The Cortico-Basal Ganglia-Cerebellar Network: Past, Present and Future Perspectives

Diffusion-weighted (DW) MR images contain information about the orientation of brain white matter fibres that potentially can be used to study human brain connectivity in vivo using tractography techniques. Currently, the diffusion tensor model is widely used to extract fibre directions from DW-MRI data, but fails in regions containing multiple fibre orientations. The spherical deconvolution technique has recently been proposed to address this limitation. It provides an estimate of the fibre orientation distribution (FOD) by assuming the DW signal measured from any fibre bundle is adequately described by a single response function. However, the deconvolution is ill-conditioned and susceptible to noise contamination. This tends to introduce artefactual negative regions in the FOD, which are clearly physically impossible. In this study, the introduction of a constraint on such negative regions is proposed to improve the conditioning of the spherical deconvolution. This approach is shown to provide FOD estimates that are robust to noise whilst preserving angular resolution. The approach also permits the use of super-resolution, whereby more FOD parameters are estimated than were actually measured, improving the angular resolution of the results. The method provides much better defined fibre orientation estimates, and allows orientations to be resolved that are separated by smaller angles than previously possible. This should allow tractography algorithms to be designed that are able to track reliably through crossing fibre regions.

Time is a fundamental dimension of life. It is crucial for decisions about quantity, speed of movement and rate of return, as well as for motor control in walking, speech, playing or appreciating music, and participating in sports. Traditionally, the way in which time is perceived, represented and estimated has been explained using a pacemaker-accumulator model that is not only straightforward, but also surprisingly powerful in explaining behavioural and biological data. However, recent advances have challenged this traditional view. It is now proposed that the brain represents time in a distributed manner and tells the time by detecting the coincidental activation of different neural populations.

Early anatomically based models of language consisted of an arcuate tract connecting Broca's speech and Wernicke's comprehension centers; a lesion of the tract resulted in conduction aphasia. However, the heterogeneous clinical presentations of conduction aphasia suggest a greater complexity of perisylvian anatomical connections than allowed for in the classical anatomical model. This article re-explores perisylvian language connectivity using in vivo diffusion tensor magnetic resonance imaging tractography. Diffusion tensor magnetic resonance imaging data from 11 right-handed healthy male subjects were averaged, and the arcuate fasciculus of the left hemisphere reconstructed from this data using an interactive dissection technique. Beyond the classical arcuate pathway connecting Broca's and Wernicke's areas directly, we show a previously undescribed, indirect pathway passing through inferior parietal cortex. The indirect pathway runs parallel and lateral to the classical arcuate fasciculus and is composed of an anterior segment connecting Broca's territory with the inferior parietal lobe and a posterior segment connecting the inferior parietal lobe to Wernicke's territory. This model of two parallel pathways helps explain the diverse clinical presentations of conduction aphasia. The anatomical findings are also relevant to the evolution of language, provide a framework for Lichtheim's symptom-based neurological model of aphasia, and constrain, anatomically, contemporary connectionist accounts of language.