Figure 4D clearly demonstrates

the time specificity of po

Figure 4D clearly demonstrates

the time specificity of population coding during the cue processing period, whereas population coding in the delay period is more time stable. Again, there is no evidence for cross-generalization of coding during the cue or associated delay period to the target-related response (Figure 4E). The results so far suggest that information concerning selleck screening library trial type is maintained through the delay period as a stable low-energy state. Although the population response differentiates between the three alternative contexts, the underlying code does not resemble patterns observed during cue processing or the expected target. This nonstationary coding scheme contrasts with classic models of WM that posit persistent maintenance of the initial input representations (Miller et al., 1996; Wang, 2001) or preactivation of the expected target/memory probe (Rainer et al.,

1999). We suggest that the postcue state could reflect a temporary reconfiguration of the tuning profile in prefrontal cortex for flexible behavior, i.e., to discriminate choice stimuli according to context for “go”/“no-go” decision making. A systematic reconfiguration of the network state in prefrontal cortex would also be expected to alter the response characteristic of the network to fixed input (Mongillo et al., 2008; Sugase-Miyamoto et al., 2008). Indeed, we find that the population response to the neutral stimulus clearly differed as a function TCL of trial type (Figure 5A), even though the same neutral stimulus was used for all trial types (see Experimental Procedures). This suggests that the activation profile of the network is patterned according to trial type. To visualize the separation of activity states driven by the fixed neutral stimulus, we plot four independent estimates of the activity pattern associated with each trial type (color coded) onto the first two dimensions determined by MDS (Figure 5B; the full time course is captured in the Movie S3 available online). Data points clearly cluster as a function of trial type at 250 ms after stimulus

onset, reflecting systematic activity states that differentiate the response to the fixed neutral stimulus according to context. We propose that cue processing establishes a state in PFC that temporarily tunes prefrontal neurons to respond according to the current task context, i.e., to decide the appropriate behavioral response to choice stimuli. In a final set of analyses, we examined responses to the three choice stimuli that, according to the rule established by the current cue, could serve as either a “go” or “no-go” signal for the behavioral response. We defined stimulus 1 as the stimulus serving as a target with cue 1, but a distractor with cues 2 or 3, and similarly for stimulus 2 (target with cue 2) and stimulus 3 (target with cue 3).

Neuromodulation of circuit function has been studied for more tha

Neuromodulation of circuit function has been studied for more than 40 years in crustaceans and mollusks. The crustacean stomatogastric ganglion (STG) contains ∼30 neurons and the crustacean cardiac ganglion

contains only nine neurons. Both are central pattern generating circuits that generate fictive motor patterns when removed from the animal, and both are modulated by a large number of different substances (Blitz and Nusbaum, 2011; Cruz-Bermúdez and Marder, 2007; Johnson et al., 2011; Marder and Bucher, 2007; Stein, 2009; Wiwatpanit et al., 2012). Figure 2 summarizes a partial list of what is known about the neuromodulatory control of the crab STG. These data were accumulated over the years by many laboratories using a combination of immunocytochemistry and biochemical techniques. Most recently, mass spectrometry has allowed buy VX-770 the identification and characterization of many individual members of a number of different peptide families (Dickinson et al., 2009; Ma et al., 2009a, 2009b, 2009c; Stemmler et al., 2010). Many of the same substances are released both by descending modulatory neurons and by neurosecretory structures

as hormones. It is unlikely that the STG is unusual in the number of its modulatory inputs. A large number of neuromodulators are known to have important functions in the Aplysia feeding circuit ( Brezina and Weiss, 1997; Furukawa et al., 2003; Koh and Weiss, 2007; Li et al., 2001; Proekt et al., 2005; Sweedler et al., 2002; Vilim et al., 2010; Wu et al., 2010), another system in which the search for modulators selleckchem has been intense. And certainly, the number of important peptide modulators known in C. elegans and Drosophila is also large ( Bargmann, 2012; Taghert and Nitabach, 2012). In contrast, there are relatively few vertebrate circuits, in which there have been determined attempts

to find all of the modulatory inputs to the circuit. But, whether there are five or 12 or 25 modulators that can influence the output of a given circuit in the brain, no circuit is likely to be modulated by only one or two substances, no matter how tempting it is to think that a single substance is solely responsible for through controlling a significant piece of the brain. The exogenous application of neuromodulatory substances and the stimulation of modulatory projection neurons can significantly alter circuit output (Blitz et al., 2004, 1999, 1995, 2008; Dando and Selverston, 1972; Dickinson et al., 2001; Dickinson and Marder, 1989; Dickinson et al., 1990; Dickinson and Nagy, 1983; Eisen and Marder, 1984; Flamm and Harris-Warrick, 1986a, 1986b; Hooper and Marder, 1984, 1987; Nagy and Dickinson, 1983; Nagy et al., 1988; Nusbaum and Marder, 1988, 1989a, 1989b; Saideman et al., 2006, 2007).

