, 2009). Here, our data reveal that CNIH-2/-3 selectively bind to GluA1 in hippocampal neurons, allowing GluA1A2 receptors to reach the surface, and suggest that CNIH-2/-3 interaction with non-GluA1 subunits is prevented by γ-8. Removal of CNIH-2/-3 also speeds up the deactivation kinetics of surface AMPARs, an effect attributable to the loss of GluA1A2 receptors, which deactivate more slowly than GluA2A3 receptors. Thus, our data point to a model in which the trafficking and gating of individual AMPARs are determined by the interplay of AMPAR subunits,

cornichons, and TARPs. Cnih2fl/fl and Cnih3fl/fl mice were generated by standard procedures Selleckchem PCI-32765 ( Figure S1 available online). GSK1120212 mouse Cnih2fl/fl and Cnih3fl/fl mice were first bred as homozygotes, and then Cnih2fl/fl mice were bred with Cnih3fl/fl mice and NEX-CRE mice. Importantly, homozygous Cnih2fl/fl and Cnih3fl/fl were indistinguishable from wild-type mice. In addition, the NEX-CRE Cnih2fl/fl (NexCnih2−/−) mice, in which CNIH-2 is deleted from all forebrain pyramidal neurons, appeared grossly normal, and breeding was Mendelian. We used three strategies to study the effects of deleting CNIH-2. Using Cnih2fl/fl mice, we (1) injected AAV-CRE-GFP into the hippocampus of postnatal day 0–2 (P0–P2) mouse pups and then made acute slices 3 weeks later; (2) made

hippocampal slice cultures at P6–P9, biolistically transfected neurons with CRE-GFP at 4 days in vitro (DIV), and recorded 2–3 weeks

later (see Experimental Procedures for details); and (3) crossed Cnih2fl/fl mice with because the NEX-CRE mouse line. In the first two sets of experiments, simultaneous recordings of AMPAR- and NMDAR-evoked excitatory postsynaptic currents (AMPAR- and NMDAR-eEPSCs, respectively) were made from a green-infected/-transfected CA1 pyramidal neuron expressing CRE and a neighboring control nongreen pyramidal neuron during stimulation of excitatory axons in stratum radiatum. This approach permitted a pairwise, internally controlled comparison of the consequence of our genetic manipulation. In the third approach using acute slices prepared from NexCnih2−/− mice, the ratio of the AMPAR- and NMDAR-eEPSCs was calculated and compared to wild-type neurons. CNIH-2 deletion in single neurons by P0–P2 injection (red circles) and in slice culture (black circles) caused a 54% reduction in AMPAR-eEPSCs (Figure 1A), but no change in NMDAR-eEPSCs (Figure 1B). Because there was no significant difference between the results from acute and cultured slices, the data were combined. CNIH-2 deletion also caused a speeding in the decay of AMPAR-EPSCs in acute slices. This included eEPSCs (Figure 1C) and miniature EPSCs (mEPSCs) (Figure 1E). Furthermore, mEPSC amplitude was reduced (Figure 1D), consistent with a reduction in AMPAR number at individual synapses.

These same factors may have also caused the almost complete and sustained suppression of renal CYP27B1. Although, at the end of the treatment period, serum calcitriol returned to baseline levels, FGF23 remained elevated. We do not presently know the mechanism B-Raf assay sustaining FGF23 levels; however, this would likely continue to suppress CYP27B1 expression and maintain CYP24A1 elevation. This FGF23 “memory” effect would be expected to have an impact on the efficacy of subsequent dosing, further supporting gradual repletion over bolus treatments. Previous studies have demonstrated that increased

expression of CYP24A1 in kidney and extra-renal target tissues is differentially regulated following increased calcitriol production [21], [22] and [23]. This differential regulation may depend on whether the target tissue in question can respond to FGF23 and whether FGF23

