November 19, 2015 16:00 - 17:00
BSI Central Building 1F Seminar Room
"Adult hippocampal neurogenesis in natural populations of mammals: is more always better?"
Adult neurogenesis in the mammalian hippocampus (AHN) has remained enigmatic. Denied for a long time and then enthusiastically accepted in the late nineties (and massively promoted since) two lines of research have emerged. One is focusing on adult neurogenesis as a repair mechanism, the other one on analyzing its physiological role, chiefly in cognitive processes. The main problems of the latter approach are inappropriate statistical analysis, selective choice of behavioral tests and lack of studies in which individual variation of AHN is correlated with individual behavioral measurements.
AHN can be found in most mammalian species but its expression is highly variable. Species with the lowest level of expression are primates and many small bats, while shrews can switch off AHN completely after the first hibernation.. Levels of AHN appear high in some rodents showing a daily turnover rate of up to 1.5% of dentate granule cells, counterbalanced by increased apoptosis. A general finding is that AHN declines substantially and exponentially during lifetime. Finally, some of the most popularized phenomena in AHN, the increase after running shown to increase mouse cognition, could not be demonstrated in wild-living rodent species.
Therefore, it is legitimate to ask what benefit is associated with the reduction of AHN observed thus far in most species. In terms of lifespan biology, we propose that long-term reduction of AHN might be one of the brain processes stabilizing acquired behavioral traits optimized for the environment and ecology of the respective species, and is thus a widespread mammalian trait depending on natural selection for an optimal reserve for AHN capacity. On the other hand, temporary increase of AHN may reflect a mechanism for breaking acquired adult routines and habits in rapidly changing environments, enabling learning of new routines that may then be “fixed” by local down-regulation of AHN again. Finally, the genetic (and epigenetic) regulation of developmental stages of newly born granule cells might be another mechanism providing the necessary flexibility yet independent of proliferation rate.
"The analysis of spontaneous and cognitive behavior of group-housed mice in IntelliCage: from automated data collection to automated data analysis"
Intellicages are large homecages housing groups of up to 16 transponder-chipped mice. Each cage contains four learning corners wherein identified mice can be trained for a variety of operant procedures, discrimination learning and spatial patrolling patterns using reward or punishment by air-puffs. Graphic set-up files allow for an almost unlimited set of procedures assessing impulsivity, cognitive abilities, behavioral flexibility and social interactions. All actions of the system and the mice are stored and results displayed graphically during ongoing testing. However, the enormous amount of data generated needs to be extracted and prepared for appropriate statistical analysis. Up to now, there has been no software to achieve rapid data analysis. Here we present a novel software (FlowR), which extracts raw data from IntelliCage data files matching the set-up files for experiments. Using a graphic interface to combine statistical R-routines taken from public libraries, the collected data can be analyzed a few minutes after termination of the experiment, producing publication-ready tabulated and graphic output for expert multivariate statistics of spontaneous and conditioned behavior, even including Markov chains showing social dependencies in task solving. Thus, the combination of IntelliCage and experiment-specific analysis software provides the most powerful single-apparatus system to assess nearly all aspects of mouse behavior and cognition. In practical terms, the system and automated software quickly recognize whether a genetic or pharmacological treatment has an effect on behavior or not, allowing to decide which experimental models should be selected for further investigation.
- Open to Public
- Shigeyoshi Itohara [Shigeyoshi Itohara, Behavioral Genetics ]
Name: Shigeyoshi Itohara