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We investigate the extent to which Spiking Neural Networks (SNNs) trained with Surrogate Gradient Descent (Surrogate GD), with and without delay learning, can learn from precise spike timing beyond fi...

Nature Communications - Temporal coding in the hippocampus is thought to be key for memory and predictions. Here, the authors show that blocking one entorhinal input affects two aspects of...

Studies in neuroscience have shown that biological synapses follow a log-normal distribution whose transitioning can be explained by noisy multiplicative dynamics. Biological networks can function sta...

NWO has made 25 million euros available to facilitate the transition of top international researchers to the Netherlands. Later this summer, the call for proposals for the Tulip Fund, as the new fund will be called, will open. The fund will enable renowned international scientists from outside the EU to continue their research at a Dutch research institution. Knowledge institutions can nominate top researchers or talents who wish to continue their work here in the Netherlands due to the growing threats to academic freedom to be considered for funding.

Computation in recurrent networks of neurons has been hypothesized to occur at the level of low-dimensional latent dynamics, both in artificial systems and in the brain. This hypothesis seems at odds ...

Andres Canales-Johnson research group

Recurrent neural networks (RNNs) trained on neuroscience-inspired tasks offer powerful models of brain computation. However, typical training paradigms rely on open-loop, supervised settings, whereas ...

Theories of predictive processing propose that sensory systems constantly predict incoming signals, based on spatial and temporal context. However, evidence for prediction in sensory cortex largely co...

The cerebral cortex, from sensory to higher cognitive areas, is hierarchically organised Several dynamical and anatomical measures, such as timescales and neurotransmitter receptor expression, have in...