Method and apparatus for neuroenhancement
A method of facilitating a skill learning process or improving performance of a task, comprising: determining a brainwave pattern reflecting neuronal activity of a skilled subject while engaged in a respective skill or task; processing the determined brainwave pattern with at least one automated processor; and subjecting a subject training in the respective skill or task to brain entrainment by a stimulus selected from the group consisting of one or more of a sensory excitation, a peripheral excitation, a transcranial excitation, and a deep brain stimulation, dependent on the processed temporal pattern extracted from brainwaves reflecting neuronal activity of the skilled subject.
1 . An apparatus for facilitating a skill or task, comprising:
a memory, configured to store automatically processed dynamic neuronal electrical activity patterns comprising at least one of a delta rhythm and a theta rhythm selectively associated with the skill or task;
an input configured to receive electroencephalographic signals from a subject;
a parallel processor, configured to perform mathematical transforms for processing of the electroencephalographic signals from the subject in parallel, to at least extract frequency and phase information; and
a stimulator, configured to entrain brainwaves of the subject with at least one sensory stimulus, comprising frequencies dependent on the stored dynamic neuronal activity patterns comprising the at least one of the delta rhythm and the theta rhythm selectively associated with the skill or task, and being dependent on a relative frequency and phase of the stored dynamic neuronal electrical activity patterns comprising the at least one of the delta rhythm and the theta rhythm with respect to the extracted frequency and phase information from the electroencephalographic signals, to facilitate performance of the respective skill or task by the subject.
2 . The apparatus according to claim 1 , wherein the at least one sensory stimulus comprises a concurrent plurality of frequencies.
3 . The apparatus according to claim 1 , further comprising an input configured to acquire the dynamic neuronal electrical activity patterns comprising the at least one of the delta rhythm and the theta rhythm associated with the skill or task of the subject.
4 . The apparatus according to claim 1 , wherein the stimulator comprises at least one sensory stimulator configured to generate at least one of an audio, visual, or audiovisual stimulus.
5 . The apparatus according to claim 1 , wherein the stimulator is configured to cause brainwave entrainment of the subject with the dynamic neuronal electrical activity patterns comprising the at least one of the delta rhythm and the theta rhythm.
6 . The apparatus according to claim 1 , wherein the at least one sensory stimulus comprises a central nervous system stimulation of the subject with a signal having a modulation corresponding to a dynamic neuronal electrical activity pattern comprising the at least one of the delta rhythm and the theta rhythm defined by a recording of brainwaves of a human.
7 . The apparatus of claim 1 , wherein the stimulator is configured to deliver a tactile stimulus in addition to at least one of a visual and an auditory stimulus.
8 . The apparatus according to claim 1 , wherein the stimulator comprises an optical illuminator configured to produce optical patterns having a time-varying intensity pattern corresponding to the dynamic neuronal electrical activity patterns, wherein the dynamic neuronal electrical activity patterns comprising the at least one of the delta rhythm and the theta rhythm have a waveform corresponding to an acquired brainwave.
9 . The apparatus according to claim 1 , further comprising:
an input configured to receive electrical brainwave signals; and
at least one processor configured to process the received electrical brainwave signals to define the dynamic electrical neuronal activity patterns comprising the at least one of the delta rhythm and the theta rhythm,
wherein the received electrical brainwave signals are not from the same subject at the same time.
10 . The apparatus according to claim 1 ,
wherein the processed dynamic electrical neuronal activity pattern comprising the at least one of the delta rhythm and the theta rhythm comprises a plurality of sequential frequency patterns of electrical brainwave activity of a human while engaged in different aspects of the skill or task; and
the at least one sensory stimulus comprises a sequence of phases respectively representing the plurality of frequency patterns.
11 . A system for determining a target brain activity state-dependent neurostimulation pattern, dependent on a task, comprising:
a memory configured to store a model of electrical brainwave activity data comprising a plurality of concurrent waves including at least one of a delta rhythm and a theta rhythm over time of a first subject during a plurality of distinct aspects of performance of the task and transitions between respective aspects of performance of the task, dependent on rhythm frequencies and respective phase differences between the plurality of concurrent waves, for each of the plurality of distinct aspects and transitions between respective aspects;
an input configured to receive brainwaves from a second subject;
a single-instruction multiple-data processor, configured to perform parallel mathematical transforms of the brainwaves from the second subject in parallel, and to determine at least frequency and phase information; and
at least one processor configured to determine a sequence of neurostimulation patterns for a multichannel neurostimulator,
the multichannel neurostimulator being configured to stimulate a brain of the second subject, associated with a performance of the task by the second subject, with a stimulus comprising the at least one of the delta rhythm and the theta rhythm and being dependent on a relationship of:
the determined frequencies and the phases, and
the rhythm frequencies and respective phase differences between the plurality of concurrent waves of the modelled electrical brainwave activity data comprising a plurality of concurrent waves including at least one of an delta rhythm and a theta rhythm over time of the first subject.
