In humans, deletions/mutations in the CHL1/CALL gene are associated with mental retardation and schizophrenia. Juvenile CHL1-deficient (CHL1 À/À ) mice have been shown to display abnormally high numbers of parvalbumin-expressing (PV + ) hippocampal interneurons and, as adults, display behavioral traits observed in neuropsychiatric disorders. Here, we addressed the question whether inhibitory interneurons and synaptic plasticity in the CHL1 À/À mouse are affected during brain maturation and in adulthood. We found that hippocampal, but not neocortical, PV + interneurons were reduced with age in CHL1 À/À mice, from a surplus of +27% at 1 month to a deficit of -20% in adulthood compared with wild-type littermates. This loss occurred during brain maturation, correlating with microgliosis and enhanced interleukin-6 expression. In parallel with the loss of PV + interneurons, the inhibitory input to adult CA1 pyramidal cells was reduced and a deficit in short-and long-term potentiation developed at CA3-CA1 excitatory synapses between 2 and 9 months of age in CHL1 À/À mice.This deficit could be abrogated by a GABA A receptor agonist. We propose that region-specific aberrant GABAergic synaptic connectivity resulting from the mutation and a subsequently enhanced synaptic elimination during brain maturation lead to microgliosis, increase in pro-inflammatory cytokine levels, loss of interneurons, and impaired synaptic plasticity.

In a random number generation task, participants are asked to generate a random sequence of numbers, most typically the digits 1 to 9. Such number sequences are not mathematically random, and both extent and type of bias allow one to characterize the brain's “internal random number generator”. We assume that certain patterns and their variations will frequently occur in humanly generated random number sequences. Thus, we introduce a pattern-based analysis of random number sequences. Twenty healthy subjects randomly generated two sequences of 300 numbers each. Sequences were analysed to identify the patterns of numbers predominantly used by the subjects and to calculate the frequency of a specific pattern and its variations within the number sequence. This pattern analysis is based on the Damerau-Levenshtein distance, which counts the number of edit operations that are needed to convert one string into another. We built a model that predicts not only the next item in a humanly generated random number sequence based on the item′s immediate history, but also the deployment of patterns in another sequence generated by the same subject. When a history of seven items was computed, the mean correct prediction rate rose up to 27% (with an individual maximum of 46%, chance performance of 11%). Furthermore, we assumed that when predicting one subject′s sequence, predictions based on statistical information from the same subject should yield a higher success rate than predictions based on statistical information from a different subject. When provided with two sequences from the same subject and one from a different subject, an algorithm identifies the foreign sequence in up to 88% of the cases. In conclusion, the pattern-based analysis using the Levenshtein-Damarau distance is both able to predict humanly generated random number sequences and to identify person-specific information within a humanly generated random number sequence.

Background: Platelet-leukocyte aggregation (PLA) and platelet activation are found to be on the higher side in ischemic stroke patients. The correlation of PLA with clinical features has not been intensively investigated and the influence of genetic factors on PLA is still unexplored. The interaction of platelets with leukocytes is mainly determined by the proteins encoded by six genes: P-Selectin (SELP encodes CD62P) on the thrombocyte binding to P-Selectin-Glycoprotein-Ligand-1 (PSGL1) on the leukocyte, intracellular-adhesion-molecule 2 (ICAM2) interacting with Integrin alpha M (ITGAM) and Glycoprotein 1b-alpha (GP1BA) binding to Integrin alpha L (ITGAL). Methods: Seventy-nine patients with acute ischemic stroke and 151 controls without vascular disease from a single German center were enrolled. A neurologist and a neuroradiologist ascertained clinical and radiological features. PLA and platelet activation were analyzed using flow cytometry with various antibodies. Coding as well as tagging SNPs in six genes determining PLA were genotyped. Three groups of parameters were correlated with each other: (i) clinical and radiological parameters, (ii) laboratory parameters, (iii) genetic parameters. For the comparisons, robust nonparametric statistical tests were applicable. Results: PLA and platelet activation were higher in ischemic stroke patients compared to controls. Both, anticoagulant and antiplatelet treatment in the patient group affected platelet activation but not PLA. PLA correlated weakly with measures of stroke severity but not with thrombus length or stroke etiology. The association of SNP rs2228315 in the P-Selectin Glycoprotein Ligand-1-gene (PSGL1) with ischemic stroke and platelet activation was significant before correction for multiple testing while a trend was observed for the association with PLA. Regression analysis revealed that (i) platelet activation was an independent determinant of stroke, (ii) that PLA correlated with stroke, sex, age and platelet activation and (iii) that platelet activation correlated only with stroke. None of the SNPs survived in the regression analysis for stroke, PLA or platelet activation as dependent variables. Conclusions: The most important result of our study is that PLA and platelet activation are independent of other vascular risk factors correlated with stroke in our sample. In addition, we identified the missense SNP rs2228315 in the PSGL1-gene as a candidate polymorphism for ischemic stroke-related PLA. Association between this SNP and stroke as well as coronary artery disease has also been shown by two other studies.

Spatial attention is a lateralized feature of the human brain. Whereas the role of cortical areas of the nondominant hemisphere on spatial attention has been investigated in detail, the impact of the BG, and more precisely the subthalamic nucleus, on signs and symptoms of spatial attention is not well understood. Here we used unilateral deep brain stimulation of the subthalamic nucleus to reversibly, specifically, and intraindividually modify the neuronal BG outflow and its consequences on signs and symptoms of visuospatial attention in patients suffering from Parkinson disease. We tested 13 patients with Parkinson disease and chronic deep brain stimulation in three stimulation settings: unilateral right and left deep brain stimulation of the subthalamic nucleus as well as bilateral deep brain stimulation of the subthalamic nucleus. In all three stimulation settings, the patients viewed a set of pictures while an eye-tracker system recorded eye movements. During the exploration of the visual stimuli, we analyzed the time spent in each visual hemispace, as well as the number, duration, amplitude, peak velocity, acceleration peak, and speed of saccades. In the unilateral left-sided stimulation setting, patients show a shorter ipsilateral exploration time of the extrapersonal space, whereas number, duration, and speed of saccades did not differ between the different stimulation settings. These results demonstrated reduced visuospatial attention toward the side contralateral to the right subthalamic nucleus that was not being stimulated in a unilateral left-sided stimulation. Turning on the right stimulator, the reduced visuospatial attention vanished. These results support the involvement of the subthalamic nucleus in modulating spatial attention. Therefore, the subthalamic nucleus is part of the subcortical network that subserves spatial attention.

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