It is widely held that the frontal cortex plays a critical part in certain aspects of spatial and non-spatial working memory. One unresolved issue is whether there are functionally distinct subdivisions of the lateral frontal cortex that subserve different aspects of working memory. The present study used positron emission tomography (PET) to demonstrate that working memory processes within the human mid-dorsolateral and mid-ventrolateral frontal regions are organized according to the type of processing required rather than according to the nature (i.e. spatial or non-spatial), of the information being processed, as has been widely assumed. Two spatial working memory tasks were used which varied in the extent to which they required different executive processes. During a 'spatial span' task that required the subject to hold a sequence of five previously remembered locations in working memory a significant change in blood-flow was observed in the right mid-ventrolateral frontal cortex, but not in the anatomically and cytoarchitectonically distinct mid-dorsolateral frontal-lobe region. By contrast, during a '2-back' task that required the subject to continually update and manipulate an ongoing sequence of locations within working memory, significant blood flow increases were observed in both mid-ventrolateral and mid-dorsolateral frontal regions. When the two working memory tasks were compared directly, the one that emphasized manipulation of information within working memory yielded significantly greater activity in the right mid-dorsolateral frontal cortex only. This dissociation provides unambiguous evidence that the mid-dorsolateral and mid-ventrolateral frontal cortical areas make distinct functional contributions to spatial working memory and corresponds with a fractionation of working memory processes in psychological terms.

Time‐lapse diffusion‐weighted magnetic resonance imaging (DWI) was used to detect and characterize complex waves of cortical spreading depression (CSD) evoked with KCl placed upon the suprasylvian gyrus of anaesthetized cats. The time‐lapse representations successfully demonstrated primary CSD waves that propagated with elliptical wavefronts selectively over the ipsilateral cerebral hemispheres with a velocity of 3.8 ± 0.70 mm min−1 (mean ± s.e.m. of 5 experiments). In contrast, the succeeding secondary waves often remained within the originating gyrus, were slower (velocity 2.0 ± 0.18 mm min−1), more fragmented and varied in number. Computed traces of the apparent diffusion coefficients (ADCs) showed negative deflections followed by monotonic decays (amplitudes: primary wave, ‐19.9 ± 2.8 %; subsequent waves, ‐13.6 ± 1.9 %; duration at half‐maximal decay, 150‐200 s) when determined from regions of interest (ROIs) through which both primary and succeeding CSD waves propagated. The passage of both the primary and the succeeding waves often correlated with transient DC potential deflections recorded from the suprasylvian gyrus. The detailed waveforms of the ADC and the T2*‐weighted (blood oxygenation level‐dependent: BOLD) traces showed a clear reciprocal correlation. These imaging features that reflect disturbances in cellular water balance agree closely with BOLD measurements that followed the propagation velocities of the first and subsequent CSD events. They also provide a close physiological correlate for clinical observations of cortical blood flow disturbances associated with human migraine.

No abstract

Background:The hippocampus plays a central role in cognition, and understanding the specific contributions of its subregions will likely be key to explaining its wide-ranging functions. However, delineating substructures within the human hippocampus in vivo from magnetic resonance image scans is fraught with difficulties. To our knowledge, the extant literature contains only brief descriptions of segmentation procedures used to delineate hippocampal subregions in magnetic resonance imaging/functional magnetic resonance imaging studies.Methods:Consequently, here we provide a clear, step-by-step and fully illustrated guide to segmenting hippocampal subregions along the entire length of the human hippocampus on 3T magnetic resonance images.Results:We give a detailed description of how to segment the hippocampus into the following six subregions: dentate gyrus/Cornu Ammonis 4, CA3/2, CA1, subiculum, pre/parasubiculum and the uncus. Importantly, this in-depth protocol incorporates the most recent cyto- and chemo-architectural evidence and includes a series of comprehensive figures which compare slices of histologically stained tissue with equivalent 3T images.Conclusion:As hippocampal subregion segmentation is an evolving field of research, we do not suggest this protocol is definitive or final. Rather, we present a fully explained and expedient method of manual segmentation which remains faithful to our current understanding of human hippocampal neuroanatomy. We hope that this ‘tutorial’-style guide, which can be followed by experts and non-experts alike, will be a practical resource for clinical and research scientists with an interest in the human hippocampus.

Highlights20–30% of patients with refractory focal epilepsy have normal MRI scans.We evaluated the role of repeated MRI with better technology in detecting pathology.804 patients underwent MRI at 1.5T and subsequently at 3T with superior head coils.Relevant new diagnoses were made in 37 (5%) and affected patient management.Rescanning patients with focal epilepsy and previously normal MRI is beneficial.

No abstract

No abstract

PurposeHippocampal sclerosis, a common cause of refractory focal epilepsy, requires hippocampal volumetry for accurate diagnosis and surgical planning. Manual segmentation is time-consuming and subject to interrater/intrarater variability. Automated algorithms perform poorly in patients with temporal lobe epilepsy. We validate and make freely available online a novel automated method.MethodsManual hippocampal segmentation was performed on 876, 3T MRI scans and 202, 1.5T scans. A template database of 400 high-quality manual segmentations was used to perform automated segmentation of all scans with a multi-atlas–based segmentation propagation method adapted to perform label fusion based on local similarity to ensure accurate segmentation regardless of pathology. Agreement between manual and automated segmentations was assessed by degree of overlap (Dice coefficient) and comparison of hippocampal volumes.Key FindingsThe automated segmentation algorithm provided robust delineation of the hippocampi on 3T scans with no more variability than that seen between different human raters (Dice coefficients: interrater 0.832, manual vs. automated 0.847). In addition, the algorithm provided excellent results with the 1.5T scans (Dice coefficient 0.827), and automated segmentation remained accurate even in small sclerotic hippocampi. There was a strong correlation between manual and automated hippocampal volumes (Pearson correlation coefficient 0.929 on the left and 0.941 on the right in 3T scans).SignificanceWe demonstrate reliable identification of hippocampal atrophy in patients with hippocampal sclerosis, which is crucial for clinical management of epilepsy, particularly if surgical treatment is being contemplated. We provide a free online Web-based service to enable hippocampal volumetry to be available globally, with consequent greatly improved evaluation of those with epilepsy.