The effects of adaptation in V1 neurons were manifestly different

The effects of adaptation in V1 neurons were manifestly different: receptive field profiles showed a marked repulsion (Figures 2E–2H). This repulsion distorted the relationship between stimulus position and preferred position (Figure 2F). The maximum repulsion occurred for V1 cells with receptive field profiles peaking ∼5° away from the adaptor (Figure 2H). The receptive field profiles of these cells were shifted

by ∼3.5°. Given the typical Enzalutamide ic50 tuning width (full-width at half-height [FWHH]) of 21°, this equates to a shift of ∼17%. These marked shifts in preference were accompanied by small changes in response gain (Figure 2G) and minor changes in tuning width (data not shown). These effects did not seem to depend on cortical layer and appeared to be weaker in some putative inhibitory interneurons, as judged by spike width (Figure S2). How can the same kind of adaptation regime impact two adjacent stages of processing so differently? One possibility is that adaptation changes the way that V1 operates on signals from the LGN. In particular, perhaps it changes the way that V1 neurons summate their LGN inputs, enhancing the contribution of LGN neurons tuned for positions that are distant from the

adaptor. Alternatively, V1 might be unaware of spatial adaptation and inherit it entirely from the changes that adaptation causes in LGN. Indeed, even if the summation rules between LGN and V1 remained fixed, mafosfamide V1 neurons would integrate over different profiles of LGN activity depending on the adaptation Selleck Perifosine condition. If this “cascade hypothesis” could account for the data, it would be preferable for its parsimony. The cascade hypothesis was indeed sufficient to account for the data (Figures 2I–2L). We considered a fixed summation model where V1 neurons obtain their spatial selectivity through a weighted sum of the appropriate LGN inputs, with

weights that are not adaptable. We then applied this model to LGN responses determined from our measurements (Figure 2I). The predicted V1 responses (Figure 2J) closely resembled the measured ones (Figure 2F): they showed a mild reduction in gain at the adaptor position (Figure 2K) and a clear repulsion of the tuning curves away from that position (Figure 2L). Overall, the model accounted for ∼98% of the variance in the V1 responses, and the residuals (data not shown) did not show much structure. The fixed summation model, therefore, provides a good account of the effects of spatial adaptation in V1. To illustrate the workings of the model, consider its predictions for the responses of a V1 neuron to two stimuli (Figure 3). Take first a stimulus that is close to the adaptor, 3° away. This stimulus elicits a profile of LGN activity that is barely affected by adaptation (Figure 3A).

These compounds may accordingly be useful for the differential di

These compounds may accordingly be useful for the differential diagnosis of neurological conditions in elderly subjects on the basis of the Sunitinib cost distribution of tau lesions, thereby opening up novel avenues for research in elucidating mechanisms of tau-mediated neurodegeneration, as well as tau-focused biomarkers and therapies. Despite numerous efforts to develop imaging ligands to visualize tau pathologies in the brains of patients with AD and related tauopathies, the urgent need for these tau biomarkers remains largely unmet. To address

this significant challenge, we also took advantage of a multimodal imaging system, which facilitates a quick and label-free validation of candidate compounds in terms of

their transfer to the brain and retention in tau-rich regions. In addition, subcellular-resolution imaging optics exemplified by two-photon laser scanning microscopy provided proof of the rapid transfer of intravenously administered potential tau pathology imaging agents from plasma to the CNS extracellular matrix and subsequently to the cytoplasm of neurons, where they can bind to intracellular tau inclusions. Based on these encouraging preliminary data using nonlabeled compounds, a subset of these compounds was radiolabeled for use in PET imaging of Tg mice that model tau pathology, and a radioligand that yielded the best visualization of tau lesions in these Tg mice was selected for further testing in human AD patients and NC subjects as well as patients check details with

