Development of microstructural and morphological cortical profiles in the neonatal brain

Interruptions to neurodevelopment during the perinatal period may have long-lasting consequences. However, to be able to investigate deviations in the foundation of proper connectivity and functional circuits, we need a measure of how this architecture evolves in the typically developing brain. To this end, in a cohort of 241 term-born infants, we used magnetic resonance imaging to estimate cortical profiles based on morphometry and microstructure over the perinatal period (37-44 weeks postmenstrual age, PMA). Using the covariance of these profiles as a measure of inter-areal network similarity (morphometric similarity networks; MSN), we clustered these networks into distinct modules. The resulting modules were consistent and symmetric, and corresponded to known functional distinctions, including sensory-motor, limbic, and association regions, and were spatially mapped onto known cytoarchitectonic tissue classes. Posterior regions became more morphometrically similar with increasing age, while peri-cingulate and medial temporal regions became more dissimilar. Network strength was associated with age: Within-network similarity increased over age suggesting emerging network distinction. These changes in cortical network architecture over an 8-week period are consistent with, and likely underpin, the highly dynamic processes occurring during this critical period. The resulting cortical profiles might provide normative reference to investigate atypical early brain development

Sexual Dimorphism in the Brain Correlates of Adult-Onset Depression: A Pilot Structural and Functional 3T MRI Study

Major Depressive Disorder (MDD) is a disabling illness affecting more than 5% of the elderly population. Higher female prevalence and sex-specific symptomatology have been observed, suggesting that biologically-determined dimensions might affect the disease onset and outcome. Rumination and executive dysfunction characterize adult-onset MDD, but sex differences in these domains and in the related brain mechanisms are still largely unexplored. The present pilot study aimed to explore any interactions between adult-onset MDD and sex on brain morphology and brain function during a Go/No-Go paradigm. We hypothesized to detect diagnosis by sex effects on brain regions involved in self-referential processes and cognitive control. Twenty-four subjects, 12 healthy (HC) (mean age 68.7 y, 7 females and 5 males) and 12 affected by adult-onset MDD (mean age 66.5 y, 5 females and 7 males), underwent clinical evaluations and a 3T magnetic resonance imaging (MRI) session. Diagnosis and diagnosis by sex effects were assessed on regional gray matter (GM) volumes and task-related functional MRI (fMRI) activations. The GM volume analyses showed diagnosis effects in left mid frontal cortex (p < 0.01), and diagnosis by sex effects in orbitofrontal, olfactory, and calcarine regions (p < 0.05). The Go/No-Go fMRI analyses showed MDD effects on fMRI activations in left precuneus and right lingual gyrus, and diagnosis by sex effects on fMRI activations in right parahippocampal gyrus and right calcarine cortex (p < 0.001, ≥ 40 voxels). Our exploratory results suggest the presence of sex-specific brain correlates of adult-onset MDD-especially in regions involved in attention processing and in the brain default mode-potentially supporting cognitive and symptom differences between sexes

Analytical fusion of multimodal magnetic resonance imaging to identify pathological states in genetically selected Marchigian Sardinian alcohol-preferring (msP) rats

