Uncovering a Role for the Dorsal Hippocampal Commissure in Recognition Memory.

The dorsal hippocampal commissure (DHC) is a white matter tract that provides interhemispheric connections between temporal lobe brain regions. Despite the importance of these regions for learning and memory, there is scant evidence of a role for the DHC in successful memory performance. We used diffusion-weighted magnetic resonance imaging (DW-MRI) and white matter tractography to reconstruct the DHC in both humans (in vivo) and nonhuman primates (ex vivo). Across species, our findings demonstrate a close consistency between the known anatomy and tract reconstructions of the DHC. Anterograde tract-tracer techniques also highlighted the parahippocampal origins of DHC fibers in nonhuman primates. Finally, we derived diffusion tensor MRI metrics from the DHC in a large sample of human subjects to investigate whether interindividual variation in DHC microstructure is predictive of memory performance. The mean diffusivity of the DHC correlated with performance in a standardized recognition memory task, an effect that was not reproduced in a comparison commissure tract-the anterior commissure. These findings highlight a potential role for the DHC in recognition memory, and our tract reconstruction approach has the potential to generate further novel insights into the role of this previously understudied white matter tract in both health and disease.

Hyperconnectivity in juvenile myoclonic epilepsy: a network analysis.

OBJECTIVE: Juvenile myoclonic epilepsy (JME) is a common idiopathic (genetic) generalized epilepsy (IGE) syndrome characterized by impairments in executive and cognitive control, affecting independent living and psychosocial functioning. There is a growing consensus that JME is associated with abnormal function of diffuse brain networks, typically affecting frontal and fronto-thalamic areas. METHODS: Using diffusion MRI and a graph theoretical analysis, we examined bivariate (network-based statistic) and multivariate (global and local) properties of structural brain networks in patients with JME (N = 34) and matched controls. Neuropsychological assessment was performed in a subgroup of 14 patients. RESULTS: Neuropsychometry revealed impaired visual memory and naming in JME patients despite a normal full scale IQ (mean = 98.6). Both JME patients and controls exhibited a small world topology in their white matter networks, with no significant differences in the global multivariate network properties between the groups. The network-based statistic approach identified one subnetwork of hyperconnectivity in the JME group, involving primary motor, parietal and subcortical regions. Finally, there was a significant positive correlation in structural connectivity with cognitive task performance. CONCLUSIONS: Our findings suggest that structural changes in JME patients are distributed at a network level, beyond the frontal lobes. The identified subnetwork includes key structures in spike wave generation, along with primary motor areas, which may contribute to myoclonic jerks. We conclude that analyzing the affected subnetworks may provide new insights into understanding seizure generation, as well as the cognitive deficits observed in JME patients.

The effects of elevated endogenous GABA levels on movement-related network oscillations.

The EEG/MEG signal is generated primarily by the summation of the post-synaptic potentials of cortical principal cells. At a microcircuit level, these glutamatergic principal cells are reciprocally connected to GABAergic interneurons and cortical oscillations are thought to be dependent on the balance of excitation and inhibition between these cell types. To investigate the dependence of movement-related cortical oscillations on excitation-inhibition balance, we pharmacologically manipulated the GABA system using tiagabine, which blocks GABA Transporter 1(GAT-1), the GABA uptake transporter and increases endogenous GABA activity. In a blinded, placebo-controlled, crossover design, in 15 healthy participants we administered either 15mg of tiagabine or a placebo. We recorded whole-head magnetoencephalograms, while the participants performed a movement task, prior to, one hour post, three hour post and five hour post tiagabine ingestion. Using time-frequency analysis of beamformer source reconstructions, we quantified the baseline level of beta activity (15-30Hz), the post-movement beta rebound (PMBR), beta event-related desynchronisation (beta-ERD) and movement-related gamma synchronisation (MRGS) (60-90Hz). Our results demonstrated that tiagabine, and hence elevated endogenous GABA levels causes, an elevation of baseline beta power, enhanced beta-ERD and reduced PMBR, but no modulation of MRGS. Comparing our results to recent literature (Hall et al., 2011) we suggest that beta-ERD may be a GABAA receptor mediated process while PMBR may be GABAB receptor mediated.

Combined EEG-fMRI and tractography to visualise propagation of epileptic activity.

