Biomedical subjects

Timothy E J Behrens

Publications and source records attributed to Timothy E J Behrens.

15 recordsLinked to original sources

PubMed2006

Connectivity-based parcellation of human cortex using diffusion MRI: Establishing reproducibility, validity and observer independence in BA 44/45 and SMA/pre-SMA.

The identification of specialized, functional regions of the human cortex is a vital precondition for neuroscience and clinical neurosurgery. Functional imaging modalities are used for their delineation in living subjects, but these methods rely on subject cooperation, and many regions of the human brain cannot be activated specifically. Diffusion tractography is a novel tool to identify such areas in the human brain, utilizing underlying white matter pathways to separate regions of differing specialization. We explore the reproducibility, generalizability and validity of diffusion tractography-based localization in four functional areas across subjects, timepoints and scanners, and validate findings against fMRI and post-mortem cytoarchitectonic data. With reproducibility across modalities, clustering methods, scanners, timepoints, and subjects in the order of 80-90%, we conclude that diffusion tractography represents a useful and objective tool for parcellation of the human cortex into functional regions, enabling studies into individual functional anatomy even when there are no specific activation paradigms available.

Adult↗

PubMed2006

Optimal decision making and the anterior cingulate cortex.

Learning the value of options in an uncertain environment is central to optimal decision making. The anterior cingulate cortex (ACC) has been implicated in using reinforcement information to control behavior. Here we demonstrate that the ACC's critical role in reinforcement-guided behavior is neither in detecting nor in correcting errors, but in guiding voluntary choices based on the history of actions and outcomes. ACC lesions did not impair the performance of monkeys (Macaca mulatta) immediately after errors, but made them unable to sustain rewarded responses in a reinforcement-guided choice task and to integrate risk and payoff in a dynamic foraging task. These data suggest that the ACC is essential for learning the value of actions.

Animals↗

PubMed2006

Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data.

There has been much recent interest in using magnetic resonance diffusion imaging to provide information about anatomical connectivity in the brain, by measuring the anisotropic diffusion of water in white matter tracts. One of the measures most commonly derived from diffusion data is fractional anisotropy (FA), which quantifies how strongly directional the local tract structure is. Many imaging studies are starting to use FA images in voxelwise statistical analyses, in order to localise brain changes related to development, degeneration and disease. However, optimal analysis is compromised by the use of standard registration algorithms; there has not to date been a satisfactory solution to the question of how to align FA images from multiple subjects in a way that allows for valid conclusions to be drawn from the subsequent voxelwise analysis. Furthermore, the arbitrariness of the choice of spatial smoothing extent has not yet been resolved. In this paper, we present a new method that aims to solve these issues via (a) carefully tuned non-linear registration, followed by (b) projection onto an alignment-invariant tract representation (the "mean FA skeleton"). We refer to this new approach as Tract-Based Spatial Statistics (TBSS). TBSS aims to improve the sensitivity, objectivity and interpretability of analysis of multi-subject diffusion imaging studies. We describe TBSS in detail and present example TBSS results from several diffusion imaging studies.

Amyotrophic Lateral Sclerosis↗

PubMed2006

Applying FSL to the FIAC data: model-based and model-free analysis of voice and sentence repetition priming.

This article presents results obtained from applying various tools from FSL (FMRIB Software Library) to data from the repetition priming experiment used for the HBM'05 Functional Image Analysis Contest. We present analyses from the model-based General Linear Model (GLM) tool (FEAT) and from the model-free independent component analysis tool (MELODIC). We also discuss the application of tools for the correction of image distortions prior to the statistical analysis and the utility of recent advances in functional magnetic resonance imaging (FMRI) time series modeling and inference such as the use of optimal constrained HRF basis function modeling and mixture modeling inference. The combination of hemodynamic response function (HRF) and mixture modeling, in particular, revealed that both sentence content and speaker voice priming effects occurred bilaterally along the length of the superior temporal sulcus (STS). These results suggest that both are processed in a single underlying system without any significant asymmetries for content vs. voice processing.

Brain Mapping↗

PubMed2006

Just pretty pictures? What diffusion tractography can add in clinical neuroscience.

PURPOSE OF REVIEW: Diffusion tractography uses non-invasive brain imaging data to trace fibre bundles in the human brain in vivo. This raises immediate possibilities for clinical application but responsible use of this approach requires careful consideration of the scope and limitations of the technique. RECENT FINDINGS: To illustrate the potential for tractography to provide new information in clinical neuroscience we review recent studies in three broad areas: use of tractography for quantitative comparisons of specific white matter pathways in disease; evidence from tractography for the presence of qualitatively different pathways in congenital disorders or following recovery; use of tractography to gain insights into normal brain anatomy that can aid our understanding of the consequences of localised pathology, or guide interventions. SUMMARY: Diffusion tractography opens exciting new possibilities for exploring features of brain anatomy that previously were not visible to us in vivo.

Brain↗

PubMed2005

Quantitative investigation of connections of the prefrontal cortex in the human and macaque using probabilistic diffusion tractography.

