As previously described for IR25a ( Benton et al., 2009), IR8a is detected in both the cell body and sensory dendritic endings,

but not in axon termini, consistent RO4929097 concentration with a role in peripheral odor detection (Figures 1C and 3B; data not shown). To confirm the specificity of these antibodies and initiate functional analysis of these receptors, we generated null mutations in IR8a by the same gene-targeting strategy used for IR25a ( Benton et al., 2009) ( Figure 2A). Homozygous IR8a, IR25a, and IR8a/IR25a double mutant animals are viable and fertile, and all corresponding immunoreactivity in the antenna is abolished ( Figure 2A). The broad antennal expression and cilia localization of IR8a and IR25a indicated that these receptors might have a widespread role in odor Epacadostat clinical trial detection in IR neurons. We tested this hypothesis by performing extracellular electrophysiological recordings of odor-evoked neuronal responses in individual coeloconic sensilla in IR8a and IR25a mutants. Four classes of coeloconic sensilla have been defined, named ac1 through ac4 ( Benton et al., 2009 and Yao et al., 2005). These house neurons that express different combinations of IRs and display distinct odor sensitivities ( Figure 2B) ( Benton et al., 2009 and Yao et al., 2005), although matching of the specific ligands to receptors has yet to be determined in most cases. We tested a panel of seven odors, representing the

best sensilla-specific agonists identified in previous or on-going ligand screens ( Yao et al., 2005; R. Rytz and R. Benton, unpublished data), which we assume are recognized by different IRs. The ac4 sensilla contain three neurons and are stimulated by phenylacetaldehyde and phenylethyl amine (Figure 2B). We observed that IR8a mutant ac4 sensilla lack all responsiveness to phenylacetaldehyde, while phenylethyl amine responses are unchanged ( Figures

2B and 2C). Spontaneous activity in IR8a mutant ac4 sensilla (25 ± 4 spikes/s [mean ± SEM]; n = 13) is also markedly reduced compared with the wild-type (82 ± 1 spikes/s; n = 11). These electrophysiological phenotypes resemble those of mutants in IR84a (Y. Grosjean Idoxuridine and R.B., unpublished data), suggesting a role for IR8a in acting with this receptor in mediating both basal and evoked responses in IR84a neurons. By contrast, mutation of IR25a had no effect on phenylacetaldehyde responses but abolished phenylethyl amine-evoked activity ( Figures 2B and 2C), suggesting an essential function in a different IR neuron. Spontaneous activity in IR25a mutant ac4 sensilla was also reduced (43 ± 6 spikes/s; n = 18). The ac3 sensilla house two neurons, one of which expresses three IRs (IR75a, IR75b, and IR75c) and responds to propionic acid (Benton et al., 2009 and Yao et al., 2005). Responses to this ligand are abolished in IR8a, but not IR25a, mutants ( Figure 2B).

, 2008) also contributes to the impaired polarization phenotype, because defective migration may prevent

proper reception of other polarizing factors along their migratory route. Furthermore, downregulation of Sema3A signaling in these cortical VEGFR inhibitor progenitors resulted in significant reduction of the growth of the leading process in cells located at the IZ and CP (Figure 6). Together with our findings on the effect of Sema3A on the selective promotion of dendrite growth and suppression of axon growth in cultured hippocampal neurons (Figure 5), these results would support the notion that Sema3A might regulate neuronal polarization and dendrite development by acting directly to promote dendrite growth. We note that the identity of the AZD2281 specific Plexin coreceptors that mediate the Sema3A effects on neuronal polarization together with NP1 remain to be determined.

Intracellular signaling pathways involved in neuronal polarization have been extensively examined in cultured neurons, but the extracellular polarizing factors that activate these signaling pathways in vivo remain largely unknown. Secreted molecules such as BDNF (Yoshimura et al., 2005 and Shelly et al., 2007), NGF (Da Silva et al., 2005), Insulin-like growth factor-1 (IGF-1) (Sosa et al., 2006), netrin-1 (Mai et al., 2009), and transforming growth factor beta (TGF-β) (Yi et al., 2010) were shown to promote axon initiation and growth in cultured hippocampal neurons, although our stripe assay failed to show the polarizing effect of NGF and netrin-1 (Figure 1). CYTH4 The latter discrepancy may be caused by the differences in the culture conditions or the sensitivity of the

