16 research outputs found
Mapping degeneration of the visual system in long-term follow-up after childhood hemispherectomy - A series of four cases
OBJECTIVE: Although hemidisconnection surgery may eliminate or reduce seizure activity in patients with epilepsy, there are visual, cognitive and motor deficits which affect patients' function post-operatively, with varying severity and according to pathology. Consequently, there is a need to map microstructural changes over long time periods and develop/apply methods that work with legacy data. METHODS: In this study, we applied the novel single shell 3-Tissue method to data from a cohort of 4 patients who were scanned 20-years following childhood hemidisconnection surgery and presented with variable clinical outcomes. We have successfully reconstructed tractography of the whole visual pathway from single shell diffusion data with reduced number of gradient directions. RESULTS: All patients presented with degeneration of the visual system characterised by low fractional anisotropy and high mean diffusivity. There were no apparent microstructural differences between both optic nerves that could explain the different level of visual function across patients. However, we provide evidence suggesting an association between the level of visual function and DTI metrics within the remaining components of the visual system, particularly the optic tract, of the contralateral hemisphere post-surgery. SIGNIFICANCE: We believe this study suggests that diffusion MRI can be used to monitor the integrity of the visual system following hemispherectomy and if extended to larger cohorts and a greater number of time-points, including pre-surgically, can provide a clearer picture of the natural history of visual system degeneration. This knowledge may in turn help to identify patients at greatest risk of poor visual outcomes that might benefit from rehabilitation therapies
How our brains are wired: Are the applications of diffusion imaging useful given the current limitations?
Diffusion imaging (DI) enables researchers to study white matter (WM) pathways in the human brain in-vivo by labelling water molecules and measuring their diffusion into different directions. Connectivity patterns are inferred assuming that water diffuses rather along than across fibre bundles. This paper introduces the concept of DI, addresses suitable applications and evaluates gains versus limitations. Common applications are (1) generating WM atlases, (2) mapping connectional models of functionally subdivided brain regions, (3) linking disorders to connectivity abnormalities, (4) verifying WM pathways from animal studies, (5) linking personality traits to particular connectivity patterns, (6) measuring structural changes resulting from experience or ageing and (7) presurgical planning. Despite limitations like the moderate spatial resolution, or – more fundamentally – the lack of a gold standard and the kissing/crossing problem, DI can be regarded as a useful tool if researchers choose methods carefully and consider the known limitations
Simultaneous adaptive smoothing of relaxometry and quantitative magnetization transfer mapping
Attempts for in-vivo histology require a high spatial resolution that comes with the price of a decreased signal-to-noise ratio. We present a novel iterative and multi-scale smoothing method for quantitative Magnetic Resonance Imaging (MRI) data that yield proton density, apparent transverse and longitudinal relaxation, and magnetization transfer maps. The method is based on the propagation-separation approach. The adaptivity of the procedure avoids the inherent bias from blurring subtle features in the calculated maps that is common for non-adaptive smoothing approaches. The characteristics of the methods were evaluated on a high-resolution data set (500 μ isotropic) from a single subject and quantified on data from a multi-subject study. The results show that the adaptive method is able to increase the signal-to-noise ratio in the calculated quantitative maps while largely avoiding the bias that is otherwise introduced by spatially blurring values across tissue borders. As a consequence, it preserves the intensity contrast between white and gray matter and the thin cortical ribbon
Multiscale Exploration of Mouse Brain Microstructures Using the Knife-Edge Scanning Microscope Brain Atlas
Connectomics is the study of the full connection matrix of the brain. Recent advances in high-throughput, high-resolution 3D microscopy methods have enabled the imaging of whole small animal brains at a sub-micrometer resolution, potentially opening the road to full-blown connectomics research. One of the first such instruments to achieve whole-brain-scale imaging at sub-micrometer resolution is the Knife-Edge Scanning Microscope (KESM). KESM whole-brain data sets now include Golgi (neuronal circuits), Nissl (soma distribution), and India ink (vascular networks). KESM data can contribute greatly to connectomics research, since they fill the gap between lower resolution, large volume imaging methods (such as diffusion MRI) and higher resolution, small volume methods (e.g., serial sectioning electron microscopy). Furthermore, KESM data are by their nature multiscale, ranging from the subcellular to the whole organ scale. Due to this, visualization alone is a huge challenge, before we even start worrying about quantitative connectivity analysis. To solve this issue, we developed a web-based neuroinformatics framework for efficient visualization and analysis of the multiscale KESM data sets. In this paper, we will first provide an overview of KESM, then discuss in detail the KESM data sets and the web-based neuroinformatics framework, which is called the KESM brain atlas (KESMBA). Finally, we will discuss the relevance of the KESMBA to connectomics research, and identify challenges and future directions
