All Stories

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