Sunday, October 6th, 2024

Time	Event
1:30a	Human gray matter microstructure mapped using Neurite Exchange Imaging (NEXI) on a clinical scanner Biophysical models of diffusion in gray matter (GM) can provide unique information about microstructure of the human brain, in health and disease. Therefore, their compatibility with clinical settings is key. Neurite Exchange Imaging (NEXI) is a two-compartment model of GM microstructure that accounts for inter-compartment exchange, whose parameter estimation requires multi-shell multi-diffusion time data. In this work, we report the first estimates of NEXI in human cortex obtained on a clinical MRI scanner. To do that, we establish an acquisition protocol and fitting routine compatible with clinical scanners. The model signal equation can be expressed either in the narrow-pulse approximation, NEXINPA, or accounting for the actual width of the diffusion gradient pulses, NEXIWP. While NEXINPA enables a faster analytical fit and is a valid approximation for data acquired on high-performance gradient systems (preclinical and Connectom scanners), on which NEXI was first implemented, NEXIWP has significant relevance for data acquired on clinical scanners with longer gradient pulses. We establish that, in the context of broad pulses, NEXIWP estimates were more comparable to previous literature values. Furthermore, we evaluate the repeatability of NEXI estimates in the human cortex on a clinical MRI scanner and show intra-subject variability to be lower than inter-subject variability, which is promising for characterizing healthy and patient cohorts. Finally, we analyze the relationship of NEXI parameters on the cortical surface to the Myelin Water Fraction (MWF), estimated using an established multicomponent T2 relaxation technique. Indeed, although it is present in small quantities in the cortex, myelin can be expected to decrease permeability. We confirm a strong correlation between the exchange time (tex) estimates and the MWF, although the spatial correspondence between the two is brain-region specific and other drivers of tex than myelin density are likely at play. (Comment on this)
1:30a	Human and Mouse Models for Kabuki Syndrome Reveal Increase in Inhibitory Synapse Development. Intellectual disability, affecting 2-3% of the general population, often coincides with neurodevelopmental disorders and is frequently caused by mutations that impair synaptic function. Kabuki syndrome, a rare multisystem disorder associated with developmental delay and intellectual disability, results from mutations in either KMT2D (type 1) or KDM6A (type 2), which encode a chromatin-modifying methyltransferase and demethylase, respectively. However, the mechanisms contributing to intellectual disability in Kabuki syndrome remain poorly understood. In this study, we investigated synapse development in neurons using both in vitro human models of Kabuki syndrome types 1 and 2, as well as an in vivo mouse model of Kabuki syndrome type 1. Our findings revealed that both mature human iPSC-derived neurons and mice harboring disease-causing mutations exhibited increased inhibitory synapse development. This synaptic imbalance led to impaired excitatory information transfer within neural networks, which may underlie the cognitive deficits observed in Kabuki syndrome. (Comment on this)
1:30a	Adult lifespan effects on functional specialization along the hippocampal long axis There has been increasing attention to differences in function along the hippocampal long axis, with posterior regions proposed to have properties that are well suited to representing fine-grained details and coarser representations in anterior regions. Whether long axis functional specialization persists into older age is not known, despite well documented memory changes in older age. In this study, we used a large database of fMRI data (n =323 humans of both sexes included) from across the adult lifespan (ages 18-88) to determine the degree of functional differentiation across the hippocampal posterior-anterior axis. Our first approach was to measure the similarity among signals within each hippocampal subregion. We found that intra-region signals within the most posterior hippocampal subregion became more similar in older age, but did not relate to episodic memory performance. As a second approach, we measured functional connectivity between hippocampal subregions and the rest of the brain. The functional connectivity profiles of the posterior and anterior hippocampal subregions became more distinct from one another with increasing age, and age-related reductions in connectivity were strongest for the intermediate portion of the hippocampus. In contrast, anterior hippocampal functional connectivity remained relatively stable across the adult lifespan, and stronger anterior hippocampus connectivity with the anterior cingulate was associated with better episodic memory in older adults, suggesting that the anterior hippocampus may help some older adults compensate for age-related changes to more posterior hippocampal regions to preserve episodic memory. (Comment on this)
