Wulfram Gerstner
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Why Is Wulfram Gerstner Influential?
(Suggest an Edit or Addition)According to Wikipedia, Wulfram Gerstner is a German and Swiss computational neuroscientist. His research focuses on neural spiking patterns in neural networks, and their connection to learning, spatial representation and navigation. Since 2006 Gerstner has been a full professor of Computer Science and Life Sciences at École Polytechnique Fédérale de Lausanne , where he also serves as a Director of the Laboratory of Computational Neuroscience.
Wulfram Gerstner's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Spiking Neuron Models: Single Neurons, Populations, Plasticity (2002) (2813)
- Spiking Neuron Models (2002) (1573)
- A neuronal learning rule for sub-millisecond temporal coding (1996) (1135)
- Adaptive exponential integrate-and-fire model as an effective description of neuronal activity. (2005) (1034)
- Neuronal Dynamics: From Single Neurons To Networks And Models Of Cognition (2014) (878)
- Noninvasive brain-actuated control of a mobile robot by human EEG (2004) (725)
- Hebbian learning and spiking neurons (1999) (687)
- Connectivity reflects coding: a model of voltage-based STDP with homeostasis (2010) (571)
- Triplets of Spikes in a Model of Spike Timing-Dependent Plasticity (2006) (569)
- Inhibitory Plasticity Balances Excitation and Inhibition in Sensory Pathways and Memory Networks (2011) (562)
- Phenomenological models of synaptic plasticity based on spike timing (2008) (556)
- Spiking Neuron Models: An Introduction (2002) (546)
- Population Dynamics of Spiking Neurons: Fast Transients, Asynchronous States, and Locking (2000) (442)
- Mathematical formulations of Hebbian learning (2002) (381)
- Reduction of the Hodgkin-Huxley Equations to a Single-Variable Threshold Model (1997) (343)
- Spike-Timing-Dependent Plasticity (2010) (306)
- A History of Spike-Timing-Dependent Plasticity (2011) (297)
- Spatial cognition and neuro-mimetic navigation: a model of hippocampal place cell activity (2000) (291)
- Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning Rules (2016) (288)
- Generalized integrate-and-fire models of neuronal activity approximate spike trains of a detailed model to a high degree of accuracy. (2004) (286)
- Firing patterns in the adaptive exponential integrate-and-fire model (2008) (285)
- Spike-Timing-Dependent Plasticity: A Comprehensive Overview (2012) (284)
- Optimal Spike-Timing-Dependent Plasticity for Precise Action Potential Firing in Supervised Learning (2005) (268)
- Neural codes: firing rates and beyond. (1997) (263)
- Diverse synaptic plasticity mechanisms orchestrated to form and retrieve memories in spiking neural networks (2015) (262)
- Optimal Control of Transient Dynamics in Balanced Networks Supports Generation of Complex Movements (2014) (250)
- How Good Are Neuron Models? (2009) (247)
- What Matters in Neuronal Locking? (1996) (247)
- Associative memory in a network of ‘spiking’ neurons (1992) (229)
- Predicting spike timing of neocortical pyramidal neurons by simple threshold models (2006) (222)
- Dynamic I-V curves are reliable predictors of naturalistic pyramidal-neuron voltage traces. (2008) (212)
- Why spikes? Hebbian learning and retrieval of time-resolved excitation patterns (1993) (205)
- Intrinsic Stabilization of Output Rates by Spike-Based Hebbian Learning (2001) (201)
- Microcircuits of excitatory and inhibitory neurons in layer 2/3 of mouse barrel cortex. (2012) (200)
- Eligibility Traces and Plasticity on Behavioral Time Scales: Experimental Support of NeoHebbian Three-Factor Learning Rules (2018) (185)
- A benchmark test for a quantitative assessment of simple neuron models (2008) (178)
- Temporal whitening by power-law adaptation in neocortical neurons (2013) (163)
- Brain-actuated interaction (2004) (163)
- Noise in Integrate-and-Fire Neurons: From Stochastic Input to Escape Rates (2000) (161)
- Spiking neurons (1999) (153)
- Integrating Hebbian and homeostatic plasticity: the current state of the field and future research directions (2017) (152)
- Reinforcement Learning Using a Continuous Time Actor-Critic Framework with Spiking Neurons (2013) (152)
- Synaptic Plasticity in Neural Networks Needs Homeostasis with a Fast Rate Detector (2013) (150)
- Theory and Simulation in Neuroscience (2012) (141)
- Functional Requirements for Reward-Modulated Spike-Timing-Dependent Plasticity (2010) (136)
- Tag-Trigger-Consolidation: A Model of Early and Late Long-Term-Potentiation and Depression (2008) (135)
- Generalized Bienenstock-Cooper-Munro rule for spiking neurons that maximizes information transmission. (2005) (133)
- The quantitative single-neuron modeling competition (2008) (130)
