Cerebellar Development and Plasticity: Perspectives for Motor Coordination Strategies, for Motor Skills, and for Therapy

The role of the mammalian cerebellum ranges from motor coordination, sensory-motor integration, motor learning, and timing to nonmotor functions such as cognition. In terms of motor function, the development of the cerebellum is of particular interest because animal studies show that the development of the cerebellar cortical circuitry closely parallels motor coordination. Ultrastructural analysis of the morphological development of the cerebellar circuitry, coupled with the temporal and spatial identification of the neurochemical substrates expressed during development, will help to elucidate their roles in the establishment of the cerebellar circuitry and hence motor activity. Furthermore, the convenience of a number of naturally occurring mouse mutations has allowed a functional dissection of the various cellular elements that make up the cerebellar circuitry. This understanding will also help in the approach to possible therapies of pathologies arising during development because tile cerebellum is especially prone to such perturbation because of its late development

Manage comfort preferences conflicts using a multi-agent system in an adaptive environment system

Managing comfort preferences conflicts of the different users and locals on an IoT adaptive system is a actual problem, this paper proposes a protocol and hierarchical rules to develop a multi-agent system to achieve a Adaptive Environment System that solves the management of conflicts in an autonomous way for the users and interdependent of the user schedules and routines.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019

Corticotropin-releasing factor receptor types 1 and 2 are differentially expressed in pre- and post-synaptic elements in the post-natal developing rat cerebellum

Corticotropin-releasing factor (CRF)-like proteins act via two G-protein-coupled receptors (CRF-R1 and CRF-R2) playing important neuromodulatory roles in stress responses and synaptic plasticity. The cerebellar expression of corticotropin-releasing factor-like ligands has been well documented, but their receptor localization has not. This is the first combination of a light microscopic and ultrastructural study to localize corticotropin-releasing factor receptors immunohistologically in the developing rat cerebellum. Both CRF-R1 and CRF-R2 were expressed in climbing fibres from early stages (post-natal day 3) to the adult, but CRF-R2 immmunoreactivity was only prominent throughout the molecular layer in the posterior cerebellar lobules. CRF-R1 immunoreactivity was concentrated in apical regions of Purkinje cell somata and later in primary dendrites exhibiting a diffuse cytoplasmic appearance. In Purkinje cells, CRF-R1 immunoreactivity was never membrane bound post-synaptically in dendritic spines while CRF-R2 immunoreactivity was found on plasmic membranes of Purkinje cells from post-natal day 15 onwards. We conclude that the localization of these receptors in cerebellar afferents implies their pre-synaptic control of the release of corticotropin-releasing factor-like ligands, impacting on the sensory information being transmitted from afferents. Furthermore, the fact that CRF-R2 is membrane bound at synapses, while CRF-R1 is not, suggests that ligands couple to CRF-R2 via synaptic transmission and to CRF-R1 via volume transmission. Finally, the distinct expression profiles of receptors along structural domains of Purkinje cells suggest that the role for these receptors is to modulate afferent inputs

Prevalence of face recognition deficits in middle childhood

Approximately 2-2.5% of the adult population is believed to show severe difficulties with face recognition, in the absence of any neurological injury – a condition known as developmental prosopagnosia (DP). However, to date no research has attempted to estimate the prevalence of face recognition deficits in children, possibly because there are very few child-friendly, well-validated tests of face recognition. In the current study, we examined face and object recognition in a group of primary school children (aged 5-11 years), to establish whether our tests were suitable for children; and to provide an estimate of face recognition difficulties in children. In Experiment 1 (n = 184), children completed a pre-existing test of child face memory, the CFMT-K, and a bicycle test with the same format. In Experiment 2 (n = 413), children completed three-alternative forced choice matching tasks with faces and bicycles. All tests showed good psychometric properties. The face and bicycle tests were well-matched for difficulty and showed a similar developmental trajectory. Neither the memory nor matching tests were suitable to detect impairments in the youngest groups of children, but both tests appear suitable to screen for face recognition problems in middle childhood. In the current sample, 1.2-5.2% of children showed difficulties with face recognition; 1.2-4% showed face-specific difficulties – that is, poor face recognition with typical object recognition abilities. This is somewhat higher than previous adult estimates: it is possible that face matching tests overestimate the prevalence of face recognition difficulties in children; alternatively, some children may “outgrow” face recognition difficulties

Interacting mindreaders

Could interacting mindreaders be in a position to know things which they would be unable to know if they were manifestly passive observers? This paper argues that they could. Mindreading is sometimes reciprocal: the mindreader's target reciprocates by taking the mindreader as a target for mindreading. The paper explains how such reciprocity can significantly narrow the range of possible interpretations of behaviour where mindreaders are, or appear to be, in a position to interact. A consequence is that revisions and extensions are needed to standard theories of the evidential basis of mindreading. The view also has consequences for understanding how abilities to interact combined with comparatively simple forms of mindreading may explain the emergence, in evolution or development, of sophisticated forms of social cognition