9:47a	Layer 6 corticothalamic neurons induce high gamma oscillations through cortico-cortical and cortico-thalamo-cortical pathways Layer 6 corticothalamic (L6CT) neurons are an excitatory neuron class with projections to both cortex and thalamus. L6CT neurons have been reported to induce multiple effects, including the up- and down-modulation of cortical and thalamic firing rates, and the enhancement of high gamma oscillations in the local field potential (LFP) of the surrounding cortex. These recently reported oscillations offer a neuronal substrate to link recurrent thalamocortical interactions, a critical connection hinging on L6CT neurons, to high frequency oscillations, that have been implicated in several cognitive and pathological conditions. We hypothesize that the high gamma oscillations induced by L6CT neurons in the cortex depend on the dynamic engagement of intracortical and cortico-thalamo-cortical circuits. To test this hypothesis, we optogenetically activated L6CT neurons in NTSR1-cre mice selectively expressing channelrhodopsin-2 in L6CT neurons. Leveraging the vibrissal pathway of awake, head-fixed mice, we presented LED ramp-and-hold inputs of different intensities while recording neuronal activity in the primary somatosensory barrel cortex (S1), the ventral posteromedial nucleus (VPm), and the reticular nucleus (TRN) of thalamus using silicon probes. First, we confirmed that the activation of L6CT neurons induces high-frequency oscillation of S1 local field potential. These oscillations are modulated in frequency, but not in amplitude, across LED intensities and over time. To identify which neuronal classes contribute to these oscillations, we examined the evolution over time of the firing rate of cortical neurons across layers and electrophysiologic cell classes, VPm, and TRN. While the firing rate of most cortical and TRN neurons was steadily suppressed over time, the firing rate of VPm and Layer 4 fast spiking (L4 FS) neurons evolved from being suppressed to being facilitated within 500 ms. Using dimensionality reduction, we found that this pattern reflects two underlying components: one stable component that is represented across all units, and one evolving component that is mainly represented in VPm and in L4 FS neurons, suggestive of differential recruitment of the cortico-cortical vs cortico-thalamo-cortical pathways. Finally, we related the firing rate of each unit to the amplitude and frequency of S1 LFP, finding that the evolution of S1 LFP amplitude weakly correlates with all neurons, while its frequency selectively correlates with VPm firing rate. Taken together, our data suggests that L6CT neurons generate high gamma oscillations in S1 LFP through a combination of intracortical and cortico-thalamo-cortical pathways and can sculpt its oscillation frequency through the cortico-thalamo-cortical pathway. Our findings provide a neuronal substrate for linking recurrent interactions, mediated by L6CT neurons, to the modulations of high gamma oscillations observed in several brain states and pathological conditions. (Comment on this)
10:18a	A shared code for perceiving and imagining objects in human ventral temporal cortex Mental imagery is a remarkable phenomenon that allows us to remember previous experiences and imagine new ones. Animal studies have yielded rich insight into mechanisms for visual perception, but the neural mechanisms for visual imagery remain poorly understood. Here, we first determined that ~80% of visually responsive single neurons in human ventral temporal cortex (VTC) used a distributed axis code to represent objects. We then used that code to reconstruct objects and generate maximally effective synthetic stimuli. Finally, we recorded responses from the same neural population while subjects imagined specific objects and found that ~40% of axis-tuned VTC neurons recapitulated the visual code. Our findings reveal that visual imagery is supported by reactivation of the same neurons involved in perception, providing single neuron evidence for existence of a generative model in human VTC. (Comment on this)
10:18a	Transcriptomic Insights into Hypothalamic Aging During Menopause: A Comparative Analysis of Human and Mouse Models Menopause significantly impacts women's health, yet hypothalamic changes during this transition remain poorly understood. We analyzed gene expression in human hypothalamic samples across menopausal stages, revealing significant changes in inflammatory pathways, KNDy neuron signaling, and thermoregulatory genes. This analysis also identified novel central markers of menopause, including AKAP5 and CDKN1A (p21). To further investigate these changes, we developed a novel mouse model based on long-term (4 months) ovariectomy (OVX) that mimics the gonadotropin and temperature fluctuations of menopausal transition. Remarkably, the posterior hypothalamus of 4-month OVX mice closely mirrored the transcriptional changes observed in perimenopausal women. Both species exhibited increased inflammatory signaling and glial activation, alongside altered KNDy neuron activity. Our findings provide new insights into the central mechanisms of menopausal symptoms and offer a valuable preclinical model for testing interventions. (Comment on this)
5:31p	Neuromodulatory influences on propagation of brain waves along the unimodal-transmodal gradient Brain activity fluctuates over time, and understanding the factors that influence such fluctuations is important to understand the flexible nature of the brain and cognition. Growing evidence suggests that fMRI brain activity shows spatio-temporal patterns of propagation following specific gradients. In particular, activity around global peaks propagates as a travelling wave following a gradient from unimodal to associative areas. Some properties of these travelling waves seem to be related to behavioral and arousal states, however their meaning remains unknown. Here we assess the possibility that travelling waves explain the finding that there are specific time points when the brain presents larger brain integration. We reasoned that a faster speed of propagation would be related to more brain integration as measured with fMRI. Furthermore, we explored whether increased pupil-linked arousal, which has been related to more integration in specific brain regions, would be increased during periods of whole brain propagation. To test these hypotheses, we detected brain travelling waves and characterized them in terms of speed, directionality and ratio. We compared these features between different task conditions, and after a pharmacological challenge affecting neuromodulatory tone. We then studied the relation between travelling wave speed, pupil size and a graph-based measure of brain integration. Our results suggest that neuromodulatory tone affects travelling wave propagation, and that this propagation reflects changes in arousal and integrated functional connectivity features. This study provides a novel view of brain dynamics in terms of the effects of neruomodulatory influences across time scales. (Comment on this)
