Mechanics of the Developing Brain: From Smooth-walled Tube to the Folded Cortex

Over the course of human development, the brain undergoes dramatic physical changes to achieve its final, convoluted shape. However, the forces underlying every cinch, bulge, and fold remain poorly understood. This doctoral research focuses on the mechanical processes responsible for early (embryonic) and late (preterm) brain development. First, we examine early brain development in the chicken embryo, which is similar to human at these stages. Research has primarily focused on molecular signals to describe morphogenesis, but mechanical analysis can also provide important insights. Using a combination of experiments and finite element modeling, we find that actomyosin contraction is responsible for initial segmentation of the forebrain. By considering mechanical forces from the internal and external environment, we propose a role for mechanical feedback in maintaining these segments during subsequent inflation and bending. Next, we extend our analysis to division of right and left cerebral hemispheres. In this case, we discover that morphogen signals and mechanical feedback act synergistically to shape the hemispheres. In human, cerebral hemispheres go on to form complex folds through a mechanical process that involves rapid expansion of the cortical surface. However, the spatiotemporal dynamics of cortical growth remain unknown in human. Here, we develop a novel strain energy minimization approach to measure regional growth in complex surfaces. By considering brain surfaces of preterm subjects, reconstructed from magnetic resonance imaging (MRI), this analysis reveals distinct patterns of cortical growth that evolve over the third trimester. This information provides a comprehensive view of cortical growth and folding, connecting what is known about patterns of development at the cellular and folding scales. Abnormal brain morphogenesis can lead to serious structural defects and neurological disorders such as epilepsy and autism. By integrating mechanics, biology, and neuroimaging, we gain a more complete understanding of brain development. By studying physical changes from the simple, microscopic embryo to the macroscopic, folded cortex, we gain insight into relevant biological and physical mechanisms across developmental stages

Probing resting-state functional connectivity in the infant brain: methods and potentiality

Early brain development is characterized by rapid growth and perpetual reconfiguration, driven by a dynamic milieu of heterogeneous processes. Moreover, potent postnatal brain plasticity engenders increased vulnerability to environmental stimuli. However, little is known regarding the ontogeny and temporal manifestations of inter- and intra-regional functional connectivity that comprise functional brain networks. Recently, resting-state functional magnetic resonance imaging (fMRI) emerged as a promising non-invasive neuroinvestigative tool, measuring spontaneous fluctuations in blood oxygen level dependent (BOLD) signal at rest that reflect baseline neuronal activity. Its application has expanded to infant populations in the past decade, providing unprecedented insight into functional organization of the developing brain, as well as early biomarkers of abnormal/ disease states. However, rapid extension of the resting-state technique to infant populations leaves many methodological issues need to be resolved prior to standardization of the technique. The purpose of this thesis is to describe a protocol for intrinsic functional connectivity analysis, and extraction of resting-state networks in infants <12 months of age using the data-driven approach independent component analysis (ICA). To begin, we review the evolution of resting-state fMRI application in infant populations, including the biological premise for neural networks. Next, we present a protocol designed such that investigators without previous knowledge in the field can implement the analysis and reliably obtain viable results consistent with previous literature. Presented protocol provides detailed, albeit basic framework for RSN analysis, with interwoven discussion of basic theory behind each technique, as well as the rationale behind selecting parameters. The overarching goal is to catalyze efforts towards development of robust, infant-specific acquisition and preprocessing pipelines, as well as promote greater transparency by researchers regarding methods used. Finally, we review the literature, current methodological challenges and potential future directions for the field of infant resting-state fMRI

The role of MRI in diagnosing autism: a machine learning perspective.

