Biology subjects

Sridharan, D.

Publications and source records attributed to Sridharan, D..

11 recordsLinked to original sources

bioRxiv2026

Oxidative Stress-Induced Microglial CD22 Upregulation Impairs Phagocytosis and Exacerbates Huntingtons Disease

BackgroundHuntingtons disease (HD) is a neurodegenerative disorder caused by an abnormal polyglutamine expansion in mutant huntingtin (mHTT) and is characterized by movement dysfunction and neuronal loss. Siglecs, a family of sialic acid-binding proteins, are expressed on brain microglia and implicated in Alzheimers disease. Sialic acids are abundant in mammalian brains and cap the termini of the glycocalyx of various brain cells. Alterations in sialoglycans or Siglecs may affect interactions between microglia and other brain cells. However, the roles of Siglecs in HD have not been investigated. MethodsWe profiled Siglecs in postmortem caudate nucleus samples from HD subjects and in a mouse model of HD (R6/2) using RT-qPCR and mass cytometry analyses. CD22 functions in microglia were evaluated using a microglial cell line (BV2) and primary microglia. Native ligands for microglial CD22 were assessed via glycomic profiling and flow cytometry. Regulation of CD22 ligands in astrocytes was investigated in an astrocytic cell line (C8-D1A) and primary astrocytes. The role of CD22 in HD was examined by genetic deletion in HD mice, followed by behavioral analyses and pathological evaluation with immunofluorescence staining and MRI. ResultsUpregulation of CD22 in microglia, observed in the brains of patients and mice with HD, impairs microglial phagocytosis via ITIM-ITAM signaling crosstalk. This CD22 upregulation was driven by chronic oxidative stress, as antioxidant treatment (N-acetylcysteine) markedly normalized CD22 levels. CD22 ligand, 2,6-sialylated-6-sulfo-LacNAc, primarily expressed by astrocytes, was significantly reduced in HD mice. mHTT, but not wild-type HTT, suppressed ligand synthesis in astrocytes under elevated oxidative stress, allowing more CD22 on the microglial surface to inhibit phagocytosis. Treatment with a neutralizing antibody or ligand-enriched extracellular vesicles depleted surface CD22 and restored the phagocytic function of microglia. Genetic deletion of CD22 in HD mice improved rotarod performance, reduced mHTT inclusion burden, increased Darpp32 expression, and alleviated brain atrophy, supporting the concept that CD22-mediated inhibition of microglial phagocytosis contributes to HD pathogenesis. ConclusionOur findings suggest that CD22 acts as a checkpoint-like regulator that restrains microglial phagocytosis and contributes to HD progression when astrocyte-microglia communication is impaired, thereby highlighting CD22 as a promising therapeutic target.

neuroscience↗

bioRxiv2024

Neural mechanisms of attention, not expectation, govern spatial selection by probabilistic cueing

Spatial probabilistic "Posner" cueing is widely employed in studies of endogenous spatial attention. Such cueing guides attention by providing prior knowledge about the likely spatial location of task-relevant events. Yet, it has been compellingly argued that such spatial priors also elicit expectation effects, rendering Posner cueing unsuitable for measuring attentional effects in isolation. We address this debate by combining signal detection theory models of behavior with concurrent electrophysiological recordings, and directly compare Posner cueing effects with those of attention and expectation cueing. Participants performed two tasks: a dual cueing task, with orthogonal relevance (attention) and probability (expectation) cues, as well as a Posner cueing task. Relevance and probability cueing independently modulated distinct behavioral parameters - perceptual sensitivity and decisional criterion, respectively - whereas Posner cueing modulated both sensitivity and criterion. However, only sensitivity modulations by Posner cueing were correlated with those of relevance cueing. Criterion modulations by Posner cueing were uncorrelated with those of probability cueing. Both Posner and relevance cueing, but not probability cueing, modulated various neural markers of spatial attention, including steady-state visually evoked potential (SSVEP) amplitude and alpha-band (8-12 Hz) oscillation power. Representational similarity analysis and cue-label prediction with deep convolutional neural networks revealed dissociable underpinnings of relevance and probability cueing, and identified Posner cueings neural representations with those of relevance cueing. Our results address a long-standing debate in the attention literature and clearly demonstrate that spatial selection by probabilistic cueing is governed by neural mechanisms of attention, not expectation. Significance StatementHow does our brain select relevant information for accomplishing task goals? "Posner cueing" is a popular choice for studying brain mechanisms of goal-driven attention in the lab. Posner cues guide attention by providing advance information about the likely location of task-relevant events. Yet, Posner cueing has been criticized because it engages brain mechanisms not only of attention but of event expectation, as well. We address this critique by employing state-of-the-art neural decoding approaches, including deep convolutional neural networks, and show that behavioral and neural underpinnings of Posner cueing closely match those of attention, not expectation. The results address a long-standing debate in the attention literature and validate Posner cueing as a reliable method for measuring attentions effects in the brain.

