deep neural networks

Neuroscientist Kalanit Grill-Spector studies the physiology of human vision and says that the ways computers and people see are in some ways similar, but in other ways quite different. In fact, she says, rapid advances in computational modeling, such as deep neural networks, applied to brain data and new imaging technologies, like quantitative MRI and diffusion MRI, are revolutionizing our understanding of how the human brain sees. We’re unraveling how the brain “computes” visual information, as Grill-Spector tells host Russ Altman on this episode of Stanford Engineering’s The Future of Everything podcast.

Chapter Time Stamps:

(00:01:30) Episode introduction: Exploring the fascinating field of cognitive neuroscience and brain development with Kalanit Grill-Spector.

(00:02:45) Dr Grill-Spector's background and research interests: The intersection of cognitive neuroscience, psychology, and computer science.

(00:04:00) The crucial role of experience in shaping brain development: Understanding how environmental factors influence neural specialization.

(00:09:55) The development of word processing regions in the brain: Investigating the emergence and evolution of brain regions associated with reading and word recognition.

(00:11:30) The evolution of word specialization and its implications: Exploring how the brain acquires the ability to read and process words.

(00:14:20) Shift in research focus to studying brain development in infants: Exploring the critical early phases of brain development and the impact of experience on neural circuits.

(00:16:40) Pokemon, Brain Representation, and Perception: The surprising findings on the continued development of word and face processing regions. Discovering the extended period of specialization and plasticity in these brain areas.

(00:19:10) Unexpected decline in specialization for body parts, particularly hands: Examining the trade-off between different cognitive abilities as brain regions specialize.

(00:22:00) Understanding the potential impact of experience on brain organization: Examining how environmental factors shape the neural pathways and cognitive capabilities.

(00:25:00) Investigating the influence of Pokemon on brain representation and perception: Analyzing the effects of exposure to specific visual stimuli on brain organization.

(00:27:15) The unique characteristics of Pokemon stimuli: Exploring how visual features, animacy, and stimulus size affect brain responses.

(00:29:00) Specificity of brain representation for Pokemons: Uncovering whether the brain develops distinct neural pathways for Pokemon stimuli.

(00:31:45) Comparing the effects of word learning: Understanding the potential trade-offs in brain specialization.

(00:32:45) Technical challenges in studying infant's brains: Discussing the need for new tools and analysis methods to study developing brains.

Connect With Us:

Episode Transcripts >>> The Future of Everything Website

Connect with Russ >>> Threads or Twitter/X

Connect with School of Engineering >>> Twitter/X

Dr. Geoffrey Hinton recently retired from Google, saying that he wanted to be able to speak freely about his concerns regarding artificial intelligence without having to consider the impact to his employer. So what is the Godfather of AI worried about? 

See omnystudio.com/listener for privacy information.

Neural networks are complex. Mindtech makes tools that help create vision data sets for training these neural nets. In this week’s Embedded Executive podcast with Chris Longstaff, Vice President of Product Management at Mindtech, I discussed what an engineer would do with the data set once in-hand.