#neural technology

[jaesungku-blog]

CBMM envisions a world where intelligence and its emergence from brain activity is truly understood. A successful plan for realizing this vision requires integrated areas of research that are guided by a unifying theoretical foundation. The Center is engaged in six major Research Thrusts with interlocking teams and working groups: Development of Intelligence, Neural Circuits for Intelligence, Vision and Language, Social Intelligence, Theoretical Frameworks for Intelligence and Exploring Future Directions.

1. Development of Intelligence

Understanding the development of intelligence in a human infant is a key project of CBMM. This project engages the fundamental tradeoff between nature and nurture, or priors and data, and ultimately the origin of priors—how constraints are selected by evolution, encoded in genes, and instantiated in genetically wired brain circuits.

2.  Neural Circuits for Intelligence

Abstract thinking and complex problem solving constitute paradigmatic examples of computation emerging from interconnected neuronal circuits. The biological hardware represents the output of millions of years of evolution leading to neuronal circuits that provide fast, efficient, and fault-tolerant solutions to complex problems.

3.  Vision and Language

The goal is to combine vision with aspects of language and social cognition to obtain complex knowledge about the surrounding environment. To obtain full understanding of visual scenes, computational models should be able to extract from the scene any meaningful information that a human observer can extract, about actions, agents, goals, scenes and object configurations, social interactions, and more.

4.  Social Intelligence

Social cognition is at the core of human intelligence.  It is through social interactions that we learn, and it is social interactions that drove much of the evolution of the human brain. Indeed, the neural machinery of social cognition comprises a substantial proportion of the brain.

[jaesungku-blog]

[Index]

Abraham: Rebel Genius................................................. 9 Anderson: After Phrenology ....................................... 18 Arbib: From Neuron to Cognition via Computational Neuroscience ................................. IF Arbib: Language, Music, and the Brain ..................... 20 Arbib: The Handbook of Brain Theory and Neural Networks..................................................... 8 Ascoli: Trees of the Brain, Roots of the Mind.............. 6 Austin: Living Zen Remindfully................................... 12 Austin: Zen-Brain Horizons......................................... 12 Ballard: Brain Computation as Hierarchical Abstraction ............................................... 8 Berwick: Why Only Us.................................................. 20 Bolhuis: Birdsong, Speech, and Language................ 21 Christiansen: Creating Language................................ 20 Churchland: The Computational Brain, 25th Anniversary Edition.............................................. 8 Cohen: Analyzing Neural Time Series Data................ 5 Cohen: MATLAB for Brain and Cognitive Scientists... 5 Computational Psychiatry Journal................................ 2 Costandi: Neuroplasticity............................................. 23 Dayan: Theoretical Neuroscience.................................. 4 Decety: The Moral Brain.............................................. 15 Dennett: Elbow Room.................................................. 24 Dowling: Vision............................................................. 10 Durt: Embodiment, Enaction, and Culture................ 11 Engel: The Pragmatic Turn .......................................... 13 Fawcett: The Handbook of Attention........................ 18 Fedyk: The Social Turn in Moral Psychology.............. 15 Feinberg: The Ancient Origins of Consciousness ...... 26 Feynman: The Character of Physical Law ................. BC Fried: Single Neuron Studies of the Human Brain...... 4 Gazzaley: The Distracted Mind ..................................... 1 Gazzaniga: The Cognitive Neurosciences ................... 4 Gennaro: Disturbed Consciousness............................ 17 Gerrans: The Measure of Madness............................. 16 Glickstein: Neuroscience ................................................ 9 Guenther: Neural Control of Speech............................ 7 Harris: Invisible Mind .................................................. 14 Hasselmo: How We Remember................................... 23 Herculano-Houzel: The Human Advantage............... 26 Herzing: Dolphin Communication and Cognition... 21 Hutto: Evolving Enactivism.......................................... 13 Jablonka: Evolution in Four Dimensions.................... 26 Journal of Cognitive Neuroscience............................. 29 Klein: What the Body Commands .............................. 19 Koch: Consciousness..................................................... 22 Kramer: Case Studies in Neural Data Analysis............ IF Lende: The Encultured Brain....................................... 26 Lu: Visual Psychophysics............................................... 10

