The time constant of the decaying phase of gating currents was determined using a single or double time-exponential fitting procedure (see Figure S1). A weighted time constant was OSI906 calculated when a double exponential fit was used. The time constant of the activating (Nav and Kv) or deactivating (Nav) phases of ionic currents was determined using distinct monoexponential fits (see Figure S1). The V1/2 values were determined by fitting the Q-V curves with a two-state Boltzmann function. The statistical

analysis of the τmax values was performed using a standard two-tailed paired Student’s t test. All error bars indicate ±SEM. We thank Dr. Allan Drummond and Dr. Ramon Latorre for their insightful comments on the manuscript, Dr. Christopher Ahern and Dr. Stephan Pless for providing us with a plasmid encoding the human Nav1.5, and Dr. Ernesto Vargas for providing the pdb files for the all-atom simulation of the consensus resting state model. This work was

ALK mutation supported by National Institutes of Health grant GM030376. “
“Although amygdala circuitry has been implicated in anxiety in both humans (Büchel et al., 1999, Etkin et al., 2009 and Somerville et al., 2004) and rodent models (Adamec et al., 1999 and Davidson, 2002), the way in which it interacts with a distributed neural circuit to mediate anxiety is poorly understood. In rodents, a causal role for the amygdala microcircuitry has emerged in fear and anxiety (Ciocchi et al., 2010, Han

et al., 2009, Haubensak et al., 2010 and Tye et al., 2011), but relationships between the amygdala and distal regions are still unclear. One distal amygdalar projection target implicated in anxiety-related behaviors is the ventral hippocampus (vHPC; File and Gonzalez, 1996, McHugh et al., 2004 and Richardson et al., 2004). The vHPC shares robust reciprocal connections with the basolateral nucleus of the amygdala (BLA; O’Donnell and Grace, 1995 and Pikkarainen et al., 1999). Subsequent studies have concluded that the ventral, but not the dorsal, to hippocampus is required for the expression of anxiety-related behaviors in the elevated plus maze (EPM) and open-field test (OFT) (Bannerman et al., 2003, Kheirbek et al., 2013 and Kjelstrup et al., 2002). In vivo electrophysiology recordings have revealed neural correlates in the BLA and vHPC to anxiety-related behaviors, such as increased tonic firing in BLA (Wang et al., 2011) and increased theta-frequency synchrony between the vHPC and prefrontal cortex (PFC; Adhikari et al., 2010 and Adhikari et al., 2011). Although these studies establish neural correlates between anxiety-related behaviors and the BLA or vHPC during anxiety assays, the precise neural encoding dynamics of the BLA-vHPC projection are unknown.

Conversely, we observed a decrease in the numbers of basal YFP-labeled cells expressing Krt14 ( Figure 5B) and ICAM1 ( Figure 5C) in the mutant background, indicating

a depletion of HBCs under these conditions. Lineage-traced, Sox2-positive globose-shaped basal cells are present in the p63 knockout, consistent with the idea that the HBCs have differentiated into Selleckchem Everolimus proliferative GBCs (basal cells in Figure 5D). As judged by staining for activated caspase 3, the number of cells undergoing apoptosis is low in the wild-type background (∼0.2% of YFP-labeled cells are caspase 3 positive) and increases slightly to ∼0.4% of YFP-labeled cells in the conditional p63 knockout ( Figure 5M); the difference between mutant and control is not statistically significant,

however, suggesting that cell survival is not affected in p63 mutants at the stage we examined. New neurons are generated in the adult nervous system through the proliferation and differentiation of local adult neural stem cells, a process critical for supporting plasticity and regeneration (Zhao et al., 2008). The olfactory epithelium provides an attractive model system for illuminating the mechanisms regulating self-renewal and differentiation of adult neural stem cells, NVP-BKM120 owing to its capacity to regenerate over the entire lifespan of the animal, its relative simplicity, and the ease of experimental access to this neural structure in vivo. Previous studies have identified the HBC as the earliest multipotent stem cell in the postnatal olfactory epithelium in vivo (Iwai et al., 2008 and Leung et al., 2007). It was recently shown that ΔNp63 is expressed in HBCs, and a germline mutation in the p63 gene results in the absence of HBCs in the perinatal olfactory epithelium ( Packard et al., 2011). These latter observations demonstrate a role of p63 in the formation of HBCs from earlier progenitor cells in the embryonic olfactory epithelium, although the mechanism through which p63 functions in this developmental

process is unknown. For example, is Farnesyltransferase p63 required cell autonomously to direct olfactory progenitors to differentiate into HBCs, or does it function in some other way to support the generation of HBCs during late-stage embryogenesis? Given p63′s role in the maintenance of other embryonic epithelial stem cells ( Blanpain and Fuchs, 2007 and Crum and McKeon, 2010), it is possible that the absence of HBCs in the germline p63 null background is due to a defect in their survival once they are formed. Whatever the case, the cellular and molecular mechanisms driving the decision between the alternate cell fates of self-renewal and differentiation in HBCs have so far remained uncharacterized.

