On the last day of physiology, BDA injections were made along the recording paths to estimate recording sites. We measured average firing rates, Z scores, precision,

and selectivity from the responses of individual neurons. Z scores were measured as (driven firing rate − baseline firing rate)/(SD of baseline firing rate). We quantified trial-to-trial precision by first computing the shuffled autocorrelogram using the spiking responses to individual songs ( Joris et al., 2006). The shuffled autocorrelogram quantifies the propensity of neurons to fire spikes across multiple presentations of the same stimulus at varying lags. The correlation index is the shuffled autocorrelogram value at a lag of 0 ms, and it indicates SRT1720 clinical trial the propensity to fire spikes at the same time (±0.5 ms) each time the stimulus is presented. To quantify selectivity, we first determined the number of songs that drove at least one significant spiking event. Significant spiking events were defined by two criteria: (1) the smoothed PSTH (binned at 1 ms and smoothed with a 20 ms Hanning window) had to exceed baseline activity (p < 0.05), and (2) during this duration, spiking activity had to occur on >50% of trials. Selectivity was then quantified as 1 − (n/15), where n was the number of songs (out of 15) that drove at least one significant spiking event. To quantify population sparseness, we computed the fraction of neurons that produced significant

spiking events during every 63 ms epoch, using a sliding window. We then quantified the fraction of neurons active during each window, with low values indicating PAK6 higher levels of sparseness. To create population PSTHs, we first computed Microbiology inhibitor the PSTH of each individual

neuron within a population in response to a single song, smoothed with a 5 ms Hanning window. We then averaged the PSTHs of every neuron in a population, without normalizing. To quantify the degree to which neural responses to auditory scenes reflected the individual song within the scene, we computed an extraction index using the PSTHs to a scene at a particular SNR, as well as the PSTHs to the song and chorus components of that scene. From these PSTHs we computed two correlation coefficients: Rsong was the correlation between the song and scene PSTHs and Rchor was the correlation coefficient between the scene and the chorus PSTHs. The extraction index was defined as (Rsong − Rchor)/(Rsong + Rchor). Other methods for quantifying the extraction index from the PSTHs or from single spike trains produced qualitatively and quantitatively similar results. STRFs were calculated from the spiking responses to individual vocalization and the corresponding spectrograms using a generalized linear model, as previously described (Calabrese et al., 2011). We validated the predictive quality of each STRF by predicting the response to a song not used during estimation. We then calculated the correlation coefficient between the predicted and actual PSTHs.

The presynaptic protein synaptophysin is not affected by NLG1 cleavage, indicating that shedding of NLG1 is not accompanied by gross structural changes in presynaptic terminals (Figures 5D and 5F). Considering the expanding set of transsynaptic NRX binding partners, these results suggest that postsynaptic NLG1 is an important regulator of NRX1β stability at synapses. Previous studies have shown that deletion of αNRXs in mice reduces action-potential-evoked

VX-770 mw neurotransmitter release due to impaired presynaptic Ca2+ channel function (Missler et al., 2003). However, due to the role of NRXs in synapse maturation, it has been unclear whether this effect is due to indirect developmental effects or reflects an ongoing role of NRXs in neurotransmitter release. Using the highly selective thrombin-induced XAV-939 in vivo cleavage of NLG1, we show an overall reduction in excitatory transmission and release probability concurrent with NRX1β

loss (Figure 6). These findings support the notion that the NLG-NRX complex is a critical regulator of neurotransmitter release (Futai et al., 2007; Missler et al., 2003; Zhang et al., 2005) and provide evidence that NLG1-dependent regulation of presynaptic function can occur over time scales of minutes. In mature hippocampal and cortical cultures, postsynaptic receptor blockade increases mEPSC frequency (Burrone et al., 2002; Thiagarajan et al., 2005; Wierenga et al., 2006) and augments presynaptic terminal size and release probability (Murthy et al., 2001; Thiagarajan et al., 2005). By contrast, local stimulation of dendrites acutely reduces release probability of contacting presynaptic terminals (Branco et al., 2008). These data have implied the existence of local transsynaptic negative feedback signals capable of modifying presynaptic function based on postsynaptic activity. Our next results indicate

