Heidi Johansen-Berg

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 FMRIBs Software Library (FSL).

Characterization and propagation of uncertainty in diffusion-weighted MR imaging.

A fully probabilistic framework is presented for estimating local probability density functions on parameters of interest in a model of diffusion. This technique is applied to the estimation of parameters in the diffusion tensor model, and also to a simple partial volume model of diffusion. In both cases the parameters of interest include parameters defining local fiber direction. A technique is then presented for using these density functions to estimate global connectivity (i.e., the probability of the existence of a connection through the data field, between any two distant points), allowing for the quantification of belief in tractography results. This technique is then applied to the estimation of the cortical connectivity of the human thalamus. The resulting connectivity distributions correspond well with predictions from invasive tracer methods in nonhuman primate. Magn Reson Med 50:1077–1088, 2003.

Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging

Evidence concerning anatomical connectivities in the human brain is sparse and based largely on limited post-mortem observations. Diffusion tensor imaging has previously been used to define large white-matter tracts in the living human brain, but this technique has had limited success in tracing pathways into gray matter. Here we identified specific connections between human thalamus and cortex using a novel probabilistic tractography algorithm with diffusion imaging data. Classification of thalamic gray matter based on cortical connectivity patterns revealed distinct subregions whose locations correspond to nuclei described previously in histological studies. The connections that we found between thalamus and cortex were similar to those reported for non-human primates and were reproducible between individuals. Our results provide the first quantitative demonstration of reliable inference of anatomical connectivity between human gray matter structures using diffusion data and the first connectivity-based segmentation of gray matter.

Training induces changes in white-matter architecture

Although experience-dependent structural changes have been found in adult gray matter, there is little evidence for such changes in white matter. Using diffusion imaging, we detected a localized increase in fractional anisotropy, a measure of microstructure, in white matter underlying the intraparietal sulcus following training of a complex visuo-motor skill. This provides, to the best of our knowledge, the first evidence for training-related changes in white-matter structure in the healthy human adult brain.

Plasticity in gray and white: neuroimaging changes in brain structure during learning

Human brain imaging has identified structural changes in gray and white matter that occur with learning. However, ascribing imaging measures to underlying cellular and molecular events is challenging. Here we review human neuroimaging findings of structural plasticity and then discuss cellular and molecular level changes that could underlie observed imaging effects. Greater dialog between researchers in these different fields would help to facilitate cross-talk between cellular and systems level explanations of how learning sculpts brain structure.

The role of ipsilateral premotor cortex in hand movement after stroke

Movement of an affected hand after stroke is associated with increased activation of ipsilateral motor cortical areas, suggesting that these motor areas in the undamaged hemisphere may adaptively compensate for damaged or disconnected regions. However, this adaptive compensation has not yet been demonstrated directly. Here we used transcranial magnetic stimulation (TMS) to interfere transiently with processing in the ipsilateral primary motor or dorsal premotor cortex (PMd) during finger movements. TMS had a greater effect on patients than controls in a manner that depended on the site, hemisphere, and time of stimulation. In patients with right hemiparesis (but not in healthy controls), TMS applied to PMd early (100 ms) after the cue to move slowed simple reaction-time finger movements by 12% compared with controls. The relative slowing of movements with ipsilateral PMd stimulation in patients correlated with the degree of motor impairment, suggesting that functional recruitment of ipsilateral motor areas was greatest in the more impaired patients. We also used functional magnetic resonance imaging to monitor brain activity in these subjects as they performed the same movements. Slowing of reaction time after premotor cortex TMS in the patients correlated inversely with the relative hemispheric lateralization of functional magnetic resonance imaging activation in PMd. This inverse correlation suggests that the increased activation in ipsilateral cortical motor areas during movements of a paretic hand, shown in this and previous functional imaging studies, represents a functionally relevant, adaptive response to the associated brain injury.

