Presbyopia management with Q-factor modulation without additive monovision: One-year visual and refractive results.

PURPOSE: To analyze refractive results after hyperopic presbyopia surgery by Q-factor modulation without additive monovision. SETTING: Quinze-Vingts National Ophthalmology Hospital, Paris, France. DESIGN: Prospective nonrandomized study. METHODS: Forty-five hyperopic presbyopic patients not tolerating monovision were included. The target for the dominant eye was emmetropia, whereas that for the nondominant eye was emmetropia associated with a target Q factor of -0.8. The postoperative follow-up included assessments of spherical equivalent (SE) refraction, monocular and binocular corrected and uncorrected (UDVA) distance visual acuities, and binocular corrected and uncorrected (UNVA) near visual acuities. Corneal pachymetry, topography, aberrometry and an analysis of patient satisfaction were performed at the 12-month examination. RESULTS: The study comprised 90 eyes of 45 consecutive patients. The mean age at surgery was 53.8 years ± 4.99 (SD). The mean preoperative SE was +2.33 ± 1.16 diopters (D) in the dominant eyes and +2.26 ± 1.17 D in the nondominant eyes. At 12 months postoperatively, 42 patients (93%) had a binocular UDVA of Snellen 20/20 and 37 patients (82%) had a binocular UNVA of Jaeger 2 (Parinaud 3). The mean SE at 12 months was -0.22 ± 0.35 D in the dominant eyes (P < .0001) and -0.83 ± 0.50 D in the nondominant eyes (P < .0001). Two eyes required retreatment. Overall, 39 patients (87%) said that they were satisfied and would recommend the intervention. CONCLUSION: The Q-factor modulation without additive monovision aims to compensate for presbyopia by changing the Q factor of the nondominant eye to generate a greater depth of field in hyperopic presbyopic patients who are unable to tolerate monovision. The visual outcomes and quality of vision were satisfactory, and only a few patients required additional correction.

Contribution of Fourier-domain optical coherence tomography to the diagnosis of keratoconus progression.

PURPOSE: To determine the anatomic criteria for diagnosing keratoconus progression by corneal optical coherence tomography (OCT). SETTING: Quinze-Vingts National Ophthalmology Hospital, Paris, France. DESIGN: Prospective case series. METHODS: Scanning-slit corneal topography (Orbscan II) and Fourier-domain corneal OCT (RTVue) were performed in eyes with mild to moderate keratoconus (progressive or nonprogressive [stable] ectasia) at each examination to assess the keratoconus. Disease progression was defined as an increase of at least 1.0 diopter (D) in the steepest keratometry (K) measurement over 6 months. RESULTS: Of the 134 eyes of 134 patients with mild to moderate keratoconus, 98 had had progressive ectasia and 36 nonprogressive ectasia. The mean maximum K increased significantly in the progressive group (2.1 D ± 1.2 [SD], P < .0001) and remained constant in the stable group (-0.03 ± 0.39 D, P = .31). The mean thinnest corneal thickness increased significantly in the progressive group (-7.98 ± 9.3 µm, P < .0001) and remained constant in the stable group (-0.52 ± 4.21 µm, P = .22). The change in maximum K was significantly correlated with changes in the thinnest corneal thickness (r = -0.61, P < .0001). A cutoff value of -5 µm for the change in thinnest corneal thickness was identified on receiver operating characteristic curves as a threshold separating cases of progressive and stable keratoconus (area under the curve, 0.79; sensitivity, 68%; specificity, 89%). CONCLUSIONS: Topographic data partly reflected the structural changes occurring during the progression of corneal ectasia. Based on the pachymetric parameters provided by OCT, corneal and epithelial thinning was correlated with corneal deformation. The use of corneal OCT might therefore improve the diagnostic sensitivity for keratoconus progression.

Asynchronous decoding of finger position and of EMG during precision grip using CM cell activity: application to robot control.

Recent brain-machine interfaces (BMI) have demonstrated the use of intracortical signals for the kinematic control of robotic arms. However, for potential restoration of manual dexterity, two issues remain to be addressed: (1) Can hand and digit movements for dexterous manipulation be controlled in a similar way to arm movements? (2) Can the potentially large signal space for decoding of the many degrees of freedom (dof) of hand and digit movements be minimized? The first question addresses BMI control of dexterous prosthetic devices, while the second addresses the problem of whether few, but identified, neurons might provide adequate decoding. Asynchronous decoding of precision grip finger movement kinematics from identified corticomotoneuronal (CM) cell activity was performed with an artificial neural network (ANN). After training over a given session, the ANNs successfully decoded trial-by-trial movement kinematics. Average accuracy over sessions was in the order of 80% and 50% for data sets of two monkeys respectively. Decoding accuracy increased as a function of (1) number of simultaneously recorded CM cells used for prediction, and (2) size of the sliding input window. Subsequently, a robot digit actuated by pneumatic artificial muscles, fed with the predicted trajectory, mimicked the recorded movement offline. Furthermore, CM cell signals were used for decoding of time-varying hand muscle EMG activity. The performance of EMG prediction tended to increase if CM cells that facilitated this particular muscle (compared to CM cells that facilitated other muscles) were used. These results provide evidence that an anthropomorphic robot finger can be controlled offline by spike trains recorded from identified corticospinal neurons. This represents a step towards neuroprosthetic devices for dexterous hand movements.

Integration of gravitational torques in cerebellar pathways allows for the dynamic inverse computation of vertical pointing movements of a robot arm.

BACKGROUND: Several authors suggested that gravitational forces are centrally represented in the brain for planning, control and sensorimotor predictions of movements. Furthermore, some studies proposed that the cerebellum computes the inverse dynamics (internal inverse model) whereas others suggested that it computes sensorimotor predictions (internal forward model). METHODOLOGY/PRINCIPAL FINDINGS: This study proposes a model of cerebellar pathways deduced from both biological and physical constraints. The model learns the dynamic inverse computation of the effect of gravitational torques from its sensorimotor predictions without calculating an explicit inverse computation. By using supervised learning, this model learns to control an anthropomorphic robot arm actuated by two antagonists McKibben artificial muscles. This was achieved by using internal parallel feedback loops containing neural networks which anticipate the sensorimotor consequences of the neural commands. The artificial neural networks architecture was similar to the large-scale connectivity of the cerebellar cortex. Movements in the sagittal plane were performed during three sessions combining different initial positions, amplitudes and directions of movements to vary the effects of the gravitational torques applied to the robotic arm. The results show that this model acquired an internal representation of the gravitational effects during vertical arm pointing movements. CONCLUSIONS/SIGNIFICANCE: This is consistent with the proposal that the cerebellar cortex contains an internal representation of gravitational torques which is encoded through a learning process. Furthermore, this model suggests that the cerebellum performs the inverse dynamics computation based on sensorimotor predictions. This highlights the importance of sensorimotor predictions of gravitational torques acting on upper limb movements performed in the gravitational field.