Viewed from a perspective of temporal dynamics, the high similarity of node relationships within SSM and visual systems and the default mode system might indicate that these systems in particular are relatively stationary, whereas other subgraphs SB203580 research buy such as task control systems might have more dynamic sets of relationships. It should also be noted

that several studies (Buckner et al., 2009 and Cole et al., 2010) have implicated the default mode system as the seat of the most prominent “hubs” in rs-fcMRI brain graphs. Although default mode nodes may indeed have many ties, the isolated nature of the default mode subgraph recasts the meaning of these nodes as hubs in the context of brain-wide rs-fcMRI networks. One of the more striking features of the modified voxelwise analysis is that subgraphs appear to be

arranged in spatial motifs throughout the cortex. Figure 7 demonstrates the presence of motifs at a single threshold of the modified voxelwise analysis. For each subgraph, the distribution of its spatial interfaces (defined as en face voxels) with other subgraphs is plotted, and then these neighboring subgraphs are examined to see whether they are themselves unlikely to interface selleck screening library (implying a 3-step motif). For example, the light blue subgraph interfaces predominantly with red and yellow subgraphs, which are themselves miniscule portions

of each others’ borders (red is 3.5% of yellow’s border, and yellow is 2.6% of red’s border), implying a yellow-light blue-red motif. Plots of relevant subgraphs on brain surfaces visually confirm the presence of motifs. Three instances of this motif are demonstrated, for the light blue, black (salience), and green (dorsal attention) subgraphs. Other 3-step motifs are present but not shown (e.g., red-teal-purple), and these motifs can be found up and down subgraph hierarchies (i.e., thresholds). A principal concern about such spatial motifs is that they are artifactual—that they arise as intermediate mixtures of adjacent signals, particularly when averaging over subjects. C1GALT1 Although these concerns cannot be entirely excluded, several interposed subgraphs (e.g., the green dorsal attention system or the teal ventral attention system) have firm and extensive experimental bases. If these are not considered artifactual, then other subgraphs deserve similar consideration. At the onset of functional neuroimaging some 25 years ago, investigators made educated guesses about the types of operations that the human brain must perform, and designed experimental paradigms to elicit such operations (Lueck et al., 1989, Pardo et al., 1991, Petersen et al., 1988 and Posner et al., 1988).

, 2011; Hupbach et al., 2007; Schwabe and Wolf, 2009) and during (Kuhl et al., 2011) new encoding has typically been linked to increased susceptibility to interference. For example, reactivation of memories prior to encoding of overlapping events has been associated with increased forgetting of reactivated memories (Diekelmann et al., 2011). However, one recent report demonstrated that reactivation of reward contexts associated with prior experiences during encoding of related events tracked the retention of originally learned information (Kuhl et al., 2010), providing speculative evidence that memory reactivation plays a role in reducing forgetting. The present data fundamentally

extend this work by demonstrating an alternate adaptive function of reactivation that supports memory integration and successful inference. Moreover, the current study provides evidence for the role of anterior Neratinib chemical structure MTL cortex in the reactivation Trametinib ic50 of prior event details during related experiences. Existing rodent (Ji and Wilson, 2007; Karlsson and Frank, 2009) and human (Kuhl et al., 2010) research

has primarily linked memory reactivation with hippocampal responses. In the present study, activation changes in anterior MTL cortex, but not hippocampus, correlated with the degree of overlapping memory reactivation across participants. We propose that hippocampus drives memory reactivation within ventral temporal regions through Peroxiredoxin 1 interactions with anterior MTL cortex. Anatomical evidence reveals that information from content-sensitive ventral temporal regions reaches the hippocampus primarily through inputs from entorhinal cortex, which, in turn, receives visual information from perirhinal and parahippocampal cortices (Suzuki and Amaral, 1994; Witter and Amaral, 1991). The output of hippocampal processing reaches ventral temporal regions through reciprocal pathways. This anatomical connectivity suggests that reactivation

of prior experience within hippocampus would first impact anterior MTL cortex responses, which, in turn, would influence processing in ventral temporal cortex. Thus, reactivation within ventral temporal cortex may be more closely coupled with anterior MTL cortex responses than with hippocampal activation. In the present study, changes in encoding activation within hippocampus were correlated with activation changes in anterior MTL cortex across participants (r = 0.46, p = 0.02), consistent with the idea of an indirect hippocampal influence on reactivation through anterior MTL cortex. As a second step in retrieval-mediated learning, the hippocampus would then bind reactivated memory content with the current event. Therefore, while anterior MTL cortex would track the degree of reactivation, it would be hippocampal responses that determine subsequent inference success. Future high-resolution fMRI studies of MTL function that utilize multivariate measures (Diana et al., 2008; Liang et al.