5:31p	Parent-offspring brain similarity: Specificities and commonalities across gender combinations - the Transmit Radiant Individuality to Offspring (TRIO) study Research suggests that parent-offspring brain similarities may underlie intergenerational transmission of psychopathology. However, most studies have focused on mothers and offspring, with few including fathers. This study aimed to extend understanding of parent-offspring neural similarities by examining parent-offspring trios. The study included 152 Japanese biological parent-offspring trios who participated in the Transmit Radiant Individuality to Offspring (TRIO) study. We analyzed the parent-offspring similarities in brain structural features (cortical thickness, surface area, local gyrification index, and subcortical volume) across different parent-offspring gender combinations (father-son, father-daughter, mother-son, and mother-daughter). Additionally, we investigated the relationship between brain similarities and similarities in intelligence and personality traits in parents and offspring. Our findings confirmed that correlations in brain structural features between father-offspring or mother-offspring dyads were significantly stronger than those between unrelated individuals. Notably, both sons and daughters exhibited brain regions similar to their fathers only, mothers only, both parents, or neither parent. Furthermore, a significant association was observed between similarities in general intelligence and the surface area of auditory regions in both father-offspring and mother-offspring dyads. These results provide valuable insights into the genetic and environmental factors influencing brain development and aging across generations. This study is expected to contribute to future research elucidating the mechanisms underlying the intergenerational transmission of psychiatric disorders. (Comment on this)
5:31p	Gradual consolidation of skilled sequential movements in primary motor cortex of non-human primates Expert-level performance of sequential movements can be achieved through extensive practice. The primary motor cortex (M1) is suggested to play a key role in acquiring and retaining sequential movements, with evidence of reorganization in M1 following prolonged practice, such as changes in fMRI activation in humans and altered neuron activity in monkeys. Here, we examined the timeline of plastic changes in M1 of monkeys during learning of sequential movements. A challenge in studying a role of M1 in learning is that its inactivation impairs movement, masking learning processes. To address this, we used a protein synthesis inhibitor to disrupt memory consolidation in M1 during learning. Our results show that inhibiting protein synthesis in M1 disrupted memory-guided performance at all stages of learning, though the effect decreased with continued practice. This suggests that neural traces for sequential movements are repeatedly consolidated through protein synthesis, with the rate of consolidation slowing as learning progresses. (Comment on this)
5:31p	A complete account of the behavioral repertoire uncovers principles of larval zebrafish hunting behavior In goal-directed behavior animals select actions from a diverse repertoire of possible movements. Accurately quantifying the complete behavioral repertoire can uncover the underlying rules that guide such goal-directed behavior. However, these movements are usually complex, high-dimensional, and lead to various outcomes, posing a challenge to fully capture the complete repertoire. By tracking freely hunting zebrafish larvae using a highspeed camera and analyzing their movements, we developed a mathematical model that accurately reproduces the complete repertoire. Using the model, we show that fish position and change in heading angle following a movement are coupled, such that the choice of one of them limits the possibilities of the other. This repertoire structure uncovered fundamental principles of movements, showing that fish rotate around an identified rotation point and then move forward or backward along straight lines. From the uncovered movement principles, we identified a new guiding rule for prey interaction: in each movement, fish turn to face the prey and then move forward or backward. This enables decoupling between orientation and distance selections of the fish during the hunt. These results provide a comprehensive and continuous description of the repertoire of movements, reveal underlying algorithmic rules that govern the behavior, and offer insights into the potential neural implementation of the repertoire. (Comment on this)
