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BioRxiv : the Preprint Server For... Jun 2024Human language comprehension is remarkably robust to ill-formed inputs (e.g., word transpositions). This robustness has led some to argue that syntactic parsing is...
UNLABELLED
Human language comprehension is remarkably robust to ill-formed inputs (e.g., word transpositions). This robustness has led some to argue that syntactic parsing is largely an illusion, and that incremental comprehension is more heuristic, shallow, and semantics-based than is often assumed. However, the available data are also consistent with the possibility that humans always perform rule-like symbolic parsing and simply deploy error correction mechanisms to reconstruct ill-formed inputs when needed. We put these hypotheses to a new stringent test by examining brain responses to a) stimuli that should pose a challenge for syntactic reconstruction but allow for complex meanings to be built within local contexts through associative/shallow processing (sentences presented in a backward word order), and b) grammatically well-formed but semantically implausible sentences that should impede semantics-based heuristic processing. Using a novel behavioral syntactic reconstruction paradigm, we demonstrate that backward- presented sentences indeed impede the recovery of grammatical structure during incremental comprehension. Critically, these backward-presented stimuli elicit a relatively low response in the language areas, as measured with fMRI. In contrast, semantically implausible but grammatically well-formed sentences elicit a response in the language areas similar in magnitude to naturalistic (plausible) sentences. In other words, the ability to build syntactic structures during incremental language processing is both necessary and sufficient to fully engage the language network. Taken together, these results provide strongest to date support for a generalized reliance of human language comprehension on syntactic parsing.
SIGNIFICANCE STATEMENT
Whether language comprehension relies predominantly on structural (syntactic) cues or meaning- related (semantic) cues remains debated. We shed new light on this question by examining the language brain areas' responses to stimuli where syntactic and semantic cues are pitted against each other, using fMRI. We find that the language areas respond weakly to stimuli that allow for local semantic composition but cannot be parsed syntactically-as confirmed in a novel behavioral paradigm-and they respond strongly to grammatical but semantically implausible sentences, like the famous 'Colorless green ideas sleep furiously' sentence. These findings challenge accounts of language processing that suggest that syntactic parsing can be foregone in favor of shallow semantic processing.
PubMed: 38948870
DOI: 10.1101/2024.06.21.599332 -
BioRxiv : the Preprint Server For... Jun 2024Functional connectivity (FC) is the degree of synchrony of time series between distinct, spatially separated brain regions. While traditional FC analysis assumes the...
Functional connectivity (FC) is the degree of synchrony of time series between distinct, spatially separated brain regions. While traditional FC analysis assumes the temporal stationarity throughout a brain scan, there is growing recognition that connectivity can change over time and is not stationary, leading to the concept of dynamic FC (dFC). Resting-state functional magnetic resonance imaging (fMRI) can assess dFC using the sliding window method with the correlation analysis of fMRI signals. Accurate statistical inference of sliding window correlation must consider the autocorrelated nature of the time series. Currently, the dynamic consideration is mainly confined to the point estimation of sliding window correlations. Using in vivo resting-state fMRI data, we first demonstrate the non-stationarity in both the cross-correlation function (XCF) and the autocorrelation function (ACF). Then, we propose the variance estimation of the sliding window correlation considering the nonstationary of XCF and ACF. This approach provides a means to dynamically estimate confidence intervals in assessing dynamic connectivity. Using simulations, we compare the performance of the proposed method with other methods, showing the impact of dynamic ACF and XCF on connectivity inference. Accurate variance estimation can help in addressing the critical issue of false positivity and negativity.
PubMed: 38948863
DOI: 10.1101/2024.06.18.599636 -
BioRxiv : the Preprint Server For... Jun 2024While genome-wide association studies and expression quantitative trait loci (eQTL) analysis have made significant progress in identifying noncoding variants associated...
