Abstract: A method for training vibrotactile speech perception in the absence of auditory speech can comprise selecting a first word, generating a first control signal configured to cause at least one vibrotactile transducer to vibrate against a person's body with a first vibration pattern based on the first word, sampling a second word, generating a second control signal configured to cause a vibrotactile transducer to vibrate against the person's body with a second vibration pattern based on the second word, and presenting a comparison between the first word and the second word to the person. An apparatus for training vibrotactile speech perception can comprise array of vibrotactile transducers can be in contact with the person's body. The array of vibrotactile transducers can replicate a vibration pattern based on one or more spoken words.

Abstract: A method for training vibrotactile speech perception in the absence of auditory speech includes selecting a first word, generating a first control signal configured to cause at least one vibrotactile transducer to vibrate against a person's body with a first vibration pattern based on the first word, sampling a second word spoken by the person, generating a second control signal configured to cause at least one vibrotactile transducer to vibrate against the person's body with a second vibration pattern based on the sampled second word, and presenting a comparison between the first word and the second word to the person. An array of vibrotactile transducers can be in contact with the person's body.

Abstract: A method for training vibrotactile speech perception in the absence of auditory speech can comprise selecting a first word, generating a first control signal configured to cause at least one vibrotactile transducer to vibrate against a person's body with a first vibration pattern based on the first word, sampling a second word spoken by the person, generating a second control signal configured to cause at least one vibrotactile transducer to vibrate against the person's body with a second vibration pattern based on the sampled second word, and presenting a comparison between the first word and the second word to the person. An array of vibrotactile transducers can be in contact with the person's body.

Abstract: Provided herein are methods related to identifying an early, asymptomatic (prodromal) stage of a neurodegenerative disease or identifying a subject with a symptomatic neurodegenerative disease, including, for example, mild cognitive impairment (MCI), Alzheimer's Disease (AD), or HIV-associated neurocognitive disorder (HAND), using functional MRI data from the subject. Methods are also provided for treating a subject identified with the methods taught herein and for modifying or selecting treatment based on the results of fMRI. Methods are also available for staging neurodegenerative disease and for identifying agents useful in treating them.

Abstract: Provided herein are methods related to identifying an early, asymptomatic (prodromal) stage of a neurodegenerative disease or identifying a subject with a symptomatic neurodegenerative disease, including, for example, mild cognitive impairment (MCI), Alzheimer's Disease (AD), or HIV-associated neurocognitive disorder (HAND), using functional MRI data from the subject. Methods are also provided for treating a subject identified with the methods taught herein and for modifying or selecting treatment based on the results of fMRI. Methods are also available for staging neurodegenerative disease and for identifying agents useful in treating them.

Abstract: An artificial visual recognition system and method employ a digital processor and a model executed by the digital processor. The model has a loose hierarchy of layers. Each layer, from a lowest hierarchy level to a top level, provides relatively increasing selectivity and invariance of the input image. The hierarchy allows bypass routes between layers. On output, the model produces feature recognition and classification of an object in the input image. In some embodiments, windowing means provide windows of the input image to the model, and the model responds to shape-based objects in the input image. In another feature, segmenting means segment the input image and enables the model to determine texture-based objects in the input image.

Abstract: An artificial visual recognition system and method employ a digital processor and a model executed by the digital processor. The model has a loose hierarchy of layers. Each layer, from a lowest hierarchy level to a top level, provides relatively increasing selectivity and invariance of the input image. The hierarchy allows bypass routes between layers. On output, the model produces feature recognition and classification of an object in the input image. In some embodiments, windowing means provide windows of the input image to the model, and the model responds to shape-based objects in the input image. In another feature, segmenting means segment the input image and enables the model to determine texture-based objects in the input image.