5:31p	Genetically encoded biosensor for fluorescence lifetime imaging of PTEN dynamics in the intact brain The phosphatase and tensin homolog (PTEN) is a vital signaling protein which maintains an inhibitory brake that is critical for cellular metabolism, proliferation, and growth. The importance of PTEN signaling is evident from the broad spectrum of human pathologies associated with its loss of function. Moreover, loss or gain of PTEN function in animal models leads to aberrant cellular morphology, function, and metabolic regulation. However, despite the important role of PTEN signaling, there is currently no method to dynamically monitor its activity with cellular specificity within intact biological systems. Here, we describe the development of a novel PTEN biosensor, optimized for two-photon fluorescence lifetime imaging microscopy (2pFLIM). This biosensor is designed to measure PTEN activity within intact cells, tissues, and organisms. Our approach is based on monitoring FRET-dependent changes in PTEN conformation, which serves as a proxy for the activity state in living cells. We identify a point mutation that allow us to express this biosensor with minimal interference to endogenous PTEN signaling and cellular function. We demonstrate the utility of imaging PTEN signaling in cell lines, developing C. elegans, and in the living mouse brain. To complement this approach, we developed a red-shifted PTEN sensor variant that permits simultaneous imaging with GFP-based sensors. Finally, we use in vivo PTEN imaging in the mouse brain to identify cell-type specific dynamics of PTEN activity in excitatory and inhibitory cortical cells. In summary, our approach enables dynamic imaging of PTEN activity in vivo with unprecedented spatial and temporal resolution. (Comment on this)
5:31p	Neural dynamics for working memory and evidence integration during olfactory navigation in Drosophila To navigate towards an unknown food source, animals must accumulate evidence about the location of a goal and store this information in working memory. Here we identify a population of local neurons in the fan-shaped body of Drosophila that exhibits both evidence integration and working memory dynamics. Imaging from these neurons during virtual odor-guided navigation reveals a bump of activity that is activated by odor, but can outlast the odor stimulus by several seconds. Persistent bump activity is associated with persistent movement in the direction adopted during odor, arguing that these neurons represent a directional working memory. When the fly navigates a virtual odor plume, bump activity slowly ramps up with successive odor encounters, indicating that it integrates odor information over time. We do not observe these dynamics in a set of neighboring local neurons, although both populations show slow modulation correlated with engagement in the task. Silencing the first population impairs the integration of odor encounters and the persistence of upwind heading. Our work identifies a small group of genetically-identified neurons that integrate and store stochastic sensory evidence to support navigation in complex natural environments. (Comment on this)
6:47p	Biologically Realistic Computational Primitives of Neocortex Implemented on Neuromorphic Hardware Improve Vision Transformer Performance Understanding the computational principles of the brain and replicating them on neuromorphic hardware and modern deep learning architectures is crucial for advancing neuro-inspired AI (NeuroAI). Here, we develop an experimentally-constrained biophysical network model of neocortical circuit motifs, focusing on layers 2-3 of the primary visual cortex (V1). We investigate the role of four major cortical interneuron classes in a competitive-cooperative computational primitive and validate these circuit motifs implemented soft winner-take-all (sWTA) computation for gain modulation, signal restoration, and context-dependent multistability. Using a novel parameter mapping technique, we configured IBM's TrueNorth (TN) chip to implement sWTA computations, mirroring biological neural dynamics. Retrospectively, we observed a strong correspondence between the biophysical model and the TN hardware parameters, particularly in the roles of four key inhibitory neuron classes: Parvalbumin (feedforward inhibition), Somatostatin (feedback inhibition), VIP (disinhibition), and LAMP5 (gain normalization). Moreover, the sparse coupling of this sWTA motif was also able to simulate a two-state neural state machine on the TN chip, replicating working memory dynamics essential for cognitive tasks. Additionally, integrating the sWTA computation as a pre-processing layer in the Vision Transformer (ViT) enhanced its performance on the MNIST digit classification task, demonstrating improved generalization to previously unseen data and suggesting a mechanism akin to zero-shot learning. Our approach provides a framework for translating brain-inspired computations to neuromorphic hardware, with potential applications on platforms like Intel's Loihi2 and IBM's Northpole. By integrating biophysically accurate models with neuromorphic hardware and advanced machine learning techniques, we offer a comprehensive roadmap for embedding neural computation into NeuroAI systems. (Comment on this)
6:47p	Leveraging Single-Cell RNA-Seq to Generate Robust Microglia Aging Clocks 'Biological aging clocks' - composite molecular markers thought to capture an individual's biological age - have been traditionally developed through bulk-level analyses of mixed cells and tissues. However, recent evidence highlights the importance of gaining single-cell-level insights into the aging process. Microglia are key immune cells in the brain shown to adapt functionally in aging and disease. Recent studies have generated single-cell RNA sequencing (scRNA-seq) datasets that transcriptionally profile microglia during aging and development. Leveraging such datasets, we develop and compare computational approaches for generating transcriptome-wide summaries to establish robust microglia aging clocks. Our results reveal that unsupervised, frequency-based featurization approaches strike a balance in accuracy, interpretability, and computational efficiency. We further extrapolate and demonstrate applicability of such microglia clocks to readily available bulk RNA-seq data with environmental inputs. Single-cell-derived clocks can yield insights into the determinants of brain aging, ultimately promoting interventions that beneficially modulate health and disease trajectories. (Comment on this)
