Biology subjects

Markicevic, M.

Publications and source records attributed to Markicevic, M..

13 recordsLinked to original sources

bioRxiv2026

Cortical excitability inversely modulates fMRI connectivity via low-frequency neuronal coupling

The neural mechanisms supporting fMRI connectivity are poorly understood. Leveraging an aggregated analysis of novel and existing chemogenetic manipulations and electrophysiological recordings in the mouse medial prefrontal cortex (PFC), we show that local cortical excitability inversely modulates large-scale fMRI connectivity. Specifically, we find that bidirectional chemogenetic manipulations of cortical excitability produce opposite effects on fMRI connectivity, resulting in fMRI hypoconnectivity when excitability is enhanced, and fMRI hyperconnectivity when excitability is suppressed, despite corresponding increases or decreases in local neuronal firing. Notably, while each chemogenetic manipulation produces a distinct profile of interareal electrophysiological coherence, only low-frequency (< 4Hz) coherence predicts the direction and magnitude of the ensuing fMRI connectivity changes. Biophysical network modelling shows that the observed electrophysiological coherence profiles can arise from the interaction between direct inter-area communication changes mediated by local firing-rate variations, and shared larger-scale low-frequency covariation of ongoing neuronal activity. Together, our results reveal an inverse relationship between regional cortical excitability and large-scale fMRI connectivity, and indicate that fMRI connectivity is primarily supported by low frequency (<4 Hz) electrophysiological coupling. These findings open new avenues for modeling and interpreting fMRI connectivity in health, and in response to pathological or exogenous perturbations linked to cortical excitability.

neuroscience↗

bioRxiv2025

Geometric influences on the regional organization of the mammalian brain

The mammalian brain comprises anatomically and functionally distinct regions, yet the principles governing their organization across scales remain unclear. Efforts to map regional boundaries use expert judgement or data-driven clustering of functional, connectional, and/or architectonic properties, but these approaches are often descriptive, have limited generalizability, and do not elucidate generative mechanisms. Here, we develop a geometrically constrained framework for the hierarchical, multiscale regional organization of neocortical and non-neocortical structures. The framework yields parcels at any resolution with high internal homogeneity across hundreds of anatomical, functional, cellular, and molecular properties in humans, macaques, marmosets, and mice, and it generalizes to understudied mammalian species. Finally, we demonstrate that the framework captures the essence of a reaction-diffusion mechanism in which brain geometry shapes the spatial expression of putative patterning molecules that establish a blueprint of regional identity during development. Our findings point to a conserved, universal influence of geometry on mammalian brain organization.

neuroscience↗

bioRxiv2024

Canonical time-series features for characterizing biologically informative dynamical patterns in fMRI

The interdisciplinary time-series analysis literature encompasses thousands of statistical features for quantifying interpretable properties of dynamical data. But for any given application, it is likely that just a small subset of informative time-series features is required to capture the dynamical quantities of interest. So, while comprehensive libraries of time-series features have been developed, it is useful to construct reduced and computationally efficient subsets for specific applications. In this work, we demonstrate a systematic process to deduce such a reduced set, focused on the problem of distinguishing changes to functional Magnetic Resonance Imaging (fMRI) time series caused by a range of experimental manipulations of excitatory and inhibitory neural activity in mouse cortical circuits. We reduce a comprehensive library of over 7000 candidate time-series features down to a subset of 16 features, which we call catchaMouse16, that aims to both: (i) accurately characterize biologically relevant properties of fMRI time series; and (ii) minimize inter-feature redundancy. The catchaMouse16 feature set accurately classifies experimental perturbations of neuronal activity from fMRI recordings, and also shows strong generalization performance on an unseen mouse and human resting-state fMRI data where it tracks spatial variations in excitatory and inhibitory cortical cell densities, often with greater statistical power than the full hctsa feature set. We provide an efficient, open-source implementation of the catchaMouse16 feature set in C (achieving an approximately 60 times speed-up relative to the native Matlab code of the same features), with wrappers for Python and Matlab. This work demonstrates a procedure to reduce a large candidate time-series feature set down to the key statistical properties of mouse fMRI dynamics that can be used to efficiently quantify and interpret informative dynamical patterns in neural time series.