that NLG1 cleavage is bidirectionally regulated by activity (Figures 3A and 3B). Moreover, acute NLG1 cleavage decreases release probability, whereas expression of a cleavage-resistant NLG1 isoform induces the opposite effect (Figure 6). Together, these data support a model where increased or decreased local NLG1 cleavage alternately dampens or augments presynaptic function based on postsynaptic activity, thereby contributing to overall levels of neuronal excitability. The developmental profile of NLG1-NTFs in the brain (Figures 2G and 2H) indicates that NLG1 cleavage is upregulated during early stages of development, a time when activity-dependent mechanisms sculpt new circuits (Hensch, 2004). Moreover, our results indicate that MMP9-dependent cleavage of NLG1 is regulated by sensory experience during visual cortex maturation (Figures 7E and 7F). Interestingly, tissue plasminogen activator, a robust activator of MMP9 (Wang et al., 2003), regulates synapse maintenance during cortical development (Mataga et al.

For example, improving bone density, cardio-pulmonary outcomes, physical functioning, psychological symptoms, quality of life, and immune system functioning.22 Tai Ji Quan interventions have been shown to reduce falls in randomized controlled trials (RCTs) in Australia25 and the US.26 and 27 Although most interventions used programs modified for older adults and taught one style of Tai Ji Quan, one RCT that demonstrated effectiveness used existing community Tai Ji

Quan programs and local Tai Ji Quan instructors who taught a variety of styles.25 In a comprehensive review of the JQ1 price health benefits of Tai Ji Quan, Jahnke et al.22 found that Tai Ji Quan improved balance VE-822 chemical structure and postural stability and reduced the risk and rate of falls among community-dwelling older adults. A more recent meta-analysis by Gillespie et al.18 reported that Tai Ji Quan programs reduced fall risk by 28%. However, not all studies have found that Tai Ji Quan was effective in reducing falls.28, 29 and 30 A meta-analysis of exercise-based falls interventions indicated that, to be effective, exercise must: 1) focus on improving balance, 2) become progressively more challenging,

and 3) involve at least 50 h of practice.31 For some ineffective Tai Ji Quan interventions, participants may not have obtained a sufficient “dose”. Participants may have attended classes infrequently or the program may not have continued long enough to demonstrate effectiveness. Additionally,

there is growing Thymidine kinase evidence that the effectiveness of Tai Ji Quan as a falls intervention depends, at least in part, on the health status of participants. A recent Cochrane review concluded that Tai Ji Quan classes reduced the risk of falling but were less effective in trials with high-risk participants.18 Tai Ji Quan appears to be most beneficial for healthy, and possibly transitionally frail, older adults, but less suitable for older frail individuals.32, 33 and 34 A number of public health organizations have recognized that Tai Ji Quan programs are an effective fall prevention approach. The World Health Organization recommends community-based programs that link Tai Ji Quan-based exercises with an educational component.35 The CDC has published the CDC Compendium of Effective Fall Interventions that includes 10 exercise-based interventions; 36 three of these are Tai Ji Quan programs. Additionally, the US Administration for Community Living includes Tai Ji Quan programs among those that, for funding purposes, meet their criteria for evidence-based falls interventions. 37 After an intervention has demonstrated effectiveness in an RCT, the next step is to translate the intervention into practice.

In an interesting additional approach, they use the recently developed TRAP technique (Heiman et al., 2008) to show that lamin B2 mRNA is associated with ribosomes in RGC axons in vivo. In this method, animals are generated expressing GFP-tagged ribosomes, then the ribosomes are immunoprecipitated

using anti-GFP antibodies, and associated RNAs are identified. Here, the authors created Xenopus tadpoles in which GFP-tagged ribosomes were only expressed in a transplanted eye. These RGC axons innervated the host tectum, ensuring that tectal lysates would contain GFP-tagged ribosomes originating exclusively from RGC axons. Anti-GFP immunoprecipitation demonstrated the association of lamin B2 mRNA with ribosomes in Ulixertinib ic50 retinal axons, providing evidence that lamin B2 is locally translated in these axons in vivo. Having demonstrated that lamin B2 is produced in RGC axons, Yoon et al. then examined its function there in vivo. First, they knocked down lamin B2 in the eye by antisense morpholino and found that RGC axons degenerated after they reached the tectum, while their cell bodies survived. This shows that lamin B2 is essential for RGC axon maintenance in vivo. They then asked whether its role in axon maintenance relied on its presence in the axon rather than in the nucleus. Consistent with this hypothesis, the lamin B2 knockdown phenotype

