Current neurobiological models of adolescent decision-making suggest that heightened risk taking during adolescence is a result of the asynchronous development of neural regions underlying cognitive control and reward processing, particularly during periods of heightened social and affective arousal (e.g., Casey, Getz, & Galván, 2008; Steinberg, 2008). Despite the emphasis on the interplay of cognitive and emotional processes during adolescence, the developmental literature has largely overlooked the potential importance of maturational changes in the anterior insular cortex (AIC), a region known for its role as a cognitive-emotional hub. In a recent review we proposed a theory of adolescent risk-taking in which development of the AIC, and its connectivity to other regions, biases adolescents towards engagement in risky behaviors (Smith, Steinberg, & Chein, 2014b). The current studies provide a test of the proposed model through an examination of specific aspects of AIC development and functioning, including the trajectory of structural development within the AIC, the role of AIC engagement in adolescents' risky decision-making, and the impacts of affective arousal on AIC recruitment. Results from Study 1 suggest that the AIC exhibits continued developmental changes during adolescence that likely affect its involvement in cognitive processes. Using a risk-taking task, Study 2 demonstrates the flexible role of the AIC during adolescent decision-making and explores how affective arousal biases the AIC towards engagement in risky behaviors. Implications for both the proposed model and the developmental literature are discussed. / Psychology

Neuropsychotherapy is a new philosophy in the treatment of mental disorders that bases its principles in the application of the information we have about the brain activations and brain functioning to adjust the therapy to them, in order to center the process in how the brain evolves to its normal activations. New tools in the field of neuroimaging have helped in this process, providing accurate and detailed information about how the particular brain of each patient works. Between the many neuroimaging techniques available nowadays, the functional magnetic resonance (fMRI) stands out by its high spatial resolution, which allows a better knowledge of which brain area is activated before each stimulus or while performing each activity. The disadvantages this technique presents in terms of size of the scanner and restriction of movements give light to another technique, more suitable in certain domains: the electroencephalography (EEG), which provides a greater freedom of movement and higher temporal resolution. For the purposes of this PhD Thesis, both techniques will be compared, in order to find which one better suits our interests. For doing so, another factor will be taken into account. Due to the limitations the neuroimaging techniques have in terms of presentation of the stimuli, we are not able to expose the subject to certain kinds of real life situations. There is where the virtual reality (VR) enters the scene. With VR we are able to move the subject to a virtual world where any kind of stimulus is possible. In the case of neuropsychotherapy, it will allow the exposition of the patient to a situation related to his disorder, in a safer and more controlled environment. In fact, virtual reality has been widely used for the treatment of psychological disorders; but, until now, it has not been applied during the assessment of the disease. For the aims of this Thesis, virtual environments will be used for the assessment of subjects before and after undergoing a psychological treatment for a specific disorder, using neuroimaging techniques to find useful information that could help during the therapeutic process. As an example of disorder, the phobia to small animals (spiders and cockroaches) has been chosen, although the conclusions of this study could be extended to other kinds of psychological disorders. Before being able to assure that the brain activations obtained are related to the disorder and not to other issues, it is needed to measure the sense of presence the subjects felt during the virtual experience. This is why before the assessment of a psychological disorder, a study of the sense of presence in a virtual environment was introduced. This study also helped in the decision of which neuroimaging technique apply in the second part of the Thesis. EEG and fMRI were used for the measure of presence in the same virtual environments, and the results in terms of brain activations were compared. Presence was also measured by means of questionnaires, the traditional subjective way of measuring it. As a result of this study it is expected to check if VR could effectively stimulate presence and which neuroimaging technique is more appropriate for the targets of this Thesis. To sum up, the initial hypotheses of this Thesis are that: 1- The new neuroimaging techniques can provide of useful information to use during neuropsychotherapy. 2- Virtual reality would help in the assessment of the disorder, improving the accuracy in the way the subjects are exposed to the stimuli. 3- The environments used would be immersive enough so the patient will feel present in them and feel them as real. For fulfilling these objectives, each of the two courses of work (study of presence and assessment of a mental disorder) was divided in two parts. In total, four studies were developed: 1- Study of the sense of presence in a virtual environment using fMRI: the aim of this part of the Thesis was to check if the environments were able to stimulate the sense of presence, correlating the results with those given to questionnaires. 2- Study of the sense of presence in a virtual environment using EEG: the aim here was to compare the brain activations obtained with EEG with those from the previous study, and if the responses of the questionnaires were equivalent despite being in a less intrusive scanner. As a result of these two studies, it was decided that the environments were immersive enough to induce the sense of presence, and that the best neuroimaging technique for the next part of the Thesis was the fMRI, due to the higher spatial resolution it brought. 3- Assessment of a psychological disorder, pre-treatment: once decided the study will continue with fMRI, the areas related to a specific disorder (small animals¿ phobia) were studied using VR as stimulus. Until now, the assessment has been done using real animals as stimuli but not using VR, which here is hypothesized to allow a better approach to the phobic experience than the view of photographs or videos of real animals. 4- Assessment of the state of subjects with a psychological disorder, post-treatment: once the patients had underwent a treatment to cure the disorder, they were assessed again to check if the brain areas related to the phobia stopped being activated after it. As a result of this second part of the Thesis, the brain areas related to the phobia (that stopped being activated after the treatment) were obtained, and this information is hoped to be useful in future neuropsychotherapeutic works, for the better adjustment of the disorder. In conclusion, this PhD Thesis studies the advantages that the new neuroimaging techniques and virtual reality could bring to the study of neuropsychotherapy. / Clemente Bellido, M. (2014). Contributions to Neuropsychotherapy of the Combined Use of Neuroimaging and Virtual Exposure for Assessment in Psychological Treatments [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/37234

