While the introduction of magnetic resonance imaging (MRI) in the mid-1980s has certainly added accuracy and reliability to the diagnosis of a wide array of pathological conditions linked to brain dysfunction, accumulating preclinical and clinical research indicates that neuropsychological testing combined with electroencephalogram (EEG) data acquisition still offers many advantages, including improved spatial and temporal resolution. Moreover, EEG-based neuropsychological tests are relatively inexpensive to run and can be repeated as often as necessary, without any associated risk or side-effect.
In particular, event related potentials (ERPs) are widely used to non-invasively explore anomalies in the EEG waveform in response to the presentation of one or more stimuli (e.g., auditory or visual). For example, ERP testing can be used for the detection of subclinical lesions in the brain , the prediction of long-term disability , and/or to monitor the progression of a disease using objective measures . Below are few examples of their clinical applications.
Visual Evoked Potentials
Visual evoked potentials (VEPs) allow the detection of functional anomalies in the visual pathway, from the retina to the occipital cortex (the area of the brain that is mostly responsible for the processing of visual stimuli). For example, VEPs have been shown to be superior to optical coherence tomography (OCT) for detecting mild to moderate forms of optic neuritis, in both symptomatic and asymptomatic eyes .
Also, multiple sclerosis research has demonstrated that VEPs are sensitive to asymptomatic brain demyelination and microstructural damage, while clinical trials also support their ability to detect remyelination/neuroprotection [5, 6].
Mismatch negativity (MMN) is a deflection of the EEG waveform that is associated with the ability of the brain to detect stimulus feature change during auditory stimulation (e.g., a train of notes with the same volume and pitch).
Abnormalities in the MMN response have been shown typically in neurodegenerative disorders, including schizophrenia, Alzheimer’s disease and Parkinson’s disease [7, 8].
However, research also supports clinical applications of MMN in several other conditions/diseases including dyslexia, speech disorders, autism, attention deficit hyperactivity disorder (ADHD), Tourette syndrome, depression, addiction, sleep disorder, and drug response monitoring .
The P300 measure is a deflection in the EEG waveform that is classically associated with cognitive activity. Abnormalities in P300 have been demonstrated in Parkinson’s disease (PD), dementia, Alzheimer’s disease, schizophrenia, ADHD, autism, traumatic brain injury (TBI), mood disorders (e.g., depression and bipolar disorder), and alcohol dependence [3, 10].
An important clinical function of the P300 measure is also to provide useful information for the discrimination among disorder subtypes by relating patient data to normative values, which can improve the accuracy of diagnosis and the targeting of interventions.
The N400 potential is another measure that is used for the assessment of cognitive functions and is elicited is by semantic incongruence in normal subjects.
Disruption of the N400 deflection has been found in stroke patients with damage in the left temporal lobe or temporoparietal junction. Damage to these brain regions can lead to a semantic comprehension deficit, which offers the possibility of using the N400 measure as a quantitative assessment tool for the evaluation of severity in comprehension deficits.
Another clinical application of N400 is found in epilepsy. Focal seizure disorders, for example, are often associated with abnormalities in the brain temporal lobe. Tests for language comprehension and verbal memory are used to make decisions about surgery and monitor treatment effects and changes in the N400 measure have been shown to serve as a specific and sensitive index of left temporal dysfunction.
Finally, the use of the N400 measure is supported in the diagnosis of Alzheimer’s disease, (although effects are highly dependent on the disease progression) and in schizophrenia as a biomarker of disorganized speech, a fundamental clinical symptom of the disease .
ERPs are of particular relevance in a variety of clinical applications in both neurology and psychiatry. The collection of ERP data is fast and cost-effective and modern EEG systems make ERP-based neuropsychological testing ideally suited for long-term monitoring of both disease progression and treatment response.
- Grecescu, M., Optical coherence tomography versus visual evoked potentials in detecting subclinical visual impairment in multiple sclerosis. J Med Life, 2014. 7(4): p. 538-41.
- Kiylioglu, N., et al., Evoked potentials and disability in multiple sclerosis: A different perspective to a neglected method. Clin Neurol Neurosurg, 2015. 133: p. 11-7.
- Duncan, C.C., et al., Event-related potentials in clinical research: guidelines for eliciting, recording, and quantifying mismatch negativity, P300, and N400. Clin Neurophysiol, 2009. 120(11): p. 1883-1908.
- Naismith, R.T., et al., Optical coherence tomography is less sensitive than visual evoked potentials in optic neuritis. Neurology, 2009. 73(1): p. 46-52.
- Mallik, S., et al., Imaging outcomes for trials of remyelination in multiple sclerosis. J Neurol Neurosurg Psychiatry, 2014. 85(12): p. 1396-404.
- Connick, P., et al., Autologous mesenchymal stem cells for the treatment of secondary progressive multiple sclerosis: an open-label phase 2a proof-of-concept study. Lancet Neurol, 2012. 11(2): p. 150-6.
- Bartha-Doering, L., et al., A systematic review of the mismatch negativity as an index for auditory sensory memory: From basic research to clinical and developmental perspectives. Psychophysiology, 2015. 52(9): p. 1115-30.
- Pekkonen, E., Mismatch negativity in aging and in Alzheimer’s and Parkinson’s diseases. Audiol Neurootol, 2000. 5(3-4): p. 216-24.
- Naatanen, R. and C. Escera, Mismatch negativity: clinical and other applications. Audiol Neurootol, 2000. 5(3-4): p. 105-10.
- Seer, C., et al., Event-related potentials and cognition in Parkinson’s disease: An integrative review. Neurosci Biobehav Rev, 2016. 71: p. 691-714.