The mean size of the uEPSC was 36.2 pA (±20.3 pA; ±SD; range: 16–74 pA; n = 10), though our measurements may be biased toward slightly larger, more easily resolved responses. The success rate (0.52 ± 0.047; n = 10) placed a lower bound on the probability of synaptic vesicle release at recurrent synapses. We next determined the number of synaptic contacts each ChR2+ axon makes onto a given layer II pyramidal cell by measuring quantal responses (qEPSC) evoked by

replacing extracellular Ca2+ with Sr2+ to desynchronize synaptic release. In SCR7 in vivo slices bathed in Sr2+, light pulses evoked a large, early synchronous response with a tail of many small events that are thought to represent quantal synaptic currents (Figure 2Ci; Dodge et al., 1969, Franks and Isaacson, 2006 and Goda and Stevens, 1994). The similar amplitude of the light-evoked uEPSCs

and qEPSCs (25 ± 10 pA; ±SD; n = 11; Figures 2Cii and 2Civ) suggests that a recurrent axon typically makes a single en passant synaptic contact with a given pyramidal cell in the piriform cortex, consistent with anatomical predictions (Datiche et al., 1996 and Johnson et al., 2000). Moreover, at this contact, a presynaptic action potential releases, at most, a single quantum of transmitter. The light-evoked qEPSCs were larger and had faster kinetics than qEPSCs evoked from electrical stimulation of mitral and tufted cell axons in the lateral olfactory tract (LOT) in the same cells over (14 ± 4.0 pA; n = 9; Figures 2Ciii and 2Civ). The amplitudes of qEPSCs from afferent and recurrent inputs were consistent with Ruxolitinib the range of amplitudes of miniature EPSCs we recorded in tetrodotoxin (TTX) (17.3 ± 7.1 pA; ±SD; n = 562 events, n = 9 cells). The difference in the size of the afferent and recurrent qEPSCs may reflect differences in their biophysical properties (Schikorski and Stevens, 1999) or may simply reflect

greater dendritic filtering of the more distal LOT inputs. The ratio between the average EPSC (500 pA) evoked with a saturating light intensity that activates all ChR2+ inputs (see Figure 3E) and the unitary ESPC (25 pA) suggests that a cell receives, on average, 20 active inputs from the population of ChR2+ neurons. From the distribution of ChR2+ cells, we estimate that we infected about 8,000 excitatory neurons per animal (Figures S1E–S1H). This implies that the connectivity between any two pyramidal cells is less than 1%, and this value is largely independent of the distance between two piriform cells. Moreover, given that we infected less than 1% of all piriform pyramidal neurons (8,000 neurons out of a total of an assumed 106 pyramidal cells in the piriform), our observation of 20 activated ChR2+ inputs per cell implies that each neuron receives, at least, 2,000 recurrent excitatory inputs.

After three PBS washes, slices were incubated in PBS during 1 hr at room temperature and incubated 2 hr at room temperature with the secondary antibody: Alexa-488 goat anti-chicken (1:1,000, Molecular Probes) or Cyanine 3 donkey anti-rat, anti-mouse, or anti-rabbit (1:500, Jackson ImmunoResearch). Slices were then treated as described elsewhere (Dufour et al., 2003). Analyses GDC 973 were performed using a Zeiss Axioplan fluorescence microscope or a Zeiss

