#computationalneuroscience — Public Fediverse posts

Spiking neural network people - this year's SNUFA workshop is live!

Talks by:
⭐ Eugene Izhikevich
⭐ Giulia D'Angelo
⭐ Mihai Petrovici
⭐ Susanne Schreiber

Submit your abstracts by Sept 25th. Registration is open!

More info at: https://snufa.net/2026/

cc @fzenke

#SpikingNeuralNetworks #ComputationalNeuroscience #Neuroscience

Spiking neural network people - this year's SNUFA workshop is live!

Talks by:
⭐ Eugene Izhikevich
⭐ Giulia D'Angelo
⭐ Mihai Petrovici
⭐ Susanne Schreiber

Submit your abstracts by Sept 25th. Registration is open!

More info at: https://snufa.net/2026/

cc @fzenke

#SpikingNeuralNetworks #ComputationalNeuroscience #Neuroscience

Spiking neural network people - this year's SNUFA workshop is live!

Talks by:
⭐ Eugene Izhikevich
⭐ Giulia D'Angelo
⭐ Mihai Petrovici
⭐ Susanne Schreiber

Submit your abstracts by Sept 25th. Registration is open!

More info at: https://snufa.net/2026/

cc @fzenke

#SpikingNeuralNetworks #ComputationalNeuroscience #Neuroscience

Spiking neural network people - this year's SNUFA workshop is live!

Talks by:
⭐ Eugene Izhikevich
⭐ Giulia D'Angelo
⭐ Mihai Petrovici
⭐ Susanne Schreiber

Submit your abstracts by Sept 25th. Registration is open!

More info at: https://snufa.net/2026/

cc @fzenke

#SpikingNeuralNetworks #ComputationalNeuroscience #Neuroscience

Spiking neural network people - this year's SNUFA workshop is live!

Talks by:
⭐ Eugene Izhikevich
⭐ Giulia D'Angelo
⭐ Mihai Petrovici
⭐ Susanne Schreiber

Submit your abstracts by Sept 25th. Registration is open!

More info at: https://snufa.net/2026/

cc @fzenke

#SpikingNeuralNetworks #ComputationalNeuroscience #Neuroscience

📚 📈#Worte entwickeln sich weiter: Warum #Sprache, #Meme und #Gehirne der #Logik der #Evolution folgen 🧬🧠

📽 https://youtu.be/M2qiVz95ZYk

📎 https://philosophies.de/index.php/2023/12/25/naturalistic-view/

#DanielDennett #PhilosophieDesGeistes #Kognitionswissenschaft #Memetik #KulturelleEvolution #Evolutionstheorie #Bewusstsein #KünstlicheIntelligenz #AGI #Neurowissenschaft #ComputationalNeuroscience #Zoomposium #SelbstUndIdentität #GeistUndGehirn #Naturalismus #Funktionalismus #Embodiment #Informationstheorie #Wissenschaftskommunikation

Spike-timing-dependent #plasticity (#STDP) is a core rule in #ComputationalNeuroscience that adjusts #synaptic strength based on precise pre- vs. postsynaptic #spike timing, enabling #TemporalCoding and #learning in #SNN. In this post, I summarize its mathematical formulation, functional consequences for learning and #memory along with a simple #Python example:

🌍 https://www.fabriziomusacchio.com/blog/2026-02-12-stdp/

#CompNeuro #Neuroscience #SNN #NeuralDynamics #NeuralPlasticity

Spike-timing-dependent #plasticity (#STDP) is a core rule in #ComputationalNeuroscience that adjusts #synaptic strength based on precise pre- vs. postsynaptic #spike timing, enabling #TemporalCoding and #learning in #SNN. In this post, I summarize its mathematical formulation, functional consequences for learning and #memory along with a simple #Python example:

🌍 https://www.fabriziomusacchio.com/blog/2026-02-12-stdp/

#CompNeuro #Neuroscience #SNN #NeuralDynamics #NeuralPlasticity

Spike-timing-dependent #plasticity (#STDP) is a core rule in #ComputationalNeuroscience that adjusts #synaptic strength based on precise pre- vs. postsynaptic #spike timing, enabling #TemporalCoding and #learning in #SNN. In this post, I summarize its mathematical formulation, functional consequences for learning and #memory along with a simple #Python example:

🌍 https://www.fabriziomusacchio.com/blog/2026-02-12-stdp/

#CompNeuro #Neuroscience #SNN #NeuralDynamics #NeuralPlasticity

Spike-timing-dependent #plasticity (#STDP) is a core rule in #ComputationalNeuroscience that adjusts #synaptic strength based on precise pre- vs. postsynaptic #spike timing, enabling #TemporalCoding and #learning in #SNN. In this post, I summarize its mathematical formulation, functional consequences for learning and #memory along with a simple #Python example:

🌍 https://www.fabriziomusacchio.com/blog/2026-02-12-stdp/

#CompNeuro #Neuroscience #SNN #NeuralDynamics #NeuralPlasticity

Spike-timing-dependent #plasticity (#STDP) is a core rule in #ComputationalNeuroscience that adjusts #synaptic strength based on precise pre- vs. postsynaptic #spike timing, enabling #TemporalCoding and #learning in #SNN. In this post, I summarize its mathematical formulation, functional consequences for learning and #memory along with a simple #Python example:

🌍 https://www.fabriziomusacchio.com/blog/2026-02-12-stdp/

#CompNeuro #Neuroscience #SNN #NeuralDynamics #NeuralPlasticity

#NeuralPlasticity & #learning are distinct but interrelated processes. #Plasticity denotes biological change in #NeuralSystems, while learning is its functional expression in #NetworkDynamics & #behavior. Learning arises from coordinated plastic processes, reshaping #NeuralStateSpace & #attractors to support stable yet flexible representations. Here's a new post on these concepts & their implications for #ComputationalNeuroscience:

🌍https://www.fabriziomusacchio.com/blog/2026-02-02-neural_plasticity_and_learning/

#CompNeuro #Neuroscience

#NeuralPlasticity & #learning are distinct but interrelated processes. #Plasticity denotes biological change in #NeuralSystems, while learning is its functional expression in #NetworkDynamics & #behavior. Learning arises from coordinated plastic processes, reshaping #NeuralStateSpace & #attractors to support stable yet flexible representations. Here's a new post on these concepts & their implications for #ComputationalNeuroscience:

🌍https://www.fabriziomusacchio.com/blog/2026-02-02-neural_plasticity_and_learning/

#CompNeuro #Neuroscience

#NeuralPlasticity & #learning are distinct but interrelated processes. #Plasticity denotes biological change in #NeuralSystems, while learning is its functional expression in #NetworkDynamics & #behavior. Learning arises from coordinated plastic processes, reshaping #NeuralStateSpace & #attractors to support stable yet flexible representations. Here's a new post on these concepts & their implications for #ComputationalNeuroscience:

🌍https://www.fabriziomusacchio.com/blog/2026-02-02-neural_plasticity_and_learning/

#CompNeuro #Neuroscience

#NeuralPlasticity & #learning are distinct but interrelated processes. #Plasticity denotes biological change in #NeuralSystems, while learning is its functional expression in #NetworkDynamics & #behavior. Learning arises from coordinated plastic processes, reshaping #NeuralStateSpace & #attractors to support stable yet flexible representations. Here's a new post on these concepts & their implications for #ComputationalNeuroscience:

🌍https://www.fabriziomusacchio.com/blog/2026-02-02-neural_plasticity_and_learning/

#CompNeuro #Neuroscience

#NeuralPlasticity & #learning are distinct but interrelated processes. #Plasticity denotes biological change in #NeuralSystems, while learning is its functional expression in #NetworkDynamics & #behavior. Learning arises from coordinated plastic processes, reshaping #NeuralStateSpace & #attractors to support stable yet flexible representations. Here's a new post on these concepts & their implications for #ComputationalNeuroscience:

🌍https://www.fabriziomusacchio.com/blog/2026-02-02-neural_plasticity_and_learning/

#CompNeuro #Neuroscience

Reminder if you missed #SNUFA spiking neural network and neuromorphic workshop earlier this month, all our talks were recorded and are now available to watch.

https://www.youtube.com/playlist?list=PL09WqqDbQWHEyTZPLMKEi9-RD6kax0tCR

#Neuroscience #ComputationalNeuroscience #SpikingNeuralNetworks

Talks from #SNUFA 2025 are now available on YouTube:

https://youtube.com/playlist?list=PL09WqqDbQWHEyTZPLMKEi9-RD6kax0tCR&si=Y-sJeZvIn3O062DG

#neuroscience #ComputationalNeuroscience #SpikingNeuralNetworks

Spiking NN fans - the #SNUFA workshop (Nov 5-6) agenda is finalised and online now. Make sure to register (free) soon. (Note you can register for either day and come to both.)

Agenda: https://snufa.net/2025/
Registration: https://www.eventbrite.co.uk/e/snufa-2025-tickets-1549418545579

Thanks to all who voted on abstracts!