- Hebbian plasticity requires compensatory processes on multiple timescales (2017) (130)
- Comparison of face verification results on the XM2VTFS database (2000) (125)
- Is there a geometric module for spatial orientation? Insights from a rodent navigation model. (2009) (124)
- The temporal paradox of Hebbian learning and homeostatic plasticity (2017) (123)
- Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail (2009) (121)
- Noise shaping in populations of coupled model neurons. (1999) (118)
- Towards a theory of cortical columns: From spiking neurons to interacting neural populations of finite size (2016) (117)
- Voltage and Spike Timing Interact in STDP – A Unified Model (2010) (114)
- Cognitive navigation based on nonuniform Gabor space sampling, unsupervised growing networks, and reinforcement learning (2004) (109)
- Extracting Oscillations: Neuronal Coincidence Detection with Noisy Periodic Spike Input (1998) (108)
- Adaptive exponential integrate-and-fire model (2009) (108)
- Artificial Neural Networks — ICANN'97 (1997) (103)
- Extraction of Network Topology From Multi-Electrode Recordings: Is there a Small-World Effect? (2011) (101)
- Synaptic Shot Noise and Conductance Fluctuations Affect the Membrane Voltage with Equal Significance (2005) (99)
- Inference of neuronal network spike dynamics and topology from calcium imaging data (2013) (96)
- Learning Navigational Maps Through Potentiation and Modulation of Hippocampal Place Cells (2004) (91)
- Parameter extraction and classification of three cortical neuron types reveals two distinct adaptation mechanisms. (2012) (90)
- Non-Invasive Brain-Actuated Control of a Mobile Robot (2003) (88)
- Chapter 12 A framework for spiking neuron models: The spike response model (2001) (85)
- Stochastic variational learning in recurrent spiking networks (2014) (81)
- Robust self-localisation and navigation based on hippocampal place cells (2005) (79)
- Stress, genotype and norepinephrine in the prediction of mouse behavior using reinforcement learning (2009) (78)
- Extracting non-linear integrate-and-fire models from experimental data using dynamic I–V curves (2008) (78)
- Biologically plausible deep learning - but how far can we go with shallow networks? (2019) (76)
- Predicting neuronal activity with simple models of the threshold type: Adaptive Exponential Integrate-and-Fire model with two compartments (2007) (75)
- Piecewise linear differential equations and integrate-and-fire neurons: insights from two-dimensional membrane models. (2003) (72)
- 25th Annual Computational Neuroscience Meeting: CNS-2016 (2016) (71)
- Automated High-Throughput Characterization of Single Neurons by Means of Simplified Spiking Models (2015) (70)
- Stable Propagation of Activity Pulses in Populations of Spiking Neurons (2002) (69)
- A biologically motivated and analytically soluble model of collective oscillations in the cortex (1993) (66)
- Limits to high-speed simulations of spiking neural networks using general-purpose computers (2014) (66)
- Optimality Model of Unsupervised Spike-Timing-Dependent Plasticity: Synaptic Memory and Weight Distribution (2007) (65)
- A computational model of parallel navigation systems in rodents (2007) (63)
- Non-normal amplification in random balanced neuronal networks. (2012) (63)
- Hebbian learning of pulse timing in the Barn Owl auditory system (1999) (60)
- Spike-Based Compared to Rate-Based Hebbian Learning (1998) (59)
- Neuronavigation combined with electrophysiological monitoring for surgery of lesions in eloquent brain areas in 42 cases: a retrospective comparison of the neurological outcome and the quality of resection with a control group with similar lesions. (2003) (58)
- Balancing New against Old Information: The Role of Puzzlement Surprise in Learning (2018) (58)
- Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation (2018) (57)
- Intracellular Ca2+ stores can account for the time course of LTP induction: a model of Ca2+ dynamics in dendritic spines. (1995) (57)
- Predicting non-linear dynamics by stable local learning in a recurrent spiking neural network (2017) (56)
- Coding and learning of behavioral sequences (2004) (56)
- Nonlinear Hebbian Learning as a Unifying Principle in Receptive Field Formation (2016) (56)
- Integrate-and-Fire models with adaptation are good enough (2005) (52)
- Significance of intraoperative motor function monitoring using transcranial electrical motor evoked potentials (MEP) in patients with spinal and cranial lesions near the motor pathways (2009) (49)
- Coding and information processing in neural networks (1994) (48)
- Noise and the PSTH Response to Current Transients: I. General Theory and Application to the Integrate-and-Fire Neuron (2001) (48)