sanguineus. The esters acted on oocytes in the early development stages (I and II), which showed smaller size due to the impaired synthesis and incorporation of vitelline elements, making these cells unviable due to the action of the toxic product. The quality of the oocyte growth in arthropods is measured by the amount of proteins, lipids and carbohydrates incorporated during the formation of yolk granules. Despite controversies

about the way of acquisition (endogenous or exogenous) of lipid components deposited inside the cytoplasm, their presence is related to important functions, such as a nutritional reserve for the future embryo and the structuring of the oocyte chorion (Camargo-Mathias and Fontanetti, 1998). In the Enzalutamide mouse present study, lipid components were more evident in oocytes from all stages in TG individuals when compared to CG individuals it seems that, as with the protein components, there is an indirect effect of the action of esters on the synthesis Protein Tyrosine Kinase inhibitor of lipids. Ticks could be using lipids of oocytes

as the main source of energy to compensate for the reduction or absence of carbohydrates that had their synthesis affected by the ester. This explains the increased presence of lipids in the cytoplasm of TG oocytes demonstrated by the strong staining through the technique applied. In addition to the oocyte participation

in the synthesis of yolk components (endogenous), there is also the participation of other cells and structures in the vitellogenesis of ticks. According to Oliveira et al. (2007), pedicel cells also play an important role in the vitellogenesis of ticks, synthesizing and transferring different substances into the oocyte. The present study found the occurrence of extensive vacuolated areas often located in the oocyte region that makes direct contact with the pedicel cell, suggesting that the toxic agent circulating in the hemolymph could reach the oocyte via pedicel cells. Similar results were obtained by Roma et al. (2011) Evodiamine for ticks exposed to permethrin and by Denardi et al. (2010) when studying the effect of aqueous extract of neem leaves on the vitellogenesis of ticks. Thus, the part of the oocyte in direct contact with the pedicel cells would be the first region to receive the toxic agent and the first to suffer from its action. According to Oliveira et al. (2006), the protein components of the yolk are only deposited in the form of granules in R. sanguineus oocytes in the most advanced development stages (VI and V). However, it could be observed that in oocytes I, II III, there is positive staining for proteins ranging from weakly to moderately positive, with the exception of oocytes I from CG individuals, which are negative to the technique used.

, 2002 and Liu et al., 2007). However, the molecular mechanism

underlying the differences between DG and SVZ neurogenesis is largely a mystery. The cytoarchitecture of the two adult neurogenic regions are quite different. There are four key cell types in the SVZ: ciliated ependymal cells that face the ventricle lumen, providing a barrier and filtration system for cerebrospinal fluid; slowly proliferating stem cells; actively proliferating progenitor cells; and proliferating neuroblasts (Doetsch et al., 1999 and Seri et al., 2004). Ependymal cells were proposed to be SVZ stem cells (Johansson et al., 1999), but mounting evidence indicates that ependymal cells are not proliferative and do not have the properties of NPCs (Capela

Docetaxel and Temple, 2002 and Doetsch et al., 1999). Since FXR2 expression is restricted to NPCs and Noggin expression is restricted to the Selleck SB431542 ependymal cells, this differential expression prevents the direct regulation of Noggin expression by FXR2. We detected very low levels of Noggin protein in the early passage SVZ-NPCs, which could be due to contamination of residual ependymal cells during SVZ dissection. The DG lies deep within the hippocampal parenchyma. Type 1 radial glia-like (GFAP+Nestin+) cells are found to have stem cell properties, which can generate type 2a (GFAP-Nestin+) transient amplifying NPCs that differentiate into type 3 (DCX+) neuroblasts in the DG (Kriegstein and Alvarez-Buylla, 2009, Ming and Song, 2005, Seri et al., 2004 and Zhao et al., 2008). We found that Noggin and FXR2 are colocalized in the DG type 1 cells and FXR2 deficiency leads to increased proliferation of these cells. An ependymal-equivalent cell type has not been found in the DG. However, the neurons in the DG are in much closer proximity to stem cells compared with those in the SVZ; therefore, granule neurons may create a plausible stem cell niche in the DG, and increased neuronal Noggin

