Anders Lansner
Cognitive Neuroscience · 2000–2015
A researcher in the Science corpus: 7 papers; trusts 12 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Cognitive Neuroscience — 90 citations into it; #3,932 of 10,852 by trust here, #2,905 by citations
- Cellular and Molecular Neuroscience — 36 citations into it; #1,061 of 2,998 by trust here, #1,454 by citations
- Electrical and Electronic Engineering — 22 citations into it; #14,270 of 16,539 by trust here, #6,657 by citations
- Neuroscience — 22 citations into it
- Statistical and Nonlinear Physics — 7 citations into it
- Artificial Intelligence — 6 citations into it; #32,799 of 35,345 by trust here, #30,347 by citations
- Model Architectures — 6 citations into it
Whom Anders Lansner trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Teuvo Kohonen
- John J. Hopfield
- Christoph von der Malsburg
- Nicolas J.-B. Brunel
- D. Marr
- Shun-ichi Amari
- Erkki Oja
- Moshe Abeles
- S. Cooper
- Eugene M. Izhikevich
Who trusts Anders Lansner overall
Papers from Anders Lansner's perspective
Ordered by how strongly the researchers Anders Lansner trusts endorse each paper. Same corpus, a different order for every researcher.
- Neural networks and physical systems with emergent collective computational abilities.
- Dynamics of Sparsely Connected Networks of Excitatory and Inhibitory Spiking Neurons
- Competitive Hebbian learning through spike-timing-dependent synaptic plasticity
- A quantitative description of membrane current and its application to conduction and excitation in nerve
- What determines the frequency of fast network oscillations with irregular neural discharges? I. Synaptic dynamics and excitation-inhibition balance. (Journal of Neurophysiology)
- Spike-Timing-Dependent Plasticity in Balanced Random Networks
- The Correlation Theory of Brain Function
- The Prefrontal Cortex
- Dynamics of a recurrent network of spiking neurons before and following learning
- Non-Holographic Associative Memory
Their papers
- Simulation of networks of spiking neurons: A review of tools and strategies (2006) — 884 citations
- A palimpsest memory based on an incremental Bayesian learning rule (2000) — 32 citations
- A working memory model based on fast Hebbian learning (2003) — 91 citations
- Neurocognitive architecture of working memory (2015) — 595 citations
- Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models (2015) — 348 citations
- Associative memory models: from the cell-assembly theory to biophysically detailed cortex simulations. (2009) — 192 citations
- A Palimpsest Memory based on anIn remental Bayesian Learning