levels have been increased by vitamin D treatment. The observed PTH lowering in rats was equivalent at 24 h post-dose mTOR inhibitor after both IV and MR dosing. However, we postulate that PTH suppression would not have been sustained for much longer after IV dosing because CYP24A1 was increased in both kidney and parathyroid gland, serum FGF23 was elevated and CYP27B1 was suppressed. This is supported by the greater and more sustained PTH suppression observed in CKD patients between 24 and 72 h after the 900 μg MR dose. Bolus IV administration of calcifediol induced a 40-fold surge in kidney CYP24A1 expression by 8 h post-dose. This rapid induction of CYP24A1 was similar to that observed previously in rats (46-fold increase in kidney and 25-fold increase in intestine) following MycoClean Mycoplasma Removal Kit 2.5 weeks of high-dose vitamin D (three treatments per week of 25,000 IU each) [23]. This previous study demonstrated that consecutive rapid administrations of vitamin D progressively raise CYP24A1 levels, attenuating the intended impact of treatment. Recent clinical studies have shown that treatment of CKD patients with bolus cholecalciferol

results in a shift of vitamin D balance to net degradation with increased production of 24,25-dihydroxyvitamin D3, reduced production of 1,25-dihydroxyvitamin D and increased FGF23 expression [24]. Consistent with our findings, bolus cholecalciferol was not effective at suppressing iPTH. In our study, patients receiving bolus calcifediol exhibited elevated and sustained production of 24,25-dihydroxyvitamin D3. This likely reflects elevated CYP24A1 expression both in the kidney as well as in other vitamin D target tissues, but the mechanism underlying continued production of 24,25-dihydroxyvitamin D3 over 42 days is unknown. It is notable that both rat and patient responses to different rates of calcifediol administration were similar.

As there is no detectable morphological cycling in either the

Clk knockdown or the DAPT Mef2 rescue ( Figure 5D), Clk is upstream of Mef2 and cycling CLK/CYC activity is important for the circadian regulation of neuronal morphology. Although the reported circadian fasciculation-defasciculation cycle of adult Drosophila s-LNv neurons ( Fernández et al., 2008) had no known molecular connection to the core clock, we report here that the cycle requires the transcription factor Mef2. Mef2 is a direct target of the CLK/CYC complex, which is probably related to the observed mRNA and protein oscillations of Mef2 within PDF cells. Because the fasciculation phenotype of a Clk knockdown is rescued by Mef2 overexpression, it may function as the principal target of the CLK/CYC complex affecting neuronal morphology.

Mef2 itself targets numerous genes affecting neuronal development and morphology, including Fas2. This gene is genetically epistatic to Mef2, as increasing Fas2 levels rescues Mef2 overexpression effects on behavior as well as neuronal morphology. The results indicate that the transcription factor Mef2 links the CLK/CYC complex to Fas2, to circadian alterations in neuronal morphology, and even to locomotor activity rhythms. The mammalian Mef2 family is known to translate extra- and intracellular signals into transcriptional activity in multiple cell types and Kinase Inhibitor Library mw tissues of different species (Potthoff and Olson, 2007). This role is achieved via diverse mechanisms, which include transcriptional, translational, and posttranslational mechanisms as well as collaboration with specific coregulators (Black et al., 1998, Molkentin and Olson, 1996, Nojima et al., 2008 and Sandmann et al., 2007). Neuronal processes are regulated by Mef2, and it also regulates stimulus-dependent changes in synapse number (Flavell et al., 2006). In addition, mammalian Mef2 often plays opposing roles in the regulation of neuronal plasticity. For example, it promotes synapse development during early neuronal differentiation (Li et al., 2008) and then restricts synaptic number at later stages of development (Barbosa et al., 2008). It has similar

dual effects on dendritogenesis, affecting it positively via the miR379–miR410 cluster (Fiore et al., 2009) and negatively in response to cocaine (Pulipparacharuvil et al., 2008). This is likely due to the regulation of different gene Endonuclease sets at different times of development. Despite this complexity, it is possible that Mef2 plays a simple “linear” role in the described cycling of Drosophila PDF neuron fasciculation: the core clock cyclically regulates Mef2 expression, and Mef2 then cyclically regulates, either positively or negatively (such as in the case of Fas2), the transcription of genes functioning in neuronal remodeling ( Figure 6). Relevant to this model are recent experiments in Drosophila by Blau and coworkers, demonstrating cycling Mef2 levels within s-LNv neurons ( Blanchard et al., 2010).

