Estimation of brain state changes associated with behavior, stimulation and epilepsy

Brain state dynamics vary at different spatiotemporal scales with behavior, stimulation, and disease, and may be unobserved (latent). Using a state-space model framework and subspace identification, we estimated spatiotemporally localized, latent state changes associated with the application of transcranial magnetic stimulation (TMS), to assess the effect of stimulation on brain state dynamics. State appeared to be modulated by behavior in a spatially-specific manner and small-amplitude state fluctuations were temporally locked to stimulus presentations. In addition, during and following TMS, an overall, bilateral and spatially nonspecific decrease in brain state was observed. We also estimated brain state changes during seizure evolution (independent of TMS), in focal and generalized seizures, which have very different epileptogenesis and propagation mechanisms, possibly resulting also in distinct spatiotemporal dynamics. Indeed, our preliminary results showed that in focal seizures, temporally localized dynamic state changes occur at least 1 min prior to seizure onset, with a decrease in steady-state followed by an increase which reaches a maximum during the ictal interval. In contrast, no such dynamic pattern was evident in state estimates during generalized seizures.

Large-scale mapping of mutations affecting zebrafish development

Background

Large-scale mutagenesis screens in the zebrafish employing the mutagen ENU have isolated several hundred mutant loci that represent putative developmental control genes. In order to realize the potential of such screens, systematic genetic mapping of the mutations is necessary. Here we report on a large-scale effort to map the mutations generated in mutagenesis screening at the Max Planck Institute for Developmental Biology by genome scanning with microsatellite markers.

Results

We have selected a set of microsatellite markers and developed methods and scoring criteria suitable for efficient, high-throughput genome scanning. We have used these methods to successfully obtain a rough map position for 319 mutant loci from the Tübingen I mutagenesis screen and subsequent screening of the mutant collection. For 277 of these the corresponding gene is not yet identified. Mapping was successful for 80 % of the tested loci. By comparing 21 mutation and gene positions of cloned mutations we have validated the correctness of our linkage group assignments and estimated the standard error of our map positions to be approximately 6 cM.

Conclusion

By obtaining rough map positions for over 300 zebrafish loci with developmental phenotypes, we have generated a dataset that will be useful not only for cloning of the affected genes, but also to suggest allelism of mutations with similar phenotypes that will be identified in future screens. Furthermore this work validates the usefulness of our methodology for rapid, systematic and inexpensive microsatellite mapping of zebrafish mutations.

Neuronal Modifications During Visuomotor Association Learning Assessed by Electric Brain Tomography

In everyday life specific situations need specific reactions. Through repetitive practice, such stimulus-response associations can be learned and performed automatically. The aim of the present EEG study was the illustration of learning dependent modifications in neuronal pathways during short-term practice of visuomotor associations. Participants performed a visuomotor association task including four visual stimuli, which should be associated with four keys, learned by trial and error. We assumed that distinct cognitive processes might be dominant during early learning e.g., visual perception and decision making. Advanced learning, however, might be indicated by increased neuronal activation in integration- and memory-related regions. For assessment of learning progress, visual- and movement-related brain potentials were measured and compared between three learning stages (early, intermediate, and late). The results have revealed significant differences between the learning stages during distinct time intervals. Related to visual stimulus presentation, Low Resolution Electromagnetic Brain Tomography (LORETA) revealed strong neuronal activation in a parieto-prefrontal network in time intervals between 100-400 ms post event and during early learning. In relation to the motor response neuronal activation was significantly increased during intermediate compared to early learning. Prior to the motor response (120-360 ms pre event), neuronal activation was detected in the cingulate motor area and the right dorsal premotor cortex. Subsequent to the motor response (68-430 ms post event) there was an increase in neuronal activation in visuomotor- and memory-related areas including parietal cortex, SMA, premotor, dorsolateral prefrontal, and parahippocampal cortex. The present study has shown specific time elements of a visuomotor-memory-related network, which might support learning progress during visuomotor association learning.

The role of the right dorsal premotor cortex in visuomotor learning: a transcranial magnetic stimulation study

To study the role of the right dorsal premotor cortex in visuomotor association learning (association of four visual stimuli to four buttons), transcranial magnetic stimulation was applied to this area to interfere with the ongoing learning processes. Two transcranial magnetic stimulation pulses to the right dorsal premotor cortex at 150 and 200 ms after onset of the imperative stimulus resulted in the abolishing of reaction time decreases during learning. Transcranial magnetic stimulation applied to a control region revealed no influence on reaction time decreases. During both conditions, however, there were similar increases of accuracy scores. We conclude that the right dorsal premotor cortex is not directly involved in associating visual with motor cues. We suggest that this area is intimately involved in selection and preparation of forthcoming movements.