Neural Sampling by Irregular Gating Inhibition of Spiking Neurons and Attractor Networks

A long tradition in theoretical neuroscience casts sensory processing in the brain as the process of inferring the maximally consistent interpretations of imperfect sensory input. Recently it has been shown that Gamma-band inhibition can enable neural attractor networks to approximately carry out such a sampling mechanism. In this paper we propose a novel neural network model based on irregular gating inhibition, show analytically how it implements a Monte-Carlo Markov Chain (MCMC) sampler, and describe how it can be used to model networks of both neural attractors as well as of single spiking neurons. Finally we show how this model applied to spiking neurons gives rise to a new putative mechanism that could be used to implement stochastic synaptic weights in biological neural networks and in neuromorphic hardware

A differential memristive synapse circuit for on-line learning in neuromorphic computing systems

Spike-based learning with memristive devices in neuromorphic computing architectures typically uses learning circuits that require overlapping pulses from pre- and post-synaptic nodes. This imposes severe constraints on the length of the pulses transmitted in the network, and on the network's throughput. Furthermore, most of these circuits do not decouple the currents flowing through memristive devices from the one stimulating the target neuron. This can be a problem when using devices with high conductance values, because of the resulting large currents. In this paper we propose a novel circuit that decouples the current produced by the memristive device from the one used to stimulate the post-synaptic neuron, by using a novel differential scheme based on the Gilbert normalizer circuit. We show how this circuit is useful for reducing the effect of variability in the memristive devices, and how it is ideally suited for spike-based learning mechanisms that do not require overlapping pre- and post-synaptic pulses. We demonstrate the features of the proposed synapse circuit with SPICE simulations, and validate its learning properties with high-level behavioral network simulations which use a stochastic gradient descent learning rule in two classification tasks.Comment: 18 Pages main text, 9 pages of supplementary text, 19 figures. Patente

A neuromorphic systems approach to in-memory computing with non-ideal memristive devices: From mitigation to exploitation

Memristive devices represent a promising technology for building neuromorphic electronic systems. In addition to their compactness and non-volatility features, they are characterized by computationally relevant physical properties, such as state-dependence, non-linear conductance changes, and intrinsic variability in both their switching threshold and conductance values, that make them ideal devices for emulating the bio-physics of real synapses. In this paper we present a spiking neural network architecture that supports the use of memristive devices as synaptic elements, and propose mixed-signal analog-digital interfacing circuits which mitigate the effect of variability in their conductance values and exploit their variability in the switching threshold, for implementing stochastic learning. The effect of device variability is mitigated by using pairs of memristive devices configured in a complementary push-pull mechanism and interfaced to a current-mode normalizer circuit. The stochastic learning mechanism is obtained by mapping the desired change in synaptic weight into a corresponding switching probability that is derived from the intrinsic stochastic behavior of memristive devices. We demonstrate the features of the CMOS circuits and apply the architecture proposed to a standard neural network hand-written digit classification benchmark based on the MNIST data-set. We evaluate the performance of the approach proposed on this benchmark using behavioral-level spiking neural network simulation, showing both the effect of the reduction in conductance variability produced by the current-mode normalizer circuit, and the increase in performance as a function of the number of memristive devices used in each synapse.Comment: 13 pages, 12 figures, accepted for Faraday Discussion

Toward genome editing in X-linked RP-development of a mouse model with specific treatment relevant features

Genome editing represents a powerful tool to treat inherited disorders. Highly specific endonucleases induce a DNA double strand break near the mutant site, which is subsequently repaired by cellular DNA repair mechanisms that involve the presence of a wild type template DNA. In vivo applications of this strategy are still rare, in part due to the absence of appropriate animal models carrying human disease mutations and knowledge of the efficient targeting of endonucleases. Here we report the generation and characterization of a new mouse model for X-linked retinitis pigmentosa (XLRP) carrying a point mutation in the mutational hotspot exon ORF15 of the RPGR gene as well as a recognition site for the homing endonuclease I-SceI. Presence of the genomic modifications was verified at the RNA and protein levels. The mutant protein was observed at low levels. Optical coherence tomography studies revealed a slowly progressive retinal degeneration with photoreceptor loss starting at 9 months of age, paralleling the onset of functional deficits as seen in the electroretinogram. Early changes to the outer retinal bands can be used as biomarker during treatment applications. We further show for the first time efficient targeting using the I-SceI enzyme at the genomic locus in a proof of concept in photoreceptors following adeno-associated virus mediated gene transfer in vivo. Taken together, our studies not only provide a human-XLRP disease model but also act as a platform to design genome editing technology for retinal degenerative diseases using the currently available endonucleases