[EN] Alcohol abuse is one of the most alarming issues for the health authorities. It is estimated that at least 23 million of European citizens are affected by alcoholism causing a cost around 270 million euros. Excessive alcohol consumption is related with physical harm and, although it damages the most of body organs, liver, pancreas, and brain are more severally affected. Not only physical harm is associated to alcohol-related disorders, but also other psychiatric disorders such as depression are often comorbiding. As well, alcohol is present in many of violent behaviors and traffic injures. Altogether reflects the high complexity of alcohol-related disorders suggesting the involvement of multiple brain systems. With the emergence of non-invasive diagnosis techniques such as neuroimaging or EEG, many neurobiological factors have been evidenced to be fundamental in the acquisition and maintenance of addictive behaviors, relapsing risk, and validity of available treatment alternatives. Alterations in brain structure and function reflected in non-invasive imaging studies have been repeatedly investigated. However, the extent to which imaging measures may precisely characterize and differentiate pathological stages of the disease often accompanied by other pathologies is not clear. The use of animal models has elucidated the role of neurobiological mechanisms paralleling alcohol misuses. Thus, combining animal research with non-invasive neuroimaging studies is a key tool in the advance of the disorder understanding. As the volume of data from very diverse nature available in clinical and research settings increases, an integration of data sets and methodologies is required to explore multidimensional aspects of psychiatric disorders. Complementing conventional mass-variate statistics, interests in predictive power of statistical machine learning to neuroimaging data is currently growing among scientific community. This doctoral thesis has covered most of the aspects mentioned above. Starting from a well-established animal model in alcohol research, Marchigian Sardinian rats, we have performed multimodal neuroimaging studies at several stages of alcohol-experimental design including the etiological mechanisms modulating high alcohol consumption (in comparison to Wistar control rats), alcohol consumption, and treatment with the opioid antagonist Naltrexone, a well-established drug in clinics but with heterogeneous response. Multimodal magnetic resonance imaging acquisition included Diffusion Tensor Imaging, structural imaging, and the calculation of magnetic-derived relaxometry maps. We have designed an analytical framework based on widely used algorithms in neuroimaging field, Random Forest and Support Vector Machine, combined in a wrapping fashion. Designed approach was applied on the same dataset with two different aims: exploring the validity of the approach to discriminate experimental stages running at subject-level and establishing predictive models at voxel-level to identify key anatomical regions modified during the experiment course. As expected, combination of multiple magnetic resonance imaging modalities resulted in an enhanced predictive power (between 3 and 16%) with heterogeneous modality contribution. Surprisingly, we have identified some inborn alterations correlating high alcohol preference and thalamic neuroadaptations related to Naltrexone efficacy. As well, reproducible contribution of DTI and relaxometry -related biomarkers has been repeatedly identified guiding further studies in alcohol research. In summary, along this research we demonstrate the feasibility of incorporating multimodal neuroimaging, machine learning algorithms, and animal research in the advance of the understanding alcohol-related disorders.[ES] El abuso de alcohol es una de las mayores preocupaciones de las autoridades sanitarias en la Unión Europea. El consumo de alcohol en exceso afecta en mayor o menor medida la totalidad del organismo siendo el páncreas e hígado los más severamente afectados. Además de estos, el sistema nervioso central sufre deterioros relacionados con el alcohol y con frecuencia se presenta en paralelo con otras patologías psiquiátricas como la depresión u otras adicciones como la ludopatía. La presencia de estas comorbidades demuestra la complejidad de la patología en la que multitud de sistemas neuronales interaccionan entre sí. El uso imágenes de resonancia magnética (RM) han ayudado en el estudio de enfermedades psiquiátricas facilitando el descubrimiento de mecanismos neurológicos fundamentales en el desarrollo y mantenimiento de la adicción al alcohol, recaídas y el efecto de los tratamientos disponibles. A pesar de los avances, todavía se necesita investigar más para identificar las bases biológicas que contribuyen a la enfermedad. En este sentido, los modelos animales sirven, por lo tanto, a discriminar aquellos factores únicamente relacionados con el alcohol controlando otros factores que facilitan el desarrollo del alcoholismo. Estudios de resonancia magnética en animales de laboratorio y su posterior evaluación en humanos juegan un papel fundamental en el entendimiento de las patologías psiquatricas como la addicción al alcohol. La imagen por resonancia magnética se ha integrado en entornos clínicos como prueba diagnósticas no invasivas. A medida que el volumen de datos se va incrementando, se necesitan herramientas y metodologías capaces de fusionar información de muy distinta naturaleza y así establecer criterios diagnósticos cada vez más exactos. El poder predictivo de herramientas derivadas de la inteligencia artificial como el aprendizaje automático sirven de complemento a tradicionales métodos estadísticos. En este trabajo se han abordado la mayoría de estos aspectos. Se han obtenido datos multimodales de resonancia magnética de un modelo validado en la investigación de patologías derivadas del