Computational neuroscience, neural network models of perceptual and cognitive processes including cortical and hippocampal memory systems, spatial memory, semantic memory organization, frontal executive control of memory.
Builds mathematical and computational models of neural processing, with a particular emphasis on representation and learning. The main focus is on reinforcement learning and unsupervised learning, covering the ways that animals come to choose appropriate actions in the face of rewards and punishments, and the ways and goals of the process by which they come to form neural representations of the world. The models are informed and constrained by neurobiological, psychological and ethological data.
Research at the lab concentrates on trying to understand how we organize sensory information in order to build meaningful representations of objects, sounds and surface textures in the environment.
The laboratory addresses a variety of basic issues in the analysis and representation of visual imagery. 1) construction of mathematical theories for the representation of visual information, 2) development of functional models for biological visual processing, and 3) creation of novel algorithms for image processing and computer vision applications.
Features a wealth of background knowledge about learning and memory (with an emphasis on associative learning) together with published and unpublished original research on the fruitfly Drosophila and the sea-slug Aplysia.
Focus in visual neuroscience, approached using computational modeling, human psychophysics and functional neuroimaging. In particular, studies on visual attention in primates.
He is interested in the mechanisms that have led to neural tissue being able to control complex organisms. Photography is another artistic way of slicing the timeline and recombining it for analysis.
Goal is to understand the structure, function and plasticity of the mammalian visual system. Uses a combination of electrophysiological, psychophysical, and computational techniques to analyze how visual information is coded in the spiking activity of neurons in the visual cortex.
Our goal is to devise learning rules that can develop a feature-detector hierarchy similar to that proposed by Fukushima et al. (1983) in order to recognize objects independent of location, scale, or orientation.
The Purves laboratory is studying visual perception and its neurobiological underpinnings. Shows a lot of interactive demos of psychophysical effects and optical illusions.
This lab at Michigan State University is researching the hormonal modulation of the developing and adult nervous system that leads to changes in behavior.
Relationship between the autonomic nervous system and the vascular system, mechanisms underlying disease in human arteries, cerebral and coronary arteries. Relevant to clinical medicine. Saphenous vein for CABG, and neurodegenerative diseases. University College London.
What are the mechanisms of learning and memory? How are actions and experiences encoded in the activity patterns of neurons in the brain? In the Wilson Lab we are addressing these questions through multineuron recording from the hippocampus and other brain areas of rats and mice during active behavior.
Goal is to develop methods for evolving embedded intelligent systems, such as Autonomous Robots, capable of adaptation to physical environments. Interested in artificial sensory-motor systems that display life-like properties and are based upon bio-inspired mechanisms (genetics, cellular biology, neural networks, bio-morphic engineering).
Digital signal processing (DSP) is applied to the analysis of electro-physiological signals (such as EEG), with emphasis on human brain electrical activity. From the State Committee for Scientific Research; Warsaw, Poland.
The lab investigates the cellular and molecular mechanisms used by neurons to decode synaptic and electrical activities that propagate through neural circuits.
Involved in developing independent component analysis (ICA). Page supplies papers and code for reproducing experiments. Addresses generative model based vision and statistics of natural scenes.
Studies processing in visual neurons of Drosophila as well as effects of molecular components on neural computations and sensory adaptation. Influence of rearing and environment on signalling is studied and signalling during natural stimulation is analyzed and modeled.
Neuroscientist doing both experiments and theory at the Institute of Neurology, London. Specializes in Bayesian Statistics and Statistics of Natural scenes. Applications to Visual, Somatosensory, Auditory and Motor problems.
Women who are contributing to our knowledge of neuroscience today including Ellen Kuwana, Frances Mary Ashcroft, Leslie P. Tolbert, Rae Nishi, Christine H. Block and Rosamund Langston.
The Neural Imaging Lab uses cellular imaging techniques in combination with electrophysiology and genetic approaches to study local biochemical signalling at excitatory synapses of different type of central neurons.
Curriculum vitae, lists of skills, publications, participations at conferences and a description of research into the development of the midbrain and hindbrain.
The Frisen Lab at the Karolinska Institute in Sweden is studying the development of the nervous system and the continued neurogenesis from neural stem cells in the adult.
Research at the Institute for Neuroinformatics in Zurich, Switzerland centers on using neuromorphic design principles to make practical vision sensors.
Ed Adelson focuses on topics in human and machine vision, including mid-level vision, lightness perception, motion analysis, perceptual organization, and image data compression.