Varying levels of DA D1R stimulation would correspondingly weaken

nonpreferred connections, sharpening tuning under conditions of salient events (e.g., a rewarding stimulus or pressure from a deadline). The sculpting of network inputs may be optimal for performance of a spatial working memory task in which one is trying to maintain the representation of a small location in space but may be harmful when cognitive demands require more flexible network connections (Arnsten et al., 2009). This may explain why D1R stimulation is needed for spatial working memory but actually impairs attentional set-shifting (Robbins and Arnsten, 2009), even though both functions depend on dlPFC. Thus, the optimal neuromodulatory environment depends on the cognitive demands: insightful solutions to problems or creative endeavors that require LDN193189 wide network connections would be optimal under relaxed, alert conditions with less D1R sculpting (e.g., in the shower),

while more focused work may be best performed under the conditions that increase DA release (e.g., the pressure of working for a reward) (Arnsten et al., 2009). This may also Venetoclax explain why stimulant medications can be helpful for some schoolwork (e.g., math) but harmful to others (e.g., composing a poem or song). The right side of the inverted U in Figure 6A shows the progressive weakening of network connections and progressive decrease in dlPFC firing with increasing stress (Arnsten, 1998, 2009). Evidence of this phenomenon has been seen in human imaging studies, where a GABA Receptor mild uncontrollable stressor (watching a gory movie) impairs working memory and reduces the BOLD signal over the dlPFC, while disinhibiting activity in the amygdala and default mode network (Qin et al., 2009), consistent with loss of dlPFC regulation and strengthening

of more primitive circuits. Data from animals indicate that that the same neurochemical pathways that take PFC off-line (D1R-cAMP and β1-AR-cAMP, α1-AR-Ca+2-PKC) serve to strengthen subcortical and sensory/motor circuits, switching the brain from a reflective to reflexive mode (Arnsten, 2009). The feed-forward nature of these signaling pathways would promote a very rapid switch to primitive circuits, that is, “Going to Hell in a Handbasket” (Arnsten, 2009). Thus, regulatory interactors, such as DISC1-PDE4A, would serve a critical role to reign in feed-forward Ca+2-cAMPsignaling and restore dlPFC top-down regulation of thought and behavior. Loss of this regulation and/or chronic stress exposure leads to architectural changes in PFC pyramidal cells, with loss of spines and retraction of dendrites (Cook and Wellman, 2004; Liston et al., 2006; Radley et al., 2008). The molecular basis for stress-induced atrophy has just begun to be studied.

As such, this adaptive change is not likely sufficient to cause addiction but rather represents a building block of the adaptations that underlie addictive behavior with repetitive exposure. Studying the effect of a single injection of drug enabled us to systematically probe the mechanism underlying the plasticity of the slow IPSC. We discovered the methamphetamine-induced loss of the slow IPSC arises from a reduction in the GABABR-GIRK currents, due to changes in protein trafficking, and is accompanied by a significant decrease in the sensitivity of presynaptic GABAB receptors in GABA neurons of the VTA. In contrast, GABA neurons of the hippocampus and prelimbic cortex did not show similar

changes in GABAB-GIRK signaling, suggesting the GABABRs in the VTA are uniquely targeted by psychostimulants. Bcl-2 inhibitor The psychostimulant-evoked reduction of GABAB-GIRK currents in VTA GABA neurons could arise from a change in G protein coupling (Nestler et al., 1990 and Labouèbe et al., 2007) or internalization of the receptor-channel (González-Maeso et al., 2003, Fairfax et al., 2004, Guetg

et al., 2010, Maier et al., 2010 and Terunuma et al., 2010). In support of the latter possibility, quantitative immunogold electron microscopy revealed a significant reduction in surface expression of GABAB receptors and GIRK channels in GABA neurons of METH-injected mice, coincident with a decrease in phosphorylation of GABABRs. In cortical and hippocampal neurons, a balance of AMP-activated protein kinase (AMPK)-dependent phosphorylation of GABAB2-S783 and PP2A-dependent either dephosphorylation governs buy Forskolin postendocytic sorting of GABAB receptors (Terunuma et al., 2010). The persistence of the GABAB-GIRK depression and the rapid recovery with phosphatase inhibitors suggest the balance of surface and internalized GABAB receptors in GABA neurons might be controlled by a molecular switch in a phosphatase, perhaps akin to the autophosphorylation switch in CaMKII (Lucchesi et al., 2011) or through an endogenous

