Embedded thumbnail for Ben Deen: Multivoxel Pattern Analysis for Understanding Representational Content
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June 5, 2014
Part of
Brains, Minds and Machines Summer Course 2014
Topics: Motivation for multivoxel pattern analysis (MVPA); correlation based classification analysis; results of analysis of EBA and pSTS cortical regions: EBA patterns carry information about body pose that is invariant to body motion kinematics,...
Embedded thumbnail for Development of Intelligence - Laura Schulz: Cognitive Development and Commonsense Reasoning, Part 1
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June 4, 2014
Part of
Brains, Minds and Machines Summer Course 2014
Topics: Historical perspective on underestimating the challenge of commonsense intelligence in AI; studying children may provide key insights; early representations of objects (e.g. object permanence, Spelke objects, expectations of object behavior...
Embedded thumbnail for Jim DiCarlo: Introduction to the Visual System, Part 2
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June 4, 2014
Part of
Brains, Minds and Machines Summer Course 2014
Topics: Decoding of IT signals for object classification (Poggio, DiCarlo, Science 2009); 3D object models; detection experiments with objects of different pose placed on random background images; neural population state space; LaWS of RAD IT...
Embedded thumbnail for Jim DiCarlo: Introduction to the Visual System, Part 1
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June 4, 2014
Part of
Brains, Minds and Machines Summer Course 2014
Topics: Why study object recognition in the brain; comparison of behavior in humans and monkeys; overview of the ventral visual stream and the ventral (what) vs. dorsal (where) pathways; retinal receptive fields; simple and complex cells in V1;...
Embedded thumbnail for Emily Mackevicius: Learning from a Computational Neuroscience Perspective
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June 2, 2014
Part of
Brains, Minds and Machines Summer Course 2014
Topics: Marr levels of analysis, types of learning (unsupervised, supervised, reinforcement), Hebb rule, LTP, correlation and covariance based learning, reinforcement learning, classical conditioning, conditioning paradigms, credit assignment...
Embedded thumbnail for Gabriel Kreiman: Neurons and Models
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June 2, 2014
Part of
Brains, Minds and Machines Summer Course 2014
Topics: General features of brain-based computations, brain anatomy, structure of neurons, equivalent electrical circuit, synapses, single neuron models at multiple resolutions, integrate-and-fire model, Hodgkin-Huxley model; empirical methods used...
Embedded thumbnail for Jed Singer: Neural Coding
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June 2, 2014
Part of
Brains, Minds and Machines Summer Course 2014
Topics: Characterizing neural firing rates, tuning curves, identifying effective stimuli, modeling spike trains, integrating information across time and across neurons, estimating response using reverse correlation, decoding fundamentals, two-way...
Embedded thumbnail for Sam Gershman (continuation of previous talk), and Josh Tenenbaum: Bayesian Inference
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May 31, 2014
Part of
Brains, Minds and Machines Summer Course 2014
Topics: (Sam Gershman) Application of Bayesian learning to motion perception; automatic structure learning
(Joshua Tenenbaum) Learning to learn: hierarchical Bayes; empirical studies of word learning and the relevant object features; transfer...
Embedded thumbnail for Sam Gershman: Structure Learning, Clusters, Features, and Functions
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May 31, 2014
Part of
Brains, Minds and Machines Summer Course 2014
Topics: Basic introduction to parameter learning, structure learning, nonparametric Bayes, mixture models, conditioning as clustering, learning relational concepts, multi-level category learning, latent feature models, function learning, Gaussian...
Embedded thumbnail for Lorenzo Rosasco: Learning Theory, Part 1 (local methods, bias-variance, cross validation) and Part 2 (regularization: linear least squares, kernel least squares)
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May 30, 2014
Part of
Brains, Minds and Machines Summer Course 2014
Topics: Supervised learning, nearest neighbor methods and overfitting, k-nearest neighbors - choosing k, bias-variance tradeoff, cross validation, regularization, least squares, linear systems, computational complexity, kernel least squares using...

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