Biology subjects

Moran, I.

Publications and source records attributed to Moran, I..

11 recordsLinked to original sources

bioRxiv2026

Control of cortical population activity with patterned microstimulation

Closed-loop control of cortical activity is a central goal in systems neuroscience and clinical neuromodulation, but most approaches either rely on detailed circuit models that are unattainable in vivo or on open-loop stimulation tuned by trial and error. Here we introduce REACHable manifold Control (REACH-Ctrl), a data-driven brain-computer interface that achieves real-time control of population spiking activity using patterned microstimulation and multi-electrode recordings. REACH-Ctrl learns a finite-horizon controllability map directly from short training epochs in which random multi-electrode pulse sequences are delivered through a subset of electrodes while recording evoked responses. From these input-output data, it identifies the "reachable manifold" of population states and computes low-current microstimulation sequences that steer activity toward designated targets, without explicit knowledge of the underlying connectivity or dynamics. We test REACH-Ctrl in macaque prefrontal cortex, demonstrating high control accuracy, robust across sessions and stimulation parameters. Geometric analyses showed that multi-pulse sequences traverse a well-defined reachable manifold with substantial, but incomplete, overlap with the intrinsic neural activity manifold, revealing both on- and off-manifold components of control. Encoding models further revealed that, in our weak-stimulation regime, population responses to multi-electrode sequences are well approximated by the linear sum of localized "stimulation fields" with modest history dependence, explaining the success of our linear control approach. These results demonstrate precise, sample-efficient control of cortical population activity with clinically relevant microstimulation hardware, and provide a general blueprint for designing perturbations for sparsely observed neural circuits.

neuroscience↗

bioRxiv2023

Crossmodal correspondence of natural amplitude modulations

Crossmodal correspondence is the ability to recognize objects from different sensory modalities to be similar. Here, we investigated the capacity of humans to perform crossmodal discriminations between visual, acoustic, and tactile stimuli modulated in amplitudes of low-pass filtered envelopes obtained from natural sounds. We found that the perception of crossmodal correspondence emerged from the number of amplitude prominences in each stimulus rather than from temporal variations. Therefore, we propose saliency as the supramodal trade coin of temporal modulations.

neuroscience↗

bioRxiv2023

Multiple genetic variants at the SLC30A8 locus affect a local super-enhancer cluster to influence pancreatic β-cell survival and function

Variants at the SLC30A8 locus are associated with type 2 diabetes (T2D) risk. The lead variant, rs13266634, encodes an amino acid change, Arg325Trp (R325W), at the C-terminus of the secretory granule-enriched zinc transporter, ZnT8. Although this protein-coding variant was previously thought to be the sole driver of T2D risk at this locus, recent studies have provided evidence for lowered expression of SLC30A8 mRNA in protective allele carriers. In the present study, combined allele-specific expression (cASE) analysis in human islets revealed multiple variants that influence SLC30A8 expression. Epigenomic mapping identified an islet-selective enhancer cluster at the SLC30A8 locus, hosting multiple T2D risk and cASE associations, which is spatially associated with the SLC30A8 promoter and additional neighbouring genes. Deletions of variant-bearing enhancer regions using CRISPR-Cas9 in human-derived EndoC-{beta}H3 cells lowered the expression of SLC30A8 and several neighbouring genes, and improved insulin secretion. Whilst down-regulation of SLC30A8 had no effect on beta cell survival, loss of UTP23, RAD21 or MED30 markedly reduced cell viability. Although eQTL or cASE analyses in human islets did not support the association between these additional genes and diabetes risk, the transcriptional regulator JQ1 lowered the expression of multiple genes at the SLC30A8 locus and enhanced stimulated insulin secretion.

cell biology↗

bioRxiv2021

Genetic regulation of RNA splicing in human pancreatic islets

Genetic variants that influence transcriptional regulation in pancreatic islets play a major role in the susceptibility to type 2 diabetes (T2D). For many susceptibility loci, however, the mechanisms are unknown. We examined splicing QTLs (sQTLs) in islets from 399 donors and observed that genetic variation has a widespread influence on splicing of genes with important functions in islet biology. In parallel, we profiled expression QTLs, and used transcriptome-wide association and co-localization studies to assign islet sQTLs or eQTLs to T2D susceptibility signals that lacked candidate effector genes. We found novel T2D associations, including an sQTL that creates a nonsense isoform in ERO1B, a regulator of ER-stress and proinsulin biosynthesis. The expanded list of T2D risk effectors revealed overrepresented pathways, including regulators of G-protein-mediated cAMP production. This data exposes an underappreciated layer of genetic regulation in pancreatic islets, and nominates molecular mediators of T2D susceptibility.

genetics↗

bioRxiv2021

TIGER: The gene expression regulatory variation landscape of human pancreatic islets

GWAS have identified more than 700 genetic signals associated with type 2 diabetes (T2D). To gain insight into the underlying molecular mechanisms, we created the Translational human pancreatic Islet Genotype tissue-Expression Resource (TIGER), aggregating >500 human islet RNA-seq and genotyping datasets. We imputed genotypes using 4 reference panels and meta-analyzed cohorts to improve coverage of expression quantitative trait loci (eQTL) and developed a method to combine allele-specific expression across samples (cASE). We identified >1 million islet eQTLs (56% novel), of which 53 colocalize with T2D signals (60% novel). Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identified 8 novel cASE colocalizations, among which an SLC30A8 T2D associated variant. We make all the data available through the open-access TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translate this into therapeutic insight and precision medicine for T2D.

bioinformatics↗

bioRxiv2020

Neuronal Correlates of the Perceptual Invariance of Words and Other Sounds in the Supplementary Motor Area of Macaques