consumo del alcohol, las ratas Marchigian-Sardinian desarrolladas en la Universidad de Camerino (Italia) y con consumos de alcohol comparables a los humanos. Para cada animal se han adquirido datos antes y después del consumo de alcohol y bajo dos condiciones de abstinencia (con y sin tratamiento de Naltrexona, una medicaciones anti-recaídas usada como farmacoterapia en el alcoholismo). Los datos de resonancia magnética multimodal consistentes en imágenes de difusión, de relaxometría y estructurales se han fusionado en un esquema analítico multivariable incorporando dos herramientas generalmente usadas en datos derivados de neuroimagen, Random Forest y Support Vector Machine. Nuestro esquema fue aplicado con dos objetivos diferenciados. Por un lado, determinar en qué fase experimental se encuentra el sujeto a partir de biomarcadores y por el otro, identificar sistemas cerebrales susceptibles de alterarse debido a una importante ingesta de alcohol y su evolución durante la abstinencia. Nuestros resultados demostraron que cuando biomarcadores derivados de múltiples modalidades de neuroimagen se fusionan en un único análisis producen diagnósticos más exactos que los derivados de una única modalidad (hasta un 16% de mejora). Biomarcadores derivados de imágenes de difusión y relaxometría discriminan estados experimentales. También se han identificado algunos aspectos innatos que están relacionados con posteriores comportamientos con el consumo de alcohol o la relación entre la respuesta al tratamiento y los datos de resonancia magnética. Resumiendo, a lo largo de esta tesis, se demuestra que el uso de datos de resonancia magnética multimodales en modelos animales combinados en esquemas analíticos multivariados es una herramienta válida en el entendimiento de patologías[CAT] L'abús de alcohol es una de les majors preocupacions per part de les autoritats sanitàries de la Unió Europea. Malgrat la dificultat de establir xifres exactes, se estima que uns 23 milions de europeus actualment sofreixen de malalties derivades del alcoholisme amb un cost que supera els 150.000 milions de euros per a la societat. Un consum de alcohol en excés afecta en major o menor mesura el cos humà sent el pàncreas i el fetge el més afectats. A més, el cervell sofreix de deterioraments produïts per l'alcohol i amb freqüència coexisteixen amb altres patologies com depressió o altres addiccions com la ludopatia. Tot aquest demostra la complexitat de la malaltia en la que múltiple sistemes neuronals interactuen entre si. Tècniques no invasives com el encefalograma (EEG) o imatges de ressonància magnètica (RM) han ajudat en l'estudi de malalties psiquiàtriques facilitant el descobriment de mecanismes neurològics fonamentals en el desenvolupament i manteniment de la addició, recaiguda i la efectivitat dels tractaments disponibles. Tot i els avanços, encara es necessiten més investigacions per identificar les bases biològiques que contribueixen a la malaltia. En aquesta direcció, el models animals serveixen per a identificar únicament dependents del abús del alcohol. Estudis de ressonància magnètica en animals de laboratori i posterior avaluació en humans jugarien un paper fonamental en l' enteniment de l'ús del alcohol. L'ús de probes diagnostiques no invasives en entorns clínics has sigut integrades. A mesura que el volum de dades es incrementa, eines i metodologies per a la fusió d' informació de molt distinta natura i per tant, establir criteris diagnòstics cada vegada més exactes. La predictibilitat de eines desenvolupades en el camp de la intel·ligència artificial com la aprenentatge automàtic serveixen de complement a mètodes estadístics tradicionals. En aquesta investigació se han abordat tots aquestes aspectes. Dades multimodals de ressonància magnètica se han obtingut de un model animal validat en l'estudi de patologies relacionades amb el consum d'alcohol, les rates Marchigian-Sardinian desenvolupades en la Universitat de Camerino (Italià) i amb consums d'alcohol comparables als humans. Per a cada animal es van adquirir dades previs i després al consum de alcohol i dos condicions diferents de abstinència (amb i sense tractament anti-recaiguda). Dades de ressonància magnètica multimodal constituides per imatges de difusió, de relaxometria magnètica i estructurals van ser fusionades en esquemes analítics multivariats incorporant dues metodologies validades en el camp de neuroimatge, Random Forest i Support Vector Machine. Nostre esquema ha sigut aplicat amb dos objectius diferenciats. El primer objectiu es determinar en quina fase experimental es troba el subjecte a partir de biomarcadors obtinguts per neuroimatge. Per l'altra banda, el segon objectiu es identificar el sistemes cerebrals susceptibles de ser alterats durant una important ingesta de alcohol i la seua evolució durant la fase del tractament. El nostres resultats demostraren que l'ús de biomarcadors derivats de varies modalitats de neuroimatge fusionades en un anàlisis multivariat produeixen diagnòstics més exactes que els derivats de una única modalitat (fins un 16% de millora). Biomarcadors derivats de imatges de difusió i relaxometria van contribuir de distints estats experimentals. També s'han identificat aspectes innats que estan relacionades amb posterior preferències d'alcohol o la relació entre la resposta al tractament anti-recaiguda i les dades de ressonància magnètica. En resum, al llarg de aquest treball, es demostra que l'ús de dades de ressonància magnètica multimodal en models animals combinats en esquemes analítics multivariats són una eina molt valida en l'enteniment i avanç de patologies psiquiàtriques com l'alcoholisme.Cosa Liñán, A. (2017). Analytical fusion of multimodal magnetic resonance imaging to identify pathological states in genetically selected Marchigian Sardinian alcohol-preferring (msP) rats [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/90523TESI

