- Perceptual Learning (2) Tsodyks and Gilbert, Neural networks and perceptual learning (2004)
- http://nro.sagepub.com The Neuroscientist
- 2. Decoding (continued) !180 !90 0 90 180
- CCN Lab 2: Models of Spiking Neurons Peggy Series, pseries@inf.ed.ac.uk
- Computational Cognitive Neuroscience Peggy Seris,
- Neuroeconomics George Loewenstein,1
- Neurocomputing 38}40 (2001) 881}888 A network view of the structure of center/surround
- Perceptual learning in visual hyperacuity: A reweighting model Grigorios Sotiropoulos a
- 1Neuroeconomics: Decision Making and the Brain 2009, Elsevier Inc. Introduction: A Brief History of
- Encoding (continued): very quick survey of visual areas
- The `Bayesian Brain' Readings: Knill & Pouget, TINS, 2004
- Plasticity: Learning and Long-Term Memory Declarative Memory and the Hippocampus
- Models of networks -continued Readings: D&A, chapter 7.
- Tools of computational neuroscience : Models of neurons D&A Chapter 5.
- CCN assignment 1: How do expectations influence visual perception?
- Sustained activity, Working Memory, Associative memory C.Constandinis and XJ Wang, , "a neural circuit basis for
- THSE DE DOCTORAT DE L'UNIVERSIT DE PARIS-VI Spcialit : BIOMATHMATIQUES
- Sustained activity, Working Memory, Associative memory C.Constandinis and XJ Wang, , "a neural circuit basis for
- " If you're talking about what you can feel, what you can smell, what you can taste and see, then !real" is simply electrical signals interpreted by your
- ABSTRACT The search for anatomical correlates of special skills dates from the end of the 19th
- A unified model for perceptual learning Aaron Seitz1,2
- " If you're talking about what you can feel, what you can smell, what you can taste and see, then !real" is simply electrical signals interpreted by your
- Current Biology, Vol. 14, 257262, February 3, 2004, 2004 Elsevier Science Ltd. All rights reserved. DOI 10.1016/j.cub.2004.01.029 The Ventriloquist Effect Results
- Neurocomputing 26}27 (1999) 505}510 Synchrony and delay activity in cortical column models
- Proc. Natl. Acad. Sci. USA Vol. 92, pp. 3844-3848, April 1995
- Models of networks Readings: D&A, chapter 7.
- CCN assignment 1: Exploring the Relationship between Neuronal and Behavioral Responses to
- CCN Assignment 2: Models of Decision Making Peggy Seris, pseries@inf.ed.ac.uk
- Lab 5: A Simple Network Model of Perceptual Peggy Seris, pseries@inf.ed.ac.uk
- 1. Encoding (continued) encoding D&A ch.1readings
- *Department of Physiology, Centre for Neuroscience
- Models of networks -continued Readings: D&A, chapter 7.
- Perceptual Learning Tsodyks and Gilbert, Neural networks and perceptual learning (2004)
- Neural Networks That Learn (Supervised Learning)
- The `Bayesian Brain' Readings: Knill & Pouget, TINS, 2004
- CCN Assignment 2: TD learning, Bayes and Peggy Seri`es, pseries@inf.ed.ac.uk
- Why did you choose this course? Why did you choose the clothes you!re wearing?
- Models of Attention Maunsell & Cook, the role of attention
- Preprint --To appear in the British Journal for the Philosophy of Science Bayes in the Brain. On Bayesian Modelling in Neuroscience
- Rapidly learned stimulus expectations alter perception of motion
- Rapidly learned stimulus expectations alter perception of motion Supplementary Materials
- Dynamic competition between contour integration and contour segmentation probed with moving stimuli
- Orientation dependent modulation of apparent speed: a model based on the dynamics of feed-forward and horizontal connectivity
- Orientation dependent modulation of apparent speed: psychophysical evidence
- Peggy Seris, PhD Institute for Adaptive and Neural Computation (ANC)
- Computational Cognitive Neuroscience Assignment 1: Hopeld networks, Schizophrenia and the
- CCN assignment 2: Perceptual Learning as a Change in the Read-out
- Attentional modulation of firing rate and synchrony in a model cortical network: a critical analysis
- CCN Matlab Lab 3: the `ring model' Peggy Seris, pseries@inf.ed.ac.uk
- 1. Encoding (continued) encoding D&A ch.1readings
- Neural Networks That Learn (Supervised Learning)
- Reinforcement Learning in the brain Reading: Y Niv, Reinforcement learning in the brain, 2009.
- Why did you choose this course? Why did you choose the clothes you!re wearing?
- CCN Assignment 1: Hopfield Networks, Schizophrenia and the Izhikevich Neuron Model
- VOL. 15, NO. 3, 1989 Cortical Pruning and
- Linking Animal Models of Psychosis to Computational Models of Dopamine Function
- COMPUTATIONAL COGNITIVE NEUROSCIENCE : E C I ' 2 0 0 9
- Computational Cognitive Neuroscience Peggy Seris,
- 2. Decoding readings: Decoding D&A ch.3
- Models of Networks of Neurons Neurons are organized in large networks. A typical neuron is cortex
- Maunsell & Cook, the role of attention in visual processing, 2002.
- 2002 NaturePublishing Group PERSPECTIVES
- erceptual learning is the improvement in per-formance on a variety of simple sensory tasks,
- Hannes Saal h.saal@sms.ed.ac.uk
- Computational Cognitive Neuroscience Peggy Seris,
- CCN Assignment 3 Research Review
- 2. Decoding (continued) readings: Decoding D&A ch.3
- The ``silent'' surround of V1 receptive fields: theory and experiments Peggy Series *, Jean Lorenceau, Yves Fregnac *
- From drugs to deprivation: a Bayesian framework for understanding models of psychosis
- Changing expectations about speed alters perceived motion di-Grigorios Sotiropoulos1, Aaron R. Seitz2, and Peggy Seris1
- Supplemental Information: Changing expectations about speed alters perceived motion direction
- 1. Encoding (continued) encoding D&A ch.1readings
- A-'Unaware' Adaptation!
- 2. Decoding (continued) readings: Decoding D&A ch.3
