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Despite a myriad of potential pathways linking neighborhood change and gentrification to health, existing quantitative measures failed to capture individual-level, self-reported perceptions of these processes. We developed the Perceptions About Change in Environment and Residents (PACER) survey to measure the gentrification-related neighborhood change experienced by individuals relevant to health. We employed a multi-stage process to develop PACER including a scoping review, question refinement, content validity, and cognitive interviews. Content validity and cognitive interviews were assessed within the National Neighborhood Indicators Partnership (NNIP) and for residents of different tenure in both gentrifying and non-gentrifying neighborhoods to ensure PACER considers the complex nature of neighborhood change for different people within different urban contexts. We piloted the instrument to a sample from the resident panel BeHeardPhilly to assess acceptability and data quality. Finally, we assessed internal consistency, dimensionality, and criterion-related validity using Principal Components Analysis (PCA), descriptive statistics, and correlation coefficients. Testing showed good internal consistency for PACER questions, as well as for each of four resulting factors (Feelings, Built Environment, Social Environment, and Affordability). Correlations between factors and other context measures demonstrated strong criterion-related validity. PACER offers an unprecedented tool for measuring and understanding resident perceptions about gentrification-related neighborhood change relevant to health. Rigorously tested and tailored for health, PACER holds utility for application across different settings to examine changes from events that may impact and shift neighborhoods.

Echolocating bats can identify three-dimensional objects exclusively through the analysis of acoustic echoes of their ultrasonic emissions. However, objects of the same structure can differ in size, and the auditory system must achieve a size-invariant, normalized object representation for reliable object recognition. This study describes both the behavioral classification and the cortical neural representation of echoes of complex virtual objects that vary in object size. In a phantom-target playback experiment, it is shown that the bat Phyllostomus discolor spontaneously classifies most scaled versions of objects according to trained standards. This psychophysical performance is reflected in the electrophysiological responses of a population of cortical units that showed an object-size invariant response (14/109 units, 13%). These units respond preferentially to echoes from objects in which echo duration (encoding object depth) and echo amplitude (encoding object surface area) co-varies in a meaningful manner. These results indicate that at the level of the bat's auditory cortex, an object-oriented rather than a stimulus-parameter-oriented representation of echoes is achieved.