Biocorrelation - Cognitive model correlation - Brainprint aquisition

Individual-specific electromagnetic targeting

How is it possible that a specific individual within a crowd is electromagnetically targeted? Why is one individual susceptible to an electromagnetic targeting signal and another is not? That is because the electromagnetic signal tunes only to the neural circuitry of the specific individual, meaning to the specific "brain fingerprint"/"brainprint" or cognitive model or the specific brain biometric. 

Once this brainprint is acquired, remote brain interfacing is enabled and a bi-directional biocommunication can be established. Remote accessibility and influence of the corresponding brain space is hence possible. In 1948, N. Wiener from the MIT defined cybernetics as "the scientific study of control and communication in the animal and the machine" [*] [*]. Following the acquisition of the brainprint, an individual can be potentially considered to represent a cybernetic access node. 

Further specific entrainment practices can lead the brain to learn a neurolinguistic programming that alters brain plasticity and associates new outcomes to specific inputs. For instance, simultaneous presentation of an auditory stimulus and an electromagnetic stimulus may lead to an association of the two. As a result, upon presentation of the latter, the brain may consider that it has heard something. As new associations are formed in the direction of a neurolanguage that is only known by the actuating party, we may refer to neurocryptology and neuroencryption. The signal that may be directed to the target may trigger one of these created associations, which has been created to that specific target and as a result be interpreted only by that target.

Figure 1: "Cybernetics: Or Control and Communication in the Animal and the Machine", a book by Norbert Wiener [*] [*]

Biocorrelation - Correlation to a database cognitive model and acquisition of the brainprint

How is the brainprint or the cognitive model acquired? The cognitive model can be thought of as a real-time simulation of the electric activity or magnetic activity of the brain. Alternatively, it may be considered as a digital representation or a “digital twin” [*]. Databases of cognitive models exist. Adopting signal intelligence (SIGINT) terminology, we would say that the signal must be autocorrelated and biocorrelated. Signal autocorrelation, meaning correlation to self, allows us to identify if the signal is repeating itself, and if yes, to isolate the minimal signal that characterizes the system. It is noted that the brain has a basal signal which repeats itself in time. Different types of basal brain signals exist. Signal biocorrelation means that correlation must be performed to the activity of a biological system. We practically have to correlate or match the signal to a database cognitive model. The procedure is similar to a mathematical fitting process. 

In order to understand signal correlation better, we may refer to the example of the GPS/navigation satellite signal correlation performed by our mobile phones. Our mobile phones have stored in their processors the templates of the signals for all the different satellites. By performing correlation, they establish a match for the signals of three different satellites, which is a necessary condition for triangulation allowing precise localization.

In order to perform this correlation, the brain signal can be enacted upon to make it as comparable as possible to an available template. It must be synchronized or aligned to the template. The brain is characterized by entrainability given that it will tend to follow a periodically repeating signal. This characteristic is termed “frequency following response”. By entraining the major macrocircuits and microcircuits using specific frequencies, we obtain the profile of the brain which we can match to a database cognitive model. This may be possible for a majority of cases. Figure 2 shows on the top left the waveform of the subject and on the top right, the waveform of a reference cognitive model. Once the two waveforms are synchronized and the combined match shows minimal differences, it is considered that the cognitive model or brainprint of a given individual has been acquired. At the same time, the brain entrainment may also alter the neural signalling, rendering the brain more susceptible to external manipulation.

Also, the brain activity in certain conditions, such as the resting state, can be self-repeating. This means that macrocircuits and microcircuits may have specific patterns of activation and deactivation that are repeating themselves in time in a specific order e.g., macrocircuit A followed by microcircuit B, which is followed by macrocircuit C (ABC, ABC, ABC) similarly to the profile shown in Figure 3. While the brain is in auto-repeat mode, if we perform a correlation of the signal to itself, called autocorrelation, we can isolate this autorepeating signal (e.g. ABC) and infer the cognitive model to a certain degree.