Luck: An Introduction to the Event-Related Potential Technique........................................................ 5 Madary: Visual Phenomenology................................. 10 Marr: Vision................................................................... 10 McCulloch: Embodiments of Mind ............................... 9 MIT CogNet................................................................... 29 Montemayor: Consciousness, Attention, and Conscious Attention ............................................. 22 Moro: Impossible Languages....................................... 21 Moro: The Boundaries of Babel.................................. 21 Musholt: Thinking about Oneself............................... 14 Nautilus Journal............................................................ 29 Network Neuroscience Journal ..................................... 3 Neural Computation Journal....................................... 29 Nikolich: Translational Neuroscience.......................... 17 Oliveira: The Digital Mind ........................................... 27 Open Mind: Discoveries in Cognitive Science Journal.. 2 Parker: Cannabinoids and the Brain .......................... 19 Pennartz: The Brain’s Representational Power ........ 22 Pessoa: The Cognitive–Emotional Brain..................... 14 Poggio: Visual Cortex and Deep Networks.................. 7 Poland: Extraordinary Science and Psychiatry........... 17 Portugal: The Least Likely Man................................... 27 Ramón y Cajal: Advice for a Young Investigator ........ 9 Ramón y Cajal: Recollections of my Life ...................... 9 Redish: Computational Psychiatry ................................ 2 Robinson: Mind in Architecture.................................. 25 Sauer: Moral Judgments as Educated Intuitions....... 16 Schneider: Brain Structure and Its Origins................... 6 Sherman: Functional Connections of Cortical Areas .. 4 Sinnott-Armstrong: Moral Psychology, Volume 5..... 15 Sporns: Discovering the Human Connectome............. 3 Sporns: Networks of the Brain...................................... 3 Stanovich: The Rationality Quotient.......................... 27 Starr: Feeling Beauty ................................................... 25 Sterling: Principles of Neural Design............................ 6 Tse: The Neural Basis of Free Will............................... 24 Varela: The Embodied Mind........................................ 11 Vartanian: Neuroscience of Creativity........................ 25 Wegner: The Illusion of Conscious Will...................... 13 Werner: The New Visual Neurosciences..................... 10 Westphal: The Mind–Body Problem........................... 13 Windt: Dreaming.......................................................... 23 Wiseman: The Myth of the Moral Brain.................... 16 Wittmann: Felt Time ................................................... 12

[jaesungku-blog]

Our lab studies how people hear. Sound is produced by events in the world, travels through the air as pressure waves, and is measured by two sensors (the ears). The brain uses signals from these sensors to infer a vast number of important things -- what someone said, their emotional state when they said it, and the whereabouts and nature of events we cannot see, to name a few. Humans make such auditory judgements hundreds of times a day, but their basis in our acoustic sensory input is often not obvious, and reflects many stages of sophisticated processing that remain poorly characterized. We seek to understand the computational basis of these impressive yet routine perceptual inferences. We hope to use our research to improve devices for assisting those whose hearing is impaired, and to design more effective machine systems for recognizing and interpreting sound, which at present perform dramatically worse in real-world conditions than do normal human listeners.

[jaesungku-blog]

Today, science and technology is at the threshold of paradigm-shifting discoveries. However, an obstacle remains: as technology grows exponentially, our understanding of the human mind does not. We are approaching an era in which the benefits of a highly technologized society won’t be fully realized unless we are able to understand how humans encode, process, retain, predict and imagine. To this end, we combine methods from computer science, neuroscience and cognitive science to explain and model how perception and cognition are realized in human and machine. Our research in Computational Neuroscience, Cognitive Computing and Computer Vision, bridges from theory to experiments to applications, accelerating the rate at which discoveries are made by solving problems through a multi-disciplinary way of thinking.

[jaesungku-blog]

Areas of research include biophysical mechanisms underlying information processing; experimental and modeling studies of the visual system; the circuitry, computational function, and modeling of the olfactory cortex; the theory of collective circuits for biological and machine computations; experimental studies of the circuitry and control of insect locomotor function; the relation between problem complexity communication, and computation in parallel machines; modeling and representation of physical objects for the general analysis of images; and the use of optical devices in parallel computational hardware.

[jaesungku-blog]

Neural engineering applies quantitative engineering principles to understand and model circuit operations in the nervous system, to determine their relationship to behavior, and to design devices to interface with this circuitry. This emerging field draws from many disciplines, including computational neuroscience, neurobiology, electrophysiology, information theory, electronics, control systems, mathematical modeling, imaging, biomaterials and tissue engineering. Theoretical and computational approaches have become critical tools in the evaluation of the nervous system. Therefore, combined experimental and theoretical approaches are most promising to understand the operation of the brain and to explain behavior by the underlying neuronal mechanisms. Many faculty of the program are currently working on these aspects with the help of a significant number of bioengineering students.

[jaesungku-blog]

Aurel A. Lazar (Co-Director), Bionet Group, Electrical Engineering Paul Sajda (Co-Director), Laboratory for Intelligent Imaging and Neural Computing, Biomedical Engineering

[jaesungku-blog]

A Brain-Computer Interface (BCI) uses electrophysiological measures of brain activity to communicate with external devices, bypassing normal neuromuscular pathways. We develop BCIs for neuroprosthetic control of advanced prosthetic limbs and restoration of motor control for amputees.

Our group focuses on signal processing techniques and developing novel cortical and myoelectric control strategies for control of prosthetic limbs using: ECoG (electrocorticography) Noninvasive EEG (electroencephalography) Local field potentials (LFP) Single and multi-unit activity Surface EMG (electromyography)