Krasoulis A.,Institute for Adaptive and Neural Computation |
Nazarpour K.,Newcastle University |
Vijayakumar S.,Institute for Adaptive and Neural Computation
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS | Year: 2015
One way of enhancing the dexterity of powered myoelectric prostheses is via proportional and simultaneous control of multiple degrees-of-freedom (DOFs). Recently, it has been demonstrated that the reconstruction of finger movement is feasible by using features of the surface electromyogram (sEMG) signal. In such paradigms, the number of predictors and target variables is usually large, and strong correlations are present in both the input and output domains. Synergistic patterns in the sEMG space have been previously exploited to facilitate kinematics decoding. In this work, we propose a framework for simultaneous input-output dimensionality reduction based on the generalized eigenvalue problem formulation of multiple linear regression (MLR). We demonstrate that the proposed methodology outperforms simultaneous input-output dimensionality reduction based on principal component analysis (PCA), while the prediction accuracy of the full rank regression (FRR) method can be achieved by using only a few relevant dimensions. © 2015 IEEE.
Paradis A.-L.,University Pierre and Marie Curie |
Paradis A.-L.,French Institute of Health and Medical Research |
Paradis A.-L.,French National Center for Scientific Research |
Morel S.,University Pierre and Marie Curie |
And 6 more authors.
Frontiers in Human Neuroscience | Year: 2012
Waves of activity following a focal stimulation are reliably observed to spread across the cortical tissue. The origin of these waves remains unclear and the underlying mechanisms and function are still debated. In this study, we ask whether waves of activity modulate the MEG signals recorded in humans during visual stimulation with Gabor patches sequentially flashed along a vertical path, eliciting a perception of vertical apparent motion. Building upon the functional properties of long-rang horizontal connections, proposed to contribute to spreading activity, we specifically probe the amplitude and latency of MEG responses as a function of Gabor contrast and orientation. The results indicate that in the left hemisphere the response amplitude is enhanced and the half height response latency is shortened for co-aligned Gabor as compared to misaligned Gabor patches at a low but not at a high contrast. Building upon these findings, we develop a biologically plausible computational model that performs a 'spike time alignment' of the responses to elongated contours with varying contrast, endowing them with a phase advance relative to misaligned contours. © 2012 Paradis, Morel, Seriès and Lorenceau.
Maccione A.,Italian Institute of Technology |
Hennig M.H.,Institute for Adaptive and Neural Computation |
Gandolfo M.,Italian Institute of Technology |
Muthmann O.,Institute for Adaptive and Neural Computation |
And 4 more authors.
Journal of Physiology | Year: 2014
The immature retina generates spontaneous waves of spiking activity that sweep across the ganglion cell layer during a limited period of development before the onset of visual experience. The spatiotemporal patterns encoded in the waves are believed to be instructive for the wiring of functional connections throughout the visual system. However, the ontogeny of retinal waves is still poorly documented as a result of the relatively low resolution of conventional recording techniques. Here, we characterize the spatiotemporal features of mouse retinal waves from birth until eye opening in unprecedented detail using a large-scale, dense, 4096-channel multielectrode array that allowed us to record from the entire neonatal retina at near cellular resolution. We found that early cholinergic waves propagate with random trajectories over large areas with low ganglion cell recruitment. They become slower, smaller and denser when GABAA signalling matures, as occurs beyond postnatal day (P) 7. Glutamatergic influences dominate from P10, coinciding with profound changes in activity dynamics. At this time, waves cease to be random and begin to show repetitive trajectories confined to a few localized hotspots. These hotspots gradually tile the retina with time, and disappear after eye opening. Our observations demonstrate that retinal waves undergo major spatiotemporal changes during ontogeny. Our results support the hypotheses that cholinergic waves guide the refinement of retinal targets and that glutamatergic waves may also support the wiring of retinal receptive fields. © 2014 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society..
Solanka L.,University of Edinburgh |
Solanka L.,Institute for Adaptive and Neural Computation |
Van Rossum M.C.W.,Institute for Adaptive and Neural Computation |
Nolan M.F.,University of Edinburgh
eLife | Year: 2015
Neural computations underlying cognitive functions require calibration of the strength of excitatory and inhibitory synaptic connections and are associated with modulation of gamma frequency oscillations in network activity. However, principles relating gamma oscillations, synaptic strength and circuit computations are unclear. We address this in attractor network models that account for grid firing and theta-nested gamma oscillations in the medial entorhinal cortex. We show that moderate intrinsic noise massively increases the range of synaptic strengths supporting gamma oscillations and grid computation. With moderate noise, variation in excitatory or inhibitory synaptic strength tunes the amplitude and frequency of gamma activity without disrupting grid firing. This beneficial role for noise results from disruption of epileptic-like network states. Thus, moderate noise promotes independent control of multiplexed firing rate- and gamma-based computational mechanisms. Our results have implications for tuning of normal circuit function and for disorders associated with changes in gamma oscillations and synaptic strength. © Solanka et al.