Biocorrelation - Cognitive model fine-tuning using evoked biokey signatures 

Biokey signature evoked acquisition - Full cognitive model (brainprint) acquisition: evoked response to key electromagnetic sequences 

Based on the biokey signatures. Based on macrocircuits and microcircuits of the brain. ERP-biometrics.

In the procedure described above, we are trying to perform biocorrelation or cognitive model correlation to a database model by entraining the brain and monitoring its activity. This may be possible for a majority of cases while in some cases only a gross and not a fine biocorrelation may be established. Furthering the biocorrelation process, it is possible to perform cognitive model fine-tuning using evoked biokey signatures. 

In neuroscience, we know that a sudden stimulus, such as an auditory stimulus e.g., a “click”, may elicit a stereotyped electrophysiological response which is characterized by a specific electric potential waveform, referred to as an “evoked response” or “event-related potential” (ERP). The most known is the P300 event-related potential which is a positive peak occurring at approximately 300 ms following the presentation of a sudden stimulus which may be auditory, visual etc.

Figure 1: Typical event-related potential (ERP) waveform components including the P300, which is labeled here as P3 (Wikipedia) [By Original: Choms Vector: Mononomic - Own work based on: Constudevent.gif, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=5543904]

We also know that biometric systems are developed for human identity recognition including authentication using brain biometrics under auditory stimulation. In this case, the acquisition protocol adopts auditory stimulation to elicit a special class of brainwaves known as steady-state Auditory Evoked Potentials (AEPs) [https://tspace.library.utoronto.ca/handle/1807/108661]. Auditory stimulation may use specific sound sequences or streams. 

Additionally, in the case of the microwave auditory effect or Frey effect, an electromagnetic wave and by extension an electromagnetic sequence may elicit through pressure wave mechanisms involving cochlea mechanical stimulation, the activation of the auditory nerve [https://doi.org/10.17226/25889 [p.60] and the generation of a nerve potential.

We may infer that electromagnetic sequences or streams may be used to elicit evoked responses that can be used to further characterize the brainprint and perform detailed cognitive model correlation. 

An electromagnetic sequence may be generated from a digital template that can be represented with a stream of 0 and 1 digits (bits). For example, two indicative bitstreams or biokeys may be the following: 0101010101 and 1010101010. When these stimuli are directed towards different individuals, it may be that one individual is responsive to the one and another to the other. 

It may also be possible that these bitstreams have to be provided in specific instances of the self-repeating pattern of the brain, to match internal signaling processes and therefore to be accepted by the system and to be amplified by recurring mechanisms. Having already performed a gross cognitive model correlation, it is possible to calculate the specific timing to be used to present these biokeys in order to evoke a response and fine-tune the cognitive model.

We are anticipating that the evoked response protocols for fine-tuning the brain print cannot be performed for instance in a crowd or in the presence of many people because it would be impossible to detect an individual response. We may conclude that these protocols are mostly performed when a person is isolated.

How the microwave auditory effect could be used for brain biometrics

Dr. Duncan would refer to means similar to the microwave auditory effect that can be used for obtaining the brainprint (i.e. brain biometric) and for mapping the auditory cortex. We may infer that complex algorithms are involved.

Here is an EEG-based biometric system using auditory stimulation: https://tspace.library.utoronto.ca/handle/1807/108661

It is used to obtain the brain biometric (brainprint) by sound presentation.

It belongs to the category of ERP (evoked response potential) brain biometrics.

In Figure 2.3 on page 20, a sound stimulus, shown on the left, having a 40 Hz repetition rate, evokes an auditory brain response shown on the right, which is characterized by a 40 Hz peak.

As mentioned in the abstract, auditory stimulation is adopted "to elicit a special class of brainwaves known as steady-state Auditory Evoked Potentials (AEP)".

As the microwave auditory effect can perform auditory stimulation, we may infer how that is relevant. By analyzing the brain response, we can perform classification of the brain to a specific brain model type.