LSM510 confocal microscope. For immunohistochemistry, paraffin sections 4 μm thick were incubated at 98°C for 30 min in sodium citrate buffer (10 mM sodium citrate, 0.2% Tween 20, pH 6.0). The sections were immersed in 0.2% hydrogen peroxide for 30 min and preincubated in a humid chamber in PBS plus 5% horse serum with 0.3% Tween 20 for 30 min at room temperature, followed by overnight incubation with goat-ephrinB1 (1:40, R&D Systems) at 4°C. The sections were incubated with biotinylated rabbit anti-goat immunoglobulin G (5.0 mg/ml), followed by an avidin-biotin

peroxidase complex, and developed by immersing in DAB substrate according to the manufacturer’s instructions (Vectastain Elite ABC kit, Vector). The specificity of the staining was verified by incubation without the primary or secondary antibodies. Mouse ephrin-B1 complementary DNA (with or without Myc-tag sequence) SNS-032 manufacturer was cloned into pCAG-IRES-GFP (pCIG) plasmid using XhoI/HindIII restriction sites. Ephrin-B1T was deleted for the last 72 amino acids, fused in frame with enhanced green fluorescent protein sequence, and cloned into pCAG-IRES-RFP plasmid using XhoI/HindIII restriction sites. pEGFP plasmids with GFP-tagged

WT or dominant-negative human Prex1 and Myc-tagged WT from or ΔPDZ human Prex1 are a kind gift of M. Hoshino (Kyoto University Graduate School of Medicine). N-terminal 3× Flag-tagged WT and dominant-negative (T17N) human Rac3 in pCDNA3.1 were a kind gift from J. Collard (The Netherlands Cancer Institute). They were amplified by PCR, sequence verified, and cloned into pCIG using XhoI and EcoRI restriction sites. B1S37 EfnB1 S37D (A358G) was generated by PCR from pCIG-EfnB1 (F primer: ctcgagatggcccggcctgggca; R primer: tttgaattccaggcccatgtagtCggggctgaactcttg), sequence verified, and cloned back into pCIG-EfnB1 with XhoI (within pCIG multiple cloning site) and EcoRI (within EfnB1 coding sequence). For adhesion assays, embryos were in utero electroporated with pCIG or pCIG-EfnB1 at E14.5 as described earlier.

The authors thank R. Frackowiak and C. Lopez for their critical comments on an earlier version of the manuscript. This work was supported by the Stoicescu Foundation, the Swiss Science Foundation (Sinergia grant Balancing Body and Self), the Centre d’Imagerie BioMédicale (CIBM) of the University of Lausanne (UNIL), the Swiss Federal Institute of Technology Lausanne (EPFL), the University of Geneva (UniGe), the Centre Hospitalier Universitaire Vaudois (CHUV), the Hôpitaux Universitaires de Genève (HUG), and the Leenaards and the Jeantet Foundations. LH is supported by the Swiss National Science Foundation (SNSF, grant

323530-123718). The authors are supported by the Swiss National Foundation (SINERGIA CRSII1-125135/1). “
“(Neuron 70, 141–152; April 14, 2011) Because of an error during production, the first sentence

of Dabrafenib molecular weight the abstract mistakenly used “attend” instead of “attended”: Neurons in the primate dorsolateral prefrontal cortex (dlPFC) filter attend targets distinctly from distracters through their response rates. The journal regrets this error, and the online version of the manuscript now correctly reads “attended. “
“Endoplasmic SCH 900776 ic50 reticulum (ER) homeostasis, protein synthesis, and protein quality control processes are tightly coordinated events that together ensure a smooth and adequate flow of proteins through cellular compartments, without build-up of misfolded or unfolded proteins. In mammalian cells, disturbances in ER homeostasis trigger three distinct adaptive signaling pathways (Figure 1). First, the accumulation of unfolded proteins activates the ER-resident kinase PERK, whose major substrate is the translation initiation factor eiF2a. Upon phosphorylation of eiF2a, translation is inhibited, thus reducing the load on the folding machinery. In parallel, eiF2a phosphorylation Cell press stimulates

the translation of a specific subset of mRNAs, including that encoding the transcription factor ATF4. In turn, ATF4 drives the transcription of several critical genes including CHOP, the transcription factor that can trigger the expression of pro-apoptotic genes. A second pathway relies on the bifunctional transmembrane kinase-endonuclease IRE1. Upon detecting unfolded proteins in the ER lumen, IRE1 undergoes multimerization and autophosphorylation, which activates its ribonuclease domain. Active IRE1 is responsible for the unconventional splicing of the mRNA coding for XBP1: when activated, IRE1 ribonuclease removes the intron in XBP1 mRNA, allowing the mRNA to properly code for XBP1, a transcription factor that upregulates ER membrane biosynthesis, ER chaperones, and ER-associated degradation complexes. A third system is based on the cleavage of the transmembrane domain of the transcription factor ATF6.

