Visually responsive neurons typically exhibit a monotonic-saturating increase of firing with luminance contrast of the stimulus and are able to adapt to the current spatiotemporal context by shifting their selectivity, therefore being perfectly suited for optimal contrast encoding and discrimination. Here we report the first evidence of the existence of neurons showing selective tuning for contrast in area V4d of the behaving macaque (Macaca mulatta), i.e., narrow bandpass filter neurons with peak activity encompassing the whole range of visible contrasts and pronounced attenuation at contrasts higher than the peak. Crucially, we found that contrast tuning emerges after a considerable delay from stimulus onset, likely reflecting the contribution of inhibitory mechanisms. Selective tuning for luminance contrast might support multiple functions, including contrast identification and the attentive selection of low contrast stimuli.

Although a lot is known about various properties of the motion aftereffect (MAE), there is no systematic study of the topographic organization of MAE. In the current study, first we provided a topographic map of the MAE to investigate its spatial properties in detail. To provide a fine topographic map, we measured MAE with small test stimuli presented at different loci after adaptation to motion in a large region within the visual field. We found that strength of MAE is highest on the internal edge of the adapted area. Our results show a sharper aftereffect boundary for the shearing motion compared to compression and expansion boundaries. In the second experiment, using a similar paradigm, we investigated topographic deformation of the MAE area after a single saccadic eye movement. Surprisingly, we found that topographic map of MAE splits into two separate regions after the saccade: one corresponds to the retinal location of the adapted stimulus and the other matches the spatial location of the adapted region on the display screen. The effect was stronger at the retinotopic location. The third experiment is basically replication of the second experiment in a smaller zone that confirms the results of previous experiments in individual subjects. The eccentricity of spatiotopic area is different from retinotopic area in the second experiment; Experiment 3 controls the effect of eccentricity and confirms the major results of the second experiment.

Background: Amyloid-β positivity (Aβ+) based on PET imaging is part of the enrollment criteria for many of the clinical trials of Alzheimer's disease (AD), particularly in trials for amyloid-targeted therapy. Predicting Aβ positivity prior to PET imaging can decrease unnecessary patient burden and costs of running these trials. Objective: The aim of this study was to evaluate the performance of a machine learning model in estimating the individual risk of Aβ+ based on gold-standard of PET imaging. Methods: We used data from an amnestic mild cognitive impairment (aMCI) subset of the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort to develop and validate the models. The predictors of Aβ status included demographic and ApoE4 status in all models plus a combination of neuropsychological tests (NP), MRI volumetrics, and cerebrospinal fluid (CSF) biomarkers. Results: The models that included NP and MRI measures separately showed an area under the receiver operating characteristics (AUC) of 0.74 and 0.72, respectively. However, using NP and