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Patent US9451883
Issued 2016-09-27
Apparatus And Method For Decoding Sensory And Cognitive Information From Brain Activity
Decoding and reconstructing a subjective perceptual or cognitive experience is described. A first set of brain activity data produced in response to a first brain activity stimulus is acquired from a subject using a brain imaging device. An encoding model is used to convert the brain activity data into a corresponding set of predicted response values. A second set of brain activity data produced in response to a second brain activity stimulus is acquired from a subject and decoded using a decoding distribution derived from the encoding model, and the probability the second set of brain activity data corresponds to said predicted response values is determined. The second set of brain activity stimuli is then reconstructed based on the probability of correspondence between the second set of brain activity data and the predicted response values.
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- 1. A method for decoding and reconstructing a subjective perceptual or cognitive experience, the method comprising:
acquiring a first set of brain activity data from a first subject, wherein said first set of brain activity data is acquired using a first brain imaging device, and wherein said first set of brain activity data is produced in response to a first set of brain activity stimuli; converting said first set of brain activity data into a corresponding set of encoding model parameter values for each of one or more linearizing feature spaces; acquiring a second set of brain activity data from said first subject or a second subject, wherein said second set of brain activity data is acquired using a second brain imaging device, and wherein said second set of brain activity data is produced in response to a second set of brain activity stimuli; creating a decoding database comprising one or more items; generating a corresponding set of predicted brain activity signals for each of the one or more items in the decoding database using the set of encoding model parameter values corresponding to each of the one or more linearizing features spaces; determining a probability for each of the one or more items that said second set of brain activity data corresponds to said set of predicted brain activity signals corresponding to the item; selecting at least one item from the decoding database based on the probability determined for each of the one or more items in the decoding database; and producing a reconstructed set of brain activity stimuli based on the selected at least one item.
- 13. An apparatus for decoding and reconstructing a subjective perceptual or cognitive experience, the apparatus comprising:
(a) a processor: and (b) programming executable on the processor for performing a method comprising: acquiring a first set of brain activity data from a first subject, wherein said first set of brain activity data is acquired using a first brain imaging device, and wherein said first set of brain activity data is produced in response to a first set of brain activity stimuli; converting said first set of brain activity data into a corresponding set of encoding model parameter values for each of one or more linearizing feature spaces; acquiring a second set of brain activity data from said first subject or a second subject, wherein said second set of brain activity data is acquired using a second brain imaging device, and wherein said second set of brain activity data is produced in response to a second set of brain activity stimuli; obtaining a plurality of stimulus items; generating a corresponding set of predicted brain activity signals for each of the plurality of stimulus items using the set of encoding model parameter values corresponding to each of the one or more linearizing feature spaces; determining a probability for each of the plurality of stimulus items that said second set of brain activity data corresponds to said set of predicted brain activity signals corresponding to the stimulus item; selecting one or more of the plurality of stimulus items based on the probability determined for each of the plurality of stimulus items; and producing a reconstructed set of brain activity stimuli based on the selected one or more stimulus items.
- 21. A method comprising:
obtaining training data comprising one or more training stimuli and training brain activity data, the training brain activity data representing brain activity elicited in at least one first subject by each of the one or more training stimuli; transforming each of the one or more training stimuli into one or more training feature spaces to obtain a set of training feature spaces; calculating a plurality of encoding model parameter values that model a linear relationship between the set of training feature spaces and the training brain activity data; obtaining measured brain activity data representing brain activity elicited in at least one second subject by a particular stimulus; obtaining a plurality of candidate stimulus items; transforming each of the plurality of candidate stimulus items into a corresponding feature space set comprising one or more candidate feature spaces; generating predicted brain activity data for each of the plurality of candidate stimulus items using the feature space set that corresponds to the candidate stimulus item and the set of encoding model parameter values; comparing the measured brain activity data to the predicted brain activity data generated for each of the plurality of candidate stimulus items; selecting one or more of the plurality of candidate stimulus items based on the comparison; and producing a reconstructed stimulus based on the selected one or more candidate stimulus items.