expression in the DG neurons of Fxr2 KO mice may be partially responsible for the phenotypes of DG-NPCs in Fxr2 KO mice. In summary, our data support the notion that the differences both in the intrinsic properties of NPCs and in the stem cell niche may contribute to the differences in neurogenesis seen between the DG and the SVZ. Noggin SPTLC1 plays important roles in many types of stem cells and helps maintain pluripotency in cultured stem cells (Chambers et al., 2009 and Chaturvedi et al., 2009). With regard to adult neurogenesis, Noggin inhibits BMP signaling to promote NPC proliferation and neuronal differentiation, while inhibiting glial differentiation (Chmielnicki et al., 2004 and Lim et al., 2000). Our data, together with previous study (Bonaguidi et al., 2008), suggest that Noggin and BMP may be key components of the mechanism underlying the differential regulation of DG and SVZ neurogenesis. Bonaguidi et al.

In addition, we also performed coculture experiments between cortical neurons expressing PCDH17-EGFP and CHO cells selleck inhibitor expressing either PCDH17-myc or PCDH10-myc. A significant portion of PCDH17-EGFP in neurons was localized next to PCDH17-myc in CHO cells at contact

points, but not PCDH10-myc in CHO cells (Figure 4E). Taking these results together with the finding that PCDH17 is mainly localized at both excitatory and inhibitory perisynaptic sites (Figure 3), we conclude that PCDH17 mediates homophilic intercellular interactions at synapses in basal ganglia (Figure 4F). To examine the physiological role of PCDH17, we generated PCDH17−/− mice ( Figure S3A). The success of the procedure was confirmed by Southern blot (data not shown) and PCR analysis ( Figure S3B). We confirmed the absence of the PCDH17 protein in PCDH17−/− mice by immunoblotting and immunostaining ( Figures S3C and S3D). The loss of PCDH17 in PCDH17−/− mice was also confirmed by immunoelectron microscopy (

Figure S3E). Quantitative analysis in the anterior Staurosporine manufacturer striatum verified a 96% reduction in numbers of immunogold particles in comparison with wild-type mice. The numbers of PCDH17−/− mice produced followed a Mendelian segregation pattern and these mice attained normal body size and appeared healthy (data not shown). Histological analysis using Nissl-stained coronal sections from the central nervous system from PCDH17−/− mice did not show any gross abnormalities in cytoarchitecture

( Figure S3F). In addition, the absence of PCDH17 did not find more affect the expression of synapse-specific markers, including N-cadherin, Synaptophysin, VGLUT1, PSD-95, NMDA receptor subunits, and AMPA receptor subunits in the anterior and posterior striatum ( Figure S3G). We examined whether axonal projections were abrogated in the absence of PCDH17. Immunostaining analyses showed that PCDH17 deficiency did not affect overall axonal projections, including corticothalamic/thalamocortical projections, striatopallidal/striatonigral projections, and nigrostriatal projections ( Figures S4A and S4B). Therefore, in contrast to the abnormal axonal projection phenotypes observed in PCDH10−/− mice ( Uemura et al., 2007), the overall circuitry in basal ganglia appeared to be intact in PCDH17−/− mice. We next evaluated whether ablation of PCDH17 affected the topographic connections within the corticobasal ganglia circuits. In retrograde tracing, local injections of CTb-Alexa Fluor 488 into the anterior striatum and CTb-Alexa Fluor 555 into the posterior striatum resulted in the labeled signals in medial prefronatal cortex and motor cortex, respectively, in both wild-type and PCDH17−/− mice ( Figure S4C). Thus, PCDH17 deficiency did not affect projection topography in corticostriatal pathways.