#Neuroscience #ComputationalNeuroscience #SpikingNeuralNetworks

Message for participants of the #SNUFA 2025 spiking neural network workshop. We got almost 60 awesome abstract submissions, and we'd now like your help to select which ones should be offered talks. To take part, follow the "abstract voting" link at:

https://snufa.net/2025/

It should take <15m. Thanks! ❤️

#neuroscience #SpikingNeuralNetworks #ComputationalNeuroscience

New preprint available!

Henri S. Chastain, A. D. Redish (2025). Multiple Decision-Making
Systems and the Common Currency Hypothesis. psyArxiv.
https://osf.io/preprints/psyarxiv/75k6d_v1

In this just-released new preprint, we analyze the consequences of taking both the #neuroeconomic theory of "Common Currency" and the #DecisionMaking theory of "Multiple decision systems" seriously from a #computationalNeuroscience perspective and find that these theories interact and lead to a fascinating set of testable predictions.

#psyarxiv #neuroecononomics #neuroscience #DecisionMaking

In the same vein as my #arxivfeed thing, here's a paper that I've been reading and really enjoying. I decided to spend more time on it than I usually do when reading papers because I wanted to search for gaps in my knowledge, and I really don't regret that decision! I'm only at the 4th section at the moment and I find it very well written, especially in the framing of things. So far it's a great overview!

"Neural Field Models: A mathematical overview and unifying framework"
https://arxiv.org/abs/2103.10554v4

#Neuroscience #ComputationalNeuroscience #MathematicalNeuroscience #NeuralFieldModelling #Biophysical #DynamicalSystems

#arxivfeed

"JGAT: a joint spatio-temporal graph attention model for brain decoding"
https://arxiv.org/abs/2306.05286

#Neuroscience #Neuroimaging #ComputationalNeuroscience #Connectivity #MachineLearning #ML

#arxivfeed

"Learning low-dimensional dynamics from whole-brain data improves task capture"
https://arxiv.org/abs/2305.14369

#Neuroscience #ComputationalNeuroscience #MachineLearning #Neuroimaging #NeuralODE #DynamicalSystems #Cognition

After a long break, new #arxivfeed

"Generalized Bayesian Inference for Scientific Simulators via Amortized Cost Estimation"
https://arxiv.org/abs/2305.15208

#BayesianInference #MachineLearning #Modelling #SBI #ComputationalNeuroscience

#arxivfeed

"Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias"
https://www.biorxiv.org/content/10.1101/2023.03.10.532087v1

#Neuroscience #ComputationalNeuroscience #DynamicalModels #DynamicalSystems #Neuroimaging #neurodegeneration #TheVirtualBrain

#Arxivfeed :

"Simulation-based inference for efficient identification of generative models in connectomics"
https://www.biorxiv.org/content/10.1101/2023.01.31.526269v1

#Neuroscience #ComputationalNeuroscience #MachineLearning #SimulationBasedInference #Inference #Connectome #Connectivity

#arxivfeed :

"Neurophysiological signatures of cortical micro-architecture"
https://www.biorxiv.org/content/10.1101/2023.01.23.525101v1

#Neuroscience #Neuro #ComputationalNeuroscience #Multimodal #Neuroimaging #Neurophysiology

Wonderful work!

#arxivfeed :

"Mesoscopic modeling of hidden spiking neurons"
https://arxiv.org/abs/2205.13493

#Neuroscience #Neuro #ComputationalNeuroscience #MachineLearning #SpikingNeuralNetworks

#arxivfeed :

"Emergence of brain-like mirror-symmetric viewpoint tuning in convolutional neural networks"
https://www.biorxiv.org/content/10.1101/2023.01.05.522909v1

#Neuroscience #Neuro #ComputationalNeuroscience #Vision #MachineLearning #DeepLearning #ConvolutionalNeuralNetworks

#arxivfeed :

"CI-GNN: A Granger Causality-Inspired Graph Neural Network for Interpretable Brain Network-Based Psychiatric Diagnosis"
https://arxiv.org/abs/2301.01642

#Neuroscience #Neuro #ComputationalNeuroscience #MachineLearning #GraphNeuralNetworks #Psychiatry #FunctionalConnectivity #CausalInference

#arxivfeed :

"Inhibition stabilization and paradoxical effects in recurrent neural networks with short-term plasticity"
https://www.biorxiv.org/content/10.1101/2022.12.19.520986v1

#Neuroscience #Neuro #Brain #ComputationalNeuroscience #DynamicalSystems #Plasticity

#arxivfeed :

"Multi-modal and multi-model interrogation of large-scale functional brain networks"
https://www.biorxiv.org/content/10.1101/2022.12.19.520967v1

#Neuroscience #Neuro #Brain #Neuroimaging #fMRI #MEG #ComputationalNeuroscience #DynamicalSystems #WholeBrainModel #Connectivity