New aspects on the migration and differentiation of neural crest stem cells
s Neuroscience Research 68S (2010) e4 e52 e39 sues including neurons, glial cells, melanocytes and cranial mesenchymal tissues in distinct locations. In this study, we have identified ATF4, a basicleucine zipper transcription factor, as one of the neural crest EMT regulators. Although ATF4 alone was not sufficient to drive the formation of migratory neural crest cells, ATF4 cooperated with Sox9 to induce neural crest EMT by controlling the expression of cell cell and cell extracellular matrix adhesion molecules. This was likely, at least in part, by inducing the expression of Foxd3, which encodes another neural crest transcription factor. We also found that ATF4 protein level was strictly regulated by proteasomal degradation and p300 mediated stabilization, allowing ATF4 protein to accumulate in the nuclei of neural crest cells undergoing EMT. Thus, our results emphasize the importance of the regulation of protein stability in the neural crest EMT. doi:10.1016/j.neures.2010.07.414 S3 4 1 4 New aspects on the migration and differentiation of neural crest stem cells Shinsuke Shibata Hideyuki Okano Department of Physiology, Keio University Scool of Medicine, Tokyo, Japan A recent burst of findings including our reports has shown that neural crest derived stem cells (NCSCs) can be found in diverse mammalian tissues (Tomita et al. J Cell Biol. 2005; Yoshida et al. Stem Cells, 2006; Nagoshi et al. Cell Stem Cell, 2008; Nagoshi et al. J Cell Biochem. 2009; Morikawa et al. J. Exp Med. 2009; Morikawa et al. BBRC, 2009) These recent reports of ours and others could provide new insights on the origin, migration, and lineage potential of NCSCs from various mammalian tissue sources. In addition to the identification of NCSCs in tissues that are canonically known to be derived from the neural crest, recent studies have revealed NCSCs in tissues that are not specifically derived from the neural crest, such as bone marrow. NCSCs can express a wide range of characteristics, and the properties mainly depend on their tissue sources and the ontogenic stages of the animal. However, their underlying mechanisms remain unsolved. In this symposium, I would also like to present new data on the molecular characterization of NCSCs. doi:10.1016/j.neures.2010.07.415 S3 4 1 5 Gene environment interactions in enteric neural crest development: New ideas about preventing Hirschsprung disease Robert O. Heuckeroth Pediatrics, and Developmental Biology, Washington University School of Medicine The enteric nervous system (ENS) is a complex network of neurons and glia that controls most aspects of intestinal function. There are approximately 500 million neurons in 20 functional classes in the human ENS. All of these cells originate in the neural crest with the majority originating in the vagal region. Vagal crest derived precursor cells populate the entire bowel migrating in a proximal to distal direction. The molecular mechanisms that guide cell migration, control proliferation, regulate differentiation and then permit formation of a functional neuronal network are now partially understood. When these mechanisms fail, intestinal function is compromised, and in its most severe form the ENS is completely missing from the distal bowel, a problem called Hirschsprung disease. ENS development may also fail in many other ways resulting in poor motility and causing vomiting, severe constipation, growth failure, and early death. There are now many dozens of proteins that are known to control specific aspects of ENS development. Because of the elaborate molecular machinery that must cooperate for normal ENS morphogenesis, there are also many different genetic mechanisms that cause Hirschsprung disease in humans, or disrupt development in mouse models. We will discuss many of the signaling pathways required for enteric neural crest development and new data suggesting that non genetic factors, including vitamin A deficiency and specific medications may increase the risk of distal bowel aganglionosis. Because Hirschsprung disease is partially penetrant, these observations suggest that in some cases Hirschsprung disease might be prevented by optimizing maternal nutrition and judicious use of medicines. doi:10.1016/j.neures.2010.07.416 S3 4 2 1 How to design the high performance BMI by ECoG signals Tadashi Isa Department of Developmental Physiology, National Institute for Physiological Sciences Brain machine interface (BMI) uses cortical neural activity to decode the movements intended by the subject. Many lines of BMI studies use multichannel electrode arrays to record a large number of single neuron activity in monkeys and humans, however, they are generally invasive and unstable for long term recording. In this aspect, development of high performance BMI using electrocorticogram (ECoG) which is less invasive than the array, has been longed for, but for this purpose, it is important to know what kind of neuronal signal can be extracted from the ECoG. In this study, we tried simultaneous recording of high density multi channel ECoG signals and deep layer local field potentials in both the barrel cortex of anesthetized rats and the hand/arm region of the primary motor cortex (M1) of awake monkeys to study how to estimate the deeper layer neuron activity from the ECoG by clarifying the relationship between the two signals. For the ECoG recording, we used flexible ECoG net containing 32 channel electrodes, each of which was separated by 1 mm, made of palylene C. For the in depth recordings, we used either a Silicon probe 16 channel electrodes or self designed 16 channel electrodes with each exposure separated by 200 m. The correlation was estimated by a machine learning algorithm based on sparse logistic regression, a regression method with automatic relevance determination prior to discard irrelevant features for good generalization ability. The goodness of fit and the feasibility of such system in efficient decoding of whisker stimuli from the neural activity in the barrel cortex, and limb movements from the M1 activity will be discussed. doi:10.1016/j.neures.2010.07.417 S3 4 2 2 Cortical low frequency local field potentials and action potentials act as largely independent information channels Stefano Panzeri 1 Christoph Kayser 2, Nikos K. Logothetis 2 1 Robotics, Brain and Cognitive Sciences, Italian Institute of Technology 2 Max Planck Institute for Biological Cybernetics, Tuebingen, Germany Our recent worked has examined how the information encoded by the cerebral cortex is distributed across the range of temporal frequencies of its activity. We have investigated this issue by recording local field potentials and spiking activity from visual and auditory cortices of macaque monkeys during the presentation of naturalistic stimuli, and by analyzing these recordings with information theoretic methods. We found that the neural code is highly distributed along the temporal frequency range. Sensory information is encoded at two time scales at least: one slow scale, related to low frequency (less than 10 Hz) network fluctuations measured by the phase and power of low frequency LFPs; and one fast scale, related to spike times emitted with a precision of a few (or at most a few tens) of milliseconds. Neural responses at these different timescales encode different stimulus attributes, resulting in temporal multiplexing of sensory information. Multiplexing increases the encoding capacity of neural responses, enables disambiguation of stimuli that cannot be discriminated at a single response timescale, and makes sensory representations stable to the presence of variability in the sensory world. Thus, temporal multiplexing could be a key strategy used by the brain to form an information rich and stable representation of the environment. These findings have implications for the development of brain machine interfaces, because decoding based on multiple time scales can be used to enhance the amount of information that can be extracted by each single electrode. doi:10.1016/j.neures.2010.07.418 S3 4 2 3 Multi dimensional decoding in primate electrocorticograms Naotaka Fujii Laboratory for Adaptive Intelligence, BSI, RIKEN Decoding motor variables based on single unit activity has been the main stream of the Brain machine interface (BMI) research. The dominant approach in the research has been to decode those variables based on single unit activity (SUA) However, their invasive implementation suffers from high surgical risks and poor long term stability that required high maintenance cost for reliable daily performance. On the other hand, other less invasive recording techniques, such as ECoG, was widely considered
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