Amplitudes of resting-state functional networks – investigation into their correlates and biophysical properties

Resting-state fMRI studies have shown that multiple functional networks, which consist of distributed brain regions that share synchronised spontaneous activity, co-exist in the brain. As these resting-state networks (RSNs) have been thought to reflect the brain's intrinsic functional organization, intersubject variability in the networks' spontaneous fluctuations may be associated with individuals' clinical, physiological, cognitive, and genetic traits. Here, we investigated resting-state fMRI data along with extensive clinical, lifestyle, and genetic data collected from 37,842 UK Biobank participants, with the object of elucidating intersubject variability in the fluctuation amplitudes of RSNs. Functional properties of the RSN amplitudes were first examined by analyzing correlations with the well-established between-network functional connectivity. It was found that a network amplitude is highly correlated with the mean strength of the functional connectivity that the network has with the other networks. Intersubject clustering analysis showed the amplitudes are most strongly correlated with age, cardiovascular factors, body composition, blood cell counts, lung function, and sex, with some differences in the correlation strengths between sensory and cognitive RSNs. Genome-wide association studies (GWASs) of RSN amplitudes identified several significant genetic variants reported in previous GWASs for their implications in sleep duration. We provide insight into key factors determining RSN amplitudes and demonstrate that intersubject variability of the amplitudes primarily originates from differences in temporal synchrony between functionally linked brain regions, rather than differences in the magnitude of raw voxelwise BOLD signal changes. This finding additionally revealed intriguing differences between sensory and cognitive RSNs with respect to sex effects on temporal synchrony and provided evidence suggesting that synchronous coactivations of functionally linked brain regions, and magnitudes of BOLD signal changes, may be related to different genetic mechanisms. These results underscore that intersubject variability of the amplitudes in health and disease need to be interpreted largely as a measure of the sum of within-network temporal synchrony and amplitudes of BOLD signals, with a dominant contribution from the former

SARS-CoV-2 is associated with changes in brain structure in UK Biobank

There is strong evidence of brain-related abnormalities in COVID-191,2,3,4,5,6,7,8,9,10,11,12,13. However, it remains unknown whether the impact of SARS-CoV-2 infection can be detected in milder cases, and whether this can reveal possible mechanisms contributing to brain pathology. Here we investigated brain changes in 785 participants of UK Biobank (aged 51–81 years) who were imaged twice using magnetic resonance imaging, including 401 cases who tested positive for infection with SARS-CoV-2 between their two scans—with 141 days on average separating their diagnosis and the second scan—as well as 384 controls. The availability of pre-infection imaging data reduces the likelihood of pre-existing risk factors being misinterpreted as disease effects. We identified significant longitudinal effects when comparing the two groups, including (1) a greater reduction in grey matter thickness and tissue contrast in the orbitofrontal cortex and parahippocampal gyrus; (2) greater changes in markers of tissue damage in regions that are functionally connected to the primary olfactory cortex; and (3) a greater reduction in global brain size in the SARS-CoV-2 cases. The participants who were infected with SARS-CoV-2 also showed on average a greater cognitive decline between the two time points. Importantly, these imaging and cognitive longitudinal effects were still observed after excluding the 15 patients who had been hospitalised. These mainly limbic brain imaging results may be the in vivo hallmarks of a degenerative spread of the disease through olfactory pathways, of neuroinflammatory events, or of the loss of sensory input due to anosmia. Whether this deleterious effect can be partially reversed, or whether these effects will persist in the long term, remains to be investigated with additional follow-up

Behavioral and fMRI-based Characterization of Cognitive Processes Supporting Learning and Retrieval of Memory for Words in Young Adults