neuroscience↗

bioRxiv2024

Distinct neural bases of subcomponents of the attentional blink

The attentional blink reflects a ubiquitous bottleneck with selecting and processing the second of two targets that occur in close temporal proximity. An extensive literature has examined the attention blink as a unitary phenomenon. As a result, which specific component of attention - perceptual sensitivity, choice bias or both - are compromised during the attentional blink, and their respective neural bases, remains unknown. Here, we address this question with a multialternative task and novel signal detection model, which decouples sensitivity from bias effects. We find that the attentional blink impairs specifically one component of attention - sensitivity - while leaving the other component - bias - unaffected. Distinct neural markers of the attentional blink mapped on to distinct subcomponents of the sensitivity deficits. Parieto- occipital N2p and P3 potential amplitudes characterized target detection deficits whereas long- range high-beta band (20-30 Hz) coherence between frontoparietal electrodes signalled target discrimination deficits. We synthesized these results with representational geometry analysis. The analysis revealed that detection and discrimination deficits were encoded along separable neural dimensions, whose configural distances robustly correlated with the neural markers of each. Overall, these findings provide detailed insights into the subcomponents of the attentional blink, and reveal dissociable neural bases underlying its detection and discrimination bottlenecks. Lay summaryIn daily life, our attention switches rapidly between different objects. For example, when driving, we may shift focus from a billboard on the roadside to a pedestrian in front, in quick succession. Yet, our ability to process the second object is severely compromised especially when it appears soon after the first: an impairment called the "attentional blink". In previous work, the attentional blink has been studied essentially as a "monolithic" (indivisible) phenomenon. We design a behavioral model to divide the attentional blink into sub- components and show that the blink affects only one specific component (sensitivity). We also identify key neural markers for deficits associated with this component. Our findings may aid in understanding the neural origins of attention deficit disorders.

neuroscience↗

bioRxiv2023

Distractors induce space-specific neural biases in visual working memory

Information held in working memory (WM) is remarkably resilient to distraction. Yet, perceptual distractors that share mnemonic features can impact WM profoundly; the neural basis of this phenomenon remains unclear. With multivariate decoding of human electroencephalography recordings, we investigate how delay-period perceptual distractors bias WM. Participants memorized the orientations of cued and uncued grating memoranda that appeared in opposite hemifields. A grating distractor, flashed during the delay period, produces space-specific biases: memorized features are attracted towards or repelled away from the distractors orientation depending, respectively, on when the distractor appeared in the same hemifield as the memorandum, or opposite to it. Neural prioritization in WM by cueing, and stronger memorandum maintenance mitigate this bias, whereas stronger distractor encoding enhances it. Lastly, a ring-attractor model with cross-hemifield inhibition mechanistically explains the origins of these spatially-antagonistic biases. Our results reveal how lateralized sensory buffers critically enable perceptual distractors to bias visual WM. Lay SummaryWorking memory (WM) - the ability to momentarily store important items - is remarkably robust to distraction. Yet, when a salient object with features resembling the memorized item ("perceptual distractor") appears in the environment, it can alter WM appreciably. What neural mechanisms render WM resilient to distraction, and how can perceptual distractors affect it so profoundly? We address this question by presenting a salient distractor, at unpredictable times, during the WM delay-period. Surprisingly, the distractors bias on WM depends on its proximity to the memorandums original location. With state-of-the-art neural decoding and computational modeling, we identify mechanisms that mediate these space-specific distractor effects. The findings advance our understanding of WMs resilience to distraction and may inform cognitive therapies for treating WM deficits.

