Roger Penrose
Sir Roger Penrose OM FRS (born 8 August 1931), is an English mathematical physicist, mathematician and philosopher of science. He is the Emeritus Rouse Ball Professor of Mathematics at the Mathematical Institute of the University of Oxford, as well as an Emeritus Fellow of Wadham College. Penrose is known for his work in mathematical physics, in particular for his contributions to general relativity and cosmology. He has received a number of prizes and awards, including the 1988 Wolf Prize for physics, which he shared with Stephen Hawking for their contribution to our understanding of the universe.[1] Early life and academia[edit] As a student in 1954, Penrose was attending a conference in Amsterdam when by chance he came across an exhibition of Escher's work. In 1967, Penrose invented the twistor theory which maps geometric objects in Minkowski space into the 4-dimensional complex space with the metric signature (2,2). A Penrose tiling Later Activity[edit] An earlier universe[edit] Prof.
Neurophysics
Neurophysics (or neural physics) is the branch of biophysics dealing with the nervous system including the brain and the spinal cord and the nerves. The term is a portmanteau of neurology and physics, to represent an emerging science which investigates the fundamentally physical basis for the brain, hence the basis for cognition. The field covers a wide spectrum of phenomena from molecular and cellular mechanisms to techniques to measure and influence the brain and to theories of brain function. It can be viewed as an approach to neuroscience that is based on solid understanding of the fundamental laws of nature. See also[edit] Books[edit] External links[edit]
Radioactive decay
Alpha decay is one example type of radioactive decay, in which an atomic nucleus emits an alpha particle, and thereby transforms (or 'decays') into an atom with a mass number decreased by 4 and atomic number decreased by 2. Many other types of decays are possible. Radioactive decay, also known as nuclear decay or radioactivity, is the process by which a nucleus of an unstable atom loses energy by emitting particles of ionizing radiation. Radioactive decay is a stochastic (i.e. random) process at the level of single atoms, in that, according to quantum theory, it is impossible to predict when a particular atom will decay.[1] However, the chance that a given atom will decay is constant over time. There are many different types of radioactive decay (see table below). The first decay processes to be discovered were alpha decay, beta decay, and gamma decay. By contrast, there are radioactive decay processes that do not result in transmutation. Discovery and history[edit] Types of decay[edit]
Computational neuroscience
Computational neuroscience is the study of brain function in terms of the information processing properties of the structures that make up the nervous system.[1] It is an interdisciplinary science that links the diverse fields of neuroscience, cognitive science, and psychology with electrical engineering, computer science, mathematics, and physics. Computational neuroscience is distinct from psychological connectionism and from learning theories of disciplines such as machine learning, neural networks, and computational learning theory in that it emphasizes descriptions of functional and biologically realistic neurons (and neural systems) and their physiology and dynamics. These models capture the essential features of the biological system at multiple spatial-temporal scales, from membrane currents, proteins, and chemical coupling to network oscillations, columnar and topographic architecture, and learning and memory. History[edit] Major topics[edit] Single-neuron modeling[edit]
Quantum cognition
Quantum cognition is an emerging field which applies the mathematical formalism of quantum theory to model cognitive phenomena such as information processing by the human brain, decision making, human memory, concepts and conceptual reasoning, human judgment, and perception.[1][2] [3][4] The field clearly distinguishes itself from the quantum mind as it is not reliant on the hypothesis that there is something micro-physical quantum mechanical about the brain. Quantum cognition is based on the quantum-like paradigm[5][6] or generalized quantum paradigm [7] or quantum structure paradigm [8] that information processing by complex systems such as the brain, taking into account contextual dependence of information and probabilistic reasoning, can be mathematically described in the framework of quantum information and quantum probability theory. Main subjects of research[edit] Quantum-like models of information processing ("quantum-like brain")[edit] Decision making[edit] Human memory[edit]
Neural network
An artificial neural network is an interconnected group of nodes, akin to the vast network of neurons in a brain. Here, each circular node represents an artificial neuron and an arrow represents a connection from the output of one neuron to the input of another. For example, a neural network for handwriting recognition is defined by a set of input neurons which may be activated by the pixels of an input image. After being weighted and transformed by a function (determined by the network's designer), the activations of these neurons are then passed on to other neurons. This process is repeated until finally, an output neuron is activated. This determines which character was read. Like other machine learning methods - systems that learn from data - neural networks have been used to solve a wide variety of tasks that are hard to solve using ordinary rule-based programming, including computer vision and speech recognition. Background[edit] History[edit] Farley and Wesley A. Models[edit] or both
Hard problem of consciousness
The existence of a "hard problem" is controversial and has been disputed by some philosophers.[4][5] Providing an answer to this question could lie in understanding the roles that physical processes play in creating consciousness and the extent to which these processes create our subjective qualities of experience.[3] Several questions about consciousness must be resolved in order to acquire a full understanding of it. These questions include, but are not limited to, whether being conscious could be wholly described in physical terms, such as the aggregation of neural processes in the brain. If consciousness cannot be explained exclusively by physical events, it must transcend the capabilities of physical systems and require an explanation of nonphysical means. For philosophers who assert that consciousness is nonphysical in nature, there remains a question about what outside of physical theory is required to explain consciousness. Formulation of the problem[edit] Easy problems[edit] T.H.
Transkranielle Magnetstimulation – Wikipedia
De transkranielle Magnetstimulation De transkranielle Magnetstimulation, kuaz TMS, is a ned-invasive medizinische Methode, de wo zua Diagnostik und Therapie vawendt wead. Mit da Huif vo stoakn Magnetfäida wean Tei vom Hian stimuliat oda ghemmt. De Technologie wead zua Diagnostik und Behondlung vo Tinnitus, Apoplexie, Epilepsie, Parkinson-Kronkheit und fia psychiatirische Sterunga (wia Depression und Schizophrenie) eingsetzt. Bei da repetitiven transkraniellen Magnetstimulation (rTMS) wean duach stoake magnetische Wejn s Hian und seine Neavnzejn woiweis zua Aktivität und Entsponnung stimuliat. Ois ned-invasive, medikamentnfreie Therapie zäid de TMS zu de Natuaheimethodn. Beleg[VE | Weakln] Hochspringen ↑ Was ist rTMS? Im Netz[VE | Weakln]
