All Stories

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