- Evaluation of a method for noninvasive intracranial pressure assessment during infusion studies in patients with hydrocephalus. (2000) (48)
- Spontaneous Excitations in the Visual Cortex: Stripes, Spirals, Rings, and Collective Bursts (1995) (48)
- Modeling spatial and temporal aspects of visual backward masking. (2008) (47)
- The Spike Response Model: A Framework to Predict Neuronal Spike Trains (2003) (46)
- Variational Learning for Recurrent Spiking Networks (2011) (46)
- What is Different with Spiking Neurons (2001) (45)
- Algorithmic Composition of Melodies with Deep Recurrent Neural Networks (2016) (45)
- Stability of working memory in continuous attractor networks under the control of short-term plasticity (2018) (45)
- Coding and Decoding with Adapting Neurons: A Population Approach to the Peri-Stimulus Time Histogram (2012) (43)
- Synaptic Consolidation: From Synapses to Behavioral Modeling (2015) (43)
- Associative Memory in a Network of 'Biological' Neurons (1990) (41)
- Coding properties of spiking neurons: reverse and cross-correlations (2001) (41)
- How to Describe Neuronal Activity: Spikes, Rates, or Assemblies? (1993) (40)
- Improved Similarity Measures for Small Sets of Spike Trains (2011) (39)
- Therapeutic management of grade IV aneurysm patients. (1997) (38)
- How the threshold of a neuron determines its capacity for coincidence detection. (1998) (35)
- Deep Artificial Composer: A Creative Neural Network Model for Automated Melody Generation (2017) (34)
- Changing the responses of cortical neurons from sub- to suprathreshold using single spikes in vivo (2013) (34)
- STDP in Adaptive Neurons Gives Close-To-Optimal Information Transmission (2010) (34)
- Perceptual learning, roving and the unsupervised bias (2012) (33)
- Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons (2016) (33)
- Short-Term Synaptic Plasticity Orchestrates the Response of Pyramidal Cells and Interneurons to Population Bursts (2005) (33)
- Does computational neuroscience need new synaptic learning paradigms? (2016) (32)
- Spike-timing prediction in cortical neurons with active dendrites (2014) (31)
- Statistics of subthreshold neuronal voltage fluctuations due to conductance-based synaptic shot noise. (2006) (31)
- Reward-based learning under hardware constraints—using a RISC processor embedded in a neuromorphic substrate (2013) (31)
- Fluctuations and information filtering in coupled populations of spiking neurons with adaptation. (2013) (31)
- Noise spectrum and signal transmission through a population of spiking neurons. (1999) (30)
- Spike-response model (2008) (30)
- Populations of spiking neurons (1999) (30)
- Spatial orientation in navigating agents: Modeling head-direction cells (2001) (29)
- Weight-space symmetry in deep networks gives rise to permutation saddles, connected by equal-loss valleys across the loss landscape (2019) (28)
- Homeostasis and Learning through Spike-Timing Dependent Plasticity (2003) (28)
- Predicting spike times of a detailed conductance-based neuron model driven by stochastic spike arrival (2004) (28)
- Automated point-neuron simplification of data-driven microcircuit models (2016) (28)
- Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model (2004) (28)
- Beyond Pair-Based STDP: a Phenomenological Rule for Spike Triplet and Frequency Effects (2005) (27)
- Spatial Representation and Navigation in a Bio-inspired Robot (2005) (27)
- Modeling rodent head-direction cells and place cells for spatial learning in bio-mimetic robotics (2000) (27)
- From spiking neurons to rate models: a cascade model as an approximation to spiking neuron models with refractoriness. (2006) (27)
- From Stochastic Nonlinear Integrate-and-Fire to Generalized Linear Models (2011) (27)
- Dependence of the spike-triggered average voltage on membrane response properties (2006) (26)
- Temporal coding in the sub-millisecond range: Model of barn owl auditory pathway (1995) (26)
- Optimal Hebbian Learning: A Probabilistic Point of View (2003) (26)
- Universality in neural networks: the importance of the ‘mean firing rate’ (1992) (25)
- How single neuron properties shape chaotic dynamics and signal transmission in random neural networks (2018) (24)
- Consciousness & the small network argument (2007) (23)
- Local plasticity rules can learn deep representations using self-supervised contrastive predictions (2020) (23)
- A biologically motivated and analytically soluble model of collective oscillations in the cortex (2004) (23)
- Connectivity reflects coding: A model of voltage-based spike-timing-dependent-plasticity with homeostasis (2009) (23)
- Rapid suppression and sustained activation of distinct cortical regions for a delayed sensory-triggered motor response (2020) (23)
- Geometry of the Loss Landscape in Overparameterized Neural Networks: Symmetries and Invariances (2021) (23)
