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Background and purpose
The aim was to characterize a combined vestibular, ocular motor and postural syndrome induced by deep brain stimulation (DBS) of the subthalamic nucleus in a patient with Parkinson's disease.
Methods
In a systematic DBS programming session, eye, head and trunk position in roll and pitch plane were documented as a function of stimulation amplitude and field direction. Repeat ocular coherence tomography was used to estimate ocular torsion. The interstitial nucleus of Cajal (INC), zona incerta (ZI) and ascending vestibular fibre tracts were segmented on magnetic resonance imaging using both individual and normative structural connectomic data. Thresholded symptom-associated volumes of tissue activated (VTA) were calculated based on documented stimulation parameters.
Results
Ipsilateral ocular tilt reaction and body lateropulsion as well as contralateral torsional nystagmus were elicited by the right electrode in a current-dependent manner and subsided after DBS deactivation. With increasing currents, binocular tonic upgaze and body retropulsion were observed. Symptoms were consistent with an irritative effect on the INC. Symptom-associated VTA was found to overlap with the dorsal ZI and the ipsilateral vestibulothalamic tract, while lying rather distant to the INC proper. A ZI-to-INC ‘incerto-interstitial’ tract with contact to the medial-uppermost portion of the VTA could be traced.
Conclusion
Unilateral stimulation of INC-related circuitry induces an ipsilateral vestibular, ocular motor and postural roll-plane syndrome, which converts into a pitch-plane syndrome when functional activation expands bilaterally. In this case, tractography points to an incerto-interstitial pathway, a tract previously only characterized in non-human primates. Directional current steering proved useful in managing this rare side effect.
Background
Eye movement abnormalities are commonplace in neurological disorders. However, unaided eye movement assessments lack granularity. Although videooculography (VOG) improves diagnostic accuracy, resource intensiveness precludes its broad use. To bridge this care gap, we here validate a framework for smartphone video-based nystagmography capitalizing on recent computer vision advances.
Methods
A convolutional neural network was fine-tuned for pupil tracking using > 550 annotated frames: ConVNG. In a cross-sectional approach, slow-phase velocity of optokinetic nystagmus was calculated in 10 subjects using ConVNG and VOG. Equivalence of accuracy and precision was assessed using the “two one-sample t-test” (TOST) and Bayesian interval-null approaches. ConVNG was systematically compared to OpenFace and MediaPipe as computer vision (CV) benchmarks for gaze estimation.
Results
ConVNG tracking accuracy reached 9–15% of an average pupil diameter. In a fully independent clinical video dataset, ConVNG robustly detected pupil keypoints (median prediction confidence 0.85). SPV measurement accuracy was equivalent to VOG (TOST p < 0.017; Bayes factors (BF) > 24). ConVNG, but not MediaPipe, achieved equivalence to VOG in all SPV calculations. Median precision was 0.30°/s for ConVNG, 0.7°/s for MediaPipe and 0.12°/s for VOG. ConVNG precision was significantly higher than MediaPipe in vertical planes, but both algorithms’ precision was inferior to VOG.
Conclusions
ConVNG enables offline smartphone video nystagmography with an accuracy comparable to VOG and significantly higher precision than MediaPipe, a benchmark computer vision application for gaze estimation. This serves as a blueprint for highly accessible tools with potential to accelerate progress toward precise and personalized Medicine.