Three-dimensional (3D) ex vivo imaging of cleared intact brains of animal models and large human and non-human primate postmortem brain specimens is important for understanding the physiological neural network connectivity patterns and the pathological alterations underlying neuropsychiatric and neurological disorders. Light-sheet microscopy has emerged as a highly effective imaging modality for rapid high-resolution imaging of large cleared samples. However, the orthogonal arrangements of illumination and detection optics in light sheet microscopy limits the size of specimen that can be imaged. Recently developed light sheet theta microscopy (LSTM) technology addressed this by utilizing a unique arrangement of two illumination light paths oblique to the detection light path, while allowing perpendicular arrangement of the detection light path relative to the specimen surface. Here, we report development of a next-generation, fully integrated, and user-friendly LSTM system for rapid sub-cellular resolution imaging uniformly throughout a large specimen without constraining the lateral (XY) size. In addition, we provide a seamlessly integrated workflow for image acquisition, data storage, pre- and post-processing, enhancement, and quantitative analysis. We demonstrate the system performance by high-resolution 3D imaging of intact mouse brains and human brain samples, and complete data analysis including digital neuron tracing, vessel reconstruction and design-based stereological analysis in 3D. This technically enhanced and user-friendly LSTM implementation will enable rapid quantitative mapping of molecular and cellular features of interests in diverse types of very large samples.

BACKGROUND: Cocaine use (CU) is prevalent in people with HIV (PWH). Both conditions are linked to changes in cognitive functioning and neural network topology. The current study utilizes graph theory to investigate functional connectomics associated with HIV and CU, focusing on disruption of densely connected nodes called hubs.
METHODS: Resting state functional magnetic resonance imaging (fMRI) from 206 adults (ages 22-55 years) were analyzed. A HIV x CU factorial design was implemented with participants in four groups: HIV+CU (n= 41), HIV only (n= 88), CU only (n= 36), and controls (n= 41). Functional connectomes were constructed, and thresholded graph metrics were calculated. Network centrality metrics - betweenness centrality (BC), participation coefficient (PC), and within module degree (WD) - were quantified into hub disruption indices (HDI). For each index, a 2×2 ANCOVA was performed controlling for education.
RESULTS: Participants were 68 % male and 74 % African-American with a mean age of 44.4 years. HIV and CU were associated with hub disruption in all three indices. Interactions were significant for HDI-PC and HDI-WD, such that HIV disease was associated with greater hub disruption among participants without CU, but not among participants with CU. Overall, lower global cognitive functioning was associated with greater hub disruption on all three indices.
CONCLUSIONS: Widespread hub disruption was evident in HIV disease and CU, highlighting topological reorganization in both diseases with neurocognitive effects. Hub-related measures inform functional connectivity disruptions in HIV disease and CU, particularly with respect to changes in network topology throughout the connectome.

The neural pathways that start human color vision begin in the complex synaptic network of the foveal retina where signals originating in long (L), middle (M), and short (S) wavelength-sensitive cone photoreceptor types are compared through antagonistic interactions, referred to as opponency. In nonhuman primates, two cone opponent pathways are well established: an L vs. M cone circuit linked to the midget ganglion cell type, often called the red-green pathway, and an S vs. L + M cone circuit linked to the small bistratified ganglion cell type, often called the blue-yellow pathway. These pathways have been taken to correspond in human vision to cardinal directions in a trichromatic color space, providing the parallel inputs to higher-level color processing. Yet linking cone opponency in the nonhuman primate retina to color mechanisms in human vision has proven particularly difficult. Here, we apply connectomic reconstruction to the human foveal retina to trace parallel excitatory synaptic outputs from the S-ON (or \"blue-cone\") bipolar cell to the small bistratified cell and two additional ganglion cell types: a large bistratified ganglion cell and a subpopulation of ON-midget ganglion cells, whose synaptic connections suggest a significant and unique role in color vision. These two ganglion cell types are postsynaptic to both S-ON and L vs. M opponent midget bipolar cells and thus define excitatory pathways in the foveal retina that merge the cardinal red-green and blue-yellow circuits, with the potential for trichromatic cone opponency at the first stage of human vision.

