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Theory of Mind (ToM) is the ability to infer mental states of others and this skill relies on a distributed network of brain regions. A brain region that has been traditionally disregarded in relation to non-motor functions is the cerebellum. Here, we leveraged large-scale multimodal neuroimaging data to elucidate the structural and functional role of the cerebellum in ToM. We used functional activations to determine whether the cerebellum has a domain-general or domain-specific functional role. We found that the cerebellum is organized in a domain-specific way. We used effective connectivity and probabilistic tractography to map the cerebello-cerebral ToM network. We found a left cerebellar effective and structural lateralization, with more and stronger effective connections from the left cerebellar hemisphere to the contralateral cerebral ToM areas and greater cerebello-thalamo-cortical (CTC) and cortico-ponto-cerebellar (CPC) streamline counts from and to the left cerebellum. Lastly, we examined the relationship between CTC and CPC white matter and ToM speed and accuracy but found no correlation. Our study provides novel insights to the network organization of the cerebellum, an overlooked brain structure, and ToM, one of humans’ most essential abilities to navigate the social world. / Psychology

Non-suicidal self-injury (NSSI), defined as the deliberate damaging or destruction of body tissue without intent to die, are common behaviors amongst youth. Although prior work has shown heightened response to negative outcomes and dampened response to positive outcomes across multiple methods, including behavioral and physiological measures, little is known about the neural processes involved in NSSI. This study examined associations between NSSI engagement and responsivity to rewards and losses in youth with and without a lifetime engagement in NSSI. We employed a task-based functional magnetic resonance imaging (fMRI) study to examine differences between regions of interest (ROIs; ventral and dorsal striatum [VS, DS], anterior cingulate cortex [ACC], orbitofrontal cortex [OFC], ventrolateral and ventromedial prefrontal cortex [vlPFC; vmPFC], and insula) and whole-brain connectivity (utilizing bilateral DS, mPFC, and insula seed ROIs) in youth with and without NSSI. We used two reward tasks, in order to examine differences between groups across domains of reward (i.e., monetary and social). Additionally, we examined the specificity of the associations by controlling for dimensional levels of related psychopathology (i.e., aggression and depression). Results from the current study found that NSSI was associated with decreased activation following monetary gains in all ROIs. Further, these differences remained significant when controlling for comorbid psychopathology, including symptoms of aggression and depression. Finally, exploratory connectivity analyses found that NSSI was associated with differential connectivity between regions including the DS, vmPFC, insula, parietal operculum cortex, supramarginal gyrus, cerebellum, and central opercular cortex. Weakened connectivity between these regions could suggest deficits in inhibitory control of emotions in individuals with NSSI, as well as dysfunction in pain processing in individuals with NSSI, whereby these individuals experience pain as more salient or rewarding than individuals without NSSI. Although results did not support our hypotheses, findings suggest disrupted reward processes in youth with NSSI, contributing to our understanding of the role that reward processes may play in NSSI, in the engagement and reinforcement of these behaviors. We also conducted an extensive systematic review of the studies indexing neural structure and function in NSSI, summarizing the literature on the neurobiological correlates of several psychological processes implicated in NSSI engagement, including emotion processes, pain processes, executive processes, social processes, and reward processes. Results of the review highlighted the neural regions most consistently associated with NSSI, including the amygdala, insula, frontal, prefrontal, and orbitofrontal cortices, and the anterior cingulate, dorsal striatum, and ventral striatum. Additionally, data showed that NSSI is associated with greater emotional responses in negative situations, poorer down-regulation of negative emotions, and poorer inhibitory control over impulsive behaviors. Overall, findings suggest that NSSI is associated with maladaptive coping, and that this down-regulation of negative emotion resulting from NSSI may be experienced as rewarding and may serve to reinforce engagement in these behaviors. Finally, this review highlighted the importance of standardizing the methods of indexing neural structure and function in NSSI, specifically in terms of how NSSI is categorized, which comorbid disorders are examined, and how neuroimaging data are collected and analyzed, so that research in this area is comparable and reproducible. / Psychology

