Biology subjects

Keliris, G. A.

Publications and source records attributed to Keliris, G. A..

16 recordsLinked to original sources

bioRxiv2025

Direction of motion decoding in mouse V1: Neuron predictive power relates to functional connectivity organization

Variability in single neuron responses presents a challenge in establishing reliable representations of visual stimuli essential for driving behavior. To enhance accuracy, integration of responses from multiple neurons is imperative. This study leverages simultaneous recordings from a large population (tens of hundreds) of neurons, achieved through in vivo mesoscopic 2-photon calcium imaging of the primary visual cortex (V1) in mice, under visual stimulus conditions as well as in resting state (absence of stimulus). The visual stimulus consisted of 16 distinct randomly shuffled directions of motion presented to the mice. We employed mutual information to identify neurons that contain the most significant information about the stimulus direction. As expected, neurons displaying high predictive power (HPP) in stimulus decoding exhibit elevated firing event rates during stimulus presentation. Furthermore, functional connectivity among HPP neurons during visual stimulation is denser and stronger compared to functional connectivity among other visually responsive neurons. Functional connections among HPP neurons appear to form independently of distance, suggesting a distributed yet highly coordinated network. In contrast, HPP neuronal activity and functional connectivity differed significantly at resting state. Specifically, during the resting state, HPP neurons exhibited lower event rates and functional connectivity structure that was not significantly different from that of other visually responsive neurons. This suggests that HPP neurons are less susceptible to being driven simultaneously by internal brain states in the absence of a stimulus. Finally, the tuning properties of HPP neurons were unexpectedly diverse: while some were sharply tuned, others conveyed a similar amount of mutual information, despite exhibiting much weaker tuning. This study sheds light on the organization of neuronal ensembles important for decoding visual motion direction in mouse area V1, contributing to the understanding of information processing in mouse visual cortex.

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bioRxiv2024

Early altered directionality of resting brain network state transitions in the TgF344-AD rat model of Alzheimer's disease

Alzheimers disease (AD) is a progressive neurodegenerative disease resulting in memory loss and cognitive decline. Synaptic dysfunction is an early hallmark of the disease whose effects on whole-brain functional architecture can be identified using resting-state functional MRI (rsfMRI). Insights into mechanisms of early, whole-brain network alterations can help our understanding of the functional impact of ADs pathophysiology. Here, we obtained rsfMRI data in the TgF344-AD rat model at the pre- and early-plaque stages. This model recapitulates the major pathological and behavioural hallmarks of AD. We used co-activation pattern (CAP) analysis to investigate if and how the dynamic organization of intrinsic brain functional networks states, undetectable by earlier methods, is altered at these early stages. We identified and characterized six intrinsic brain states as CAPs, their spatial and temporal features, and the transitions between the different states. At the pre-plaque stage, the TgF344-AD rats showed reduced co-activation of hub regions in the CAPs corresponding to the default mode-like and lateral cortical network. Default mode-like network activity segregated into two distinct brain states, with one state characterised by high co-activation of the basal forebrain. This basal forebrain co-activation was reduced in TgF344-AD animals mainly at the pre-plaque stage. Brain state transition probabilities were altered at the pre-plaque stage between states involving the default mode-like network, lateral cortical network, and basal forebrain regions. Additionally, while the directionality preference in the network-state transitions observed in the wild-type animals at the pre-plaque stage had diminished at the early-plaque stage, TgF344-AD animals continued to show directionality preference at both stages. Our study enhances the understanding of intrinsic brain state dynamics and how they are impacted at the early stages of AD, providing a nuanced characterization of the early, functional impact of the diseases neurodegenerative process.

