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Intracortical microelectrodes can be used to treat various neurological disorders given their capabilities to interface with single or multiple populations of neurons. However, most of these penetrating devices have been reported to fail over time, within weeks to months, putatively due to the foreign body response (FBR) which persistently aggravates the surrounding brain tissues. A number of studies...
Neuronal networks cultured on microelectrode arrays (MEAs) have been utilized as biosensors that can detect all or nothing extracellular action potentials, or spikes. Coating the microelectrodes with carbon nanotubes (CNTs), either pristine or conjugated with a conductive polymer, has been previously reported to improve extracellular recordings presumably via reduction in microelectrode impedance...
Deep Brain Stimulation (DBS) is an established treatment in Parkinson's Disease. The target area is defined based on the state and brain anatomy of the patient. The stimulation delivered via state-of-the-art DBS leads that are currently in clinical use is difficult to individualize to the patient particularities. Furthermore, the electric field generated by such a lead has a limited selectivity, resulting...
It has been proved that Transcranial DCS (tDCS) can modulate cortical excitability, enhancing or decreasing, respectively by anodal or cathodal polarity. The short-term and lasting alterations induced by tDCS are strictly related to the charge density, duration of stimulation and the depth of neuron below the skull. Epilepsy represents a pathophysiological model of unbalanced relation between cortical...
To perform large-scale simulations of the brain or build biologically-inspired cognitive architectures, it is essential to have a succinct and flexible model of spiking neurons. The model should be able to capture the nonlinear dynamical properties of various types of neurons and the nonstationary properties such as the spike-timing-dependent plasticity (STDP). In this paper, we propose a generalized...
Current electronic noses, or e-noses, that employ insect odorant receptors (Ors) as their sensory front end are potentially limited by the fact that the Ors come from a single species. In addition, a realistic e-nose also demands low numbers of Ors at its sensory front end due to the difficulties of receptor/sensor integration and functionalisation. In this work, we report the first investigations...
Neuroinformatics has recently emerged as a powerful field for the statistical analysis of neural data. This study uses machine learning techniques to analyze neural spiking activities within a population of neurons with the aim of finding spiking patterns associated with different stages of movement. Neural data was recorded during many experimental trials of a cat performing a skilled reach and withdrawal...
The technology underlying brain computer interfaces has recently undergone rapid development, though a variety of issues remain that are currently preventing it from becoming a viable clinical assistive tool. Though decoding of motor output has been shown to be particularly effective when using spikes, these decoders tend to degrade with the loss of subsets of these signals. One potential solution...
Hand orientation is an important control parameter during reach-to-grasp task. In this paper, we presented a study for predicting hand orientation of non-human primate by decoding neural activities from primary motor cortex (M1). A non-human primate subject was guided to do reaching and grasping tasks meanwhile neural activities were acquired by chronically implanted microelectrode arrays. A Support...
Observing an action being performed and executing the same action cause similar patterns of neural activity to emerge in the primary motor cortex (MI). Previous work has shown that the neural activity evoked during action observation (AO) is informative as to both the kinematics and muscle activation patterns of the action being performed, although the neural activity recorded during action observation...
When imitating biological sensors, we have not completely understood the early processing of the input to reproduce artificially. Building hybrid systems with both artificial and real biological components is a promising solution. For example, when a dragonfly is used as a living sensor, the early processing of visual information is performed fully in the brain of the dragonfly. The only significant...
It is possible to cause a sensation of light in patients who have lost photoreceptors due to degenerative eye diseases by targeting surviving neurons with electrical stimulation by means of visual prosthetic devices. All stimulation strategies in currently used visual prostheses are open-loop, that is, the stimulation parameters do not depend on the level of activation of neurons surrounding stimulating...
We present a computational model of the optic pathway which has been adapted to simulate cortical responses to visual-prosthetic stimulation. This model reproduces the statistically observed distributions of spikes for cortical recordings of sham and maximum-intensity stimuli, while simultaneously generating cellular receptive fields consistent with those observed using traditional visual neuroscience...
The rectification of EMG signals is a preprocessing method widely used for inferring neural connectivity by coherence analysis. The assumption for the use of this non-linear operator is that it enhances the neural information in the signal, i.e. the motor unit spike trains. However, because of non-linearity, it is difficult to predict the effect of rectification on the EMG power spectrum. In this...
The ability of an organism to specifically attend to relevant sensory information during learning and subsequent performance of a task is highly dependent on the release of the neurotransmitter Acetylcholine (ACh). Electrophysiological studies have shown that pairing endogenous ACh with specific visual or auditory stimuli induces long lasting enhancements of subsequent cortical responses to the previously...
Mathematical models of the neuronal activity in the affected brain regions of Essential Tremor (ET) and Parkinson's Disease (PD) patients could shed light into the underlying pathophysiology of these diseases, which in turn could help develop personalized treatments including adaptive Deep Brain Stimulation (DBS). In this paper, we use an Ornstein Uhlenbeck Process (OUP) to model the neuronal spiking...
Understanding how M1 neurons innervate flexible coordinated upper limb reaching and grasping is important for BMI systems that attempt to reproduce the same actions. In this paper, we presented a study for exploring M1 neuronal activities while a non-human primate subject was guided to finish different visual cued spatial reaching and grasping tasks. By applying various configurations of target objects...
In order to reverse-engineer the information processing capabilities of the cortical circuit, we need to densely sample neural circuit; it may be necessary to sample the activity of thousands of neurons simultaneously. Frame scanning techniques do not scale well in this regard, due to the time ”wasted” scanning extracellular space. For scanners in which inertia can be neglected, path length minimization...
Ensembles of single-neurons in motor cortex can show strong low-dimensional collective dynamics. In this study, we explore an approach where neural decoding is applied to estimated low-dimensional dynamics instead of to the full recorded neuronal population. A latent state-space model (SSM) approach is used to estimate the low-dimensional neural dynamics from the measured spiking activity in population...
In our previous work, we have investigated the classification of odorants based on their chemical classes only, e.g. Alcohol, Terpene or Ester, using Artificial Neural Networks (ANN) as the signal processing backend of an insect olfactory electronic nose, or e-nose. However, potential applications of e-noses in the food and beverage industry which include the assessment of a fruit's ripeness, quality...
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