RTConTrack: Real Time Connectom Tracking (Patent WO 2016/059055 A1)


 

RTConTrack, acronym for Real Time Connectom Tracking, is a dedicated algorithm (patent WO 2016/059055 A1) that automatically identifies the Brain Grey and White Matter Structures involved in the Brain Functions occuring during a fMRI performed task, and creates dynamic maps of their informations exchanges patterns.

 

 

RTConTrack can be compared to a Real-Time« GPS » system, where the « Cities » are the Grey Matter Structures, the « Roads » the White Matter Bundles, and the « Cars » the neuronal informations going through specific maps, each map characterizing one or several brain functions.

 

fmri-menthe_med

 

To be able to identify those structures and informations, RTConTrack uses functional MRI BOLD activation maps, analyzed in «Pseudo Real-Time» using fast MRI sequences and dedicated time interpolation algorithm in order to assess the Effective Functional Connectomics (seeing the informations going from one « city » to another through time), and MRI Diffusion HARDI sequences processed using Global Semi-Probabilistic Tractography (to individualize the «Highways»).

 

 

To identify the Grey and White Matter Structures involved in a specific function, RTConTrack uses dedicated Brain Functional and Structural Deterministic Anatomy Atlases. It first computes the Structural Connectoms maps from 58 identified main Fiber Bundles and 116 cortico-cortical (U fibers) and cortico-subcortical Projection Fibers automatically extracted by Stand-Alone Tractography:

 

AmazingLimbicSystem

 

Left Hippocampus all Fibers Connections

 

Then processes the Dynamic (through time) Structural Connectomic variation map (assessing the variation of fiber bundles used for the neural information transmission through time) :

 

Grey Matter Connectom Graph

 

 

Then computes the Functional Dynamic (through time) Connectoms maps from the 116 identified Cortical and Sub-cortical Grey Matter structures:

 

Functional Dynamic Connectom Map

 

to be able to automatically identify the known brain functions networks (recorded in its specific database) performed by the Brain during the fMRI (either using bloc paradigm or resting state design) acquisition. Then RTConTrack back reconstructs the identified Grey and White Matter structures to match the Anatomy Templates in a Dynamic Anatomy Activation Mapping:

 

 

In a Dynamic 4D (Time and Space) Functional Anatomic Reconstruction:

 

 

And in a Dynamic 4D Connectomics Reconstruction:

 

 

These Dynamic Functional Anatomic and Connectomic Reconstructions maps are used to visualize the Dynamic Effective Connectomics (the dynamic « GPS » maps assessing the detected Neural Networks activated during the fMRI acquisition), each Effective Connectomics map characterizing one or several Brain Functions. These maps are stored in a dedicated database, decomposed, classified using the Cantor’s Set Theory and Venn’s Diagrams in Main Functions (Audition, Cognition, Emotion, Langage, Memory, Motricity, Proprioception, Senses, Vision, …) interconnected with each others assessing a specific Brain Function (eg. Audition + Cognitive + Langage + Emotion = “Emotion Related Langage”) and compared using an artificial intelligence algorithm to other similar maps in order to assess similarity scores and variations of the Brain Functions Usage among the known brain functions, the tasks and the subjects.

 

 

The known Brain Functions occuring during the fMRI acquisition are thus automatically identified (from its 408 Brain Functions Networks database entries), decomposed, analyzed, compared and scored, and end user’s reports, statistical files and maps are generated studying the Normalized Percentage of Use (Minimum, Maximum, Average, Standard Deviation) for the identified Brain Functions, either activated (positive values) or deactivated (negative values), and assessing the Single Subject or Group Statistical Analysis of Brain Functions variations among the Subjects.

 

 

 

These scores and statistical analysis can be used to assess e.g. the chemical therapy efficacy (brain functions usage variations before and after treatment) in psychiatric patients (depressed, study in progress in Bicetre ; schizoid, autistic, …), in Mild Traumatic Brain Injury patients (brain functions alterations scoring, study in progress in Bicetre), in coma patients (existence of emotional and cognitive processes during e.g. an auditory stimulation), or used in normal subject in lie detection, consumer satisfaction scoring, emotional shifts studies using sents, music, lights stimulations, aso… Applications are limitless.

 

Group Statistical variations through Time of Brain Functions detected for an olfactory stimulation fMRI task 

 

Group Statistical repartitions through Time of Brain Functions detected for an olfactory stimulation fMRI task

 

Olf

Single Subject versus Group Z Score Function Use variations through Time for the Olfactory Brain network Function

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