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bioRxiv2022

Cholinergic modulation supports DMN suppression during resting state

Brain activity during the resting state is widely used to examine brain organization, cognition and alterations in disease states. While it is known that neuromodulation and the state of alertness impact resting-state activity, neural mechanisms behind such modulation of resting-state activity are unknown. In this work, we used a computational model to demonstrate that change in excitability and recurrent connections, due to cholinergic modulation, impacts resting-state activity. The results of such modulation in the model match closely with experimental work on direct cholinergic modulation of Default Mode Network (DMN) in rodents. We further extended our study to the human connectome derived from diffusion-weighted MRI. In human resting-state simulations, an increase in cholinergic input resulted in a brain-wide reduction of functional connectivity. Furthermore, selective cholinergic modulation of DMN closely captured experimentally observed transitions between the baseline resting state and states with suppressed DMN fluctuations associated with attention to external tasks. Our study thus provides insight into potential neural mechanisms for the effects of cholinergic neuromodulation on resting-state activity and its dynamics.

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bioRxiv2022

Longitudinal investigation of changes in resting-state co-activation patterns and their predictive ability in the zQ175 DN mouse model of Huntington's disease

Huntingtons disease (HD) is a neurodegenerative disorder caused by expanded ([≥]40) glutamine-encoding CAG repeats in the huntingtin gene, which leads to dysfunction and death of predominantly striatal and cortical neurons. While the genetic profile and behavioural signs of the disease are better known, changes in the functional architecture of the brain, especially before the behavioural symptoms become apparent, are not fully and consistently characterized. In this study, we sought markers at pre, early and late manifest states of phenotypic progression in the heterozygous (HET) zQ175 delta-neo (DN) mouse model, using resting-state functional magnetic resonance imaging (RS-fMRI). This mouse model shows molecular, cellular and circuitry alterations that resemble those seen in HD in humans. Specifically, we investigated, longitudinally, changes in co-activation patterns (CAPs) that are the transient states of brain activity constituting the resting-state networks (RSNs). Most robust changes in the temporal properties of CAPs occurred at the late manifest state; the durations of two anti-correlated CAPs, characterized by simultaneous co-activation of default-mode like network (DMLN) and co-deactivation of lateral-cortical network (LCN) and vice-versa, were reduced in the zQ175 DN HET animals compared to the wild-type mice. Changes in the spatial properties, measured in terms of activation levels of different brain regions, during CAPs were found at all three states and became progressively more pronounced at the manifest states. We then assessed the cross-validated predictive power of CAP metrics to distinguish HET animals from controls. Spatial properties of CAPs performed significantly better than the chance level at all three states with 80% classification accuracy at the early and late manifest states.

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bioRxiv2022

Selective cholinergic stimulation of the medial septum-diagonal band of Broca via DREADDs improves spatial learning in healthy rats

The septohippocampal pathway plays an important role in learning and memory. It projects from the medial septum-vertical limb of the diagonal band of Broca (MSDB) to the hippocampus and provides the latter with its main cholinergic innervation. To assess the importance of cholinergic selectivity and timing of MSDB stimulation in modulating learning and memory, we directly compared the effects of several MSDB stimulation strategies in healthy rats. We evaluated the effects of DREADD-mediated selective cholinergic neuronal MSDB stimulation and nonselective neuronal MSDB stimulation on spatial learning and memory in the appetitive radial arm maze and on resting-state brain networks using resting-state functional MRI. DREADDs were activated with the novel DREADD agonist J60. Selective cholinergic MSDB stimulation during - but not after - radial arm maze training improved spatial learning compared with J60-treated sham rats and had no effect on working memory or reversal learning. J60-treated sham rats had a worse working memory than saline-treated sham rats during the reversal phase of the radial arm maze task, suggesting an adverse effect of chronic use of J60. Nonselective MSDB stimulation during training resulted in a loss of appetite and exclusion from the radial arm maze training. Acute selective cholinergic and nonselective MSDB stimulation induced decreased functional connectivity (FC) in the default mode-like network. In addition, acute nonselective MSDB stimulation resulted in increased intrahippocampal FC, while selective cholinergic MSDB stimulation led to globally increased FC with the nucleus accumbens. While the combined effect of radial arm maze learning and the necessary chronic food restriction with or without chronic MSDB stimulation had no observable effect on resting-state networks, chronic food restriction alone globally increased FC in the brain.