6:47p	Continuous cell type diversification throughout the embryonic and postnatal mouse visual cortex development The mammalian cortex is composed of a highly diverse set of cell types and develops through a series of temporally regulated events that build out the cell type and circuit foundation for cortical function. The mechanisms underlying the development of different cell types remain elusive. Single-cell transcriptomics provides the capacity to systematically study cell types across the entire temporal range of cortical development. Here, we present a comprehensive and high-resolution transcriptomic and epigenomic cell type atlas of the developing mouse visual cortex. The atlas was built from a single-cell RNA-sequencing dataset of 568,674 high-quality single-cell transcriptomes and a single-nucleus Multiome dataset of 194,545 high-quality nuclei providing both transcriptomic and chromatin accessibility profiles, densely sampled throughout the embryonic and postnatal developmental stages from E11.5 to P56. We computationally reconstructed a transcriptomic developmental trajectory map of all excitatory, inhibitory, and non-neuronal cell types in the visual cortex, identifying branching points marking the emergence of new cell types at specific developmental ages and defining molecular signatures of cellular diversification. In addition to neurogenesis, gliogenesis and early postmitotic maturation in the embryonic stage which gives rise to all the cell classes and nearly all subclasses, we find that increasingly refined cell types emerge throughout the postnatal differentiation process, including the late emergence of many cell types during the eye-opening stage (P11-P14) and the onset of critical period (P21), suggesting continuous cell type diversification at different stages of cortical development. Throughout development, we find cooperative dynamic changes in gene expression and chromatin accessibility in specific cell types, identifying both chromatin peaks potentially regulating the expression of specific genes and transcription factors potentially regulating specific peaks. Furthermore, a single gene can be regulated by multiple peaks associated with different cell types and/or different developmental stages. Collectively, our study provides the most detailed dynamic molecular map directly associated with individual cell types and specific developmental events that reveals the molecular logic underlying the continuous refinement of cell type identities in the developing visual cortex. (Comment on this)
6:47p	Differential Speed and Accuracy Trade-off in Working Memory Retrieval and Bilateral Precuneus between Older Men and Women Background: Despite various hypotheses, including differences in longevity, hormones, genetics, and neuroanatomy, the reasons for the higher prevalence of Alzheimer's disease in older women compared to men remain unclear. Emerging evidence suggests that the precuneus, a key region of the default mode network, is linked to internally focused processes like memory retrieval. This study examined sex differences in the relationship between precuneus volumes and working memory retrieval speed in cognitively normal older adults, hypothesizing that disparities in precuneus size and function contribute to reduced working memory performance in older women. Method: A cohort of participants (N=45; 25 women; Mage =77) from the University of Kentucky Alzheimer's Disease Research Center completed the Bluegrass Working Memory Task while undergoing 3T Siemens magnetic resonance imaging scans. Result: Applying Spearman correlation analyses, the results revealed correlations between working memory accuracy and volumes in the left (r=-.43, p<.01) and right (r=-.36, p<.05) precuneus across all subjects. Sex difference analysis indicated a tendency for the accuracy of the memory task to correlate more frequently with the left precuneus in women (r= 0.54; p < 0.05) than in men. Similarly, volumes in the left precuneus displayed a significant negative correlation with reaction time in response to memory target (r = -0.426; p < 0.05) and memory distractor (r = -0.549; p < 0.01) in women. There is a sex difference in accuracy and speed trade-off. While men were faster in reaction time, women were better in the accuracy of the memory task. Particularly noteworthy was the consistent association in women, where neurocognitive measures (Trail A, r= -.50, p<.01; Trail B, r= -.06, p<.01) reliably correlated with volumes in the left precuneus--a relationship not observed in men. Discussion: Our findings suggest that the left precuneus volume is associated with processing speed and accuracy of working memory performance, especially in women. Given that the left precuneus plays a key role in supporting various aspects of cognition, including memory retrieval, our findings point to the potential of reaction time serving as a surrogate marker for fMRI in predicting cognitive decline, particularly when considering sex differences. (Comment on this)

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