The topological organization of the turtle cranium is constrained and conserved over long evolutionary timescales

The cranium of turtles (Testudines) is characterized by the secondary reduction of temporal fenestrae and loss of cranial joints (i.e., characteristics of anapsid, akinetic skulls). Evolution and ontogeny of the turtle cranium are associated with shape changes. Cranial shape variation among Testudines can partially be explained by dietary and functional adaptations (neck retraction), but it is unclear if cranial topology shows similar ecomorphological signal, or if it is decoupled from shape evolution. We assess the topological arrangement of cranial bones (i.e., number, relative positioning, connections), using anatomical network analysis. Non-shelled stem turtles have similar cranial arrangements to archosauromorph outgroups. Shelled turtles (Testudinata) evolve a unique cranial organization that is associated with bone losses (e.g., supratemporal, lacrimal, ectopterygoid) and an increase in complexity (i.e., densely and highly interconnected skulls with low path lengths between bones), resulting from the closure of skull openings and establishment of unusual connections such as a parietal-pterygoid contact in the secondary braincase. Topological changes evolutionarily predate many shape changes. Topological variation and taxonomic morphospace discrimination among crown turtles are low, indicating that cranial topology may be constrained. Observed variation results from repeated losses of nonintegral bones (i.e., premaxilla, nasal, epipterygoid, quadratojugal), and changes in temporal emarginations and palate construction. We observe only minor ontogenetic changes. Topology is not influenced by diet and habitat, contrasting cranial shape. Our results indicate that turtles have a unique cranial topology among reptiles that is conserved after its initial establishment, and shows that cranial topology and shape have different evolutionary histories.

[Deep brain stimulation as a treatment for severe multidrug-resistant obsessive compulsive disorder]

Obsessive compulsive disorder (OCD) is a common and disabling psychiatric condition. About 10 % of patients are considered to be severely affected and refractory to the usual treatments, combining antidepressants and psychotherapy. Deep brain stimulation (DBS) is a promising treatment, reserved for specialized university centers. It is based on the implantation of electrodes aimed at modulating dysfunctional cortico-striato-thalamo-cortical circuits. After studying the different targets to be used, it is now proposed to rethink DBS in terms of networks. The improvement of pathophysiological knowledge of OCD and the development of functional neuroimaging techniques should allow the design of individualized treatment protocols.

Characteristics of Neural Network Changes in Normal Aging and Early Dementia

To understand the mechanisms underlying preserved and impaired cognitive function in healthy aging and dementia, respectively, the spatial relationships of brain networks and mechanisms of their resilience should be understood. The hub regions of the brain, such as the multisensory integration and default mode networks, are critical for within- and between-network communication, remain well-preserved during aging, and play an essential role in compensatory processes. On the other hand, these brain hubs are the preferred sites for lesions in neurodegenerative dementias, such as Alzheimer's disease. Disrupted primary information processing networks, such as the auditory, visual, and sensorimotor networks, may lead to overactivity of the multisensory integration networks and accumulation of pathological proteins that cause dementia. At the cellular level, the brain hub regions contain many synapses and require a large amount of energy. These regions are rich in ATP-related gene expression and had high glucose metabolism as demonstrated on positron emission tomography (PET). Importantly, the number and function of mitochondria, which are the center of ATP production, decline by about 8% every 10 years. Dementia patients often have dysfunction of the ubiquitin-proteasome and autophagy-lysosome systems, which require large amounts of ATP. If there is low energy supply but the demand is high, the risk of disease can be high. Imbalance between energy supply and demand may cause accumulation of pathological proteins and play an important role in the development of dementia. This energy imbalance may explain why brain hub regions are vulnerable to damage in different dementias. Here, we review (1) the characteristics of gray matter network, white matter network, and resting state functional network changes related to resilience in healthy aging, (2) the mode of resting state functional network disruption in neurodegenerative dementia, and (3) the cellular mechanisms associated with the disruption.

Precision Estimates of Macroscale Network Organization in the Human and Their Relation to Anatomical Connectivity in the Marmoset Monkey

Precision estimates of network organization from functional connectivity MRI in the human and tract-tracing data in the marmoset monkey converge to reveal an orderly macroscale gradient of sequential networks across the cerebral cortex. Parallel networks begin with a sequence of multiple nested sensory-motor networks in both species progressing to more distributed association networks in rostral prefrontal and temporal association zones, which are expanded and differentiated in the human. From this perspective, the spatially-distributed motif encountered in association networks appears to be on a continuum with primary sensory-motor networks. Network motifs supporting sophisticated forms of human cognition may arise from specializations of distributed anatomical networks formed in an ancestor at least 45 million years ago.