methods for assaying polarization. However, no axon formation defect was detected in mice with targeted deletion of genes for NGF (Crowley et al., 1994) and BDNF (Jones et al., 1994), or for their respective receptors TrkA (Smeyne et al., 1994) and TrkB (Klein et al., 1993). A notable exception is TGF-β, whose receptors are essential for axon formation in embryonic cortical neurons in vivo (Yi et al., 2010). We note that in utero electroporation was used in the latter study to perturb the signaling of TGF-β receptors in a subpopulation of cortical neurons, unlike the earlier studies with genetic deletion over entire population of neurons throughout prolonged developmental period. Differences between the methods used to assay effects of gene downregulation may account for the lack of apparent effects in some of these studies. In this study, we provided evidence that Sema3A may also regulate neuronal polarization in vivo. However, neuronal polarization in the developing brain is likely to depend on the coordinated actions of many extracellular factors. In addition to Sema3A (Polleux et al., 2000 and Chen et al., 2008), the spatially regulated expression of other secreted molecules in the developing cortex has been reported.

Bargmann, L.Vosshall, and members of the Young Lab for critical comments on the manuscript and discussions. This research was supported by NIH grants NS053087, GM054339, and MH015125 to M.W.Y., and by NIH Ruth L. Kirchstein postdoctoral fellowship GM080934 to N.S. “
“A major neural substrate for the rewarding actions of opiates is dopaminergic (DA) neurons within the ventral tegmental area (VTA). Opiates acutely activate VTA DA neurons by inhibiting

their GABAergic input through hyperpolarization of local GABA interneurons (Johnson and North, 1992), and decreasing long-term potentiation of GABAergic synapses onto DA neurons (Niehaus et al., 2010). Additionally, VTA DA neuron activity in vivo is increased in morphine-dependent rats, an effect normalized by either spontaneous or naloxone-precipitated Autophagy Compound Library research buy withdrawal (Georges et al., 2006). However, the influence of chronic opiates on the intrinsic excitability of VTA DA neurons remains unknown. selleck chemicals llc At a cellular level, we have shown that both chronic morphine administration and heroin self-administration in rats decreases the soma size

of VTA DA neurons (Russo et al., 2007 and Sklair-Tavron et al., 1996). This reduced soma size is mediated by downregulation of a specific brain-derived neurotrophic factor (BDNF) signaling pathway involving insulin receptor substrate 2 (IRS2): the decrease in DA cell size is blocked by local infusion of BDNF (Sklair-Tavron et al., 1996) or viral-mediated overexpression of IRS2 in VTA, and mimicked by viral-mediated overexpression of a dominant-negative mutant of IRS2 (IRS2dn) in this brain

region (Russo et al., 2007). Importantly, the decrease in soma size correlates with reward tolerance (Russo et al., 2007), where repeated drug use decreases the rewarding effect of the drug and leads to an escalation heptaminol of drug intake, as seen in humans (O’Brien, 2001). While these studies suggest that the protein kinase AKT, which is downstream of IRS2, is necessary and sufficient for the morphine-induced decrease in VTA cell size, the downstream signaling mechanisms involved remain unexplored. Moreover, the net effect of this decrease in VTA DA neuron soma size, along with any change in cell excitability, is unknown, although there are several reports of altered VTA DA soma size under other conditions (see Discussion). Here, we focused on adaptations that chronic opiates induce in VTA DA neurons by further characterizing morphine-induced changes in VTA soma size, excitability, and functional output to target brain regions. We focus on AKT and one of its major downstream pathways, mammalian target of rapamycin (mTOR), as the critical mediators of morphine action, given the widely established role of this signaling pathway in cell growth. The serine/threonine kinase activity of mTOR, and its downstream substrates, depend on mTOR’s association into two distinct complexes designated mTORC1 and mTORC2 (Foster and Fingar, 2010 and Laplante and Sabatini, 2009).