Movement of organisms is a fundamental component of many ecological processes, and should be subject to strong selective pressures. Spatial selection is the process by which individuals choose the locations to acquire necessary resources or avoid risk, and the relative importance of different factors on spatial selection may change depending on the scale being analyzed. Under the framework of optimality, an individual should attempt to structure their spatial selection economically to maximize fitness. I studied black bear (Ursus americanus) space use, habitat selection, and movement under the optimality paradigm in three populations (Michigan, Missouri, and Mississippi) at four different scales: regional, annual home range, seasonal home range, and denning sites. At the regional scale, I found that black bears displayed scale-dependent land cover selection for movement, selecting forested areas at coarser scales and avoiding anthropogenic disturbance at finer scales, and that large contiguous forests and riparian corridors most facilitate connectivity among protected areas. At the annual and seasonal home range scales, I found black bears display scale-dependent optimizing strategies. Individuals locating their annual ranges to maximize access to areas of high vegetation productivity, together with the high productivity of ranges of all sizes, suggests an energy maximizing strategy, while the negative relationship between range size and both fragmentation and forest proportion suggests area minimizing. More limiting factors act at larger scales, which suggests productivity is the strongest limiting factor and energy maximizing is the dominant strategy while plasticity allows for seasonal area minimizing. At the den site scale, I found that both female and male black bears appeared to minimize anthropogenic risk during denning; however female black bears have a flexible response to anthropogenic disturbance, attempting to minimize it when alone or with older offspring, yet having increased tolerance when infanticide is greater after cubs are born and following den emergence. By quantifying black bear space use and selection across multiple scales, diverse areas, over time, and among and within individuals, I revealed consistent scale-dependent responses to environmental and biological factors while highlighting the intrinsic plasticity of this flexible omnivore.

Improperly designed road-stream crossings can fragment stream networks by restricting or preventing aquatic organism passage. These crossings may also be more vulnerable to high flow events, putting critical human infrastructure at risk. Climate change, which will require access to suitable habitat for species persistence, and is also predicted to increase the frequency and magnitude of extreme floods, underscores the importance of maintaining stream connectivity and resilient infrastructure. Given the large number of road-stream crossings and the expense of replacement, it is increasingly important to prioritize removals and account for the multiple benefits of these management actions. I developed an aquatic barrier prioritization scheme that combines potential habitat gain, stream thermal resilience, aquatic organism passage, and culvert risk of failure. To assess relative thermal resilience, I deployed paired air-water thermographs in several New England watersheds and analyzed relative thermal sensitivity (relationship of water to air temperature) and exposure (duration, frequency, and magnitude of warm stream temperature episodes) among streams. These were combined into a single metric of thermal resilience corresponding with the distance of that stream’s sensitivity and exposure from the watershed median. To test the relationship between risk of failure, culvert dimensions, and stream connectivity, I developed a logistic regression to predict risk of failure using data from two watersheds that experienced extreme flooding from Hurricane Irene (2011). Finally, I applied the resultant prioritization scheme to 66 road-stream crossings in the Westfield River watershed (MA). Thermal habitat quality varied considerably within and among watersheds. Stream sensitivity was generally lower than the widely accepted 0.8 ̊C increase in stream temperature for every 1 ̊C increase in air temperature (Westfield median sensitivity = 0.44), with substantial differences among streams. Exposure also varied widely among streams, indicating that some headwater streams in New England are more thermally resilient than previously thought. Risk of infrastructure failure was predicted with a logistic regression using culvert constriction ratio and predicted aquatic organism passage as predictors (Likelihood ratio test, X2=59.1, df=3, p- value=9.2e-13), indicating that underdesigned culverts were more likely to be barriers to passage and more likely to fail in extreme flow events. To prioritize culverts, this study ultimately used a piecewise approach that identified culverts opening the longest reaches of thermally resilient habitat, and then ranked those culverts by infrastructure replacement need. In the Westfield River, the prioritization clearly identified crossing replacements most likely to yield multiple benefits. The scheme I developed can accommodate changes in the relative weights of the different criteria, which will reflect differences in management and conservation concerns in the confidence of inputs. In conclusion, increasing connectivity by removing barriers may be one of the most effective ways to mitigate the effects of climate change on aquatic systems, but it is important to remove the right barriers.