- Cerebral Vasodilatation Causing Acute Intracranial Hypertension: A Method for Noninvasive Assessment (1999) (23)
- Noise and the PSTH Response to Current Transients: II. Integrate-and-Fire Model with Slow Recovery and Application to Motoneuron Data (2002) (22)
- Encoding and Decoding of Patterns which are Correlated in Space and Time (1990) (21)
- Paradoxical Evidence Integration in Rapid Decision Processes (2012) (21)
- Cortical Dynamics in Presence of Assemblies of Densely Connected Weight-Hub Neurons (2017) (21)
- Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze-like Environments (2015) (21)
- Dynamics of interacting finite-sized networks of spiking neurons with adaptation (2013) (21)
- Mesoscopic population equations for spiking neural networks with synaptic short-term plasticity (2018) (20)
- Gamma Oscillations in a Nonlinear Regime: A Minimal Model Approach Using Heterogeneous Integrate-and-Fire Networks (2008) (20)
- Place Cells and Spatial Navigation Based on 2D Visual Feature Extraction, Path Integration, and Reinforcement Learning (2000) (20)
- Integrate-and-Fire Neurons and Networks (2002) (19)
- Effect of lateral connections on the accuracy of the population code for a network of spiking neurons. (2001) (18)
- Spike-triggered averages for passive and resonant neurons receiving filtered excitatory and inhibitory synaptic drive. (2008) (18)
- Analysis of a correlation-based model for the development of orientation-selective receptive fields in the visual cortex. (1998) (18)
- The Performance (and Limits) of Simple Neuron Models: Generalizations of the Leaky Integrate-and-Fire Model (2012) (18)
- Surgery and outcome for aneurysmal subarachnoid hemorrhage in elderly patients. (2002) (17)
- Spiking Neuron Models: Formal spiking neuron models (2002) (17)
- Multicontact Co-operativity in Spike-Timing–Dependent Structural Plasticity Stabilizes Networks (2017) (17)
- Neuronal Dynamics: Preface (2014) (17)
- Place Cells and Spatial Navigation based on Vision, Path Integration, and Reinforcement Learning (2001) (17)
- Learning in Volatile Environments With the Bayes Factor Surprise (2021) (16)
- Towards deep learning with spiking neurons in energy based models with contrastive Hebbian plasticity (2016) (16)
- An online Hebbian learning rule that performs independent component analysis (2007) (15)
- Three-dimensional computer-assisted stereotactic-guided microneurosurgery combined with cortical mapping of the motor area by direct electrostimulation. (1997) (15)
- Associative binding and segregation in a network of spiking neurons (1994) (15)
- Special issue on quantitative neuron modeling (2008) (15)
- Signal buffering in random networks of spiking neurons: microscopic versus macroscopic phenomena. (2005) (15)
- Connection-type-specific biases make uniform random network models consistent with cortical recordings (2014) (14)
- Rapid signal transmission by populations of spiking neurons (1999) (14)
- Rescaling, thinning or complementing? On goodness-of-fit procedures for point process models and Generalized Linear Models (2010) (13)
- One-shot learning and behavioral eligibility traces in sequential decision making (2017) (13)
- Multi-contact synapses for stable networks: a spike-timing dependent model of dendritic spine plasticity and turnover (2016) (11)
- Balancing New Against Old Information: The Role of Surprise (2016) (11)
- Neural pre-coding increases the pattern retrieval capacity of Hopfield and Bidirectional Associative Memories (2011) (11)
- Escape rate models for noisy integrate-and-free neurons (2000) (11)
- Quantitative Single-Neuron Modeling: Competition 2009 (1970) (11)
- A developmental learing rule for coincidence tuning in the barn owl auditory system (1997) (11)
- Predicting non-linear dynamics: a stable local learning scheme for recurrent spiking neural networks. (2017) (11)
- When shared concept cells support associations: Theory of overlapping memory engrams (2021) (10)
- Combining Multimodal Sensory Input for Spatial Learning (2002) (10)
- A new kernel clustering algorithm (2002) (10)
- Transient information flow in a network of excitatory and inhibitory model neurons: Role of noise and signal autocorrelation (2004) (10)
- From Hebb Rules to Spike-Timing-Dependent Plasticity: A Personal Account (2010) (9)
- Prospective documentation and analysis of the pre- and early clinical management in severe head injury in southern Bavaria at a population based level. (2004) (9)
- Code-specific policy gradient rules for spiking neurons (2009) (9)
- The Silent Period of Evidence Integration in Fast Decision Making (2013) (9)
- Non-linear motor control by local learning in spiking neural networks (2017) (9)
- Hebbian Learning and Plasticity (2018) (9)
