Biology subjects

Moore, T.

Publications and source records attributed to Moore, T..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

ArborSim: Articulated, branching, OpenSim routing for constructing models of multi-jointed appendages with complex muscle-tendon architecture

Computational models of musculoskeletal systems are essential tools for understanding how muscles, tendons, bones, and actuation signals generate motion. In particular, the OpenSim family of models has facilitated a wide range of studies on diverse human motions, clinical studies of gait, and even non-human locomotion. However, biological structures with many joints, such as fingers, necks, tails, and spines, have been a longstanding challenge to the OpenSim modeling community, especially because these structures comprise numerous bones and are frequently actuated by extrinsic muscles that span multiple joints--often more than three--and act through a complex network of branching tendons. Existing model building software, typically optimized for limb structures, makes it difficult to build OpenSim models that accurately reflect these intricacies. Here, we introduce ArborSim, customized software that efficiently creates musculoskeletal models of highly jointed structures and can build branched muscle-tendon architectures. We used ArborSim to construct toy models of articulated structures to determine which morphological features make a structure most sensitive to branching. By comparing the joint kinematics of models constructed with branched and parallel muscle-tendon units, we found that the number of tendon branches and the number of joints between branches are most sensitive to branching modeling method--notably, the differences between these models showed no predictable pattern with increased complexity. As the proportion of muscle increased, the kinematic differences between branched and parallel models units also increased. Our findings suggest that stress and strain interactions between distal tendon branches and proximal tendon and muscle greatly affect the overall kinematics of a musculoskeletal system. By incorporating complex muscle-tendon branching into OpenSim models using ArborSim, we can gain deeper insight into the interactions between the axial and appendicular skeleton, model the evolution and function of diverse animal tails, and understand the mechanics of more complex motions and tasks.

biophysics↗

bioRxiv2023

Oligodendrocyte-specific expression of PSG8-AS1 suggests a role in myelination with prognostic value in oligodendroglioma.

The segmentally duplicated Pregnancy-specific glycoprotein (PSG) locus on chromosome 19q13 may be one of the most rapidly evolving in the human genome. It comprises ten coding genes (PSG1-9, 11) and one predominantly non-coding gene (PSG10) that are expressed in the placenta and gut, in addition to several poorly characterized long non-coding RNAs. We report that long non-coding RNA PSG8-AS1 has an oligodendrocyte-specific expression pattern and is co-expressed with genes encoding key myelin constituents. PSG8-AS1 exhibits two peaks of expression during human brain development coinciding with the most active periods of oligodendrogenesis and myelination. PSG8-AS1 orthologs were found in the genomes of several primates but significant expression was found only in the human, suggesting a recent evolutionary origin of its proposed role in myelination. Additionally, because co-deletion of chromosomes 1p/19q is a genomic marker of oligodendroglioma, expression of PSG8-AS1 was examined in these tumors. PSG8-AS1 may be a promising diagnostic biomarker for glioma, with prognostic value in oligodendroglioma.

neuroscience↗

bioRxiv2023

Cue-specific neuronal ensembles span intermittent rate coding of working memory

Persistent, memorandum-specific neuronal spiking activity has long been hypothesized to underlie working memory. However, emerging evidence suggests a possible role for activity-silent synaptic mechanisms. This issue remains controversial because evidence for either view has largely depended on datasets that fail to capture single-trial population dynamics or on indirect measures of neuronal spiking. We addressed this by examining the dynamics of mnemonic information on single trials obtained from large, local populations of prefrontal neurons recorded simultaneously in monkeys performing a working memory task. We show that mnemonic information does not persist in the spiking activity of prefrontal neurons, but instead alternates between On and Off periods during memory delays. At the level of single neurons, Off periods are driven by a coordinated loss of selectivity for memoranda and a return of firing rates to baseline levels. Further exploiting the large-scale recordings, we asked whether the functional connectivity among large neuronal ensembles depended on information held in working memory. We show that mnemonic information is available in the pattern of ensemble connectivity during the memory delay in both On and Off periods of neuronal activity. Intermittent epochs of memoranda-specific spiking therefore coexist with activity-silent mechanisms to span memory delays.

neuroscience↗

bioRxiv2023

Dissociating the Contributions of Frontal Eye Field Activity to Spatial Working Memory and Motor Preparation

