Hamker lab of computational neuroscience and AI

Burkhardt2023_SpatialCognition

Contains the code for simulation and analysis of the Spatial Cognition model.

Baladron2023-MotorLearning-BG-Cereb

ML-Karoprod-MeshPredictor

Mesh regression library of the ML@Karoprod BMBF project

Larisch2023_EventBasedSNN

Python code for to train a spiking neural network on N-MNIST and evaluate it on different corruption types.

Maith2021_ANNarchyBOLDmonitor

Source code of simulations and analyses from Maith, O., Dinkelbach, H. Ü., Baladron, J., Vitay, J., & Hamker, F. H. (2022). BOLD Monitoring in the Neural Simulator ANNarchy. Frontiers in Neuroinformatics.

Maith2022_ExplorationSTNGPe

Source code of simulations and analyses from Maith, O., Baladron, J., Einhäuser, W., & Hamker, F. H. (2022). Exploration behavior after reversals is predicted by STN-GPe synaptic plasticity in a basal ganglia model. Submitted to iScience.

Neurorobotics_SummerSchool2022

Repository for neurorobotics summer school 2022

.github

README for hamkerlab

Goenner2017-PredictivePlaceCells

Lorenz Gönner, Julien Vitay, and Fred H. Hamker (2017). Predictive Place-Cell Sequences for Goal-Finding Emerge from Goal Memory and the Cognitive Map: A Computational Model.

Goenner2020-Stopsignaltask_BG

Package with main scripts of the Basal Ganglia model for Stop Signal Task simulations from Goenner, Maith, Koulouri, Baladron & Hamker (2020).

Larisch2023_Detecting_Anomalies

Github repository to the manuscript: Detecting anomalies in system logs with compact convolutional transformer

Maith2024_DBS_Habit

Source code of simulations and analyses from Maith, O., Apenburg, D., & Hamker, F. H. (2024). Pallidal deep brain stimulation enhances habitual behavior in a neuro-computational basal ganglia model during a reward reversal learning task. Submitted to European Journal of Neuroscience.

neurorobotik-reservoir

Lecture on Reservoir Computing for the Neurorobotik course.

Schmid2019-CerebellumForwardModel

Teichmann2021_NeuralNetworks

Repository for the publication: Teichmann, M., Larisch, R., & Hamker, F. H. (2021). Performance of biologically grounded models of the early visual system on standard object recognition tasks. Neural Networks, 144, 210–228. https://doi.org/10.1016/j.neunet.2021.08.009

Vitay2014-TimingReward

Model for Vitay and Hamker (2014). Timing and expectation of reward: a neuro-computational model of the afferents to the ventral tegmental area. Frontiers in Neurorobotics 8(4)

Dinkelbach2022_ANNarchyAutoTuning

Source code of simulations and analyses from Dinkelbach, Bouhlal, Vitay & Hamker (2022) Auto-Selection of an Optimal Sparse Matrix Format in the Neuro-Simulator ANNarchy.

Dinkelback2019-ANNarchyBenchmark-CCN

Code repository for the benchmarks of the article.

Fietzek2024_Reaching_Adaptation_iCub

Code for the Conference Paper will be added soon

hamkerlab.github.io

Website for the lab of AI - TUC

Larisch2021_PLOSComBio

Repository for the publication: Larisch, R., Gönner, L., Teichmann, M. & Hamker, F. H. (2021). Sensory coding and contrast invariance emerge from the control of plastic inhibition over emergent selectivity

Maith2021-CognitiveLearningAgent

Source code of the cognitive learning agent for emergent attention from basal ganglia onto the visual system from Maith, Schwarz & Hamker (2021).