A simple method for detecting chaos in nature

Chaos, or exponential sensitivity to small perturbations, appears everywhere in nature. Moreover, chaos is predicted to play diverse functional roles in living systems. A method for detecting chaos from empirical measurements should therefore be a key component of the biologist's toolkit. But, classic chaos-detection tools are highly sensitive to measurement noise and break down for common edge cases, making it difficult to detect chaos in domains, like biology, where measurements are noisy. However, newer tools promise to overcome these limitations. Here, we combine several such tools into an automated processing pipeline, and show that our pipeline can detect the presence (or absence) of chaos in noisy recordings, even for difficult edge cases. As a first-pass application of our pipeline, we show that heart rate variability is not chaotic as some have proposed, and instead reflects a stochastic process in both health and disease. Our tool is easy-to-use and freely available

An approach for identifying brainstem dopaminergic pathways using resting state functional MRI.

Here, we present an approach for identifying brainstem dopaminergic pathways using resting state functional MRI. In a group of healthy individuals, we searched for significant functional connectivity between dopamine-rich midbrain areas (substantia nigra; ventral tegmental area) and a striatal region (caudate) that was modulated by both a pharmacological challenge (the administration of the dopaminergic agonist bromocriptine) and a dopamine-sensitive cognitive trait (an individual's working memory capacity). A significant inverted-U shaped connectivity pattern was found in a subset of midbrain-striatal connections, demonstrating that resting state fMRI data is sufficiently powerful to identify brainstem neuromodulatory brain networks

The Molecular Signature for Local Adaptation in the Seagrass <i>Posidonia oceanica</i>

In the last century, seagrass ecosystems have suffered a worldwide decline ascribed to multiple environmental stressors, among which the reduction of light available for the photosynthesis and the increase in temperature represent the strongest constraints for their growth and survival. Despite conservation, this decline is at present still continuing. In order to understand the genetic adaptive response to light and temperature in the seagrass Posidonia oceanica, two different strategies have been pursued: a genome scan approach along a latitudinal and a bathymetric gradient and a differential gene expression analysis along the bathymetric gradient, where light and temperature were the two main selective factors. For the genome scan approach 6 populations (Delimara - Malta, Lacco Ameno - Island of Ischia, Italy, Marettimo Island- Italy, Meloria - Italy, Piombino - Italy and Stareso - Corsica, France) were sampled along the bathymetric gradient at two different depths (-5m and -25m). The same populations were used for the latitudinal gradient analysis by grouping them on the basis of their geographic location (Southern group: Delimara, Lacco Ameno and Marettimo; Northern group: Meloria, Piombino and Stareso). No genes under selection were identified in the genome scan along the bathymetric gradient. Three putative genes under selection were identified in the genome scan along the latitudinal gradient and were involved in the photosynthesis and in the translation process. For assessing differential gene expression, a transcriptome sequencing of plants sampled at two different depths and different times of the day in the Stareso meadow was performed by RNAseq technology. The analysis highlighted the capability of plants living in shallow waters to cope with environmental stresses imposed by high light and high temperature. Transcriptome data generated from this study increased the resources available in P. oceanica and will be very useful for further investigations of the adaptation of in this plant

Development of three-dimensional, ex vivo optical imaging

The ability to analyse tissue in 3-D at the mesoscopic scale (resolution: 2-50 µm) has proven essential in the study of whole specimens and individual organs. Techniques such as ex vivo magnetic resonance imaging (MRI) and X-ray computed tomography (CT) have been successful in a number of applications. Although MRI has been used to image embryo development and gene expression in 3-D, its resolution is not sufficient to discriminate between the small structures in embryos and individual organs. Furthermore, since neither MRI nor X-ray CT are optical imaging techniques, none of them is able to make use of common staining techniques. 3-D images can be generated with confocal microscopy by focusing a laser beam to a point within the sample and collecting the fluorescent light coming from that specific plane, eliminating therefore out-of-focus light. However, the main drawback of this microscopy technique is the limited depth penetration of light (~1 mm). Tomographic techniques such as optical projection tomography (OPT) and light sheet fluorescence microscopy (also known as single plane illumination microscopy, SPIM) are novel methods that fulfil a requirement for imaging of specimens which are too large for confocal imaging and too small for conventional MRI. To allow sufficient depth penetration, these approaches require specimens to be rendered transparent via a process known as optical clearing, which can be achieved using a number of techniques. The aim of the work presented in this thesis was to develop methods for threedimensional, ex vivo optical imaging. This required, in first instance, sample preparation to clear (render transparent) biological tissue. In this project several optical clearing techniques have been tested in order to find the optimal method per each kind of tissue, focusing on tumour tissue. Indeed, depending on its structure and composition (e.g. amount of lipids or pigments within the tissue) every tissue clears at a different degree. Though there is currently no literature reporting quantification of the degree of optical clearing. Hence a novel, spectroscopic technique for measuring the light attenuation in optically cleared samples is described in this thesis and evaluated on mouse brain. 5 Optical clearing was applied to the study of cancer. The main cancer model investigated in this report is colorectal carcinoma. Fluorescently labelled proteins were used to analyse the vascular network of colorectal xenograft tumours and to prove the effect of vascular disrupting agents on the vascular tumour network. Furthermore, optical clearing and fluorescent compounds were used for ex vivo analysis of perfusion of a human colorectal liver metastasis model