could be rescued by overexpressing a mutant form of lamin B2 that cannot enter the nucleus. Moreover, knockdown of lamin B2 by applying morpholino Rebamipide Selleck Anti-diabetic Compound Library specifically to the tectum, presumably affecting RGC axons but not their cell bodies, led to axon degeneration without altering lamin B2 levels in the soma. These results indicate that lamin B2 functions in the

axon to promote axon survival independently from its role in the nucleus. By what mechanism, then, might lamin B2 play a role in axon survival? A first indication of its function in axons came from its localization: in axons, lamin B2 immunolabeling was found to coincide well with mitochondria. Furthermore, lamin B2 knockdown led to elongated mitochondrial morphology and reduced the mitochondrial potential necessary to drive ATP synthesis. This was also accompanied by reduced bidirectional movement of vesicles in the axon, a process heavily dependent on the ATP produced by mitochondria. These data show that lamin B2 promotes mitochondrial function, providing a plausible explanation for its effects on axon survival. Taken together, these results clearly show that lamin B2 is synthesized within the axon, and provide impressive evidence that this local synthesis is required for maintenance of RGC axons in vivo within the tectum. Regarding the precise developmental roles of this mechanism, these interesting results suggest more than one potential model.

SHH activates GLI3 (and GLI2) by inducing its proteolytic conversion from a full-length transcriptional activator into a truncated N-terminal repressor ( Ruppert et al., 1990, Dai et al., 1999 and Wang et al., 2000). It is believed that PKA phosphorylation stimulates GLI3 cleavage ( Wang et al., 2000 and Tempe et al., 2006), which might underlie

the repressive action of PKA on SHH signaling since truncated GLI3 represses the SHH pathway ( Dai et al., 1999, Wang et al., 2000, Bai et al., 2004 and Tempe et al., 2006). GLI3 is not the only component of the SHH pathway that can be PKA phosphorylated, and PKA has been shown to Protein Tyrosine Kinase inhibitor play a positive as well as a negative role in SHH signaling. For example, in Drosophila, PKA phosphorylation of SMO, the Hedgehog (HH) coreceptor, promotes SMO accumulation on the primary cilium and triggers HH pathway Ku 0059436 activation ( Jia et al., 2004). Also, during limb development, elevating PKA activity by Forskolin treatment or by infecting with a retroviral PKA expression vector exerts a positive effect on SHH signaling, resulting in an altered pattern of digits ( Tiecke et al., 2007). We examined the effect of stimulating the PKA pathway in neonatal mouse cortical cell cultures

with Forskolin and dibutyryl cyclic AMP (db-cAMP), a cell-permeable analog of cAMP, and found that the number of NG2-positive OLPs was significantly decreased compared to untreated cultures (Figure S7). This is consistent with expectation since our other data predict that elevating PKA activity should increase OLIG2-S147 phosphorylation and stimulate neurogenesis at the expense of OLPs. However, in the light of the above discussion, it is clear that PKA probably has multiple parallel functions, and our experiments with Forskolin/db-cAMP should be interpreted cautiously. Our data raise the obvious question: What is the key event that signals S147 dephosphorylation and triggers the MN-OLP switch in pMN? Notch signaling is known to play an important role in glial cell development in the CNS (Wang et al., 1998, Park and Appel, 2003, Park et al., 2005 and Deneen et al., 2006). over Constitutive activation

of components of the Notch pathway in chick spinal cord can downregulate NGN2 expression in pMN and initiate OLP generation (Zhou et al., 2001). Notch1 is expressed by neuroepithelial cells throughout the neural tube, and its ligand Jagged-2 is expressed exclusively in the pMN domain of zebrafish spinal cord during late neurogenesis (Yeo and Chitnis, 2007). These and other observations frame the Notch pathway as a potential key player in the MN-OLP switch. It is possible that activated Notch-1, via its effector HES5, might induce expression of specific phosphatases and/or repress phosphatase inhibitors, resulting in dephosphorylation of OLIG2-S147 and initiation of OLP production. It will be worth exploring these ideas in the future.