- Competition between cue response and place response: a model of rat navigation behaviour (2005) (9)
- Why spikes? Hebbian learning and retrieval of time-resolved excitation patterns (2004) (9)
- Supervised Learning for Neural Networks : A Tutorial with JAVA exercises 1 (9)
- A Model of Synaptic Reconsolidation (2016) (8)
- Dynamical principles for neuroscience and intelligent biomimetic devices (2006) (8)
- Novelty is not surprise: Human exploratory and adaptive behavior in sequential decision-making (2021) (8)
- BachProp: Learning to Compose Music in Multiple Styles (2018) (8)
- Excitable neuronal assemblies with adaptation as a building block of brain circuits for velocity-controlled signal propagation (2018) (7)
- Frequency Spectrum of Coupled Stochastic Neurons with Refractoriness (1998) (7)
- Noise-enhanced computation in a model of a cortical column (2005) (7)
- A ‘microscopic’ model of collective oscillations in the cortex (1992) (7)
- Spikes or Rates? -- Stationary, oscillatory, and spatio-temporal states in an associative network of spiking neurons (1993) (6)
- How Can the Brain Be So Fast (2006) (6)
- New support vector algorithms for multicategorical data applied to real-time object (2003) (6)
- Motion detection in a Linsker network (1994) (6)
- On the choice of metric in gradient-based theories of brain function (2018) (6)
- Surprise: a unified theory and experimental predictions (2021) (6)
- Modelling Path Integrator Recalibration Using Hippocampal Place Cells (2005) (5)
- Can We Predict Every Spike (2013) (5)
- Emergence of spatiotemporal receptive fields and its application to motion detection (1994) (5)
- Visual backward masking: Feed-forward or recurrent? (2005) (5)
- Learning to Generate Music with BachProp (2018) (5)
- Optimal Stimulation Protocol in a Bistable Synaptic Consolidation Model (2018) (5)
- Exponentially Long Orbits in Hopfield Neural Networks (2017) (4)
- Online Processing of Multiple Inputs in a Sparsely-Connected Recurrent Neural Network (2003) (4)
- Brain signals of a Surprise-Actor-Critic model: Evidence for multiple learning modules in human decision making (2021) (4)
- Multi-Timescale Memory Dynamics Extend Task Repertoire in a Reinforcement Learning Network With Attention-Gated Memory (2017) (4)
- Paradoxical Results of Long-Term Potentiation explained by Voltage-based Plasticity Rule (2020) (4)
- Efficient low-dimensional approximation of continuous attractor networks (2017) (4)
- Dendrites and synapses (2014) (4)
- Neuro-mimetic navigation systems: A computational model of the rat Hippocampus (1999) (4)
- Reinforcement Learning in Continuous State and Action Space (2003) (4)
- Correction: Spike-Based Reinforcement Learning in Continuous State and Action Space: When Policy Gradient Methods Fail (2009) (4)
- A taxonomy of surprise definitions (2022) (4)
- Oscillations and synchrony (2002) (3)
- Sparse-distributed codes for image categorization (1999) (3)
- On the role of dimensionality in face authentication (2000) (3)
- Nonlinear integrate-and-fire models (2014) (3)
- Towards truly local gradients with CLAPP: Contrastive, Local And Predictive Plasticity (2020) (3)
- Poisson-like neuronal firing due to multiple synfire chains in simultaneous action (1997) (3)
- Effect of noise on neuron transient response (2000) (3)
- Neuronal Dynamics: Variability of spike trains and neural codes (2014) (3)
- A vision-driven model of hippocampal place cells and temporally asymmetric LTP-induction for action learning (1999) (3)
- Modulation of a decision-making process by spatiotemporal spike patterns decoding: evidence from spike-train metrics analysis and spiking neural network modeling (2013) (3)
- Dynamic Noise Annealing for Learning Temporal Sequences with Recurrent Neural Networks (2002) (3)
- Modeling directional firing properties of place cells (2003) (3)
- Spike timing prediction with active dendrites (2013) (3)
- Complexity and performance in simple neuron models (1970) (3)
- Effect of lateral connections on the accuracy of the population code for a network of spiking neurons (2001) (3)
- Cooperation across timescales between and Hebbian and homeostatic plasticity (2016) (3)
- Estimating small-world topology of neural networks from multi-electrode recordings (2010) (3)
- Effect of correlations on signal transmission in a population of spiking neurons (2000) (3)
- Novelty is not Surprise: Exploration and learning in human sequential decision-making (2020) (3)
- Vertical signal flow and oscillations in a three-layer model of the cortex (1996) (3)
- Hippocampal spatial model for state space representation in robotic reinforcement learning (2001) (2)
- A novel information theoretic measure of surprise (2016) (2)
- Quantitative single-neuron modeling: competition 2008 (2008) (2)