12 . A computer-readable medium, storing therein non-transitory instructions for a programmable processor to perform a process, comprising the computer-implemented steps of:
reading information from a memory representing dynamic neuronal electrical activity patterns comprising at least one frequency within a range of 1 Hz to 8 Hz selectively associated with the skill or task;
receiving electroencephalographic signals from a subject;
performing mathematical transforms using a parallel processor to process of the electroencephalographic signals from the subject in parallel, to at least extract frequency and phase information; and
controlling a neurostimulator, to entrain brainwaves of a subject with at least one sensory stimulus, dependent on the dynamic neuronal electrical activity patterns selectively associated with the skill or task, and a frequency and phase difference of the dynamic neuronal electrical activity patterns from the extracted frequency and phase information, the at least one sensory stimulus comprising the at least one frequency within the range of 1 Hz to 8 Hz, to facilitate performance of the respective skill or task by a stimulated subject.
13 . A method for determining a target brain electrical activity state, dependent on a task, comprising:
acquiring electrical brainwave activity data comprising a plurality of concurrent waves including at least one of a delta rhythm and a theta rhythm over time of a first subject during a plurality of distinct aspects of performance of the task and transitions between respective aspects of performance of the task;
analyzing the acquired electrical brainwave activity data comprising the plurality of concurrent waves including the at least one of the delta rhythm and the theta rhythm over time of the first subject, comprising determining rhythm frequencies of the plurality of concurrent waves, and phase differences between the plurality of concurrent waves, including at least one of a delta rhythm and a theta rhythm over time, for each of the plurality of distinct aspects of performance of the task and transitions between respective aspects of performance of the task;
modelling electrical brainwave characteristics of the first subject for each distinct aspect of performance of the task and transitions between respective aspects of performance of the task based on at least the rhythms frequencies of the plurality of concurrent waves and the phase differences between the plurality of concurrent waves;
acquiring second electrical brainwave activity data over time of a second subject;
performing parallel mathematical transforms of the second electrical brainwave activity data an automated parallel processor, configured to determine at least frequency and phase information of the second electrical brainwave activity data;
modelling second electrical brainwave activity data characteristics of the second subject based on at least the frequency and phase information; and
determining a sequence of neurostimulation patterns for a multichannel neurostimulator configured to entrain brainwaves of the second subject, associated with a performance of the task by the second subject, with the determined rhythm frequencies of the plurality of concurrent waves, and being dependent on the phase differences between the plurality of concurrent waves, the modelled electrical brainwave activity data characteristics of the first subject, and the modelled second electrical brainwave activity data characteristics of the second subject based on at least the frequency and phase information.
14 . The method according to claim 13 , wherein the acquired electrical brainwave activity data over time of the first subject and the acquired second electrical brainwave activity of the second subject are each spatially localized.
15 . The method according to claim 13 , wherein said analyzing comprises performing a mathematical transform of the electrical brainwave activity data to preserve spatial and state transition history.
16 . The method according to claim 15 , further comprising modifying the mathematically transformed electrical brainwave activity data and performing an inverse mathematical transform on the modified mathematically transformed electrical brainwave activity data.
17 . The method according to claim 15 , further comprising filtering noise from the mathematically transformed electrical brainwave activity data.
18 . The method according to claim 13 , further comprising temporally synchronizing the sequence of neurostimulation patterns with the acquired second electrical brainwave activity data over time of the second subject.
19 . The method according to claim 13 , further comprising normalizing a sequence of neurostimulation patterns based on differences between the modelled electrical brainwave characteristics of the first subject and the modelled second electrical brainwave characteristics of the second subject.
20 . The method according to claim 13 , wherein the analyzing of the acquired brain activity data over time of the first subject comprises representing the electrical brainwave activity data over time as an at least four dimensional matrix.
21 . The method according to claim 13 , wherein the analyzing of the acquired brain activity data over time of the first subject comprises processing of the acquired electrical brainwave activity data over time with a convolutional neural network.
22 . The method according to claim 13 , wherein the multichannel neurostimulator comprises at least one of an audio stimulator and a visual stimulator.
23 . The method according to claim 13 , further comprising presenting the sequence of neurostimulation patterns to the second subject.