However, what intrigued me about the invitation, and why I ultimately agreed to help with the start of the Journal of Sport and Health Science (JSHS), was the fact that health and sport science research has remained geographically isolated. Thousands of health and sport

sciences manuscripts are published every year in China, but they remain inaccessible to the rest of the world because of the language barrier. I am aware of several other countries with a great tradition in the health and sport sciences area, Korea and Brazil come to mind, where I have encountered top rate research first hand, but because of the language barrier, these works are condemned Roxadustat purchase to obscurity in the international field of science. One of the goals of JSHS is to make the journal truly international, and to have an impact worldwide. Because it is published in China, we have the unique opportunity to capture much of the research performed in Asia in addition to the more traditional health and sport sciences research originating in Europe and North America, and other parts of the globe. In order to achieve this goal, it will be necessary to have excellent editorial staff that can help in overcoming geographical and language barriers. One of my main points at the recent

editorial board meeting was that we need to implement first-class help with English writing so that no manuscript fails because of language. Another GDC-0199 mouse strategy we will employ is to identify leaders in health and sport sciences from scientifically underrepresented countries, who are willing to help and contribute to

the journal so that geographic barriers are eliminated. This is an ongoing process, and input from Australia/New Zealand, South America, and Asia (other than China and Japan) is required. In time, we need to strike the right balance for true global representation. Your input in this quest is highly appreciated click here and any suggestions you may have are welcome and will receive serious consideration. We are committed to make JSHS a leading journal in the field. Needless to say that a scientific journal is only as good as the research it publishes, and ultimately the publications can only reflect what is submitted to the journal. Therefore, we invite all of you to be active contributors to JSHS. We guarantee an excellent turnaround and constructive reviews of your work. We are here to help and our philosophy is to make every submitted manuscript the best it can be. Thank you for considering JSHS for your next contribution! “
“Up to this day I still can vividly remember a routine in my elementary school: the daily school-wide morning calisthenics. It started at about 7:45 am in the school courtyard. Our physical education teacher stood on the concrete stage where our principal would give her talk at school assemblies.

e., laminar) fMRI could potentially be used to address such questions. The six cortical layers have different distributions of cell types, cell sizes, connectivity, energy use, etc., reflecting the different functions of the layers. For instance, Bleomycin supplier input to a cortical area typically arrives in layer IV, while output is typically generated in layer V. In primary visual

cortex (V1), the different stimulus selectivity of the layers, e.g., the magno- and parvocellular pathways, is well known (Callaway, 1998). The relative thickness of the layers also varies for different cortical areas depending on the function of the area. If these anatomical and functional differences have a counterpart in the fMRI signals, fMRI at laminar resolution might be used to elucidate such different cortical computations. However, laminar differences under different stimulus conditions have remained elusive. There could be multiple reasons for this, for instance resolution limitations. Another possible reason is that the profile of the BOLD response as a function of cortical depth could be determined by the properties of the vasculature, with the laminar profile

of the BOLD response only exhibiting amplitude differences, independent of which layers show strongest neural activity. Yet another possibility is that the point spread function (PSF) of the hemodynamic Everolimus chemical structure response is larger than the thickness of the layers. To address these questions and to investigate whether obvious laminar differences in the patterns of the BOLD response exist, we compared the laminar properties of positive and negative BOLD responses. We chose these stimuli because of the large differences between the responses and because the negative BOLD signal has been reported to have different properties; namely, to be more specific than the positive BOLD signal (Bressler et al., 2007) and to provide independent information about brain function (Wade and Rowland, 2010). Negative

BOLD responses have been observed in humans and animals (Allison et al., 2000; Harel et al., 2002; Huang et al., 1996; Shmuel et al., 2002, 2006; Resminostat Tootell et al., 1998). In V1, negative responses can be reliably observed adjacent to positive BOLD signals (Huang et al., 1996; Shmuel et al., 2002, 2006; Tootell et al., 1998; Wade and Rowland, 2010). They were also observed upon ipsilateral inhibition in visual-, motor- and somatosensory cortex (Allison et al., 2000; Hlushchuk and Hari, 2006; Schäfer et al., 2012; Smith et al., 2004; Stefanovic et al., 2004; Whittingstall et al., 2008). Negative BOLD signals were shown to be associated with decreases in cerebral blood flow (CBF) and neural activity (Boorman et al., 2010; Devor et al., 2007; Shmuel et al., 2002, 2006).