probable CBD. This stepwise strategy enabled us to identify and advance the most promising PET probe for the visualization and quantitative assessment of tau pathology in the CNS of living human subjects. Interestingly, another research group has recently reported development of 18F-labeled PET ligands for tau lesions mostly through assessments of binding to brain tissues, but not recombinant tau assemblies (Zhang et al., 2012 and Chien et al., 2013), as in the present approach. These radioligands have been implied to produce considerably high contrasts for tau pathologies in living AD brains, Oxalosuccinic acid and relatively long radioactive half-life of 18F would enable delivery of radioligands from a radiosynthesis sites to multiple PET facilities. [11C]PBB3 has distinct advantages over these compounds, as exemplified by affinity for diverse tau lesions, including Tg mouse tau aggregates, applicability to multimodal imaging, and induction of smaller radioactive exposure than 18F-labeled ligands. In the present work, we clinically validated the performance of [11C]PBB3 as a tau imaging agent by comparing the distribution of [11C]PBB3 with that of [11C]PIB in AD brains.

Finally, the strength of a dendritic spike on a particular dendri

Finally, the strength of a dendritic spike on a particular dendritic branch has been shown to undergo activity- and experience-dependent plasticity (Losonczy et al., 2008; Makara et al., 2009). However, the functional interaction of dendritic NA+ spikes and inhibitory GABAergic microcircuits is so far completely unknown. Therefore, it is important to resolve how dendritic spikes could maintain their specific signaling functions, while interacting with an activity-dependent inhibitory micronetwork. The central question of this study is how linear and nonlinear excitatory signals in CA1 dendrites are controlled by recurrent inhibition. We coactivated excitation and inhibition by simultaneously

Selleck Selisistat using branch-targeted microiontophoresis of glutamate together with either selective electrical stimulation of CA1 recurrent inhibitory microcircuits or local GABA microiontophoresis. We demonstrate that correlated excitatory input on highly excitable dendritic branches can resist recurrent inhibitory control by initiating strong dendritic spikes, whereas inputs on other branches are subjected to powerful and dynamic regulation by inhibition. Selleckchem Ivacaftor Moreover, potentiation of branch excitability serves to achieve effective coupling of branch input to precisely triggered action potential output, independent of recurrent inhibition. To examine the interaction of dendritic excitation and inhibition

it is necessary to evoke spatially defined excitation. We achieved this tuclazepam by using glutamate microiontophoresis locally on dendritic branches of CA1 pyramidal neurons (Figure 1A;

Figures S2A and S2B available online; see also Experimental Procedures). Systematically increasing the iontophoretic current caused somatic EPSPs (iEPSPs) of increasing amplitude, which ultimately triggered action potentials (Figure 1B). The iEPSPs initially increased linearly in all branches, but a subset of basal and apical oblique dendrites exhibited supralinear dendritic spikes (Figure 1C). Supralinear events were not observed when microiontophoretic stimulation was applied to apical tuft dendrites (n = 42 branches; Figure S3). In the somatic recording, the dendritic spike manifested as a fast spikelet riding on the iEPSP followed by a slower NMDA receptor and voltage gated Ca2+ channel dependent component (Losonczy and Magee, 2006). The fast spikelet could be easily detected as a sudden increase of the first derivative of the voltage signal (ΔV/Δt; Figure 1C, lower traces). The latencies of the fast spikelet components did not differ significantly between weak (median latency 4.5 ± 2.6 ms SD; n = 186 dendritic spikes) and strong dendritic spikes (median latency 3.9 ± 2.2 ms SD, n = 185 dendritic spikes; p > 0.05; Mann-Whitney test, data not shown); yet, weak dendritic spikes showed higher temporal jitter (F-test, data not shown).

These studies have identified a set of intrinsic polarity regulat

These studies have identified a set of intrinsic polarity regulators, which function to ensure proper segregation of cell fate determinants into two daughter cells (Doe, 2008, Guo and Kemphues, 1996, Knoblich, 2010 and Lu et al., 2000). Compared to these advances, much less is understood about the regulation of asymmetric cell division and subsequent daughter cell fate choice in vertebrates. Despite that conserved counterparts to the invertebrate genes are found in vertebrates, the function of these proteins is only beginning to be elucidated (Doe, Alectinib research buy 2008, Götz and Huttner, 2005, Knoblich, 2010 and Williams et al., 2011). Available data suggest that vertebrates

may deploy these factors in new and different ways that remain enigmatic.

