Interplay between perivascular and perineuronal extracellular matrix remodelling in neurological and psychiatric diseases.

Vascular damage, central nervous system (CNS) injury, seizure or even psychological stress may trigger activation of microglia and infiltration of other immune cells, accompanied by high levels of expression and activity of extracellular proteases, such as matrix metalloproteinases (MMPs), and degradation/remodelling of the perivascular and perineuronal extracellular matrix (ECM). This acute response is followed by the recovery/chronic phase, during which the activation of astrocytes leads to the upregulated synthesis of ECM molecules, which, in combination with elevated expression of tissue inhibitor of metalloproteinases (TIMP) proteins, increases the aggregation of ECM molecules. This biphasic dysregulation of local balance between extracellular proteases and the ECM activates multiple temporally overlapping signalling cascades, involving receptor-type protein tyrosine phosphatases, integrins, Toll-like receptors, cell adhesion molecules, and ion channels, resulting in impaired synaptic plasticity and cognition. An additional level of complexity is related to the leakage of blood plasma proteins, such as fibrinogen, and the diffusion of perivascularly overproduced MMPs, TIMPs and ECM molecules into the CNS parenchyma, leading to diverse effects on neurons and incorporation of these molecules into the interstitial neural ECM. This review aims to outline these complex common mechanisms in stroke, CNS injury, depression, epilepsy, multiple sclerosis and cerebral small vessel disease and to discuss translational strategies to advance the development of new therapies for these neurological and psychiatric diseases.

The cone method: Inferring decision times from single-trial 3D movement trajectories in choice behavior.

Ongoing goal-directed movements can be rapidly adjusted following new environmental information, e.g., when chasing pray or foraging. This makes movement trajectories in go-before-you-know decision-making a suitable behavioral readout of the ongoing decision process. Yet, existing methods of movement analysis are often based on statistically comparing two groups of trial-averaged trajectories and are not easily applied to three-dimensional data, preventing them from being applicable to natural free behavior. We developed and tested the cone method to estimate the point of overt commitment (POC) along a single two- or three-dimensional trajectory, i.e., the position where the movement is adjusted towards a newly selected spatial target. In Experiment 1, we established a "ground truth" data set in which the cone method successfully identified the experimentally constrained POCs across a wide range of all but the shallowest adjustment angles. In Experiment 2, we demonstrate the power of the method in a typical decision-making task with expected decision time differences known from previous findings. The POCs identified by cone method matched these expected effects. In both experiments, we compared the cone method's single trial performance with a trial-averaging method and obtained comparable results. We discuss the advantages of the single-trajectory cone method over trial-averaging methods and possible applications beyond the examples presented in this study. The cone method provides a distinct addition to existing tools used to study decisions during ongoing movement behavior, which we consider particularly promising towards studies of non-repetitive free behavior.

What makes a reach movement effortful? Physical effort discounting supports common minimization principles in decision making and motor control.

When deciding between alternative options, a rational agent chooses on the basis of the desirability of each outcome, including associated costs. As different options typically result in different actions, the effort associated with each action is an essential cost parameter. How do humans discount physical effort when deciding between movements? We used an action-selection task to characterize how subjective effort depends on the parameters of arm transport movements and controlled for potential confounding factors such as delay discounting and performance. First, by repeatedly asking subjects to choose between 2 arm movements of different amplitudes or durations, performed against different levels of force, we identified parameter combinations that subjects experienced as identical in effort (isoeffort curves). Movements with a long duration were judged more effortful than short-duration movements against the same force, while movement amplitudes did not influence effort. Biomechanics of the movements also affected effort, as movements towards the body midline were preferred to movements away from it. Second, by introducing movement repetitions, we further determined that the cost function for choosing between effortful movements had a quadratic relationship with force, while choices were made on the basis of the logarithm of these costs. Our results show that effort-based action selection during reaching cannot easily be explained by metabolic costs. Instead, force-loaded reaches, a widely occurring natural behavior, imposed an effort cost for decision making similar to cost functions in motor control. Our results thereby support the idea that motor control and economic choice are governed by partly overlapping optimization principles.