Layer II contains the somata of superficial pyramidal cells, with apical

dendrites extending into Layer I and basal dendrites into Layer III. Layer IIa, a thin, superficial component of Layer II contains the somata of the pyramidal cell-like semilunar cells. These cells lack basal dendrites and appear to preferentially receive input from mitral/tufted cells, with relatively less input from association fibers (Suzuki and Bekkers, 2011). Unlike other pyramidal cells, they do not project back to the olfactory bulb. Layer III contains the somata of deep pyramidal cells, as well as a variety of interneurons. At least five classes of piriform cortical GABAergic interneurons have been identified (Suzuki and Bekkers, 2010a and Young and Sun, 2009). Deep to layer III lies the endopiriform nucleus. Whether the endopiriform nucleus should be considered piriform cortical DNA Damage inhibitor layer IV is unclear, though the two structures are highly interconnected. Protein Tyrosine Kinase inhibitor The endopiriform nucleus contains dense local and extended excitatory interconnections with relatively low levels of GABAergic interneurons (Behan and Haberly, 1999 and Ekstrand et al., 2001). This combination of autoexcitation and low

inhibition makes the endopiriform highly susceptible to seizure development (Behan and Haberly, 1999). It sends strong, dispersed output throughout the piriform cortex and other perirhinal structures. These characteristics have led to the hypothesis (Behan and Haberly, 1999) that the endopiriform nucleus may be involved in generating sharp-waves in olfactory cortex similar to those described in the hippocampal formation (Buzsáki, 1986) and that these sharp-waves may contribute to plasticity and odor memory. In fact as described below, sharp-waves have recently been described in piriform cortex (Manabe et al., 2011). Understanding the role of olfactory cortex in odor perception has been the focus of a variety of theoretical and computational models (Ambros-Ingerson et al., 1990,

Granger and Lynch, much 1991, Haberly, 1985, Haberly, 2001, Haberly and Bower, 1989, Hasselmo et al., 1990 and Linster et al., 2009). An underlying theme of many of these is olfactory cortex as autoassociative combinatorial array, capable of content addressable memory. Here, we use this model as an organizing framework to describe recent advances in understand olfactory cortical structure and function. The basic model describes the olfactory cortex in terms of a combinatorial, autoassociative array capable of content addressable memory (Haberly, 2001). Put simply, the model proposes that unique combinations of odorant features, encoded in the spatiotemporal pattern of olfactory bub glomerular output, can be synthesized, stored and recalled in the activity of distributed ensembles of olfactory cortical pyramidal cells (Figure 2).

In PBS-treated control neurons, α-syn colocalized with VAMP2

at the presynaptic terminal. PLX3397 solubility dmso Addition of α-syn-hWT pffs led to a depletion of α-syn from the presynaptic terminal such that it showed minimal colocalization with presynaptic VAMP2 (Figure 7A). To further investigate the molecular consequences of recruitment of endogenous α-syn into insoluble aggregates, we examined additional synaptic proteins that could be impacted by the pathological sequestration of α-syn into aggregates and away from the presynaptic terminal. Although β-synuclein (β-syn), another member of the same family of neuronal proteins as α-syn, but lacking the NAC domain, colocalized with α-syn at presynaptic terminals in MEK inhibitor control neurons (Murphy et al., 2000), α-syn-hWT pff addition did not change the presynaptic localization of β-syn (Figure S3). Furthermore, Tx-100 extraction showed that, unlike pathological α-syn, which localized to detergent insoluble

aggregates, β-syn remained soluble (Figure S3). Immunoblot analyses showed that endogenous β-syn was Tx-100 soluble 14 days after adding α-syn pffs (Figure 7B) and protein levels in pff-treated neurons were not statistically significantly different from PBS-treated neurons. Thus, like LBs in PD brains, the aggregates that developed in primary neurons are composed of insoluble α-syn, but not β-syn (Spillantini et al., 1998). Importantly, this is consistent with the selective recruitment of α-syn by pffs as opposed to the indiscriminate disruption of adjacent presynaptic components. Nonetheless, we were able to detect statistically significant reductions in a subpopulation of synaptic proteins two weeks after the addition of α-syn-hWT pffs, including the synaptic vesicle-associated SNARE proteins, Snap25 and

VAMP2, as well as Thalidomide soluble proteins that participate in SNARE complex assembly or the exo-endocytic synaptic vesicle cycle such as CSPα, and synapsin II (Figure 7B). Levels of other synaptic proteins showed slight, but not statistically significant reductions. Changes were not observed in GAPDH, the plasma membrane-associated SNARE protein, syntaxin 1, or the transmembrane synaptic protein synaptophysin. Since loss of synaptic proteins may correlate with neurodegeneration, we asked whether the accumulation of α-syn aggregates leads to neuron loss. NeuN-positive neurons were counted in cultures treated with PBS or α-syn-hWT pffs 4, 7, or 14 days after α-syn pff addition. While there was a slight but not statistically significant decrease in number of neurons 7 days after α-syn-hWT pff treatment, by 14 days after pff treatment, there was a significant 40% decrease in neurons relative to PBS controls (Figure 6C). Cell death did not occur in α-syn-hWT pff-treated neurons derived from α-syn −/− mice, demonstrating that intracellular aggregates, rather than the mere addition of exogenous pffs, caused neuron death.