While genome-wide association studies and expression quantitative trait loci (eQTL) analysis have made significant progress in identifying noncoding variants associated with prostate cancer risk and bulk tissue transcriptome changes, the regulatory effect of these genetic elements on gene expression remains largely unknown. Recent developments in single-cell sequencing have made it possible to perform ATAC-seq and RNA-seq profiling simultaneously to capture functional associations between chromatin accessibility and gene expression. In this study, we tested our hypothesis that this multiome single-cell approach allows for mapping regulatory elements and their target genes at prostate cancer risk loci. We applied a 10X Multiome ATAC + Gene Expression platform to encapsulate Tn5 transposase-tagged nuclei from multiple prostate cell lines for a total of 65,501 high quality single cells from RWPE1, RWPE2, PrEC, BPH1, DU145, PC3, 22Rv1 and LNCaP cell lines. To address data sparsity commonly seen in the single-cell sequencing, we performed targeted sequencing to enrich sequencing data at prostate cancer risk loci involving 2,730 candidate germline variants and 273 associated genes. Although not increasing the number of captured cells, the targeted multiome data did improve eQTL gene expression abundance by about 20% and chromatin accessibility abundance by about 5%. Based on this multiomic profiling, we further associated RNA expression alterations with chromatin accessibility of germline variants at single cell levels. Cross validation analysis showed high overlaps between the multiome associations and the bulk eQTL findings from GTEx prostate cohort. We found that about 20% of GTEx eQTLs were covered within the significant multiome associations ( -value ≤ 0.05, gene abundance percentage ≥ 5%), and roughly 10% of the multiome associations could be identified by significant GTEx eQTLs. We also analyzed accessible regions with available heterozygous SNP reads and observed more frequent association in genomic regions with allelically accessible variants ( = 0.0055). Among these findings were previously reported regulatory variants including rs60464856- multiome -value = 0.0099 in BPH1 and rs7247241- multiome -value = 0.0002- 0.0004 in 22Rv1 . We also functionally validated a new regulatory SNP and its target gene rs2474694- multiome -value = 0.00956 in BPH1 and 0.00625 in DU145) by reporter assay and SILAC proteomics sequencing. Taken together, our data demonstrated the feasibility of the multiome single-cell approach for identifying regulatory SNPs and their regulated genes.
PubMed: 38948854
DOI: 10.1101/2024.06.19.599704 -
BioRxiv : the Preprint Server For... Jun 2024Decreased excitability of pyramidal tract neurons in layer 5B (PT5B) of primary motor cortex (M1) has recently been shown in a dopamine-depleted mouse model of...
Decreased cellular excitability of pyramidal tract neurons in primary motor cortex leads to paradoxically increased network activity in simulated parkinsonian motor cortex.
Decreased excitability of pyramidal tract neurons in layer 5B (PT5B) of primary motor cortex (M1) has recently been shown in a dopamine-depleted mouse model of parkinsonism. We hypothesized that decreased PT5B neuron excitability would substantially disrupt oscillatory and non-oscillatory firing patterns of neurons in layer 5 (L5) of primary motor cortex (M1). To test this hypothesis, we performed computer simulations using a previously validated computer model of mouse M1. Inclusion of the experimentally identified parkinsonism-associated decrease of PT5B excitability into our computational model produced a paradoxical increase in rest-state PT5B firing rate, as well as an increase in beta-band oscillatory power in local field potential (LFP). In the movement-state, PT5B population firing and LFP showed reduced beta and increased high-beta, low-gamma activity of 20-35 Hz in the parkinsonian, but not in control condition. The appearance of beta-band oscillations in parkinsonism would be expected to disrupt normal M1 motor output and contribute to motor activity deficits seen in patients with Parkinson's disease (PD).
PubMed: 38948850
DOI: 10.1101/2024.05.23.595566 -
BioRxiv : the Preprint Server For... Jun 2024Inhibitory control is a crucial cognitive-control ability for behavioral flexibility that has been extensively investigated through action-stopping tasks. Multiple...
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Inhibitory control is a crucial cognitive-control ability for behavioral flexibility that has been extensively investigated through action-stopping tasks. Multiple neurophysiological features have been proposed to represent 'signatures' of inhibitory control during action-stopping, though the processes signified by these signatures are still controversially discussed. The present study aimed to disentangle these processes by comparing simple stopping situations with those in which additional action revisions were needed. Three experiments in female and male humans were performed to characterize the neurophysiological dynamics involved in action-stopping and - changing, with hypotheses derived from recently developed two-stage 'pause-then-cancel' models of inhibitory control. Both stopping and revising an action triggered an early broad 'pause'-process, marked by frontal EEG β-bursts and non-selective suppression of corticospinal excitability. However, partial-EMG responses showed that motor activity was only partially inhibited by this 'pause', and that this activity can be further modulated during action-revision. In line with two-stage models of inhibitory control, subsequent frontocentral EEG activity after this initial 'pause' selectively scaled depending on the required action revisions, with more activity observed for more complex revisions. This demonstrates the presence of a selective, effector-specific 'retune' phase as the second process involved in action-stopping and -revision. Together, these findings show that inhibitory control is implemented over an extended period of time and in at least two phases. We are further able to align the most commonly proposed neurophysiological signatures to these phases and show that they are differentially modulated by the complexity of action-revision.
