Transcriptional Regulation of TelencephalonDevelopment
Prof. John Rubenstein
University of California at San Francisco
John Rubenstein, MD, Phd is a Professor in the Department of Psychiatry at the University of California San Francisco. His research focuses on the regulatory genes that orchestrate development of the forebrain.In the mammalian embryo, the forebrain is the portion of the neural tube where primitive cells are organized to form the cerebral cortex, the basal ganglia and other components of the adult brain -- the structures of the human brain most involved in key functions such as speech, language, cognition and fine motor skills.
The Molecular Logic of Neural Circuits: Implications for Autism and Schizophrenia
Prof. Thomas Südhof
Stanford University School of Medicine, Howard Hughes Medical Institute, USA
Thomas Südhof is interested in how synapses are formed and function during development and in the adult. His work focuses on the role of synaptic cell-adhesion molecules in shaping synapse properties, on pre- and postsynaptic mechanisms of membrane traffic, and on impairments in synapse formation and function in neuropsychiatric disorders. To address these questions, Südhof's laboratory employs approaches ranging from biophysical and biochemical studies to the physiological and behavioral analyses of mutant mice and the in vitro derivation of human neurons.
Regulation and Function of Adult Neurogenesis in the Mammalian Hippocampus
Prof. Fred H. Gage
The Salk Institute, Laboratory of Genetics, USA
Fred H. Gage, a professor in the Laboratory of Genetics, concentrates on the adult central nervous system and unexpected plasticity and adaptability to environmental stimulation that remains throughout the life of all mammals. Gage's lab showed that, contrary to accepted dogma, human beings are capable of growing new nerve cells throughout life. Small populations of immature nerve cells are found in the adult Human brain, a process called Neurogenesis. Gage is working to understand how these cells can be induced to become mature functioning nerve cells in the adult brain and spinal cord. They showed that environmental enrichment and physical exercise can enhance the growth of new brain cells and they are studying the underlying cellular and molecular mechanisms of neurogenesis.
Life at the Single Molecule Level: Imaging and Sequencing Individual Molecules in Single Cells
Department of Chemistry and Chemical Biology, Harvard University, UAS
Recent advances in single-molecule imaging in living cells allow quantitative and system-wide descriptions of gene expression and regulation with single molecule sensitivity. It was found that low probability events of single molecules can have important biological consequences, such as the change of a cellular phenotype.? This has everything to do with the fact that DNA are single molecules in individual cells. Meanwhile, recent advances in high throughput DNA sequencing have allowed sequencing the genome and transcriptome of a single human cell. The combination of single molecule and single cell imaging and sequencing offers exciting possibilities for biology.
Reverse engineering the brain: what tools do we need?
Imaging functional signals in explant tissues and living animals has greatly benefited from specific properties of two-photon excitation, its longer excitation wavelength and the confinement of exciation to the focal region. This has, for example allowed the study of dendritic computation that occurs in retinal interneurons during the presentation of moving stimuli. Ultimately, however, understanding computation in neural tissue will require a much better understanding of neural circuit diagrams. We are, therefore, working on methods to reconstruct tissue structure at the nanometer level but over volumes sufficiently large to contain local circuits in their entirety. Serial blockface scanning electron microcopy (SBFSEM) combines cutting and imaging processes. This avoids registration errors, loss of sections, and allows complete automation of data generation. With SBFSEM we can acquire data at 25 nm section thickness and have developed staining protocols that enhance cell boundaries. This helps the automation of data segmentation, for which we use various machine-learning approaches.