Abstract: A method includes generating a trading performance model for a trading activity involving a set of decisions by a set of expert traders. The trading performance model includes a set of input data sets, a set of data processing workflows operating on the input data sets, and a set of trading decision outputs resulting from interaction of the expert traders with a user interface representing the trading performance model. The method includes generating a brain state model representing a sequential set of brain states of the set of expert traders that characterize brain states measured during the interactions of the expert traders with the user interface representing the trading performance model, assessing the quality of the trading decisions, determining a preferred pattern of trader brain state sequences, and modifying a subsequent trading activity.

Abstract: To identify physiological states that are predictive of a person's performance, a system provides physiological and behavioral interfaces and a data processing pipeline. Physiological sensors generate physiological data about the person while performing a task. The behavioral interface generates performance data about the person while performing the task. The pipeline collects the physiological and performance data along with reference data from a population of people performing the same or similar tasks. In various implementations, the physiological states are brain states. In one implementation, the pipeline computes bandpower ratios.

Abstract: To identify physiological states that are predictive of a person's performance, a system provides physiological and behavioral interfaces and a data processing pipeline. Physiological sensors generate physiological data about the person while performing a task. The behavioral interface generates performance data about the person while performing the task. The pipeline collects the physiological and performance data along with reference data from a population of people performing the same or similar tasks. In various implementations, the physiological states are brain states. In one implementation, the pipeline computes bandpower ratios.

Abstract: A method of predicting response to a sensory stimulus includes, with a processor, automatically receiving behavioral data representing the response of a first population of subjects to a reference stimulus. Data representing the neurological responses of a second, different population of subjects to the reference sensory stimulus are received and processed to provide group-representative data indicating commonality between the neurological responses of at least two members of the second population. A mapping from the group-representative data to the received behavioral data is produced. Test data representing the neurological responses of a third population of subjects to a test sensory stimulus are received and processed to provide test group-representative data indicating commonality between the neurological responses to the test sensory stimulus of at least two members of the third population. The mapping is applied to the test group-representative data to provide predicted behavioral data.

Abstract: To identify physiological states that are predictive of a person's performance, a system provides physiological and behavioral interfaces and a data processing pipeline. Physiological sensors generate physiological data about the person while performing a task. The behavioral interface generates performance data about the person while performing the task. The pipeline collects the physiological and performance data along with reference data from a population of people performing the same or similar tasks. In various implementations, the physiological states are brain states. In one implementation, the pipeline computes bandpower ratios.

Abstract: Methods are disclosed for determining an efficacy of a stimulus based on one or more measurable physiological responses to one or more stimuli including one or more stimulus features. Data is acquired on physiological responses of a group of one or more subjects to presentation of one or more stimuli including one or more stimulus features. The data on the one or more physiological responses of the one or more subjects is correlated with the presentation of the one or more stimulus features included in the one or more stimuli. The correlated data on the one or more physiological responses are associated with a separately-determined efficacy of the one or more stimuli to form a stimulus efficacy model. From this information, a projected efficacy of a stimulus is determinable by comparing one or more subsequently-measured physiological responses to the stimulus with the stimulus efficacy model.

Abstract: Methods are disclosed for determining an efficacy of a stimulus based on one or more measurable physiological responses to one or more stimuli including one or more stimulus features. Data is acquired on physiological responses of a group of one or more subjects to presentation of one or more stimuli including one or more stimulus features. The data on the one or more physiological responses of the one or more subjects is correlated with the presentation of the one or more stimulus features included in the one or more stimuli. The correlated data on the one or more physiological responses are associated with a separately-determined efficacy of the one or more stimuli to form a stimulus efficacy model. From this information, a projected efficacy of a stimulus is determinable by comparing one or more subsequently-measured physiological responses to the stimulus with the stimulus efficacy model.