Radial glia in the developing vertebrate central nervous system (CNS) have stem cell-like properties (Götz and Huttner, 2005, Kriegstein and Alvarez-Buylla, 2009, Malatesta et al., 2000, Miyata et al., 2001, Noctor et al., 2001 and Temple, 2001). Previous studies in mammals (Bultje et al., 2009, Cayouette et al., 2001, Chenn and McConnell, 1995, Miyata et al., 2001, Miyata et al., Pifithrin �� 2004 and Noctor et al., 2004) and zebrafish (Alexandre et al., 2010, Baye and Link, 2007 and Das et al., 2003) show that during the peak phase of neurogenesis, radial glia progenitors predominantly undergo asymmetric divisions, serving as an excellent model for understanding how asymmetric cell division, self-renewal, and differentiation are regulated in vertebrate ALOX15 stem cells. An interesting behavior that vertebrate radial glia progenitors display is the interkinetic nuclear migration (INM) (Baye and Link, 2008, Miyata, 2008 and Sauer, 1935), which refers to the movement of progenitor nuclei between the apical and basal surfaces of the neuroepithelium in phase with their cell cycle. Studies in the developing chick CNS (Murciano et al., 2002) and zebrafish retina (Baye and Link, 2007 and Del Bene et al., 2008) suggest that proliferative (self-renewing) versus neurogenic (differentiating)

potential of radial glia progenitors is largely determined by their pattern of INM. In particular, Del Bene et al. (2008) proposes the presence of a Notch gradient between the apical and basal surfaces of the neuroepithelium, raising the possibility that extrinsic signals play a critical role in determining vertebrate progenitor self-renewal or differentiation in a location-dependent manner. Here, we carry out in vivo time-lapse imaging with single-cell resolution and perform clonal genetic mosaic analysis of individual radial glia lineages in the developing zebrafish brain. Our study uncovers a stereotyped pattern of asymmetric division that invariably generates a self-renewing daughter that migrates to a basal position and a differentiating sibling remaining at the apical position.

For each condition and decay, the value of the integral 20–10 ms

For each condition and decay, the value of the integral 20–10 ms before saccade initiation was recorded as the trigger threshold ( Figure S5B). We found that the trigger threshold was invariant with respect to task conditions (Fast/Neutral/Accurate condition) and made or missed deadline (premature Accurate/late Fast) when the selleck compound decay constant was in the range of plausible values (7.1 ms < τ < 166.7; McCormick et al., 1985). What differed between SAT conditions was

the amount of time needed for this integration to reach a single, constant threshold ( Figures 5 and S5B). We also computed the time course of integration for each RT quantile, separated by made/missed deadline and SAT condition. Remarkably, the trigger thresholds remained constant for both movement and visuomovement neurons ( Figures S5B and S5C). For each of 5,000 simulated trials per SAT condition, a start point (A) was drawn from a uniform distribution, and a drift rate (v) was drawn from a normal distribution with standard deviation s. The drift rate for distractor items was set to 1 − v. Activation functions that increased linearly with rate v were integrated with leak τ in the same manner as the movement activity described above. The values for A, v, and nondecision time T0 were allowed to vary between SAT conditions.

Selleckchem Osimertinib Leakage τ was not fixed but was shared across SAT conditions because cognitive state is unlikely to influence brainstem saccade-triggering mechanisms. The distribution of simulated RTs and proportions correct were compared against Vincentized behavioral data using

χ2. Outliers were removed from the behavioral and simulated data by eliminating values beyond median ± 1.5 × the interquartile range for each condition separately. Data are presented as defective CDFs, normalized to the mean accuracy rate. Minimization was carried out in several steps, first using multiple runs of the genetic algorithm in MATLAB with different random number seeds and values for s. The best fitting of these were minimized again with bounded simplex algorithms. This work was supported by F32-EY019851 to R.P.H. and by R01-EY08890, P30-EY08126, P30-HD015052, and the E. Bronson Ingram Chair in Neuroscience. We would like to thank S. Cediranib (AZD2171) Brown, J. Cohen, R. Desimone, P. Holmes, G. Logan, A. Maier, P. Middlebrooks, T. Palmeri, M. Paré, B. Purcell, R. Ramachandran, R. Ratcliff, F. Tong, M. Wallace, X.J. Wang, and B. Zandbelt for comments. R.P.H. designed the study, collected the data, and analyzed the results. R.P.H. and J.D.S. wrote the paper. “
“Despite the widespread use of functional magnetic resonance imaging (fMRI), the relative contributions of processes like feedforward, feedback, excitation, and inhibition to the blood oxygenation level-dependent (BOLD) signal remain unknown.

