All Stories

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