In cases in which normal distribution

of data could be assumed (p > buy Duvelisib 0.05), the parametric two-tailed Student’s t test was employed to compare means. For testing the statistical significance of the deviation of the proportion of values compared to equal distribution, the χ2 test was applied. A p value of p < 0.05 was considered significant. The authors thank Jia Lou for help with preparing the figures, Sarah Bechtold and Rosa Karl for virus preparation, Rebecca Mease for help with data analysis, Rita Förster for perfusion of mice, and the other laboratory members for critical comments on the manuscript. This work was supported by the Friedrich Schiedel Foundation and by the European Commission under the 7th Framework Programme, Project Corticonic. S. Fischer and C. Rühlmann were supported by the DFG (IRTG 1373). A. Konnerth designed the study. A. Stroh and Autophagy Compound Library C. Rühlmann performed the viral construct injections and confocal imaging. A. Stroh, C. Rühlmann, A. Schierloh, and H. Adelsberger performed the optical fiber recordings. S. Fischer and H. Adelsberger conducted and analyzed the camera recordings. A. Groh and A. Stroh conducted the electrophysiological measurements. A. Stroh and K. Deisseroth established the optogenetic procedures. A. Konnerth and A. Stroh wrote the manuscript.

“
“Schizophrenia is a devastating mental disorder characterized by three clusters of symptoms: positive symptoms (psychosis and thought disorder), negative symptoms (social and emotional deficits), and cognitive click here symptoms. Understanding the cognitive symptoms of schizophrenia is of particular significance because they are highly predictive for the long-term

prognosis of the disease, and at present they are essentially resistant to treatment (Green, 1996). Cognitive symptoms include deficits in working memory and behavioral flexibility (Forbes et al., 2009; Leeson et al., 2009), two processes of executive function that are essential for activities of daily living. Functional magnetic resonance imaging studies have consistently shown an association between impaired executive function and altered activity in the prefrontal cortex (PFC) of patients, leading to the influential hypothesis that prefrontal dysfunction underlies the cognitive symptoms of schizophrenia (Weinberger and Berman, 1996). Due to its dense excitatory reciprocal connection with the PFC (Jones, 2007), the mediodorsal thalamus (MD) has become a focus of attention in the study of cognitive symptoms. Imaging studies have repeatedly shown decreased activation of the MD in patients under a variety of test conditions that address executive functions (Andrews et al., 2006; Minzenberg et al., 2009). Altered correlation between activity in the MD and the PFC at rest or during cognitive testing has also been observed (Minzenberg et al., 2009; Mitelman et al., 2005; Woodward et al., 2012).

This model has been used to provide a mechanistic explanation of the symptoms associated with several basal ganglia disorders, most notably Parkinson disease (PD), (Albin et al., 1989). In PD, loss of dopamine Alectinib input mainly from substantia nigra pars compacta, would have opposing effects on direct and indirect pathway neurons, which express mostly D1 versus D2-type dopamine receptors, respectively (Gerfen et al., 1990). This would result in overactivation of the indirect pathway (and the consequent inhibition of GPe) and less activation of the direct pathway and to lack of movement (Kravitz et al., 2010). Other studies show that PD is accompanied by the emergence of abnormal oscillations in basal ganglia,

most notably prominent beta oscillations in STN and GPe (Mallet et al., 2008 and Nini et al., 1995), which are thought to constitute a pacemaker circuit (Plenz and Kital, 1999). The GPe, central to basal ganglia function, has been traditionally portrayed as a structure organized in different domains of homogeneous cell populations of projection neurons, all projecting to the STN with some collaterals reaching other structures. In this issue of Neuron, Mallet and colleagues ( Mallet et al., 2012) demonstrate

that the organization of the GPe is more complex than previously thought, and that it is composed of at least two populations of GABAergic projection neurons. selleck kinase inhibitor The authors had previously shown that in a PD rat model, two different types of GPe neurons could be identified based on their entrainment to different phases of