This dissertation proposes new statistical methods for modeling and inference for two specific types of time series: integer-valued data and multivariate nonstationary extreme data. We rely on the class of integer-valued autoregressive (INAR) processes for the former, proposing a novel, flexible and elegant way of modeling count phenomena. As for the latter, we are interested in the human brain and its multi-channel electroencephalogram (EEG) recordings, a natural source of extreme events. Thus, we develop new extreme value theory methods for analyzing such data, whether in modeling the conditional extremal dependence for brain connectivity or clustering extreme brain communities of EEG channels. Regarding integer-valued time series, INAR processes are generally defined by specifying the thinning operator and either the innovations or the marginal distributions. The major limitations of such processes include difficulties deriving the marginal properties and justifying the choice of the thinning operator. To overcome these drawbacks, this dissertation proposes a novel approach for building an INAR model that offers the flexibility to prespecify both marginal and innovation distributions. Thus, the thinning operator is no longer subjectively selected but is rather a direct consequence of the marginal and innovation distributions specified by the modeler. Novel INAR processes are introduced following this perspective; these processes include a model with geometric marginal and innovation distributions (Geo-INAR) and models with bounded innovations. We explore the Geo-INAR model, which is a natural alternative to the classical Poisson INAR model. The Geo-INAR process has interesting stochastic properties, such as MA($\infty$) representation, time reversibility, and closed forms for the $h$-th-order transition probabilities, which enables a natural framework to perform coherent forecasting. In the front of multivariate nonstationary extreme data, the focus lies on multi-channel epilepsy data. Epilepsy is a chronic neurological disorder affecting more than 50 million people globally. An epileptic seizure acts like a temporary shock to the neuronal system, disrupting normal electrical activity in the brain. Epilepsy is frequently diagnosed with EEGs. Current statistical approaches for analyzing EEGs use spectral and coherence analysis, which do not focus on extreme behavior in EEGs (such as bursts in amplitude), neglecting that neuronal oscillations exhibit non-Gaussian heavy-tailed probability distributions. To overcome this limitation, this dissertation proposes new approaches to characterize brain connectivity based on extremal features of EEG signals. Two extreme-valued methods to study alterations in the brain network are proposed. One method is Conex-Connect, a pioneering approach linking the extreme amplitudes of a reference EEG channel with the other channels in the brain network. The other method is Club Exco, which clusters multi-channel EEG data based on a spherical $k$-means procedure applied to the "pseudo-angles," derived from extreme amplitudes of EEG signals. Both methods provide new insights into how the brain network organizes itself during an extreme event, such as an epileptic seizure, in contrast to a baseline state.

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The growing demand for urban areas has been a driving force for extensive changes to landscape. Thisrequires more focus on finding a balance between promoting urban development, and conservingbiodiversity in urban areas. The Intergovernmental Science-Policy Platform on Biodiversity andEcosystem Services (“IPBES”) suggests encouraging sustainable urban planning, as well as“maintaining, and designing for, ecological connectivity in urban spaces”. Ecological connectivity canbe modelled based on circuit theory. Landscape can be depicted as a conductive surface and resistancecan be attributed to landscape types according to its permeability to the movement of a species.Frösön is a district in the growing municipality of Östersund, Sweden, where several developmentplans are intended. This study aimed to identify where structural ecological connectivity existed inFrösön. It also aimed to determine where connectivity was disturbed by urban development, andexplore the options available to strengthen connectivity through establishing new ecological corridors.Land cover data was analysed to identify the forest patches that were larger than 50 000m2, andresistance values were attributed per land cover type. Circuitscape was used to model the connectivitybetween the forest patches, revealing the connectivity across Frösön. The development plans wereassessed to determine where the developments overlapped existing corridors with high connectivityvalues between forest patches. New corridors (pathways connecting high connectivity valuesbetween forest patches) that could compensate for the impact by development plans on connectivityas well as strengthen connectivity throughout Frösön were proposed. The findings in this reportconcur with the IPBES that urban development can be sustainable while preserving biodiversity.Additionally, the inclusion of connectivity models in the environmental impact assessment (“EIA”)process for developments, enables proactive decision-making on the design and location ofdevelopments. Moreover, it encourages urban development and the preservation of landscapeconnectivity. This study will be valuable to environmentalists carrying out EIAs and specialists thatopine on environmental policy and/or legislation. / <p>2022-0604</p>

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