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Brain mapping is a set of neuroscience techniques predicated on the mapping of (biological) quantities or properties onto spatial representations of the (human or non-human) brain resulting in maps.
Standard brain maps such as the Talairach-Tournoux or templates from the Montréal Neurological Institute (MNI) allow researchers from across the world to compare their results. Images can be smoothed to make the data less noisy (similar to the 'blur' effect used in some image-editing software) by which voxels are averaged with their neighbours ...
A 2-D model of cortical sensory homunculus. A cortical homunculus (from Latin homunculus 'little man, miniature human' [1] [2]) is a distorted representation of the human body, based on a neurological "map" of the areas and portions of the human brain dedicated to processing motor functions, and/ or sensory functions, for different parts of the body.
An example of this would be the map in primary visual cortex (V1). Second-order representations, also known as a field discontinuity map, are maps that are organized such that it appears that a discontinuity has been introduced in either the visual field or the retina. The maps in V2 and other extrastriate cortex are second-order ...
There are numerous types of research methods used when conducting neurological research, all with the purpose of trying to view the activity that occurs within the brain during a certain activity or behavior.
An example that identified 10 large-scale brain networks from resting state fMRI activity through independent component analysis [15]. Because brain networks can be identified at various different resolutions and with various different neurobiological properties, there is currently no universal atlas of brain networks that fits all circumstances. [16]
Cognitive maps are a function of the working brain that humans and animals use for movement in a new environment. They help us in recognizing places, computing directions and distances, and in critical-thinking on shortcuts. They support us in wayfinding in an environment, and act as blueprints for new technology.
Many theoretical studies ask how the nervous system could implement Bayesian algorithms. Examples are the work of Pouget, Zemel, Deneve, Latham, Hinton and Dayan. George and Hawkins published a paper that establishes a model of cortical information processing called hierarchical temporal memory that is based on Bayesian network of Markov chains ...