Fluorescence microscopy has become an indispensable technology to push fundamental neuroscience by recovering labeled neural structures with high resolution. To enable these studies, the field has adopted the use of low-cost widefield 1-photon epi-fluorescence microscopes to image fixed samples and miniaturized head-mounted miniscopes to monitor neural activity in freely behaving animals. However, fluorescence imaging platforms face a number of challenges such as a limited depth of field (DoF), lack of optical sectioning, and susceptibility to scattering and aberrations which compromises the image quality and signal fidelity. As a result, neural studies are often constrained to a shallow volume near the surface of the sample and are limited by high noise and background. To overcome these challenges, this thesis introduces two novel frameworks that combine pupil engineering with computational imaging to push the performance of miniaturized and tabletop fluorescence neural imaging platforms. These strategies will directly optimize and integrate custom phase elements on the often-vacant pupil plane to enable the encoding of extended fluorescence signals by designing a point spread function (PSF) that exhibits an extended depth of field (EDoF) in scattering media. Next, these strategies will use tailored post processing algorithms to recover that extended information from the resulting images. As a result, this strategy allows for the recovery of sources in an extended neural volume without compromising the optical resolution or imaging speed on the underlying platform. First, this thesis introduces EDoF-Miniscope, a miniaturized neural imaging platform which utilizes a novel physics-informed genetic algorithm to optimize a lightweight binary diffractive optical element (DOE) on the pupil plane. By integrating the binary DOE into a prototype platform, EDoF-Miniscope is able to achieve a 2.8x extension in the DoF between twin imaging foci in neural samples. To enable the recovery of the extended sources, this thesis utilizes a straightforward post-processing filter, which can recover neuronal signals with an SBR down to 1.08. Overall, this framework introduces a generalizable, compact and lightweight solution for augmenting miniscopes with a computational EDoF. Next, I improve upon the proposed framework by designing a flexible 1-photon widefield tabletop platform, entitled EDoF-Tabletop, that exhibits comparable field-of-view (FoV, FoV = 0.6x0.6mm), numerical aperture (NA, NA = 0.5) and aberrations to a miniscope. This platform utilizes a spatial light modulator (SLM) on the pupil plane to rapidly deploy optimized pupil phase profiles without the need of manufacturing, aligning and integrating miniaturized optics. EDoF-Tabletop incorporates a deep optics pipeline, which utilizes novel physical modeling, initialization and training strategies to simultaneously and reliably learn a user-defined EDoFs and a reconstruction using synthetic-only data. As a result, EDoF-Tabletop is able to encode and recover signals from EDoFs up to 140-microns deep in neural samples and 400-microns deep in non-scattering samples. By combining pupil engineering with computational imaging, EDoF-Miniscope and EDoF-Tabletop showcase the potential to enhance neural imaging platforms by extracting information from extended volumes in the brain. By focusing on flexible optimization algorithms and rapid prototyping capabilities, the advancements introduced in this thesis promise broader utility across fluorescence microscopy, where capturing detailed information from complex biological samples is essential for advancing scientific understanding.