A novel word is rarely defined explicitly during the first encounter. With repeated exposure, a decontextualized meaning of the word is integrated into semantic memory. With the overarching goal of characterizing the functional neuroanatomy of semantic processing in young adults, we employed a contextual word learning paradigm, creating novel synonyms for common animal/artifact nouns that, along with additional real words, served as stimuli for the lexical-decision based functional MRI (fMRI) experiment. Young adults (n=28) were given two types of word learning training administered in multiple sessions spread out over three days. The first type of training provided perceptual form-only training to pseudoword (PW) stimuli using a PW-detection task. The second type of training assigned the meaning of common artifacts and animals to PWs using multiple sentences to allow contextual meaning acquisition, essentially creating novel synonyms. The underlying goals were twofold: 1) to test, using a behavioral semantic priming paradigm, the hypothesis that novel words acquired in adulthood get integrated into existing semantic networks (discussed in Chapter 2); and 2) to investigate the functional neuroanatomy of semantic processing in young adults, at the single word level, using the newly learned as well as previously known word stimuli as a conduit (discussed in Chapter 3). As outlined in Chapter 2, in addition to the semantic priming test mentioned above, two additional behavioral tests were administered to assess word learning success. The first was a semantic memory test using a two-alternative sentence completion task. Participants demonstrated robust accuracy (~87%) in choosing the appropriate meaning-trained item to complete a novel sentence. Second, an old/new item recognition test was administered using both meaning and form trained stimuli (old) as well as novel foil PWs (new). Participants demonstrated: a) high discriminability between trained and novel PW stimuli. (d-prime=2.72); and b)faster reaction times and higher accuracy for meaning-trained items relative to perceptually-trained items, consistent with prior level-of-processing research. The results from the recognition and semantic memory tests confirmed that subjects could explicitly recognize trained items as well as demonstrate knowledge of the newly acquired synonymous meanings. Finally, using a lexical decision task, a semantic priming test assessed semantic integration using the novel trained items as primes for word targets that had no prior episodic association to the primes. Relative to perceptually trained primes, meaning-trained primes significantly facilitated lexical decision latencies for synonymous word targets. Taken together, the behavioral findings outlined above demonstrate that a contextual approach is effective in facilitating word learning in young adults. Words learned over a few experimental sessions were successfully retained in declarative memory, as demonstrated by behavioral performance in the semantic memory and recognition memory experiments. In addition, relative to perceptually-trained PWs, the newly meaning-trained PWs, when used as primes in a semantic priming test, facilitated lexical decisions for synonymous real words, with which the primes had no prior episodic association. The latter finding confirms our primary behavioral hypothesis that novel words acquired in adulthood are represented similarly, i.e. integrated in the same semantic memory representational network, as common words likely acquired early in the lifetime. Chapter 3 outlines the findings from the fMRI experiment used to investigate the functional neuroanatomy of semantic processing using the newly learned as well as previously known words as stimuli in a lexical decision task. fMRI data were collected using a widely-spaced event-related design, allowing isolation of item-level hemodynamic responses. Two fMRI sessions were administered separated by 2-3 days, the 1st session conducted prior to, and the 2nd session following word-learning training. Using the same items as stimuli in the fMRI sessions conducted before and after behavioral training, facilitated a within-item analysis where each item effectively served as its own control. A set of stringent criteria, outlined below, were established a-priori describing characteristics expected from regions with a role in retrieving/processing meanings at the single word level. We expected a putative semantic processing region to exhibit: a) higher BOLD activity during the 1st fMRI session for real words relative to novel PWs; b) reduced BOLD activity for repeated real words presented in the 2nd fMRI session relative to levels seen in the 1st fMRI session; c) higher BOLD activity for meaning-trained PWs relative to novel PWs; d) higher BOLD activity for meaning-trained PWs relative to perceptually-trained PWs, e) higher BOLD activity for correctly identified meaning-trained PWs (hits) relative to their incorrect counterparts (misses). Given their previously documented associations with semantic processing, we expected to identify regions in left middle temporal gyrus (MTG) and left ventral inferior frontal gyrus (vIFG) to exhibit timecourses consistent with most of the semantic criteria outlined above. Individual ANOVA contrasts, essentially targeting each of the criteria outlined above, were conducted at the voxelwise level. A fixed effects analysis based on 4 correct trial ANOVA contrasts (corresponding to criteria a-d, above) generated 81 regions of interest; and two individual error vs. correct trial ANOVA contrasts generated an additional 16 regions, for a total of 97 study-driven regions. Using region-level ANOVAs and qualitative timecourse examinations, the regions were probed for the presence of the effects outlined in the above criteria. To ensure a comprehensive analysis, additional regions were garnered from prior studies that have used a variety of tasks to target semantic processing. The literature-derived regions were subjected to similar ANOVAs and