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bioRxiv2022

Early Electrophysiological Aberrations in the Hippocampus of the TgF344-AD Rat Model as a Potential Biomarker for Alzheimer's Disease Prognosis

The hippocampus is thought to guide navigation and has an essential contribution to learning and memory. Hippocampus is one of the brain regions impaired in Alzheimers disease (AD), a neurodegenerative disease with progressive memory impairments and cognitive decline. Although successful treatments for AD are still not available, developing new strategies to detect AD at early stages before clinical manifestation is crucial for timely interventions. Here, we investigated in the TgF344-AD rat model the classification of AD-transgenic rats versus Wild-type littermates (WT) from electrophysiological activity recorded in the hippocampus of freely moving subjects at an early, pre-symptomatic stage of the disease (6 months old). To this end, recorded signals were filtered in two separate frequency regimes namely low frequency LFP signals and high frequency spiking activity and passed to machine learning (ML) classifiers to identify the genotype of the rats (TG vs. WT). For the low frequency analysis, we first filtered the signals and extracted the power spectra in different frequency bands known to carry differential information in the hippocampus (delta, theta, slow- and fast-gamma) while for the high frequency analysis, we extracted spike-trains of neurons and calculated different distance metrics between them, including Van Rossum (VR), Inter Spike Interval (ISI), and Event Synchronization (ES). These measures were then used as features for classification with different ML classifiers. We found that both low and high frequency signals were able to classify the rat genotype with a high accuracy with specific signals such as the gamma band power, providing an important fraction of information. In addition, when we combined information from both low and high frequency the classification was boosted indicating that independent information is present across the two bands. The results of this study offer a better insight into how different regions of the hippocampus are affected in earlier stages of AD.

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bioRxiv2022

Dynamics of brain-fluid circulation are altered in the mature-onset Tet-off APP mouse model of amyloidosis

Alzheimers disease (AD), the most common type of dementia, is an incurable brain disorder characterised by the progressive build-up of toxic amyloid-beta (A{beta}) and tau protein aggregates. AD gradually inflicts cognitive functions of an individual such as memory, thinking, reasoning, and language by degrading synaptic function and the integrity of neuronal networks. It has been recently suggested that the efficacy of different brain-clearance systems like the glymphatic system (GS), involved in the removal of toxic waste and homeostatic balance, plays a key role in the pathology of AD. Moreover, the observed coupling between brain fluid movement and global brain activity implies that an alteration of the neuronal network integrity can impact brain fluid circulation throughout the brain and thereby the efficacy of the GS. Here, we investigated the dynamics of brain fluid circulation in Tet-Off APP (AD) mice, a mature-onset model of amyloidosis in which we have recently shown a deterioration of neuronal network integrity by resting-state fMRI. By utilizing dynamic contrast enhanced-MRI and gadoteric acid (Gd-DOTA) T1 contrast agent injected into the cisterna magna, we demonstrated that brain fluid exchange was significantly altered in 14-month-old AD mice compared to control littermates. More specifically, AD mice showed higher Gd-DOTA accumulation in areas proximal to the injection cite and computational modeling of time courses demonstrated significantly lower inflow time constants relative to the controls. Immunohistochemistry demonstrated abundant amyloid plaque burden in the forebrain of the AD group coinciding with extensive astrogliosis and microgliosis. The neuroinflammatory responses were also found in plaque-devoid regions, potentially impacting brain fluid circulation.

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bioRxiv2021

An in-vivo digital atlas of the spatially reliable cerebral vasculature in mice

Cerebral vascular abnormalities can have a large impact on brain function and have been frequently detected as a comorbidity in various neuropathologies. The mouse is the most common pre-clinical animal model used to investigate neuropathologies and thus cerebral vascular atlases of this species are indispensable. In particular, an atlas derived from multiple animals and that can address inter-subject variability is still absent. The current study presents a mouse cerebral vascular atlas developed from MR 2D-TOF angiograms acquired from a relatively high number (N=21) of 12 weeks old male C57BL/6 mice. The vascular atlas we present depicts large arteries, veins and sinuses that are more spatially reliable across animals than smaller vessels. The atlas is available for download and contains multiple datasets: i) a cerebral vascular atlas; ii) a digital segmentation of large vessels (arteries and veins); iii) a high resolution T2 anatomical background aligned to the atlas; iv) a skeletonized vascular atlas; and v) a vascular graph model. We suggest that these components provide a very potent analysis tool for mouse fMRI data and that the atlas can be used as a template for multimodal brain imaging studies. To this end, we also demonstrate an explicit application of the atlas for the investigation of vascular influences in resting-state fMRI.