neuroscience↗

bioRxiv2024

Repetitive mild closed-head injury induced synapse loss and increased local BOLD-fMRI signal homogeneity

Repeated mild head injuries due to sports, or domestic violence and military service are increasingly linked to debilitating symptoms in the long term. Although symptoms may take decades to manifest, potentially treatable neurobiological alterations must begin shortly after injury. Better means to diagnose and treat traumatic brain injuries, requires an improved understanding of the mechanisms underlying progression and means through which they can be measured. Here, we employ a repetitive mild closed-head injury (rmTBI) and chronic variable stress (CVS) mouse model to investigate emergent structural and functional brain abnormalities. Brain imaging is achieved with [18F]SynVesT-1 positron emission tomography, with the synaptic vesicle glycoprotein 2A ligand marking synapse density and BOLD (blood-oxygen-level-dependent) functional magnetic resonance imaging (fMRI). Animals were scanned six weeks after concluding rmTBI/Stress procedures. Injured mice showed widespread decreases in synaptic density coupled with an increase in local BOLD-fMRI synchrony detected as regional homogeneity. Injury-affected regions with higher synapse density showed a greater increase in fMRI regional homogeneity. Taken together, these observations may reflect compensatory mechanisms following injury. Multimodal studies are needed to provide deeper insights into these observations.

neuroscience↗

bioRxiv2024

Multimodal identification of the mouse brain using simultaneous Ca2+ imaging and fMRI

Individual differences in neuroimaging are of interest to clinical and cognitive neuroscientists based on their potential for guiding the personalized treatment of various heterogeneous neurological conditions and diseases. Despite many advantages, the workhorse in this arena, BOLD (blood-oxygen-level-dependent) functional magnetic resonance imaging (fMRI) suffers from low spatiotemporal resolution and specificity as well as a propensity for noise and spurious signal corruption. To better understand individual differences in BOLD-fMRI data, we can use animal models where fMRI, alongside complementary but more invasive contrasts, can be accessed. Here, we apply simultaneous wide-field fluorescence calcium imaging and BOLD-fMRI in mice to interrogate individual differences using a connectome-based identification framework adopted from the human fMRI literature. This approach yields high spatiotemporal resolution cell-type specific signals (here, from glia, excitatory, as well as inhibitory interneurons) from the whole cortex. We found mouse multimodal connectome-based identification to be successful and explored various features of these data.

neuroscience↗

bioRxiv2024

Functional-based parcellation of the mouse prefrontal cortex for network perturbation analysis

The prefrontal cortex (PFC) is a region of the brain involved in higher-order cognitive processes such as attention, emotional regulation, and social behavior, making it a hotspot for an ongoing clinical and fundamental research. Importantly, its functionality is intricately interconnected within a wide array of functional networks encompassing multiple other brain areas. However, the delineation of distinct subdivisions within the mouse PFC and their contributions to the broader brain network function remain topics of ongoing debate. In the current study, we used resting-state functional magnetic resonance imaging (rsfMRI) from a large cohort of wildtype animals to derive the functional-connectivity (FC) based parcellation of the mouse PFC with voxel resolution. Our findings indicate the presence of FC-based clusters that deviate from the established anatomical subdivisions within the cingulate and prelimbic areas, while they align in infralimbic and orbital cortices. To further underscore the association of these FC-based clusters with distinct functional networks, we performed network-specific perturbations using chemogenetics in the identified clusters in dorsal PFC and monitor the elicited effects with fMRI (chemo-fMRI). Our recordings revealed that FC perturbations were observed only within the functional networks linked to the targeted clusters and did not spread to neighbouring anatomical areas or functional clusters. We propose that FC-based parcellation is a valuable approach for tracking the impact of external activations and confirming the precise site of activation. O_FIG O_LINKSMALLFIG WIDTH=127 HEIGHT=200 SRC="FIGDIR/small/586664v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@11d4042org.highwire.dtl.DTLVardef@165cb5forg.highwire.dtl.DTLVardef@b0a4aorg.highwire.dtl.DTLVardef@d093c9_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2023

Multipair phase-modulated temporal interference electrical stimulation combined with fMRI.