qualitative timecourse analysis as was conducted on the study-driven regions to examine if the regions exhibited effects outlined in the above criteria. The above analysis resulted in three principal observations. First, we identified regions in the left parahippocamal gyrus (PHG) and left medial superior frontal cortex (mSFC) that, by satisfying essentially all the above criteria, demonstrated a role in semantic memory retrieval for recently acquired and previously known words. Second, despite strong expectations, regions in the left MTG and left vIFG failed to show activity in support of a role in semantic retrieval for the novel words. On the contrary, the profiles seen in the two said regions, namely a ‘word \u3e novel PW’ and a word repetition suppression effect, were consistent with a role in semantic retrieval exclusively for the previously known words. The latter observation suggests that the novel words have yet to undergo adequate consolidation to engage, in addition to PHG and mSFC, canonical semantic regions such as left MTG. Third, despite the potentially crucial distinctions noted in Chapter 3, left lateral/medial parietal regions implicated in episodic memory retrieval exhibited many similar properties as those outlined for PHG and mSFC above during retrieval of newly learned words. Crucially, instead of exhibiting repetition suppression for real words, as observed in PHG/mSFC, the parietal regions showed the opposite effect resembling the episodic ‘old\u3enew’ retrieval success effect. The latter observation argues against a sematic role and in support of an episodic role consistent with previous literature. Taken together, these observations suggest that in addition to the role played by PHG/mSFC supporting semantic memory retrieval for the novel words, the parietal regions are also making significant contributions for memory retrieval of the novel words via complementary episodic processes. Finally, using item-level timecourses derived from the 97 study-driven ROI, clustering algorithms were used to group regions with similar characteristics, with the goal of identifying a cluster corresponding to a putative semantic brain system. A number of clusters were identified containing regions with anatomical and functional correspondence to previously well-characterized systems. For instance, a cluster containing regions in left lateral parietal cortex, precuneus, and superior frontal cortex corresponding to a previously described episodic memory retrieval system (Nelson et al., 2010) was identified. Two additional clusters, corresponding to frontoparietal and cinguloopercular task control systems (Dosenbach et al., 2006, 2007) were also among the identified clusters. However, the clustering analysis did not identify a cluster of regions with semantic properties, such as PHG and mSFC noted above, that could potentially correspond with a semantic brain system. The above outlined findings from the current study, juxtaposed with prior findings from the literature, were interpreted in the following manner. The two regions identified in the current study, i.e. left parahippocampal gyrus and medial superior frontal gyrus, constitute regions that are used for learning new words, and are also recruited during semantic retrieval of previously well-established meanings. In addition, the current results also suggest complementary episodic contributions to the word learning process from regions in left parietal/superior frontal cortex. The latter observation may imply strong episodic contributions to the observed behavioral semantic priming effects. A potential counter argument, i.e. in support of a semantic basis for the priming effects, is the shared recruitment, in a manner consistent with semantics, of PHG/mSFC by both novel and real word stimuli. The left middle temporal gyrus, a region that the task-evoked and neuropsychological literature consistently associates with word-level semantic processing, was not recruited during memory retrieval of novel words, despite robust engagement by previously known word stimuli. Given their association with category-selective semantic deficits, as well as their role in conceptual/perceptual processing in healthy brains, the memory consolidation literature proposes regions in the lateral temporal lobes as potential neocortical loci for consolidated long-term memory. In the current setting, it is likely the case that the novel words have yet to be adequately consolidated to engage left MTG as did the previously known words. Finally, the left vIFG exhibited similar characteristics as the left middle temporal gyrus, in that it was not recruited by the newly meaning trained stimuli, despite showing engagement by previously known words. Given that the region failed to appear in our primary contrasts, even those targeting real word stimuli, and its absence in other prior studies that have used similar lexical decision tasks as the current study, we have a slightly different interpretation for that region. The left vIFG is typically recruited in task settings that require controlled/strategic meaning retrieval, a process that may not be critical for adequate performance of the lexical decision task as employed in the current study. Taken together, these findings suggest that a relatively small amount of word learning training is sufficient to create novel words that, in young adults, behaviorally resemble the semantic characteristics of well-known words. On the other hand, the fMRI findings, particularly the failure of the newly meaning-trained items to engage regions that are canonically responsive to single word meanings (e.g. middle temporal gyrus), may suggest a more protracted timecourse for the functional signature of novel words to resemble that of well-known words. That said, the fMRI findings identified brain regions (left PHG/mSFC) that, consistent with the memory consolidation literature, serve as the functional neuroanatomical “bridge” that connects the novel words to the eventual functional representational destination

