All Stories

  1. Efficient event-based delay learning in spiking neural networks
  2. Building on models—a perspective for computational neuroscience
  3. Bio-inspired event-based looming object detection for automotive collision avoidance
  4. Understanding the mechanism of facilitation in hoverfly TSDNs
  5. Introduction to the proceedings of the CNS*2024 meeting
  6. How the quality of an answer is measured is important for efficient learning
  7. EvDownsampling: A Robust Method for Downsampling Event Camera Data
  8. Adaptive Route Memory Sequences for Insect-Inspired Visual Route Navigation
  9. Efficient Visual Navigation with Bio-inspired Route Learning Algorithms
  10. Estimating orientation in natural scenes: A spiking neural network model of the insect central complex
  11. Learning efficient backprojections across cortical hierarchies in real time
  12. Estimating orientation in Natural scenes: A Spiking Neural Network Model of the Insect Central Complex
  13. Descending neurons of the hoverfly respond to pursuits of artificial targets
  14. Insect-inspired Spatio-temporal Downsampling of Event-based Input
  15. Familiarity-taxis: A bilateral approach to view-based navigation
  16. Neural responses to reconstructed target pursuits
  17. Easy and efficient spike-based Machine Learning with mlGeNN
  18. Production of adaptive movement patterns via an insect inspired Spiking Neural Network Central Pattern Generator
  19. Event-based dataset for classification and pose estimation
  20. Efficient GPU training of LSNNs using eProp
  21. mlGeNN: accelerating SNN inference using GPU-enabled neural networks
  22. Non-synaptic interactions between olfactory receptor neurons, a possible key feature of odor processing in flies
  23. Geosmin suppresses defensive behaviour and elicits unusual neural responses in honey bees
  24. Learning with reinforcement prediction errors in a model of the Drosophila mushroom body
  25. Larger GPU-accelerated brain simulations with procedural connectivity
  26. Dynamics of a Mutual Inhibition Circuit between Pyramidal Neurons Compared to Human Perceptual Competition
  27. Non-synaptic interactions between olfactory receptor neurons, a possible key feature of odor processing in flies
  28. Dynamics of a mutual inhibition between pyramidal neurons compared to human perceptual competition
  29. Larger GPU-accelerated brain simulations with procedural connectivity
  30. Brian2GeNN: accelerating spiking neural network simulations with graphics hardware
  31. Exploring the robustness of insect-inspired visual navigation for flying robots
  32. Can Small Scale Search Behaviours Enhance Large-Scale Navigation?
  33. Insect Inspired View Based Navigation Exploiting Temporal Information
  34. Snapshot Navigation in the Wavelet Domain
  35. Odor Stimuli: Not Just Chemical Identity
  36. The Emergence of a Stable Neuronal Ensemble from a Wider Pool of Activated Neurons in the Dorsal Medial Prefrontal Cortex during Appetitive Learning in Mice
  37. An unsupervised neuromorphic clustering algorithm
  38. Correction to: Computing reward prediction errors and learning valence in the insect mushroom body
  39. Our GPU based simulator framework is faster than previous solutions
  40. The sense of smell appears to work better with mixtures of odourants than with single chemicals
  41. Brian2GeNN: a system for accelerating a large variety of spiking neural networks with graphics hardware
  42. An inexpensive flying robot design for embodied robotics research
  43. A Biophysical Model of the Early Olfactory System of Honeybees
  44. Olfactory experience shapes the evaluation of odour similarity in ants: a behavioural and computational analysis
  45. Artificial neural network approaches for fluorescence lifetime imaging techniques
  46. Burst Firing Enhances Neural Output Correlation
  47. Classifying continuous, real-time e-nose sensor data using a bio-inspired spiking network modelled on the insect olfactory system
  48. Comparing Neuromorphic Solutions in Action: Implementing a Bio-Inspired Solution to a Benchmark Classification Task on Three Parallel-Computing Platforms
  49. GeNN: a code generation framework for accelerated brain simulations
  50. GPU acceleration of time-domain fluorescence lifetime imaging
  51. Easy-to-use GPU acceleration of neural network simulations with GeNN
  52. Simulating a biologically accurate model of the honeybee olfactory system on the GPU
  53. Input-Modulation as an Alternative to Conventional Learning Strategies
  54. Voltage Clamp Technique
  55. Patch Clamp Technique
  56. Dynamic Clamp Technique
  57. Gap Junctions in Small Networks
  58. Dynamic Clamp
  59. Testing fruit fly olfactory receptors for technical applications
  60. Challenges of Correct Validation
  61. Classifying chemical sensor data using GPU-accelerated bio-mimetic neuronal networks based on the insect olfactory system
  62. SpineML and Brian 2.0 interfaces for using GPU enhanced Neuronal Networks (GeNN)
  63. Simulating spiking neural networks on massively parallel graphical processing units using a code generation approach with GeNN
  64. Influence of Wiring Cost on the Large-Scale Architecture of Human Cortical Connectivity
  65. Stimulus-onset asynchrony can aid odor segregation
  66. Feature selection in Enose applications
