Perception is the ability to see, hear, or become aware of external stimuli through the senses. Visual stimuli are electromagnetic waves that interact with the eye and elicit a sensation. Sensations, indeed, imply the detection, resolution, and recognition of objects and images, and their accuracy depends on the integrity of the visual system. In clinical practice, evaluating the integrity of the visual system relies greatly on the assessment of visual acuity, that is to say on the capacity to identify a signal. Visual acuity, indeed, is of utmost importance for diagnosing and monitoring ophthalmological diseases. Visual acuity is a function that detects the presence of a stimulation (a signal) and resolves its detail(s). This is the case of a symbol like “E”: the stimulus is detected, then it is resolved as three horizontal bars and a vertical bar. In fact, within the clinical setting visual acuity is usually measured with alphanumeric symbols and is a three-step process that involves not only detection and resolution, but, due to the semantic content of letters and numbers, their recognition. Along with subjective (psychophysical) procedures, objective methods that do not require the active participation of the observer have been proposed to estimate visual acuity in non-collaborating subjects, malingerers, or toddlers. This paper aims to explain the psychophysical rationale underlying the measurement of visual acuity and revise the most common procedures used for its assessment.

Abstract: Myopia prevalence is dramatically increasing in recent years and in cases in which the refractive error is greater than ?6.00 D this disease can lead to severe visual impairment as well as even blindness. Changes in visual input affect the balance between ocular growth and refractive power development. If a mismatch occurs during eye development, the severity of this error affects the degree of myopia. In different animal models of this disease, we found that spatial visual stimuli are essential for maintaining a stable refractive status and normal vision. This is evident because the effects of changes in temporal visual stimuli (e.g., flickering light) on this process depend on whether spatial information is present or absent in the visual environment. Furthermore, the frequency, wavelength and intensity of light are involved in controlling refraction development. However, the molecular mechanisms underlying light-induced refraction changes are still unclear. There is definitive evidence that dopamine (DA) is one of the regulators of this process. This retinal neurotransmitter released by dopaminergic amacrine cells appears to play an important role in vision-guided eye growth because its synthesis and release are positively associated with the light intensity and spatial stimuli impinging on the retina. We found that bright light enhances retinal DA synthesis, and attenuates form deprivation myopia (FDM) development via activation of the dopamine receptor 1 (D1R). A nonselective DA receptor agonist apomorphine (APO) inhibited FDM in dopamine receptor 2 (D2R) knockout mice. These individual similar effects of DA and APO in wildtype and D2R knockout mice suggest that D1R activation has a protective effect against myopia development. On the other hand, D2R activation instead appears to promote myopia development because either genetic D2R ablation or pharmacological inactivation of D2R also attenuates myopia development. Based on these results, we hypothesize that the visual environment regulates the retinal DA levels, which in turn affects the relative balance between D1R and D2R activation. When D1R is relatively hyperactivated, the ocular refractive status shifts towards hyperopia. In contrast, such an effect on D2Rpromotes the refractive status to shift in the opposite direction towards myopia.

Background: Visual cortex neurons often respond to stimuli very differently on repeated trials. This trial-by-trial variability is known to be correlated among nearby neurons. Our long-term goal is to quantitatively estimate neuronal response variability, using multi-channel local field potential (LFP) data from single trials.

Methods: Acute experiments were performed with anesthetized (Remifentanil, Propofol, nitrous oxide) and paralyzed (Gallamine Triethiodide) cats. Computer-controlled visual stimuli were displayed on a gamma-corrected CRT monitor. For the principal experiment, two kinds of visual stimuli were used: drifting sine-wave gratings, and a uniform mean-luminance gray screen. These two stimuli were each delivered monocularly for 100 sec in a random order, for 10 trials. Multi-unit activity (MUA) and LFP signals were extracted from broadband raw data acquired from Area 17 and 18 using A1X32 linear arrays (NeuroNexus) and the OpenEphys recording system. LFP signal processing was performed using Chronux, an open-source MATLAB toolbox. Current source density (CSD) analysis was performed on responses to briefly flashed full-field stimuli using the MATLAB toolbox, CSDplotter. The common response variability (global noise) of MUA was estimated using the model proposed by Scholvinck et al. [2015].