regulator of protein phosphatase activity (Guo et al., 1993). It remains possible that other kinases are also involved; both PKA- and CaMKII-dependent phosphorylation have been implicated in stabilization of GABAB1 on the plasma membrane (Couve et al., 2002 and Guetg et al., 2010). Interestingly, total protein levels of GABAB2 receptors were not significantly changed in METH-injected mice, suggesting that the internalized pool of receptors was not redirected to a degradation pathway, in contrast to activity-dependent degradation of GABAB receptors observed in cortex (Terunuma et al., 2010). If phosphorylation controls surface expression of GABAB receptors, then what controls the surface expression of GIRK channels? CaMKII-dependent phosphorylation of GIRK2 has been implicated in stabilizing GIRK2 channels on the plasma membrane of hippocampal neurons (Chung et al., 2009).

Our study aimed at cognitively phenotyping the GFAP- APOE3 and APOE4 mice using two different tests including Enzalutamide in vivo spatial and non-spatial tasks. While APOE4 have been associated with accelerated cognitive declines 6, 7 and 56 and neurodegenerative diseases, 24, 57 and 58 reports regarding cognitive outcomes in young APOE4 population have remained inconclusive. In humans, APOE4 has been associated with better performance in young individuals which then shifts

to a negative outcome in older individuals. 20, 21 and 22 This antagonistic pleiotropy has not been well studied and has remained elusive. Studies in animal models have led to conflicting results with some studies showing early signs of deleterious effects with APOE4, 16 and others showing improvements. 12, 19, 23 and 24 Some of the differences may be due to the mouse model chosen: targeted replacement model vs. hAPP-Yac/APOE-TR model, as well as the different behavioral

tests conducted. In our study we opted to use the GFAP-APOE mice, in which the expression of the human APOE isoforms is under glial promoter control. 56 Our findings suggested that APOE4 performed better on the discriminative component of the active avoidance but not on the avoidance component, which is more difficult to learn P-gp inhibitor and achieve. Furthermore, even though there was no main effect of Sex on any of the measures, it is noteworthy that on the MWM, female APOE4 in the SedCon group seemed to perform better than the APOE3 SedCon ones. Our data suggested that indeed APOE4 may confer some type of beneficial effect at a younger age. Our mice were about 5–6 months when tested for cognitive function, and it is possible that the APOE effect would have been larger if tested at

a younger age. Interestingly, in the current study, the APOE4 mice exhibited a behavioral profile that seemed to match the one of the wild-type mice on activity- and affective-related Smoothened tasks. The speed measured in the water maze task and the anxiety levels of the APOE4 mice were similar to the wild-type ones, while the APOE3 mice were less active in the water and seemed more anxious. Studies of older mice showed that E3 and E4 mice were more anxious than the wild-type. 56 Furthermore, while our study yielded a better performance on the MWM for the wild-type compared to APOE3 and E4 mice, other studies have indicated a lack of effect of genotype on this particular task. 56 While the methodology was different, it is noteworthy that E3 and E4 mice did not differ in their performance in both studies. Interestingly, both studies showed differences in working memory with Hartman et al. 56 showing impairments associated with APOE4 while our study yielded a better performance associated with E4 when compared to E3.

Thus, topographic information for axon-target interactions within the MNTB are preserved, even when axons form

synapses in the wrong hemisphere. However, functional maturation of the synaptic contacts was severely impaired. In wild-type animals, calyx of Held synapses acquire characteristic morphological and functional properties during the first 3 postnatal weeks. Each MNTB neuron is Palbociclib chemical structure innervated by a single calyx, and calyces exhibit extraordinarily fast transmitter release properties. In Robo3 conditional knockout mice, the ipsilaterally misplaced synapses were markedly underdeveloped by functional and morphological criteria. In 9- to 12-day-old animals, MNTB neurons were innervated by multiple smaller calyx-like terminals. Evoked transmission was severely reduced, and synapses showed immature forms of synaptic plasticity. In adolescent and adult animals, some of these defects were corrected, as multi-innervation receded and synapse size appeared normal. However, synaptic transmission remained strongly reduced, most likely due to a persistent decrease in the fast-releasable

