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Henry Markram builds a brain in a supercomputer

Henry Markram builds a brain in a supercomputer

Neuron All neurons are electrically excitable, maintaining voltage gradients across their membranes by means of metabolically driven ion pumps, which combine with ion channels embedded in the membrane to generate intracellular-versus-extracellular concentration differences of ions such as sodium, potassium, chloride, and calcium. Changes in the cross-membrane voltage can alter the function of voltage-dependent ion channels. If the voltage changes by a large enough amount, an all-or-none electrochemical pulse called an action potential is generated, which travels rapidly along the cell's axon, and activates synaptic connections with other cells when it arrives. Neurons do not undergo cell division. Overview[edit] A neuron is a specialized type of cell found in the bodies of all eumetozoans. Although neurons are very diverse and there are exceptions to nearly every rule, it is convenient to begin with a schematic description of the structure and function of a "typical" neuron. Polarity[edit]

Blue Brain Project Functional magnetic resonance imaging Researcher checking fMRI images Functional magnetic resonance imaging or functional MRI (fMRI) is a functional neuroimaging procedure using MRI technology that measures brain activity by detecting associated changes in blood flow.[1] This technique relies on the fact that cerebral blood flow and neuronal activation are coupled. When an area of the brain is in use, blood flow to that region also increases. The primary form of fMRI uses the Blood-oxygen-level dependent (BOLD) contrast,[2] discovered by Seiji Ogawa. The procedure is similar to MRI but uses the change in magnetization between oxygen-rich and oxygen-poor blood as its basic measure. This measure is frequently corrupted by noise from various sources and hence statistical procedures are used to extract the underlying signal. FMRI is used both in the research world, and to a lesser extent, in the clinical world. Overview[edit] History[edit] Three studies in 1992 were the first to explore using the BOLD contrast in humans.

Bob the Blue Brain Builder Can we build an artificial brain in silicon? Regardless of whether it’s a good idea or not (insert paranoid fear of unleashing skynet here) is it even possible? I think it is, not that I know how, but maybe I’m not enough of a mad scientist. This is where I introduce our modern Frankenstein, one Professor Henry Markram and his Blue Brain Project. He has claimed that by 2018 his team will have created the world’s first artificial conscious and intelligent mind. That’s no small claim. Let’s start by looking at the plus side. So he’s no fringe lunatic, but does he have the resources to have a serious go at building an artificial brain? He’s got the street cred, he’s got the cash, he’s ev en got a ‘bad-ass’ crew (Michael Hines and Ted Carnevale, the world leaders in neural simulation are helping program his IBM super-cruncher). Almost certainly not. General principles are sorely missing in the neuroscience field. Is the Blue Brain therefore a monstrous white elephant? From

Diffusion MRI Diffusion MRI (or dMRI) is a magnetic resonance imaging (MRI) method which came into existence in the mid-1980s.[1][2][3] It allows the mapping of the diffusion process of molecules, mainly water, in biological tissues, in vivo and non-invasively. Molecular diffusion in tissues is not free, but reflects interactions with many obstacles, such as macromolecules, fibers, membranes, etc. Water molecule diffusion patterns can therefore reveal microscopic details about tissue architecture, either normal or in a diseased state. The first diffusion MRI images of the normal and diseased brain were made public in 1985.[4][5] Since then, diffusion MRI, also referred to as diffusion tensor imaging or DTI (see section below) has been extraordinarily successful. Its main clinical application has been in the study and treatment of neurological disorders, especially for the management of patients with acute stroke. Diffusion[edit] Given the concentration and flux where D is the diffusion coefficient. .

Brain Atlas - Introduction The central nervous system (CNS) consists of the brain and the spinal cord, immersed in the cerebrospinal fluid (CSF). Weighing about 3 pounds (1.4 kilograms), the brain consists of three main structures: the cerebrum, the cerebellum and the brainstem. Cerebrum - divided into two hemispheres (left and right), each consists of four lobes (frontal, parietal, occipital and temporal). The outer layer of the brain is known as the cerebral cortex or the ‘grey matter’. It covers the nuclei deep within the cerebral hemisphere e.g. the basal ganglia; the structure called the thalamus, and the ‘white matter’, which consists mostly of myelinated axons. – closely packed neuron cell bodies form the grey matter of the brain. Cerebellum – responsible for psychomotor function, the cerebellum co-ordinates sensory input from the inner ear and the muscles to provide accurate control of position and movement. Basal Ganglia Thalamus and Hypothalamus Ventricles Limbic System Reticular Activating System Neurons Glia

Electroencephalography Simultaneous video and EEG recording of two guitarists improvising. Electroencephalography (EEG) is the recording of electrical activity along the scalp. EEG measures voltage fluctuations resulting from ionic current flows within the neurons of the brain.[1] In clinical contexts, EEG refers to the recording of the brain's spontaneous electrical activity over a short period of time, usually 20–40 minutes, as recorded from multiple electrodes placed on the scalp. EEG is most often used to diagnose epilepsy, which causes obvious abnormalities in EEG readings.[2] It is also used to diagnose sleep disorders, coma, encephalopathies, and brain death. Derivatives of the EEG technique include evoked potentials (EP), which involves averaging the EEG activity time-locked to the presentation of a stimulus of some sort (visual, somatosensory, or auditory). History[edit] Hans Berger In 1934, Fisher and Lowenback first demonstrated epileptiform spikes. Source of EEG activity[edit] Clinical use[edit]

Thanks for the context! I find this a very fascinating field. You seem quite knowledgeable on the subject: any other sites you would recommend to follow this up? by cassius Nov 21

Henry Markram simulates a brain's neurons and the neurons' connections (ie. a 'connectome' cf. "Sebastian Seung: i am my connectome") on a supercomputer. A striking difference with AI artificial neural networks is a each neuron and its bochemistry is simulated on a processor, whereas AI uses an (over) simplified model of a few bytes as a neuron and simple caltulations (adding, multiplying) as signal exchange. Markram's technology driven approach differs from Ramachandran's low-tech (mirrors in a box) clinical approach in "Ramachandran: on your mind". by kaspervandenberg Nov 7