Directed and acyclic synaptic connectivity in the human layer 2-3 cortical microcircuit
Y Peng, A Bjelde, PV Aceituno, FX Mittermaier… - Science, 2024 - science.org
The computational capabilities of neuronal networks are fundamentally constrained by their
specific connectivity. Previous studies of cortical connectivity have mostly been carried out in …
specific connectivity. Previous studies of cortical connectivity have mostly been carried out in …
Theoretical principles explain the structure of the insect head direction circuit
PV Aceituno, D Dall'Osto, I Pisokas - Elife, 2024 - elifesciences.org
To navigate their environment, insects need to keep track of their orientation. Previous work
has shown that insects encode their head direction as a sinusoidal activity pattern around a …
has shown that insects encode their head direction as a sinusoidal activity pattern around a …
Approximating nonlinear functions with latent boundaries in low-rank excitatory-inhibitory spiking networks
WF Podlaski, CK Machens - Neural Computation, 2024 - direct.mit.edu
Deep feedforward and recurrent neural networks have become successful functional models
of the brain, but they neglect obvious biological details such as spikes and Dale's law. Here …
of the brain, but they neglect obvious biological details such as spikes and Dale's law. Here …
Exploring neural oscillations during speech perception via surrogate gradient spiking neural networks
Understanding cognitive processes in the brain demands sophisticated models capable of
replicating neural dynamics at large scales. We present a physiologically inspired speech …
replicating neural dynamics at large scales. We present a physiologically inspired speech …
Enhancing learning in spiking neural networks through neuronal heterogeneity and neuromodulatory signaling
A Rodriguez-Garcia, J Mei, S Ramaswamy - arXiv preprint arXiv …, 2024 - arxiv.org
Recent progress in artificial intelligence (AI) has been driven by insights from neuroscience,
particularly with the development of artificial neural networks (ANNs). This has significantly …
particularly with the development of artificial neural networks (ANNs). This has significantly …
Learning of state representation in recurrent network: the power of random feedback and biological constraints
How external/internal 'state'is represented in the brain is crucial, since appropriate
representation enables goal-directed behavior. Recent studies suggest that state …
representation enables goal-directed behavior. Recent studies suggest that state …
The insect compass system: from theory to circuitry
PV Aceituno, D Dall'Osto, I Pisokas - bioRxiv, 2023 - biorxiv.org
To navigate their environment, insects need to keep track of their orientation. Previous work
has shown that insects encode their head direction as a sinusoidal activity pattern around a …
has shown that insects encode their head direction as a sinusoidal activity pattern around a …
Relationship between behavioral output and internal dynamics in biological and recurrent neural networks
A Rabus - 2024 - prism.ucalgary.ca
An organism controls its state in the environment through behavior; behavior, in turn,
influences neuronal dynamics through feedback to the brain. Despite this apparent …
influences neuronal dynamics through feedback to the brain. Despite this apparent …
[PDF][PDF] Reinforcement learning of state representation and value: the power of random feedback and
T Tsurumi, A Kato, A Kumar, K Morita - Nat Neurosci, 2013 - biorxiv.org
How external/internal 'state'is represented in the brain is crucial, since appropriate
representation enables goal-directed behavior. Recent studies suggest that state …
representation enables goal-directed behavior. Recent studies suggest that state …