Domain Adaptive Synapse Detection with Weak Point Annotations

The development of learning-based methods has greatly improved the detection of synapses from electron microscopy (EM) images. However, training a model for each dataset is time-consuming and requires extensive annotations. Additionally, it is difficult to apply a learned model to data from different brain regions due to variations in data distributions. In this paper, we present AdaSyn, a two-stage segmentation-based framework for domain adaptive synapse detection with weak point annotations. In the first stage, we address the detection problem by utilizing a segmentation-based pipeline to obtain synaptic instance masks. In the second stage, we improve model generalizability on target data by regenerating square masks to get high-quality pseudo labels. Benefiting from our high-accuracy detection results, we introduce the distance nearest principle to match paired pre-synapses and post-synapses. In the WASPSYN challenge at ISBI 2023, our method ranks the 1st place

Representational dynamics across multiple timescales in human cortical networks

Human cognition occurs at multiple timescales, including immediate processing of the ongoing experiences and slowly drifting higher-level thoughts. To understand how the brain selects and represents these various types of information to guide behavior, this thesis examined representational content within sensory regions, multiple demand (MD) network, and default mode network (DMN). Chapter 1 provides a background review of the current literature. It begins by reviewing experimental investigations of component visual processes that unfold over time. Next, the MD network is introduced as a collection of frontal and parietal regions involved in implementing cognitive control by assembling the required operations for task-relevant behavior. Finally, the DMN is introduced in the context of temporal processing hierarchies, with focus on its representation of situation models summarizing interactions among entities and the environment. The first experiment, presented in Chapter 2, used EEG/MEG to track multiple component processes of selective attention. Five distinct processing operations with different time-courses were quantified, including representation of visual display properties, target location, target identity, behavioral significance, and finally, possible reactivation of the attentional template. Chapter 3 used fMRI to examine neural representations of task episodes, which are temporally organized sequences of steps that occur within a given context. It was found that MD and visual regions showed sensitivity to the fine structure of the contents within a task. DMN regions showed gradual change throughout the entire task, with increased activation at the offset of the entire episode. Chapter 4 analyzed activation profiles of DMN regions using six diverse tasks to examine their functional convergence during social, episodic, and self-referential thought. Results supported proposals of separate subsystems, yet also suggest integration within the DMN. The final chapter, Chapter 5, provides an extended discussion of theoretical concepts related to the three experiments and proposes possible avenues for further research

Functional Brain Organization in Space and Time

The brain is a network functionally organized at many spatial and temporal scales. To understand how the brain processes information, controls behavior and dynamically adapts to an ever-changing environment, it is critical to have a comprehensive description of the constituent elements of this network and how relationships between these elements may change over time. Decades of lesion studies, anatomical tract-tracing, and electrophysiological recording have given insight into this functional organization. Recently, however, resting state functional magnetic resonance imaging (fMRI) has emerged as a powerful tool for whole-brain non-invasive measurement of spontaneous neural activity in humans, giving ready access to macroscopic scales of functional organization previously much more difficult to obtain. This thesis aims to harness the unique combination of spatial and temporal resolution provided by functional MRI to explore the spatial and temporal properties of the functional organization of the brain. First, we establish an approach for defining cortical areas using transitions in correlated patterns of spontaneous BOLD activity (Chapter 2). We then propose and apply measures of internal and external validity to evaluate the credibility of the areal parcellation generated by this technique (Chapter 3). In chapter 4, we extend the study of functional brain organization to a highly sampled individual. We describe the idiosyncratic areal and systems-level organization of the individual relative to a standard group-average description. Further, we develop a model describing the reliability of BOLD correlation estimates across days that accounts for relevant sources of variability. Finally, in Chapter 5, we examine whether BOLD correlations meaningfully vary over the course of single resting-state scans

Trans-Diagnostic Relations Between Functional Brain Network Integrity and Cognition