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bioRxiv2021

Visual Motion Coherence Responses in Human Visual Cortex

1Random dot kinematograms (RDKs) have recently been used to train subjects with cortical scotomas to perform direction of motion discrimination, partially restoring visual motion perception. To study recovery of visual perception, it is important to understand how visual areas in normal subjects and subjects with cortical scotomas respond to RDK stimuli. Studies in normal subjects have shown that Blood Oxygen Level Dependent (BOLD) responses in human area hV5/MT+ increase monotonically with coherence, in general agreement with electrophysiology studies in primates. However, RDK responses in prior studies were obtained while the subject was performing fixation, not a motion discrimination condition. Furthermore, BOLD responses were gauged against a baseline condition of uniform illumination or static dots, potentially decreasing the specificity of responses for the spatial integration of local motion signals (motion coherence). Here we revisit this question starting from a baseline RDK condition of no coherence, thereby isolating the component of BOLD response due specifically to the spatial integration of local motion signals. In agreement with prior studies, we found that responses in area hV5/MT+ of healthy subjects were monotonically increasing when subjects fixated without performing a motion discrimination task. In contrast, when subjects were performing an RDK direction of motion discrimination task, responses in area hV5/MT+ remained flat, changing minimally, if at all, as a function of motion coherence. A similar pattern of responses was seen in area hV5/MT+ of subjects with dense cortical scotomas performing direction of motion discrimination for RDKs presented inside the scotoma. Passive RDK presentation within the scotoma elicited no significant hV5/MT+ responses. These observations shed further light on how visual cortex responses behave as a function of motion coherence, helping to prepare the ground for future studies using these methods to study visual system recovery after injury.

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bioRxiv2020

Resting-state Co-activation Patterns as Accurate Predictors of Alzheimer's Disease in Aged Mice.

Alzheimers disease (AD), a neurodegenerative disorder marked by accumulation of extracellular amyloid-beta (A{beta}) plaques leads to progressive loss of memory and cognitive function. Resting state fMRI (RS-fMRI) studies have provided links between these two observations in terms of disruption of default mode and task positive resting state networks (RSNs). Important insights underlying these disruptions were recently obtained by investigating dynamic fluctuations in RS-fMRI signals in old TG2576 mice (mouse model of amyloidosis) using a set of quasi-periodic patterns (QPP). QPPs represent repeating spatiotemporal patterns of neural activity of predefined temporal length. In this article, we used an alternative methodology of co-activation patterns (CAPs) that represent instantaneous and transient brain configurations that are likely contributors to the emergence of commonly observed resting state networks (RSNs) and QPPs. We followed a recently published approach for obtaining CAPs that divided all time frames, instead of those corresponding to supra-threshold activations of a seed region as done traditionally, to extract CAPs from RS-fMRI recordings in 10 TG2576 female mice and 8 wild type littermates at 18 months of age. Subsequently we matched the CAPs from the two groups using the Hungarian method and compared the temporal (duration, occurrence rate) and the spatial (lateralization of significantly activated voxels) properties of matched CAPs. We found robust differences in the spatial components of matched CAPs. Finally, we used supervised learning to train a classifier using either the temporal or the spatial component of CAPs to distinguish the transgenic mice from the WT. We found that while duration and occurrence rates of all CAPs performed the classification with significantly higher accuracy than the chance-level, blood oxygen level dependent (BOLD) signals of significantly activated voxels from individual CAPs turned out to be a significantly better predictive feature demonstrating a near perfect classification accuracy. Our results demonstrate resting-state co-activation patterns are a promising candidate for a diagnostic, and potentially, prognostic biomarker of Alzheimers disease.

