Delayed on- and off-retinal responses of cones pathways in regular cannabis users: An On-Off flash electroretinogram case-control study

Retinal electrophysiology in central nervous system disorders. A review of human and mouse studies

The retina and brain share similar neurochemistry and neurodevelopmental origins, with the retina, often viewed as a "window to the brain." With retinal measures of structure and function becoming easier to obtain in clinical populations there is a growing interest in using retinal findings as potential biomarkers for disorders affecting the central nervous system. Functional retinal biomarkers, such as the electroretinogram, show promise in neurological disorders, despite having limitations imposed by the existence of overlapping genetic markers, clinical traits or the effects of medications that may reduce their specificity in some conditions. This narrative review summarizes the principal functional retinal findings in central nervous system disorders and related mouse models and provides a background to the main excitatory and inhibitory retinal neurotransmitters that have been implicated to explain the visual electrophysiological findings. These changes in retinal neurochemistry may contribute to our understanding of these conditions based on the findings of retinal electrophysiological tests such as the flash, pattern, multifocal electroretinograms, and electro-oculogram. It is likely that future applications of signal analysis and machine learning algorithms will offer new insights into the pathophysiology, classification, and progression of these clinical disorders including autism, attention deficit/hyperactivity disorder, bipolar disorder, schizophrenia, depression, Parkinson's, and Alzheimer's disease. New clinical applications of visual electrophysiology to this field may lead to earlier, more accurate diagnoses and better targeted therapeutic interventions benefiting individual patients and clinicians managing these individuals and their families.

Retinal electroretinogram features can detect depression state and treatment response in adults: A machine learning approach

BACKGROUND

Major depressive disorder (MDD) is a major public health problem. The retina is a relevant site to indirectly study brain functioning. Alterations in retinal processing were demonstrated in MDD with the pattern electroretinogram (PERG). Here, the relevance of signal processing and machine learning tools applied on PERG was studied.

METHODS

PERG - whose stimulation is reversible checkerboards - was performed according to the International Society for Clinical Electrophysiology of Vision (ISCEV) standards in 24 MDD patients and 29 controls at the inclusion. PERG was recorded every 4 weeks for 3 months in patients. Amplitude and implicit time of P50 and N95 were evaluated. Then, time/frequency features were extracted from the PERG time series based on wavelet analysis. A statistical model has been learned in this feature space and a metric aiming at quantifying the state of the MDD patient has been derived, based on minimum covariance determinant (MCD) mahalanobis distance.

RESULTS

MDD patients showed significant increase in P50 and N95 implicit time (p = 0,006 and p = 0,0004, respectively, Mann-Whitney U test) at the inclusion. The proposed metric extracted from the raw PERG provided discrimination between patients and controls at the inclusion (p = 0,0001). At the end of the follow-up at week 12, the difference between the metrics extracted on controls and patients was not significant (p = 0,07), reflecting the efficacy of the treatment.

CONCLUSIONS

Signal processing and machine learning tools applied on PERG could help clinical decision in the diagnosis and the follow-up of MDD in measuring treatment response.

Variations of retinal dysfunctions with the level of cannabis use in regular users: Toward a better understanding of cannabis use pathophysiology

The impact of regular cannabis use on retinal function has already been studied using flash (fERG) and pattern (PERG) electroretinogram. Delayed ganglion and bipolar cells responses were observed as showed by increased peak time of PERG N95 and fERG b-wave recorded in photopic condition. Hypoactivity of amacrine cells was also showed by decreased amplitudes of oscillatory potentials (OPs). However, it is unknown how these retinal anomalies evolve according to the level of cannabis use in cannabis users. The aim of this study was to longitudinally assess the retinal function during a treatment aiming to reduce cannabis use. We recorded PERG and fERG in 40 regular cannabis users receiving either an 8 weeks mindfulness-based relapse prevention program or an 8 weeks treatment-as-usual therapy. ERGs were recorded before treatment, at the end of it, and 4 weeks afterward. We found reduced peak times in PERG N95 and fERG b-wave (p = 0.032 and p = 0.024: Dunn's post-hoc test) recorded at week 8 and increased amplitudes in OP2 and OP3 (p = 0.012 and p = 0.030: Dunn's post-hoc test) recorded at week 12 in users with decreased cannabis use. These results support variations of retinal anomalies with the level of cannabis use, implying that reduction of cannabis use could restore retinal function in regular users.