There is approximately 1 in every 44 children in the United States suffers from autism spectrum disorder (ASD), a disorder characterized by social and behavioral impairments. Communication difficulties, interpersonal difficulties, and behavioral difficulties are the top common symptoms. Even though symptoms can begin as early as infancy, it may take multiple visits to a pediatric specialist before an accurate diagnosis can be made. In addition, the diagnosis can be subjective, and different specialists may give different scores. There is a growing body of research suggesting differences in brain development and/or environmental and/or genetic factors contribute to autism development, but scientists have yet to identify exactly the pathology of this disorder. ASD can currently be diagnosed by a set of diagnostic evaluations, regarded as the gold standard, such as the Autism Diagnostic Observation Schedule (ADOS) or the Autism Diagnostic Interview-Revised (ADI-R). A team of qualified clinicians is needed for performing the behavioral and communication tests as well as clinical history information, hence a considerable amount of time, effort, and subjective judgment is involved in using these gold-standard diagnostic instruments. In addition to standard observational assessment, recent advancements in neuroimaging and machine learning suggest a rapid and objective alternative, using brain imaging. An investigation of the employment of different imaging modalities, namely Diffusion Tensor Imaging (DTI), and resting state functional MRI (rs-fMRI) for autism diagnosis is presented in this comprehensive work. A detailed study of the implementation of feature engineering tools to find discriminant insights from different brain imaging modalities, including the use of novel feature representations, and the use of a machine learning framework to assist in the accurate classification of autistic individuals is introduced in this dissertation. Based on three large publicly available datasets, this extensive research highlights different decisions along the pipeline and their impact on diagnostic accuracy. It also identifies potentially impacted brain regions that contribute to an autism diagnosis. Achieving high global state-of-the-art cross-validated accuracy confirms the benefits of feature representation and feature engineering in extracting useful information, as well as the potential benefits of utilizing neuroimaging in the diagnosis of autism. This should enable an early, automated, and more objective personalized diagnosis

Resting-State Functional Connectivity in the Infant Brain: Methods, Pitfalls, and Potentiality

Early brain development is characterized by rapid growth and perpetual reconfiguration, driven by a dynamic milieu of heterogeneous processes. Postnatal brain plasticity is associated with increased vulnerability to environmental stimuli. However, little is known regarding the ontogeny and temporal manifestations of inter- and intra-regional functional connectivity that comprise functional brain networks. Resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a promising non-invasive neuroinvestigative tool, measuring spontaneous fluctuations in blood oxygen level dependent (BOLD) signal at rest that reflect baseline neuronal activity. Over the past decade, its application has expanded to infant populations providing unprecedented insight into functional organization of the developing brain, as well as early biomarkers of abnormal states. However, many methodological issues of rs-fMRI analysis need to be resolved prior to standardization of the technique to infant populations. As a primary goal, this methodological manuscript will (1) present a robust methodological protocol to extract and assess resting-state networks in early infancy using independent component analysis (ICA), such that investigators without previous knowledge in the field can implement the analysis and reliably obtain viable results consistent with previous literature; (2) review the current methodological challenges and ethical considerations associated with emerging field of infant rs-fMRI analysis; and (3) discuss the significance of rs-fMRI application in infants for future investigations of neurodevelopment in the context of early life stressors and pathological processes. The overarching goal is to catalyze efforts toward development of robust, infant-specific acquisition, and preprocessing pipelines, as well as promote greater transparency by researchers regarding methods used

Resting-State Functional Connectivity in the Infant Brain: Methods, Pitfalls, and Potentiality

Early brain development is characterized by rapid growth and perpetual reconfiguration, driven by a dynamic milieu of heterogeneous processes. Postnatal brain plasticity is associated with increased vulnerability to environmental stimuli. However, little is known regarding the ontogeny and temporal manifestations of inter- and intra-regional functional connectivity that comprise functional brain networks. Resting-state functional magnetic resonance imaging (rs-fMRI) has emerged as a promising non-invasive neuroinvestigative tool, measuring spontaneous fluctuations in blood oxygen level dependent (BOLD) signal at rest that reflect baseline neuronal activity. Over the past decade, its application has expanded to infant populations providing unprecedented insight into functional organization of the developing brain, as well as early biomarkers of abnormal states. However, many methodological issues of rs-fMRI analysis need to be resolved prior to standardization of the technique to infant populations. As a primary goal, this methodological manuscript will (1) present a robust methodological protocol to extract and assess resting-state networks in early infancy using independent component analysis (ICA), such that investigators without previous knowledge in the field can implement the analysis and reliably obtain viable results consistent with previous literature; (2) review the current methodological challenges and ethical considerations associated with emerging field of infant rs-fMRI analysis; and (3) discuss the significance of rs-fMRI application in infants for future investigations of neurodevelopment in the context of early life stressors and pathological processes. The overarching goal is to catalyze efforts toward development of robust, infant-specific acquisition, and preprocessing pipelines, as well as promote greater transparency by researchers regarding methods used

Monitoring Subcellular Calcium by Designed Calcium Sensors and the Calcium Sensing Receptor Structure and Function