  67. A modelling framework for the olfactory system of the honeybee using GeNN (GPU enhanced Neuronal Network simulation environment)
  68. Feature Selection for Chemical Sensor Arrays Using Mutual Information
  69. Erratum to “Optimal feature selection for classifying a large set of chemicals using metal oxide sensors” [Sens. Actuators B Chem. 187 (2013) 471–480]
  70. Voltage-Clamp Technique
  71. Patch Clamp Technique
  72. Gap Junctions in Small Networks
  73. Dynamic Clamp Technique
  74. Machine Learning for Automatic Prediction of the Quality of Electrophysiological Recordings
  75. Data-driven honeybee antennal lobe model suggests how stimulus-onset asynchrony can aid odour segregation
  76. Optimal feature selection for classifying a large set of chemicals using metal oxide sensors
  77. Gain Control Network Conditions in Early Sensory Coding
  78. A numerical renormalisation group method for the analysis of critical spreading activity in spiking neural networks
  79. The Green Brain Project – Developing a Neuromimetic Robotic Honeybee
  80. Bioinspired solutions to the challenges of chemical sensing
  81. Correction: Probing the Dynamics of Identified Neurons with a Data-Driven Modeling Approach
  82. Single electrode dynamic clamp with StdpC
  83. Inhibition in Multiclass Classification
  84. Multi-Neuronal Refractory Period Adapts Centrally Generated Behaviour to Reward
  85. Benchmarking Drosophilareceptor neurons for technical applications
  86. On the equivalence of Hebbian learning and the SVM formalism
  87. Transient dynamics between displaced fixed points: An alternate nonlinear dynamical framework for olfaction
  88. Modelling the signal delivered by a population of first-order neurons in a moth olfactory system
  89. Dynamic Clamp
  90. Bio-inspired solutions to the challenges of chemical sensing
  91. Interaction of cellular and network mechanisms for efficient pheromone coding in moths
  92. Transient dynamics between displaced fixed points: an alternate nonlinear dynamical framework for olfaction
  93. The effect of intrinsic subthreshold oscillations on the spontaneous dynamics of a ring network with distance-dependent delays
  94. Flexible neuronal network simulation framework using code generation for NVidia® CUDA™
  95. Dynamic observer: ion channel measurement beyond voltage clamp
  96. Coarse-grained statistics for attributing criticality to heterogeneous neural networks
  97. Multiscale Model of an Inhibitory Network Shows Optimal Properties near Bifurcation
  98. Normalization for Sparse Encoding of Odors by a Wide-Field Interneuron
  99. Dynamic clamp with StdpC software
  100. Competition-Based Model of Pheromone Component Ratio Detection in the Moth
  101. Pacemaker and Network Mechanisms of Neural Rhythm Generation
  102. Criteria for robustness of heteroclinic cycles in neural microcircuits
  103. Consistency and Diversity of Spike Dynamics in the Neurons of Bed Nucleus of Stria Terminalis of the Rat: A Dynamic Clamp Study
  104. Parallel implementation of a spiking neuronal network model of unsupervised olfactory learning on NVidia® CUDA™
  105. A new notion of criticality: Studies in the pheromone system of the moth
  106. Erratum (“Fast and Robust Learning by Reinforcement Signals: Explorations in the Insect Brain” by Ramón Huerta and Thomas Nowotny, Neural Computation, August 2009, Vol. 21, No. 8: 2123–2151)
  107. Fast and Robust Learning by Reinforcement Signals: Explorations in the Insect Brain
  108. Moving beyond convergence in the pheromone system of the moth
  109. Divergence alone cannot guarantee stable sparse activity patterns if connections are dense
  110. Homeostasis versus neuronal variability: Models and experiments in crustaceans
  111. “Sloppy Engineering” and the Olfactory System of Insects
  112. A neuronal network model for the detection of binary odor mixtures
  113. Neuronal synchrony: Peculiarity and generality
  114. Erratum: Dynamical Origin of Independent Spiking and Bursting Activity in Neural Microcircuits [Phys. Rev. Lett. 98 , 128106 (2007)]
  115. Pacemaker and network mechanisms of rhythm generation: Cooperation and competition
  116. Probing the Dynamics of Identified Neurons with a Data-Driven Modeling Approach
  117. Models Wagging the Dog: Are Circuits Constructed with Disparate Parameters?
  118. Dynamical Origin of Independent Spiking and Bursting Activity in Neural Microcircuits
  119. StdpC: A modern dynamic clamp
  120. Spike-Timing-Dependent Plasticity of Inhibitory Synapses in the Entorhinal Cortex
  121. Self-organization in the olfactory system: one shot odor recognition in insects
  122. Learning Classification in the Olfactory System of Insects
  123. Explaining synchrony in feed-forward networks:
  124. Explaining synchrony in feed-forward networks:
  125. Spatial representation of temporal information through spike-timing-dependent plasticity
  126. Phase diagram of the random field Ising model on the Bethe lattice
  127. Convolution of multifractals and the local magnetization in a random-field Ising chain
  128. Orbits and phase transitions in the multifractal spectrum
  129. Pregeometric concepts on graphs and cellular networks as possible models of space-time at the Planck-scale
  130. Defining the concept of a dimension for a network