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We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, including Hodgkin-Huxley type, integrate-and-fire models, interacting with current-based or conductance-based synapses, using clock-driven or event-driven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integration strategy and simulation tool to use for a given modeling problem related to spiking neural networks.

Two basic tasks must be performed by an olfactory robot tracking a specific odor source: navigate in a turbulent odor plume and recognize an odor regardless of its concentration. For these two tasks, we propose simple biologically inspired strategies, well suited for building dedicated circuits and for on-board implementation on real robots. The odor recognition system is based on a spiking neural network using a synchronization coding scheme. The robot navigation system is based on the use of bilateral comparison between two spatially separated gas sensors arrays at either side of the robot. We propose binary or analog navigation laws depending on the nature of the available sensory information extracted from the plume structure (isolated odor patches or smoother concentration field).

This paper describes the Inria team's integrated robotics system used in the 1st euROBIN coopetition, during which service robots performed voice-activated household tasks in a kitchen setting.The team developed a modified Tiago++ platform that leverages a whole-body control stack for autonomous and teleoperated modes, and an LLM-based pipeline for instruction understanding and task planning. The key contributions (opens-sourced) are the integration of these components and the design of custom teleoperation devices, addressing practical challenges in the deployment of service robots.

This paper presents a complete processing chain for decoding intracranial data recorded in the cortex of a monkey and replicates the associated movements on a JACO robotic arm by Kinova. We developed specific modules inside the OpenViBE platform in order to build a Brain-Machine Interface able to read the data, compute the position of the robotic finger and send this position to the robotic arm. More pre- cisely, two client/server protocols have been tested to transfer the finger positions: VRPN and a light protocol based on TCP/IP sockets. According to the requested finger position, the server calls the associ- ated functions of an API by Kinova to move the fin- gers properly. Finally, we monitor the gap between the requested and actual fingers positions. This chain can be generalized to any movement of the arm or wrist.

Although the spike-trains in neural networks are mainly constrained by the neural dynamics itself, global temporal constraints (refractoriness, time precision, propagation delays, ..) are also to be taken into account. These constraints are revisited in this paper in order to use them in event-based simulation paradigms. We first review these constraints, and discuss their consequences at the simulation level, showing how event-based simulation of time-constrained networks can be simplified in this context: the underlying data-structures are strongly simplified, while event-based and clock-based mechanisms can be easily mixed. These ideas are applied to punctual conductance-based generalized integrate-and-fire neural networks simulation, while spike-response model simulations are also revisited within this framework. As an outcome, a fast minimal complementary alternative with respect to existing simulation event-based methods, with the possibility to simulate interesting neuron models is implemented and experimented.

The Baculovirus/insect cell expression system is a powerful technology for reconstitution of eukaryotic macromolecular assemblies. Most multigene expression platforms rely on Tn7-mediated transposition for transferring the expression cassette into the baculoviral genome. This allows a rigorous characterization of recombinant bacmids but involves multiple steps, a limitation when many constructs are to be tested. For parallel expression screening and potential high throughput applications, we have established an open source multigene-expression toolbox exploiting homologous recombination, thus reducing the recombinant baculovirus generation to a single-step procedure and shortening the time from cloning to protein production to 2 weeks. The HR-bac toolbox is composed of a set of engineered bacmids expressing a fluorescent marker to monitor virus propagation and a library of transfer vectors. They contain single or dual expression cassettes bearing different affinity tags and their design facilitates the mix and match utilization of expression units from Multibac constructs. The overall cost of virus generation with HR-bac toolbox is relatively low as the preparation of linearized baculoviral DNA only requires standard reagents. Various multiprotein assemblies (nuclear hormone receptor heterodimers, the P-TEFb or the ternary CAK kinase complex associated with the XPD TFIIH subunit) are used as model systems to validate the toolbox presented.

Nuclear receptors (NRs) are ligand‐dependent transcription factors that control a large number of physiological events through the regulation of gene transcription. NRs function either as homodimers or as heterodimers with retinoid X receptor/ultraspiracle protein (RXR/USP). A structure‐based sequence analysis aimed at discovering the molecular mechanism that controls the dimeric association of the ligand‐binding domain reveals two sets of differentially conserved residues, which partition the entire NR superfamily into two classes related to their oligomeric behaviour. Site‐directed mutagenesis confirms the functional importance of these residues for the dimerization process and/or transcriptional activity. All homodimers belong to class I, in which the related residues contribute a communication pathway of two salt bridges linking helix 1 on the cofactor‐binding site to the dimer interface. A salt bridge involving a differentially conserved arginine residue in loop H8–H9 defines the signature motif of heterodimers. RXR/USP and all Caenorhabditis elegans NRs belong to class I, supporting the hypothesis of an earlier emergence of this class.