CHIASM, the human brain albinism and achiasma MRI dataset
We describe a collection of T1-, diffusion- and functional T2*-weighted magnetic resonance imaging data from human individuals with albinism and achiasma. This repository can be used as a test-bed to develop and validate tractography methods like diffusion-signal modeling and fiber tracking as well as to investigate the properties of the human visual system in individuals with congenital abnormalities. The MRI data is provided together with tools and files allowing for its preprocessing and analysis, along with the data derivatives such as manually curated masks and regions of interest for performing tractography
Towards in vivo g-ratio mapping using MRI: unifying myelin and diffusion imaging
The g-ratio, quantifying the comparative thickness of the myelin sheath
encasing an axon, is a geometrical invariant that has high functional relevance
because of its importance in determining neuronal conduction velocity. Advances
in MRI data acquisition and signal modelling have put in vivo mapping of the
g-ratio, across the entire white matter, within our reach. This capacity would
greatly increase our knowledge of the nervous system: how it functions, and how
it is impacted by disease. This is the second review on the topic of g-ratio
mapping using MRI. As such, it summarizes the most recent developments in the
field, while also providing methodological background pertinent to aggregate
g-ratio weighted mapping, and discussing pitfalls associated with these
approaches. Using simulations based on recently published data, this review
demonstrates the relevance of the calibration step for three myelin-markers
(macromolecular tissue volume, myelin water fraction, and bound pool fraction).
It highlights the need to estimate both the slope and offset of the
relationship between these MRI-based markers and the true myelin volume
fraction if we are really to achieve the goal of precise, high sensitivity
g-ratio mapping in vivo. Other challenges discussed in this review further
evidence the need for gold standard measurements of human brain tissue from ex
vivo histology. We conclude that the quest to find the most appropriate MRI
biomarkers to enable in vivo g-ratio mapping is ongoing, with the potential of
many novel techniques yet to be investigated.Comment: Will be published as a review article in Journal of Neuroscience
Methods as parf of the Special Issue with Hu Cheng and Vince Calhoun as Guest
Editor
Automated Reconstruction of Neurovascular Networks in Knife-Edge Scanning Microscope Mouse and Rat Brain Nissl Stained Data Sets
The Knife-Edge Scanning Microscope (KESM), developed at the Brain Network
Laboratory at Texas A&M University, can image a whole small animal brain at sub-
micrometer resolution. Nissl data from the KESM enable us to look into vasculatures
and cell bodies at the same time. Hence, analyzing the images from KESM mouse
and rat Nissl data can help understand interactions between cerebral blood flow and its surrounding tissue. However, analysis is difficult since the image data contain
complex cellular features, as well as imaging artifacts, which make it hard to extract
the geometry of the vasculature and the cells.
In this project, we propose a novel approach to reconstructing the neurovascular networks from whole-brain mouse and partial rat Nissl data sets. The proposed method consists of (1) pre-processing, (2) thresholding, and (3) post-processing. Initially, we enhanced the raw image data in the pre-processing step. Next, we applied a dynamic global thresholding to ex-tract vessels in the thresholding step. Subsequently, in the post-processing step, we computed local properties of the connected components to remove various sources of noise and we applied artificial neural networks to extract vasculatures. Concurrently, the proposed method connected small and large discontinuities in the vascular traces.
To validate the performance of the proposed method, we compared reconstruction
results of the proposed method with an alternative method (Lim's method). The
comparison shows that the proposed method significantly outperforms (nine times
faster, and more robust to noise) Lim's method. As a consequence, the proposed
method provides a framework that can be applied to other data sets, even when
the images contain a large portion of low-contrast images across the image stacks.