Results: On different trials, a given neuron responded with different firing to the same visual stimuli. Within one trial, a neuron’s firing rate also fluctuated across successive cycles of a drifting grating. When the animal was given extra anesthesia, neurons fired in a desynchronized pattern; with lighter levels of anesthesia, neuronal firing because more synchronized. By examining the cross-correlations of LFP signals recorded from different cortical layers, we found LFP signals could be divided to two groups: those recorded in layer IV and above, and those from layers V and VI. Within each group, LFP signals recorded by different channels are highly correlated. These two groups were observed in lighter and deeper anesthetized animals, also in sine-wave and uniform gray stimulus conditions. We also investigated correlations between LFP signals and global noise. Power in the LFP beta band was highly correlated with global noise, when animals were in deeper anesthesia.

Conclusions: Brain states contribute to variations in neuronal responses. Raw LFP correlation results suggest that we should analyze LFP data according to their laminar organization. Correlation of low-frequency LFP under deeper anesthesia with global noise gives us some insight to predict noise from single-trial data, and we hope to extend this analysis to lighter anesthesia in the future.

Perception is the ability to see, hear, or become aware of external stimuli through the senses. Visual stimuli are electromagnetic waves that interact with the eye and elicit a sensation. Sensations, indeed, imply the detection, resolution, and recognition of objects and images, and their accuracy depends on the integrity of the visual system. In clinical practice, evaluating the integrity of the visual system relies greatly on the assessment of visual acuity, that is to say on the capacity to identify a signal. Visual acuity, indeed, is of utmost importance for diagnosing and monitoring ophthalmological diseases. Visual acuity is a function that detects the presence of a stimulation (a signal) and resolves its detail(s). This is the case of a symbol like “E”: the stimulus is detected, then it is resolved as three horizontal bars and a vertical bar. In fact, within the clinical setting visual acuity is usually measured with alphanumeric symbols and is a three-step process that involves not only detection and resolution, but, due to the semantic content of letters and numbers, their recognition. Along with subjective (psychophysical) procedures, objective methods that do not require the active participation of the observer have been proposed to estimate visual acuity in non-collaborating subjects, malingerers, or toddlers. This paper aims to explain the psychophysical rationale underlying the measurement of visual acuity and revise the most common procedures used for its assessment.

Background: The complexity of the glaucoma pathophysiology is directly reflected on its experimental modeling for studies about pathological mechanisms and treatment approaches. Currently, a variety of in vivo models are available for the study of glaucoma, although they do not reach an exact reproduction of all aspects characterizing the human glaucoma. Therefore, a comprehensive view of disease onset, progression and treatment efficacy can only be obtained by the integration of outcomes deriving from different experimental models.

Methods: The present article summary experimental procedures and analytical methodologies related with two experimental models of glaucoma belonging to the classes of induced intraocular pressure (IOP)-elevation and genetic models, methyl cellulose (MCE)-induced ocular hypertension and DBA/2J mouse strain. Point-by-point protocols are reported with a particular focus on the critical point for the realization of each model. Moreover, typical strength and drawbacks of each model are described in order to critically handle the outcomes deriving from each model.

Discussion: This paper provides a guideline for the realization, analysis and expected outcomes of two models allowing to study IOP-driven neurodegenerative mechanisms rather than IOP-independent neurodegeneration. The complementary information from these models could enhance the analysis of glaucomatous phenomena from different points of view potentiating the basic and translational study of glaucoma.

Background: The complexity of the glaucoma pathophysiology is directly reflected on its experimental modeling for studies about pathological mechanisms and treatment approaches. Currently, a variety of in vivo models are available for the study of glaucoma, although they do not reach an exact reproduction of all aspects characterizing the human glaucoma. Therefore, a comprehensive view of disease onset, progression and treatment efficacy can only be obtained by the integration of outcomes deriving from different experimental models.

Methods: The present article summary experimental procedures and analytical methodologies related with two experimental models of glaucoma belonging to the classes of induced intraocular pressure (IOP)-elevation and genetic models, methyl cellulose (MCE)-induced ocular hypertension and DBA/2J mouse strain. Point-by-point protocols are reported with a particular focus on the critical point for the realization of each model. Moreover, typical strength and drawbacks of each model are described in order to critically handle the outcomes deriving from each model.

Discussion: This paper provides a guideline for the realization, analysis and expected outcomes of two models allowing to study IOP-driven neurodegenerative mechanisms rather than IOP-independent neurodegeneration. The complementary information from these models could enhance the analysis of glaucomatous phenomena from different points of view potentiating the basic and translational study of glaucoma.