An important caveat in the study of ICMs by EEG or MEG is that, due to their limited spatial resolution, these methods are prone to signal mixing artifacts, which are especially severe for estimates of brain interactions (Nolte et al., 2004 and Stam et al., 2007a). Through volume spread, any active source contributes, in weighted manner, to the signals at all sensors (Figure 2A). This can give rise to spurious signal correlations and, thus, distort connectivity measures. Several methods have been suggested to address this problem, which Sirolimus mw are based on the notion that volume spread contributes to apparent coupling with negligible

delay, whereas true neuronal communication also occurs at other delays. One possibility is to analyze the imaginary part of coherence, which, if significant, cannot be explained by volume spread (Nolte et al., 2004). Subsequent studies have introduced related measures such as the phase lag index (Stam et al., 2007a). Another approach that has Akt inhibitor recently been introduced has used phase orthogonalization of oscillatory signals from different sources before analyzing power envelope correlations (Figure 2B) (Hipp et al., 2012). This is equivalent to removing, after Fourier transformation, those components that have the same phase for the two signals. This method is insensitive to trivial correlations arising from two sensors seeing the identical signal component and enables the

selective study of true neuronal interactions from MEG or EEG recordings (Figures 2D and 2E) (Hipp et al., 2012 and Brookes et al., 2012). It should be noted, however, that this comes at the cost of also discarding true zero-phase synchrony, which is known from microelectrode recordings to be abundant in the brain (Singer, 1999 and Engel et al., 2001). For studying ICMs, it is also highly interesting to quantify functional relationships between waves new of different frequencies (Jensen and Colgin, 2007 and Palva and Palva, 2011). Measures such as n:m phase locking for n≠m, phase-amplitude coupling, or amplitude-amplitude coupling

can reveal nonlinear coupling across different frequencies, which is also less susceptible to volume spread artifacts. Functional connectivity, in whatever form, can in principle be estimated between all pairs of voxels specified on a grid or surface. It is essentially impossible to visualize such a connectivity matrix in its complete form and hence approaches using graph-theoretical measures (Bullmore and Sporns, 2009) have become popular to characterize ICMs with a small set of parameters for each voxel. Beyond data compression, this representation may indicate general properties of brain connections having, for instance, small world topology, in which there are many local but few remote connections, such that the neural nodes are generally connected by short paths (Bullmore and Sporns, 2012). Correlation patterns in ongoing activity were first described in animal studies.

4). There were no related SAEs, no immediate AEs or AEs leading to

withdrawal, and no other safety concerns were identified. SAEs considered not related to vaccination were reported for 44 children during the study period, 10 in JE-CV Group, 21 in MMR Group, and 13 in Co-Ad Group. Vaccinations were well tolerated, selleck compound with a similar percentage of children in each group reporting solicited injection site reactions (21.5% to 23.7%) (Table 2). Fewer solicited systemic reactions were reported when JE-CV was administered alone (47.8%) than after either MMR administered alone (54.2), or when the two vaccines were co-administered (64.8). There were no reported ARs. AESIs within 28 days after JE-CV vaccination were reported by 30 children (29.4%) in Group JE-CV, GSI-IX 49 children (25.0%) in Group MMR and 77 children (35.0%) in Group Co-Ad; a higher rate of children reported skin and subcutaneous disorders in Co-Ad Group. These AEs were reported at a similar frequency in MMR recipients irrespective of MMR administration concomitantly to the JE-CV vaccination; therefore, the higher frequency of AEs in the Co-Ad group is representative of the AE incidence after MMR vaccination. The most frequently

reported AESI was somnolence: 26 children (25.5%) in JE-CV Group, 45 children (23.0%) in MMR Group and 67 children (30.5%) in Co-Ad Group. One event of hypersensitivity was reported by one child in MMR Group. Thirty AEs, classed as skin and subcutaneous much tissue disorders and suggestive of hypersensitivity/allergic reactions (e.g. rash), were reported by 29 children, 22 of which were in Co-Ad Group. Two children suffered a febrile convulsion during the study, both in MMR Group: one 4 weeks after MMR vaccination; one on Day 256, during the safety follow-up. No vaccine failure was reported during the study. This study was designed to demonstrate whether co-administration of JE-CV and MMR vaccines had an impact on the immunogenicity or safety profile of the two vaccines compared with either vaccine administered alone. A non-inferiority design was used to assess