, 2010; for similar conclusions on mitochondrial dysfunction in AD, see Cho et al., 2009;

for a critical review, see Fukui and Moraes, 2008). The upshot of these Bioactive Compound Library datasheet studies is that elevated ROS levels and mitochondrial dysfunction in DA SNc neurons are clearly associated with PD. Mitochondrial vulnerability might be a first hit target, predisposing DA SNc neurons for vulnerability to PD, but the mitochondrial respiratory chain dysfunctions may be an aggravating consequence rather than a cause of disease. Further supporting the notion that a selective vulnerability of DA SNc neurons to PD is linked to mitochondrial dysfunction, genes whose mutations are causally related to PD code Epigenetics inhibitor for proteins that either accumulate at mitochondria (Pink1, DJ-1, Htra2, LRRK2), are implicated in mitochondrial functionality (Parkin), or influence each other’s role in disease (Parkin and α-synuclein, Parkin and Pink1; e.g., Bogaerts et al., 2008 and Banerjee et al., 2009). However, like for the pharmacological evidence, it is not clear whether the genes cause PD by specifically impairing mitochondrial functions. For example, studies of α-synuclein function have provided evidence that this protein

has a critical role as a chaperone for SNARE assembly, and in regulating synaptic vesicle cycling (e.g., Nemani et al., 2010 and Burré et al., 2010). The mechanistic relationship between α-synuclein mutations and PD may thus involve synaptic transmission and excitability. Likewise, DJ-1 has a role as oxidative stress sensor, and Parkin also has a role in stress protection (e.g., Banerjee et al., 2009 and Guzman

et al., 2010), suggesting that the relationship between these genes and PD may involve cellular stress pathways. The etiology of PD may thus involve overburdening of stress pathways involving mitochondria, which are particularly sensitive in DA SNc neurons. How might DA SNc neurons be more vulnerable to mitochondrial dysfunction than other neurons? Studies addressing the excitability properties of PD-vulnerable neurons have provided exciting evidence as to how this vulnerability may come about. The studies show that adult DA SNc neurons are Ca-dependent next pacemakers whose intrinsic activity is driven by Cav1.3 low voltage-dependent L-type Ca-channels (Chan et al., 2007). These particular channels open at relatively hyperpolarized membrane potentials, leading to high Ca flux loads in DA SNc neurons. Notably, reducing Ca load with L-type Ca channel antagonists reduced the susceptibility of the SNc neurons to parkinsonism-inducing drugs (Chan et al., 2007). A recent study provided evidence that the pacemaking produces oxydative stress selectively in SNc dopaminergic neurons (Guzman et al., 2010). The oxydative stress is compensated by partial uncoupling of mitochondria, which is impaired in the absence of DJ-1 (Guzman et al., 2010).

Instead, we hypothesize that larger responses (in the form of an additive offset) aid in propagating the relevant visual information through a static pooling rule leading to more efficient selection of relevant signals. Whereas the particular form of max-pooling selection rule used was not essential, we used it because it has a plausible neural implementation. Cytoskeletal Signaling inhibitor We implemented a continuum of selection rules from averaging

to max pooling by taking the sum of the exponent of input signals. Other selection rules such as a soft-max operator (Kouh and Poggio, 2008) could have been used to achieve the same function. However, an exponential relation to inputs has been observed for visual neurons in sensory areas; these neurons are well modeled as linear operators with a static output nonlinearity

in the range of two to four (Albrecht and Hamilton, 1982). Higher exponent values might be achieved as sensory signals pass from one area to the next, each area contributing a part of the full exponent value. Our selection rule also includes a root operator, the purpose of which was simply to keep the output of the selection rule in the same range as the input, and could Screening Library in vitro also be achieved by other computations such as divisive normalization (Heeger, 1992). A prediction of our selection model is that distracters that evoke large responses (for example, those presented with higher contrast) will be better able to pass through the selection mechanism and, thus, disrupt performance. We tested and confirmed this prediction. These results parallel other reports (Palmer and Moore, 2009 and Yigit-Elliott et al., 2011) that show that high-contrast distracters (foils) can be incorrectly selected, leading to errors in behavioral performance. Similarly, searching for a high-contrast target among low-contrast distracters is less impaired relative to searching for a low-contrast target among high-contrast distracters when attention is allocated elsewhere (Braun, 1994) or V4 is lesioned (Schiller and Lee,

1991). These results all suggest that high-contrast stimuli preferentially access perception (but see Jonides and Yantis, 1988). Efficient selection with winner-take-all like selection below mechanisms as described here and elsewhere (e.g., Koch and Ullman, 1985 and Lee et al., 1999) provides a unified framework that can explain both these types of bottom-up effects as well as top-down effects of focal attention. Our conceptualization of the processes involved in the contrast discrimination task did not consider the limits of working memory in changing behavioral performance. To perform a two-interval discrimination task, observers must hold the contrast perceived in the first interval in working memory to compare with the perceived contrast in the second interval.