, 2009), indicative of strong Ca2+ clearance followed by an integrating increase in signal. Sites distal to the synapse show little change initially, consistent with the source of Ca2+ being at a distance, followed by a slow increase. The later signals (Figures 7I–7K), corresponding to the onset of the superlinear response, present

a different picture. Ca2+ at the synapse shows an abrupt CP868596 increase in signal, followed by a plateau and decrease in signal even in the face of constant Ca2+ entry (Figures 7D and 7J). Ca2+ signals away from the synapse show a slower integrating signal followed by a sudden increase in signal whose rate is faster and peak greater than that observed at the synaptic region (Figure 7J). The change in kinetics at these distant sites suggests a secondary source of Ca2+. Similar results

were obtained in five cells where the superlinear release component was observed. Smaller depolarizations revealed simple integrating responses that diminished away from the synapse while larger depolarizations yielded similar complex responses (Figure S7). Together these data suggest http://www.selleckchem.com/products/MK-2206.html that Ca2+ dynamics are complex, clearance near the synapse is strong, and a second source of Ca2+ may play a role in vesicle trafficking. Also, although the second component of release appears to be superlinear when compared to the Ca2+ integral, indicating more release per Ca2+

for the second component, when compared to the Ca2+ fluorescent signal the opposite is true. By using fluorescence changes at the synapse, the ratio (Cap/Fluor) of the first component divided by the second component provided an indicator of relative efficiency of release and was 1.5 ± 0.4 (n = 3), indicating that release was more efficient at lower values of Ca2+. Utilization Thymidine kinase of a two-sine technique for real-time tracking of vesicle fusion has allowed for more detailed investigation of presynaptic release components at the auditory hair cell-afferent fiber synapse. By using stimuli that did not elicit maximal ICa, saturable pools were clearly identified, whereas variability between and within cells made this impossible (in turtle) with the single-sine technique (Schnee et al., 2005). A superlinear release component whose onset varied with Ca2+ load and correlated with release of an additional source of Ca2+ was also revealed. The superlinear component of release is postulated to reflect the ability of hair cells to rapidly recruit vesicles from regions distant from the synapse, which may underlie the inability to deplete vesicle pools and the ability of hair cell synapses to operate at high rates for sustained periods of time.

Changes

between rest, quality, speed, and aerobic training phases did not appear to elicit any significant change in cardiac autonomic nervous system activity Saracatinib manufacturer for either amputee swimmer. This similarity in training quantity may have blunted any shift in autonomic nervous system activity from one training phase to another. Further, the minimal variation in cardiac autonomic nervous system activity suggests the periodised training program may have been similar in load, volume, and consequent training response even though there were apparent changes in training emphasis. Similar results have been seen in able-bodied swimmers, with no apparent change in HRV following four weeks of training in the lead up to competition, suggesting the athletes did

not require further adaptive responses to training.18 Results from the current study suggest this lead in period of 17 weeks and the periodised program prepared each athlete effectively as they each made the final and swam a personal this website best in their main event. Despite each athlete’s exposure to various forms of progressive overload training during the lead up to the Paralympic games, each athlete appeared to respond well during periods of rest and recovery throughout each training phase. These results are in contrast to research showing a shift in cardiac autonomic activity following periods of intense training in elite junior rowers.19 Iellamo and colleagues19 found a distinct shift in cardiac autonomic function when rowers

were exposed to endurance training loads at 100% of their maximum efforts, in the lead up to the world championships. The results observed in the current study may differ from previous research19 as the swimmers in the current study were not exposed to endurance based intensive training loads and as such displayed a different cardiac autonomic response to training. While all HRV indices for athlete 2 and 3 were similar for all training phases, HF (nu) for athlete 1 was significantly higher during the quality training phase compared against all why other training phases. Increases in vagal-related HRV indices have been linked with improved performance in adolescent swimmers.13 Finally, no significant change in HRV was observed when each athlete shifted from their normal periodised training program to their specific taper in the lead up to the London 2012 Paralympic Games. These findings contradict previous reports of increased HRV following a 2-week taper.13 Unlike the previous research, the taper phase in the current study followed a gradually reduced training load, to alleviate the stress of international travel. This steady decline in training load prior to the taper and subsequent competition may have diminished the rebound in autonomic nervous system activity often evident during periods of reduced training.