Calcium (Ca2+) regulates various biological and pathological functions via calcium dynamics and interacting with key calcium binding proteins such as the calcium sensing receptor (CaSR). In this dissertation, the first X-ray structure of the extracellular domain of CaSR was determined by engineering mammalian expression systems. The revealed Ca2+/Mg2+ and Trp derivative L-1,2,3,4-tetrahydronorharman-3-carboxylic acid (TNCA) binding sites and key determinants contribute to the functional cooperativity of CaSR in cells. Magnesium (Mg2+) acts as a heterotropic cooperative co-agonist with calcium to co-activate the function of CaSR, including calcium oscillations. TNCA potentiates CaSR co-activation and recovers a loss of function caused by mutation at the dimer interface calcium binding site. Several mutations of the main Ca2+/TNCA binding site at the hinge region eliminate CaSR activity. Mutations S272A and D216N at the hinge region lead to a loss of Ca2+ binding and complete loss of cooperative binding for Tb3+ using bacterially expressed protein and Trp-sensitized FRET assay. Efforts in the development of new CaSR therapeutics using structure-based drug design were also explored. Next, we aimed to monitor endoplasmic/sarcoplasmic reticulum (ER/SR) mediated subcellular Ca2+ dynamics using our designed calcium sensors CatchER+ and CatchER+-JP45. Using highly inclined laminated optical (HILO) microscopy, we report calcium dynamics in the ER/SR with differential calcium responses to 4-cmc for release and recovery indicating differential Ca2+ signaling from Ca2+ and protein expression subcellular microdomains. We find Ca2+ dynamic differences between the localized high Ca2+ release region of the junctional SR for E-C coupling with targeted CatchER+-JP45 to ryanodine receptor over the global Ca2+ ER/SR regulation of CatchER+ sensor. To understand ER Ca2+ dynamics in neurons, we utilized our sensor CatchER+ and high-resolution HILO imaging to show that 100 µM DHPG induced mGluR1/5 activation leads to IP3R Ca2+ release as well as Ca2+ uptake throughout the soma and dendrites. The differential release and uptake for the ER Ca2+ dynamics in response to DHPG indicates subcellular microdomains throughout the neurons as well. These sensors will significantly impact Ca2+ dynamics research and molecular basis of ER Ca2+ related diseases by exposing Ca2+ dynamics, function, mobility, and trafficking in the ER/SR

Brain mechanisms of acoustic communication in humans and nonhuman primates: An evolutionary perspective

Any account of “what is special about the human brain” (Passingham 2008) must specify the neural basis of our unique ability to produce speech and delineate how these remarkable motor capabilities could have emerged in our hominin ancestors. Clinical data suggest that the basal ganglia provide a platform for the integration of primate-general mechanisms of acoustic communication with the faculty of articulate speech in humans. Furthermore, neurobiological and paleoanthropological data point at a two-stage model of the phylogenetic evolution of this crucial prerequisite of spoken language: (i) monosynaptic refinement of the projections of motor cortex to the brainstem nuclei that steer laryngeal muscles, presumably, as part of a “phylogenetic trend” associated with increasing brain size during hominin evolution; (ii) subsequent vocal-laryngeal elaboration of cortico-basal ganglia circuitries, driven by human-specific FOXP2 mutations.;>This concept implies vocal continuity of spoken language evolution at the motor level, elucidating the deep entrenchment of articulate speech into a “nonverbal matrix” (Ingold 1994), which is not accounted for by gestural-origin theories. Moreover, it provides a solution to the question for the adaptive value of the “first word” (Bickerton 2009) since even the earliest and most simple verbal utterances must have increased the versatility of vocal displays afforded by the preceding elaboration of monosynaptic corticobulbar tracts, giving rise to enhanced social cooperation and prestige. At the ontogenetic level, the proposed model assumes age-dependent interactions between the basal ganglia and their cortical targets, similar to vocal learning in some songbirds. In this view, the emergence of articulate speech builds on the “renaissance” of an ancient organizational principle and, hence, may represent an example of “evolutionary tinkering” (Jacob 1977)

Lycium barbarum (wolfberry) polysaccharide facilitates ejaculatory behaviour in male rats

