This lecture covers modeling the neuron in silicon, modeling vision and audition and sensory fusion using a deep network.
Presentation of past and present neurocomputing approaches and hybrid analog/digital circuits that directly emulate the properties of neurons and synapses.
Presentation of the Brian neural simulator, where models are defined directly by their mathematical equations and code is automatically generated for each specific target.
The lecture covers a brief introduction to neuromorphic engineering, some of the neuromorphic networks that the speaker has developed, and their potential applications, particularly in machine learning.
This lecture provides an overview of depression (epidemiology and course of the disorder), clinical presentation, somatic co-morbidity, and treatment options.
Part 1 of 2 of a tutorial on statistical models for neural data
What is the difference between attention and consciousness? This lecture describes the scientific meaning of consciousness, journeys on the search for neural correlates of visual consciousness, and explores the possibility of consciousness in other beings and even non-biological structures.
The "connectome" is a term, coined in the past decade, that has been used to describe more than one phenomenon in neuroscience. This lecture explains the basics of structural connections at the micro-, meso- and macroscopic scales.
From the retina to the superior colliculus, the lateral geniculate nucleus into primary visual cortex and beyond, this lecture gives a tour of the mammalian visual system highlighting the Nobel-prize winning discoveries of Hubel & Wiesel.
In an overview of the structure of the mammalian neocortex, this lecture explains how the mammalian cortex is organized in a hierarchy, describing the columnar principle and canonical microcircuits