The inherently constrained regenerative capacity of neuronal tissue poses a major obstacle to repairing traumatic brain injury. While neural stem cell transplantation holds promise, its efficacy is constrained by slow and inefficient neuronal differe...
Advanced large-scale neural interfaces call for efficient algorithms to automatically process and optimally exploit the richness of their heavy continuous flow of data. In this context, we introduce here a very frugal generic single-layer Spiking Neu...
Continuous bump attractor networks (CBANs) are a prevailing model for how neural circuits represent continuous variables. CBANs maintain these representations by temporally integrating inputs that encode differential (i.e., incremental) changes to a ...
Spike sorting, which involves detecting and attributing spikes to their putative neurons from extracellular recordings, is a common process in electrophysiology and brain-computer interface systems. Recent advances in large-scale neural recording tec...
Correlative imaging is a powerful analytical approach in bioimaging, as it offers complementary information on the samples measured by different modalities. Particularly, correlative transmission electron microscopy (EM) and nanoscale secondary ion m...
Computational models of neural processing in the auditory cortex usually ignore that neurons have an internal memory: they characterize their responses from simple convolutions with a finite temporal window. To circumvent this limitation, we propose ...
The Journal of neuroscience : the official journal of the Society for Neuroscience
Oct 8, 2025
Early structural and molecular development of the human cortex is extensively studied, but little is known about the development of neuronal activity across cortical regions. We used dense array electroencephalography recordings and a machine learnin...
The Journal of neuroscience : the official journal of the Society for Neuroscience
Oct 8, 2025
The integration of multiple sensory inputs is essential for human perception and action in uncertain environments. This process includes reference frame transformations as different sensory signals are encoded in different coordinate systems. Studies...
Current machine learning systems consume vastly more energy than biological brains. Neuromorphic systems aim to overcome this difference by mimicking the brain's information coding via discrete voltage spikes. However, it remains unclear how both art...
In this work, a supervised learning rule based on Temporal Single Spike Coding for Effective Transfer Learning (TS4TL) is presented, an efficient approach for training multilayer fully connected Spiking Neural Networks (SNNs) as classifier blocks wit...
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