cortical slow wave oscillations ( Mallet et al., 2008): some fired preferentially during the surface-negative component of the cortical oscillation (inactive, hence named GP-TI); others during the surface-positive phase of the cortical oscillation (active phase, GP-TA). In this study, Mallet et al. (2012) used juxtacellular labeling of in vivo recorded cells to establish that these two types of neurons, identified based on their firing dynamics, constitute indeed different cell types within GPe, also with quite distinct molecular profiles, neuronal structures, and projection patterns. The authors observed that all GP-TA neurons expressed the neuropeptide precursor preproenkephalin (PPE), while none of the GP-TI neurons did. Other markers, like parvalbumin, were more expressed in GP-TI neurons, but were also found in GP-TA neurons. Therefore, PPE could be used as a specific marker for GP-TA neurons. Using this marker, the authors showed that GP-TA and GP-TI neuronal populations are spatially intermingled in GPe, and that they are both GABAergic neurons. Next, they characterized the structure and projection specificity of individual neurons from both populations. They observed that while GP-TI neurons have the projection profile expected for GPe neurons—descending projections to downstream BG nuclei such as STN, which sometimes sent collaterals to striatum—GP-TA neurons had an unanticipated projection pattern.

This was the case in every trial for all animals (Figure 2A). Which aspects of the motor and sensory

activity determine the timing of the jump? We found that the time at which the cocontraction ended (triggering) was highly correlated with take-off (ρ = 0.95, p < 10−9). Moreover, this correlation exists regardless of l/|v|, since the partial correlation coefficient between these two variables controlling for l/|v| remained high (ρpart = 0.94, p < 10−9). On average take-off occurred 36 ms after triggering (SD: 15, nL = 4, nT = 29; Figure 2B, dashed line) and 90% of the variance in the timing of take-off could be explained by the timing of triggering. At the sensory level, we found that the timing of the DCMD peak firing Topoisomerase inhibitor rate and take-off were highly correlated as well (ρ = 0.87, p < 10−9) and that the partial correlation coefficient between these variables controlling for l/|v| also remained high (ρpart = 0.73, p = 9.2 × 10−8). Epigenetics inhibitor Locusts took off on average 70 ms (SD: 13) after the DCMD firing rate peaked, regardless of l/|v| (Figure 2C, dashed line) and the timing of the peak accounted for 75% of the variance of the take-off time. Not all looming stimuli led to a final take-off. Thus,

locusts jumped with a median probability of 32%. The jump probability was significantly reduced compared to that of animals without a telemetry backpack (Fotowat and Gabbiani, 2007; median: 64%, pKWT = 0.003). Figure 3 shows a trial in which the same locust as in Figure 1 did not jump (Movie S2). It started preparing by cocontracting its hindleg

flexor and extensor muscles. However, compared to jump trials, the cocontraction started late, such that after a few spikes in the extensor, the through looming stimulus reached its full size, the DCMD firing rate declined, and the cocontraction ended. This was the case in 85% of trials without take-off, whereas in the remaining 15% the cocontraction failed to initiate altogether. Across animals, we found that cocontraction onset occurred significantly earlier relative to collision in jump trials (Figure 4A), whereas the timing of the DCMD peak itself did not change (Figure 4B). Thus, while the DCMD peak time predicts the time of take-off, it fails to predict its occurrence. Since cocontraction started earlier in jump trials, the number of extensor spikes was also significantly higher (Figure 4C). In contrast, there was no difference in the total number of DCMD spikes between jump and no-jump trials (Figure 4D), although the peak DCMD firing rate was higher in jump trials (Figure S2A). However, we found that if we started counting the DCMD spikes from cocontraction onset rather than stimulus onset (shaded areas in Figure 1 and Figure 3), their number was significantly higher in jump trials (Figure 4E). Furthermore, the number of DCMD spikes from cocontraction onset was highly correlated with the number of extensor spikes (ρ = 0.73, p < 10−9, Figure 4F), such that on average 4.

Alternatively, other complement-dependent and/or -independent mechanisms may be involved. For example, C3 could bind all synapses and only those synapses that are “stronger” or more active are selectively protected by membrane-bound complement regulatory molecules

