Data on the precise mechanisms of the complex interactions of factors related to clinical impact of knee osteoarthritis (KOA) in the elderly population remain limited. To find predictors that explain pain intensity, physical function, and quality of life in elderly KOA subjects, we performed a cross-sectional analysis of the baseline data from a randomized trial. The trial included 104 subjects (aged ≥60) with KOA pain and dysfunctional endogenous pain-inhibitory system activity assessed by conditioned pain modulation (CPM). Three multiple linear regression models were performed to understand the independent predictors of Brief Pain Inventory (BPI), WOMAC function subscale (WOMACFunc), and SF-12 physical subscale (SF12-PCS). Model 1 showed that BPI pain score was predicted by low CPM response, high von-Frey light touch threshold, worse radiological severity as indexed by Kellgren-Lawrence grade (KL), high von-Frey punctate pain intensity and high levels of anxiety (adjusted R2 = 27.1%, F (6,95) = 7.27, P < 0.0001). In model 2, von-Frey light touch threshold, KL, depressive symptoms indexed by Beck Depression Inventory (BDI), level of sleepiness and pain pressure threshold were risk factors for SF12-PCS (adjusted R2 = 31.9%, F (5,96) = 10.5, P < 0.0001). Finally, model 3 showed that WOMACFunc was predicted by BDI, KL and BPI (adjusted R2 = 41%, F (3,98) = 24.42, P < 0.0001). Our data provides an interesting framework to understand the predictors of KOA pain in the elderly and highlights how its related outcomes are affected by disease-specific factors, somatosensory dysfunction and emotional factors.

Several studies showed that shifting of visuospatial attention modulates sensory processing at multiple levels of the visual pathways and beyond, including the occipital striate cortices level. However, inconsistent findings have been reported thus leaving these issues still disputed. 21 participants took part to the present study (the EEG signals of 4 of them were discarded due to artifacts). We used ERPs and their neural sources to investigate whether shifting spatial attention in space across the horizontal meridian of the visual field affected striate cortices activation at the earliest latency. Time-series of scalp topographical maps indicated that, unlike ERPs to attentional-neutral central cues, ERPs to attention-directing local cues showed earliest polarity inversions as a function of stimulated field and processing latency range considered, at occipital-parietal electrodes. In between 60-75 ms, attentional shifting cues elicited a positivity for both visual fields, whereas at a later latency (75-90 ms) they elicited a positivity and a negativity for the upper and lower visual hemifields, respectively. Computed neural sources included striate, besides extrastriate, cortices for both visual hemifields and latency ranges. Conjointly, behavioral responses to targets were faster when they were preceded by local than by neutral cues, and when presented in the upper than the lower hemifield. Our findings support the hypothesis that attention shifts may affect early sensory processing in visual cortices.

Neuroscience is inherently interdisciplinary, rapidly expanding beyond its roots in biological sciences to many areas of the social and physical sciences. This expansion has led to more sophisticated ways of thinking about the links between brains and behavior and has inspired the development of increasingly advanced tools to characterize the activity of large populations of neurons. However, along with these advances comes a heightened risk of fostering confusion unless efforts are made to better integrate findings across different model systems and to develop a better understanding about how different measurement techniques provide mutually constraining information. Here we use selective visuospatial attention as a case study to highlight the importance of these issues, and we suggest that exploiting multiple measures can better constrain models that relate neural activity to animal behavior.