All recordings were taken at physiological temperature (36°C ± 1°C). Brains were frozen in “Lamb OCT” compound (Thermo Fisher Scientific) and CP-690550 ic50 cryostat sectioned at 12 μm in the transverse plane. Sections were incubated with primary Abs to Kv3.1b (1:1000; NeuroMab), Kv3.3 (1:1000; Alomone), Kv3.4 (1:100; Alomone), Kv2.1 (1:100;

Alomone), and diluted in PBS-T containing 1% BSA and 10% NGS overnight at 4°C. After three washes in PBS-T, sections were incubated with secondary Abs (1:1000, Invitrogen; Molecular Probes anti-goat Alexa Fluor 488 and 546 depending on primary Ab), and diluted in PBS-T, 1% BSA, and 10% NGS for 2 hr at room temperature. Images were acquired with a Zeiss laser-scanning confocal microscope (LSM 510; Carl Zeiss International). Tissue samples from the CA3 soma region of the hippocampus were excised Ivacaftor solubility dmso from the same batch of frozen cryostat sections used for immunostaining using laser microdissection (PALM laser system; Zeiss). PCR primers were designed using the Primer Express Software version 2.0 program (Applied Biosystems, Foster City, CA, USA). Primers were designed to cross exon-exon regions, and the gene of interest was normalized against a housekeeping

gene (β-actin) (see Supplemental Experimental Procedures). Statistical analyses utilized unpaired two-tailed Student’s t test and analysis of variance (ANOVA) with posttest to test for significance at p < 0.05. Data were tested for normality distributions. Data are denoted as mean ± SEM; “n” indicates number of neurons tested. Activation plots were fit by a Boltzmann function (I = Imax/(1+exp(V-V1/2/k)), with variables Imax, V1/2, and k (the slope factor).

Fits were performed using Clampfit 9.2 (Molecular Devices) or Excel (Microsoft) with least-squares minimization. Input resistance (Rs) was determined Lenvatinib ic50 using Ohm’s law applied to the voltage deflection in response to a 180 ms injection of 50 pA hyperpolarizing current applied at the resting potential. The membrane time constant was determined from a single exponential fit to the membrane-charging curve. This work was funded by the MRC, Deafness Research UK (M.D.H., PhD scholarship), and The Wellcome Trust’s Knockout Mouse Resource Committee for provision of the transgenic mouse lacking kcnb2 (LEX1551). Thanks to David Read for assistance with confocal imaging, and to Andy Randall, Timothy O’Leary, and David Wyllie for comments on a draft manuscript. “
“Neurons are rarely silent in the intact brain. Rather, intrinsic and network mechanisms interact to drive action potential firing, even in the absence of external stimuli. For example, multiple classes of inhibitory interneuron exhibit spontaneous spiking behavior in vivo (Gentet et al., 2010, Klausberger et al., 2003 and Ruigrok et al., 2011) and in vitro (Parra et al., 1998).

Increased ACR-16 targeting to synapses could provide a mechanism to explain the aldicarb-induced enhancement of synaptic transmission in rig-3 mutants. Consistent with this idea, the aldicarb hypersensitivity, the increased EPSC amplitudes, and the increased ACh-activated current after aldicarb treatment were all eliminated in acr-16; rig-3 double mutants ( Figure 5). The residual ACh-activated current in acr-16 mutants are a direct measure of Lev receptor function; consequently, this double

mutant analysis demonstrates that ACR-16 receptors are absolutely required for the synaptic effects of RIG-3, and changes in Lev receptor mediated currents are not observed in rig-3 mutants. Overexpression of ACR-16 in wild-type body muscles also produced hypersensitivity to aldicarb ( Figure 5A), suggesting that increased ACR-16 levels are sufficient to cause this defect. Tofacitinib nmr However, increased expression of the acr-16 gene is unlikely to explain the rig-3 mutant phenotype because quantitative PCR did not detect significant changes in acr-16 mRNA levels after aldicarb treatment: acr-16 mRNA levels after aldicarb treatment (normalized to untreated controls) rig-3 = 0.80 ± 0.09, www.selleckchem.com/products/Adriamycin.html wild-type = 0.77 ± 0.13. These results suggest that aldicarb regulates ACR-16 in a posttranscriptional manner in rig-3 mutants,

thereby enhancing synaptic transmission. These results also indicate that changes in ACR-16 can account for all of the rig-3 synaptic defects. The receptors present at a synapse are provided by the dynamic exchange between a mobile pool of receptors, and receptors bound at postsynaptic elements (Opazo and Choquet, 2011). To determine how RIG-3 alters this equilibrium,