neuroscience↗

bioRxiv2023

A surprising lack of presaccadic benefits during visual change detection

Even before the eyes move, visual sensitivity improves at the target of the planned eye movement. Yet, it is unknown if such "presaccadic" benefits are merely sensory, or also influence decisional processes. We teased apart these contributions with signal detection theory, and discovered a surprising absence of presaccadic benefits in visual change detection tasks. Participants planned and executed saccades while concurrently detecting and localizing either orientation or contrast changes. Spatial choice bias reliably improved presaccadically but, surprisingly, without a concomitant increase in perceptual sensitivity. Additional investigation with an orientation estimation task, and a Bayesian "variable precision" model, revealed that sensory precision increased at the saccade target, but only for the most recent of two successive stimuli. Moreover, the recent stimulus perceptually biased feature estimates of the prior stimulus, rendering accurate change detection even more challenging. Our results uncover novel perceptual and decisional mechanisms that mediate presaccadic change detection. Lay SummaryPlanning a rapid eye movement (saccade) changes how we perceive our visual world. Even before we move the eyes visual sensitivity improves at the impending target of eye movements, a phenomenon termed "presaccadic attention". We report a surprising lack of such presaccadic attention benefits in a common, everyday setting: change detection. In fact, presaccadic attention renders change detection more challenging by biasing percepts toward the most recent of successive stimuli at the saccade target location. With a Bayesian model, we show how such perceptual and choice biases induced by eye movement planning affect change detection behavior. Our findings may have critical implications for real-world scenarios, like driving, that involve rapid gaze shifts in dynamically changing environments.

neuroscience↗

bioRxiv2021

Inhibition of BKCa channels protects neonatal hearts against myocardial ischemia and reperfusion injury

BKCa channels are large-conductance calcium and voltage-activated potassium channels that are heterogeneously expressed in a wide array of cells. Activation of BKCa channels present in mitochondria of adult ventricular cardiomyocytes is implicated in cardioprotection against ischemia-reperfusion (IR) injury. However, the BKCa channels activity has never been detected in the plasma membrane of adult ventricular cardiomyocytes. In this study, we report the presence of the BKCa channel in the plasma membrane and mitochondria of neonatal murine and rodent cardiomyocytes which protects the heart on inhibition but not activation. Furthermore, K+ currents measured in neonatal cardiomyocyte (NCM) was sensitive to iberiotoxin (IbTx), suggesting the presence of BKCa channels in the plasma membrane. Neonatal hearts subjected to IR when post-conditioned with NS1619 during reoxygenation increased the myocardial infarction whereas IbTx reduced the infarct size. In agreement, isolated NCM also presented increased apoptosis on treatment with NS1619 during hypoxia and reoxygenation, whereas IbTx reduced TUNEL positive cells. In NCMs, activation of BKCa channels increased the intracellular reactive oxygen species post HR injury. Electrophysiological characterization of NCMs indicated that NS1619 increased the beat period, field, and action potential duration, and decreased the conduction velocity and spike amplitude. In contrast, IbTx had no impact on the electrophysiological properties of NCMs. Taken together, our data established that inhibition of plasma membrane BKCa channels in the NCM protects neonatal heart/cardiomyocytes from IR injury. Furthermore, the functional disparity observed towards the cardioprotective activity of BKCa channels in adults compared to neonatal heart could be attributed to their differential localization.

physiology↗

bioRxiv2019

Decoding task-specific cognitive states with slow, directed functional networks in the human brain

Flexible functional interactions among brain regions mediate critical cognitive functions. Such interactions can be measured from functional magnetic resonance imaging (fMRI) data with either instantaneous (zero-lag) or lag-based (time-lagged) functional connectivity; only the latter approach permits inferring directed functional interactions. Yet, the fMRI hemodynamic response is slow, and sampled at a timescale (seconds) several orders of magnitude slower than the underlying neural dynamics (milliseconds). It is, therefore, widely held that lag-based fMRI functional connectivity, measured with approaches like as Granger-Geweke causality (GC), provides spurious and unreliable estimates of underlying neural interactions. Experimental verification of this claim has proven challenging because neural ground truth connectivity is often unavailable concurrently with fMRI recordings. We address this challenge by combining machine learning with GC functional connectivity estimation. We estimated instantaneous and lag-based GC functional connectivity networks using fMRI data from 1000 participants, drawn from the Human Connectome Project database. A linear classifier, trained on either instantaneous or lag-based GC, reliably discriminated among seven different task and resting brain states, with over 80% cross-validation accuracy. With network simulations, we demonstrate that instantaneous and lag-based GC exploited interactions at fast and slow timescales, respectively, to achieve robust classification. With human fMRI data, instantaneous and lag-based GC identified distinct, cognitive core networks. Finally, variations in GC connectivity explained inter-individual variations in a variety of cognitive scores. Our findings show that instantaneous and lag-based methods reveal complementary aspects of functional connectivity in the brain, and suggest that slow, directed functional interactions, estimated with fMRI, provide robust markers of behaviorally relevant cognitive states.\n\nAuthor SummaryFunctional MRI (fMRI) is a leading, non-invasive technique for mapping networks in the human brain. Yet, fMRI signals are noisy and sluggish, and fMRI scans are acquired at a timescale of seconds, considerably slower than the timescale of neural spiking (milliseconds). Can fMRI, then, be used to infer dynamic processes in the brain such as the direction of information flow among brain networks? We sought to answer this question by applying machine learning to fMRI scans acquired from 1000 participants in the Human Connectome Project (HCP) database. We show that directed brain networks, estimated with a technique known as Granger-Geweke Causality (GC), accurately predicts individual subjects task-specific cognitive states inside the scanner, and also explains variations in a variety of behavioral scores across individuals. We propose that directed functional connectivity, as estimated with fMRI-GC, is relevant for understanding human cognitive function.