This overlap is easily explained by the fact that Cav2 channels are physically and functionally tightly associated with exocytotic sites. Not surprisingly, the Cav2 proteome also contains many PSD proteins since in that study no separation of pre- and postsynaptic compartments was attempted. Considering the high purity of our docked synaptic vesicle fraction, with proteins from other organelles (except mitochondria) being virtually absent, the identification of 30 hitherto uncharacterized proteins suggests that many of them are indeed constituents of the presynaptic active zone and adjacent

areas. While further work will be needed to clarify which of them is involved in presynaptic function, we have used in silico-based analyses for a preliminary characterization (Table S4). Accordingly, 16 proteins possess one or more predicted transmembrane domains. Twenty-six proteins appear to be conserved Obeticholic Acid between vertebrates, among these 12 are also conserved in invertebrates. Noteworthy, 18 proteins appear to be well expressed

in the mammalian brain based on standardized in situ hybridization (Allen Mouse Brain Atlas, http://mouse.brain-map.org). Thus, we consider it highly probable that at least some of these proteins will turn out to be constituents of the presynaptic membrane and/or the vesicular release apparatus. We extended our study to investigate the differences between glutamatergic versus GABAergic docking complexes by a slight modification of our original protocol. We Selleck LGK 974 find that, except of the transmitter-specific transporters and enzymes, only very few proteins are selectively enriched in glutamatergic and GABAergic docking complexes. These results confirm and extend our previous observation that glutamatergic and oxyclozanide GABAergic synaptic vesicles have

a largely identical protein composition. Two major conclusions can be drawn from these findings. First, the release machineries of glutamatergic and GABAergic synapses are very similar if not identical. In particular, we did not detect any major difference between the expression levels of SNAP25 and SNAP23 in the two types of synapses, arguing against a specialization of these SNAREs for glutamatergic versus GABAergic release as suggested previously (Garbelli et al., 2008; Verderio et al., 2004). Obviously, the overall similarity between the populations does not exclude major variations in the composition of the docking and release apparatus between individual synapses. However, such variations do not appear to correlate with the neurotransmitter phenotype. Second, it is only the biosynthetic enzymes and the transmitter transporters (particularly the vesicular transporters) that define the neurotransmitter phenotype of glutamatergic and GABAergic synapses. Taken together, we have made significant progress toward the aim of establishing a “parts list” of the presynaptic docking and release machinery and of the presynaptic membrane.

Consistent with the action of Homer1a to compete with Homer1c, Homer1a expression reduced the coimmunoprecipitation (co-IP) of mGluR5 with Homer1c compared to GFP-expressing neurons (Figure 4F). We monitored Homer1a mRNA and protein in DIV 14 cortical neurons treated with TTX or bicuculline for 3 hr, 6 hr, 12 hr, 24 hr, and 48 hr (Figure 5A). Galunisertib price Bicuculline produced a time-dependent increase that was maximum at 6hrs for mRNA and 12 hr for protein (each ∼8-fold), and returned to basal levels at 48 hr. By

contrast, TTX treatment reduced Homer1a mRNA ∼5-fold by 24 hr and protein by ∼4-fold at 48 hr. To assess how Homer1a KO affects homeostatic scaling, we examined the surface levels of AMPARs after chronic TTX or bicuculline treatment. Biotinylation and IHC assays revealed an absence of homeostatic adaptations of GluA2/3 in Homer1a KO neurons (Figures 5B–5E). Homeostatic adaptations of GluA1 were significantly reduced in Homer 1a KO neurons, but not as strikingly disrupted as GluA2. Homeostatic adaptations of mGluR5 were not significantly different in Homer1a KO neurons. Disruption

of homeostatic scaling in Homer1a KO neurons was also evident in mEPSCs recordings (Figures 5F and 5G). In contrast to WT neurons where TTX resulted in an increase of mEPSC (WT-control Epacadostat mouse 20.9 ± 1.1 pA; n = 24 cells; TTX-treated 30.1 ± 2.2 pA; n = 15 cells, ∗∗∗p < 0.001), mEPSC amplitudes of TTX-treated Homer1a KO neurons