pool of synaptic vesicles. A key question resulting from these findings is whether synapse development is indeed altered due to a failure of commissural neuron reprogramming after midline crossing or whether Robo3 has a postnatal Depsipeptide chemical structure function in synaptogenesis. Robo3 is strongly downregulated during late embryonic development and not detectable during the postnatal period when calyces develop (Michalski et al., 2013). Moreover, conditional ablation of Robo3 at the time

of birth did not alter synaptogenesis. Thus, the postnatal defects in synapse maturation are indeed a consequence of the Robo3 loss-of-function during embryonic development. The authors propose that axon midline crossing “conditions” synapse maturation. According to this model, midline crossing Plasmin would be a prerequisite for normal synapse development due to reprogramming of gene expression and/or protein trafficking in the commissural neurons. An additional interpretation would be that the inappropriate ipsilateral convergence of VCN-derived information with other neuronal activities causes the developmental changes. However, phenotypes emerge before hearing onset (postnatal day 12), and other synapses such as MNTB-LSO connections develop normally. This supports a rather selective defect in the misrouted VCN-MNTB connections. The key targets of the presumptive midline-dependent re-programming remain to be identified. However, several molecular signals that direct the growth and functional properties of calyx of Held synapses have emerged in recent studies. Thus, mouse mutants lacking the active zone proteins RIM1 and RIM2 exhibit a reduction in the fast-releasable pool of synaptic vesicles (Han et al., 2011).

For example, while the monkey performs a visual discrimination task, the noradrenergic neurons in the LC exhibit both phasic and tonic modes of firing, which are correlated with good and bad performance (Usher et al., 1999). Subsequent experiments showed that the phasic activity of LC neurons occurs specifically before the behavioral response, and it may serve to facilitate the task-related decision process (Clayton et al., 2004). In a study in the rat performing an odor-guided decision task, serotonergic neurons in the DRN showed transient firing precisely time locked to a variety of

task-related events (Ranade and Mainen, 2009). Another study in the monkey showed that firing rates this website of the DRN neurons were modulated by both the expected and received reward sizes (Nakamura et al., 2008). Neurons in the primate basal forebrain are also modulated by novel or reinforced stimuli (Wilson and Rolls, 1990). In behaving rats, the noncholinergic basal forebrain neurons showed strong burst responses to

both reward- and punishment-predicting stimuli, and the occurrence of the burst is strongly correlated with successful sensory detection (Lin and Nicolelis, 2008). The neuromodulator especially linked to vigilance and attention is ACh. In the rat, behaviorally relevant sensory cues can evoke transient increases in ACh concentration in the prefrontal cortex at the time scale of seconds (Parikh et al., 2007), and activating cholinergic transmission in the prefrontal cortex improves the performance of a sustained attention task (St Peters et al., 2011). ERK inhibitor mw A recent study based on genetic manipulation with recombinant viral vectors in the prefrontal cortex further demonstrated the importance of nicotinic ACh receptors (nAChRs) in sustained attention

(Guillem et al., 2011). Cholinergic signaling is also involved in selective attention. In the monkey performing a top-down spatial attention task, local application of ACh in the primary visual cortex was found to enhance the attentional modulation of neuronal firing rates, whereas mAChR pentoxifylline antagonist had the opposite effect (Herrero et al., 2008). Together, these studies indicate that in addition to the daily sleep-wake cycle, the subcortical neuromodulatory circuits also serve to regulate arousal and attention on a faster time scale. Numerous studies in monkeys performing selective attention tasks have shown increased neuronal responses (Reynolds and Chelazzi, 2004), which are thought to enhance the perceptual saliency of the attended stimuli. Recent studies have shown that attention also causes a decrease in stimulus-independent correlated firing between neurons (Cohen and Maunsell, 2009; Mitchell et al., 2009), which may improve sensory encoding at the ensemble level (Zohary et al., 1994).