Neurons within dorsolateral prefrontal cortex of primates are characterized by robust persistent spiking activity exhibited during the delay period of working memory tasks. This includes the frontal eye field (FEF) where nearly half of the neurons are active when spatial locations are held in working memory. Past evidence has established the FEFs contribution to the planning and triggering of saccadic eye movements as well as to the control of visual spatial attention. However, it remains unclear if persistent delay activity reflects a similar dual role in movement planning and visuospatial working memory. We trained monkeys to alternate between different forms of a spatial working memory task which could dissociate remembered stimulus locations from planned eye movements. We tested the effects of inactivation of FEF sites on behavioral performance in the different tasks. Consistent with previous studies, FEF inactivation impaired the execution of memory-guided saccades, and impaired performance when remembered locations matched the planned eye movement. In contrast, memory performance was largely unaffected when the remembered location was dissociated from the correct eye movement response. Overall, the inactivation effects demonstrated clear deficits on eye movements, regardless of task type, but little or no evidence of a deficit in spatial working memory. Thus, our results indicate that persistent delay activity in the FEF contributes primarily to the preparation of eye movements and not to spatial working memory.

neuroscience↗

bioRxiv2023

Pupil size predicts the onset of exploration in brain and behavior.

In uncertain environments, intelligent decision-makers exploit actions that have been rewarding in the past, but also explore actions that could be even better. Several neuromodulatory systems are implicated in exploration, based, in part, on work linking exploration to pupil size-a peripheral correlate of neuromodulatory tone and index of arousal. However, pupil size could instead track variables that make exploration more likely, like volatility or reward, without directly predicting either exploration or its neural bases. Here, we simultaneously measured pupil size, exploration, and neural population activity in the prefrontal cortex while two rhesus macaques explored and exploited in a dynamic environment. We found that pupil size under constant luminance specifically predicted the onset of exploration, the first exploratory trial in a sequence, beyond what could be explained by reward history. Pupil size also predicted disorganized patterns of prefrontal neural activity at both the single neuron and population levels, even within periods of exploitation. Ultimately, our results support a model in which pupil-linked mechanisms promote the onset of exploration via driving the prefrontal cortex through a critical tipping point where prefrontal control dynamics become disorganized and exploratory decisions are possible. Significance StatementHumans and other animals learn about the world through exploration: through making decisions that offer the opportunity to learn and discover, even when these decisions are not the best option in the moment. Neuroscience research has historically focused on understanding good choices, delivering many key insights into the neural mechanisms involved in these calculations. However, much less is known about how the brain generates exploratory decisions. This study identifies certain "early warning signs" of exploratory decisions in the brain and body, including certain signals in size of the pupil and the speed of neural activity in the prefrontal cortex. These early warning signs suggest that exploration may be the result of a critical tipping point in prefrontal brain states.

neuroscience↗

bioRxiv2023

Large-scale brain-wide neural recording in nonhuman primates

High-density, integrated silicon electrodes have begun to transform systems neuroscience, by enabling large-scale neural population recordings with single cell resolution. Existing technologies, however, have provided limited functionality in nonhuman primate species such as macaques, which offer close models of human cognition and behavior. Here, we report the design, fabrication, and performance of Neuropixels 1.0-NHP, a high channel count linear electrode array designed to enable large-scale simultaneous recording in superficial and deep structures within the macaque or other large animal brain. These devices were fabricated in two versions: 4416 electrodes along a 45 mm shank, and 2496 along a 25 mm shank. For both versions, users can programmatically select 384 channels, enabling simultaneous multi-area recording with a single probe. We demonstrate recording from over 3000 single neurons within a session, and simultaneous recordings from over 1000 neurons using multiple probes. This technology represents a significant increase in recording access and scalability relative to existing technologies, and enables new classes of experiments involving fine-grained electrophysiological characterization of brain areas, functional connectivity between cells, and simultaneous brain-wide recording at scale.

neuroscience↗

bioRxiv2022

Functional Connections Among Neurons within Single Columns of Macaque V1

Recent developments in high-density neurophysiological tools now make it possible to record from hundreds of single neurons within local, highly interconnected neural networks. Among the many advantages of such recordings is that they dramatically increase the quantity of identifiable, functional connections between neurons thereby providing an unprecedented view of local circuit interactions. Using high-density, Neuropixels recordings from single neocortical columns of primary visual cortex in nonhuman primates, we identified 1000s of functionally connected neuronal pairs using established crosscorrelation approaches. Our results reveal clear and systematic variations in the strength and synchrony of functional connections across the cortical column. Despite neurons residing within the same column, both measures of functional connectivity depended heavily on the vertical distance separating neuronal pairs, as well as on the similarity of stimulus tuning. In addition, we leveraged the statistical power afforded by the large numbers of connected pairs to categorize functional connections between neurons based on their crosscorrelation functions. These analyses identified distinct, putative classes of functional connections within the full population. These classes of functional connections were corroborated by their unique distributions across defined laminar compartments and were consistent with known properties of V1 cortical circuitry, such as the lead-lag relationship between simple and complex cells. Our results provide a clear proof-of-principle for the use of high-density neurophysiological recordings to assess circuit-level interactions within local neuronal networks.