SIGNIFICANCE STATEMENT
Inhibitory control is one of the most important control processes by which humans can regulate their behavior. Multiple neurophysiological signatures have been proposed to reflect inhibitory control. However, these play out on different time scales and appear to reflect different aspects of cognitive control, which are controversially debated.Recent two-stage models of inhibitory control have proposed that two phases implement the revisions of actions: 'pause' and 'retune'. Here, we provide the first empirical evidence for this proposition: Action revisions engendered a common initial low-latency 'pause', during which motor activity is broadly suppressed. Later activity, however, distinguishes between simple stopping of actions and more complex action revisions. These findings provide novel insights into the sequential dynamics of human action control.
PubMed: 38948849
DOI: 10.1101/2024.06.18.597172 -
BioRxiv : the Preprint Server For... Jun 2024Cirrhosis, advanced liver disease, affects 2-5 million Americans. While most patients have compensated cirrhosis and may be fairly asymptomatic, many decompensate and...
UNLABELLED
Cirrhosis, advanced liver disease, affects 2-5 million Americans. While most patients have compensated cirrhosis and may be fairly asymptomatic, many decompensate and experience life-threatening complications such as gastrointestinal bleeding, confusion (hepatic encephalopathy), and ascites, reducing life expectancy from 12 to less than 2 years. Among patients with compensated cirrhosis, identifying patients at high risk of decompensation is critical to optimize care and reduce morbidity and mortality. Therefore, it is important to preferentially direct them towards specialty care which cannot be provided to all patients with cirrhosis. We used discovery Top-down Proteomics (TDP) to identify differentially expressed proteoforms (DEPs) in the plasma of patients with progressive stages of liver cirrhosis with the ultimate goal to identify candidate biomarkers of disease progression. In this pilot study, we identified 209 DEPs across three stages of cirrhosis (compensated, compensated with portal hypertension, and decompensated), of which 115 derived from proteins enriched in the liver at a transcriptional level and discriminated the three stages of cirrhosis. Enrichment analyses demonstrated DEPs are involved in several metabolic and immunological processes known to be impacted by cirrhosis progression. We have preliminarily defined the plasma proteoform signatures of cirrhosis patients, setting the stage for ongoing discovery and validation of biomarkers for early diagnosis, risk stratification, and disease monitoring.
HIGHLIGHTS
Performed a pilot top-down LC-MS/MS analysis to identify proteoforms (PFRs) in the plasma of patients with 3 progressive stages of liver cirrhosis.Identified 2867 proteoforms (PFRs) and 209 differentially regulated proteoforms (DRPs) in the different stages of the disease.Identified DRP profiles able to potentially distinguish early from late stages of the disease, including 115 liver-derived DRPs.Fibrinogen alpha chain, haptoglobin, and Apo A-I are the proteins with the highest number of DRPs and represent potential candidate biomarkers of liver cirrhosis progression.
PubMed: 38948836
DOI: 10.1101/2024.06.19.599662 -
BioRxiv : the Preprint Server For... Jun 2024The mammalian spinal locomotor network is composed of diverse populations of interneurons that collectively orchestrate and execute a range of locomotor behaviors....
UNLABELLED
The mammalian spinal locomotor network is composed of diverse populations of interneurons that collectively orchestrate and execute a range of locomotor behaviors. Despite the identification of many classes of spinal interneurons constituting the locomotor network, it remains unclear how the network's collective activity computes and modifies locomotor output on a step-by-step basis. To investigate this, we analyzed lumbar interneuron population recordings and multi-muscle electromyography from spinalized cats performing air stepping and used artificial intelligence methods to uncover state space trajectories of spinal interneuron population activity on single step cycles and at millisecond timescales. Our analyses of interneuron population trajectories revealed that traversal of specific state space regions held millisecond-timescale correspondence to the timing adjustments of extensor-flexor alternation. Similarly, we found that small variations in the path of state space trajectories were tightly linked to single-step, microvolt-scale adjustments in the magnitude of muscle output.
ONE SENTENCE SUMMARY
Features of spinal interneuron state space trajectories capture variations in the timing and magnitude of muscle activations across individual step cycles, with precision on the scales of milliseconds and microvolts respectively.
PubMed: 38948833
DOI: 10.1101/2024.06.20.599927 -
BioRxiv : the Preprint Server For... Jun 2024Gas vesicles (GVs) based on acoustic reporter genes have emerged as potent contrast agents for cellular and molecular ultrasound imaging. These air-filled, genetically...
