5 Tesla MAGNETOM Vision

MRI scanner (Erlangen, Germany) a

5 Tesla MAGNETOM Vision

MRI scanner (Erlangen, Germany) as described in Dosenbach et al. (2010). The third data set (n = 106: a 53 subject cohort, 52 subject cohort, and an additional single subject) was acquired on a Siemens MAGNETOM Tim Trio 3.0T Scanner with a Siemens 12 channel Head Matrix Coil (Erlangen, Germany) as described in Dosenbach et al. Buparlisib (2010). See Supplemental Experimental Procedures for acquisition details. Functional images underwent standard fMRI preprocessing to reduce artifacts, register subjects to a target atlas, and resample the data on a 3 mm isotropic grid (Shulman et al., 2010). See Supplemental Experimental Procedures for further details. For rs-fcMRI analyses, several additional preprocessing steps were utilized to reduce spurious variance unlikely to reflect neuronal activity (Fox et al., 2009). These steps included: (1), a temporal band-pass filter (0.009 Hz < f < 0.08 Hz) and spatial smoothing

(6 mm full width at half maximum); (2), regression of six parameters obtained by rigid body head motion correction; (3), regression of the whole brain signal averaged across the whole brain; (4), regression of ventricular signal averaged from ventricular ROIs; and (5), regression of white matter signal Sirolimus averaged from white matter ROIs. The first derivatives of these regressors were also regressed. The first method of identifying putative functional areas searched a large fMRI data set acquired in a single scanner (data set 1) for brain regions that reliably displayed significant activity when certain tasks were performed (e.g., button-pressing) or certain signal types (e.g., error-related activity) were expected (see Table S1). Meta-analyses identified 322 ROIs (10 mm diameter spheres, see Figure S1), which were reduced to a final collection of 151 nonoverlapping meta-analytic ROIs. Full details of meta-analyses are available in Supplemental Experimental Procedures. fc-Mapping techniques were applied to

eyes-open fixation rs-fcMRI data from 40 healthy young adults (data set 2: 27 M/13 F, average age = 26.4 years old, average RMS movement = first 0.42 mm, average number of volumes = 432). See Cohen et al. (2008) and Nelson et al. (2010a) for full conceptual and technical descriptions of fc-Mapping on cortical patches. Here, patches extending over the entire cortical surface (one per hemisphere) were used to define putative functional areas. This technique generated 254 ROIs across the cortex, which were reduced to a final set of 193 nonoverlapping ROIs. See Supplemental Experimental Procedures for further details. Meta-analytic ROIs and fc-Mapping ROIs were merged to form a maximally-spanning collection of ROIs. Meta-analytic ROIs were given preference, and nonoverlapping fc-Mapping ROIs were then added, resulting in 264 independent ROIs. A 90-node parcel-based network was formed by using the 90-parcel automated anatomical labeling (AAL) atlas (Tzourio-Mazoyer et al.

This suggests a strong feature

This suggests a strong feature Entinostat order tolerance in this area, which generalizes even beyond sensory input modality and early sensory experience, while maintaining the relative category selectivity implied by the term “visual word form area.” Moreover, this area shows remarkable adult plasticity, such that it can be recruited in an adult blind individual reading in a novel sensory modality after as little as 2 hr of training (Figure 4). After ∼70 hr of training in a group of subjects,

this area already displayed full category selectivity (Figure 2). These findings impact several of the major issues regarding the function and developmental origin of the VWFA, as well as the balance between plasticity and conserved cortical functions resulting from sensory deprivation. Specifically, they suggest that the VWFA performs a highly Selleckchem GDC-941 flexible task-specific reading-related operation that can be sensory modality independent (Reich

et al., 2012). We suggest that this operation is the learned link between letter shapes and their associated phonological content. This category and task selectivity is maintained in the congenital absence of vision, despite otherwise extreme plasticity for other functions and input types shown previously in the blind brain (see reviews in Frasnelli et al., 2011; Merabet and Pascual-Leone, 2010; Striem-Amit et al., 2011). This implies the presence of innately determined constraints (Striem-Amit et al., 2012a) on the emergence of VWFA selectivity for reading. Furthermore, in the context of visual rehabilitation, this study also shows that the recognition of many complex visual stimulus categories can be learned using SSDs, including detailed images of faces and houses (see Movies S1 and S2). We describe how such training was implemented on computer and in natural three-dimensional (3D) environments, details

