A Manifesto for Neurophysiology — Part 1: The specialty nobody talks about (and why that’s a problem)

This is the first in a series of posts making the case for a different kind of neurophysiology. It starts with an honest look at where we are.

I spend roughly half my working life doing clinical neurophysiology — EMG clinics, EEG reporting, the familiar rhythm of the department. The other half I spend as a researcher, building computational models of the very systems I assess in clinic. This split role gives me an interesting vantage point, and it has prompted some questions I want to work through in this series — not as criticisms of colleagues or the field, but as a genuine attempt to think about where neurophysiology is heading, and where it could be going instead.

The starting point is a fairly simple observation: neurophysiology is operating in an increasingly competitive diagnostic environment, and the specialty has not yet fully articulated what its distinctive contribution is or should be.

A changing landscape

Consider what has happened in adjacent fields over the past two to three decades. Advances in neuroimaging have transformed the diagnostic workup for many neurological conditions, giving clinicians — and patients — direct visual access to anatomy and pathology. MRI and ultrasound findings are immediately legible across specialties in a way that a table of latencies and amplitudes is not. Meanwhile, molecular genetics has reshaped the diagnosis of inherited neuromuscular disease; conditions that would once have required extensive electrophysiological characterisation can now be resolved with a gene panel. And in autoimmune neurology, the explosion of antibody discovery has been transformative — conditions like myasthenia gravis and CIDP, once diagnosed principally through electrophysiology and clinical pattern recognition, now have specific, actionable biomarkers that predict prognosis and guide treatment selection. The discovery of antibodies targeting nodes of Ranvier, for instance, has defined an entirely new category of autoimmune nodopathy within what was previously considered the CIDP spectrum. The pace of this development shows no sign of slowing. Pathogenic autoantibodies against paranodal membrane proteins in CIDP, and against muscle-specific kinase in myasthenia gravis, are now recognised as essential to clinical diagnosis and are reshaping treatment algorithms.

None of this diminishes what neurophysiology offers. But it does change the context in which we work, and it raises a legitimate question: where is the equivalent leap in electrophysiological technique?

The question of new tests

The core tools of clinical neurophysiology — nerve conduction studies and needle EMG — were established in their essential form decades ago and remain the foundation of clinical practice. There is nothing wrong with that; they remain powerful and, in skilled hands, genuinely irreplaceable. But the question of whether the field has developed new measurement approaches at a pace commensurate with advances in adjacent fields is worth asking. A systematic review of neurophysiological outcome measures used in ALS clinical trials — one of the better-studied areas for novel electrophysiological techniques — found that despite 32 interventional trials employing neurophysiological outcome measures since 1986, there is limited standardisation between studies and an apparent ‘scatter-gun’ approach to technique selection, which the authors argue reflects the absence of a coherent, updated toolkit. Neurophysiology has many promising tools. The challenge is developing and standardising them into something clinically usable.

What referrers actually need

The second issue is less about technique and more about communication. A report that confirms or excludes a diagnosis with a clear management implication is enormously valuable. But a significant proportion of referrals do not yield that. The result is “indeterminate” or “within normal limits given technical constraints” — and the referring clinician, often not a neurophysiology specialist, is left to decide what to do next. Should the test be repeated? Was there a technical limitation? Does a normal result exclude pathology, or is the test simply not sensitive to what the patient has?

Studies of referral concordance suggest frequent inconsistency between the clinical diagnosis expected by the referring physician and what EDX testing finds — with normal results in around a quarter of cases and referral diagnosis confirmed in only around 60% overall. This is not necessarily a problem with neurophysiology per se; it partly reflects the difficulty of the clinical questions being asked, and the reality that abnormal electrophysiology sometimes follows rather than precedes clinical symptoms. But it does mean that a substantial proportion of patients and their referrers receive a result that does not obviously tell them what to do next.

Part of the issue is a fundamental one about how our results are presented. Electrodiagnostic testing is, to many clinicians, a “black box” — a commonly ordered test that can provide very definitive information that is often not well understood, with most clinicians relying primarily on the concluding statements rather than the underlying data. If that is the experience of clinicians ordering these tests, it is worth reflecting on what that means for how we structure and communicate our findings.

There is an instructive contrast here with imaging. A radiologist’s report arrives alongside images that the referrer can look at directly. The findings are immediately interpretable, at least in broad terms. Our reports, by contrast, present numerical data — latencies, amplitudes, recruitment patterns — that require specialist training to interpret, and where the meaning of marginal or borderline findings is often unclear even to the specialist. The gap between what we measure and what we can communicate to a non-specialist referrer is one that the field has not systematically addressed.

An opportunity, not a crisis

None of this is a counsel of despair. The NHS neurology waiting list grew by 76% between 2021 and 2023, and the demand for objective electrophysiological assessment is not diminishing. The data our tests generate — when properly analysed — contains far more information than conventional reporting captures. The motor unit, the fundamental unit of voluntary movement, encodes information about its structure, recruitment and mechanical behaviour in every contraction. We are currently using a fraction of that signal.

The rest of this series will work through what a more expansive neurophysiology might look like: more quantitative, more objective, more legible to the clinicians and patients we serve, and more integrated with the computational and imaging tools that now surround us. Some of what I’ll describe is already being developed in research settings; some of it requires a cultural shift in how we think about what our job is.

The first step, as with most things, is being honest about where we are.

Next week: We need to talk about our data.