Temporal and spatial regulation of interneuron distribution in the developing cerebral cortex--an in vitro study

Cortical distribution of GABAergic interneurons is determined by migration time and brain size

Cortical interneurons (CINs) originate in the ganglionic eminences (GEs) and migrate tangentially to the cortex guided by different attractive and repulsive cues. Once inside the cortex, the cellular and molecular mechanisms determining the migration of CINs along the rostrocaudal axis are less well understood. Here, we investigated the cortical distribution of CINs originating in the medial and caudal GEs at different time points. Using molecular and genetic labeling, we showed that, in the mouse, early- and late-born CINs (E12 versus E15) are differentially distributed along the rostrocaudal axis. Specifically, late-born CINs are preferentially enriched in cortical areas closer to their respective sites of origin in the medial or caudal GE. Surprisingly, our in vitro experiments failed to show a preferential migration pattern along the rostrocaudal axis for medial- or caudal-born CINs. Moreover, in utero transplantation experiments suggested that the rostrocaudal dispersion of CINs depends on the developmental stage of the host brain and is limited by the migration time and the increasing size of the developing brain. These data suggest that the embryonic expansion of the cortex contributes to the rostrocaudal distribution of CINs.

Ex Utero Electroporation and Organotypic Slice Cultures of Embryonic Mouse Brains for Live-Imaging of Migrating GABAergic Interneurons

GABAergic interneurons (INs) are critical components of neuronal networks that drive cognition and behavior. INs destined to populate the cortex migrate tangentially from their place of origin in the ventral telencephalon (including from the medial and caudal ganglionic eminences (MGE, CGE)) to the dorsal cortical plate in response to a variety of intrinsic and extrinsic cues. Different methodologies have been developed over the years to genetically manipulate specific pathways and investigate how they regulate the dynamic cytoskeletal changes required for proper IN migration. In utero electroporation has been extensively used to study the effect of gene repression or overexpression in specific IN subtypes while assessing the impact on morphology and final position. However, while this approach is readily used to modify radially migrating pyramidal cells, it is more technically challenging when targeting INs. In utero electroporation generates a low yield given the decreased survival rates of pups when electroporation is conducted before e14.5, as is customary when studying MGE-derived INs. In an alternative approach, MGE explants provide easy access to the MGE and facilitate the imaging of genetically modified INs. However, in these explants, INs migrate into an artificial matrix, devoid of endogenous guidance cues and thalamic inputs. This prompted us to optimize a method where INs can migrate in a more naturalistic environment, while circumventing the technical challenges of in utero approaches. In this paper, we describe the combination of ex utero electroporation of embryonic mouse brains followed by organotypic slice cultures to readily track, image and reconstruct genetically modified INs migrating along their natural paths in response to endogenous cues. This approach allows for both the quantification of the dynamic aspects of IN migration with time-lapse confocal imaging, as well as the detailed analysis of various morphological parameters using neuronal reconstructions on fixed immunolabeled tissue.

Discovering Patterns in Brain Signals Using Decision Trees

Even with emerging technologies, such as Brain-Computer Interfaces (BCI) systems, understanding how our brains work is a very difficult challenge. So we propose to use a data mining technique to help us in this task. As a case of study, we analyzed the brain's behaviour of blind people and sighted people in a spatial activity. There is a common belief that blind people compensate their lack of vision using the other senses. If an object is given to sighted people and we asked them to identify this object, probably the sense of vision will be the most determinant one. If the same experiment was repeated with blind people, they will have to use other senses to identify the object. In this work, we propose a methodology that uses decision trees (DT) to investigate the difference of how the brains of blind people and people with vision react against a spatial problem. We choose the DT algorithm because it can discover patterns in the brain signal, and its presentation is human interpretable. Our results show that using DT to analyze brain signals can help us to understand the brain's behaviour.