: A Potential Risk Phenotype For mental Illness

BOLD fMRI of visual and somatosensory–motor stimulations in baboons

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