of which may be of interest to those specializing in visual rehabilitation (see Supplemental Experimental Procedures). In the next sections, we address all these topics in more depth. In the visual modality, the VWFA has proved to be selective for letters over other complex visual stimuli such as drawings of objects, faces, much and houses (Cohen and Dehaene, 2004; Dehaene and Cohen, 2011; Dehaene et al., 2010; Hasson et al., 2002; Puce et al., 1996; Szwed et al., 2011; Tsapkini and Rapp, 2010), thus justifying its “visual word form area” label. Note that the VWFA, like other specialized ventral areas (Kanwisher, 2010), is also partially responsive to stimuli from nonpreferred categories and that its preference for alphabetic stimuli may be missed under some experimental conditions (reviewed in Price, 2012; Price and Devlin, 2011).

In this issue of Neuron, Tischbirek et al (2012) reveal

In this issue of Neuron, Tischbirek et al. (2012) reveal

that APDs are released Ivacaftor price during SV fusion at concentrations sufficient to inhibit presynaptic voltage-gated sodium channels. This results in reduced presynaptic calcium influx, which limits subsequent SV exocytosis and neurotransmitter release ( Figure 1). Therefore, in addition to established high affinity effects on dopaminergic receptors by the free circulating drug, Tischbirek et al. (2012) describe a novel lower-affinity, use-dependent effect at voltage-gated sodium channels that only manifests during evoked neurotransmitter release. To demonstrate vesicular accumulation of APDs, the fluorescent reporter lysotracker red (LTR) was used as a mimic of drug behavior. LTR is also a weak base, and was shown to accumulate in SVs by either colocalization with presynaptic markers or photoconversion followed by ultrastructural http://www.selleckchem.com/products/Bafilomycin-A1.html analysis (Tischbirek et al., 2012). Importantly Tischbirek and colleagues also demonstrated that LTR was released

on stimulation with a train of action potentials, indicating that the dye (and by extension APDs) could be released by SV exocytosis. Parallel mathematical modeling studies predicted that APDs would be accumulated inside SVs in the micromolar range. Therefore, Tischbirek et al. (2012) next questioned whether acute application of such concentrations of APDs modulated presynaptic function. The effects of four

APDs were assessed (haloperidol, chlorpromazine, clozapine, and risperidone). SV exocytosis was monitored using the pH-sensitive fluorescent genetic reporter synaptopHluorin (Sankaranarayanan and Ryan, 2000) and calcium influx measured using the fluorescent dye fluo-4. In all cases, acute PDK4 application of APDs inhibited both calcium influx and SV exocytosis evoked by action potential stimulation in a dose-dependent manner. Both effects were due to an upstream inhibition of voltage-gated sodium channels, since acute APD application had no effect on SV exocytosis elicited by KCl, a stimulus that bypasses these channels. This observed inhibition of presynaptic function by APDs can only be physiologically relevant if the drugs were (1) concentrated inside SVs and (2) released on neuronal stimulation. To test this, Tischbirek et al. (2012) applied APDs to cultured neurons which had previously accumulated LTR. This resulted in displacement of LTR, providing indirect evidence that APDs were accumulating in SVs. Unfortunately, APD enrichment inside SVs was not directly confirmed (by using fluorescent-labeled APDs for example; Rayport and Sulzer, 1995). Therefore, a direct estimate of the intravesicular concentration of APDs could not be determined. Importantly, however, APDs were shown to be released on neuronal stimulation in vivo, in experiments performed using animals treated with clinically relevant doses of haloperidol.

g , muscarinic antagonists, H1-histamine antagonists, or α2-adren

g., muscarinic antagonists, H1-histamine antagonists, or α2-adrenergic agonists) cause acute sleepiness, but chronic ablation of the basal forebrain cholinergic neurons (Kaur et al., 2008), tuberomammillary histaminergic neurons (Gerashchenko et al., 2004), the LC and pontine cholinergic neurons (Lu et al., 2006a, Shouse and Siegel, 1992 and Webster selleck inhibitor and Jones, 1988), or combinations of these structures (Blanco-Centurion et al., 2007) have minimal effects on the amount of wakefulness. One possible reason for this puzzling result is that the arousal system may contain sufficient redundancy that remaining wake-promoting systems may be able to compensate for the chronic (but perhaps