Colocalization between nectin1 and nectin3 was observed at multiple locations within the cell bodies and distal

processes of CR cells (Figure S3C). Together, these data demonstrate that nectin1 and nectin3 are appropriately localized to mediate interactions between CR cells and migrating neurons. Because nectin3 preferentially forms heterotypic adhesions with nectin1 (Satoh-Horikawa et al., 2000), we next determined whether nectin1 expression in CR cells is required for the radial migration of nectin3-expressing neurons. For this purpose, we took advantage of our double-electroporation strategy (Figure 5A). We first electroporated hem-derived CR cells at E11.5 with a DN-nectin1 BKM120 solubility dmso construct that lacks the afadin binding site (Brakeman et al.,

2009 and Takahashi et al., 1999). The same embryos were re-electroporated at E13.5 with a Dcx-mCherry expression vector to label migrating neurons and then analyzed at E17.5. CR cells expressing DN-nectin1 still migrated along their normal route within the cortical MZ (Figures S4A–S4D). Quantitative evaluation confirmed that ∼50% of all reelin+ CR cells expressed DN-nectin1, even in the lateral cortex at a substantial selleck inhibitor distance from the cortical hem (Figures 5C and 5D). These findings show that our electroporation method targets half of all CR cells and that DN-nectin1 does not significantly affect their tangential migration. However, the positions of radially migrating neurons were strikingly

altered after nectin1 perturbation in CR cells. Neurons in controls had migrated into the upper part of the CP, whereas large numbers of neurons remained in the lower part of the CP following expression of DN-nectin1 in CR cells (Figures 5E and 5F). Neurons in controls had normal bipolar morphologies with leading processes that branched in the MZ, whereas branch density was drastically decreased following expression of DN-nectin1 however in CR cells (Figures 5G and 5H). Similar defects in migration and leading-process arborization were found when nectin1 function in CR cells was perturbed using shRNAs (Figures S4E–S4I). Finally, nectin1 perturbation in CR cells did not produce obvious changes in the morphologies of RGC processes or the localization of RGC endfeet (Figure S4J). We conclude that perturbation of nectin1 function in CR cells affects interactions between neuronal leading processes and CR cells, thereby nonautonomously perturbing somal translocation of radially migrating neurons into the CP. We have previously shown that Cdh2 in neurons is required for glia-independent somal translocation (Franco et al., 2011); we now show that nectin3 and afadin in neurons are also required for this process. In epithelial cells, nectins form nascent cell-cell adhesion sites, to which afadin is recruited by binding to the cytoplasmic tails of nectins.

In addition to confirming the functionality of tAGO2, it is essential

Apoptosis Compound Library order to reliably and systematically deliver tAGO2 to different cell types at consistent levels. We achieved this using the Cre/loxp binary expression system (Figure 1B). We generated a knockin allele at the Gt(ROSA)26Sor (Rosa26) locus which expresses tAGO2 upon Cre/loxp recombination (R26-LSL-tAGO2). Combined with an increasing inventory of cell type-restricted Cre driver lines ( Taniguchi et al., 2011) this strategy would allow systematic analysis of miRNA expression in different cell types in mice. To test the functionality of the LSL-tAgo2 allele, we first crossed the reporter mouse to a CMV-Cre line to activate tAgo2 expression in the germline. Offspring