(31.4 ± 2.6 pA; n = 20 cells) were not significantly greater than untreated Homer1a KO neurons (28.9 ± 1.3 pA; n = 33 cells) (Figure 5G). Similarly, chronic bicuculline treatment reduced mEPSC amplitudes in WT neurons (14.1 ± 0.2 pA; n = 28 cells; ∗∗∗p < 0.001), but did not produce a significant decrease in mEPSC amplitudes in Homer1a KO neurons (27.2 ± 1.9 pA; n = 35 cells) compared to untreated Homer1a KO neurons. Comparison of Homer1a KO neurons treated with bicuculline versus TTX suggested a small difference but was not statistically significant below (27.2 ± 1.9 pA compared to 31.4 ± 2.6 pA; p = 0.19, not significant); this is dramatically different than WT neurons (14.1 ± 0.2 pA compared to 30.1 ± 2.2 pA). There was no difference in the frequency of mEPSCs between TTX-treated WT neurons (24.4 ± 2.6 Hz; n = 24 cells), bicuculline-treated WT neurons (22.2 ± 1.7 Hz; n = 28 cells), untreated WT neurons (23.4 ± 2.6 Hz; n = 24 cells), or similarly treated Homer1a KO neurons (TTX-treated, 24.9 ± 2.6 Hz; n = 20 cells; bicuculline-treated 27.6 ± 2.8 Hz; n = 35 cells; untreated 25.3 ± 2.9 Hz; n = 33 cells) (Figure 5G). These observations confirm that homeostatic changes of synaptic strength are markedly disrupted in Homer1a KO neurons.

In summary, the studies by Chen et al. (2012) and van Versendaal et al. (2012) convincingly show that inhibitory synapses in the adult brain display profound structural dynamics

of their own. By means of the tracking of individual postsynaptic inhibitory synaptic scaffolds in vivo they were able to reveal that L2/3 cell ocular dominance plasticity may be initiated by the pruning of predominantly inhibitory spine synapses on apical dendrites. This pruning occurs close to dynamic spines and may regulate plasticity of circuits that preferentially impinge on distal dendrites. These studies firmly establish that inhibitory structural remodeling has its share in visual cortex plasticity and provide a framework for future endeavors to unravel its mechanisms. “
“In the 1998 film The Truman Show, a group of television producers labors with Herculean selleck chemicals passion to manufacture an artificial but believable world for an insurance PI3K Inhibitor Library nmr salesman, Truman Burbank (played by actor Jim Carrey), who unwittingly stars in his own reality show. As each new day dawns, or is meant to dawn, in the town of Seahaven, the order is shouted within the TV control room to “cue the sun!” The well-timed appearance of a heavenly orb—perhaps the most reliable and dependable sensory cue known to roosters and humans alike—signals morning and launches Truman out of bed. Hollywood actors notwithstanding, human and nonhuman animals

of all sorts readily utilize sensory cues to predict events and guide behavior. External cues, typically arriving in visual, olfactory, auditory, or verbal format, may announce a general state-based change in behavior or in the environmental milieu, for example, the sound of a dinner bell signaling that food is imminent. Alternatively, external cues may forecast more specific information about the identity of an upcoming event, enhancing sensory discrimination, response speed, and perceptually based decisions. The roasted smell of coffee in the morning sets up an expectation of coffee flavor that is met upon sipping from your breakfast mug. Not infrequently, an

external cue can be uninformative or misinformative, or absent altogether. Having learned to predict the through presence of something that is actually not there has adverse behavioral consequences, reducing discrimination and response speed, and creating cognitive dissonance. Finding that the same coffee smell leads not to coffee but, unexpectedly, to black tea (sipping from the wrong mug, for example) may result in breakfast dismay. The majority of neuroscientific research on sensory expectation, awareness, and prediction has focused on the visual system (Gilbert and Sigman, 2007, Kouider and Dehaene, 2007 and Summerfield and Egner, 2009), whereas comparable studies of the chemical senses—smell and taste—are, well, to be unexpected. In this issue of Neuron, Samuelsen et al.