neuroscience↗

bioRxiv2022

Rapid Selectivity to Natural Images Across Layers of Primate V1

Visual systems are thought to have adapted to the statistical properties of natural scenes. However, the extent to which visual neurons respond selectively to natural images, and the stage at which that selectivity emerges remains unclear. To address these questions, we recorded the visual activity of neurons in macaque V1 using high-density electrode arrays (Neuropixels), and compared neuronal responses to images presented at three levels of naturalness. We found that within 60 ms of stimulus onset, neurons in all cortical layers, including input layers 4C alpha and beta, responded more vigorously to natural images than to statistically matched naturalistic texture and noise images. The result remained when residual variations in the local image statistics were factored out. V1 neurons also showed high population and lifetime sparseness for natural images. Across the population of V1 neurons, sensitivity to natural images exceeded the sensitivity to other image categories. The results reveal a rapid and pervasive preference for natural images is present at the earliest stages of cortical processing.

neuroscience↗

bioRxiv2022

Genetic variation of human myokine signaling is dominated by biologic sex and sex hormones

Abstract/IntroductionProteins secreted from skeletal muscle, termed myokines, allow muscle to impact systemic physiology and disease. Myokines play critical roles in a variety of processes, including metabolic homeostasis, exercise improvements, inflammation, cancer and cognitive functions1-6. Despite the clear relevance of these factors in mediating a multitude of physiological outcomes, the genetic architecture, regulation and functions of myokines, as well as degree of conservation of these communication circuits remains inadequately understood. Given that biologic sex controls critical aspects of nearly every physiologic outcome, it is essential to consider when relating specific mechanisms to complex genetic and metabolic interactions. Specifically, many metabolic traits impacted by myokines show striking sex differences arising from hormonal7-10, genetic7,11 or gene-by-sex interactions12,13. In this study, we performed a genetic survey of myokine gene regulation and cross-tissue signaling in humans where sex as a biological variable was emphasized. While expression levels of a majority of myokines and cell proportions within skeletal muscle showed little differences between males and females, nearly all significant cross-tissue enrichments operated in a sex-specific or hormone-dependent fashion; in particular, with estrogens. These sex- and hormone-specific effects were consistent across key metabolic tissues: liver, pancreas, hypothalamus, intestine, heart, visceral and subcutaneous adipose tissue. Skeletal muscle estrogen receptor enrichments across metabolic tissues appeared stronger than androgen receptor and, surprisingly, ~3-fold higher in males compared to females. To define the causal roles of estrogen signaling on myokine gene expression and functions, we generated male and female mice which lack estrogen receptor (Esr1) specifically in skeletal muscle and integrated global RNA-Sequencing with human data. These analyses highlighted mechanisms of sex-dependent myokine signaling conserved between species, such as myostatin enriched for divergent substrate utilization pathways between sexes. Several other sex-dependent mechanisms of myokine signaling were uncovered, such as muscle-derived TNF exerting stronger inflammatory signaling in females compared to males and GPX3 as a male-specific link between glycolytic fiber abundance and hepatic inflammation. Collectively, we provide the first genetic survey of human myokines and highlight sex and estrogen receptor signaling as critical variables when assaying myokine functions and how changes in cell composition impact other metabolic organs.

physiology↗

bioRxiv2021

Attentional modulation of intrinsic timescales in visual cortex and spatial networks

Intrinsic timescales characterize dynamics of endogenous fluctuations in neural activity. Variation of intrinsic timescales across the neocortex reflects functional specialization of cortical areas, but less is known about how intrinsic timescales change during cognitive tasks. We measured intrinsic timescales of local spiking activity within columns of area V4 while monkeys performed spatial attention tasks. The ongoing spiking activity unfolded across at least two distinct timescales, fast and slow. The slow timescale increased when monkeys attended to the receptive fields location and correlated with reaction times. By evaluating predictions of several network models, we found that spatiotemporal correlations in V4 activity were best explained by the model in which multiple timescales arise from recurrent interactions shaped by spatially arranged connectivity, and attentional modulation of timescales results from an increase in the efficacy of recurrent interactions. Our results suggest that multiple timescales arise from the spatial connectivity in the visual cortex and flexibly change with the cognitive state due to dynamic effective interactions between neurons.