neuroscience↗

bioRxiv2019

Neurally-constrained modeling of human gaze strategies in a change blindness task

Visual attention enables us to engage selectively with the most important events in the world around us. Yet, sometimes, we fail to notice salient events. \"Change blindness\" - the surprising inability to detect and identify salient changes that occur in flashing visual images - enables measuring such failures in a laboratory setting. We discovered that human participants (n=39) varied widely (by two-fold) in their ability to detect changes when tested on a laboratory change blindness task. To understand the reasons for these differences in change detection abilities, we characterized eye-movement patterns and gaze strategies as participants scanned these images. Surprisingly, we found no systematic differences between scan paths, fixation maps or saccade patterns between participants who were successful at detecting changes, versus those who were not. Yet, two low-level gaze metrics - the mean fixation duration and the variance of saccade amplitudes - systematically predicted change detection success. To explain the mechanism by which these gaze metrics could influence performance, we developed a neurally constrained model, based on the Bayesian framework of sequential probability ratio testing (SPRT), which simulated gaze strategies of successful and unsuccessful observers. The models ability to detect changes varied systematically with mean fixation duration and saccade amplitude variance, closely mimicking observations in the human data. Moreover, the models success rates correlated robustly with human observers success rates, across images. Our model explains putative human attention mechanisms during change blindness tasks and provides key insights into effective strategies for shifting gaze and attention for artificial agents navigating dynamic, crowded environments.\n\nAuthor SummaryOur brain has the remarkable capacity to pay attention, selectively, to the most important events in the world around us. Yet, sometimes, we fail spectacularly to notice even the most salient events. We tested this phenomenon in the laboratory with a change-blindness experiment, by having participants freely scan and detect changes across discontinuous image pairs. Participants varied widely in their ability to detect these changes. Surprisingly, their success correlated with differences in low-level gaze metrics. A Bayesian model of eye movements, which incorporated neural constraints on stimulus encoding, could explain the reason for these differences, and closely mimicked human performance in this change blindness task. The models gaze strategies provide relevant insights for artificial, neuromorphic agents navigating dynamic, crowded environments.

neuroscience↗

bioRxiv2018

Exogenous attention facilitates performance through dissociable sensitivity and bias mechanisms

Selective attention enables prioritizing the most important information for differential sensory processing and decision-making. Here, we address an active debate regarding whether attention reflects a unitary phenomenon or involves the operation of dissociable sensory enhancement (perceptual sensitivity) and decisional gating (choice bias) processes. We developed a multialternative task in which participants detected and localized orientation changes in gratings at one of four spatial locations. Exogenous attention cues (high contrast flashes) preceded or followed the change events in close temporal proximity. Analysis of participants behavior with a multidimensional signal detection model revealed markedly distinct effects of exogenous cueing on perceptual sensitivity and choice bias. Whereas sensitivity enhancement was localized to the stimulus proximal to the exogenous cue, bias enhancement occurred even for distal stimuli in the cued hemifield. Modulations of sensitivity and bias were uncorrelated at both cued and uncued locations. Finally, exogenous cueing produced reaction time benefits only at the cued location and costs only at locations contralateral to the cue. These disparate effects of exogenous cueing on sensitivity, bias and reaction times could be parsimoniously explained within the framework of a diffusion-decision model, in which the drift rate was determined by a linear combination of sensitivity and bias at each location. Exogenous cueing effects on sensitivity and bias differed systematically from previously reported effects of endogenous cueing. We propose that the search for shared neural substrates of exogenous and endogenous attention would benefit from investigating neural correlates of their component sensory and decisional mechanisms.\n\nSignificance statementWhen we voluntarily direct attention \"endogenously\", we are able to better perceive stimuli at the attended location (sensitivity), and to prioritize information from that location for guiding behavioral decisions (bias). But when a salient stimulus, such as a flash of lightning, captures our attention \"exogenously\", does it also produce these same effects? To answer this question, we designed a multiple alternative task in which task events occurred in close conjunction with salient exogenous cues (high contrast flashes). We discovered that exogenous attention enhanced both sensitivity and bias for cued stimuli, but each of these changes followed distinct spatial patterns across locations. Our results provide novel insights into component processes of exogenous attention and motivate the search for their neural correlates.

