QPSK coherent state discrimination via a hybrid receiver

We propose and experimentally demonstrate a near-optimal discrimination scheme for the quadrature phase shift keying protocol (QPSK). We show in theory that the performance of our hybrid scheme is superior to the standard scheme - heterodyne detection - for all signal amplitudes and underpin the predictions with our experimental results. Furthermore, our scheme provides the hitherto best performance in the domain of highly attenuated signals. The discrimination is composed of a quadrature measurement, a conditional displacement and a threshold detector

Experimental determination of the degree of quantum polarisation of continuous variable states

We demonstrate excitation-manifold resolved polarisation characterisation of continuous-variable (CV) quantum states. In contrast to traditional characterisation of polarisation that is based on the Stokes parameters, we experimentally determine the Stokes vector of each excitation manifold separately. Only for states with a given photon number does the methods coincide. For states with an indeterminate photon number, for example Gaussian states, the employed method gives a richer and more accurate description. We apply the method both in theory and in experiment to some common states to demonstrate its advantages.Comment: 5 page

Toward More Versatile and Intuitive Cortical Brain–Machine Interfaces

Brain–machine interfaces have great potential for the development of neuroprosthetic applications to assist patients suffering from brain injury or neurodegenerative disease. One type of brain–machine interface is a cortical motor prosthetic, which is used to assist paralyzed subjects. Motor prosthetics to date have typically used the motor cortex as a source of neural signals for controlling external devices. The review will focus on several new topics in the arena of cortical prosthetics. These include using: recordings from cortical areas outside motor cortex; local field potentials as a source of recorded signals; somatosensory feedback for more dexterous control of robotics; and new decoding methods that work in concert to form an ecology of decode algorithms. These new advances promise to greatly accelerate the applicability and ease of operation of motor prosthetics

A cognitive neuroprosthetic that uses cortical stimulation for somatosensory feedback

Present day cortical brain–machine interfaces (BMIs) have made impressive advances using decoded brain signals to control extracorporeal devices. Although BMIs are used in a closed-loop fashion, sensory feedback typically is visual only. However medical case studies have shown that the loss of somesthesis in a limb greatly reduces the agility of the limb even when visual feedback is available. Approach. To overcome this limitation, this study tested a closed-loop BMI that utilizes intracortical microstimulation to provide 'tactile' sensation to a non-human primate. Main result. Using stimulation electrodes in Brodmann area 1 of somatosensory cortex (BA1) and recording electrodes in the anterior intraparietal area, the parietal reach region and dorsal area 5 (area 5d), it was found that this form of feedback can be used in BMI tasks. Significance. Providing somatosensory feedback has the poyential to greatly improve the performance of cognitive neuroprostheses especially for fine control and object manipulation. Adding stimulation to a BMI system could therefore improve the quality of life for severely paralyzed patients

Stability Analysis of Asynchronous States in Neuronal Networks with Conductance-Based Inhibition

Oscillations in networks of inhibitory interneurons have been reported at various sites of the brain and are thought to play a fundamental role in neuronal processing. This Letter provides a self-contained analytical framework that allows numerically efficient calculations of the population activity of a network of conductance-based integrate-and-fire neurons that are coupled through inhibitory synapses. Based on a normalization equation this Letter introduces a novel stability criterion for a network state of asynchronous activity and discusses its perturbations. The analysis shows that, although often neglected, the reversal potential of synaptic inhibition has a strong influence on the stability as well as the frequency of network oscillations