11/03/2025
Does labeling the (mental health) smoke allow us to put out the fire? In traditional mental health, we have historically diagnosed patients by verbally derived symptoms: sadness, inattention, worry, fatigue.
But in the neuroscience of psychology, symptoms are outputs — they’re the smoke signals of deeper biological and network-level dysfunction. We in neuropsychology refer to this as “symptom diagnosis” and it can have some clinical value. It asks “What does the patient feel?” And, of course, this is a fruitful starting point yet relies on subjective reports and symptom checklists. Likewise, it clusters phenomena into broad categories such as depression or ADHD.
“Systems diagnosis”, by contrast, looks beneath the surface and maps how the brain’s circuits, biochemistry, and genetics interact to produce the observable mind. It asks: “What’s happening within the patient’s neuroconnectome, the intricate networks of the brain?” It uses qEEG, PGX and AI based analytics to detect dysregulation.
Why is this imperative you ask? Because the case could be made that we don’t biologically treat a diagnosis we treat a central nervous system …that through its “dysregulatory recurrences” gives rise to the patient’s inner experience that we then, in turn, label. Understanding this at scale can drive precision mental health treatment.
If we want to level up the mental health paradigm many believe that we will need to level up our systems analysis capabilities. When we can visualize brain network dysregulation and accurately predict medication-neuromodulation response, diagnosis becomes more than a label — it becomes a map to healing.
What do you think? We'd love to hear how you see this evolution unfolding in your field – and the challenges inherent in this paradigm shift.