Brain connectivity dynamics in cisgender and transmen people with gender incongruence before gender affirmative hormone treatment

Large-scale brain network interactions have been described between trans- and cis-gender binary identities. However, a temporal perspective of the brain's spontaneous fuctuations is missing. We investigated the functional connectivity dynamics in transmen with gender incongruence and its relationship with interoceptive awareness. We describe four states in native and meta-state spaces: (i) one state highly prevalent with sparse overall connections; (ii) a second with strong couplings mainly involving components of the salience, default, and executive control networks. Two states with global sparse connectivity but positive couplings (iii) within the sensorimotor network, and (iv) between salience network regions. Transmen had more dynamical fuidity than cismen, while cismen presented less meta-state fuidity and range dynamism than transmen and ciswomen. A positive association between attention regulation and fuidity and meta-state range dynamism was found in transmen. There exist gender diferences in the temporal brain dynamism, characterized by distinct interrelations of the salience network as catalyst interacting with other networks. We ofer a functional explanation from the neurodevelopmental cortical hypothesis of a gendered-self

Identification of neurobiological mechanisms associated with attention deficits in adults post traumatic brain injury

Traumatic Brain Injury (TBI) is one of the major public health concerns with approximately 70 million new cases occurring worldwide per year. It is often caused by a forceful bump, blow, or jolt to the head, resulting in brain tissue damage and normal brain functions disruption. All grades of TBI, ranging from mild to severe, can cause wide-ranging and long-term effects on affected individuals, resulting in physical impairments, and neurocognitive consequences that permanently affect their abilities to perform daily activities. Attention deficits are the most common persisting neurocognitive consequences following TBI, which significantly contribute to poor academic and social functioning, and life-long learning difficulties of affected individuals. However, attention deficits have been evaluated and treated based on symptom endorsements from subjective observations, with few therapeutic interventions successfully translated to the clinic. The consensus regarding appropriate evaluation and treatment of TBI induced attention deficits in this cohort is rather limited due to the lack of investigations of the neurobiological substrates associated with this syndrome. The overall aim of this dissertation research is to systematically investigate the neurobiological mechanisms associated with attention deficits in adults post TBI by utilizing multiple powerful neuroimaging techniques including the functional near-infrared spectroscopy (fNIRS) and multimodal magnetic resonance imaging (MRI), with an ultimate goal of translating hypothesis-driven neurobiological correlates into the quantitatively measurable biomarkers for diagnosis of TBI-induced attention deficits and development of more refined long-term treatment and intervention strategies. This dissertation research is conducted through three specific projects. Project 1 focuses on the investigation of brain functional patterns including the regional cortical brain activation and between-regional pairwise functional connectivity responding to visual sustained attention processing in individuals with and without TBI, by utilizing the fNIRS technique. Project 2 continues the examination of brain functional patterns by assessing the whole brain network topological properties responding to visual sustained attention processing in a larger sample of individuals with and without TBI, by utilizing the functional MRI technique and a graph theoretic approach. Project 3, on the other hand, investigates the brain structural characteristics based on the same sample involved in Project 2, by utilizing the structural MRI and diffusion tensor imaging techniques. For all these three projects, the differences of these brain imaging measures are compared between the groups of TBI and control. Correlation analyses are further conducted between those brain imaging measures which shows significant between-group differences and attention-related behaviors. In addition, Project 3 additionally investigates gender-specific patterns of the altered brain structural properties in TBI patients, relative to controls. The outcome of this novel and valuable dissertation research may shed light on the neural mechanisms of attention deficits in adults post TBI, and may suggest the neurobiological targets for treatment of this severe and common condition. It may also provide important neural foundation for future research to develop effective rehabilitation strategies to improve attention processing in adults post TBI