Poster Session AOBJECTIVE: Lycium barbarum (wolfberry) is a traditional Chinese medicine, which has been considered to have therapeutic effect on male infertility. However, there is a lack of studies support the claims. We thus investigated the effect of Lycium barbarum polysaccharide (LBP), a major component of wolfberry, on male rat copulatory behavior. METHOD: Sprague-Dawley rats were divided into two groups (n=8 for each group). The first group received oral feeding of LBP at dosage of 1mg/kg daily. The control group received vehicle (0.01M phosphate-buffered saline, served as control) feeding daily for 21 days. Copulatory tests were conducted at 7, 14 and 21 days after initiation of treatment. RESULTS: Compared to control animals, animals fed with 1mg/kg LBP showed improved copulatory behavior in terms of: 1. Higher copulatory efficiency (i.e. higher frequency to show intromission rather than mounting during the test), 2. higher ejaculation frequency and 3. Shorter ejaculation latency. The differences were found at all time points (Analyzed with two-tailed student’s t-test, p<0.05). There is no significant difference found between the two groups in terms of mount/intromission latency, which indicates no difference in time required for initiation of sexual activity. Additionally, no difference in mount frequency and intromission frequency was found. CONCLUSION: The present study provides scientific evidence for the traditional use of Lycium barbarum on male sexual behavior. The result provides basis for further study of wolfberry on sexual functioning and its use as an alternative treatment in reproductive medicine.postprintThe 30th Annual Meeting of the Australian Neuroscience Society, in conjunction with the 50th Anniversary Meeting of the Australian Physiological Society (ANS/AuPS 2010), Sydney, Australia, 31 January-3 February 2010. In Abstract Book of ANS/AuPS, 2010, p. 177, abstract no. POS-TUE-19

Effects of mutations in the eEF1A2 gene in mouse gene expression profiles and identification of potential markers for motor neuron degeneration

The elongation factor 1 alpha (eEF1A) exists in mammals as two highly conserved isoforms: eEF1A1 and eEF1A2 which share 98% amino acid sequence similarity. When bound with GTP, both forms recruit aminoacylated-tRNA for delivery to the ribosome during translation elongation. eEF1A1 is expressed ubiquitously during development and is downregulated in mature neurones, cardiomyocytes and myocytes. Downregulation is observed concurrently with eEF1A2 expression increasing in the terminally differentiated cells. This shift in expression may be resultant of non-canonical roles that can differ between isoforms, and although eEF1A1 is well characterised, less is known about eEF1A2. Given the tissue-specific nature of this shift, it suggests that eEF1A2 may be involved in the development of neurodegeneration. eEF1A2 in humans has been implicated in severe neurodevelopmental disorders, in which sufferers can display symptoms of repeated seizures, intellectual disability and autism. However, patients carry differing mutations in eEF1A2 and each case can present varied severity of symptoms. To explore the effects that mutations in eEF1A2 have, two mouse lines were generated using CRISPR/Cas9; a mutation that was found in humans, D252H and a deletion that arose in the founders, Del.22.ex3. Homozygous (-/-) mice displayed a severe neurodegenerative phenotype. In Del.22.ex3, eEF1A2 is absent in homozygotes, whereas in D252H, mice express eEF1A2 but the protein is impaired or non-functional. An analysis of the founder mice identified mosaic alleles, some had incorporated the target mutation but a range of insertions and deletions were also present. The expression of eEF1A2 was observed to be reduced across the mosaic mice. The extent of neuronal damage that loss of functioning eEF1A2 may cause was investigated by immunohistochemistry. Identification of biomarkers for prognostic purposes for potential therapies of motor neuron degeneration was conducted by a bottom up proteomic approach. Label-free quantitative mass spectrometry was used to define the proteome of spinal cords from homozygotes and wild types for comparative study and identified potential biomarkers. In complement, an analysis on microarray data from wasted mice spinal cords identified differentially expressed genes. Some of these supported proteins of interest as being significantly differentially regulated, whilst not being confounded by varying protein turnover rates or stability. Proteins and genes that were significantly differentially expressed underwent gene ontology enrichment analysis exploring which pathways and functions were overrepresented to better understand pathogenesis, some of which demonstrated affiliation with neuronal disorders and cell metabolism. Understanding the loss of eEF1A2 and its neuronal degeneration phenotype, the affected protein and genetic expression patterns across the spinal cord has elucidated proteins enriched for particular pathways, and provided possible prognostic benchmarks for future therapeutic development. However these finding are only preliminary and more penetrating study is required into the differences of expression profiles between healthy and diseased mice with more replicates, as well as establishing whether the changes observed are within the translationally impaired motor neurons or glial cells