not acute) loss of one or even a few components, e.g., by increasing activity or receptor sensitivity in intact arousal systems. A related issue is which of these wake-promoting cell groups participate in the switching between sleep and wakefulness, as opposed to the maintenance of the waking state. This issue will be taken up in the section of this review on switching circuitry. During the epidemic of encephalitis lethargica around click here the time of the World War I, Von Economo (1930) reported that patients with lesions in the preoptic region around the rostral

end of the third ventricle demonstrated profound insomnia. Experimental lesions of the preoptic-basal forebrain region reduced sleep in rats and cats (McGinty and Sterman, 1968 and Nauta, 1946), but the exact population of sleep-promoting neurons was unknown. Sherin and colleagues (Sherin et al., 1996) subsequently identified a population of neurons in the ventrolateral preoptic nucleus (VLPO) that innervate the histaminergic TMN and that express Fos protein selectively during sleep but not wakefulness. VLPO neurons, containing the inhibitory neurotransmitters GABA and galanin,

innervate other components of the ascending arousal system as well, including the LC, raphe system, periaqueductal gray matter, parabrachial nucleus, and lateral hypothalamic area (Sherin et al., 1998). The VLPO was Sodium butyrate found to consist of a dense core of sleep-active, galanin-positive neurons that project heavily to the TMN. However, this is surrounded dorsally and medially by a more diffuse population of sleep-active, galanin-positive neurons, the extended VLPO, which more extensively targets the dorsal raphe and LC (Lu et al., 2000 and Sherin et al., 1998). As is true for many cell groups in the hypothalamus that are defined on the basis of common neurotransmitter, connections and physiology, the VLPO neurons are mixed in among other cell types. In addition, while there are other galaninergic neurons laterally in the basal forebrain and medially in the preoptic area, none of these are sleep-active or project to the TMN, LC, or dorsal raphe (Sherin et al., 1998 and Gaus et al., 2002).

As illustrated in Figure 6 and Table S2, taking TPSM-phase into a

As illustrated in Figure 6 and Table S2, taking TPSM-phase into account to discriminate between IN-PF and OUT-PF firing (IN versus OUT EpF in the wheel) still provided significant

increase in spatial information content when bursts (taken as successive spikes separated by less than 10 ms) were omitted from the original spike train, as well as when only spikes emitted at high frequency (ISI < 10 ms) or on the contrary at frequencies lower than 25 Hz (ISI > 40 ms) were taken into account. These results suggest that a direct relationship between firing rate and TPSM-phase is unlikely to account for the observed TPSM phase-related gain of spatial information. HA-1077 cost Another possibility is that of a location-dependent modulation of theta power itself. For example, if theta amplitude was systematically maximal within a given place field area, the spikes discharged within this place field would likely be biased toward the corresponding phase of TPSM (i.e., π, for maximal theta power). We therefore computed signal-phase histograms corresponding to the TPSM phases expressed in each place field (i.e., distribution of LFP TPSM-phase relative to physical space; see Experimental Procedures). Although in the open field a significant signal modulation relative

to TPSM phase was observed in 41% of TPSM phase-locked place fields (18 place fields among 44 whose IN-PF spikes were significantly phase locked to TPSM; Rayleigh test, p < SP600125 in vivo 0.05; Figure 7A), it was most often (13 among 18 place fields) significantly different (p < 0.05, Kuiper test) from the distribution of IN-PF spikes relative to TPSM phase. This observation suggests that the TPSM phase-locking of spikes inside a place field cannot be explained by the preferred TPSM phase of the signal within this same place field. A different situation prevailed in the maze in which, as expected from classical track running experiments,

running was accompanied by a highly reproducible sequence of place cells firing, along with the animal’s stereotypical spatial progression (Pastalkova et al., 2008). As observed in Figures 7B–7D and S3, TPSM was remarkably conserved Thiamine-diphosphate kinase from one run to the other, as was the motor behavior of the animal. Accordingly, we observed that TPSM was in fact phase locked to the environment (Figures 7B–7E), in accordance with a recent study reporting a strong correlation between theta power and animal’s position in a maze (Montgomery et al., 2009). As a result, the relationship between IN-PF spikes and TPSM phase in the maze appears to be tightly related to the coincidence of place field position and phase locking of TPSM to space (Figures 6C and 7C–7E). To further investigate the potential relative influences of time and space on hippocampal activity, we examined TPSM during wheel running, in which although the animal is running, its spatial location does not change (Czurkó et al., 1999; Pastalkova et al., 2008).