Aggression linked to peer-based social rejection is a damaging and highly prevalent problem, especially during adolescence when peer relationships are particularly important. Because adolescence is a sensitive period for neural plasticity, identifying neural mechanisms that bias youth towards perpetrating aggression before habitual antisocial tendencies are instantiated may help develop novel interventions. Aggressive behavior is likely influenced by a complex cascade of neural responses that unfold across a social interaction, therefore methods that examine how neural network associations predict rejection-elicited aggression are needed. Progress towards this goal has been hindered by the limited availability of ecologically-valid fMRI-based social interaction tasks that delineate temporal stages within a social interaction, such as anticipation and receipt of peer feedback, and contemplating aggression. This study addresses these limitations by using a novel fMRI-based paradigm, the Virtual School and Aggression (VSA) task, to evoke rejection-elicited aggressive behavior in adolescents (N=34; 10-15 years). We demonstrate that engagement in the threat network while receiving rejecting feedback is predictive of subsequent aggressive behavior in adolescents. Lastly, we illustrate that engagement in the threat network while receiving nice feedback leads to inhibition in the cognitive control network while responding. These findings provide important targets to inform novel interventions for rejection-elicited aggression. / Psychology

Music's effect on non-musical domains has been an area of intense research. Musical training has been shown to positively affect the processing of phonology, lexical tone, and syntax. While music also has positive effects in second language phonology acquisition, its effect on grammar acquisition is contested. This thesis aimed to study the under-researched topic of music and second language grammar acquisition using electroencephalography (EEG), thereby studying the electrical responses of the brain. Beginning level Spanish students were trained on a new grammatical principle prior to performing a grammaticality judgment task, and their behavioral and neural results were analyzed. Those students with a stronger musical aptitude did not perform better than the other students in the grammaticality judgement task, nor was there any difference in their neural responses to critical syntactic violations.

Neurosurgery is a demanding medical discipline that requires a complex interplay of several neuroimaging techniques. This allows structural as well as functional information to be recovered and then visualized to the surgeon. In the case of tumor resections this approach allows more fine-grained differentiation of healthy and pathological tissue which positively influences the postoperative outcome as well as the patient's quality of life. In this work, we will discuss several approaches to establish thermal imaging as a novel neuroimaging technique to primarily visualize neural activity and perfusion state in case of ischaemic stroke. Both applications require novel methods for data-preprocessing, visualization, pattern recognition as well as regression analysis of intraoperative thermal imaging. Online multimodal integration of preoperative and intraoperative data is accomplished by a 2D-3D image registration and image fusion framework with an average accuracy of 2.46 mm. In navigated surgeries, the proposed framework generally provides all necessary tools to project intraoperative 2D imaging data onto preoperative 3D volumetric datasets like 3D MR or CT imaging. Additionally, a fast machine learning framework for the recognition of cortical NaCl rinsings will be discussed throughout this thesis. Hereby, the standardized quantification of tissue perfusion by means of an approximated heating model can be achieved. Classifying the parameters of these models yields a map of connected areas, for which we have shown that these areas correlate with the demarcation caused by an ischaemic stroke segmented in postoperative CT datasets. Finally, a semiparametric regression model has been developed for intraoperative neural activity monitoring of the somatosensory cortex by somatosensory evoked potentials. These results were correlated with neural activity of optical imaging. We found that thermal imaging yields comparable results, yet doesn't share the limitations of optical imaging. In this thesis we would like to emphasize that thermal imaging depicts a novel and valid tool for both intraoperative functional and structural neuroimaging.