we analyzed fluorescence recovery after GSK3B photobleaching (FRAP) of ACR-16::GFP puncta in the dorsal nerve cord (Figure 6). The ACR-16 FRAP observed in untreated wild-type controls and rig-3 mutants were not significantly different. After aldicarb treatment, FRAP was significantly increased in rig-3 mutants, but was unaltered in wild-type controls. By contrast FRAP of UNC-49::GFP (GABAA receptor) was unaltered by aldicarb treatment in both wild-type and rig-3 mutants ( Figure S5). These experiments indicate that aldicarb treatment significantly increased the population of mobile ACR-16 receptors in rig-3 mutants, but not in wild-type controls. These results support the idea that RIG-3 restricts the exchange between synaptic and mobile ACR-16 receptors, and that it does so by controlling the number of mobile receptors available for synaptic recruitment. A prior study showed that CAM-1, a Ror-type receptor tyrosine kinase (RTK), promotes ACR-16 delivery to NMJs, but does not regulate Lev receptor levels (Francis et al., 2005).

Highly overlapping structures are also identified for pain processing (Gauriau and Bernard, 2002; Saper, 2002). Autonomic and motor responses are tightly coupled to rewarding as well as aversive

events (and their expectations) or the saliency of sensory cues. In this sense, efferent copies of autonomic or motor signals may serve as a surrogate of important information for dopamine neurons, such as reward expectation and motivational saliency, in addition to general states of the animal. Although the role of these motor and autonomic inputs in the regulation of dopamine neuron activities is unclear, RG7204 cell line our finding provides a framework with which to explore the mechanisms of dopamine neuron regulation. It has been proposed that PTg plays an important role in reward prediction error computations PD0332991 order (Kawato and Samejima, 2007; Okada et al., 2009).

Previous studies have shown that electrical stimulation of PTg produced monosynaptic activation of dopamine neurons (Futami et al., 1995; Lokwan et al., 1999; Scarnati et al., 1984). Some anatomical studies have also indicated that PTg projects to both VTA and SNc using anterograde and retrograde tracing methods (Jackson and Crossman, 1983; Oakman et al., 1995; Zahm et al., 2011). These results appear to differ from our data indicating relatively sparse labeling of PTg from the VTA compared to SNc dopamine neurons. This difference may be explained if single PTg neurons make many synapses onto VTA dopamine neurons or synapses transmissions are strong. The aforementioned results may also be confounded by nonspecific electrical stimulation of passing fibers or uptake of tracers. Whether VTA receives strong direct inputs from PTg neurons remains to be clarified. Our method allowed us to avoid limitations of previous methods (i.e., cell-type specificity and labeling axons of passage), and the difference from

other studies may come, at least in part, from the Beta Amyloid specificity achieved using our method although the exact reasons need to be clarified in the future. It should also be noted that other anatomical studies have indicated that VTA does not receive strong inputs from PTg (Geisler and Zahm, 2005; Phillipson, 1979). Degeneration of SNc dopamine neurons leads to the severe motor impairments of Parkinson’s disease. Symptoms of this disease can be ameliorated by high-frequency electrical stimulation of specific brain areas (deep brain stimulation [DBS]) (Benabid et al., 2009; Wichmann and Delong, 2006). Despite the wide use and success of DBS, its mechanisms remain highly debated, and it is unknown why specific targets are more effective than others. The most popular target of DBS is the STh. As described earlier, we found relatively strong direct projections from the STh to SNc dopamine neurons.

3 channels.

Therefore, we may propose that CaV2.3 channels, in addition to other players, including T-type Ca2+ channels, the SR-ER Ca2+ ATPase (SERCA), and SKs ( Cueni et al., 2008, Huguenard, 1996, Llinas, 1988 and Perez-Reyes, 2003), have a critical role in oscillatory burst discharges in RT neurons. Simulation of such oscillatory discharges in a model neuron further strengthens our proposal: a simulated neuron lacking CaV2.3 component of Ca2+ currents mimics very closely the firing pattern of the mutant neurons in the experimental setting ( Figure S5). For details on simulation see Supplemental Experimental Procedures. CaV2.3 channels appear to play an important role in boosting the excitability of RT neurons. A significant reduction in the number of intraburst spikes in the first LT burst was observed in CaV2.3−/− RT neurons Bleomycin datasheet GW3965 cell line compared to the wild-type ( Figure 3). Similarly, in response to depolarizing

