Geographic and socioeconomic access disparities to Phase 3 clinical trials in ophthalmology in the United States.

BACKGROUND/OBJECTIVE: To identify geographic and socioeconomic variables associated with residential proximity to Phase 3 ophthalmology clinical trial sites. METHODS: The geographic location of clinical trial sites for Phase 3 clinical trials in ophthalmology was identified using ClinicalTrials.gov. Driving time from each United States (US) census tract centroid to nearest clinical trial site was calculated using real traffic patterns. Travel data were crosslinked to census-tract level public datasets from United States Census Bureau American Community Survey (ACS). Cross-sectional multivariable regression was used to identify associations between census-tract sociodemographic factors and driving time (>60 min) from each census tract centroid to the nearest clinical trial site. RESULTS: There were 2330 unique clinical trial sites and 71,897 census tracts. Shortest median time was to retina sites [33.7 min (18.7, 70.1 min)]. Longest median time was to neuro-ophthalmology sites [119.8 min (48.7, 240.4 min)]. Driving >60 min was associated with rural tracts [adjusted odds ratio (aOR) 7.60; 95% CI (5.66-10.20), p < 0.0001]; Midwest [aOR 1.84(1.15-2.96), p = 0.01], South [aOR 2.57 (1.38-4.79), p < 0.01], and West [aOR 2.52 (1.52-4.17), p < 0.001] v. Northeast; and tracts with higher visual impairment [aOR 1.07 (1.03-1.10), p < 0.001)]; higher poverty levels [4th v.1st Quartile of population below poverty, aOR 2.26 (1.72-2.98), p < 0.0001]; and lower education levels [high school v. Bachelor's degree or higher aOR 1.02 (1.00-1.03), p = 0.0072]. CONCLUSIONS: There are significant geographic and socioeconomic disparities in access to ophthalmology clinical trial sites for rural, non-Northeastern, poorer, and lower education level census tracts, and for census tracts with higher levels of self-reported visual impairment.

Auditory cortex shapes sound responses in the inferior colliculus.

The extensive feedback from the auditory cortex (AC) to the inferior colliculus (IC) supports critical aspects of auditory behavior but has not been extensively characterized. Previous studies demonstrated that activity in IC is altered by focal electrical stimulation and pharmacological inactivation of AC, but these methods lack the ability to selectively manipulate projection neurons. We measured the effects of selective optogenetic modulation of cortico-collicular feedback projections on IC sound responses in mice. Activation of feedback increased spontaneous activity and decreased stimulus selectivity in IC, whereas suppression had no effect. To further understand how microcircuits in AC may control collicular activity, we optogenetically modulated the activity of different cortical neuronal subtypes, specifically parvalbumin-positive (PV) and somatostatin-positive (SST) inhibitory interneurons. We found that modulating the activity of either type of interneuron did not affect IC sound-evoked activity. Combined, our results identify that activation of excitatory projections, but not inhibition-driven changes in cortical activity, affects collicular sound responses.

How do we hear the world around us? Hearing begins when hair cells in the inner ear translate incoming sound waves into electrical signals. These signals travel via the auditory nerve and the brainstem to the midbrain, where an area called the inferior colliculus processes them. The inferior colliculus then passes the signals on to another area deep within the brain, the thalamus, which processes the signals further before it too passes them on to an area of the brain's outer layer called the auditory cortex. At each stage of the auditory pathway, the signals undergo more complex processing than at the previous stage. Researchers have tended to think of this pathway as a one-way route from the ear to the brain. But in reality, feedback occurs at various points along the pathway, enabling areas that do higher processing to shape the responses of areas earlier in the pathway. This feedback is particularly prevalent in the auditory system, where one such strong feedback route is from the auditory cortex to the inferior colliculus. This reverse connection helps animals learn new behavioral responses to sounds, for example, to run away from a loud noise. By manipulating the activity of this pathway in mice using a technique called optogenetics, Blackwell et al. provide further clues to how the auditory pathway works. Optogenetics involves introducing light-sensitive ion channels into neurons, and then using light to activate or inhibit those neurons on demand. Blackwell et al. show that activating the feedback pathway from the auditory cortex to the inferior colliculus in awake mice changes how the inferior colliculus responds to sounds. By contrast, inhibiting the pathway has no effect on inferior colliculus responses. This suggests that the feedback pathway is not active all the time, but instead influences inferior colliculus activity only during specific behavior, for example, perhaps when we are listening for a specific sound like the ringing of a phone. Understanding how the brain processes sound is important for understanding how we communicate and why we appreciate music. It could also help in treating hearing loss. Stimulating the inferior colliculus using a device implanted in the brainstem can improve hearing in people with certain types of deafness. Strengthening or weakening the feedback pathway from the auditory cortex to the inferior colliculus could make these implants more effective. In the future, it may even be possible that stimulating the pathway directly could restore hearing without any implant being required.

Projection from the Amygdala to the Thalamic Reticular Nucleus Amplifies Cortical Sound Responses.

Many forms of behavior require selective amplification of neuronal representations of relevant environmental signals. Emotional learning enhances sensory responses in the sensory cortex, yet the underlying circuits remain poorly understood. We identify a pathway between the basolateral amygdala (BLA), an emotional learning center in the mouse brain, and the inhibitory reticular nucleus of the thalamus (TRN). Optogenetic activation of BLA suppressed spontaneous, but not tone-evoked, activity in the auditory cortex (AC), amplifying tone-evoked responses. Viral tracing identified BLA projections terminating at TRN. Optogenetic activation of amygdala-TRN projections further amplified tone-evoked responses in the auditory thalamus and cortex. The results are explained by a computational model of the thalamocortical circuitry, in which activation of TRN by BLA primes thalamocortical neurons to relay relevant sensory input. This circuit mechanism shines a neural spotlight on behaviorally relevant signals and provides a potential target for the treatment of neuropsychological disorders.

Cortical Interneurons Differentially Shape Frequency Tuning following Adaptation.

Neuronal stimulus selectivity is shaped by feedforward and recurrent excitatory-inhibitory interactions. In the auditory cortex (AC), parvalbumin- (PV) and somatostatin-positive (SOM) inhibitory interneurons differentially modulate frequency-dependent responses of excitatory neurons. Responsiveness of neurons in the AC to sound is also dependent on stimulus history. We found that the inhibitory effects of SOMs and PVs diverged as a function of adaptation to temporal repetition of tones. Prior to adaptation, suppressing either SOM or PV inhibition drove both increases and decreases in excitatory spiking activity. After adaptation, suppressing SOM activity caused predominantly disinhibitory effects, whereas suppressing PV activity still evoked bi-directional changes. SOM, but not PV-driven inhibition, dynamically modulated frequency tuning with adaptation. Unlike PV-driven inhibition, SOM-driven inhibition elicited gain-like increases in frequency tuning reflective of adaptation. Our findings suggest that distinct cortical interneurons differentially shape tuning to sensory stimuli across the neuronal receptive field, altering frequency selectivity of excitatory neurons during adaptation.