Creating a new tool for Post-Traumatic Disorder treatment

The first article on real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback was published in 2003 (Weiskopf et al., 2003) with the aim to enable the subject to learn to control activation in rostral-ventral and dorsal anterior cingulate cortex (ACC). Rt-fMRI neurofeedback involves data collection of neural activity, real-time data preprocessing, online statistical analysis, providing the results back to the participant, and active effort of participant in order to either up- and/or down-regulate the target region’s activation. In the last 16 years the topic attracted great attention from different labs around the world and many different brain regions were regulated with the help of rt-fMRI neurofeedback. Nevertheless it had the most distinct impact in the clinical research as it could be used with clinical population in order to normalize their abnormal neural activity. The dissertation focused on the implementation of the rt-fMRI neurofeedback to the Post-Traumatic Stress Disorder (PTSD) patients. PTSD is developed as a result of experiencing a traumatic event in first hand or hearing that a close one experienced it. PTSD has a high prevalence (Kessler et al., 2005) and also high impact on the patient’s life quality (Warshaw et al., 1993). Unfortunately the response rate to the therapy is around 50% (Bradley et al., 2005; Stein et al., 2006). Hence, there is a need for a new treatment tool for PTSD. The neurocircuitry model of PTSD indicate that there is increased activity in amygdala, decreased activity in ventromedial prefrontral cortex (vmPFC)/rostral ACC (rACC) and hippocampus (Rauch et al., 2006). Animal model of PTSD revealed that stimulating rACC led to increase in extinction learning and rats exhibited less PTSD symptoms (Milad & Quirk, 2002). Following these findings, we decided to implement rACC rt-fMRI neurofeedback to PTSD patients. The first study focused to develop a new paradigm to target rACC and tested it with healthy population. We used Ekman faces as functional localizer in order to locate the rACC. Experimental design constituted of four functional runs in one session. The main aim was to assess the methods effectiveness in one session. Surprisingly eight out of sixteen female participants learned to regulate their rACC, whereas only four out of sixteen male participants were able to regulate their rACC at will. Interestingly the learner/non-learners are not widely reported in the rt-fMRI literature and no gender difference has been reported so far. As a result we decided to implement it with only one sex in PTSD group. In the second study we tested the paradigm with the female PTSD patients. Eight out of sixteen PTSD patients gained control over their rACC. We also found that PTSD patients recruited more brain regions, especially multi-sensory brain regions for the upregulation of rACC in comparison to healthy subjects. We failed to find a single factor to predict rACC control success across groups. There is a need for further study to identify the predictor factors. As a result we concluded that the best practice of rt-fMRI with PTSD patients would be to use it as a supportive tool to psychotherapy in order to identify the best working strategy for their treatment. Further research recommendations are discussed below

Differential structure-function network coupling in the inattentive and combined types of attention deficit hyperactivity disorder

