Human-level control through deep reinforcement learning.

The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms.

Three tools for the real-time simulation of embodied spiking neural networks using GPUs.

This paper presents a toolbox of solutions that enable the user to construct biologically-inspired spiking neural networks with tens of thousands of neurons and millions of connections that can be simulated in real time, visualized in 3D and connected to robots and other devices. NeMo is a high performance simulator that works with a variety of neural and oscillator models and performs parallel simulations on either GPUs or multi-core processors. SpikeStream is a visualization and analysis environment that works with NeMo and can construct networks, store them in a database and visualize their activity in 3D.

iSpike: a spiking neural interface for the iCub robot.

This paper presents iSpike: a C++ library that interfaces between spiking neural network simulators and the iCub humanoid robot. It uses a biologically inspired approach to convert the robot's sensory information into spikes that are passed to the neural network simulator, and it decodes output spikes from the network into motor signals that are sent to control the robot. Applications of iSpike range from embodied models of the brain to the development of intelligent robots using biologically inspired spiking neural networks.

Alpha1-AR-mediated activation of NKCC in rat cardiomyocytes involves ERK-dependent phosphorylation of the cotransporter.

We studied molecular and functional characteristics as well as hormonal regulation of the Na-K-2Cl cotransporter (NKCC) in the isolated rat heart and cardiomyocytes. NKCC activity was measured as bumetanide-sensitive (86)Rb(+) influx in isolated perfused rat hearts and isolated cardiomyocytes. Stimulation of alpha(1)-adrenoceptors (AR) by phenylephrine (30 microM) increased (86)Rb(+) influx.