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  2. Talairach coordinates - Wikipedia

    en.wikipedia.org/wiki/Talairach_coordinates

    Sagittal view of cingulate region of human brain with a Talairach grid superimposed in accordance with standard locators. Talairach coordinates, also known as Talairach space, is a 3-dimensional coordinate system (known as an 'atlas') of the human brain, which is used to map the location of brain structures independent from individual differences in the size and overall shape of the brain.

  3. Nervous system network models - Wikipedia

    en.wikipedia.org/wiki/Nervous_system_network_models

    This model is the Integrate-and-Fire (IF) model that was mentioned in Section 2.3. Closely related to IF model is a model called Spike Response Model (SRM) (Gerstner, W. (1995) [15] Pages 738-758) that is dependent on impulse function response convoluted with the input stimulus signal. This forms a base for a large number of models developed ...

  4. Network neuroscience - Wikipedia

    en.wikipedia.org/wiki/Network_neuroscience

    The utilization of graph theory in neuroscience studies has been actively applied after the discovery of functional brain networks. In graph theory, an N × N adjacency matrix (also called a connection matrix) with the elements of zero or non-zero indicates the absence or presence of a relationship between the vertices of a network with N nodes.

  5. Seq2seq - Wikipedia

    en.wikipedia.org/wiki/Seq2seq

    Shannon's diagram of a general communications system, showing the process by which a message sent becomes the message received (possibly corrupted by noise). seq2seq is an approach to machine translation (or more generally, sequence transduction) with roots in information theory, where communication is understood as an encode-transmit-decode process, and machine translation can be studied as a ...

  6. Large-scale brain network - Wikipedia

    en.wikipedia.org/wiki/Large-scale_brain_network

    As a physical system with graph-like properties, [6] a large-scale brain network has both nodes and edges and cannot be identified simply by the co-activation of brain areas. In recent decades, the analysis of brain networks was made feasible by advances in imaging techniques as well as new tools from graph theory and dynamical systems.

  7. Transduction (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Transduction_(machine...

    It will certainly struggle to build a model that captures the structure of this data. For example, if a nearest-neighbor algorithm is used, then the points near the middle will be labeled "A" or "C", even though it is apparent that they belong to the same cluster as the point labeled "B", compare semi-supervised learning.

  8. Biological neuron model - Wikipedia

    en.wikipedia.org/wiki/Biological_neuron_model

    The theta model, or Ermentrout–Kopell canonical Type I model, is mathematically equivalent to the quadratic integrate-and-fire model which in turn is an approximation to the exponential integrate-and-fire model and the Hodgkin-Huxley model. It is called a canonical model because it is one of the generic models for constant input close to the ...

  9. Neural coding - Wikipedia

    en.wikipedia.org/wiki/Neural_coding

    The brain must obtain a large quantity of information based on a relatively short neural response. Additionally, if low firing rates on the order of ten spikes per second must be distinguished from arbitrarily close rate coding for different stimuli, then a neuron trying to discriminate these two stimuli may need to wait for a second or more to ...