- 0 Hebbian Learning and Plasticity (2011) (2)
- Support Vector Features and the Role of Dimensionality in Face Authentication (2002) (2)
- Support Vector Representation of Multi-categorical Data (2002) (2)
- A General Model of Music Composition (2018) (2)
- Divergent sensory processing converges in frontal cortex for a planned motor response (2020) (2)
- A functional model of adult dentate gyrus neurogenesis (2021) (2)
- Inhibitory plasticity balances excitation and inhibition in sensory processing and Hebbian assemblies (2011) (2)
- Bias Variance Decomposition (2010) (2)
- Neuromodulation by surprise: a biologically plausible model of the learning rate dynamics (2014) (2)
- Noise in spiking neuron models (2002) (2)
- Localized random projections challenge benchmarks for bio-plausible deep learning (2018) (2)
- Detailed neuron models (2002) (2)
- The influence of structure on the response properties of biologically plausible neural network models (2011) (2)
- Stress, noradrenaline, and realistic prediction of mouse behaviour using reinforcement learning (2008) (2)
- Combining visual and proprioceptive information in a model of spatial learning and navigation (2004) (2)
- An Approximate Bayesian Approach to Surprise-Based Learning (2019) (2)
- Understanding the PSTH response to synaptic input (1999) (2)
- Fitting summary statistics of neural data with a differentiable spiking network simulator (2021) (2)
- The role of interconnected hub neurons in cortical dynamics (2014) (2)
- Neuronal Dynamics: Synaptic plasticity and learning (2014) (2)
- Proceedings of the 7th International Conference on Artificial Neural Networks (1997) (2)
- Subthreshold cross-correlations between cortical neurons: A reference model with static synapses (2005) (2)
- GENERALIZED INTEGRATE-AND-FIRE NEURONS (2014) (2)
- Automatic characterization of three cortical neuron types reveals two distinct adaptation mechanisms (2011) (2)
- Single neuron properties shape chaotic dynamics in random neural networks (2018) (2)
- Synaptic efficacy tunes speed of activity propagation through chains of bistable neural assemblies (2015) (2)
- Adult dentate gyrus neurogenesis: a functional model (2019) (2)
- The role of interconnected hub neurons in cortical dynamics (2014) (1)
- MLPGradientFlow: going with the flow of multilayer perceptrons (and finding minima fast and accurately) (2023) (1)
- Biological Learning: Synaptic Plasticity, Hebb Rule and Spike TimingDependent Plasticity (2010) (1)
- Approximating Relu Networks by Single-Spike Computation (2022) (1)
- Neuronal Dynamics: Estimating parameters of probabilistic neuron models (2014) (1)
- Bellman Equation (2010) (1)
- Introduction: neurons and mathematics (2014) (1)
- Adaptation and firing patterns (2014) (1)
- Synaptic tagging and capture: a bridge from molecular to behaviour (2011) (1)
- Mesoscopic modeling of hidden spiking neurons (2022) (1)
- Spiking Neuron Models: Signal transmission and neuronal coding (2002) (1)
- A unified voltage-based model for STDP, LTP and LTD (2008) (1)
- Learning multiple categories from sequences of examples (2002) (1)
- Attractor Network Dynamics Enable Preplay and Rapid Path Planning in Maze\textendash like Environments (2015) (1)
- The quality of Coincidence detection and ITD-tuning: a theoretical framework (1999) (1)
- Neuronal Dynamics: Competing populations and decision making (2014) (1)
- Memory and attractor dynamics (2014) (1)
- A Bayesian model for a fully automated, virtual reality-based Rubber Hand Illusion (2010) (1)
- Surprise minimization as a learning strategy in neural networks (2015) (1)
- Surprise-based learning: neuromodulation by surprise in multi-factor learning rules (2014) (1)
- Basic Lemma (2010) (1)
- Bridging spiking neuron models and mesoscopic population models - a general theory for neural population dynamics (2015) (1)
- Hebbian and non-Hebbian plasticity orchestrated to form and retrieve memories in spiking networks (2015) (1)
- A Bayesian kernel for the prediction of neuron properties from binary gene profiles (2005) (1)
- Evidence for eligibility traces in human learning (2017) (1)
- Blog Mining (2010) (1)
- Intrinsic Stabilization of Output Rates by Spike-Time Dependent Hebbian Learning (2007) (1)
- A biologically plausible 3-factor learning rule for expectation maximization in reinforcement learning and decision making (2015) (1)
- A model of perceptual discrimination under sequential sensory evidence (2013) (1)
- Adaptive sensory processing for efficient place coding (2006) (1)
- Learning associations with a neurally-computed global novelty signal (2015) (1)
- Surprise-based learning: a novel measure of surprise with applications for learning within changing environments (2016) (1)