(Kim and Song, 2006 and Song, 2006). In contrast, selective, activity-dependent elimination of synapses could be driven by a complement-independent mechanism which subsequently results in complement binding and/or microglia-mediated engulfment. For example, MHC class I molecules, another class of immune molecules demonstrated to play a critical role in retinogeniculate pruning, have been Ivacaftor chemical structure shown to be activity dependent, localized to synapses, and colocalized with C1q leaving the possibility that MHC class I molecules may play an upstream role in microglia-mediated pruning of synapses (Corriveau et al., 1998, Datwani et al., 2009, Goddard et al., 2007 and Huh et al., 2000). While our data demonstrate that CR3/C3 signaling specific to microglia http://www.selleckchem.com/products/OSI-906.html is involved in the pruning of developing circuits and suggest that engulfment is the underlying mechanism, CR3 and C3 may be acting through other pathways independent of phagocytosis or may be downstream of other

signaling pathways to mediate pruning. In addition, engulfment deficits in CR3 and C3 KO mice were reduced to approximately 50% of WT littermate control values, suggesting that other complement receptor-dependent (e.g., CR4, CRig, etc.) and independent phagocytic mechanisms may also be involved. Future studies will aim to address whether and how specific synapses are eliminated by complement and other microglia-dependent mechanisms and how neural activity plays a role in this process. Our data raise the question as to whether complement and/or microglia-dependent engulfment of synaptic inputs represents either a more global mechanism underlying CNS neural circuit plasticity. While in at

least one other developing system local axonal retraction and synapse elimination appear to occur independent of microglia (Cheng et al., 2010), recent work describes a role for microglia at developing hippocampal synapses (Paolicelli et al., 2011). In addition, in vivo imaging studies in the cortex revealed that microglia dynamics and interactions with neuronal compartments change in response to neural activity and experience (Davalos et al., 2005, Nimmerjahn et al., 2005, Tremblay et al., 2010a and Wake et al., 2009). While these studies describe microglia dynamics at synapses, a precise function and molecular mechanism(s) underlying microglia-synapse interactions in these brain regions was unknown. Our study provides mechanistic insight into the dynamic between microglia and developing synapses and provides complement-dependent signaling as a potential mechanism in other brain regions.

, 2011) or a more generalizable dissociation between attention and memory. In summary, the findings of Guerin and colleagues provide a compelling characterization of how distinct aspects of lateral parietal cortex contribute to situations in which we must carefully compare the present with the past. These findings are relevant to a very active debate concerning the role of lateral parietal cortex in memory (for reviews, see Cabeza et al., 2008; Shimamura, 2011; Wagner et al., 2005).

Additionally, the study makes an VX 770 important contribution to our understanding of memory failures (Johnson, 1997; Schacter, 1999), highlighting both the situations in which false memories are likely to occur and the neural responses that are associated with these lapses. An interesting question for future work is how necessary the contributions of lateral parietal cortex are to successful episodic remembering. While damage to lateral parietal cortex has not been associated with robust memory deficits—clearly not to the degree that occurs with damage to the medial temporal lobe system—it is possible that lateral parietal regions make subtle but meaningful contributions to memory. This could be addressed by carefully probing memory functioning in neglect patients with parietal damage. For example, in the paradigm employed by Guerin et al. (2012), perhaps damage to IPS

would impair SKI-606 cost the initial step of allocating attention to candidate pictures. Damage to IPL, on the other hand, may result in a diminished ability to make subtle discriminations between targets and related (but new) items. Both neuroimaging and patient work can further characterize the competitive interactions between IPL and IPS in tasks that carefully and cleverly separate attentional demands and memory success as Gueirin and colleagues have done. “
“Scientists around the world are wondering how changes in regulations governing animal research will influence progress in neuroscience. How, for example, would active promotion of the 3Rs, as required in the not new European Directive (European Commission, 2010) and the most recent edition of the Guide for

the Care and Use of Laboratory Animals—“the Guide”—(National Research Council, 2011) impact innovative research in neuroscience if applied globally? The principles of the 3Rs—replacement, reduction, and refinement—were first articulated over 50 years ago by W.M.S. Russell and R.L. Burch (Russell and Burch, 1959). Replacement refers to methods that avoid the use of animals either absolutely (e.g., using computer modeling or human volunteers) or relatively (e.g., using invertebrates such as Drosophila and nematodes, or cultured cell lines derived from animals). Reduction occurs when researchers obtain comparable levels of information from fewer animals, often through improved experimental design and technique or statistical analysis.