Fingers zipped up or baby mittens? Two main tetrapod strategies to return to the sea

The application of network methodology in anatomical structures offers new insights on the connectivity pattern of skull bones, skeletal elements and their muscles. Anatomical networks helped to improve our understanding of the water-to-land transition and how the pectoral fins were transformed into limbs via their modular disintegration. Here, we apply the same methodology to tetrapods secondarily adapted to the marine environment. We find that these animals achieved their return to the sea with four types of morphological changes, which can be grouped into two different main strategies. In all marine mammals and the majority of the reptiles, the fin is formed by the persistence of superficial and interdigital connective tissues, like a 'baby mitten', whereas the underlying connectivity pattern of the bones does not influence the formation of the forefin. On the contrary, ichthyosaurs 'zipped up' their fingers and transformed their digits into carpal-like elements, forming a homogeneous and better-integrated forefin. These strategies led these vertebrates into three different macroevolutionary paths exploring the possible spectrum of morphological adaptations.

Multimodal connectivity based eloquence score computation and visualisation for computer-aided neurosurgical path planning

Non-invasive assessment of cognitive importance has been a major challenge for planning of neurosurgical procedures. In the past decade, in vivo brain imaging modalities have been considered for estimating the ‘eloquence’ of brain areas. In order to estimate the impact of damage caused by an access path towards a target region inside of the skull, multi-modal metrics are introduced in this paper. Accordingly, this estimated damage is obtained by combining multi-modal metrics. In other words, this damage is an aggregate of intervened grey matter volume and axonal fibre numbers, weighted by their importance within the assigned anatomical and functional networks. To validate these metrics, an exhaustive search algorithm is implemented for characterising the solution space and visually representing connectional cost associated with a path initiated from underlying points. In this presentation, brain networks are built from resting state functional magnetic resonance imaging (fMRI) and deterministic tractography. their results demonstrate that the proposed approach is capable of refining traditional heuristics, such as choosing the minimal distance from the lesion, by supplementing connectional importance of the resected tissue. This provides complementary information to help the surgeon in avoiding important functional hubs and their anatomical linkages; which are derived from neuroimaging modalities and incorporated to the related anatomical landmarks.

Neonatal neural networks predict children behavioral profiles later in life

This study aimed to examine heterogeneity of neonatal brain network and its prediction to child behaviors at 24 and 48 months of age. Diffusion tensor imaging (DTI) tractography was employed to construct brain anatomical network for 120 neonates. Clustering coefficients of individual structures were computed and used to classify neonates with similar brain anatomical networks into one group. Internalizing and externalizing behavioral problems were assessed using maternal reports of the Child Behavior Checklist (CBCL) at 24 and 48 months of age. The profile of CBCL externalizing and internalizing behaviors was then examined in the groups identified based on the neonatal brain network. Finally, support vector machine and canonical correlation analysis were used to identify brain structures whose clustering coefficients together significantly contribute the variation of the behaviors at 24 and 48 months of age. Four meaningful groups were revealed based on the brain anatomical networks at birth. Moreover, the clustering coefficients of the brain regions that most contributed to this grouping of neonates were significantly associated with childhood internalizing and externalizing behaviors assessed at 24 and 48 months of age. Specially, the clustering coefficient of the right amygdala was associated with both internalizing and externalizing behaviors at 24 months of age, while the clustering coefficients of the right inferior frontal cortex and insula were associated with externalizing behaviors at 48 months of age. Our findings suggested that neural organization established during fetal development could to some extent predict individual differences in behavioral-emotional problems in early childhood. Hum Brain Mapp 38:1362-1373, 2017. © 2016 Wiley Periodicals, Inc.

Beyond the functional matrix hypothesis: a network null model of human skull growth for the formation of bone articulations

Craniofacial sutures and synchondroses form the boundaries among bones in the human skull, providing functional, developmental and evolutionary information. Bone articulations in the skull arise due to interactions between genetic regulatory mechanisms and epigenetic factors such as functional matrices (soft tissues and cranial cavities), which mediate bone growth. These matrices are largely acknowledged for their influence on shaping the bones of the skull; however, it is not fully understood to what extent functional matrices mediate the formation of bone articulations. Aiming to identify whether or not functional matrices are key developmental factors guiding the formation of bone articulations, we have built a network null model of the skull that simulates unconstrained bone growth. This null model predicts bone articulations that arise due to a process of bone growth that is uniform in rate, direction and timing. By comparing predicted articulations with the actual bone articulations of the human skull, we have identified which boundaries specifically need the presence of functional matrices for their formation. We show that functional matrices are necessary to connect facial bones, whereas an unconstrained bone growth is sufficient to connect non-facial bones. This finding challenges the role of the brain in the formation of boundaries between bones in the braincase without neglecting its effect on skull shape. Ultimately, our null model suggests where to look for modified developmental mechanisms promoting changes in bone growth patterns that could affect the development and evolution of the head skeleton.