Abstract: To identify physiological states that are predictive of a person's performance, a system provides physiological and behavioral interfaces and a data processing pipeline. Physiological sensors generate physiological data about the person while performing a task. The behavioral interface generates performance data about the person while performing the task. The pipeline collects the physiological and performance data along with reference data from a population of people performing the same or similar tasks. In various implementations, the physiological states are brain states. In one implementation, the pipeline computes bandpower ratios.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for developing transcranial electrical stimulation protocols are disclosed. In one aspect, a method includes forming a first array of electrodes and optimizing a plurality of electrode parameters within the first array of electrodes to achieve a desired physiological response; identifying one or more electrodes within the optimized first array that have relatively low current compared to the remaining electrodes in the first array; removing the identified low current electrodes from the first array to form a second array of electrodes, wherein the number of electrodes in the second array is less than the number of electrodes in the first array and optimizing a plurality of electrode parameters with the second array of electrodes to achieve a desired physiological response.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for developing transcranial electrical stimulation protocols are disclosed. In one aspect, a method includes forming a first array of electrodes and optimizing a plurality of electrode parameters within the first array of electrodes to achieve a desired physiological response; identifying one or more electrodes within the optimized first array that have relatively low current compared to the remaining electrodes in the first array; removing the identified low current electrodes from the first array to form a second array of electrodes, wherein the number of electrodes in the second array is less than the number of electrodes in the first array and optimizing a plurality of electrode parameters with the second array of electrodes to achieve a desired physiological response.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for developing transcranial electrical stimulation protocols are disclosed. In one aspect, a method includes the actions of accepting an image model of target tissue, obtaining a forward model having a first electrode configuration and first electrical stimulation parameters based on electrical stimulation of the target tissue, accepting electrode configuration changes or electrical stimulation parameter changes resulting in a second electrode configuration or second electrical stimulation parameters, determining an optimized tissue model using a least square methodology and based on the second electrode configuration or second electrical stimulation parameter changes, comparing the optimized tissue model with a desired outcome, and providing a confirmation of the optimized model with the desired outcome.

Abstract: A system that facilitates blind source separation in a distributed microphone meeting environment for improved teleconferencing. Input sensor (e.g., microphone) signals are transformed to the frequency-domain and independent component analysis is applied to compute estimates of frequency-domain processing matrices. Modified permutations of the processing matrices are obtained based upon a maximum magnitude based de-permutation scheme. Estimates of the plurality of source signals are provided based upon the modified frequency-domain processing matrices and input sensor signals. Optionally, segments during which the set of active sources is a subset of the set of all sources can be exploited to compute more accurate estimates of frequency-domain mixing matrices. Source activity detection can be applied to determine which speaker(s), if any, are active.

Abstract: A system that facilitates blind source separation in a distributed microphone meeting environment for improved teleconferencing. Input sensor (e.g., microphone) signals are transformed to the frequency-domain and independent component analysis is applied to compute estimates of frequency-domain processing matrices. Modified permutations of the processing matrices are obtained based upon a maximum magnitude based de-permutation scheme. Estimates of the plurality of source signals are provided based upon the modified frequency-domain processing matrices and input sensor signals. Optionally, segments during which the set of active sources is a subset of the set of all sources can be exploited to compute more accurate estimates of frequency-domain mixing matrices. Source activity detection can be applied to determine which speaker(s), if any, are active.

Abstract: The present invention provides a predictive tool for predicting Apopnea Hypopnea Index (AHI) in the diagnosis of Obstructive sleep apnea (OSA). The predictive tool is developed by recording pulse oximetry readings, obtaining delta index, oxygen saturation times and oxygen desaturation events from the oximetry readings. A multivariate non-parametric analysis and bootstrap aggregation is performed to obtain predictive models which can be used to predictive AHI in an individual and to classify an individual as having or not having OSA.

Abstract: The present invention provides a predictive tool for predicting Apopnea Hypopnea Index (AHI) in the diagnosis of Obstructive sleep apnea (OSA). The predictive tool is developed by recording pulse oximetry readings, obtaining delta index, oxygen saturation times and oxygen desaturation events from the oximetry readings. A multivariate non-parametric analysis and bootstrap aggregation is performed to obtain predictive models which can be used to predictive AHI in an individual and to classify an individual as having or not having OSA.