The Dashboard

When you open a processed session, the Coherence Workstation presents your data in a dashboard—a step-by-step walkthrough that organizes the analysis from raw signal quality through spectral content, temporal dynamics, connectivity, source localization, and perturbation-response patterns.

This isn’t a random collection of charts. The sequence matters. Each step builds on what came before, and the order mirrors how a structured clinical reading unfolds.

The Step-by-Step Structure

The left sidebar shows your analysis steps. You work through them in order—or jump to any step directly. Each step represents a distinct level of description:

Case Overview — Your starting point. Session metadata, recording parameters, and a summary of what the pipeline found. This orients you before you look at any data.

Visual Inspection — The raw signal. Three montage views (average reference, linked ears, bipolar) let you scroll through the recording and assess data quality with your own eyes before trusting any computed metric.

Resting Spectra — Power spectral density across all channels for eyes-open and eyes-closed conditions. Topographic maps, individual channel spectra, and band-by-band comparisons. This is the foundation most QEEG practitioners start from.

Vigilance Staging — How arousal state shifts across the recording. Vigilance isn’t static—it fluctuates, and those fluctuations tell you something about the nervous system’s ability to regulate state transitions.

Heart Rate Variability — Autonomic nervous system metrics derived from the PPG sensor in the Neurofield headset. HRV gives you a window into the body’s regulatory capacity that EEG alone can’t provide.

Connectivity — Functional connectivity between electrode sites using debiased weighted phase lag index (dwPLI). The connectivity matrix shows you which regions are talking to each other—and which aren’t—across frequency bands.

Temporal Hierarchy (Spectral Slope) — The 1/f spectral slope, which reflects the brain’s temporal organization. A steep slope suggests strong top-down regulation; a flat slope suggests the system is running hot with insufficient temporal constraint.

Independent Components — ICA decomposition results with ICLabel classification. Every component is profiled: its topography, power spectrum, dipole source location, brain probability, and classification. Components marked for rejection are shown in red so you can verify every decision the pipeline made.

Artifact Rejection — A before-and-after view of what the automated artifact rejection removed. You see exactly what was cleaned and can assess whether the pipeline was too aggressive or too lenient.

ERP Analysis — Event-related potentials from the perturbation-response paradigm. Channel overlays, butterfly plots, and the AODEMR sequence (developed by John LeMa) that structures how you read the brain’s response to challenge.

Global Field Power — GFP waveforms that show the overall strength and timing of the brain’s response across all channels simultaneously.

ERP Spectra — Frequency content of the event-related response, revealing oscillatory dynamics that time-domain ERPs can miss.

Single-Trial Consistency — How consistent the brain’s response is across individual trials. High consistency suggests a stable response pattern; high variability suggests the system is searching or unstable.

Time-Frequency Dynamics (ERSP) — Event-related spectral perturbation maps showing how power in each frequency band changes over time relative to the event. This reveals the dynamics that averaged ERPs smooth over.

ERP by Component — Event-related responses decomposed by ICA component, letting you see which neural sources contribute to the scalp-level ERP.

Phenotype Summary — Automated pattern detection that flags recognized clinical phenotypes across all analysis stages. These are starting points for interpretation, not conclusions.

How to Navigate

Click any step in the left sidebar to jump directly to it. The current step is highlighted. Steps you’ve already viewed are marked, so you can track your progress through the reading.

Each step includes:

• Interactive visualizations — Charts, topomaps, and matrices you can hover over for detail. Tooltips explain what you’re looking at and how to interpret it.
• Condition tabs — Toggle between Eyes Open and Eyes Closed conditions wherever both are available.
• Expert notes — Data-driven commentary generated from your specific recording. These aren’t generic descriptions—they’re observations keyed to what’s actually in your data.
• “Analyze with AI Mentor” button — Opens the AI Research Assistant panel with context from the current step. The AI sees what you see and can help you think through it.

The AI Research Assistant Panel

On the right side of the dashboard, the AI Research Assistant panel slides open when you request an analysis. It operates in the context of whatever step you’re currently viewing—it knows which analysis stage you’re looking at and what the data shows.

You can ask it to analyze the full case, focus on the current section, or engage it in conversation about specific findings. The Research Assistant maintains a chat history for the session, so your conversation builds over time as you work through the steps.

Three engagement modes let you set the level of guidance:

• Guided Tour — The AI walks you through the findings, explaining what each metric means and what to look for
• Collaborative — You and the AI work through the data together, with the AI offering observations and asking questions
• Reasoning Partner — For experienced clinicians who want a thinking companion that challenges assumptions and suggests alternative readings

Reading Across Steps

The real clinical insight often isn’t in any single step—it’s in the convergence across steps. When a flattened spectral slope in the temporal hierarchy lines up with shortened microstate durations, and the connectivity matrix shows reduced long-range alpha coherence, you’re seeing three independent views of the same organizational problem.

The dashboard is designed to make these cross-stage connections visible. As you move through the steps, you build a structural description that no single metric could provide on its own. The Reading the Analysis section of this documentation teaches you to think in exactly this way—across levels of description, not just within them.