, 2005; Barbano et al., 2009). Moreover, though dopaminergic manipulations can affect behavioral outcomes in animals trained on learning tasks, there is not strong evidence that accumbens DA is critical for the specific aspect of instrumental learning that involves the association between Enzalutamide order the instrumental action and the reinforcing outcome (Yin et al., 2008). Nevertheless, accumbens

DA clearly is important for aspects of appetitive as well as aversive motivation (Salamone et al., 2007; Cabib and Puglisi-Allegra, 2012) and participates in learning processes, at least in part through processes that involve Pavlovian approach and Pavlovian to instrumental transfer (Yin et al., 2008; Belin et al., 2009). Interference with accumbens DA transmission

blunts the acquisition of Pavlovian approach responses that are instigated by cues that predict food delivery and impairs avoidance responses elicited by cues that predict aversive stimuli. Accumbens DA depletions or antagonism reduce the activating effects of conditioned stimuli and make animals very sensitive to work-related instrumental response costs (e.g., output of ratio schedules with large ratio requirements, Selleck VE 821 barrier climbing; Salamone et al., 2007, 2012; Barbano et al., 2009). Thus, nucleus accumbens DA is clearly involved in the aspects of motivation, and the regulation of goal-directed actions, but in a rather specific and complex way that is not conveyed by the simple word “reward.” Some instrumental tasks tap into the functions subserved by mesolimbic DA (e.g., activational aspects of motivation, exertion of effort), and thus impairment of mesolimbic DA readily affects performance on these tasks, while responding on other positively reinforced tasks, or measures of primary food motivation, are left intact. In the last few years, the picture that has emerged too is that neostriatum (i.e., dorsal striatum) and its DA innervation

appears to have a clearer link to the processing of instrumental associations than does the nucleus accumbens (Yin et al., 2008). Lesions of the dorsomedial neostriatum made animals insensitive to both reinforcer devaluation and contingency degradation (Yin et al., 2005). Both cell body lesions and DA depletions in dorsolateral striatum have been shown to impair habit formation (Yin et al., 2004; Faure et al., 2005). The involvement of neostriatum in habit formation could be related to the hypothesized role of the basal ganglia in promoting the development of action sequences or “chunking” of components of instrumental behavior (Graybiel, 1998; Matsumoto et al., 1999). The idea that there is a transition from ventral striatal regulation of instrumental responding to neostriatal mechanisms that regulate habit formation has been employed extensively to provide an explanation of several features of drug addiction (see review by Belin et al.

Finally, it is unclear whether the effect of training on correlated noise is specific to tasks for which area MSTd is thought to provide critical input. If we had trained Selleck BAY 73-4506 animals to perform a task that was irrelevant to self-motion perception, such as a somatosensory or auditory discrimination task, we presumably would not expect to see changes in correlated noise in MSTd. However, this possibility remains to be tested. Despite a robust effect of training on the average noise correlation in MSTd, our simulations show that an optimal, unbiased decoding of all neurons does not predict

a substantial change in performance due to learning. Indeed, theorists have shown that correlated noise may or may not harm population PI3K inhibitor coding (Abbott and Dayan, 1999, Averbeck et al., 2006 and Wilke and Eurich, 2002). In general, positively correlated noise between neurons with similar tuning (or more generally, any situation in which both neurons fire more strongly under one stimulus/task condition than another) harms the signal to noise ratio of the population code because it cannot be removed by pooling across neurons (Bair et al., 2001, Shadlen

et al., 1996 and Zohary et al., 1994b). Reducing shared noise among neurons in such cases is thus expected to improve population sensitivity. Indeed, the effect of attention on the fidelity of population codes appears to

follow this logic (Cohen and Maunsell, 2009). In a typical spatial attention task, most neurons with receptive fields at the attended location will increase their response. Because attention has a consistent polarity of effect on the responses of nearby neurons, stronger attention will tend to increase the responses of both neurons in a pair. Hence, most pairs of nearby neurons will have positive signal correlations with respect to the effect of attention. As a result, a reduction in correlated noise due to attention can improve the signal-to-noise ratio of the population code. However, in other contexts whatever for which signals are decoded from populations that include neurons with dissimilar tuning properties, increasing correlated noise can improve the signal-to-noise ratio of a population code (Figure 7A), as differences in tuning effectively cancel more of the noise in a population response (Abbott and Dayan, 1999, Averbeck et al., 2006, Poort and Roelfsema, 2009 and Wilke and Eurich, 2002). Reducing correlated noise in the latter case can harm the coding efficiency of the population. In our heading discrimination task, it is likely that responses are decoded from neurons with a broad range of heading preferences (Gu et al., 2008b and Gu et al.