Active Coordination in Ad Hoc Networks

Abstract. The increasing ubiquity of communicating mobile devices and vastly different mobile application needs have led to the emergence of middleware models for ad hoc networks that simplify application pro-gramming. One such system, EgoSpaces, addresses specific needs of indi-vidual applications, allowing them to define what data is included in their operating context using declarative specifications constraining properties of data, agents that own the data, hosts on which those agents are run-ning, and attributes of the ad hoc network. In the resulting coordination model, application agents interact with a dynamically changing environ-ment through a set of views, or custom defined projections of the set of data present in the surrounding ad hoc network. This paper builds on EgoSpaces by allowing agents to assign behaviors to their personal-ized views. Behaviors consist of actions that are automatically performed in response to specified changes in a view. Behaviors discussed in this paper encompass reactive programming, transparent data migration, au-tomatic data duplication, and event capture. Formal semantic definitions and programming examples are given for each behavior.

A Statistically Rigorous Test for the Identification of Parent−Fragment Pairs in LC-MS Datasets

Untargeted global metabolic profiling by liquid chromato-graphy−mass spectrometry generates numerous signals that are due to unknown compounds and whose identification forms an important challenge. The analysis of metabolite fragmentation patterns, following collision-induced dissociation, provides a valuable tool for identification, but can be severely impeded by close chromatographic coelution of distinct metabolites. We propose a new algorithm for identifying related parent−fragment pairs and for distinguishing these from signals due to unrelated compounds. Unlike existing methods, our approach addresses the problem by means of a hypothesis test that is based on the distribution of the recorded ion counts, and thereby provides a statistically rigorous measure of the uncertainty involved in the classification problem. Because of technological constraints, the test is of primary use at low and intermediate ion counts, above which detector saturation causes substantial bias to the recorded ion count. The validity of the test is demonstrated through its application to pairs of coeluting isotopologues and to known parent−fragment pairs, which results in test statistics consistent with the null distribution. The performance of the test is compared with a commonly used Pearson correlation approach and found to be considerably better (e.g., false positive rate of 6.25%, compared with a value of 50% for the correlation for perfectly coeluting ions). Because the algorithm may be used for the analysis of high-mass compounds in addition to metabolic data, we expect it to facilitate the analysis of fragmentation patterns for a wide range of analytical problems

Performance evaluation of bluetooth low energy for high data rate body area networks

Bluetooth Low Energy (BLE) is a promising wireless network technology, in the context of body area network (BAN) applications, to provide the required quality of service (QoS) support concerning the communication between sensor nodes placed on a user’s body and a personal device, such as a smartphone. Most previous BLE performance studies in the literature have focused primarily in networks with a single slave (point-to-point link) or traffic scenarios with relatively low data rate. However, many BAN sensors generate high data rate traffic, and several sensor nodes (slaves) may be actively sending data in the same BAN. Therefore, this work focuses on the evaluation of the suitability of BLE mainly under these conditions. Results show that, for the same traffic, the BLE protocol presents lower energy consumption and supports more sensor nodes than an alternative IEEE 802.15.4-based protocol. This study also identifies and characterizes some implementation constraints on the tested platforms that impose limits on the achievable performance.This work has been supported by FCT (Fundação para a Ciência e Tecnologia) in the scope of the projects UID/EEA/04436/2013 and UID/CTM/50025/2013, and by FEDER funds through the COMPETE 2020 Programme

Untargeted UPLC-MS Profiling Pipeline to Expand Tissue Metabolome Coverage: Application to Cardiovascular Disease.

Metabolic profiling studies aim to achieve broad metabolome coverage in specific biological samples. However, wide metabolome coverage has proven difficult to achieve, mostly because of the diverse physicochemical properties of small molecules, obligating analysts to seek multiplatform and multimethod approaches. Challenges are even greater when it comes to applications to tissue samples, where tissue lysis and metabolite extraction can induce significant systematic variation in composition. We have developed a pipeline for obtaining the aqueous and organic compounds from diseased arterial tissue using two consecutive extractions, followed by a different untargeted UPLC-MS analysis method for each extract. Methods were rationally chosen and optimized to address the different physicochemical properties of each extract: hydrophilic interaction liquid chromatography (HILIC) for the aqueous extract and reversed-phase chromatography for the organic. This pipeline can be generic for tissue analysis as demonstrated by applications to different tissue types. The experimental setup and fast turnaround time of the two methods contributed toward obtaining highly reproducible features with exceptional chromatographic performance (CV % < 0.5%), making this pipeline suitable for metabolic profiling applications. We structurally assigned 226 metabolites from a range of chemical classes (e.g., carnitines, α-amino acids, purines, pyrimidines, phospholipids, sphingolipids, free fatty acids, and glycerolipids) which were mapped to their corresponding pathways, biological functions and known disease mechanisms. The combination of the two untargeted UPLC-MS methods showed high metabolite complementarity. We demonstrate the application of this pipeline to cardiovascular disease, where we show that the analyzed diseased groups (<i>n </i>= 120) of arterial tissue could be distinguished based on their metabolic profiles