897) during the shortening of the manuscript but would like to add it back to the manuscript: Direct coupling of PrPC to mGluR5 has been reported for an unrelated ligand, the laminin gamma-1 chain (Beraldo et al., 2010). Beraldo, F.H., Arantes, C.P., Santos, T.G., Machado, C.F., Roffe, M., Hajj, G.N., Lee, K.S., Magalhaes, A.C., Caetano, F.A., Mancini, G.L., Lopes, M.H., Americo, T.A., Magdesian, M.H., Ferguson, S.S., Linden, R., Prado, M.A., and Martins, V.R. (2011). Metabotropic glutamate receptors transduce signals for neurite outgrowth after binding of the prion

protein to laminin gamma1 chain. FASEB J. 25, 265–279. The manuscript PF 01367338 has been corrected online. “
“Important publications describing the effects of cytokines in the nervous system are demanding increasing amounts of our attention these days. Consider, for example, the chemotactic cytokines or chemokines. These small proteins have been extensively studied because of their importance in regulating leukocyte migration and inflammation. Approximately 50 different chemokines

have been shown to exist in higher vertebrates. These can be organized into four subfamilies based on structural considerations and, as far as we know, all their effects are transduced by a family of G protein coupled receptors (GPCRs). In most instances, chemokines are not expressed at high concentrations, their expression being upregulated in association with an innate immune or inflammatory response. MAPK inhibitor However, one chemokine does not fit this general description. Stromal cell-derived factor-1 (SDF-1, also called CXCL12) and its receptor CXCR4 C-X-C chemokine receptor type 7 (CXCR-7) are constitutively expressed at high levels in many tissues, including the nervous system (Li and Ransohoff 2008). Evolutionary considerations have indicated that CXCL12 is the most ancient chemokine and that it existed in animals prior to the development of a sophisticated immune system, suggesting that the original function of chemokine signaling had nothing to do with immunity (Huising et al., 2003). The ancient function of CXCL12/CXCR4

signaling appears to involve regulating the migration and development of the stem cells that generate nearly every tissue (Miller et al., 2008). Both CXCL12 and CXCR4 are highly expressed in the developing embryo, their distribution changing rapidly over time in association with the development of different structures. The overall importance of CXCR4 signaling during development has become abundantly clear from examination of CXCR4 knockout mice, which exhibit numerous phenotypes relating to the formation of nearly every tissue (Li and Ransohoff 2008). CXCR4 signaling regulates the development of many structures in the brain and peripheral nervous system, including parts of the cerebellum, cortex, and hippocampus and the dorsal root and sympathetic ganglia.

Indeed, viral tracing studies suggest that corticospinal projection neurons in these areas project mostly to spinal interneurons (Rathelot and Strick, 2009). Direct cortical projections to ventral horn neurons, and hence innervations of individual muscles, arise predominantly from more caudal aspects of primary motor cortex in the anterior bank of

the central sulcus. Thus, one may expect that the contribution of spinal circuits may be less pronounced when stimulating in the depth of the sulcus. The regularities in the stimulation-evoked muscle activation are likely influenced by the organization of motor cortex: both the pattern of divergent projections from motor

cortical neurons to subcortical targets and the strength of the lateral connections between different motorcortical circuits will heavily influence the evoked patterns. While somewhat marginal to the SB203580 research buy central selleck chemicals claims of the current paper, the location of these regularities becomes important when considering the plasticity of these circuits. Even short-term practice (20–30 min) can dramatically alter the movements that can be evoked by TMS stimulation of motor cortex (Classen et al., 1998). We would expect that such plasticity is a function of modulation of cortical activation states and lateral connections. On the other hand, there are also very long-lasting changes through experience. For example, life-long musical training alters the movement patterns evoked from M1 stimulation in a way that even reflects the specific instrument played (Gentner et al., 2010). One challenge for the future is to decipher the mechanisms of plasticity on short and long timescales that underlie these changes. It is relatively easy to see that Hebbian-type

learning (what fires together, wires together) would invariably reinforce the most often used combinations of neural activation patterns throughout the systems hierarchy, while weakening others. However, it is likely that multiple learning mechanisms at multiple sites interact in giving rise to both short- and long-term changes. The evidence provided by the authors—especially about the spatial distribution Oxaliplatin of evoked activity patterns—has the potential to shed new light on the functional relevance of this cortical organization. As stated by the authors, there is a strong intuition that synergies reflecting natural movement statistics make planning and control of movements “easier.” While we share this intuition, we also believe this argument deserves some further scrutiny. Specifically, the next challenge is to understand more precisely in what respect the structured organization of motor cortical outputs promotes the production of skilled movements.