inputs, a significant reduction in the number of intraburst spikes and in the frequency of subsequent tonic firing was observed in CaV2.3−/− neurons ( Figure 6), suggesting that CaV2.3 channels contribute to excitability of those neurons. Potential influence of the AHP on the frequency of the subsequent tonic firing has been excluded by finding no statistically significant correlation between the amplitude of the preceding AHP and the frequency of the subsequent tonic firing, supporting our interpretation (data not shown). Moreover, an application

of apamin to wild-type RT neurons in the presence of TTX unmasked a slowly decaying plateau potential ( Cueni et al., 2008). The nonselective calcium-activated cationic current permeating Na+, K+, and Ca2+ ( Luzhkov and Aqvist, 2001) could be a possible candidate of the long-lasting plateau potential that was profoundly reduced in CaV2.3−/− neurons, suggesting Pentifylline that an initial LT Ca2+ influx further recruits CaV2.3 channels, which ensure the prolonged depolarization needed for increased firing activity of RT neurons. A similar role for CaV2.3 channels was also noted in the hyperexcitability induced by apamin ( Figure S2). Cellular and circuit properties of thalamic neurons give rise to thalamocortical oscillations in arousal/sleep states as well as seizures. RT neurons are known for their propensity to generate rhythmic burst discharges (Fuentealba and Steriade, 2005). It has been proposed that rhythmic burst discharges of RT neurons mediate inhibitory postsynaptic potentials in thalamocortical cells through GABAA and GABAB receptors (Kim et al., 1997). The GABAB receptor-mediated opening of K+ channels induces rebound bursting in a large proportion of thalamocortical neurons, leading to a paroxysmal activity (Beenhakker and Huguenard, 2009, Crunelli and Leresche, 1991, Steriade et al., 1993 and von Krosigk et al.

C. elegans is a rapidly emerging genetic model for probing axon regeneration in a mature nervous system. Its simple nervous system CH5424802 solubility dmso and transparency aids fluorescent labeling and precise severing of single axons by femtosecond ( Yanik et al., 2004) or dye laser ( Wu et al., 2007 and Hammarlund

et al., 2009) in live animals. Regenerative growth has been observed in many C. elegans neurons but has been most carefully described in the D-type GABAergic motor neurons and the PLM mechanosensory neurons. Typically, severed axons undergo reproducible morphological changes over the course of several hours, starting with a retraction of the axon at the site of injury, followed by the development of a growth cone-like structure ( Yanik et al., 2004). The filopodia at the leading edge of these structures extend and guide axons toward their targets over the course of several days ( Wu et al., 2007). Remarkably, the regrowth of GABAergic motor axons can lead to a partial functional recovery of the motor circuit ( Yanik et al., 2004 and El Bejjani and Hammarlund, 2012). Comparison of the recovery of severed axons in various C. elegans mutant backgrounds has allowed for the identification Selleck Talazoparib of factors that either promote or inhibit axon regeneration. For example, Dual Leucine-Zipper Kinase (DLK-1)-mediated MAPK signaling promotes axon regeneration

in multiple C. elegans neurons ( Hammarlund et al., 2009 and Yan et al., 2009). DLK signaling also promotes Wallerian degeneration,

as well as the regeneration of axotomized Drosophila olfactory receptor neurons and mouse dorsal root ganglion neurons ( Miller et al., 2009 and Xiong et al., 2010). Moreover, similar to vertebrate neurons, increased calcium and cyclic AMP facilitate axon regeneration in severed C. elegans neurons ( Ghosh-Roy et al., 2010). Therefore, conserved machineries involved in injury repair can be discovered through the analysis of the C. elegans nervous system. Two recent studies published in Neuron further exploit the robustness of postaxotomy regeneration of C. elegans neurons to identify novel factors that affect the regenerative capacity of a mature nervous system. Chen et al. (2011) presented find more the first systematic examination of genetic factors that regulate the regenerative growth of the PLM mechanosensory neuron. The regrowth of its longitudinal axon upon laser severing during the last larval stage was monitored in 654 loss- or gain-of-function mutants. A large number of genes, with roles in diverse cellular processes—signaling, cytoskeleton remodeling, adhesion, neurotransmission, and gene expression—are required for robust PLM axon regrowth in adults. By contrast, only 16 genes emerged as potent inhibitors of axon regrowth; the loss of these genes resulted in significant overgrowth of the PLM axon upon axotomy.