of CMV-Cre;LSL-tAgo2 were identified in which tAgo2 is ubiquitously expressed in all cells of the animal (the tAgo2 mouse) (see Figure S1 available online). Using antibody against AGO2, a 100 kD endogenous band was detected in whole-brain homogenates from both the tAgo2 and LSL-tAgo2 mouse, while the higher molecular weight tAGO2 band is only detected in tAgo2 sample ( Figure 1C). This result demonstrates buy NVP-AUY922 the tight Cre-dependent activation of tAgo2 expression from the LSL-STOP cassette. Using antibody to AGO2, GFP, or MYC, tAGO2 can be efficiently immunoprecipitated (IP) from tAgo2 brain lysate ( Figure 1C). To examine the identity of coprecipitated RNAs, they were extracted from IP product, radio-labeled and visualized by denaturing urea-PAGE. Enrichment of RNAs corresponding to miRNAs (e.g., 20–23 nucleotides) was observed using AGO2, MYC or GFP antibody-conjugated Dynabeads, but not with IgG control ( Figure 1D). In addition, miRNA Taqman PCR detected miRNAs that are known to be brain specific in these RNA extracts (e.g., miR-124) at much higher levels than others that are known to be absent (e.g., miR-122, data not shown). We used the LSL-tAgo2 strategy to profile miRNA expression in

glutamatergic, GABAergic, and subclasses of GABAergic neurons in P56 MYO10 mouse neocortex and cerebellum. Cortical excitatory pyramidal neurons and inhibitory interneurons differ in their embryonic origin, neurotransmitters, and physiological function ( Sugino et al., 2006). GABAergic interneurons further consist of multiple subtypes characterized by distinct connectivity, physiological properties, and gene expression patterns ( Markram et al., 2004 and Ascoli et al., 2008). In particular, the Ca2+-binding protein parvalbumin (PV) and neuropeptide somatostatin (SST) mark two major nonoverlapping subtypes ( Gonchar et al., 2007, Xu et al., 2010b and Rudy et al., 2011). Whereas the PV interneurons innervate the soma and proximal dendrites and control the output and synchrony of pyramidal neurons, the SST interneurons innervate the more distal dendrites and control the input and plasticity of pyramidal neurons ( Somogyi et al., 1998 and Di Cristo et al., 2004).

We have exploited the predominant expression of Channelrhodopsin-2 in layer 5B pyramidal neurons of Thy-1

transgenic mice ( Arenkiel et al., 2007, Wang et al., 2007, Yu et al., 2008 and Ayling et al., 2009) to target this class of corticofugal cells directly, exposing their contribution to motor cortex topography and identifying a functional subdivision of the mouse forelimb representation based on movement direction. Prolonged trains of light or electrical stimulation revealed that activation of these subregions drives movements to distinct positions in space. To identify mechanisms that could account for the different movement types evoked by stimulation of these cortical subregions, we performed pharmacological manipulations of the intracortical circuitry and targeted anatomical C59 wnt price tracing experiments. We used optogenetic motor mapping to rapidly stimulate hundreds ON-01910 solubility dmso of cortical points in ChR2 transgenic mice (Arenkiel et al., 2007) and assemble maps based on evoked movements of the contralateral forelimb and hindlimb (Figures 1A–1C, see Ayling et al., 2009 for methodological details). In these experiments, anesthetized mice were head-fixed in the prone position with their contralateral limbs suspended. In this posture, the limbs were able to

move freely along the axis of measurement of a laser range finder. The resultant movement maps were centered at positions consistent with those obtained by EMG recording or visual observation (forelimb: 2.2 ± 0.1 mm lateral,

0.05 ± 0.09 mm anterior of bregma; hindlimb: 2.0 ± 0.11 mm lateral, 0.21 ± 0.1 mm posterior of bregma, n = 14 mice, all values ± SEM) (Pronichev and Lenkov, 1998, Ayling et al., 2009, Hira et al., 2009 and Tennant et al., 2011). Composite maps based on the average of three repetitions were highly reproducible, with a shift in center position of 0.19 ± 0.02 mm (n = 12 mice) between mapping trials those (∼30 min per composite map). In a separate group of animals implanted with cranial windows, maps remained stable for months (Figure S1 available online). Movement maps could also be generated in animals where ChR2 was expressed in pyramidal neurons of both superficial and deep cortical layers by transduction with adeno-associated virus (Figure S2). Consistent with previous results, forelimb movements could be elicited by stimulation (10 ms pulses, 0.5–10 mW or 63–1270 mW/mm2) of a broad cortical area, up to 2 mm anterior and posterior of bregma (Ayling et al., 2009 and Tennant et al., 2011). However, when forelimb movements were examined at stimulation sites across the motor cortex, a diversity of response types became apparent (Figures 1C–1F). Evoked movements were divided into two classes depending on the direction of forelimb movement (abduction or adduction, Figures 1D–1F).