Jane Fontenot, Dana Hasselschwert, and Marcus Louis for assistance with tissue collection. Thanks to Crissa Wolkey for sample processing and Rachel Dalley and Sheila Shapouri for LMD images. We wish to acknowledge Paul Wohnoutka, Amanda Ebbert, and Lon Luong for supporting data production, Chinh Dang for supporting database needs, Kelly Overly for contracting assistance, David Haynor for discussions on project design, and Christof

Koch for critical reading of the manuscript. Finally, thanks to Affymetrix for preferred pricing on rhesus microarrays. “
“After stroke, the extent of brain and behavioral recovery is influenced by local inflammatory changes and neural circuit plasticity. Inflammation exacerbates damage through a range of mechanisms, including activation of microglia, oxidative stress, and infiltration by peripheral immune cells

(Choe et al., 2011, Wnt inhibitor Hurn et al., 2007 and Offner et al., 2006). Increased functional recovery is associated with neural plasticity, including axonal sprouting in corticospinal projections that occurs days to weeks after ischemic injury (Carmichael et al., 2001, Lee et al., 2004 and Netz et al., 1997). Ischemia induces changes in neuronal excitability and alters dendritic spines within hours (Brown et al., 2007, Brown et al., 2008 and Takatsuru et al., Selleckchem 5-Fluoracil 2009). Sprouting and growth of intracortical axons are also thought to serve as substrates for recovery in the somatosensory and visual cortex after peripheral injury or retinal lesion (Florence et al., 1998 and Palagina et al., 2009; Aldehyde_oxidase reviewed in Benowitz and Carmichael, 2010) and can happen rapidly (Yamahachi et al., 2009). On the other hand, cellular correlates of synaptic plasticity, such as long-term potentiation (LTP), are diminished by stroke (Sopala et al., 2000 and Wang et al., 2005). These observations suggest that recovery might be enhanced not only by dampening inflammation, but also by increasing synaptic and structural plasticity. Recently, we discovered that mice lacking major histocompatibility

class I (MHCI) function have enhanced visual cortical and hippocampal plasticity not only in development, but also in adulthood (Corriveau et al., 1998, Datwani et al., 2009, Huh et al., 2000 and Shatz, 2009). MHCI molecules are expressed in neurons and are located at synapses in the healthy central nervous system (CNS) (Datwani et al., 2009 and Needleman et al., 2010), and knocking out (KO) just H2-Kb (Kb) and H2-Db (Db) (KbDb KO), two of the more than 50 MHCI genes, is sufficient to enhance plasticity in mouse visual cortex (Datwani et al., 2009) and cerebellum (McConnell et al., 2009). An innate immune receptor, PirB (paired immunoglobulin-like receptor B) is known to bind MHCI both in neurons (Syken et al., 2006) and in the immune system (Matsushita et al., 2011 and Takai, 2005). Like Kb and Db, PirB is expressed in forebrain neurons, and PirB KO mice also have greater visual cortical plasticity (Syken et al., 2006).

, 1995). Oocysts were sporulated in a 2.5% potassium dichromate solution at room temperature under shaking, to ensure good aeration, and stored at 4 °C until use. Purity of the samples was regularly monitored by visual inspection of the purified oocysts. find more Experimental procedures employing animals followed

the institutional guidelines for the care and use of animals for research purposes. A total of 3–5 × 107 oocysts were washed with distilled water by several centrifugations (2500 × g/5 min) to remove the potassium dichromate solution, treated with sodium hypochlorite solution (5–6%) for 10 min at 4 °C, and washed three times in distilled water. DNA extraction followed the protocol described by Fernandez et al. (2003a), with exception that before the glass-bead cracking step, the oocysts were pre-treated with SDS (0.5%) and proteinase K (100 μg/ml) in extraction buffer (Tris–HCl 10 mM, pH 8.0; EDTA 50 mM, pH 8.0) for 2 h at 50 °C. This step was introduced to facilitate the subsequent oocyst disruption

and increase the final DNA yield. We designed a pair of primers to amplify the ITS1 region based on the E. tenella ribosomal cistron sequence (accession number AF026388). DNA samples of the 11 Eimeria species of rabbit were used as templates. PCR amplification was performed using 10 ng of template DNA, 1 U of Platinum®Taq DNA Polymerase High Fidelity (Invitrogen Corporation, Carlsbad, CA, USA), 1× High Fidelity PCR Buffer, 1.5 mM MgCl2,