While there were no differences between the groups prior to immer

While there were no differences between the groups prior to immersion or when warmed, immediately after removal from the warm water, the core body temperature of DTX-treated mice dropped significantly lower than that of saline-treated mice and took longer to recover (Figures 6C and 6E, on days 3 and 6 after saline/DTX treatment). Moreover, on day 6, core body temperature at baseline was significantly lower in DTX-treated mice when compared to saline-treated controls (Figure 6E). These data collectively

indicate that CGRPα DRG neurons play a critical role in thermoregulatory mechanisms after Selleckchem GSK1210151A whole-body cooling. In the same assay, DTX-treated mice repelled water to the same extent as saline-treated mice 3 days after saline/DTX treatment (Figure 6D) but retained significantly more water weight on day 6 (Figure 6F), suggesting a moderate impairment of fur barrier function. This impairment might be due to loss of CGRP-IR guard hair innervation (Figure S2). Guard hairs add a water repellent, oily sheen to the coat of furry mammals. And CGRP-IR primary afferents fire in response to guard hair displacement (Lawson et al., 2002; Woodbury et al., 2001). Given that DTX-treated mice had enhanced responses to multiple cold stimuli and had difficulty warming themselves

when cooled, we hypothesized that DTX-treated mice might prefer a warmer environment over a relatively cooler environment. To test this possibility, we monitored the amount of time saline- and DTX-treated mice spent on two surfaces NVP-AUY922 set at equivalent (25°C versus 25°C) or different (25°C versus PAK6 30°C; 20°C versus 30°C; 30°C versus 40°C) temperatures. The mice demonstrated no preference when the two surface temperatures were equivalent, as expected (Figures 6G and 6H). However, when surface temperatures differed, DTX-treated mice spent significantly more time on the warmer surfaces

(Figures 6G and 6H). This behavior was remarkably consistent between male and female mice and suggests that DTX-treated mice prefer warmer temperatures (or show enhanced avoidance of cooler temperatures). Since ablation of CGRPα DRG neurons enhanced behavioral sensitivity to cold but did not alter peripheral nerve responses to cold, this suggested that CGRPα DRG neuron ablation might instead alter central processing of temperature signals, at postsynaptic targets in the spinal cord. To assess central alterations in function, we measured baseline and agonist-evoked spontaneous excitatory postsynaptic current (EPSC) frequency in spinal cord slices from saline- and DTX-treated CGRPα-DTX+/− mice. We used capsaicin to activate TRPV1/heat-sensing afferents and icilin to activate TRPM8/cold-sensing afferents. These agonists are known to increase EPSC frequency in spinal neurons that are postsynaptic to TRPV1 and TRPM8 DRG neurons, respectively (Yang et al., 1998; Zheng et al., 2010).

During slice experiments, mIPSCs were recorded in the presence of

During slice experiments, mIPSCs were recorded in the presence of 5 μM NBQX and 1 μM TTX to block glutamatergic transmission and spontaneous activity, respectively. At a holding potential of −80 mV, mIPSCs were easily visible in MSNs (Figures 5A and 5D). The majority of these events likely arise from FS interneurons,

which have high rates of spontaneous release (Bacci et al., 2003 and Xiang et al., 2002) and form more numerous proximal synapses on MSNs than other selleck cell types (Gittis et al., 2010 and Taverna et al., 2008). In saline-injected mice, the frequency of mIPSCs was significantly higher in D1 MSNs than D2 MSNs (p = 0.02; Figure 5H), mirroring the higher connection probability normally observed between FS interneurons and D1 MSNs (Figure 1A). Mice injected with 6-OHDA showed no significant difference in mIPSC amplitudes (Figures 5B, 5E, and 5G) but showed a nearly 2-fold increase in mIPSC frequencies selectively in D2 MSNs (p = 0.0007) (Figures 5C, 5F, and 5H). The lack of change in mIPSC amplitude distribution after dopamine depletion (and enhanced FS innervation) indicates that mIPSCs recorded from MSNs arise predominantly from FS inputs, both before and after dopamine depletion. The increase in mIPSC frequency selectively in D2 MSNs is consistent