neuroscience↗

bioRxiv2018

The Drosophila Cortactin Binding Protein 2 homolog, Nausicaa, regulates lamellipodial actin dynamics in a Cortactin-dependent manner.

Drosophila CG10915 is an uncharacterized protein coding gene with sequence similarity to human Cortactin Binding Protein 2 (CTTNBP2) and Cortactin Binding Protein 2 N-terminal like (CTTNBP2NL). We have named this gene Nausicaa (naus) and characterize it through a combination of quantitative live-cell total internal reflection fluorescence (TIRF) microscopy, electron microscopy, RNAi depletion, and genetics. We found that Naus co-localizes with F-actin and Cortactin in the lamellipodia of Drosophila S2R+ and D25c2 cells and this localization is lost following Cortactin or Arp2/3 depletion or by mutations that disrupt a conserved proline patch found in its mammalian homologs. Using Permeabilization Activated Reduction in Fluorescence (PARF) and Fluorescence Recovery after Photo-bleaching (FRAP), we find that depletion of Cortactin alters Naus dynamics leading to a decrease in its half-life. Furthermore, we discovered that Naus depletion in S2R+ cells led to a decrease in actin retrograde flow and a lamellipodia characterized by long, unbranched filaments. We demonstrate that these alterations to the dynamics and underlying actin architecture also affect D25c2 cell migration and decrease arborization in Drosophila neurons. We present the novel hypothesis that Naus functions to slow Cortactins disassociation from Arp2/3 nucleated branch junctions, thereby increasing both branch nucleation and junction stability.

cell biology↗

bioRxiv2017

Sensory and decisional components of endogenous attention are dissociable.

Endogenously cueing a stimulus for attention enhances sensory processing of the attended stimulus, and efficiently selects information from the attended stimulus for guiding behavioral decisions. Yet, it is unknown if these sensory and decisional components of endogenous attention are under the control of common, overlapping or distinct mechanisms. Here, we tested human observers in a multi-alternative visuospatial attention task with probabilistic spatial cues, whose predictive validity varied across spatial locations. Observers behavioral choices were analyzed with a multidimensional signal detection model, derived from Bayesian decision theory. The model effectively decoupled attentions effects on perceptual sensitivity from those on decisional thresholds (bias), and revealed striking dissociations between them. Sensitivity was highest at the cued location, and not significantly different among uncued locations, suggesting a spotlight-like allocation of sensory resources at the cued location. On the other hand, bias varied systematically with endogenous cue validity, suggesting a graded distribution of decision thresholds across all locations. Cueing-induced modulations of sensitivity and bias were uncorrelated within and across subjects. Finally, bias selectively correlated with key measures of decision-making: reaction times were strongly correlated with bias, cueing-induced benefits in reaction times were correlated with bias changes independently of sensitivity changes, and subjects who exhibited higher bias, rather than higher sensitivity, toward the cued location produced more optimal behavioral decisions. Our model and findings demonstrate that endogenous cueing of attention does not engage a unitary selection mechanism, but rather involves the operation of dissociable sensory enhancement and decisional selection processes.\n\nSignificance statementThe capacity for selective attention allows us to engage efficiently with the most important objects in the world around us. Attention affects the way we perceive important stimuli and also affects how we make behavioral decisions about these stimuli. In this study, we test human observers on a multiple alternative attention task and show that attentions effects on perceptual processing and decision-making can be dissociated. Specifically, attentions sensory effects alone are in line with the conventional notion of an attentional \"spotlight\". These insights are obtained with a novel Bayesian decision model, which we propose as a powerful tool for teasing apart component processes of cognitive phenomena, and could aid the search for the neural correlates of these phenomena.

neuroscience↗