Cognitive impairment occurs across the psychosis spectrum. However it is unknown whether these shared manifestations of cognitive dysfunction also reflect shared neurobiological mechanisms, or whether the source of impairment differs. One common feature of cognitive impairment across psychotic disorders is that the impairments are often ҧeneralizedӬ indicating deficits in a range of cognitive domains, including executive functioning, processing speed, memory, and attention. The goal of the current study was to determine whether the similar generalized cognitive deficit observed across psychotic disorders is also associated with a shared putative mechanism of functional brain network integrity. To address this question, we estimated resting-state functional network integrity of the cingulo-opercular and fronto-parietal networks -- two networks widely implicated in cognitive ability -- in 201 healthy controls, 143 schizophrenia, 103 schizoaffective, and 129 bipolar disorder with psychosis participants from the Bipolar and Schizophrenia Network on Intermediate Phenotypes (BSNIP1) consortium. Cognitive ability was measured using the Brief Assessment of Cognition in Schizophrenia (BACS), and generalized cognitive ability was estimated as the first factor (54% variance explained) in a principal axis factor analysis of all BACS subtests. Graph theory algorithms were used to estimate the global and local efficiency of the whole brain, cingulo-opercular network (CON), fronto-parietal network (FPN), and the auditory network (AUD), as well as participation coefficient of the anterior insula, dorsal anterior cingulate cortex, and dorsolateral prefrontal cortex. We observed significantly reduced CON global efficiency in schizophrenia and psychotic bipolar patients compared to healthy controls (pճ\u3c.01), but none of the clinical groups differed from one another (pճ\u3e.21). All psychotic disorders had significantly reduced CON local efficiency (pճ\u3c.03), but the clinical groups did not differ from one another. CON global efficiency was significantly associated with general cognitive ability across all groups (_=.099, p=.009), and significantly mediated the relationship between psychotic disorder status and general cognition (p\u3c.05). Exploratory analyses revealed that global efficiency of the subcortical network was also significantly reduced in psychotic disorders (p=.007), and positively predicted cognitive ability (_=.094, p=.009). These findings provide evidence of a role for reduced CON and subcortical network efficiency in the generalized cognitive deficit observed across the psychosis spectrum. They also support the hypothesis that a shared neurobiological mechanism underlies the dimension of cognitive impairment in psychotic disorders

Functional Connectivity of EEG LORETA in Cortical Core Components of the Self and the Default Network (DNt) of the Brain

INTRODUCTION: Recent research exploring cortical functional connectivity defines a default network (DNt) of brain function and activation of a core midline network (CMS) in the processing of self. The electroencephalographic (EEG) activity in these components of the human DNt and CMS is not well understood. METHODS: This study was conducted with 63 participants. Individuals were recorded during eyes-closed (ECB) and eyes-opened (EOB) baselines and active task (AT) conditions (e.g., self-referential, self-image, self-concept, recent symptomology, other face and object processing). We estimated EEG source localization with standardized low resolution electromagnetic tomography (sLORETA). Subjective experience was obtained for baselines and photographic conditions. RESULTS: The ECB resting condition shows higher activity in all frequencies as compared to all other conditions. Likewise, the active tasks show differential effects for increased activity as compared to EOB for each region of interest (ROI) in each frequency domain. CONCLUSION: The data are in agreement with other neuroimaging techniques (fMRI/PET) investigating the DNt of brain function and further shows that the 3-dimensional localization accuracy of LORETA EEG is sufficient for the study of the DNt. In examining both within and between functional core regions there was a higher degree of activity in lower frequency bands during eyes closed; however, this pattern does not extend to all ROIs for all frequency domains. The differences may represent functional connectivity relating to endogenous/exogenous attention states as opposed to the simple concept of “resting” or “non-activity”. Further study of the functional relationships between EEG frequencies within and between regions in the default network and during self-specific processing may prove important to understanding the complex nature of neocortical functional integration

A multimodal approach to the study of self and others’ awareness in prodromal to mild Alzheimer’s disease

Patients in the early stage of Alzheimer’s disease (AD) can manifest disorders of cognitive awareness such as a lack of/limited self-awareness of their own cognitive deficits (anosognosia) or as a reduction in the ability to be aware of others, i.e., social cognition; more specifically in the ability to recognise emotions or attribute mental states to others (also known as Theory of Mind, ToM). The present thesis intended to explain the behavioural, brain neuroanatomical, structural connectivity and resting-state functional relationship between the presence of multi-domain alterations of self-awareness/anosognosia and others awareness/social cognition to understand the cognitive and neural substrates that shape conscious awareness in early AD. Behavioural findings evidenced an association between the presence of anosognosia and reduced ToM. Individually, memory anosognosia was associated with memory proxies and total anosognosia with visuospatial abilities, while social cognition was associated with language, memory, attention and most importantly, executive functions. Neuroanatomical structural findings of non-memory and total anosognosia showed reduced grey matter volume in the anterior cingulate cortex (ACC), fusiform, lingual and precentral gyri. Conversely, ToM showed reduced grey matter volume also in the ACC, but reduction extended to encompass temporoparietal junction, orbitofrontal, superior temporal and cerebellar cortices. The ACC showed a statistical shared neural overlap between self-other awareness. At the functional level, both anosognosia and social cognition were associated with reduced internetwork connectivity between the default mode network (DMN) and the executive frontoparietal network (FPN), as well as higher connectivity between the DMN and the salience network, in which the insula seems to have an essential role. Subcortical contributions to large-scale network connectivity were also found. We propose that medial frontal executive mechanisms, such as those subserved by the ACC, might support awareness in the presence of an inherently damaged DMN in early-AD. Functional adaptive reorganisation of network dynamics might increase the strain to salient system hubs (ACC) by redirecting network traffic of executive resources to cope with the progressive decline of conscious awareness