Abstract: A method for providing personalized content via a brain computer interface. The method includes training, in a first time window, a calibration model by: providing, via the brain computer interface, stimuli to the user; measuring neural signals of the user including responses to the stimuli; extracting features from the neural signals that temporally align with the stimuli; and training the calibration model with the features and the stimuli. The method includes measuring, in a second time window, neural signals associated with the user intending an input to the brain computer interface; extracting features from the neural signals; applying the calibration model to the features to detect the input intended by the user via the brain computer interface; and presenting digital content based on the detected input.

Abstract: A method and system for providing a user with virtual objects within an environment, characterizing interactions with the virtual objects using a brain computer interface, and modulating features of the virtual objects based upon improved classifiers associated with the interactions. The method and system can be used to rapidly customize virtual objects to a specific user in applications related to increasing engagement with traditional and new media content, virtual and augmented reality products, streamlining interactions with input devices in digital and physical environments, providing user authentication tools, providing more secure cybersecurity features, and delivering tailored content to users.

Abstract: A method for providing a brain computer interface that includes detecting a neural signal of a user in response to a calibration session having a time-locked component and a spontaneous component; generating a user-specific calibration model based on the neural signal; prompting the user to undergo a verification session, the verification session having a time-locked component and a spontaneous component; detecting a neural signal contemporaneously with delivery of the verification session; generating an output of the user-specific calibration model from the neural signal; based upon a comparison operation between processed outputs, determining an authentication status of the user; and performing an authenticated action.

Abstract: A method and system for providing a user with virtual objects within an environment, characterizing interactions with the virtual objects using a brain computer interface, and modulating features of the virtual objects based upon improved classifiers associated with the interactions. The method and system can be used to rapidly customize virtual objects to a specific user in applications related to increasing engagement with traditional and new media content, virtual and augmented reality products, streamlining interactions with input devices in digital and physical environments, providing user authentication tools, providing more secure cybersecurity features, and delivering tailored content to users.

Abstract: A method and system for generating an optimal audio stimulus for achieving a target brain state value for a brain state. The method and system can be used to generate one or more brain state models which can decode brain activity signals to predict brain state values. The brain state models can be applied to brain activity signals captured while users are performing tasks with an audio stimulus. Audio features of the audio stimulus can be extracted. An audio-brain model can be trained on the predicted brain state values and the audio features. From the trained audio-brain model, the optimal audio stimulus can be generated.

Abstract: A method and system for providing a user with virtual objects within an environment, characterizing interactions with the virtual objects using a brain computer interface, and modulating features of the virtual objects based upon improved classifiers associated with the interactions. The method and system can be used to rapidly customize virtual objects to a specific user in applications related to increasing engagement with traditional and new media content, virtual and augmented reality products, streamlining interactions with input devices in digital and physical environments, providing user authentication tools, providing more secure cybersecurity features, and delivering tailored content to users.

Abstract: A method for providing a brain computer interface that includes detecting a neural signal of a user in response to a calibration session having a time-locked component and a spontaneous component; generating a user-specific calibration model based on the neural signal; prompting the user to undergo a verification session, the verification session having a time-locked component and a spontaneous component; detecting a neural signal contemporaneously with delivery of the verification session; generating an output of the user-specific calibration model from the neural signal; based upon a comparison operation between processed outputs, determining an authentication status of the user; and performing an authenticated action.

Abstract: A method for providing a brain computer interface that includes detecting a neural signal of a user in response to a calibration session having a time-locked component and a spontaneous component; generating a user-specific calibration model based on the neural signal; prompting the user to undergo a verification session, the verification session having a time-locked component and a spontaneous component; detecting a neural signal contemporaneously with delivery of the verification session; generating an output of the user-specific calibration model from the neural signal; based upon a comparison operation between processed outputs, determining an authentication status of the user; and performing an authenticated action.

Abstract: The invention(s) described relate generally to synthetic brain models implementing computer operations that are configured to understand human thoughts and feelings and modulate content accordingly, with the aim of providing better, more personalized service (e.g., in the context of entertainment, training, health, security, etc.). The empathic computing system executing the synthetic brain model(s) described brings utility to evaluation of digital content experiences (e.g., involving mixed media formats) provided to users in their daily lives (e.g., with respect to audio content, with respect to visual content, with respect to content of other formats, with respect to connected home applications, with respect to AR/VR device applications, with respect to automotive technology applications, etc.).

Abstract: A method for creating brain-machine interface based on received and filtered brain signals from a subject, classifying the filtered signals to classes of brain states, detecting one brain state from the classified brain states and executing by a machine a command that corresponds to the detected state.

Abstract: A method and system for providing a user with virtual objects within an environment, characterizing interactions with the virtual objects using a brain computer interface, and modulating features of the virtual objects based upon improved classifiers associated with the interactions. The method and system can be used to rapidly customize virtual objects to a specific user in applications related to increasing engagement with traditional and new media content, virtual and augmented reality products, streamlining interactions with input devices in digital and physical environments, providing user authentication tools, providing more secure cybersecurity features, and delivering tailored content to users.

Abstract: A method for providing a brain computer interface that includes detecting a neural signal of a user in response to a calibration session having a time-locked component and a spontaneous component; generating a user-specific calibration model based on the neural signal; prompting the user to undergo a verification session, the verification session having a time-locked component and a spontaneous component; detecting a neural signal contemporaneously with delivery of the verification session; generating an output of the user-specific calibration model from the neural signal; based upon a comparison operation between processed outputs, determining an authentication status of the user; and performing an authenticated action.

Abstract: A method for providing a brain computer interface that includes detecting a neural signal of a user in response to a calibration session having a time-locked component and a spontaneous component; generating a user-specific calibration model based on the neural signal; prompting the user to undergo a verification session, the verification session having a time-locked component and a spontaneous component; detecting a neural signal contemporaneously with delivery of the verification session; generating an output of the user-specific calibration model from the neural signal; based upon a comparison operation between processed outputs, determining an authentication status of the user; and performing an authenticated action.

Abstract: A method for providing a brain computer interface that includes detecting a neural signal of a user in response to a calibration session having a time-locked component and a spontaneous component; generating a user-specific calibration model based on the neural signal; prompting the user to undergo a verification session, the verification session having a time-locked component and a spontaneous component; detecting a neural signal contemporaneously with delivery of the verification session; generating an output of the user-specific calibration model from the neural signal; based upon a comparison operation between processed outputs, determining an authentication status of the user; and performing an authenticated action.

Abstract: A method for creating brain-machine interface based on received and filtered brain signals from a subject, classifying the filtered signals to classes of brain states, detecting one brain state from the classified brain states and executing by a machine a command that corresponds to the detected state.

Abstract: A common adjunct switch integrated with a telecommunications network and associated with a plurality of predetermined telephone numbers prefixed by a common code is provided with a facility which allows telephone subscribers that are assigned respective ones of the telephone numbers to personalize the way in which they receive long distance telephone calls. For example, such a subscriber may program his/her associated service record to put into effect call forwarding or call screening. In addition, each such subscriber may be associated with one or more caller identification numbers, in which a caller identification number is used to determine whether a call placed to a service number is billed to the called subscriber or the calling party.