A low-power stretchable neuromorphic nerve with proprioceptive feedback
By relaying neural signals from the motor cortex to muscles, devices for neurorehabilitation
can enhance the movement of limbs in which nerves have been damaged as a …
can enhance the movement of limbs in which nerves have been damaged as a …
[HTML][HTML] Human motor decoding from neural signals: a review
Many people suffer from movement disability due to amputation or neurological diseases.
Fortunately, with modern neurotechnology now it is possible to intercept motor control …
Fortunately, with modern neurotechnology now it is possible to intercept motor control …
Dynamical flexible inference of nonlinear latent factors and structures in neural population activity
Modelling the spatiotemporal dynamics in the activity of neural populations while also
enabling their flexible inference is hindered by the complexity and noisiness of neural …
enabling their flexible inference is hindered by the complexity and noisiness of neural …
Modeling and dissociation of intrinsic and input-driven neural population dynamics underlying behavior
Neural dynamics can reflect intrinsic dynamics or dynamic inputs, such as sensory inputs or
inputs from other brain regions. To avoid misinterpreting temporally structured inputs as …
inputs from other brain regions. To avoid misinterpreting temporally structured inputs as …
[HTML][HTML] Comparing open-source toolboxes for processing and analysis of spike and local field potentials data
VA Unakafova, A Gail - Frontiers in Neuroinformatics, 2019 - frontiersin.org
Analysis of spike and local field potential (LFP) data is an essential part of neuroscientific
research. Today there exist many open-source toolboxes for spike and LFP data analysis …
research. Today there exist many open-source toolboxes for spike and LFP data analysis …
[HTML][HTML] Universality, criticality and complexity of information propagation in social media
Statistical laws of information avalanches in social media appear, at least according to
existing empirical studies, not robust across systems. As a consequence, radically different …
existing empirical studies, not robust across systems. As a consequence, radically different …
[HTML][HTML] Predictive learning as a network mechanism for extracting low-dimensional latent space representations
Artificial neural networks have recently achieved many successes in solving sequential
processing and planning tasks. Their success is often ascribed to the emergence of the …
processing and planning tasks. Their success is often ascribed to the emergence of the …
[HTML][HTML] Dissociative and prioritized modeling of behaviorally relevant neural dynamics using recurrent neural networks
Understanding the dynamical transformation of neural activity to behavior requires new
capabilities to nonlinearly model, dissociate and prioritize behaviorally relevant neural …
capabilities to nonlinearly model, dissociate and prioritize behaviorally relevant neural …
A probabilistic framework for task-aligned intra-and inter-area neural manifold estimation
Latent manifolds provide a compact characterization of neural population activity and of
shared co-variability across brain areas. Nonetheless, existing statistical tools for extracting …
shared co-variability across brain areas. Nonetheless, existing statistical tools for extracting …
Dynamical flexible inference of nonlinear latent structures in neural population activity
Inferring complex spatiotemporal dynamics in neural population activity is critical for
investigating neural mechanisms and developing neurotechnology. These activity patterns …
investigating neural mechanisms and developing neurotechnology. These activity patterns …