The recent fusion of network science and neuroscience has catalyzed a paradigm shift in how we study the brain and led to the field of brain network analysis. Brain network analyses hold great potential in helping us understand normal and abnormal brain function by providing profound clinical insight into links between system-level properties and health and behavioral outcomes. Nonetheless, methods for statistically analyzing networks at the group and individual levels have lagged behind. We have attempted to address this need by developing three complementary statistical frameworks-a mixed modeling framework, a distance regression framework, and a hidden semi-Markov modeling framework. These tools serve as synergistic fusions of statistical approaches with network science methods, providing needed analytic foundations for whole-brain network data. Here we delineate these approaches, briefly survey related tools, and discuss potential future avenues of research. We hope this review catalyzes further statistical interest and methodological development in the field.

The brain atlas, which provides information about the distribution of genes, proteins, neurons, or anatomical regions, plays a crucial role in contemporary neuroscience research. To analyze the spatial distribution of those substances based on images from different brain samples, we often need to warp and register individual brain images to a standard brain template. However, the process of warping and registration may lead to spatial errors, thereby severely reducing the accuracy of the analysis. To address this issue, we develop an automated method for segmenting neuropils in the Drosophila brain for fluorescence images from the FlyCircuit database. This technique allows future brain atlas studies to be conducted accurately at the individual level without warping and aligning to a standard brain template. Our method, LYNSU (Locating by YOLO and Segmenting by U-Net), consists of two stages. In the first stage, we use the YOLOv7 model to quickly locate neuropils and rapidly extract small-scale 3D images as input for the second stage model. This stage achieves a 99.4% accuracy rate in neuropil localization. In the second stage, we employ the 3D U-Net model to segment neuropils. LYNSU can achieve high accuracy in segmentation using a small training set consisting of images from merely 16 brains. We demonstrate LYNSU on six distinct neuropils or structures, achieving a high segmentation accuracy comparable to professional manual annotations with a 3D Intersection-over-Union (IoU) reaching up to 0.869. Our method takes only about 7 s to segment a neuropil while achieving a similar level of performance as the human annotators. To demonstrate a use case of LYNSU, we applied it to all female Drosophila brains from the FlyCircuit database to investigate the asymmetry of the mushroom bodies (MBs), the learning center of fruit flies. We used LYNSU to segment bilateral MBs and compare the volumes between left and right for each individual. Notably, of 8,703 valid brain samples, 10.14% showed bilateral volume differences that exceeded 10%. The study demonstrated the potential of the proposed method in high-throughput anatomical analysis and connectomics construction of the Drosophila brain.

Declarative memory encompasses episodic and semantic divisions. Episodic memory captures singular events with specific spatiotemporal relationships, while semantic memory houses context-independent knowledge. Behavioural and functional neuroimaging studies have revealed common and distinct neural substrates of both memory systems, implicating mesiotemporal lobe (MTL) regions such as the hippocampus and distributed neocortices. Here, we explored declarative memory system reorganization in patients with unilateral temporal lobe epilepsy (TLE) as a human disease model to test the impact of variable degrees of MTL pathology on memory function. Our cohort included 31 patients with TLE as well as 60 age and sex-matched healthy controls, and all participants underwent episodic and semantic retrieval tasks during a multimodal MRI session. The functional MRI tasks were closely matched in terms of stimuli and trial design. Capitalizing on non-linear connectome gradient mapping techniques, we derived task-based functional topographies during episodic and semantic memory states, both in the MTL and in neocortical networks. Comparing neocortical and hippocampal functional gradients between TLE patients and healthy controls, we observed a marked topographic reorganization of both neocortical and MTL systems during episodic memory states. Neocortical alterations were characterized by reduced functional differentiation in TLE across lateral temporal and midline parietal cortices in both hemispheres. In the MTL, on the other hand, patients presented with a more marked functional differentiation of posterior and anterior hippocampal segments ipsilateral to the seizure focus and pathological core, indicating perturbed intrahippocampal connectivity. Semantic memory reorganization was also found in bilateral lateral temporal and ipsilateral angular regions, while hippocampal functional topographies were unaffected. Leveraging MRI proxies of MTL pathology, we furthermore observed alterations in hippocampal microstructure and morphology that were associated with TLE-related functional reorganization during episodic memory. Moreover, correlation analysis and statistical mediation models revealed that these functional alterations contributed to behavioural deficits in episodic, but again not semantic memory in patients. Altogether, our findings suggest that semantic processes rely on distributed neocortical networks, while episodic processes are supported by a network involving both the hippocampus and neocortex. Alterations of such networks can provide a compact signature of state-dependent reorganization in conditions associated with MTL damage, such as TLE.