3 ± 3.0 mV; median 6.7 mV; range 0.5 to 11.0 mV); latency (mean 8.6 ± 2.7 ms; median 8.7 ms; range 5.3 to 12.7 ms); time-to-peak (mean 16.0 ± 9.9 ms; median 13.8 ms; range 4.9 to 37.2 ms); duration (mean 52.5 ± 27.0 ms; median 51.8 ms; range 9.1 to 103.1 ms); and rate of rise (slope, mean 0.56 ± 0.49 V/s; median 0.41 V/s; range 0.09 to 1.52 V/s) (Figures 4B). Cells with shorter latency tended to exhibit larger-amplitude subthreshold responses and neurons exhibiting a fast time-to-peak also tended to have a shorter-duration response (data not shown). Neurons recorded deeper DAPT supplier in L2/3 responded with PSPs of larger-amplitude depolarizations, shorter latencies, shorter-duration

responses, and faster rates of rise (PSP slope) (Figure 4B). Therefore, deeper neurons, located

in layer 3, preferentially signal each individual contact with high temporal precision, whereas the more superficial layer 2 neurons preferentially integrate touch responses over a longer timescale. Nine identified layer 2/3 pyramidal neurons were recorded in adjacent barrel columns (Table S1). The grand averaged response to active touch of the C2 whisker with an object reveals a smaller amplitude response with longer latency in the surrounding cortical columns, but otherwise sharing a similar range of response properties (Figure S2). That the touch response spreads to neighboring columns is consistent with voltage-sensitive dye imaging data showing that a large area

of cortex can depolarize in response to single whisker active touch in awake mice RAD001 in vivo (Ferezou et al., 2007). These data are also consistent with the broad subthreshold receptive fields of layer 2/3 neurons evoked by passive whisker deflection recorded under anesthesia (Moore and Nelson, 1998, Zhu and Connors, 1999 and Brecht et al., 2003). Consecutive touches evoked different amplitude touch PSP responses (Figure 5A) (coefficient of variation mean ± SD 1.4 ± 0.7; median 1.0; range 0.4 to 3.1). Part of the variability of the touch response could be accounted for by considering the neuronal membrane potential immediately preceding the response onset, which profoundly influenced the PSP amplitude. Touch responses evoked at spontaneously hyperpolarized precontact Vm were larger in amplitude Non-specific serine/threonine protein kinase compared to touch responses occurring during spontaneously depolarized membrane potentials (Figure 5B). Indeed, at the most depolarized precontact membrane potentials, the touch response was hyperpolarizing (Figure 5B). Plotting the active touch response amplitude as a function of the precontact Vm revealed a close to linear relationship (Figure 5C). The correlation between response amplitude and precontact Vm was significant (α = 0.05) in all 17 neurons tested (cell #36 had a complex depolarizing-hyperpolarizing response and was not included in the subsequent active touch response dynamic analysis; see Table S1). The mean coefficient of correlation was −0.

0 NA) water immersion objective. SpH was excited at 488 nm using a Polychrome IV monochromator (Till Photonics). Electrophysiological and FM2-10 based measurements were carried out as previously described (Rozas et al., 2011) (see Supplemental Experimental Procedures for details). We followed the procedures previously described (Rozas et al., 2011) (see Supplemental Experimental Procedures for details). Muscles in resting

conditions or after stimulation (180 s at 30 Hz) were processed for conventional transmission electron microscopy (for details, see Supplemental Experimental Procedures). Images were taken on a CM-10 (Philips) electron microscope with Veleta (Olympus) camera controlled by iTEM platform (Olympus SIS). This work has been Target Selective Inhibitor Library cell assay supported by Spanish MINECO (Juan de la Cierva and FPU Programs, BES2008-002858, BFU2007-66008, BFU2010-15713, ERA-NET NEURON EUI2009-04084, CTQ2009-14431/BQU, SAF2010-20822-C02), Junta de Andalucía (P06-CVI-02392,

P07-CVI-02854), Xunta de Galicia (INCITE09 209 084PR), HFSP (RGP 0045/2002-C and CDA0032/2005-C), Instituto de Salud Carlos III and FEDER. We are grateful to T.C. Südhof, W.J. Betz, G. Alvarez de Toledo, W. Regehr, and F.J. Urbano for critical reading of previous or recent versions of the manuscript and insightful comments; M.L. Montesinos, R. Ruiz, O. Uchitel, and F.J. Urbano for technical advice; L. Tabares for loan of equipment; J. Lopez-Barneo for support and advice; T.C. Südhof and P. McPherson for antibodies; Alejandro Arroyo and M. Carmen Rivero for excellent technical assistance; G. Cantero for help with