The robotically-induced drift in self-location confirms a classical finding of visual dominance (the “stroking” on the video) over somatosensory cues (the robotic stroking on the participant’s back) by inducing predicted changes in self-location (Lenggenhager et al., 2007, Lenggenhager et al., 2009 and Aspell Sunitinib et al., 2009) that have also been observed in drift measures during the related rubber hand illusion (Ehrsson

et al., 2004 and Tsakiris and Haggard, 2005). We report that the direction of these drift-related changes in self-location is consistent with the experienced direction of the first-person perspective during robotic stimulation. We argue that this is due to a different visual versus bodily http://www.selleckchem.com/products/DAPT-GSI-IX.html conflict that is related to the visual-vestibular gravitational conflict that we presented during stimulation. Thus, we used a visual image that contained

a conflict between the visual gravitational cues of the seen body and the actual vestibular (and somatosensory) gravitational cues signaled from the physical body of the participants. Showing a visual body that was filmed from an elevated camera perspective (Figure 1A), these visual gravitational cues of the seen body are in conflict with the actual vestibular (and somatosensory) gravitational cues from the participants’ physical bodies signaling that they are actually lying on their backs and looking upward. Accordingly, we argue that in participants from the Up-group, there is stronger reliance on vestibular (and somatosensory) cues than on visual gravitational cues (from the seen virtual body), whereas participants from the Down-group show the opposite pattern. This is concordant with three related findings. First, comparable effects have been reported in patients with OBEs of neurological origin with abnormal self-location and first-person perspective (Blanke et al., 2002 and Blanke et al., 2004). Thus, the large majority of patients with OBEs experience

themselves to be seeing from an elevated and down-looking, first-person perspective (Blanke and Arzy, 2005 and Blanke and Mohr, 2005), and this perspective is inverted and rotated by 180° with respect to their supine and upward-oriented Cytidine deaminase physical body position (Lopez and Blanke, 2011). OBEs have been previously linked with abnormal vestibular/gravitational signals and a deficit in visuo-vestibular integration (Lopez et al., 2008 and Schwabe and Blanke, 2008). The importance of vestibular signals and visuo-vestibular integration was also suggested in a recent self-location study in healthy subjects using manual stroking, that reported an association of vestibular sensations with experimentally induced changes in self-location (Lenggenhager et al., 2009). Second, visuo-vestibular integration is characterized by strong individual differences, as also found in the present study.

In zip1 and sqhAX3 flies, reduced association of mitochondria with F-actin SB431542 price correlates with increased association of DRP1 with F-actin, observed by coprecipitation of F-actin and DRP1 from total head homogenate using biotinylated-phalloidin ( Figures 8C and 8D). These findings suggest that

myosin II facilitates tethering of mitochondria to F-actin, a connection that is required for mitochondria to interact with DRP1. To determine if myosin II has a general and conserved role in DRP1 localization, we focused on the regulatory light chain, MLC2. We transfected Cos-1 cells with siRNA targeting two independent, nonoverlapping sequences in MLC2. We first confirmed depletion of MLC2 protein by western blot analysis ( Figure S8B). We then assessed mitochondrial morphology and the subcellular localization of DRP1.

In control cells, mitochondria, detected with transfected mitoRFP, are round or slightly tubular and colocalize with DRP1. In MLC2 siRNA-transfected cells, mitochondria are significantly elongated, and DRP1 signal is diffuse ( Figure 8E, Hydroxychloroquine order insets, graph). MLC2 is phosphorylated by myosin light chain kinase (MLCK), which is essential to MLC2 activity ( Watanabe et al., 2007). Treatment of cells with ML-7, a chemical inhibitor of MLCK, recapitulates the effects of MLC2 RNAi on mitochondrial morphology and DRP1 localization ( Figure S8A, insets, graph). These results support a conserved interaction among DRP1, myosin, and actin. Here, we describe a previously unsuspected target for tau neurotoxicity in human neurodegenerative disease: mislocalization of the mitochondrial fission protein DRP1 with subsequent failure of normal mitochondrial dynamics control. Our current data extend a model of the cascade of neurotoxicity triggered by accumulation of human tau. Previous work from our laboratories and others (Ahlijanian et al., 2000; Noble et al., 2005; Steinhilb et al., 2007a, 2007b; Iijima-Ando et al., 2010) places phosphorylation of tau upstream in a sequence of cellular events, including actin stabilization

Rolziracetam (Fulga et al., 2007), which lead to neuronal death. Our new results place tau phosphorylation upstream of altered mitochondrial dynamics (Figure S1) and further indicate that proper regulation of the actin cytoskeleton is critical for localization of DRP1 to mitochondria and subsequent mitochondrial fission. Here, we show a physical interaction between F-actin and DRP1. Further, we find that myosin II is required for both localization of mitochondria to actin and DRP1 to mitochondria (Figures 7 and 8). These results support a model in which DRP1 and mitochondria are recruited to F-actin, followed by actin-based translocation, leading to mitochondrial localization of DRP1 and subsequent mitochondrial fission. Excess actin stabilization inhibits translocation and colocalization of DRP1 and mitochondria, resulting in mitochondrial elongation (Figure S8C).