The supplementary motor area (SMA) of the brain is critical for integrating memory and sensory signals into perceptual decisions. For example, in macaques, SMA activity correlates with decisions based on the comparison of sounds.1 In humans, functional MRI shows SMA activation during the invariant recognition of words pronounced by different speakers.2 Nevertheless, the neuronal correlates of perceptual invariance are unknown. Here we show that the SMA of macaques associates novel sounds with behaviors triggered by similar learned categories when recognizing sounds such as words. Notably, the neuronal activity at single and population levels correlates with the monkeys behaviors (e.g. hits and false alarms). Our results demonstrate that invariant recognitions of complex sounds involve premotor computations in areas other than the temporal and parietal speech areas. Therefore, we propose that perceptual invariance depends on motor predictions and not only sensory representations. We anticipate that studies on speech will observe sensory-motor transformations of acoustic information into motor skills.

neuroscience↗

bioRxiv2020

Auditory Decisions in the Supplementary Motor Area

In human speech and communication across various species, recognizing and categorizing sounds is fundamental for the selection of appropriate behaviors. But how does the brain decide which action to perform based on sounds? We explored whether the premotor supplementary motor area (SMA), responsible for linking sensory information to motor programs, also accounts for auditory-driven decision making. To this end, we trained two rhesus monkeys to discriminate between numerous naturalistic sounds and words learned as target (T) or non-target (nT) categories. We demonstrated that the neural population is organized differently during the auditory and the movement periods of the task, implying that it is performing different computations in each period. We found that SMA neurons perform acoustic-decision-related computations that transition from auditory to movement representations in this task. Our results suggest that the SMA integrates sensory information while listening to auditory stimuli in order to form categorical signals that drive behavior.

neuroscience↗

bioRxiv2019

Invariant recognition of words and naturalistic sounds in non-human primates

The ability to invariably identify spoken words and other naturalistic sounds in different temporal modulations and timbres requires perceptual tolerance to numerous acoustic variations. However, the mechanisms by which auditory information is perceived to be invariant are poorly understood, and no study has explicitly tested the perceptual constancy skills of nonhuman primates. We investigated the ability of two trained rhesus monkeys to learn and then recognize multiple sounds that included multisyllabic words. Importantly, we tested their ability to group unexperienced sounds into corresponding categories. We found that the monkeys adequately categorized sounds whose formants were at close Euclidean distance to the learned sounds. Our results indicate that macaques can attend and memorize complex sounds such as words. This ability was not studied or reported before and can be used to study the neuronal mechanisms underlying auditory perception.

neuroscience↗

bioRxiv2018

Human pancreatic islet 3D chromatin architecture provides insights into the genetics of type 2 diabetes

Genetic studies promise to provide insight into the molecular mechanisms underlying type 2 diabetes (T2D). Variants associated with T2D are often located in tissue-specific enhancer regions (enhancer clusters, stretch enhancers or super-enhancers). So far, such domains have been defined through clustering of enhancers in linear genome maps rather than in 3D-space. Furthermore, their target genes are generally unknown. We have now created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated enhancers with their target genes, often located hundreds of kilobases away. It further revealed sets of islet enhancers, super-enhancers and active promoters that form 3D higher-order hubs, some of which show coordinated glucose-dependent activity. Hub genetic variants impact the heritability of insulin secretion, and help identify individuals in whom genetic variation of islet function is important for T2D. Human islet 3D chromatin architecture thus provides a framework for interpretation of T2D GWAS signals.

genomics↗

bioRxiv2017

A Comprehensive Reanalysis Of Publicly Available GWAS Datasets Reveals An X Chromosome Rare Regulatory Variant Associated With High Risk For Type 2 Diabetes.

The reanalysis of publicly available GWAS data represents a powerful and cost-effective opportunity to gain insights into the genetics and pathophysiology of complex diseases. We demonstrate this by gathering and reanalyzing public type 2 diabetes (T2D) GWAS data for 70,127 subjects, using an innovative imputation and association strategy based on multiple reference panels (1000G and UK10K). This approach led us replicate and fine map 50 known T2D loci, and identify seven novel associated regions: five driven by common variants in or near LYPLAL1, NEUROG3, CAMKK2, ABO and GIP genes; one by a low frequency variant near EHMT2; and one driven by a rare variant in chromosome Xq23, associated with a 2.7-fold increased risk for T2D in males, and located within an active enhancer associated with the expression of Angiotensin II Receptor type 2 gene (AGTR2), a known modulator of insulin sensitivity. We further show that the risk T allele reduces binding of a nuclear protein, resulting in increased enhancer activity in muscle cells. Beyond providing novel insights into the genetics and pathophysiology of T2D, these results also underscore the value of reanalyzing publicly available data using novel analytical approaches.

genetics↗

bioRxiv2016

Human pancreatic β cell lncRNAs control cell-specific regulatory networks

Recent studies have uncovered thousands of long non-coding RNAs (IncRNAs) in human pancreatic {beta} cells. {beta} cell lncRNAs are often cell type-specific, and exhibit dynamic regulation during differentiation or upon changing glucose concentrations. Although these features hint at a role of lncRNAs in {beta} cell gene regulation and diabetes, the function of {beta} cell lncRNAs remains largely unknown. In this study, we investigated the function of {beta} cell-specific lncRNAs and transcription factors using transcript knockdowns and co-expression network analysis. This revealed lncRNAs that function in concert with transcription factors to regulate {beta} cell-specific transcriptional networks. We further demonstrate that lncRNA PLUTO affects local three-dimensional chromatin structure and transcription of PDX1, encoding a key {beta} cell transcription factor, and that both PLUTO and PDX1 are downregulated in islets from donors with type 2 diabetes or impaired glucose tolerance. These results implicate lncRNAs in the regulation of {beta} cell-specific transcription factor networks.

genomics↗