Neurosurgery is a demanding medical discipline that requires a complex interplay of several neuroimaging techniques. This allows structural as well as functional information to be recovered and then visualized to the surgeon. In the case of tumor resections this approach allows more fine-grained differentiation of healthy and pathological tissue which positively influences the postoperative outcome as well as the patient's quality of life. In this work, we will discuss several approaches to establish thermal imaging as a novel neuroimaging technique to primarily visualize neural activity and perfusion state in case of ischaemic stroke. Both applications require novel methods for data-preprocessing, visualization, pattern recognition as well as regression analysis of intraoperative thermal imaging. Online multimodal integration of preoperative and intraoperative data is accomplished by a 2D-3D image registration and image fusion framework with an average accuracy of 2.46 mm. In navigated surgeries, the proposed framework generally provides all necessary tools to project intraoperative 2D imaging data onto preoperative 3D volumetric datasets like 3D MR or CT imaging. Additionally, a fast machine learning framework for the recognition of cortical NaCl rinsings will be discussed throughout this thesis. Hereby, the standardized quantification of tissue perfusion by means of an approximated heating model can be achieved. Classifying the parameters of these models yields a map of connected areas, for which we have shown that these areas correlate with the demarcation caused by an ischaemic stroke segmented in postoperative CT datasets. Finally, a semiparametric regression model has been developed for intraoperative neural activity monitoring of the somatosensory cortex by somatosensory evoked potentials. These results were correlated with neural activity of optical imaging. We found that thermal imaging yields comparable results, yet doesn't share the limitations of optical imaging. In this thesis we would like to emphasize that thermal imaging depicts a novel and valid tool for both intraoperative functional and structural neuroimaging.

L’objectif de cette thèse a été de comprendre les mécanismes cérébraux associés aux symptômes du trouble de stress post-traumatique (TSPT), ainsi que les mécanismes cérébraux modulés par la disparition des symptômes, en utilisant la thérapie de désensibilisation et de retraitement de l’information par les mouvements oculaires (Thérapie EMDR). Cette thérapie associe rappel du traumatisme et stimulations bilatérales alternées (SBA). Premièrement, en utilisant l’IRM fonctionnelle (IRMf), nous avons mis en évidence une altération de l’activité fonctionnelle du système de récompense dans le TSPT, correspondant à une mobilisation déséquilibrée des processus motivationnels cognitifs et hédoniques (étude 1). Deuxièmement, par l’intermédiaire d’une étude en IRMf au repos, nous avons montré que les patients présentent des altérations de connectivité fonctionnelle entre un réseau neuronal impliqué dans les processus mnésiques et émotionnels, et un réseau neuronal impliqué dans les processus attentionnels (étude 2). Troisièmement, nous avons montré que les structures initialement altérées par la pathologie évoluent après rémission symptomatique, suggérant un rétablissement des altérations neuronales induites par le stress chronique (étude 3). Enfin, nous avons montré que les SBA employées dans la thérapie EMDR facilitent l’extinction de la peur ainsi que la récupération de cette extinction au sein d’un groupe de volontaires sains (étude 4). Ainsi, ces travaux offrent de nouvelles perspectives en termes de modélisation de la pathologie, et offre de nouvelles pistes de réflexion quant à la prise en charge thérapeutique de ce trouble. / Posttraumatic Stress Disorder (PTSD) is a debilitating psychiatric disorder that arises in the aftermath of a traumatic event. To date, the Eye Movement Desensitization and Reprocessing therapy (EMDR) therapy has shown to be the most efficient therapy for the treatment of PTSD. The aim of this thesis was therefore to understand neural mechanisms underlying PTSD and its recovery. To do so, we conducted four studies. In a first study, we showed alterations in the reward circuit activity in PTSD patients, which may underlie an imbalance mobilization of cognitive and hedonic motivational processes, possibly contributing to emotional numbing in PTSD (study 1). Following this, an altered resting state functional connectivity between a network associated with attentional processes and another associated with emotional and memory processes was also found, suggesting an atypical emotional regulation and attention processing (study 2). A third study showed changes of grey matter density in regions involved in emotional regulation after symptoms remission by EMDR therapy. Finally, we were also able to replicate, in PTSD patients, the fear extinction and fear extinction recall facilitation by bilateral alternating stimulations (BAS) a major component of EMDR therapy, previously demonstrated in animal studies. Taken together, the present findings of these studies contribute to enlarge our knowledge, opening new ways of thinking the actual model of explaining the PTSD. More importantly, we believe that our findings may contribute to improve therapeutic strategies to significantly ameliorate the life of these patients.