neuroscience↗

bioRxiv2021

Mobile Footprinting: Linking Individual Distinctiveness in Mobility Patterns to Mood, Sleep, and Brain Functional Connectivity

Mapping individual differences in behavior is fundamental to personalized neuroscience. Here, we establish that statistical patterns of smartphone-based mobility features represent unique "footprints" that allow individual identification. Critically, mobility footprints exhibit varying levels of person-specific distinctiveness and are associated with individual differences in affective instability, circadian irregularity, and brain functional connectivity. Together, this work suggests that real-world mobility patterns may provide an individual-specific signature linking brain, behavior, and mood.

neuroscience↗

bioRxiv2021

Non cell-autonomous effect of astrocytes on cerebral cavernous malformations

Cerebral cavernous malformations (CCMs) are common neurovascular lesions caused by loss-of-function mutations in one of three genes, including KRIT1 (CCM1), CCM2, and PDCD10 (CCM3), and generally regarded as an endothelial cell-autonomous disease. Here we report that proliferative astrocytes play a critical role in CCM pathogenesis by serving as a major source of VEGF during CCM lesion formation. An increase in astrocyte VEGF synthesis is driven by endothelial nitric oxide (NO) generated as a consequence of KLF2 and KLF4-dependent elevation of eNOS in CCM endothelium. The increased brain endothelial production of NO stabilizes HIF-1 in astrocytes, resulting in increased VEGF production and expression of a "hypoxic" program under normoxic conditions. We show that the upregulation of cyclooxygenase-2 (COX-2), a direct HIF-1 target gene and a known component of the hypoxic program, contributes to the development of CCM lesions because the administration of a COX-2 inhibitor significantly prevents progression of CCM lesions. Thus, non-cell-autonomous crosstalk between CCM endothelium and astrocytes propels vascular lesion development, and components of the hypoxic program represent potential therapeutic targets for CCMs.

neuroscience↗

bioRxiv2020

Heterogeneity of Neuronal Populations Within Columns of Primate V1 Revealed by High-Density Recordings

Primary visual cortex (V1) has been the focus of extensive neurophysiological investigation, and its laminar organization provides a key exemplar of the functional logic of neocortical microcircuits. Using newly developed high-density, linear array probes, we measured visual responses from large populations of simultaneously recorded neurons distributed across layers of macaque V1. In single recordings, myriad differences in the functional properties of neuronal subpopulations could be observed. In particular, we found that although standard measurements of orientation selectivity yielded only minor differences between laminar compartments, decoding of stimulus orientation from layer 4C responses was superior to that of both superficial and deep layers within the same cortical column. The superior orientation discrimination within layer 4C was associated with greater response reliability of individual neurons rather than lower correlated activity with neuronal populations. The results demonstrate the utility of high-density electrophysiology in revealing the functional organization and network properties of neocortical microcircuits in single experiments.

neuroscience↗

bioRxiv2020

Working Memory Gates Visual Input to Primate Prefrontal Neurons

Visually guided behavior relies on the integration of sensory input with information held in working memory. Yet it remains unclear how this is accomplished at the level of neural circuits. We studied the direct visual cortical inputs to neurons within a visuomotor area of prefrontal cortex in behaving monkeys. We show that the synaptic efficacy of visual cortical input to prefrontal cortex is gated by information held in working memory. Surprisingly, visual input to prefrontal neurons was found to target those with both visual and motor properties, rather than preferentially targeting other visual neurons. Furthermore, activity evoked from visual cortex was larger in magnitude, more synchronous, and more rapid, when monkeys remembered locations that matched the location of visual input. These results indicate that working memory directly influences the circuitry that transforms visual input into visually guided behavior.

neuroscience↗

bioRxiv2020

Robust Encoding of Abstract Rules by Distinct Neuronal Populations in Primate Visual Cortex