Gas vesicles (GVs) based on acoustic reporter genes have emerged as potent contrast agents for cellular and molecular ultrasound imaging. These air-filled, genetically encoded protein nanostructures can be expressed in a variety of cell types to visualize cell location and activity or injected systemically to label and monitor tissue function. Distinguishing GVs from tissue signal deep inside intact organisms requires imaging approaches such as amplitude modulation (AM) or collapse-based pulse sequences, however they have limitations in sensitivity or require irreversible collapse of the GVs that restricts its scope for imaging dynamic cellular processes. To address these limitations, this study explores the utility of harmonic imaging to enhance the sensitivity of non-destructive imaging of GVs and cellular processes. Traditional fundamental-frequency imaging utilizing cross-wave AM (xAM) sequences has been deemed optimal for GV imaging. Contrary to this, we hypothesize that harmonic imaging, integrated with xAM could significantly elevate GV detection sensitivity. To verify our hypothesis, we conducted imaging on tissue-mimicking phantoms embedded with purified GVs, mammalian cells genetically modified to express GVs, and live mice after systemic GV infusion. Our findings reveal that harmonic xAM (HxAM) imaging markedly surpasses traditional xAM in isolating GVs' nonlinear acoustic signature, showcasing significant enhancements in signal-to-background and contrast-to-background ratios across all tested samples. Further investigation into the backscattered spectra elucidates the efficacy of harmonic imaging in conjunction with xAM. HxAM imaging enables the detection of lower concentrations of GVs and cells with ultrasound and extends the imaging depth by up to 20% and imaging performance metrics by up to 10dB. These advancements bolster the capabilities of ultrasound for molecular and cellular imaging, underscoring the potential of using harmonic signals to amplify GV detection.
PubMed: 38948831
DOI: 10.1101/2024.06.18.599141 -
BioRxiv : the Preprint Server For... Jun 2024The precise timing of single-neuron activity in relation to local field potentials may support various cognitive functions. Extensive research in rodents, along with...
The precise timing of single-neuron activity in relation to local field potentials may support various cognitive functions. Extensive research in rodents, along with some evidence in humans, suggests that single-neuron activity at specific phases of theta oscillations plays a crucial role in memory processes. Our fundamental understanding of such theta-phase locking in humans and its dependency on basic electrophysiological properties of the local field potential is still limited, however. Here, using single-neuron recordings in epilepsy patients performing a spatial memory task, we thus aimed at improving our understanding of factors modulating theta-phase locking in the human brain. Combining a generalized-phase approach for frequency-adaptive theta-phase estimation with time-resolved spectral parameterization, our results show that theta-phase locking is a strong and prevalent phenomenon across human medial temporal lobe regions, both during spatial memory encoding and retrieval. Neuronal theta-phase locking increased during periods of elevated theta power, when clear theta oscillations were present, and when aperiodic activity exhibited steeper slopes. Theta-phase locking was similarly strong during successful and unsuccessful memory, and most neurons activated at similar theta phases between encoding and retrieval. Some neurons changed their preferred theta phases between encoding and retrieval, in line with the idea that different memory processes are separated within the theta cycle. Together, these results help disentangle how different properties of local field potentials and memory states influence theta-phase locking of human single neurons. This contributes to a better understanding of how interactions between single neurons and local field potentials may support human spatial memory.
PubMed: 38948829
DOI: 10.1101/2024.06.20.599841 -
BioRxiv : the Preprint Server For... Jun 2024Organismal aging is marked by decline in cellular function and anatomy, ultimately resulting in death. To inform our understanding of the mechanisms underlying this...
Organismal aging is marked by decline in cellular function and anatomy, ultimately resulting in death. To inform our understanding of the mechanisms underlying this degeneration, we performed standard RNA sequencing and Nanopore direct RNA sequencing over an adult time course in Long reads allowed for identification of hundreds of novel isoforms and age-associated differential isoform accumulation, resulting from alternative splicing and terminal exon choice. Genome-wide analysis reveals a decline in RNA processing fidelity and a rise in inosine and pseudouridine editing events in transcripts from older animals. In this first map of pseudouridine modifications for , we find that they largely reside in coding sequences and that the number of genes with this modification increases with age. Collectively, this analysis discovers transcriptomic signatures associated with age and is a valuable resource to understand the many processes that dictate altered gene expression patterns and post-transcriptional regulation in aging.
PubMed: 38948813
DOI: 10.1101/2024.06.18.599640