, 2002), rabbit anti-Caspr5 (antibody was made by immunizing rabbits with a GST-fusion protein containing the intracellular domain of human Caspr5), mouse anti-myc

(clone 9E10; Roche), rabbit anti-VAMP-1 (SYSY), and mouse anti-PSD-95 (Thermo Scientific). To isolate putative GABApre neurons, YFPON cells from p0 Ptf1a::Cre; Rosa26.lsl.YFP mice were purified Selleckchem Carfilzomib using fluorescence-activated cell sorting (FACS). Briefly, spinal cords were dissociated using Papain dissociation kit (Worthington) and sorted based on YFP fluorescence. RNA was then isolated using the Absolutely RNA Nanoprep Kit (Agilent) and cDNA was generated from these cells using WT-Pico Ovation Amplification Kit (NuGEN). RT-PCR was performed on cDNA generated from purified RNA using the following primers: ChAT (forward primer (FP): TCAGGGCAGCCTCTCTGTAT, reverse primer (RP): ATGTTGTCCACCCGACCTTC), CHL1 (FP: AGGACAGCGAAACTCTGGAA, RP: TCGTGTTCTGCATTTTGAGC), GAD2 (FP: AAAATCTCTTGGGCCCTTTC, RP: CCGGAGTCTCCATAGAGCAG), L1 (FP: CAAAGTCCAGGCAGTGAACA, check details RP:

CTGTACTCGCCGAAGGTCTC), NF (FP: ACCTGGAGACCATCAACCTG, RP: TCAGGCAAGGGAATAGATGG), NrCAM (FP: AATCCAGTGTGAGGCCAAAG, RP: GAAAGCACGAGGTTTTGAGG). S.A., J.N.B., J.D.C., S.B.-M., V.B., and J.A.K. performed experiments. S.A., J.N.B., J.D.C., E.P., T.M.J., and J.A.K. designed the study and interpreted results. E.P., S.B.-M., Y.S., and K.W. provided reagents. S.A., J.N.B., J.D.C., T.M.J., and J.A.K. wrote the paper. We thank J. Sanes for generously providing antibodies, T. Sakurai for experimental help and helpful discussions, and N. Balaskas, A. Fink, S. Poliak, only and S.-H. Shi for comments on the manuscript. We are grateful to K. Kridsada for technical assistance, D. Ng and J. Zhang for critical assistance with in situ hybridization, J. Bikoff for providing Ptf1a-derived cDNA, I. Horresh for checking antibodies to Caspr5, A. Todd

for assistance with synaptic staining, D. Montag for CHL1 mutant tissue, and T. Cutforth for providing Kirrel-3 mutant mice. We thank Y. Zhang and J. Salzer for breeding Caspr mutant mice, S. Markx and J. Gogos for breeding Caspr2 mutant mice, T. Karayannis, E. Au, and G. Fishell for breeding Caspr4 mutant mice, D. Felsenfeld for breeding L1 mutant mice, and T. Sakurai and C. Mason for breeding NrCAM mutant mice. This work was supported by a National Institutes of Health (NIH) predoctoral training grant (527975) and a Columbia University Neuroscience Fellowship (J.N.B.), a Medical Scientist Training Program (MSTP) grant from the National Institute of General Medical Sciences of the NIH under award number T32GM007739 to the Weill Cornell/Rockefeller/Sloan-Kettering Tri-Institutional MD-PhD Program (J.D.C.), a Grant-in-Aid for Scientific Research (B) (#18300120) from the Japan Society for the Promotion of Science (Y.S. and K.W.), NIH grant NS50220 and the Israel Science Foundation (E.P.), HHMI, Project ALS, The Wellcome Trust, EU Framework Program 7, and NIH RO1 NS33245 (T.M.J.