Functional Overview & Biophysical Principles
MicBrain provides an interactive, three-dimensional anatomical platform demonstrating the mapping of frequency-dependent acoustic dynamics onto corresponding functional regions of the human cerebral cortex. Built upon spatial meshes from the Destrieux cortical atlas, the visualization separates incoming auditory data into fifteen functional signal domains representing local metabolic and field potential analogies. By analyzing frequency components in real time, the application illustrates visual representations of complex cortical pathways and structural topography, offering a conceptual model of neuro-anatomical associations.
In clinical neuroscience, auditory stimuli are processed through complex thalamocortical circuits starting at the cochlea, traversing the medial geniculate body of the thalamus, and projecting into Heschl's gyrus located within the transverse temporal gyrus. MicBrain replicates this functional partitioning by routing specific bandwidths of raw acoustic signals into targeted neural regions, including the temporal auditory cortex, frontal motor planning regions, medial default-mode structures, parietal integration regions, and posterior occipital visual regions. While simplified for educational and conceptual use, this visualization serves to demonstrate biological sound-mapping processes.
Instrument Calibration & Workflow Instructions
Users can operate the instrument in either a live physical environment via microphone capture or via simulated data flows. Click the 'Start Microphone' button to request local browser media capture permissions and stream physical environmental noise, or activate the 'Start Demo' button to trigger automated physiological sweep modes. The OrbitControls interface allows users to rotate the 3D model with a click-and-drag gesture, pan with a secondary click-and-drag gesture, or zoom within set boundaries.
The 'Active Regions' slider controls how many regions of the Destrieux atlas are styled in active colors versus baseline translucent white, allowing users to toggle between a focused view of the most active structures and a comprehensive whole-brain layout. The 'Input Gain' slider scales input amplitude, and the 'Noise Gate' slider sets the threshold below which signals are filtered out to keep low-level background noise from triggering activations. Toggle 'Spectral Whitening' to balance the activation across all bands, or adjust the 'Resting-State Waves (DMN)' slider to introduce slow, organic resting-state fluctuations.
Architectural Engineering & Processing Equations
Auditory inputs are captured via the Web Audio API and processed using an AnalyserNode set to a fast Fourier transform (FFT) size of 2048. Raw bin values are aggregated into fifteen frequency ranges. In Adaptive Spectral Whitening mode, the software maintains rolling peak and noise floor values to dynamically compute a normalized range, preventing any single frequency band from dominating the display.
To model natural, slow-varying resting-state metabolic activity, each region's active material score is modulated by a slow-wave equation: $S_j = E_{B(R_j)} \cdot [1.0 + M \cdot \sin(\omega_j \cdot t + \phi_j)]$, where $E$ is the normalized energy of the frequency band, $M$ is the modulation strength, and $\omega_j$ and $\phi_j$ are a unique frequency and phase based on the region's name hash. The mesh materials share a single WebGL shader instance per frequency band to optimize rendering performance, allowing the simulation to render smoothly at high framerates.
Future Directions & Clinical Diagnostic Roadmaps
The prospective roadmap for MicBrain focuses on implementing high-density EEG source-reconstruction models to project real electrical signal readings onto the 3D Destrieux meshes. Incorporating standardized boundary element models (BEM) and forward head models would allow the tool to project physical EEG inputs to corresponding cortical origins. This would bridge the gap between educational concept models and real-time clinical diagnostics.
Additional updates will introduce on-hover anatomical labels with both clinical and common terminology, as well as customizable color palettes mapping specific cognitive networks like the Salience, Central Executive, and Default Mode Networks. These additions aim to increase the visualization's educational utility for neurological mapping studies and neurofeedback systems.
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