Cilengitide in vivo 200 μM dNTP mix, and 0.4 μM of each ITS1-F and ITS1-R primers ( Table 1). After an initial denaturation step of Akt inhibitor 2 min at 94 °C, amplification was carried out for 30 cycles consisting of 1 min at 94 °C, 1 min at 58 °C and 1 min at 72 °C, with a final extension step of 7 min at 72 °C. The amplicons were analyzed on 1.5% agarose gels stained with 0.5 μg/mL ethidium bromide. The amplification bands were quickly visualized with a portable longwave UV lamp, excised from the gel, purified with spun-columns (GFX PCR DNA and Gel Band Purification Kit, GE Healthcare Biosciences, Pittsburgh PA, USA) and eluted with TE (10 mM Tris–HCl pH 7.4; 1 mM EDTA). DNA sequencing of the ITS1 amplicons was performed using the ABI PRISM Big Dye™ Terminator Cycle Sequencing v 3.1 kit (Applied Biosystems, Foster City CA, USA) in an ABI PRISM 3100 Genetic Analyzer with POP-6 polymer. All fragments were sequenced in both strands with at least three replicates, the reads were pre-processed using EGene package ( Durham et al., 2005) and assembled with CAP3 ( Huang and Madan, 1999). Sequences were considered finished when fully covered by at least three distinct reads in both strands with no high-quality discrepancies. The nucleotide sequences determined here were deposited in the GenBank database under accession numbers HM768881 to HM768891.

The intracellular solution contained (in mM): 128 potassium gluconate, 4 MgCl2, 10 HEPES, 1 EGTA, 4 Na2ATP, 0.4 Na2GTP, 10 sodium phosphocreatine, 3 sodium L-ascorbate, and 0.02 Alexa-594 (Molecular Probes), and 3 mg/ml biocytin (pH 7.27; 287 mOsm). Cells were recorded at depths from 46 to 103 μm within the brain slice. Data were acquired using Ephus (www.ephus.org). Pyramidal neurons were selected based on Cilengitide cost their morphology confirmed under fluorescence microscopy (Alexa-594 in pipette solution) or post hoc by biocytin

staining. For sCRACM mapping, EPSC were recorded in voltage clamp while holding at −70 mV (L2/3 cells) or −75 mV (L5 cells). Access resistances ranged 10–40 MΩ. For every vM1 cell included in the data set, the site of viral infection was confirmed to lie within the barrel cortex by post hoc histological analysis. Most infections were roughly centered on the barrel field. The position of a blue laser beam (473 nm; Crystal Laser) was controlled with galvanometer scanners (Cambridge Scanning, AZD8055 Inc.). The beam passed through an air objective (4×; 0.16 NA; UPlanApo, Olympus) and was nearly cylindrical (∼8–16 μm in diameter, full-width at half max at the specimen plane). The light pulses were controlled with

a Pockels cell (ConOptics). The power (0.7–1.8 mW) of the light pulses (duration, 1–2 ms) was adjusted so that the largest EPSCsCRACM had peak values in the range of 50–100 pA; in some Resveratrol cases EPSCsCRACM were smaller even at the highest laser powers. Each trial consisted of approximately 100 ms baseline, the photostimulus, and 300 ms response period. Stimulation sites were on a 50 μm grid. Grid sizes (12 × 24, 12 × 26 or 12 × 28) were adjusted based on the size of the neuron; all

grids covered all potential sites of input within the dendritic arbor. Each map was repeated 2–4 times. The laser stimuli were given in a spatial sequence designed to maximize the intervals between stimuli arriving to neighboring spots (Shepherd et al., 2003). sCRACM pixel values corresponded to the mean EPSC amplitude in a 75 ms time window after the onset of the stimulus (given in picoamperes, pA, for consistency with previous studies). In some figure panels (Figures 3D and 4B), we display only pixels with significant responses (response amplitude >6× standard deviation of the baseline). For each cell, maps were averaged across repeats. To show the spatial distribution of input, maps were first peak-normalized (Figures 5, 7D, S9E, and S9F) and then averaged across cells within a class. Normalization was necessary because response amplitudes vary across experiments depending on the infection efficiency and the ChR2 expression level. To quantify the total input for pairs of neighboring neurons we summed all pixels that showed significant responses (>6× standard deviation of the baseline; Figures 3D, 4C–4F, 6, 7E, S8D, and S8E).