Paired Associative Stimulation of the Auditory System: A Proof-Of-Principle Study

Background Paired associative stimulation (PAS) consisting of repeated application of transcranial magnetic stimulation (TMS) pulses and contingent exteroceptive stimuli has been shown to induce neuroplastic effects in the motor and somatosensory system. The objective was to investigate whether the auditory system can be modulated by PAS. Methods Acoustic stimuli (4 kHz) were paired with TMS of the auditory cortex with intervals of either 45 ms (PAS(45 ms)) or 10 ms (PAS(10 ms)). Two-hundred paired stimuli were applied at 0.1 Hz and effects were compared with low frequency repetitive TMS (rTMS) at 0.1 Hz (200 stimuli) and 1 Hz (1000 stimuli) in eleven healthy students. Auditory cortex excitability was measured before and after the interventions by long latency auditory evoked potentials (AEPs) for the tone (4 kHz) used in the pairing, and a control tone (1 kHz) in a within subjects design. Results Amplitudes of the N1-P2 complex were reduced for the 4 kHz tone after both PAS(45 ms) and PAS(10 ms), but not after the 0.1 Hz and 1 Hz rTMS protocols with more pronounced effects for PAS(45 ms). Similar, but less pronounced effects were observed for the 1 kHz control tone. Conclusion These findings indicate that paired associative stimulation may induce tonotopically specific and also tone unspecific human auditory cortex plasticity

The cAMP pathway is important for controlling the morphological switch to the pathogenic yeast form of Paracoccidioides brasiliensis

Paracoccidioides brasiliensis is a human pathogenic fungus that switches from a saprobic mycelium to a pathogenic yeast. Consistent with the morphological transition being regulated by the cAMP-signalling pathway, there is an increase in cellular cAMP levels both transiently at the onset (< 24 h) and progressively in the later stages (> 120 h) of the transition to the yeast form, and this transition can be modulated by exogenous cAMP. We have cloned the cyr1 gene encoding adenylate cyclase (AC) and established that its transcript levels correlate with cAMP levels. In addition, we have cloned the genes encoding three Gα (Gpa1–3), Gβ (Gpb1) and Gγ (Gpg1) G proteins. Gpa1 and Gpb1 interact with one another and the N-terminus of AC, but neither Gpa2 nor Gpa3 interacted with Gpb1 or AC. The interaction of Gpa1 with Gpb1 was blocked by GTP, but its interaction with AC was independent of bound nucleotide. The transcript levels for gpa1, gpb1 and gpg1 were similar in mycelium, but there was a transient excess of gpb1 during the transition, and an excess of gpa1 in yeast. We have interpreted our findings in terms of a novel signalling mechanism in which the activity of AC is differentially modulated by Gpa1 and Gpb1 to maintain the signal over the 10 days needed for the morphological switch

The Staphylococcus aureus Peptidoglycan Protects Mice against the Pathogen and Eradicates Experimentally Induced Infection

Staphylococcus aureus, in spite of antibiotics, is still a major human pathogen causing a wide range of infections. The present study describes the new vaccine A170PG, a peptidoglycan-based vaccine. In a mouse model of infection, A170PG protects mice against a lethal dose of S. aureus. Protection lasts at least 40 weeks and correlates with increased survival and reduced colonization. Protection extends into drug-resistant (MRSA or VISA) and genetically diverse clinical strains. The vaccine is effective when administered - in a single dose and without adjuvant - by the intramuscular, intravenous or the aerosol routes and induces active as well as passive immunization. Of note, A170PG also displays therapeutic activity, eradicating staphylococci, even when infection is systemic. Sustained antibacterial activity and induction of a strong and rapid anti-inflammatory response are the mechanisms conferring therapeutic efficacy to A170PG

Clouds, circulation and climate sensitivity

Fundamental puzzles of climate science remain unsolved because of our limited understanding of how clouds, circulation and climate interact. One example is our inability to provide robust assessments of future global and regional climate changes. However, ongoing advances in our capacity to observe, simulate and conceptualize the climate system now make it possible to fill gaps in our knowledge. We argue that progress can be accelerated by focusing research on a handful of important scientific questions that have become tractable as a result of recent advances. We propose four such questions below; they involve understanding the role of cloud feedbacks and convective organization in climate, and the factors that control the position, the strength and the variability of the tropical rain belts and the extratropical storm tracks