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bioRxiv2019

Increased soluble amyloid-beta causes early aberrant brain network hypersynchronisation in a mature-onset mouse model of amyloidosis

BackgroundAlzheimers disease (AD) is the most common form of dementia in the elderly population. Currently, no effective cure is available for AD. According to the amyloid hypothesis, the accumulation and deposition of the amyloid-beta (A{beta}) peptides plays a key role in AD pathology. Soluble A{beta} (sA{beta}) oligomers were shown to be synaptotoxic and involved in pathological hypersynchronisation of brain resting-state networks in different transgenic developmental-onset mouse models of amyloidosis. However, the impact of protein overexpression during brain postnatal development may cause additional phenotypes unrelated to AD. To address this concern, we investigated sA{beta} effects on functional resting-state networks in transgenic mature-onset amyloidosis Tet-Off APP (TG) mice.\n\nMethodsTG mice and control littermates were raised on doxycycline (DOX) diet from 3d up to 3m of age to suppress transgenic A{beta} production. Thereafter, longitudinal resting-state functional MRI was performed on a 9.4T MR-system starting from week 0 (3m old mice) up to 28w post DOX treatment. Ex vivo immunohistochemistry and ELISA analysis (additional mice cohort) was performed to address the development of amyloid pathology.\n\nResultsFunctional Connectivity (FC) analysis demonstrated early abnormal hypersynchronisation in the TG mice compared to the controls at 8w post DOX treatment. This effect was observed particularly across regions of the default mode-like network, known to be affected in AD. Ex vivo analyses performed at this time point confirmed a 20-fold increase in total sA{beta} levels and the absence of A{beta} plaques in the TG mice compared to the controls. On the contrary at week 28, TG mice showed an overall hypoconnectivity, coinciding with a widespread deposition of A{beta} plaques in the brain.\n\nConclusionsBy preventing developmental influence of APP and/or sA{beta} during brain postnatal development, we demonstrated FC abnormalities driven by sA{beta} synaptotoxicity on resting state neuronal networks in mature-induced TG mice. Thus, the Tet-Off APP mouse model could be a powerful tool while used as a mature-onset model to shed light into amyloidosis mechanisms in AD. Therefore, this inducible APP expression model used in combination with early non-invasive in vivo rsfMRI readout for sA{beta} synaptotoxicity sets the stage for future A{beta} targeting preventative treatment studies.

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bioRxiv2019

Chemogenetic silencing of neurons in the mouse anterior cingulate area modulates neuronal activity and functional connectivity

The anterior cingulate area (ACA) is an integral part of the prefrontal cortex in mice and has been implicated in several cognitive functions. Previous anatomical and functional imaging studies demonstrated that the ACA is highly interconnected with numerous brain regions acting as a hub region in functional networks. However, the importance of the ACA in regulating functional network activity and connectivity remains to be elucidated. Recently developed neuromodulatory techniques, such as Designer Receptors Exclusively Activated by Designer Drugs (DREADDs) allow for precise control of neuronal activity. In this study, we used an inhibitory kappa-opioid receptor DREADDs (KORD) to temporally inhibit neuronal firing in the right ACA of mice and assessed functional network activity and connectivity using non-invasive functional MRI. We demonstrated that KORD-induced inhibition of the right ACA induced blood oxygenation-level dependent (BOLD) signal decreases and increases in connected brain regions throughout of hemispheres. Furthermore, these modulations in neuronal activity were associated with decreased intra- and interhemispheric functional connectivity. These results demonstrate that the combination of the DREADD technology and non-invasive functional imaging methods is a valuable tool for unraveling the underlying mechanisms of network function and dysfunction.