- Rapid path planning and preplay in maze{like environments using attractor networks (2015) (1)
- Surprise minimization as a learning strategy in neural networks (2015) (1)
- General conditions for spiking neurons and plasticity rules to perform independent component analysis (2011) (1)
- Bridging spiking neuron models and mesoscopic population models - a general theory for neural population dynamics (2015) (1)
- Noise Modulation by Stochastic Neurons of the Integrate-and Fire Type (1999) (1)
- Stabilizing working memory in spiking networks with biologically plausible synaptic dynamics (2014) (1)
- Modulation of a decision-making process by spatiotemporal spike patterns decoding: evidence from spike-train metrics analysis and spiking neural network modeling (2013) (1)
- A hierarchy of time scales supports unsupervised learning of behavioral sequences (2015) (1)
- Bias-Variance-Covariance Decomposition (2010) (1)
- The accuracy of the population vector estimate in networks of integrate-and-fire type neurons using stationary and transient stimuli (2001) (1)
- Head direction cells and place cells in models for navigation and robotic applications (2005) (1)
- Faculty Opinions recommendation of Locus coeruleus and dopaminergic consolidation of everyday memory. (2017) (0)
- Two-dimensional neuron models (2002) (0)
- Breakeven Point (2010) (0)
- Modeling plasticity across different time scales: the TagTriC model (2009) (0)
- Spatial reorientation and environment geometry : extraction of global parameters from local visual features (2007) (0)
- 10 Populations of Spiking Neurons (1998) (0)
- One-shot learning and behavioral eligibility (2019) (0)
- Neuronal Dynamics: Fast transients and rate models (2014) (0)
- Cortical field models for perception (2014) (0)
- Consciousness & the small network argument. Commentary (2007) (0)
- Correlation-invariant synaptic plasticity (2021) (0)
- Faculty Opinions recommendation of Random synaptic feedback weights support error backpropagation for deep learning. (2017) (0)
- Mesoscopic population equations for spiking neural networks with synaptic short-term plasticity (2020) (0)
- Noisy input models: barrage of spike arrivals (2014) (0)
- A hierarchy of time scales supports unsupervised learning of behavioral sequences (2015) (0)
- Spiking Neuron Models: References (2002) (0)
- Neuronal Dynamics: Outlook: dynamics in plastic networks (2014) (0)
- Working memory facilitates reward-modulated Hebbian learning in recurrent neural networks (2019) (0)
- network models consistent with cortical recordings Connection-type-specific biases make uniform random (2014) (0)
- Neuronal Dynamics: NETWORKS OF NEURONS AND POPULATION ACTIVITY (2014) (0)
- Equivalence of ReLU and Single-Spike Neural Networks (2023) (0)
- Bounded Differences Inequality (2010) (0)
- Quasi-renewal theory and the integral-equation approach (2014) (0)
- A model of perceptual discrimination under sequential sensory evidence (2013) (0)
- Neuronal Dynamics: Noisy output: escape rate and soft threshold (2014) (0)
- Author response: Changing the responses of cortical neurons from sub- to suprathreshold using single spikes in vivo (2012) (0)
- The curse of optimism: a persistent distraction by novelty (2022) (0)
- Unimodal or Bimodal Distribution of Synaptic Weights? (2007) (0)
- Bilingual Lexicon Extraction (2010) (0)
- layer 2 / 3 of mouse barrel cortex Microcircuits of excitatory and inhibitory neurons in (2012) (0)
- Bayes Adaptive Markov Decision Processes (2010) (0)
- Efficient modeling of neural activity using coupled renewal processes (2011) (0)
- Conclusion [18] A. Artola and W. Singer, "the Involvement of N-methyl-d-aspartate Receptors in Induction and Maintenance of Long-term (1995) (0)
- Coding properties of spiking neurons: modeling reverse correlations. (2001) (0)
- An Exact Mapping From ReLU Networks to Spiking Neural Networks (2022) (0)
- Input-Driven Spiking in Fast-Spiking Cells Inhibition-Controlled Switch Between Intrinsic and Somatosensory Cortical Inhibitory Interneurons: An Integration of Broadband Conductance Input in Rat (2015) (0)
- Ion channels and the Hodgkin–Huxley model (2014) (0)
- Complications in Cervical Arthroplasty Surgery - Single Institution Experience in 100 Patients (2010) (0)
- Dendritic Voltage Recordings Explain Paradoxical Synaptic Plasticity: A Modeling Study (2020) (0)
- Temporal Transition from Illusory Conjunctions to Object Recognition (2016) (0)
- Plasticity and stability in recurrent neural networks (2011) (0)
- Biological Learning: Synaptic Plasticity, Hebb Rule and Spike Timing Dependent Plasticity (2017) (0)
- Noisy Inputs In Vitro The Dynamical Response Properties of Neocortical Neurons to Temporally Modulated (2008) (0)