Deciding While Acting-Mid-Movement Decisions Are More Strongly Affected by Action Probability than Reward Amount.

When deciding while acting, such as sequentially selecting targets during naturalistic foraging, movement trajectories reveal the dynamics of the unfolding decision process. Ongoing and planned actions may impact decisions in these situations in addition to expected reward outcomes. Here, we test how strongly humans weigh and how fast they integrate individual constituents of expected value, namely the prior probability (PROB) of an action and the prior expected reward amount (AMNT) associated with an action, when deciding based on the combination of both together during an ongoing movement. Unlike other decision-making studies, we focus on PROB and AMNT priors, and not final evidence, in that correct actions were either instructed or could be chosen freely. This means, there was no decision-making under risk. We show that both priors gradually influence movement trajectories already before mid-movement instructions of the correct target and bias free-choice behavior. These effects were consistently stronger for PROB compared with AMNT priors. Participants biased their movements toward a high-PROB target, committed to it faster when instructed or freely chosen, and chose it more frequently even when it was associated with a lower AMNT prior than the alternative option. Despite these differences in effect magnitude, the time course of the effect of both priors on movement direction was highly similar. We conclude that prior action probability, and hence the associated possibility to plan actions accordingly, has higher behavioral relevance than prior action value for decisions that are expressed by adjusting already ongoing movements.

Integrated Dual Analysis of Quantitative and Qualitative High-Dimensional Data.

The Dual Analysis framework is a powerful enabling technology for the exploration of high dimensional quantitative data by treating data dimensions as first-class objects that can be explored in tandem with data values. In this article, we extend the Dual Analysis framework through the joint treatment of quantitative (numerical) and qualitative (categorical) dimensions. Computing common measures for all dimensions allows us to visualize both quantitative and qualitative dimensions in the same view. This enables a natural joint treatment of mixed data during interactive visual exploration and analysis. Several measures of variation for nominal qualitative data can also be applied to ordinal qualitative and quantitative data. For example, instead of measuring variability from a mean or median, other measures assess inter-data variation or average variation from a mode. In this work, we demonstrate how these measures can be integrated into the Dual Analysis framework to explore and generate hypotheses about high-dimensional mixed data. A medical case study using clinical routine data of patients suffering from Cerebral Small Vessel Disease (CSVD), conducted with a senior neurologist and a medical student, shows that a joint Dual Analysis approach for quantitative and qualitative data can rapidly lead to new insights based on which new hypotheses may be generated.

Retinal Vascular Pathology in a Rat Model of Cerebral Small Vessel Disease.

Introduction: The initial disease stages of hypertensive arteriopathy (HA) and cerebral amyloid angiopathy (CAA), the two main forms of sporadic human cerebral small vessel diseases (CSVD), are too subtle to be detectable on clinical routine imaging. Small vessel disease (SVD) is a systemic condition, affecting not only the brain, but also other organs. The retina appears as an ideal marker for the early detection of incipient CSVD. We therefore investigated the retinal microvasculature of the spontaneously hypertensive stroke-prone rat (SHRSP), an animal model of sporadic CSVD. Materials and Methods: The brains and retinas of 26 male SHRSP (18-44 weeks) were examined histologically and immunohistochemically for the presence of HA phenomena (erythrocyte thrombi, small perivascular bleeds) and amyloid angiopathy (AA). Results: CAA and AA in the retina showed a significant correlation with age (CAA: rho = 0.55, p = 0.005; AA: rho = 0.89, p < 0.001). The number of erythrocyte thrombi in the brain correlated with the severity of retinal erythrocyte thrombi (rho = 0.46, p = 0.023), while the occurrence of CAA correlated with the appearance of AA in the retina (rho = 0.51, p = 0.012). Retinal SVD markers predicted CSVD markers with good sensitivity. Conclusions: These results indicate that SVD also occurs in the retinal microvasculature of SHRSP and the prediction of cerebral erythrocyte thrombi and CAA might be possible using retinal biomarkers. This underlines the important role of the investigation of the retina in the early diagnosis of CSVD.