, 2000, 2003) but not for clearance of established deposits Prev

, 2000, 2003) but not for clearance of established deposits. Previous studies demonstrated that the modified Aβp3-42 peptide

accumulates early in the deposition cascade (Iwatsubo et al., 1996; Saido et al., 1995) and probably was specific for plaque (i.e., no soluble peptide found in physiological fluids). We immunized mice with the Aβp3-42 peptide and subsequently screened clones for Aβp3-x binding and counterscreened against Aβ1-42. A low-affinity Aβp3-42 monoclonal antibody was affinity matured to yield the high-affinity (140 pM) anti-Aβp3-x antibody mE8 (koff < 1 × 10−5/s at 25°C). Characterization of the binding properties of mE8 demonstrated that it specifically recognized the modified amino terminus of Aβp3-x in that it does not recognize full-length Aβ or unmodified Aβ3-x

http://www.selleckchem.com/products/3-methyladenine.html (see Figure S1 available online). In order to evaluate the impact of effector function on in vivo plaque clearance, mE8 was made in both mouse IgG1 (minimal effector function) and IgG2a (maximal effector function) isotypes. The affinity-matured mE8 was first used to investigate levels of the Aβp3-42 http://www.selleckchem.com/btk.html peptide in PDAPP and AD brain lysates. ELISA analyses demonstrated that low levels of the Aβp3-42 peptide could be detected in both PDAPP and AD brains (Figure 2A). Interestingly, the prevalence of the Aβp3-42 peptide was quite low (∼0.6%) with respect to the overall amount of Aβ42 deposited in these brains (Figure 2B). The analyses also showed an age-dependent accumulation of Aβp3-42 peptide in PDAPP brains that increased 47-fold between 12 and 23 months

of age (Figure 2A). The similar prevalence of Aβp3-42 in AD patients and PDAPP mouse brains demonstrates that our transgenic model recapitulates the generation of this neuropathological target. Immunohistochemical analyses were performed with anti-Aβp3-x antibodies in order to determine whether the epitope is accessible in aged PDAPP and AD brain sections. Robust Aβ staining was observed in brain sections from a 24-month-old PDAPP mouse with 3D6 (Figure 2C) and more discrete staining was observed for the mE8 antibody (Figure 2D). Histological analyses performed on fresh-frozen AD brain resulted in similar staining between the 3D6 and mE8 antibodies, where again the labeling was more intense and widespread for the 3D6 antibody Unoprostone (Figures 2E and 2F). We next investigated whether the relatively low levels of the Aβp3-42 antigen would be sufficient to enable opsonization and Fc receptor-mediated phagocytosis. Ex vivo phagocytosis studies were performed with exogenously added Aβ antibodies preincubated with AD brain sections that were subsequently treated with primary murine microglial cells (Figure 2G). The following murine Aβ antibodies were investigated: 3D6 (anti-Aβ1-x, IgG2b), mE8 (anti-Aβp3-x, IgG1), mE8 (anti-Aβp3-x, IgG2a), 21F12 (anti-Aβx-42, IgG1), 2G3 (anti-Aβx-40, IgG1), and a murine control antibody (IgG2b, same effector function as 3D6).

In our paradigm, the human-like characters were also unexpected,

In our paradigm, the human-like characters were also unexpected, unrepeated, and distinctive visual events. But, notably, our experimental settings did not involve any primary task; rather, any attentional set arose only as a consequence of the coherent unfolding of the visual environment over time. This demonstrates that, in complex and dynamic settings, task-irrelevant stimuli can activate the rTPJ even when they do not interfere with any

prespecified task rules or task sets (see click here also Iaria et al., 2008). In our study, despite being fully task-irrelevant, the human-like characters were very distinctive visual events. The orienting efficacy of these stimuli may relate to the fact that they can be recognized on the basis of previous knowledge and/or Navitoclax chemical structure category-specific representations (see also Navalpakkam and Itti, 2005 and Einhäuser et al., 2008). Also, human-like characters may have attracted attention because they

were the only moving objects in the scene. Motion was not included in our computation of salience because currently available computational models do not separate the contribution of global flow due to self motion from the local flow due to character motion, which are known to be processed in distinct brain regions (Bartels et al., 2008). Instead, to we examined the possible relationship between the human-like characters and points of maximum saliency, computed using intensity, color, and orientation. This revealed that 14 out of the 25 characters did not show any coincidence with the location of maximum saliency. Five characters coincided with the location of maximum saliency for at least 25% of the character’s duration. Three of these were scored as attention grabbing and two as non-grabbing, indicating that there was no systematic relationship between maximum saliency and the appearance of the

human-like characters in the scene. This further supports our main conclusion that the efficacy of low-level salience and the efficacy of distinctive visual events are processed separately in the dorsal and ventral attention systems, respectively. Nonetheless, future developments of saliency models will hopefully disentangle global and local motion components, which would permit further discrimination of the contribution of low-level saliency compared with that of higher-order category effects during the processing of moving objects/characters in dynamic environments. The results discussed above are derived from hypothesis-based analyses involving computations of only a few indexes of attentional orienting (e.g., shifts, timings, and distances).