Temporal Interference stimulation (TIS) is a promising non-invasive brain stimulation technique exploiting frequency-shifted kHz fields to modulate oscillatory neural activity without invasive procedures. While human studies suggest TIS efficacy in targeting relatively deep brain structures, recent computational modeling and animal studies indicate potential off-target stimulations via the application of standard TIS protocols. Here, we computationally optimized TIS targeting for the prefrontal cortex (PFC) in mice. Combining in vivo electrophysiological recordings, intracellular calcium dynamics with fiber photometry, and functional MRI, we confirmed TIS-induced amplitude modulation, neuronal entrainment and hemodynamic responses in the PFC, while also identifying off-target modulations. To mitigate off-target effects, we propose a novel configuration with three electrode pairs, one of which is actively phase-shifted by 180 degrees. This cancelling field significantly enhanced TIS focality, reducing off-target effects without compromising the TIS efficacy in the target area. This work effectively addresses one of TIS most critical shortcomings and opens new avenues for research and clinical applications. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=178 SRC="FIGDIR/small/571679v2_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@b04067org.highwire.dtl.DTLVardef@154549aorg.highwire.dtl.DTLVardef@17e63c3org.highwire.dtl.DTLVardef@c7a341_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2022

Neuromodulation of striatal D1 cells shapes BOLD fluctuations in anatomically connected thalamic and cortical regions

Understanding how the brains macroscale dynamics are shaped by underlying microscale mechanisms is a key problem in neuroscience. In animal models, we can now investigate this relationship in unprecedented detail by directly manipulating cellular-level properties while measuring the whole-brain response using resting-state fMRI. Here we focused on understanding how blood-oxygen-level-dependent (BOLD) dynamics, measured within a structurally well-defined striato-thalamo-cortical circuit, are shaped by chemogenetically exciting or inhibiting D1 medium spiny neurons (MSNs) of the right dorsomedial striatum (CPdm). We characterize changes in both the BOLD dynamics of individual cortical and subcortical brain areas, and patterns of inter-regional coupling (functional connectivity) between pairs of areas. Using a classification approach based on a large and diverse set of time-series properties, we found that CPdm neuromodulation alters BOLD dynamics within thalamic subregions that project back to dorsomedial striatum. In the cortex, the strongest changes in local dynamics were observed in unimodal regions, i.e., regions that process information from a single sensory modality, while changes in the local dynamics weakened along a putative cortical hierarchical gradient towards transmodal regions. In contrast, a decrease in functional connectivity was observed only for cortico-striatal connections after D1 excitation. Our results provide a comprehensive understanding of how targeted cellular-level manipulations affect local BOLD dynamics at the macroscale, including the role of a circuits structural characteristics and hierarchical cortical level in shaping those dynamics. These findings contribute to ongoing attempts to understand the influence of structure-function relationships in shaping inter-regional communication at subcortical and cortical levels.

neuroscience↗

bioRxiv2020

Transient Maternal IL-6 boosts glutamatergic synapses and disrupts hippocampal connectivity in the offspring

Early prenatal inflammatory conditions are thought to represent a risk factor for different neurodevelopmental disorders, with long-term consequences on adult brain connectivity. Here we show that a transient IL-6 elevation, occurring at vulnerable stages of early neurodevelopment, directly impacts brain developmental trajectories through the aberrant enhancement of glutamatergic synapses and overall brain hyper-connectivity. The IL6-mediated boost of excitatory synapse density results from the neuron-autonomous, genomic effect of the transcription factor STAT3 and causally involves the activation of RGS4 gene as a candidate downstream target. The STAT3/RGS4 pathway is also activated in neonatal brains as a consequence of maternal immune activation protocols mimicking a viral infection during pregnancy. By demonstrating that prenatal IL-6 elevations result in aberrant synaptic and brain connectivity through the molecular players identified, we provide a mechanistic framework for the association between prenatal inflammatory events and brain neurodevelopmental disorders.

neuroscience↗

bioRxiv2020

Brain mapping across 16 autism mouse models reveals a spectrum of functional connectivity subtypes