A mechanistic model of connector hubs, modularity, and cognition

The human brain network is modular--comprised of communities of tightly interconnected nodes. This network contains local hubs, which have many connections within their own communities, and connector hubs, which have connections diversely distributed across communities. A mechanistic understanding of these hubs and how they support cognition has not been demonstrated. Here, we leveraged individual differences in hub connectivity and cognition. We show that a model of hub connectivity accurately predicts the cognitive performance of 476 individuals in four distinct tasks. Moreover, there is a general optimal network structure for cognitive performance--individuals with diversely connected hubs and consequent modular brain networks exhibit increased cognitive performance, regardless of the task. Critically, we find evidence consistent with a mechanistic model in which connector hubs tune the connectivity of their neighbors to be more modular while allowing for task appropriate information integration across communities, which increases global modularity and cognitive performance

Peer aggression among adolescents: characteristics of the victims

Peer aggression is a significant problem among adolescents; it is relatively common and frequently experienced among adolescents. Recently, there has been growing attention to the occurrence and impact of bullying on adolescent's well being at school. There is still a lot to learn about why certain adolescents are targets for bullying. This study explores how certain personality traits, behaviors, and social status may be predictors for those who are targeted as victims of peer aggression. Students in three middle schools and one junior high school from three different school districts in Texas were asked to participate in this study. The sample consisted of 233 students. Students were both males and females who were attending 6th, 7th, and 8th grade and were between the ages of 12 and 15. Data was aggregated for each participating student from demographic information collected from the Cover Sheet, with participant demographics, Bullying/Victimization Scale (BVS), Behavior Assessment System for Children - Self-Report (BASC-SRP), and Social Support Scale for Children and Adolescents (Social Support - CFS). The data obtained supported the expectation that adolescents who presented with symptoms of depression, anxiety, low self-esteem, high external locus of control, low self-reliance, and high sense of inadequacy are more likely to become victims of peer aggression than adolescents who are more socially competent, more psychologically well-adjusted, and who have a higher internal locus of control. Additionally, adolescents who show signs of social stress may also be more likely to become victims of peer aggression. This is an important step in the needed research because the victim is often overlooked when peer aggression is occurring. Identification of potential victims and assistance with development of their social skills may aid them in avoiding acts of peer aggression

Network Changes in the Transition from Initial Learning to Well-Practiced Visual Categorization

Visual categorization is a remarkable ability that allows us to effortlessly identify objects and efficiently respond to our environment. The neural mechanisms of how visual categories become well-established are largely unknown. Studies of initial category learning implicate a network of regions that include inferior temporal cortex (ITC), medial temporal lobe (MTL), basal ganglia (BG), premotor cortex (PMC) and prefrontal cortex (PFC). However, how these regions change with extended learning is poorly characterized. To understand the neural changes in the transition from initially learned to well-practiced categorization, we used functional MRI and compared brain activity and functional connectivity when subjects performed an initially learned categorization task (100 trials of training) and a well-practiced task (4250 trials of training). We demonstrate that a similar network is implicated for initially learned and well-practiced categorization. Additionally, connectivity analyses reveal an increased coordination between ITC, MTL, and PMC when making category judgments during the well-practiced task. These results suggest that category learning involves an increased coordination between a distributed network of regions supporting retrieval and representation of categories

The positional-specificity effect reveals a passive-trace contribution to visual short-term memory.

The positional-specificity effect refers to enhanced performance in visual short-term memory (VSTM) when the recognition probe is presented at the same location as had been the sample, even though location is irrelevant to the match/nonmatch decision. We investigated the mechanisms underlying this effect with behavioral and fMRI studies of object change-detection performance. To test whether the positional-specificity effect is a direct consequence of active storage in VSTM, we varied memory load, reasoning that it should be observed for all objects presented in a sub-span array of items. The results, however, indicated that although robust with a memory load of 1, the positional-specificity effect was restricted to the second of two sequentially presented sample stimuli in a load-of-2 experiment. An additional behavioral experiment showed that this disruption wasn't due to the increased load per se, because actively processing a second object--in the absence of a storage requirement--also eliminated the effect. These behavioral findings suggest that, during tests of object memory, position-related information is not actively stored in VSTM, but may be retained in a passive tag that marks the most recent site of selection. The fMRI data were consistent with this interpretation, failing to find location-specific bias in sustained delay-period activity, but revealing an enhanced response to recognition probes that matched the location of that trial's sample stimulus