Deep learning approaches to multimodal MRI brain age estimation

Brain ageing remains an intricate, multifaceted process, marked not just by chronological time but by a myriad of structural, functional, and microstructural changes that often lead to discrepancies between actual age and the age inferred from neuroimaging. Machine learning methods, and especially Convolutional Neural Networks (CNNs), have proven adept in capturing patterns relating to ageing induced changes in the brain. The differences between the predicted and chronological ages, referred to as brain age deltas, have emerged as useful biomarkers for exploring those factors which promote accelerated ageing or resilience, such as pathologies or lifestyle factors. However, previous studies relied overwhelmingly on structural neuroimaging for predictions, overlooking rich details inherent in other MRI modalities, such as potentially informative functional and microstructural changes. This research, utilising the extensive UK Biobank dataset, reveals that 57 different maps spanning structural, susceptibility-weighted, diffusion, and functional MRI modalities can not only predict an individual's chronological age, but also encode unique ageing-related details. Through the use of both 3D CNNs and the novel 3D Shifted Window (SWIN) Transformers, this work uncovered associations between brain age deltas and 191 different non-imaging derived phenotypes (nIDPs), offering a valuable insight into factors influencing brain ageing. Moreover, this work found that ensembling data from multiple maps results in higher prediction accuracies. After a thorough comparison of both linear and non-linear multi-modal ensembling methods, including deep fusion networks, it was found that linear methods, such as ElasticNet, generally outperform their more complex non-linear counterparts. In addition, while ensembling was found to strengthen age prediction accuracies, it was found to weaken nIDP associations in certain circumstances where ensembled maps might have opposing sensitivities to a particular nIDP, thus reinforcing the need for guided selections of the ensemble components. Finally, while both CNNs and SWINs show comparable brain age prediction precision, SWIN networks stand out for their robustness against data corruption, while also proving a degree of inherent explainability. Overall, the results presented herein demonstrate that other 3D maps and modalities, which have not been considered previously for the task of brain age prediction, encode different information about the ageing brain. This research lays the foundation for further explorations into how different factors, such as off-target drug effects, impact brain ageing. It also ushers in possibilities for enhanced clinical trial design, diagnostic approaches, and therapeutic monitoring grounded in refined brain age prediction models

EXplainable Artificial Intelligence: enabling AI in neurosciences and beyond

The adoption of AI models in medicine and neurosciences has the potential to play a significant role not only in bringing scientific advancements but also in clinical decision-making. However, concerns mounts due to the eventual biases AI could have which could result in far-reaching consequences particularly in a critical field like biomedicine. It is challenging to achieve usable intelligence because not only it is fundamental to learn from prior data, extract knowledge and guarantee generalization capabilities, but also to disentangle the underlying explanatory factors in order to deeply understand the variables leading to the final decisions. There hence has been a call for approaches to open the AI `black box' to increase trust and reliability on the decision-making capabilities of AI algorithms. Such approaches are commonly referred to as XAI and are starting to be applied in medical fields even if not yet fully exploited. With this thesis we aim at contributing to enabling the use of AI in medicine and neurosciences by taking two fundamental steps: (i) practically pervade AI models with XAI (ii) Strongly validate XAI models. The first step was achieved on one hand by focusing on XAI taxonomy and proposing some guidelines specific for the AI and XAI applications in the neuroscience domain. On the other hand, we faced concrete issues proposing XAI solutions to decode the brain modulations in neurodegeneration relying on the morphological, microstructural and functional changes occurring at different disease stages as well as their connections with the genotype substrate. The second step was as well achieved by firstly defining four attributes related to XAI validation, namely stability, consistency, understandability and plausibility. Each attribute refers to a different aspect of XAI ranging from the assessment of explanations stability across different XAI methods, or highly collinear inputs, to the alignment of the obtained explanations with the state-of-the-art literature. We then proposed different validation techniques aiming at practically fulfilling such requirements. With this thesis, we contributed to the advancement of the research into XAI aiming at increasing awareness and critical use of AI methods opening the way to real-life applications enabling the development of personalized medicine and treatment by taking a data-driven and objective approach to healthcare

Developing neuroimaging methods for clinical translation and better understanding neonatal brain development

