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  2. BCM theory - Wikipedia

    en.wikipedia.org/wiki/BCM_theory

    Bienenstock–Cooper–Munro (BCM) theory, BCM synaptic modification, or the BCM rule, named after Elie Bienenstock, Leon Cooper, and Paul Munro, is a physical theory of learning in the visual cortex developed in 1981.

  3. Synaptic weight - Wikipedia

    en.wikipedia.org/wiki/Synaptic_weight

    For the basic pyramidal neuron, the input signal is carried by the axon, which releases neurotransmitter chemicals into the synapse which is picked up by the dendrites of the next neuron, which can then generate an action potential which is analogous to the output signal in the computational case.

  4. Synaptic plasticity - Wikipedia

    en.wikipedia.org/wiki/Synaptic_plasticity

    Two molecular mechanisms for synaptic plasticity involve the NMDA and AMPA glutamate receptors. Opening of NMDA channels (which relates to the level of cellular depolarization) leads to a rise in post-synaptic Ca 2+ concentration and this has been linked to long-term potentiation, LTP (as well as to protein kinase activation); strong depolarization of the post-synaptic cell completely ...

  5. images.huffingtonpost.com

    images.huffingtonpost.com/2012-08-30-3258_001.pdf

    Created Date: 8/30/2012 4:52:52 PM

  6. Neuron (software) - Wikipedia

    en.wikipedia.org/wiki/Neuron_(software)

    Synapse point processes are distinct for their ability to model stimulation intensities that vary non-linearly across time. These can be placed on any segment of any section of a built cell, individual or network, and their precise values, including amplitude and duration of stimulation, delay time of activation in a run and time decay ...

  7. Superforecasting: The Art and Science of Prediction - Wikipedia

    en.wikipedia.org/wiki/Superforecasting:_The_Art...

    The Economist reports that superforecasters are clever (with a good mental attitude), but not necessarily geniuses. It reports on the treasure trove of data coming from The Good Judgment Project, showing that accurately selected amateur forecasters (and the confidence they had in their forecasts) were often more accurately tuned than experts. [1]

  8. Bitcoin price prediction model running ‘like clockwork’ as ...

    www.aol.com/news/bitcoin-price-prediction-model...

    One of the most notable price prediction models that uses halving cycles as its basis is the Stock-to-Flow (S2F) model created by the pseudonymous Dutch analyst PlanB.

  9. Nonlinear autoregressive exogenous model - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_autoregressive...

    In time series modeling, a nonlinear autoregressive exogenous model (NARX) is a nonlinear autoregressive model which has exogenous inputs. This means that the model relates the current value of a time series to both: past values of the same series; and