The heterogeneous presentation of inattentive and hyperactive-impulsive core symptoms in attention deficit hyperactivity disorder (ADHD) warrants further investigation into brain network connectivity as a basis for subtype divisions in this prevalent disorder. With diffusion and resting-state functional magnetic resonance imaging data from the Healthy Brain Network database, we analyzed both structural and functional network efficiency and structure-functional network (SC-FC) coupling at the default mode (DMN), executive control (ECN), and salience (SAN) intrinsic networks in 201 children diagnosed with the inattentive subtype (ADHD-I), the combined subtype (ADHD-C), and typically developing children (TDC) to characterize ADHD symptoms relative to TDC and to test differences between ADHD subtypes. Relative to TDC, children with ADHD had lower structural connectivity and network efficiency in the DMN, without significant group differences in functional networks. Children with ADHD-C had higher SC-FC coupling, a finding consistent with diminished cognitive flexibility, for all subnetworks compared to TDC. The ADHD-C group also demonstrated increased SC-FC coupling in the DMN compared to the ADHD-I group. The correlation between SC-FC coupling and hyperactivity scores was negative in the ADHD-I, but not in the ADHD-C group. The current study suggests that ADHD-C and ADHD-I may differ with respect to their underlying neuronal connectivity and that the added dimensionality of hyperactivity may not explain this distinction.ope

Investigating structural and functional neural correlates in children and adolescents with antisocial behavior

Antisocial behavior is highly prevalent in young and adult populations worldwide and constitutes a major public health problem due to the huge burden on the individual as well as the significant economic burden on society. A better understanding of the underlying neurobiological mechanisms of antisocial behavior is warranted to improve current diagnostics (e.g. early detection of children at risk) and effective prevention/treatment programs. So far, neuroimaging studies have indicated neural atypicalities in youths with antisocial behavior; however, the direction and location of these brain alterations vary across studies. These ambiguities are most likely caused by the heterogeneity of the young samples with antisocial behavior studied, especially regarding sex, clinical diagnoses, and the presence of callous-unemotional traits. The central aim of this dissertation was to further the neuroscientific knowledge of antisocial behavior in children and adolescents by investigating the underlying structural and functional neurobiological characteristics, with an extra focus on possible sex differences and callous-unemotional traits. First, we examined the current neuroimaging literature, through meta-analyses, with the purpose of overcoming the heterogeneity of antisocial behavior and generating a common “overlapping” pattern of structural and functional atypicalities in youths with antisocial behavior. Secondly, the relation between callous-unemotional traits and brain structure was investigated separately for sex and independently of psychiatric comorbidities. Thirdly, this work investigated the white matter integrity within a homogenous group of girls with conduct disorder –the severe variant of antisocial behavior– in comparison to typically developing peers. This work expands our current knowledge on the structural and functional neural correlates in children and adolescents with antisocial behavior in several ways. For one, our meta-analytic results indicate a consistent pattern of gray matter reductions and hypoactivations in brain areas within the prefrontal and limbic cortex. These findings fit a recently proposed neurobiological model that connects alterations within similar brain regions with the behavioral dispositions of antisocial behavior (e.g. dysfunctions in empathy, emotional learning, and decision making). Secondly, we observed a positive relation between callous-unemotional traits and bilateral insula volume in a large international population of typically developing boys, but not in girls, independent of psychiatric disorders. This demonstrates that callous-unemotional traits have a sex-specific neurobiological basis beyond psychiatric samples. Thirdly, this work presents novel findings of white-matter integrity alterations in the body of the corpus callosum of girls with antisocial behavior, indicating possible reduced interhemispheric processing and consequent emotion processing abilities. In short, the present thesis provides original findings regarding the neurobiology of antisocial behavior in youths and emphasizes the importance of callous-unemotional traits and sex differences. Our results encourage future studies to further investigate the developmental trajectories and potential neural markers of antisocial behavior in order to enhance early detection and improve intervention programs, which could ultimately reduce antisocial behavior and delinquency in our society