Understanding and measuring pain and brain development in neonates is essential to be able to provide the best care for this vulnerable population. This is particularly important for premature infants, for whom early life is filled with more painful procedures, and earlier exposure to extrauterine stimuli, which can adversely affect development. Infant pain assessments combine behavioural and physiological measures such as facial expression, crying, and heart rate. However, these metrics are not specific to pain experience, nor sensitive enough to provide reliable outcome measures for clinical trials to validate pain treatments in infants. Neuroimaging techniques provide means to study brain health, development and function. EEG and fMRI measurements of noxious-evoked brain activity could be used to develop more objective and specific pain assessment tools. This thesis focusses on using EEG and MRI to measure infant pain and its relation to overall brain development. First, I present tests of the validity of an EEG template measure of noxious response in infants recruited at multiple hospital sites. EEG has been used to quantify noxious-evoked activity and study pain interventions in infants, but a standard generalisable approach needs to be established. I tested whether the EEG template discriminates between noxious and non-noxious stimuli, whether the scale of noxious response is equivalent across different hospital sites, and whether noxious response increases with age in premature infants. I found that noxious-evoked responses are significantly greater than non-noxious responses, but that the scale is not equivalent across study sites, and there was no significant age correlation. This suggests that the EEG template can be reliably used as a surrogate measure of pain, with promise for clinical trials. Additionally, data collection site should be accounted for as a confounding factor as needed. Then, I focus on how MRI can aid our understanding of infant pain and the underlying neurophysiology behind differences in noxious-evoked activity. I present a machine learning model that I developed to predict the magnitude of noxious-evoked responses from resting- state brain activity in infants, using fMRI data. By applying this model to data from the independent Developing Human Connectome Project, I explore how predicted noxious- evoked responses relate to development metrics, including resting-state cortical function and microstructure, as well as prematurity, and assessments of infant cognitive and motor ability at 2-year follow up. I found that prematurity is associated with accelerated development of the nociceptive system, but disrupted neurodevelopment overall. In summary, this thesis demonstrates the potential for neuroimaging techniques to improve our understanding of infant brain development, and improve clinical assessment and treatment of infant pain

A Gaze into politics. The role of ideology, personality and political group processing in shaping automatic social behaviors

Studies in human and non-human primates indicate that basic socio-cognitive operations are inherently linked to the power of gaze in capturing reflexively the attention of an observer. Here I report a series of behavioral and neural investigation studies that I and my collaborators have conducted on the modulation of this automatic social behavior by high order factors as politics. In particular, we showed that Gaze following behavior is permeable to social identities within the political domain, individual differences in ideology and personality and low level facial features that drive our inferences on the personality of a character. Furthermore I discussed which are the social processes that underly this basic social cognitive behavior and sketched future directions to better clarify this issue

Principles of Integrated Cognitive Training for Executive Attention: Application to an Instrumental Skill

One effective cognitive treatment is the rehabilitation of working memory (WM) using an integrated approach that targets the “executive attention” system. Recent neuroscientific literature has revealed that treatment efficacy depends on the presence of various features, such as adaptivity, empathy, customization, avoidance of automatism and stereotypies, and alertness activation. Over the last two decades, an Integrated Cognitive Training (ICT) protocol has been proposed and developed; ICT takes the above-mentioned features and existing literature into account, and has been used to promote the development of reading skills. ICT has been employed in several clinical settings and involves stimulation of a specific deteriorated system (e.g., reading) and the improvement of executive attention components, thus also increasing working memory capacity. In this context, we present two experiments. In Experiment 1, participants diagnosed with dyslexia (aged between 8 and 14 years) underwent two ICT sessions a week, with home supplements, for a duration of 7 months. The participants showed a significant improvement in the reading speed of text, words, and non-words, and in the reading accuracy of text and non-words. In Experiment 2, we replicated Experiment 1, but included a comparison between two groups (experimental group vs. control group) of young participants with diagnosis of dyslexia. The experimental group was subjected to 18 ICT sessions twice a week and with home supplements, using the same protocol as in Experiment 1. The control group was entrusted to the protocol of compensatory tools and dispense/helping procedures provided by the scholastic Personalized Educational Plan. After training, the experimental group gained about 0.5 syllables per second in text reading, and a marked decrease in error rate. The control group showed no significant improvement in reading skills after the same period. Moreover, the improvement observed in the experimental group remained stable 4 months after ICT had ended. The results of these two experiments support the efficacy of the integrated ICT protocol in improving reading skills in children with dyslexia and its sustained effect