Connectivity-Based Parcellation of Human Cingulate Cortex and Its Relation to Functional Specialization

Whole-brain neuroimaging studies have demonstrated regional variations in function within human cingulate cortex. At the same time, regional variations in cingulate anatomical connections have been found in animal models. It has, however, been difficult to estimate the relationship between connectivity and function throughout the whole cingulate cortex within the human brain. In this study, magnetic resonance diffusion tractography was used to investigate cingulate probabilistic connectivity in the human brain with two approaches. First, an algorithm was used to search for regional variations in the probabilistic connectivity profiles of all cingulate cortex voxels with the whole of the rest of the brain. Nine subregions with distinctive connectivity profiles were identified. It was possible to characterize several distinct areas in the dorsal cingulate sulcal region. Several distinct regions were also found in subgenual and perigenual cortex. Second, the probabilities of connection between cingulate cortex and 11 predefined target regions of interest were calculated. Cingulate voxels with a high probability of connection with the different targets formed separate clusters within cingulate cortex. Distinct connectivity fingerprints characterized the likelihood of connections between the extracingulate target regions and the nine cingulate subregions. Last, a meta-analysis of 171 functional studies reporting cingulate activation was performed. Seven different cognitive conditions were selected and peak activation coordinates were plotted to create maps of functional localization within the cingulate cortex. Regional functional specialization was found to be related to regional differences in probabilistic anatomical connectivity.

Polarity-Sensitive Modulation of Cortical Neurotransmitters by Transcranial Stimulation

Transcranial direct current stimulation (tDCS) modulates cortical excitability and is being used for human studies more frequently. Here we probe the underlying neuronal mechanisms by measuring polarity-specific changes in neurotransmitter concentrations using magnetic resonance spectroscopy (MRS). MRS provides evidence that excitatory (anodal) tDCS causes locally reduced GABA while inhibitory (cathodal) stimulation causes reduced glutamatergic neuronal activity with a highly correlated reduction in GABA, presumably due to the close biochemical relationship between the two neurotransmitters.

The left parietal and premotor cortices: motor attention and selection.

It is well established that the premotor cortex has a central role in the selection of movements. The role of parts of the parietal cortex in movement control has proved more difficult to describe but appears to be related to the preparation and the redirection of movements and movement intentions. We have referred to some of these processes as motor attention. It has been known since the time of William James that covert motor attention can be directed to an upcoming movement just as visuospatial attention can be directed to a location in space. While some parietal regions, particularly in the right hemisphere, are concerned with covert orienting and the redirecting of covert orienting it may be useful to consider other parietal regions, in the anterior inferior parietal lobule and in the posterior superior parietal lobule, particularly in the left hemisphere, as contributing to motor attention. Such parts of the parietal lobe are activated in neuroimaging experiments when subjects covertly prepare movements or switch intended movements. Lesions or transcranial magnetic stimulation (TMS) affect the redirecting of motor attention. The difficulties apraxic patients experience when sequencing movements may partly be due to an inability to redirect motor attention from one movement to another. The role of the premotor cortex in selecting movements is also lateralized to the left hemisphere. Damage to left hemisphere movement selection mechanisms may also contribute to apraxia. If, however, it remains intact after a stroke then the premotor cortex may contribute to the recovery of arm movements. A group of patients with unilateral left hemisphere lesions and impaired movements in the contralateral right hand was studied. Functional magnetic resonance imaging showed that in some cases the premotor cortex in the intact hemisphere was more active when the stroke-affected hand was used. TMS in the same area in the same patients had the most disruptive effect on movements. In summary, patterns of motor impairment and recovery seen after strokes can partly be explained with reference to the roles of the parietal and premotor cortices in motor attention and selection.

Distinct and Overlapping Functional Zones in the Cerebellum Defined by Resting State Functional Connectivity

The cerebellum processes information from functionally diverse regions of the cerebral cortex. Cerebellar input and output nuclei have connections with prefrontal, parietal, and sensory cortex as well as motor and premotor cortex. However, the topography of the connections between the cerebellar and cerebral cortices remains largely unmapped, as it is relatively unamenable to anatomical methods. We used resting-state functional magnetic resonance imaging to define subregions within the cerebellar cortex based on their functional connectivity with the cerebral cortex. We mapped resting-state functional connectivity voxel-wise across the cerebellar cortex, for cerebral-cortical masks covering prefrontal, motor, somatosensory, posterior parietal, visual, and auditory cortices. We found that the cerebellum can be divided into at least 2 zones: 1) a primary sensorimotor zone (Lobules V, VI, and VIII), which contains overlapping functional connectivity maps for domain-specific motor, somatosensory, visual, and auditory cortices; and 2) a supramodal zone (Lobules VIIa, Crus I, and II), which contains overlapping functional connectivity maps for prefrontal and posterior-parietal cortex. The cortical connectivity of the supramodal zone was driven by regions of frontal and parietal cortex which are not directly involved in sensory or motor processing, including dorsolateral prefrontal cortex and the frontal pole, and the inferior parietal lobule.