, 2011), likely explaining the fragmented mitochondria and altere

, 2011), likely explaining the fragmented mitochondria and altered mitochondrial dynamics seen in the disease (Pandey et al., 2010 and Shirendeb et al., 2011). Among diseases in this category, PD stands out, as it is becoming apparent that some genetic forms of the disease may be in essence disorders of mitochondrial quality control. Paradoxically, the history of PD, at least from a genetic/biochemical perspective, pointed away from such a conclusion, as the earliest observations regarding pathogenesis implied a deficiency of complex

I of the respiratory chain as the key culprit. EGFR inhibitor drugs That conclusion was based on the findings that (1) 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), a complex I inhibitor similar to rotenone, caused PD-like symptoms, (2) complex I activity was reported to be reduced in PD postmortem

tissues, (3) mutations in complex I subunits, such as nDNA-encoded NDUFV2, were associated with PD (Nishioka et al., 2010), and (4) accumulations of large-scale deletions of mtDNA were found specifically in the substantia nigra of sporadic PD patients (Bender et al., 2006 and Kraytsberg et al., 2006), the signature target region of the brain in this disease (Dauer and Przedborski, 2003). However, a notable challenge to this concept was the failure to find clear evidence of mutations in mtDNA that cause PD (Simon et al., 2010). Moreover, the identification in the last decade of at least a dozen genetic loci STK38 associated with familial Selleckchem PD0332991 PD (Table 2) has changed our perspective dramatically, as many of these gene products are associated with mitochondria but have no obvious or direct connection to OxPhos, and many

of those proteins appear to be involved in quality control. Two of those PD-related proteins may be involved in quality control in an indirect manner. Phospholipase A2, group VI (PLA2G6) (Seleznev et al., 2006) is a mitochondrial lipase that deacetylates cardiolipin and is involved in ER stress and ER-mitochondrial crosstalk via ceramide (Lei et al., 2008). GRB10-interacting GYF protein-2 (GIGYF2) enhances the activation of mitochondrially localized (Deng et al., 2000 and Galli et al., 2009) extracellular signal-regulated kinases ERK1 and ERK2 (Deng et al., 2000 and Higashi et al., 2010), both of which are involved in mitophagy (Dagda et al., 2008b) and apoptosis (Deng et al., 2000 and Higashi et al., 2010). A much stronger case for a role in mitochondrial quality control can be made for Parkin, a cytosolic E3 ubiquitin ligase. However, in this role, Parkin does not act alone, as mounting evidence implicates the necessary interaction with another PD-related and mitochondrially localized protein, PINK1. PINK1 is a kinase of unknown specificity that displays a possible dual location in the organelle, i.e., it has been found in both the outer (Zhou et al., 2008) and inner (Jin et al., 2010 and Silvestri et al., 2005) membranes.

Even though there were no differences in our predefined ROIS of l

Even though there were no differences in our predefined ROIS of left and right DLPFC when computing the contrast UG-DG, other regions of bilateral DLPFC were still preferentially engaged (Table S2), thus replicating previous findings, at least in the adult sample (Spitzer et al., 2007). In addition, we analyzed cortical thickness as a measure of brain structure in each individual (see Experimental Procedures for details). Performing AZD5363 a whole-brain assessment of cortical thickness in children, we observed

widespread thinning with increased age in bilateral prefrontal, cingulate, supramarginal, paracentral, and medial occipital regions (family-wise error [FWE] < 0.05, Figure S3). BMS387032 Although there was a small negative relationship between age and cortical thickness in our ROIs, effects failed to reach significance (p > 0.3 in both lDLPFC and rDLPFC; Figures 3A and 3D). Given that studies on structural brain development typically include samples of a greater age range (Gogtay et al., 2004 and Sowell et al., 2003), we also looked at age-related cortical thinning over the