genotyping; I. Benito for help with mouse husbandry learn more and C.O. Pintado for transgenesis. Part of the study performed at CITIUS (University of Seville). “
“At both vertebrate and invertebrate synapses, alterations in synaptic activity trigger homeostatic responses that modulate synaptic strength; it appears that these homeostatic responses manifest as changes in postsynaptic receptor expression as well as retrograde regulation of transmitter release (Branco et al., 2008, Cai et al., 2008, Davis, 2006, Goold and Nicoll, 2010, Jakawich et al., 2010, Petersen et al., 1997, Sandrock et al., 1997, Stellwagen and Malenka, 2006, Sutton and Schuman, 2006, Turrigiano and Nelson, 2004 and Turrigiano et al., 1998). Postsynaptic translation plays an important role in mafosfamide local changes in postsynaptic receptor expression (Bidinosti et al., 2010, Costa-Mattioli et al., 2009, Menon et al., 2004, Sigrist et al., 2000 and Sutton et al., 2007); however, we know little about whether translational mechanisms also participate in the retrograde control of neurotransmitter release. At the Drosophila larval neuromuscular junction (NMJ), loss or inhibition of glutamate receptor subunit IIA (GluRIIA) triggers a robust retrograde increase in neurotransmitter release to compensate for the reduction in postsynaptic receptor function ( Frank et al., 2006 and Petersen et al., 1997).

To determine whether clustering of dynamic inhibitory synapses with dynamic spines were

merely a reflection of the dendritic distribution of inhibitory synapses learn more and spines, we performed nearest neighbor analysis between every monitored dynamic and stable inhibitory synapse and every dynamic and stable spine (Figure 5C). We found that inhibitory synapse changes occur in closer proximity to dynamic dendritic spines as compared to stable spines (K-S test, p < 2.0 × 10−6; Figure 5D). Conversely, dendritic spine changes occur in closer proximity to dynamic inhibitory synapses as compared to stable inhibitory synapses (K-S test, p < 2.0 × 10−4; Figure 5E). Interestingly, dendritic spine changes were not clustered with each other and indeed occurred with less proximity to neighboring dynamic spines as compared to stable spines (stable spines versus dynamic spines, K-S selleck chemicals llc test, p < 0.05; Figure 5F). We observed no difference in nearest neighbor distribution between dynamic inhibitory synapses and their dynamic or stable inhibitory counterparts (Figure 5G). These results demonstrate that dendritic spine-inhibitory synapse changes are spatially clustered along dendritic segments, whereas dendritic spine-dendritic spine changes and inhibitory synapse-inhibitory synapse changes are not. Clustered dynamics were the same for inhibitory shaft or spine synapses in relation to the nearest

dynamic dendritic spine (Figure S5B). We next asked how altering sensory experience through MD affects clustering of inhibitory synapse and dendritic spine changes. We found that clustering between dynamic inhibitory synapses and dendritic spines persisted during MD (Figure S5C) with a similar spatial distribution compared to control conditions (Figure S5D). We compared the frequency of clustered events during normal vision and MD by quantifying the number of inhibitory synapses and dendritic spine changes occurring within 10 μm of each other. MD increased the

frequency of clustered events from 0.013 ± 0.004 Non-specific serine/threonine protein kinase to 0.020 ± 0.003 per μm dendrite (Wilcoxon rank-sum test, p < 0.05; Figure 5H). Since MD increases inhibitory synapse but not dendritic spine dynamics, we asked how an increase in clustered events could occur without a concurrent change in dendritic spine remodeling. We found that whereas the fraction of dynamic spines did not increase in response to MD (Figures 4B–4D), the fraction of dynamic spines participating in clustered events increased from 38.4% ± 9.0% to 59.0% ± 7.7% during MD (Wilcoxon rank-sum test, p < 0.05). A small fraction of spines in the SSEM were unaccounted for in the imaging. In all cases, these were z-projecting dendritic spines, obscured by the eYFP-labeled dendrite above or below. Generally, we find little or no image rotation along the x or y axis from session to session.

