Do you want to work as a Postdoc Position: Neural Circuitry Underlying Working Memory at the Faculty of Social Sciences? Check our vacancy!

The structure of brain connectivity predicts collective neural activity, with a small number of connectivity features determining activity dimensionality, linking circuit architecture to network-level...

Bifurcations—an underexplored concept in neuroscience—can help explain how small differences in neural circuits give rise to entirely novel functions.

Classic theoretical models of cortical oscillations are based on the interactions between two populations of excitatory and inhibitory neurons. Nevertheless, experimental studies and network simulatio...

Do you want to work as a PhD candidate Theory of Learning in Artificial and Biologically Inspired Neural Network? Check our vacancy!

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...