The functions of prefrontal cortex (PFC) areas are constrained by their anatomical connections. There is little quantitative information about human PFC connections, and, instead, our knowledge of primate PFC connections is derived from tracing studies in macaques. The connections of subcortical areas, in which white matter penetration and hence diffusion anisotropy are greatest, can be studied with diffusion-weighted imaging (DWI) tractography. We therefore used DWI tractography in four macaque and 10 human hemispheres to compare the connections of PFC regions with nine subcortical regions, including several fascicles and several subcortical nuclei. A distinct connection pattern was identified for each PFC and each subcortical region. Because some of the fascicles contained connections with posterior cortical areas, it was also possible to draw inferences about PFC connection patterns with posterior cortical areas. Notably, it was possible to identify similar circuits centered on comparable PFC regions in both species; PFC regions probably engage in similar patterns of regionally specific functional interaction with other brain areas in both species. In the case of one area traditionally assigned to the human PFC, the pars opercularis, the distribution of connections was not reminiscent of any macaque PFC region but, instead, resembled the pattern for macaque ventral premotor area. Some limitations to the DWI approach were apparent; the high diffusion anisotropy in the corpus callosum made it difficult to compare connection probability values in the adjacent cingulate region.

Adult↗

PubMed2005

The evolution of prefrontal inputs to the cortico-pontine system: diffusion imaging evidence from Macaque monkeys and humans.

The cortico-ponto-cerebellar system is one of the largest projection systems in the primate brain, but in the human brain the nature of the information processing in this system remains elusive. Determining the areas of the cerebral cortex which contribute projections to this system will allow us to better understand information processing within it. Information from the cerebral cortex is conveyed to the cerebellum by topographically arranged fibres in the cerebral peduncle - an important fibre system in which all cortical outputs spatially converge on their way to the cerebellum via the pontine nuclei. Little is known of their anatomical organization in the human brain. New in vivo diffusion imaging and probabilistic tractography methods now offer a way in which input tracts in the cerebral peduncle can be characterized in detail. Here we use these methods to contrast their organization in humans and macaque monkeys. We confirm the dominant contribution of the cortical motor areas to the macaque monkey cerebral peduncle. However, we also present novel anatomical evidence for a relatively large prefrontal contribution to the human cortico-ponto-cerebellar system in the cerebral peduncle. These findings suggest the selective evolution of prefrontal inputs to the human cortico-ponto-cerebellar system.

Adult↗

PubMed2005

Self-navigated multishot echo-planar pulse sequence for high-resolution diffusion-weighted imaging.

Single-shot techniques have preferentially been adopted for diffusion-weighted imaging due to their reduced sensitivity to bulk motion. However, the limited spatial resolution achievable results in orientational signal averaging within voxels containing a distribution of fibers. This leads to impaired performance of tracking algorithms. To combat partial volume effects, high-resolution multishot techniques can be used but, being more sensitive to motion, require phase correction to obtain artifact-free images. While separately acquiring 2D navigator echoes is an effective approach, it is not very efficient as the navigators do not contribute signal to the final image. Here a self-navigated interleaved echo planar imaging (EPI) sequence based on EPI with keyhole (EPIK) is proposed. The refocusing reconstruction method is successfully adapted to EPIK and compared to the standard linear approach. The resultant improvement in resolution is shown to lead to a significant increase in anisotropy in fiber-branching areas and can potentially offer a superior ability to detect fine tract splits.

Algorithms↗

PubMed2005

Mixture models with adaptive spatial regularization for segmentation with an application to FMRI data.

Mixture models are often used in the statistical segmentation of medical images. For example, they can be used for the segmentation of structural images into different matter types or of functional statistical parametric maps (SPMs) into activations and nonactivations. Nonspatial mixture models segment using models of just the histogram of intensity values. Spatial mixture models have also been developed which augment this histogram information with spatial regularization using Markov random fields. However, these techniques have control parameters, such as the strength of spatial regularization, which need to be tuned heuristically to particular datasets. We present a novel spatial mixture model within a fully Bayesian framework with the ability to perform fully adaptive spatial regularization using Markov random fields. This means that the amount of spatial regularization does not have to be tuned heuristically but is adaptively determined from the data. We examine the behavior of this model when applied to artificial data with different spatial characteristics, and to functional magnetic resonance imaging SPMs.

Algorithms↗

PubMed2005

Connectivity of the human periventricular-periaqueductal gray region.

OBJECT: The periventricular gray (PVG) zone and its continuation, the periaqueductal gray (PAG) substance, have been targets for deep brain stimulation (DBS) in the alleviation of intractable pain for longer than two decades. Nevertheless, the anatomical connectivity of this region has been fairly poorly defined. The effects of DBS in this region are probably related to the release of endogenous endorphins, but until the connectivity of this region is better understood the mechanisms will remain unclear. METHODS: Diffusion tractography was used to trace the pathways of the PVG-PAG region in seven healthy human volunteers. Images were acquired with the aid of a 1.5-tesla magnetic resonance imaging system. The region of interest was located just lateral to the posterior commissure and extended caudally to the level of the superior colliculus. Probabilistic diffusion tractography was performed from each voxel in each patient's PVG-PAG region. The PVG-PAG region was found to yield descending projections to the spinal cord and cerebellum. Ascending projections to the thalamus and frontal lobes were also observed. CONCLUSIONS: These findings suggest that the PVG-PAG region may modulate pain by two mechanisms: one involving the antinociceptive system in the spinal cord and the other involving influences on the central pain network.

