Bareesh Bhaduri
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View article: Reducing power requirements for high-accuracy decoding in iBCIs
Reducing power requirements for high-accuracy decoding in iBCIs Open
Objective. Current intracortical brain-computer interfaces (iBCIs) rely predominantly on threshold crossings (‘spikes’) for decoding neural activity into a control signal for an external device. Spiking data can yield high accuracy online …
View article: BRAND: a platform for closed-loop experiments with deep network models
BRAND: a platform for closed-loop experiments with deep network models Open
Objective. Artificial neural networks (ANNs) are state-of-the-art tools for modeling and decoding neural activity, but deploying them in closed-loop experiments with tight timing constraints is challenging due to their limited support in e…
View article: BRAND: A platform for closed-loop experiments with deep network models
BRAND: A platform for closed-loop experiments with deep network models Open
This is the supporting data for "BRAND: A platform for closed-loop experiments with deep network models". It can be analyzed using the code at github.com/brandbci/paper-figures. This dataset contains: Latency measurements from computers ru…
View article: BRAND: A platform for closed-loop experiments with deep network models
BRAND: A platform for closed-loop experiments with deep network models Open
This is the supporting data for "BRAND: A platform for closed-loop experiments with deep network models". It can be analyzed using the code at github.com/brandbci/paper-figures. This dataset contains: Latency measurements from computers ru…
View article: BRAND: A platform for closed-loop experiments with deep network models
BRAND: A platform for closed-loop experiments with deep network models Open
Artificial neural networks (ANNs) are state-of-the-art tools for modeling and decoding neural activity, but deploying them in closed-loop experiments with tight timing constraints is challenging due to their limited support in existing rea…