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bioRxiv2019

Resting brain fluctuations are intrinsically coupled to visual response dynamics

How do intrinsic brain dynamics interact with processing of external sensory stimuli? We sought new insights using functional (f)MRI to track spatiotemporal activity patterns at the whole brain level in lightly anesthetized mice, during both resting conditions and visual stimulation trials. Our results provide evidence that quasiperiodic patterns (QPPs) govern mouse resting brain dynamics. QPPs captured the temporal alignment of global brain fluctuations, anti-correlation of the Default Mode (DMN)- and Task Positive (TPN)-like networks, and activity in neuromodulatory nuclei of the reticular formation. While visual stimulation could trigger a transient spatiotemporal pattern highly similar to intrinsic QPPs, global signal fluctuations and QPPs during rest periods could explain variance in the following visual responses. QPPs and the global signal thus appeared to capture a common arousal-related brain-state fluctuation, orchestrated through neuromodulation. Our findings provide new frontiers to understand the neural processes that shape functional brain states and modulate sensory input processing.

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bioRxiv2019

Common functional networks in the mouse brain revealed by multi-centre resting-state fMRI analysis

Preclinical applications of resting-state functional magnetic resonance imaging (rsfMRI) offer the possibility to non-invasively probe whole-brain network dynamics and to investigate the determinants of altered network signatures observed in human studies. Mouse rsfMRI has been increasingly adopted by numerous laboratories world-wide. Here we describe a multi-centre comparison of 17 mouse rsfMRI datasets via a common image processing and analysis pipeline. Despite prominent cross-laboratory differences in equipment and imaging procedures, we report the reproducible identification of several large-scale resting-state networks (RSN), including a murine default-mode network, in the majority of datasets. A combination of factors was associated with enhanced reproducibility in functional connectivity parameter estimation, including animal handling procedures and equipment performance. Our work describes a set of representative RSNs in the mouse brain and highlights key experimental parameters that can critically guide the design and analysis of future rodent rsfMRI investigations.

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bioRxiv2018

Measuring single neuron visual receptive field sizes by fMRI

The non-invasive measurements of neuronal receptive field (RF) properties in-vivo allow a detailed understanding of brain organization as well as its plasticity by longitudinal following of potential changes. Visual RFs measured invasively by electrophysiology in animal models have traditionally provided a great extent of our current knowledge about the visual brain and its disorders. Voxel based estimates of population RF (pRF) by functional magnetic resonance imaging (fMRI) in humans revolutionized the field and have been used extensively in numerous studies. However, current methods cannot estimate single-neuron RF sizes as they reflect large populations of neurons with individual RF scatter. Here, we introduce a new approach to estimate RF size using spatial frequency selectivity to checkerboard patterns. This method allowed us to obtain non-invasive, single-unit, RF estimates in human V1 for the first time. These estimates were significantly smaller compared to prior pRF methods. Further, fMRI and electrophysiological experiments in non-human primates demonstrated an exceptional match validating the approach.

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bioRxiv2018

Organization of Area hV5/MT+ in Subjects with Homonymous Visual Field Defects

Damage to the primary visual cortex (V1) leads to a visual field loss (scotoma) in the retinotopically corresponding part of the visual field. Nonetheless, a small amount of residual visual sensitivity persists within the blind field. This residual capacity has been linked to activity observed in the middle temporal area complex (V5/MT+). However, it remains unknown whether the organization of hV5/MT+ changes following V1 lesions. We studied the organization of area hV5/MT+ of five patients with dense homonymous defects in a quadrant of the visual field as a result of partial V1+ or optic radiation lesions. To do so, we developed a new method, which models the boundaries of population receptive fields directly from the BOLD signal of each voxel in the visual cortex. We found responses in hV5/MT+ arising inside the scotoma for all patients and identified two possible sources of activation: 1) responses might originate from partially lesioned parts of area V1 corresponding to the scotoma, and 2) responses can also originate independent of area V1 input suggesting the existence of functional V1-bypassing pathways. Apparently, visually driven activity observed in hV5/MT+ is not sufficient to mediate conscious vision. More surprisingly, visually driven activity in corresponding regions of V1 and early extrastriate areas including hV5/MT+ did not guarantee visual perception in the group of patients with post-geniculate lesions that we examined. This suggests that the fine coordination of visual activity patterns across visual areas may be an important determinant of whether visual perception persists following visual cortical lesions.

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