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  2. Neural coding - Wikipedia

    en.wikipedia.org/wiki/Neural_coding

    The temporal structure of a spike train or firing rate evoked by a stimulus is determined both by the dynamics of the stimulus and by the nature of the neural encoding process. Stimuli that change rapidly tend to generate precisely timed spikes [28] (and rapidly changing firing rates in PSTHs) no matter what neural coding strategy is being used ...

  3. Neural encoding of sound - Wikipedia

    en.wikipedia.org/wiki/Neural_encoding_of_sound

    The neural encoding of sound is the representation of auditory sensation and perception in the nervous system. [1] The complexities of contemporary neuroscience are continually redefined. Thus what is known of the auditory system has been continually changing.

  4. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...

  5. Autoencoder - Wikipedia

    en.wikipedia.org/wiki/Autoencoder

    An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning).An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation.

  6. Neural encoding - Wikipedia

    en.wikipedia.org/?title=Neural_encoding&redirect=no

    Language links are at the top of the page. Search. Search

  7. Neuronal ensemble - Wikipedia

    en.wikipedia.org/wiki/Neuronal_ensemble

    The rate encoding theory states that individual neurons encode behaviorally significant parameters by their average firing rates, and the precise time of the occurrences of neuronal spikes is not important. The temporal encoding theory, on the contrary, states that precise timing of neuronal spikes is an important encoding mechanism.

  8. Variational autoencoder - Wikipedia

    en.wikipedia.org/wiki/Variational_autoencoder

    The first neural network takes as input the data points themselves, and outputs parameters for the variational distribution. As it maps from a known input space to the low-dimensional latent space, it is called the encoder. The decoder is the second neural network of this model.

  9. Encoding (memory) - Wikipedia

    en.wikipedia.org/wiki/Encoding_(memory)

    These changes include new protein synthesis, the formation of new synaptic connections, and finally the activation of gene expression in accordance with the new neural configuration. [26] The encoding process has been found to be partially mediated by serotonergic interneurons, specifically in regard to sensitization as blocking these ...