with increased innervation from FS interneurons. However, given the lack of increase in uIPSC amplitude (Figure 1E), these data suggest that for any given FS-MSN Alectinib purchase pair, the number of synapses formed is stereotyped. Thus, pre-existing FS-MSN pairs were not significantly strengthened, whereas new FS-MSN pairs were connected, on average, by similar numbers of synapses as preexisting pairs. To determine whether changes

in inhibitory innervation persist beyond 1 week, we measured mIPSCs in mice 2 weeks and 1 month after injections. Similar to data at 1 week, we observed changes in mIPSC frequency (but not amplitude) selectively in D2 MSNs (Figure S3). In saline-injected mice, mIPSC frequency was higher in D1 MSNs than D2 MSNs. In 6-OHDA-injected mice, mIPSC frequency in D2 MSNs was significantly increased at 2 weeks (p < 0.0001) and 1 month 17-DMAG (Alvespimycin) HCl (p = 0.003). These data suggest that increased innervation of D2 MSNs by FS interneurons persists for at least 1 month. To probe how increased connections from FS interneurons to D2 MSNs can affect striatal function, we developed a simple model of the striatal microcircuit (Figure 6A). MSNs and FS interneurons were modeled as single-compartment neurons with intrinsic properties that matched experimental data (see Experimental Procedures). Individual FS interneurons connected to D1 and D2 MSNs with probabilities based on data from Figure 1 (connection probabilities in the control model network were 0.5 for FS-D1 MSNs and 0.

5 ( Figures 3A–3E) Because Tbr2 may also label some differentiat

5 ( Figures 3A–3E). Because Tbr2 may also label some differentiating neurons ( Pontious et al., 2008), we next

analyzed the fraction of these cells that also expressed the proliferation marker Ki67. We observed that the number of Tbr2+ progenitor cells (IPCs) in the cortex of Robo1/2 mutants was almost double than in controls at E12.5 ( Figures 3F–3H). Thus loss of Robo1/2 function leads to a depletion of VZ progenitors and to an abnormal increase in the numbers of IPCs in the developing cerebral cortex. Analysis of Robo1 and Robo2 single mutant embryos revealed that the phenotypic changes found in the cortex of Robo1/2 mutants were primarily due to the loss of Robo2 ( Figure S4). Nevertheless, the raise in the number of IPCs found in Robo2 single mutants Veliparib is milder than in Robo1/2 double mutants, which suggested that Robo1 cooperates with Robo2 in regulating the production of IPCs. Altogether, these results indicated that Robo receptors modulate

neurogenesis in the developing brain. Slit proteins are the ligands of Robo receptors in cell guidance, and so we tested whether Slits AZD6738 also mediate the function of Robo receptors in neurogenesis. Analysis of the distribution of Slit1 and Slit2 mRNA at different developmental stages revealed multiple sources of Slit proteins that could influence telencephalic progenitor cells ( Figures 4A, 4B, and S5A–S5J). We were particularly intrigued by the expression of Slits in the choroid plexus and in other cells lining the ventricle, because recent work suggests that factors present in the cerebrospinal fluid (CSF) modulate the proliferation of cortical Non-specific serine/threonine protein kinase progenitor cells ( Lehtinen et al., 2011). Consistent with this idea, we found that Slit proteins are indeed present in the CSF of mouse embryos at E12.5 ( Figure 4C). We also observed that

a recombinant Slit2-alkaline phosphatase fusion protein (Slit2-AP) binds homogenously throughout the ventricular surface of E12.5 telencephalic hemispheres ( Figure 4D). This experiment reinforced the idea that Slits present in the CSF may bind to Robo receptors expressed by progenitor cells in contact with the ventricle, thereby modulating neurogenesis at early stages of cortical development. To directly test the function of Slits in regulating the proliferation of cortical progenitors, we analyzed progenitor cell dynamics in Slit mutants. Analysis of Slit1 and Slit2 single mutant embryos revealed no differences in the density of PH3+ VZ progenitor cells or in the number of Tbr2+ IPCs ( Figures S5K– S5R). In contrast, we found that the density of PH3+ nuclei in the VZ of the developing cortex was reduced in Slit1/2 double mutants compared to controls ( Figures 4E, 4F, and 4I). In addition, we observed that the amount of Tbr2+ cells was greatly increased in Slit1/2 double mutants compared to controls ( Figures 4G–4I).