Dissociative identity disorderDissociative identity disorder (DID), formerly known as multiple personality disorder, split personality disorder or dissociative personality disorder, is a member of the family of dissociative disorders classified by the DSM-5, DSM-5-TR, ICD-10, ICD-11, and Merck Manual for diagnosis. It remains a controversial diagnosis, despite rigorous study in the scientific literature since 1975. Dissociative identity disorder is characterized by the presence of at least two distinct and relatively enduring personality states.
Binding problemThe consciousness and binding problem is the problem of how objects, background and abstract or emotional features are combined into a single experience. The binding problem refers to the overall encoding of our brain circuits for the combination of decisions, actions, and perception. It is considered a "problem" due to the fact that no complete model exists. The binding problem can be subdivided into four problems of perception, used in neuroscience, cognitive science and philosophy of mind.
IndigoIndigo is a deep color close to the color wheel blue (a primary color in the RGB color space), as well as to some variants of ultramarine, based on the ancient dye of the same name. The word "indigo" comes from the Latin word indicum, meaning "Indian", as the dye was originally exported to Europe from India. It is traditionally regarded as a color in the visible spectrum, as well as one of the seven colors of the rainbow: the color between blue and violet; however, sources differ as to its actual position in the electromagnetic spectrum.
Recurrent neural networkA recurrent neural network (RNN) is one of the two broad types of artificial neural network, characterized by direction of the flow of information between its layers. In contrast to uni-directional feedforward neural network, it is a bi-directional artificial neural network, meaning that it allows the output from some nodes to affect subsequent input to the same nodes. Their ability to use internal state (memory) to process arbitrary sequences of inputs makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.
Artificial neural networkArtificial neural networks (ANNs, also shortened to neural networks (NNs) or neural nets) are a branch of machine learning models that are built using principles of neuronal organization discovered by connectionism in the biological neural networks constituting animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection, like the synapses in a biological brain, can transmit a signal to other neurons.