entire range of children and adults in our two ROIs. Indeed, this revealed significant thinning in both lDLPFC (r = −0.385, p = 0.014; ρ = −0.412, p = 0.008;) and rDLPFC (r = −0.428, p = 0.006; ρ = −0.322, p = 0.043; Figure S4), confirming previous results (Gogtay et al., 2004, Sowell et al., 2003 and Sowell et al., 2004). We also assessed whether cortical thickness predicts individual differences in strategic behavior and impulse control, irrespective of any age-related cortical thinning. After statistically controlling for age effects, we found that thickness in lDLPFC correlated positively with both strategic behavior (r = 0.528, p = 0.007; Figure 3B) and negatively with SSRT scores (r = −0.630, p = 0.001; Figure 3C). Considering

age-corrected cortical thickness Sodium butyrate of rDLPFC, on the other hand, we neither observed correlations with strategic behavior (r = 0.347, p = 0.089; Figure 3D) nor with SSRT scores (r = −0.049, p = 0.816; Figure 3E). This latter finding suggests that greater thickness of lDLPFC is related to both increased strategic behavior and impulse control, irrespective of age. In the sample of adults, analysis of the cortical thickness revealed no correlation with age in either lDLPFC or rDLPFC (p > 0.3). Interestingly, like in the sample of children, analysis of an age-corrected relationship between cortical thickness and individual differences in strategic behavior in the sample of adults revealed a significant positive correlation in lDLPFC (r = 0.663, p = 0.014; Figures 4B) but not in rDLPFC (r = 0.159; p = 0.587; Figure 4D). These data provide a striking convergence with the age-corrected cortical thickness in the children, showing that greater thickness in lDLPFC is linked to increased strategic behavior.

The mean turning angle evoked by VEGF164 in the presence

The mean turning angle evoked by VEGF164 in the presence this website of control IgG was 16.8° ± 2.4° (n = 9), but 0.0° ± 2.6° (n = 10) in the presence of the function-blocking anti-NRP1 antibody (p < 0.001). VEGF164 therefore signals through NRP1 to attract the growth cones of presumptive contralateral RGC axons. Based on these findings,

together with the expression pattern of VEGF164 and NRP1 and the loss-of-function phenotypes of the corresponding mouse mutants in vivo, we conclude that VEGF164 signals to NRP1-expressing RGC growth cones to promote axon crossing at the chiasmatic midline. Nerves and blood vessels ramify through tissues in strikingly similar patterns and develop during embryogenesis under the control of similar cellular and molecular mechanisms (reviewed by Ruiz de Almodovar et al., 2009 and Adams and Eichmann, 2010). Thus, classical axon guidance cues of the ephrin, netrin,

and SLIT families affect the growth of blood vessels. Conversely, it has been hypothesized that the main selleckchem vascular growth factor VEGF-A is important for axon growth and guidance, either in its own right or by competing with SEMA3A for NRP1 binding (reviewed by Carmeliet, 2003 and Ruiz de Almodovar et al., 2009). However, evidence is still lacking that VEGF-A controls axon guidance in vivo. By demonstrating that VEGF164 is expressed at the optic chiasm midline, is essential for RGC axon guidance and fasciculation in vivo, and promotes RGC axon outgrowth and attractive growth cone turning, we provide

evidence that VEGF-A is a physiological axon guidance cue (Figures 8A and 8B). We found that loss of VEGF164 or its receptor, NRP1, perturbs axon crossing at the optic chiasm in a similar manner in vivo, causing optic tract defasciculation and increasing ipsilateral projection. Because VEGF and NRP1 are well known for their essential roles in blood vessel growth (Kawasaki et al., 1999, Ruhrberg et al., 2002 and Gerhardt et al., 2004), we used endothelial-specific NRP1 mutants to exclude the possibility that loss of VEGF164 signaling inhibits contralateral axon growth indirectly by disrupting L-NAME HCl the brain vasculature. These mutants suffer blood vessel defects similar to those seen in full NRP1 knockouts (Gu et al., 2003), but do not display defects in midline crossing of contralateral RGC axons. VEGF164/NRP1 signaling therefore controls axon crossing at the optic chiasm independently of its role in blood vessels. Instead, our results support a model in which VEGF164 signals through NRP1 in RGC growth cones to regulate axon pathfinding directly (Figure 8B). Thus, we found that NRP1 is expressed strongly by contralateral RGC axons throughout the period of optic chiasm development, and that VEGF164 is a powerful chemoattractant for growth cones from presumptive contralateral RGC axons that acts in a NRP1-dependent fashion.