the seroconversion rates 42 days after vaccine administration, allowing the assessment of non-inferiority based on defined thresholds for each immune response. The study successfully demonstrated non-inferiority of the immune responses, in terms of seroconversion. A neutralizing antibody titer of ≥10 (1/dil) is the serological correlate of protection commonly accepted and recommended as evidence of protection by the WHO for the evaluation and licensure of new JE vaccines [8] and [9]. The demonstration of non-inferiority of the seroconversion rates after co-administration of JE-CV and MMR, versus separate administrations, means that there is no clinically meaningful immunogenic interference between these live, attenuated vaccines, in vivo.

The trigeminal ganglion has three main peripheral axonal branches, the ophthalmic, maxillary, and mandibular, which innervate the

corresponding regions of the face. Sensory information is then conveyed from the ganglia to the brainstem nuclei via a centrally projecting axonal bundle. The neurons that innervate each of these regions in the face are spatially segregated into specific domains within the ganglia and exhibit distinct gene expression profiles, reflecting the division of these otherwise similar trigeminal neurons into distinct subtypes (Hodge et al., 2007). Some of these differentially expressed genes affect axonal pathfinding programs that allow the central projections of these neurons to innervate the brainstem (Hodge AZD2281 molecular weight et al., 2007). Studies on the mechanism of the acquisition of these distinct identities have focused on BMP4, a TGF-β family member expressed in the distal epithelium of the maxillary and ophthalmic regions in the face (Hodge et al., 2007). As axons grow into these regions, they encounter BMP4, which results in a retrograde signal that leads to nuclear accumulation

of the phosphorylated and transcriptionally active forms of the SMAD1, 5, and 8 transcription factors (Nohe et al., 2004). Additionally, Tbx3, a predicted SMAD1 target ( Chen et al., 2008), is also selectively induced in selleck screening library the ophthalmic- and maxillary-innervating neurons in a BMP4-dependent manner ( Hodge et al., 2007). This retrograde signaling contributes to the gene expression differences between the ophthalmic- and maxillary-innervating neurons and mandibular-innervating trigeminal neurons ( Hodge et al., 2007). However, the nature of the retrograde BMP4 signal, and whether other factors are also involved in patterning the trigeminal ganglia remain unknown. We first sought to recapitulate retrograde BMP4 signaling in vitro by culturing dissociated

E13.5 rat trigeminal ganglia neurons in microfluidic chambers (Taylor et al., 2005). In these devices, axons grow through a 450 μm microgroove barrier and appear in the axonal compartment Bay 11-7085 by 2 days in vitro (DIV). Because the axons are fluidically isolated from the cell bodies, this approach allows experimental treatments to be applied selectively to axons (Taylor et al., 2005; Figure S1A, available online). The majority of the neurons that are adjacent to the microgrooves send an axon to the axonal compartment, as detected by retrograde labeling of cell bodies by axonal application of CM-DiI (Figure S1A). Selective application of BMP4 to the axonal compartment resulted in an increase in nuclear pSMAD1/5/8 (Figures 1A, 1B, S1B, and S1C). pSMAD1/5/8 levels nearly doubled within 15 min, with further increases over 1–2 hr (Figure S1D). Total SMAD1/5/8 localization and levels were unaffected (Figures S1E and S1F), indicating that BMP4 increases the fraction of SMAD1/5/8 that is phosphorylated.

Tout comme l’obésité, les prévalences du SMet et du DT2 s’élèvent avec l’âge. Et fait de nombreuses fois démontré par les études épidémiologiques, elles restent

supérieures chez l’homme à ce qui est observé dans le sexe féminin. A découlé fort logiquement http://www.selleckchem.com/products/LBH-589.html de ce constat, la question du rôle éventuel des stéroïdes sexuels dans cette différence liée au genre. De nombreuses études ont mis en évidence, chez l’homme adulte, un lien indiscutable entre abaissement du taux de testostérone plasmatique et syndrome d’insulino-résistance. Insulino-résistance et hypotestostéronémie sont par ailleurs impliqués dans la physiopathologie de plusieurs facteurs de risque vasculaire : hypertension artérielle, trouble de l’équilibre glycémique, dyslipidémie [1], [2], [3] and [4]. Deux constations supplémentaires ont amené à évaluer plus précisément l’équilibre androgénique des hommes suivis pour obésité, SMet ou DT2 : • la fréquence de ces anomalies métaboliques s’élève avec l’âge tandis que parallèlement la sécrétion testiculaire endocrine décline ; Chez l’homme, une baisse de la testostéronémie a été démontrée dans chacun des PD-0332991 mouse trois cadres pathologiques que constituent obésité, SMet et DT2. Il s’agit donc bien