Autism Spectrum Disorder (ASD) is characterized by substantial, yet highly heterogeneous abnormalities in functional brain connectivity. However, the origin and significance of this phenomenon remain unclear. To unravel ASD connectopathy and relate it to underlying etiological heterogeneity, we carried out a bi-center cross-etiological investigation of fMRI-based connectivity in the mouse, in which specific ASD-relevant mutations can be isolated and modelled minimizing environmental contributions. By performing brain-wide connectivity mapping across 16 mouse mutants, we show that different ASD-associated etiologies cause a broad spectrum of connectional abnormalities in which diverse, often diverging, connectivity signatures are recognizable. Despite this heterogeneity, the identified connectivity alterations could be classified into four subtypes characterized by discrete signatures of network dysfunction. Our findings show that etiological variability is a key determinant of connectivity heterogeneity in ASD, hence reconciling conflicting findings in clinical populations. The identification of etiologically-relevant connectivity subtypes could improve diagnostic label accuracy in the non-syndromic ASD population and paves the way for personalized treatment approaches.

neuroscience↗

bioRxiv2020

Intrinsic excitation-inhibition imbalance affects medial prefrontal cortex differently in autistic men versus women

Excitation-inhibition (E:I) imbalance is theorized as an important pathophysiological mechanism in autism. Autism affects males more frequently than females and sex-related mechanisms (e.g., X-linked genes, androgen hormones) can influence E:I balance. This suggests that E:I imbalance may affect autism differently in males versus females. With a combination of in-silico modeling and in-vivo chemogenetic manipulations in mice, we first show that a time-series metric estimated from fMRI BOLD signal, the Hurst exponent (H), can be an index for underlying change in the synaptic E:I ratio. In autism we find that H is reduced, indicating increased excitation, in the medial prefrontal cortex (MPFC) of autistic males but not females. Increasingly intact MPFC H is also associated with heightened ability to behaviorally camouflage social-communicative difficulties, but only in autistic females. This work suggests that H in BOLD can index synaptic E:I ratio and that E:I imbalance affects autistic males and females differently.

neuroscience↗

bioRxiv2019

Rapid Reconfiguration of the Functional Connectome after Chemogenetic Locus Coeruleus Activation

The locus coeruleus (LC) supplies norepinephrine (NE) to the entire forebrain, regulates many fundamental brain functions, and is implicated in several neuropsychiatric diseases. Although selective manipulation of the LC is not possible in humans, studies have suggested that strong LC activation might shift network connectivity to favor salience processing. To test this hypothesis, we use a mouse model to study the impact of LC stimulation on large-scale functional connectivity by combining chemogenetic activation of the LC with resting-state fMRI, an approach we term "chemo-connectomics". LC activation rapidly interrupts ongoing behavior and strongly increases brain-wide connectivity, with the most profound effects in the salience and amygdala networks. We reveal a direct correlation between functional connectivity changes and transcript levels of alpha-1, alpha-2, and beta-1 adrenoceptors across the brain, and a positive correlation between NE turnover and functional connectivity within select brain regions. These results represent the first brain-wide functional connectivity mapping in response to LC activation, and demonstrate a causal link between receptor expression, brain states and functionally connected large-scale networks at rest. We propose that these changes in large-scale network connectivity are critical for optimizing neural processing in the context of increased vigilance and threat detection.

neuroscience↗

bioRxiv2018

Cortical excitation:inhibition imbalance causes network specific functional hypoconnectivity: a DREADD-fMRI study

Abnormal brain development manifests itself at different spatial scales. However, whether abnormalities at the cellular level can be diagnosed from network activity measured withfunctional magnetic resonance imaging (fMRI) is largely unknown, yet of high clinical relevance. Here we applied fMRI while using chemogenetics to increase the excitation-to-inhibition ratio (E:I) within cortical microcircuits of the mouse brain, thereby mimicking a putative mechanism of neurodevelopmental disorders including autism. Increased E:I caused a significant reduction of long-range connectivity, irrespective of whether excitatory neurons were facilitated or inhibitory Parvalbumin interneurons were suppressed. Training a classifier on fMRI signals, we were able to accurately classify cortical areas exhibiting increased E:I. This classifier was validated in an independent cohort of Fmr1y/- knock-out mice, a model for autism with well-documented loss of Parvalbumin neurons and chronic alterations of E:I. Our findings demonstrate a promising novel approach towards inferring microcircuit abnormalities from macroscopic fMRI measurements.

neuroscience↗