We expect that the proposed method will contribute to studies investigating the
correlation between the soma of the cells and microvascular networks
High-Resolution Diffusion Tensor Imaging and Tractography of the Human Optic Chiasm at 9.4 T
The optic chiasm with its complex fiber micro-structure is a challenge for diffusion tensor models and tractography methods. Likewise, it is an ideal candidate for evaluation of diffusion tensor imaging tractography approaches in resolving inter-regional connectivity because the macroscopic connectivity of the optic chiasm is well known. Here, high-resolution (156 pm in-plane) diffusion tensor imaging of the human optic chiasm was performed ex vivo at ultra-high field (9.4 T). Estimated diffusion tensors at this high resolution were able to capture complex fiber configurations such as sharp curves, and convergence and divergence of tracts, but were unable to resolve directions at sites of crossing fibers. Despite the complex microstructure of the fiber paths through the optic chiasm, all known connections could be tracked by a line propagation algorithm. However, fibers crossing from the optic nerve to the contralateral tract were heavily underrepresented, whereas ipsilateral nerve-to-tract connections, as well as tract-to-tract connections, were overrepresented, and erroneous nerve-to-nerve connections were tracked. The effects of spatial resolution and the varying degrees of partial volume averaging of complex fiber architecture on the performance of these methods could be investigated. Errors made by the tractography algorithm at high resolution were shown to increase at lower resolutions closer to those used in vivo. This study shows that increases in resolution, made possible by higher field strengths, improve the accuracy of DTI-based tractography. More generally, post-mortem investigation of fixed tissue samples with diffusion imaging at high field strengths is important in the evaluation of MR-based diffusion models and tractography algorithms
Seuratun kappaleen poikkeuttaminen silmänräpäysten aikana: käyttäytymis- ja neuromagneettisia havaintoja
The visual world is perceived as continuous despite frequent interruptions of sensory data due to eyeblinks and rapid eye movements. To create the perception of constancy, the brain makes use of fill-in mechanisms. This study presents an experiment in which the location of an object during smooth pursuit tracking is altered during eyeblinks. The experiment investigates the effects of blink suppression and fill-in mechanisms to cloud the discrimination of these changes. We employed a motion-tracking task, which promotes the accurate evaluation of the object’s trajectory and thus can counteract the fill-in mechanisms. Six subjects took part in the experiment, during which they were asked to report any perceived anomalies in the trajectory. Eye movements were monitored with a video-based tracking and brain responses with simultaneous MEG recordings. Discrimination success was found to depend on the direction of the displacement, and was significantly modulated by prior knowledge of the triggered effect. Eye-movement data were congruent with previous findings and revealed a smooth transition from blink recovery to object locating. MEG recordings were analysed for condition-dependent evoked and induced responses; however, intersubject variability was too large for drawing clear conclusions regarding the brain basis of the fill-in mechanisms.Visuaalinen maailma koetaan jatkuvana, vaikka silmänräpäykset ja nopeat silmänliikkeet aiheuttavat keskeytyksiä sensoriseen tiedonkeruuseen. Luodakseen käsityksen pysyvyydestä, aivot käyttävät täyttömekanismeja. Tämä tutkimus esittelee kokeen, jossa kappaleen seurantaa hitailla seurantaliikkeillä häiritään muuttamalla sen sijaintia silmänräpäysten aikana. Tämä koe tutkii, kuinka silmänräpäysten aiheuttama suppressio ja täyttömekanismit sumentavat kykyä erotella näitä muutoksia. Käytimme liikeseurantatehtävää, joka vastaavasti edistää kappaleen liikeradan tarkkaa arviointia. Kuusi koehenkilöä osallistui kokeeseen, jonka aikana heitä pyydettiin ilmoittamaan kaikki havaitut poikkeamat kappaleen liikeradassa. Silmänliikkeitä tallennettiin videopohjaisella seurannalla, ja aivovasteita yhtäaikaisella MEG:llä. Erottelykyvyn todettiin riippuvan poikkeutuksen suunnasta, sekä merkittävästi a priori tiedosta poikkeutusten esiintymistavasta. Silmänliikedata oli yhtenevää aiempien tutkimusten kanssa, ja paljasti sujuvan siirtymisen silmänräpäyksistä palautumisesta kappaleen paikallistamiseen. MEG-tallenteet analysoitiin ehdollisten heräte- ja indusoitujen vasteiden löytämiseksi, mutta yksilölliset vaste-erot koehenkilöiden välillä olivat liian suuria selkeiden johtopäätösten tekemiseksi täyttömekanismien aivoperustasta