Alzheimer\'s disease (AD) presents complex challenges due to its multifactorial nature, poorly understood etiology, and late detection. The mechanisms through which genetic, fixed and modifiable risk factors influence susceptibility to AD are under intense investigation, yet the impact of unique risk factors on brain networks is difficult to disentangle, and their interactions remain unclear. To model multiple risk factors including APOE genotype, age, sex, diet, and immunity we leveraged mice expressing the human APOE and NOS2 genes, conferring a reduced immune response compared to mouse Nos2. Employing graph analyses of brain connectomes derived from accelerated diffusion-weighted MRI, we assessed the global and local impact of risk factors in the absence of AD pathology. Aging and a high-fat diet impacted extensive networks comprising AD-vulnerable regions, including the temporal association cortex, amygdala, and the periaqueductal gray, involved in stress responses. Sex impacted networks including sexually dimorphic regions (thalamus, insula, hypothalamus) and key memory-processing areas (fimbria, septum). APOE genotypes modulated connectivity in memory, sensory, and motor regions, while diet and immunity both impacted the insula and hypothalamus. Notably, these risk factors converged on a circuit comprising 63 of 54,946 total connections (0.11% of the connectome), highlighting shared vulnerability amongst multiple AD risk factors in regions essential for sensory integration, emotional regulation, decision making, motor coordination, memory, homeostasis, and interoception. These network-based biomarkers hold translational value for distinguishing high-risk versus low-risk participants at preclinical AD stages, suggest circuits as potential therapeutic targets, and advance our understanding of network fingerprints associated with AD risk.
UNASSIGNED: Current interventions for Alzheimer\'s disease (AD) do not provide a cure, and are delivered years after neuropathological onset. Addressing the impact of risk factors on brain networks holds promises for early detection, prevention, and revealing putative therapeutic targets at preclinical stages. We utilized six mouse models to investigate the impact of factors, including APOE genotype, age, sex, immunity, and diet, on brain networks. Large structural connectomes were derived from high resolution compressed sensing diffusion MRI. A highly parallelized graph classification identified subnetworks associated with unique risk factors, revealing their network fingerprints, and a common network composed of 63 connections with shared vulnerability to all risk factors. APOE genotype specific immune signatures support the design of interventions tailored to risk profiles.