In a patient with refractory temporal lobe epilepsy, EEG-fMRI showed activation in association with left anterior temporal interictal discharges, in the left temporal, parietal and occipital lobes. Dynamic causal modelling suggested propagation of neural activity from the temporal focus to the area of occipital activation. Tractography showed connections from the site of temporal lobe activation to the site of occipital activation. This demonstrates the principle of combining EEG-fMRI and tractography to delineate the pathways of propagation of epileptic activity.

Modelling cardiac signal as a confound in EEG-fMRI and its application in focal epilepsy studies.

Cardiac noise has been shown to reduce the sensitivity of functional Magnetic Resonance Imaging (fMRI) to an experimental effect due to its confounding presence in the blood oxygenation level-dependent (BOLD) signal. Its effect is most severe in particular regions of the brain and a method is yet to take it into account in routine fMRI analysis. This paper reports the development of a general and robust technique to improve the reliability of EEG-fMRI studies to BOLD signal correlated with interictal epileptiform discharges (IEDs). In these studies, ECG is routinely recorded, enabling cardiac effects to be modelled, as effects of no interest. Our model is based on an over-complete basis set covering a linear relationship between cardiac-related MR signal and the phase of the cardiac cycle or time after pulse (TAP). This method showed that, on average, 24.6 +/- 10.9% of grey matter voxels contained significant cardiac effects and 22.3 +/- 24.1% of those voxels exhibiting significantly IED-correlated BOLD signal also contained significant cardiac effects. We quantified the improvement of the TAP model over the original model, without cardiac effects, by evaluating changes in efficiency, with respect to estimating the contrast of the effects of interest. Over voxels containing significant, cardiac-related signal, efficiency was improved by 18.5 +/- 4.8%. Over the remaining voxels, no improvement was demonstrated. This suggests that, while improving sensitivity in particular regions of the brain, there is no risk that the TAP model will reduce sensitivity elsewhere.

fMRI temporal clustering analysis in patients with frequent interictal epileptiform discharges: comparison with EEG-driven analysis.

Temporal clustering analysis (TCA) is an exploratory data-driven technique that has been proposed for the analysis of resting fMRI to localise epileptiform activity without need for simultaneous EEG. Conventionally, fMRI of epileptic activity has been limited to those patients with subtle clinical events or frequent interictal epileptiform EEG discharges, requiring simultaneous EEG recording, from which a linear model is derived to make valid statistical inferences from the fMRI data. We sought to evaluate TCA by comparing the results with those of EEG correlated fMRI in eight selected cases. Cases were selected with clear epileptogenic localisation or lateralisation on the basis of concordant EEG and structural MRI findings, in addition to concordant activations seen on EEG-derived fMRI analyses. In three, areas of activation were seen with TCA but none corresponding to the electro-clinical localisation or activations obtained with EEG driven analysis. Temporal clusters were closely coincident with times of maximal head motion. We feel this is a serious confound to this approach and recommend that interpretation of TCA that does not address motion and physiological noise be treated with caution. New techniques to localise epileptogenic activity with fMRI alone require validation with an appropriate independent measure. In the investigation of interictal epileptiform activity, this is best done with simultaneous EEG recording.

Irreversible damage to the spinal cord following spinal anesthesia.

The authors report five patients with damage to the distal spinal cord following spinal anesthesia. The patients developed leg weakness and sensory disturbance. MRI of the lumbosacral spine showed an abnormal area of high signal within the conus medullaris in all patients. Symptoms and signs persisted at 1- to 2.5-year follow-ups. Incorrect needle placement and type of needle used are possible factors leading to spinal cord injury.

Screening for the beta-amyloid precursor protein mutation (APP717: Val----Ile) in extended pedigrees with early onset Alzheimer's disease.

Screening for the APP717 mutation in 5 further families with early onset Alzheimer's disease failed to reveal further cases with this variant. Screening a further 100 normal individuals for this mutation also failed to reveal further occurrences of this variant in the general population. Sequencing of exons 16 and 17 of the beta-amyloid precursor protein gene (the exons which encode the beta-amyloid fragment) in pedigree FAD4 revealed them to be of normal sequence. The significance of these observations to the genetics of Alzheimer's disease is discussed.