For these experiments, 4-week-old mouse brains were homogenized under conditions that aim to preserve native interactions and separated into various soluble (S) and pellet (P) fractions (see Experimental Procedures for further details). If the entire synapsin and CamKII population was completely soluble in nonsynaptic S2 fractions, one would expect that these proteins would exclusively migrate in the supernatant (S100) fractions. In line with that, we found that the small signaling molecule RhoGDI, selleck compound previously used as a soluble marker in neurons (Kimura et al., 2005), is predominantly enriched in the S100

fractions (Figure 5A, bottom). Though the axonal transport of signaling molecules has not been rigorously evaluated by radiolabeling, it is generally believed that their intracellular motion is largely diffusive (Brangwynne et al., 2008, Lillemeier et al., 2001 and Zeng et al., 2001). However, we found significant amounts of both synapsin and CamKII in the P100 pellet fractions (Figure 5A, bottom, see fractions within red box), indicating that fractions

of these proteins in vivo exist in a state that is not entirely soluble. As vesicles are also present in the P100 fractions, we next asked if synapsin and CamKII are associated with vesicles in these fractions. To determine this we subjected the pellet fractions to sucrose-gradient floatation assays and probed them for synapsin and CamKII, as well as classic transmembrane proteins APP and synaptophysin and a peripherally associated membrane www.selleckchem.com/products/incb28060.html protein (GAP43), all of which are conveyed in fast axonal transport. We found that while all vesicular proteins floated in lighter fractions (as expected), significant quantities of both synapsin and CamKII were present in the high-density fractions that were largely distinct

(but partially overlapping) from the transmembrane proteins (Figure 5B, top). Also, while detergent treatments disrupted the vesicular proteins, they had little effect on the higher density fractions of the two cytosolic proteins (Figure 5B, bottom and Figure S6A). The separation of membranous and cytosolic proteins Metalloexopeptidase was also observed in density gradients from axon-enriched corpus callosum preparations from mouse brains (Figure 5C). In contrast, within the synaptosomal (P2) preparations, both synapsin and CamKII were largely (though not exclusively) associated with lighter fractions (Figure S6B) and this association was disrupted by detergent treatment (Figure S6C), suggesting that in synaptic domains these proteins are largely associated with synaptic vesicles (as expected). The presence of synapsin and CamK in higher density fractions within high-speed P100 pellets and their resistance to detergents further suggest that synapsin and CamK in these fractions are organized into proteinaceous complexes.

The predominance find more of cells concerned with slow movement time scales is in line with an earlier recording study, which also showed that cells did not covary 1:1 with the whisking rhythm and that cells would globally turn off and on with whisking (Carvell et al., 1996). Hill et al. (2011) also show that motor cortical neurons accurately predict whisker movements. Most interestingly,

this covariation of motor cortical activity and whisker movements persist after removal of sensory feedback, implying that it reflects efferent control rather than afferent modulation. This finding differs from data in somatosensory cortex, where the removal of sensory feedback disrupts the comodulation of activity and whisking (Fee et al., 1997). This result is of great significance, because it presents one of the clearest dissociations of vibrissae motor and somatosensory cortical activity in sensorimotor integration discovered so far. The modulation of neural activity associated SB203580 chemical structure with whisking is fairly weak. Overall there is only a temporal redistribution of neural activity during whisking and no net firing rate increase during whisking! Does such weak modulation argue against a motor role of these neurons? Almost certainly not. In most mammalian motor cortices the activity during spontaneous behaviors is rather modest. The situation changes

when tasks become complicated or when animals are trained on certain movements. One might guess that for most of the day motor cortex is not in the driver’s seat, and instead acts like a mastermind of complicated, unusual, or very significant movements. As for the lesions to the motor cortical forelimb representation performed by Fritsch and Hitzig, damage to vibrissa motor cortex does not fully abolish whisker movements. The persistence of whisking after cortical ablation suggested early on the existence of a brain stem pattern generator for whisking. Lesions to vibrissa motor cortex do affect the amplitude distribution of whisker movements, a result much in line with the current results from Hill et al. (2011). The characteristics

of stimulation-evoked not movements in vibrissa motor cortex strongly depend on methodology of stimulation and the identity of the stimulated neurons (Brecht et al., 2006). Stimulation of pyramidal neurons and interneurons evokes movements of opposite directions. While movements evoked by brief trains of extracellular stimulation pulses are brief and restricted to few whiskers, movement fields observed with single-cell stimulation are large and single-cell-evoked movements persist for seconds (Brecht et al., 2004b). Single-cell stimulation effects are in line with the conclusion of Hill et al. (2011) that vibrissa motor cortex controls movements on long timescales. Vibrissa motor cortex distributes output to a wide variety of subcortical targets. Inputs to vibrissa motor cortex arrive from a wide variety of brain regions in an intricate extremely orderly laminar pattern.