OBJECTIVE: Anterior temporal lobe resection (ATLR) effectively controls seizures in medically refractory temporal lobe epilepsy but risks significant episodic memory decline. Beyond 1 year postoperatively, the influence of preoperative clinical factors on episodic memory and long-term network plasticity remain underexplored. Ten years post-ATLR, we aimed to determine biomarkers of successful memory network reorganization and establish presurgical features\' lasting impact on memory function.
METHODS: Twenty-five ATLR patients (12 left-sided) and 10 healthy controls underwent a memory-encoding functional magnetic resonance imaging paradigm alongside neuropsychometry 10 years postsurgery. Generalized psychophysiological interaction analyses modeled network functional connectivity of words/faces remembered, seeding from the medial temporal lobes (MTLs). Differences in successful memory connectivity were assessed between controls and left/right ATLR. Multivariate regressions and mixed-effect models probed preoperative phenotypes\' effects on long-term memory outcomes.
RESULTS: Ten years post-ATLR, lower baseline functioning (verbal and performance intelligence quotient) and a focal memory impairment preoperatively predicted worse long-term memory outcomes. Poorer verbal memory was significantly associated with longer epilepsy duration and earlier onset age. Relative to controls, successful word and face encoding involved increased functional connectivity from both or remnant MTL seeds and contralesional parahippocampus/hippocampus after left/right ATLR. Irrespective of surgical laterality, successful memory encoding correlated with increased MTL-seeded connectivity to frontal (bilateral insula, right anterior cingulate), right parahippocampal, and bilateral fusiform gyri. Ten years postsurgery, better memory performance was correlated with contralateral frontal plasticity, which was disrupted with longer epilepsy duration.
CONCLUSIONS: Our findings underscore the enduring nature of functional network reorganizations to provide long-term cognitive support. Ten years post-ATLR, successful memory formation featured stronger connections near resected areas and contralateral regions. Preoperative network disruption possibly influenced effectiveness of postoperative plasticity. These findings are crucial for enhancing long-term memory prediction and strategies for lasting memory rehabilitation.

UNASSIGNED: To determine the safety and proof of concept of a parcel-guided, repetitive Transcranial Magnetic Stimulation (rTMS) in patients who develop a heterogeneous array of symptoms, known collectively as post-concussive syndrome (PCS), following traumatic brain injury (TBI).
UNASSIGNED: We performed a retrospective review of off-label, individualized, parcel-guided rTMS in 19 patients from December 2020 to May 2023. Patients had at least one instance of mild, moderate, or severe TBI and developed symptoms not present prior to injury. rTMS targets were identified based on machine learning connectomic software using functional connectivity anomaly matrices compared to healthy controls. EuroQol (EQ-5D), as a measurement of quality of life, and additional questionnaires dependent on individual\'s symptoms were submitted prior to, after, and during follow-up from rTMS.
UNASSIGNED: Nineteen patients showed improvement in EQ-5D and Rivermead Post Concussion Symptoms Questionnaires - 3 after treatment and follow-up. For nine patients who developed depression, five (55%) attained response and remission based on the Beck Depression Inventory after treatment. Eight of ten patients with anxiety had a clinically significant reduction in Generalized Anxiety Disorder-7 scores during follow-up.
UNASSIGNED: Parcel-guided rTMS is safe and may be effective in reducing PCS symptoms following TBI and should incite further controlled studies.

Basolateral amygdala (BLA) is a key hub for affect in the brain,1,2,3 and dysfunction within this area contributes to a host of psychiatric disorders.4,5 BLA is extensively and reciprocally interconnected with frontal cortex,6,7,8,9 and some aspects of its function are evolutionarily conserved across rodents, anthropoid primates, and humans.10 Neuron density in BLA is substantially lower in primates compared to murine rodents,11 and frontal cortex (FC) is dramatically expanded in primates, particularly the more anterior granular and dysgranular areas.12,13,14 Yet, how these anatomical differences influence the projection patterns of single BLA neurons to frontal cortex across rodents and primates is unknown. Using a barcoded connectomic approach, we assessed the single BLA neuron connections to frontal cortex in mice and macaques. We found that BLA neurons are more likely to project to multiple distinct parts of FC in mice than in macaques. Further, while single BLA neuron projections to nucleus accumbens were similarly organized in mice and macaques, BLA-FC connections differed substantially. Notably, BLA connections to subcallosal anterior cingulate cortex (scACC) in macaques were least likely to branch to other medial frontal cortex areas compared to perigenual ACC (pgACC). This pattern of connections was reversed in the mouse homologues of these areas, infralimbic and prelimbic cortex (IL and PL), mirroring functional differences between rodents and non-human primates. Taken together, these results indicate that BLA connections to FC are not linearly scaled from mice to macaques and instead the organization of single-neuron BLA connections is distinct between these species.