It is widely known that neural activity in sensory representations is modulated by cognitive factors such as attention, reward value and working memory. In such cases, sensory responses are found to reflect a selection of the specific sensory information needed to achieve behavioral goals. In contrast, more abstract behavioral constraints that do not involve stimulus selection, such as task rules, are thought to be encoded by neurons at later stages. We show that information about abstract rules is encoded by neurons in primate visual cortex in the absence of sensory stimulation. Furthermore, we show that rule information is greatest among neurons with the least visual activity and the weakest coupling to local neuronal networks. Our results identify rule-specific signals within a sensory representation and suggest that distinct mechanisms exist there for mapping rule information onto sensory guided decisions.

neuroscience↗

bioRxiv2020

Influence of On-Off dynamics and selective attention on the spatial pattern of correlated variability in neocortex

Correlated activity fluctuations in neocortex influence sensory responses and behavior. Neural correlations reflect anatomical connectivity and change dynamically with cognitive states, such as attention. Yet, how anatomical connectivity and cognitive states define the population structure of correlations is not known. We measured correlations in single cortical columns and found that the magnitude of correlations, their attentional modulation and dependence on lateral distance are predicted by On-Off dynamics, synchronous fluctuations in population activity across cortical layers. We developed a network model, in which spatial connectivity correlates the On-Off dynamics across nearby columns. We show that attentional inputs modulate the spatial extent of On-Off dynamics, resulting in spatially non-uniform changes in correlations. We confirm this prediction in our columnar recordings by showing that attentional modulation of correlations depends on lateral distance. Our results reveal how heterogeneous spatial patterns of correlations arise from the connectivity and network dynamics during attention.

neuroscience↗

bioRxiv2020

Abortive Intussusceptive Angiogenesis Causes Multi-Cavernous Vascular Malformations

Mosaic inactivation of CCM2 in humans causes cerebral cavernous malformations (CCMs) containing adjacent dilated blood-filled multi-cavernous lesions. We used CRISPR-Cas9 mutagenesis to induce mosaic inactivation of zebrafish ccm2 resulting in a novel lethal multi-cavernous lesion in the embryonic caudal venous plexus (CVP) caused by obstruction of blood flow by intraluminal pillars. These pillars mimic those that mediate intussusceptive angiogenesis; however, in contrast to the normal process, the pillars failed to fuse to split the pre-existing vessel in two. Abortive intussusceptive angiogenesis stemmed from mosaic inactivation of ccm2 leading to patchy klf2a over-expression and resultant aberrant flow signaling. Surviving adult fish manifested histologically-typical hemorrhagic CCM. Formation of mammalian CCM requires the flow-regulated transcription factor KLF2; fish CCM and the embryonic CVP lesion failed to form in klf2a null fish indicating a common pathogenesis with the mammalian lesion. These studies describe a zebrafish CCM model and establish a mechanism that can explain the formation of characteristic multi-cavernous lesions.

developmental biology↗

bioRxiv2020

Separable influences of reward value on visual processing and choice

Primate vision is characterized by constant, sequential processing and selection of visual targets to fixate. Although expected reward is known to influence both processing and selection of visual targets, similarities and differences between these effects remains unclear mainly because they have been measured in separate tasks. Using a novel paradigm, we simultaneously measured the effects of reward outcomes and expected reward on target selection and sensitivity to visual motion in monkeys. Monkeys freely chose between two visual targets and received a juice reward with varying probability for eye movements made to either of them. Targets were stationary apertures of drifting gratings, causing the endpoints of eye movements to these targets to be systematically biased in the direction of motion. We used this motion-induced bias as a measure of sensitivity to visual motion on each trial. We then performed different analyses to explore effects of objective and subjective reward values on choice and sensitivity to visual motion in order to find similarities and differences between reward effects on these two processes. Specifically, we used different reinforcement learning models to fit choice behavior and estimate subjective reward values based on the integration of reward outcomes over multiple trials. Moreover, to compare the effects of subjective reward value on choice and sensitivity to motion directly, we considered correlations between each of these variables and integrated reward outcomes on a wide range of timescales. We found that in addition to choice, sensitivity to visual motion was also influenced by subjective reward value, even though the motion was irrelevant for receiving reward. Unlike choice, however, sensitivity to visual motion was not affected by objective measures of reward value. Moreover, choice was determined by the difference in subjective reward values of the two options whereas sensitivity to motion was influenced by the sum of values. Finally, models that best predicted visual processing and choice used sets of estimated reward values based on different types of reward integration and timescales. Together, our results demonstrate separable influences of reward on visual processing and choice, and point to the presence of multiple brain circuits for integration of reward outcomes.

neuroscience↗