Afferent Pathways↗

PubMed2004

New approaches for exploring anatomical and functional connectivity in the human brain.

Information processing in the primate brain is based on the complementary principles of modular and distributed information processing. The former emphasizes the specialization of functions within different brain areas. The latter emphasizes the massively parallel nature of brain networks and the fact that function also emerges from the flow of information between brain areas. The localization of function to specific brain areas ("functional segregation") is the commonest approach to investigating function; however, an emerging, complementary approach ("functional integration") describes function in terms of the information flow across networks of areas. Here, we highlight recent advances in neuroimaging methodology that have made it possible to investigate the anatomical architecture of networks in the living human brain with diffusion tensor imaging (DTI). We also highlight recent thinking on the ways in which functional imaging can be used to characterize information transmission across networks in the human brain (functional and effective connectivity).

Animals↗

PubMed2004

Functional-anatomical validation and individual variation of diffusion tractography-based segmentation of the human thalamus.

Parcellation of the human thalamus based on cortical connectivity information inferred from non-invasive diffusion-weighted images identifies sub-regions that we have proposed correspond to nuclei. Here we test the functional and anatomical validity of this proposal by comparing data from diffusion tractography, cytoarchitecture and functional imaging. We acquired diffusion imaging data in eleven healthy subjects and performed probabilistic tractography from voxels within the thalamus. Cortical connectivity information was used to divide the thalamus into sub-regions with highest probability of connectivity to distinct cortical areas. The relative volumes of these connectivity-defined sub-regions correlate well with volumetric predictions based on a histological atlas. Previously reported centres of functional activation within the thalamus during motor or executive tasks co-localize within atlas regions showing high probabilities of connection to motor or prefrontal cortices, respectively. This work provides a powerful validation of quantitative grey matter segmentation using diffusion tractography in humans. Co-registering thalamic sub-regions from 11 healthy individuals characterizes inter-individual variation in segmentation and results in a population-based atlas of the human thalamus that can be used to assign likely anatomical labels to thalamic locations in standard brain space. This provides a tool for specific localization of functional activations or lesions to putative thalamic nuclei.

Adult↗

PubMed2004

Multilevel linear modelling for FMRI group analysis using Bayesian inference.

Functional magnetic resonance imaging studies often involve the acquisition of data from multiple sessions and/or multiple subjects. A hierarchical approach can be taken to modelling such data with a general linear model (GLM) at each level of the hierarchy introducing different random effects variance components. Inferring on these models is nontrivial with frequentist solutions being unavailable. A solution is to use a Bayesian framework. One important ingredient in this is the choice of prior on the variance components and top-level regression parameters. Due to the typically small numbers of sessions or subjects in neuroimaging, the choice of prior is critical. To alleviate this problem, we introduce to neuroimage modelling the approach of reference priors, which drives the choice of prior such that it is noninformative in an information-theoretic sense. We propose two inference techniques at the top level for multilevel hierarchies (a fast approach and a slower more accurate approach). We also demonstrate that we can infer on the top level of multilevel hierarchies by inferring on the levels of the hierarchy separately and passing summary statistics of a noncentral multivariate t distribution between them.

Bayes Theorem↗

PubMed2004

Constrained linear basis sets for HRF modelling using Variational Bayes.

FMRI modelling requires flexible haemodynamic response function (HRF) modelling, with the HRF being allowed to vary spatially and between subjects. To achieve this flexibility, voxelwise parameterised HRFs have been proposed; however, inference on such models is very slow. An alternative approach is to use basis functions allowing inference to proceed in the more manageable General Linear Model (GLM) framework. However, a large amount of the subspace spanned by the basis functions produces nonsensical HRF shapes. In this work we propose a technique for choosing a basis set, and then the means to constrain the subspace spanned by the basis set to only include sensible HRF shapes. Penny et al. showed how Variational Bayes can be used to infer on the GLM for FMRI. Here we extend the work of Penny et al. to give inference on the GLM with constrained HRF basis functions and with spatial Markov Random Fields on the autoregressive noise parameters. Constraining the subspace spanned by the basis set allows for far superior separation of activating voxels from nonactivating voxels in FMRI data. We use spatial mixture modelling to produce final probabilities of activation and demonstrate increased sensitivity on an FMRI dataset.

Bayes Theorem↗

PubMed2004

Advances in functional and structural MR image analysis and implementation as FSL.

The techniques available for the interrogation and analysis of neuroimaging data have a large influence in determining the flexibility, sensitivity, and scope of neuroimaging experiments. The development of such methodologies has allowed investigators to address scientific questions that could not previously be answered and, as such, has become an important research area in its own right. In this paper, we present a review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB). This research has focussed on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data. The majority of the research laid out in this paper has been implemented as freely available software tools within FMRIB's Software Library (FSL).

Bayes Theorem↗