là d’un point commun supplémentaire à ces trois entités, point commun dont l’identification a amené à s’interroger sur son implication physiopathologique, sa valeur pronostique et l’intérêt thérapeutique d’un rééquilibrage du statut androgénique. Une réduction du taux de testostérone plasmatique, dont l’ampleur est inversement corrélée à l’index de masse corporelle (IMC), a été mise en évidence chez l’homme adulte en surcharge pondérale. Dans le surpoids simple ou l’obésité non morbide, le taux de testostérone libre reste Levetiracetam situé dans les limites de la normale pour la tranche d’âge considérée. Dans ces deux situations, l’abaissement de la testostérone totale est en effet liée à la diminution du taux de la Sex Hormone-Binding Globulin (SHBG), protéine porteuse des stéroïdes sexuels encore dénommée Testosterone-estradiol-Binding Globulin (TeBG) dont le taux est négativement corrélé

à l’IMC ( figure 1) [5]. L’obésité massive s’accompagne, par contre, d’une réduction de l’ensemble des fractions, libre et liée, de la testostérone plasmatique [6]. L’obésité androïde s’associe à une insulino-résistance. Testostéronémie totale et taux de SHBG plasmatique en représenteraient des marqueurs, susceptibles également d’être impliqués dans son développement et, à un stade évolutif ultérieur, à celui d’un DT2. Il a été montré que le taux de testostérone plasmatique était fréquemment plus bas dans la population d’hommes atteints d’insulino-résistance que dans une population du même âge indemne de pathologie quelconque [2], [7] and [8]. Les résultats de ces études font même l’hypothèse qu’un taux bas de testostérone plasmatique exposerait à un risque plus élevé de développement d’un DT2.

In cerebellum-like circuits in fish, anti-Hebbian LTD is beautifully suited to explain

sensory cancellation, but causal evidence is again lacking. Proof will not come from selective blockade of STDP (which lacks unique cellular plasticity mechanisms), so clever strategies must be developed. One strategy is already apparent but is rarely used: to measure the precise temporal patterns of spiking associated with learning in vivo, to see if they are consistent with STDP. Another approach may be to use optogenetic manipulations to edit spike selleck chemical timing during natural learning. D.E.F. is supported by NSF grant #SBE-0542013 to the Temporal Dynamics of Learning Center, and NIH R01 073912. I thank Daniel Shulz, Vincent Jacob, Vanessa Bender, and Kevin Bender for many discussions. I apologize for omitting important studies due to space limitations. “
“In determining

how the brain codes for sensory inputs and motor outputs two types of measurement dominate the literature: the outputs (action potentials or units) of identified neurons or groups thereof and the local mean synaptic find more inputs (local-, far- or extracranial field potentials). Patterns observed in either measurement are clearly related; being dependent on the computational processes occurring in compartments of individual neurons and distributed networks. However, which, if any, of the patterns of activity observed in either type of measurement correspond to psychophysical performance in an organism remains open to a great deal of debate. This review attempts to put forward a synergistic view whereby the interrelationship between rates of neuronal output are considered with respect to the frequencies and types of synaptic input in neocortex. We first consider whether the first behavior of individual neocortical neurons may relate to cognitive and/or motor performance, arguing that the interconnectedness of neurons strongly

favors population coding. Working from this argument we then consider how many neuron’s outputs may constitute such a population code, what brings the population together, what features of the population’s inputs and outputs are most psychophysically salient, and finally how this relates to patterns of short and long term plasticity in cortex. Individual neurons make a quantifiable contribution to the function of simple nervous systems (e.g., McAllister et al., 1983). But when a nervous system consists of not ca. 102 neurons but 1011 neurons, as in man, do individual neurons still matter? It is well recognized that single neuron spiking contributes to the code for specific orientations of features in specific regions of the visual field (Hubel and Wiesel, 1959). Similarly, discrete spectrotemporal properties of auditory sensory presentations can be seen to be represented by the spiking of individual cortical neurons (Fritz et al., 2003; Figure 1).