All Stories

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