The temporal specificity of functional magnetic resonance imaging (fMRI) is limited by a sluggish and locally variable hemodynamic response trailing the neural activity by seconds. Here, we demonstrate for an attention capture paradigm that it is, never the less, possible to extract information about the relative timing of regional brain activity during cognitive processes on the scale of 100 ms by comparing alternative signal models representing early versus late activation. We demonstrate that model selection is not driven by confounding regional differences in hemodynamic delay. We show, including replication, that the activity in the dorsal anterior insula is an early signal predictive of behavioral performance, while amygdala and ventral anterior insula signals are not. This specific finding provides new insights into how the brain assigns salience to stimuli and emphasizes the role of the dorsal anterior insula in this context. The general analytic approach, named “Cognitive Timing through Model Comparison” (CTMC), offers an exciting and novel method to identify functional brain subunits and their causal interactions.

Chronic neuropathic pain affects up to 8% of the United Kingdom population and is a difficult condition to manage. It is established and maintained through many mechanisms, including central sensitisation (CS) in the spinal cord and brainstem. Neuropathic pain manifests as spontaneous pain, sensory loss and evoked hypersensitivity. The development of novel treatments for neuropathic pain is challenging, in part due to inadequate experimental models of clinically relevant pain. The use of functional magnetic resonance imaging (fMRI) techniques for imaging acute and increasingly tonic states enables the assessment of the neural correlates of evoked hypersensitivity and persistent pain, with the goal of developing appropriate biomarkers to test new therapies. This thesis develops novel techniques for the assessment of ongoing pain states and their modulation by therapies. We first identified a suitable human experimental model of CS using topical capsaicin, and an fMRI pipeline for the investigation of supraspinal involvement in pain hypersensitivity. In a placebo-controlled study, we then demonstrated the improved sensitivity of fMRI above subjective reports in detecting the efficacy of a known analgesic as compared to an ineffective active compound in a small cohort. To translate this to the more clinically relevant symptom of spontaneous pain, we developed and validated the use of a multi-inversion time pseudo-continuous arterial spin labelling (ASL) imaging and analysis pipeline for the neural assessment of tonic states and the absolute quantification of cerebral blood flow (CBF). Current evidence from structural and functional studies suggests a direct role for the posterior insula cortex in the encoding of nociception and pain. Using the ASL pipeline, we found that only a CBF change in the posterior insula region was correlated with the changing perception of persistent capsaicin-induced pain, and in a separate experiment showed that suppression of CBF in this region by gabapentin was related to the drug's suppression of subjective pain perception. We also demonstrated in a cohort of phantom limb patients that pain relief resulting from transcranial direct current stimulation of the deprived sensorimotor cortex is neurally represented by a decrease in posterior insula CBF. In a separate study, we showed that baseline CBF in the periaqueductal grey can predict individuals who are most vulnerable to pain and hypersensitivity following the induction of capsaicin-related CS. Taken together, these findings suggest that fMRI can be used as a tool to assess the efficacy of established and novel analgesics, with the midbrain reticular formation and posterior insula cortex being prime candidates as biomarkers of CS mechanisms and persistent pain respectively. Relatedly, ASL-fMRI may also be an effective technique for evaluating individuals' susceptibility to pain following inflammation or injury.