- Spike-timing prediction in a neuron model with active dendrites (2009) (0)
- Fast and richly structured activity in cortical networks with local inhibition (2011) (0)
- Spike-based reinforcement learning of navigation (2008) (0)
- Noisy Inputs In Vitro The Dynamical Response Properties of Neocortical Neurons to Temporally Modulated (2008) (0)
- Stabilizing working memory in spiking networks with biologically plausible synaptic dynamics (2014) (0)
- Multi-timescale memory dynamics in a reinforcement learning network with attention-gated memory (2017) (0)
- Contextual information for maintaining coherent egocentric-allocentric maps (2010) (0)
- Spiking Neuron Models Author ' s personal copy Detailed Models of a Spiking Neuron (0)
- DYNAMICS OF COGNITION (2014) (0)
- Lecture Notes in Computer Science - Artificial Neural Networks - ICANN "97 (1997) (0)
- A developmental model of spatio-temporal receptive field properties for simple cells in the visual cortex (1995) (0)
- Bayes Net (2010) (0)
- Neural Networks and Biological Modeling (2009) (0)
- Preprint : Final version has appeared in : Science 338 : 60-65 ( 2012 ) Theory and Simulation in Neuroscience (2012) (0)
- Weight-space symmetry in neural network loss landscapes revisited (2019) (0)
- Expand-and-Cluster: Exact Parameter Recovery of Neural Networks (2023) (0)
- Long term potentiation in dendritic spines: a model study (1995) (0)
- Neuronal Dynamics: Continuity equation and the Fokker–Planck approach (2014) (0)
- Encoding and decoding with stochastic neuron models (2014) (0)
- Effective Description of Neuronal Activity Adaptive Exponential Integrate-and-Fire Model as an (2005) (0)
- Central Nervous System Injury: Prospective system analysis of the pre- and early clinical management in severe head injury (1998) (0)
- Fast Adaptation to Rule Switching using Neuronal Surprise (2022) (0)
- Management of Spontaneous Brain Stem Hemorrhage with Special Consideration to Vascular Malformations: Conservative versus Surgical Treatment (1998) (0)
- Convergence of redundancy-free spiking neural networks to rate networks (2023) (0)
- Bandit Problem with Side Information (2010) (0)
- Effects of Stress and Genotype on Meta-parameter Dynamics in Reinforcement Learning (2006) (0)
- Bandit Problem with Side Observations (2010) (0)
- 25th Annual Computational Neuroscience Meeting: CNS-2016 (2016) (0)
- Number : BICY-D-08-00052 R 1 Title : The Quantitative Single-Neuron Modeling Competition (2008) (0)
- Paradoxical evidence integration in rapid decision processes-Supporting Text S1 (2012) (0)
- Bootstrap Sampling (2009) (0)
- Bottom Clause (2010) (0)
- Kernel Memory Networks: A Unifying Framework for Memory Modeling (2022) (0)
- Belief State Markov Decision Processes (2010) (0)
- Remembering the “When”: Hebbian Memory Models for the Time of Past Events (2022) (0)
- Spike-timing dependent plasticity changes responses of cortical neurons from sub- to supra-threshold in vivo (2012) (0)
- Versatility and Relevance of the Adaptive Exponential Integrate-and-Fire Model (2008) (0)
- Neuromodulation by surprise: a biologically plausible model of the learning rate dynamics (2014) (0)
- A Memory-Augmented Reinforcement Learning Model of Food Caching Behaviour in Birds (2019) (0)
- Local learning rules for learning representations and actions (2023) (0)
- A two stage model for perceptual decision making (2010) (0)
- Predicting neuronal activity with an adaptive exponential integrate-and-fire model (2007) (0)
- Spatially structured networks (2002) (0)
- What ' s di erent with spiking neurons ? (1999) (0)
- Plasticity and coding (2002) (0)
- Author response: A functional model of adult dentate gyrus neurogenesis (2021) (0)
- Artificial neural networks : ICANN '97 : 7th International Conference, Lausanne, Switzerland, October 8-10, 1997 : proceedings (1997) (0)
- Estimation of small-world topology of cortical networks using Generalized Linear Models (2011) (0)
- The power and limits of simple neuron models: predicting neural activity spike by spike (1970) (0)
- Surprise-modulated belief update: how to learn within changing environments? (2016) (0)
- Batch Learning (2010) (0)
- Modelling feature-integration in human vision with drift diffusion models (2008) (0)
- Stable Propagation of A tivity Pulsesin Populations of Spiking (2002) (0)
- SOME GENERALIZATIONS OF INTEGRATE-AND-FIRE MODELS (2003) (0)
- Voltage Recordings and Genetic Algorithms Constraining Compartmental Models Using Multiple (2015) (0)
- 1 Spiking Neurons (2007) (0)
- New Results - Modeling cortical activity (2005) (0)
- Author response: One-shot learning and behavioral eligibility traces in sequential decision making (2019) (0)
- Dimensionality reduction and phase plane analysis (2014) (0)
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