Natural Form of Noncytolytic Flexible Human Fc as a Long-Acting Carrier of Agonistic Ligand, Erythropoietin

Human IgG1 Fc has been widely used as a bioconjugate, but exhibits shortcomings, such as antibody- and complement-mediated cytotoxicity as well as decreased bioactivity, when applied to agonistic proteins. Here, we constructed a nonimmunogenic, noncytolytic and flexible hybrid Fc (hyFc) consisting of IgD and IgG4, and tested its function using erythropoietin (EPO) conjugate, EPO-hyFc. Despite low amino acid homology (20.5%) between IgD Fc and IgG4 Fc, EPO-hyFc retained “Y-shaped” structure and repeated intravenous administrations of EPO-hyFc into monkeys did not generate EPO-hyFc-specific antibody responses. Furthermore, EPO-hyFc could not bind to FcγR I and C1q in contrast to EPO-IgG1 Fc. In addition, EPO-hyFc exhibited better in vitro bioactivity and in vivo bioactivity in rats than EPO-IgG1 Fc, presumably due to the high flexibility of IgD. Moreover, the mean serum half-life of EPO-hyFc(H), a high sialic acid content form of EPO-hyFc, was approximately 2-fold longer than that of the heavily glycosylated EPO, darbepoetin alfa, in rats. More importantly, subcutaneous injection of EPO-hyFc(H) not only induced a significantly greater elevation of serum hemoglobin levels than darbepoetin alfa in both normal rats and cisplatin-induced anemic rats, but also displayed a delayed time to maximal serum level and twice final area-under-the-curve (AUClast). Taken together, hyFc might be a more attractive Fc conjugate for agonistic proteins/peptides than IgG1 Fc due to its capability to elongate their half-lives without inducing host effector functions and hindering bioactivity of fused molecules. Additionally, a head-to-head comparison demonstrated that hyFc-fusion strategy more effectively improved the in vivo bioactivity of EPO than the hyperglycosylation approach

Spontaneous Local Gamma Oscillation Selectively Enhances Neural Network Responsiveness

Synchronized oscillation is very commonly observed in many neuronal systems and might play an important role in the response properties of the system. We have studied how the spontaneous oscillatory activity affects the responsiveness of a neuronal network, using a neural network model of the visual cortex built from Hodgkin-Huxley type excitatory (E-) and inhibitory (I-) neurons. When the isotropic local E-I and I-E synaptic connections were sufficiently strong, the network commonly generated gamma frequency oscillatory firing patterns in response to random feed-forward (FF) input spikes. This spontaneous oscillatory network activity injects a periodic local current that could amplify a weak synaptic input and enhance the network's responsiveness. When E-E connections were added, we found that the strength of oscillation can be modulated by varying the FF input strength without any changes in single neuron properties or interneuron connectivity. The response modulation is proportional to the oscillation strength, which leads to self-regulation such that the cortical network selectively amplifies various FF inputs according to its strength, without requiring any adaptation mechanism. We show that this selective cortical amplification is controlled by E-E cell interactions. We also found that this response amplification is spatially localized, which suggests that the responsiveness modulation may also be spatially selective. This suggests a generalized mechanism by which neural oscillatory activity can enhance the selectivity of a neural network to FF inputs

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)

Synaptic plasticity controls sensory responses through frequency-dependent gamma oscillation resonance

Synchronized gamma frequency oscillations in neural networks are thought to be important to sensory information processing, and their effects have been intensively studied. Here we describe a mechanism by which the nervous system can readily control gamma oscillation effects, depending selectively on visual stimuli. Using a model neural network simulation, we found that sensory response in the primary visual cortex is significantly modulated by the resonance between ‘‘spontaneous’ ’ and ‘‘stimulus-driven’’ oscillations. This gamma resonance can be precisely controlled by the synaptic plasticity of thalamocortical connections, and cortical response is regulated differentially according to the resonance condition. The mechanism produces a selective synchronization between the afferent and downstream neural population. Our simulation results explain experimental observations such as stimulus-dependent synchronization between the thalamus and the cortex at different oscillation frequencies. The model generally shows how sensory information can be selectively routed depending on its frequency components

Drd4 signaling in intra-Amygdala circuit regulates fear expression to non-predictive stimuli

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Comparison of visual quantities in untrained neural networks

Summary: The ability to compare quantities of visual objects with two distinct measures, proportion and difference, is observed even in newborn animals. However, how this function originates in the brain, even before visual experience, remains unknown. Here, we propose a model in which neuronal tuning for quantity comparisons can arise spontaneously in completely untrained neural circuits. Using a biologically inspired model neural network, we find that single units selective to proportions and differences between visual quantities emerge in randomly initialized feedforward wirings and that they enable the network to perform quantity comparison tasks. Notably, we find that two distinct tunings to proportion and difference originate from a random summation of monotonic, nonlinear neural activities and that a slight difference in the nonlinear response function determines the type of measure. Our results suggest that visual quantity comparisons are primitive types of functions that can emerge spontaneously before learning in young brains