Biology subjects

Gini, S.

Publications and source records attributed to Gini, S..

10 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↗

bioRxiv2026

Structural and dynamic embedding of the mouse functional connectome revealed by functional ultrasound imaging (fUSI)

Functional ultrasound imaging (fUSI) is an emerging hemodynamic neuroimaging modality whose potential for connectome-scale network mapping remains largely untested. Here, we establish a non-invasive transcranial fUSI protocol and an fMRI-inspired preprocessing framework that enable robust resting-state functional connectomics in the mouse. We show that fUSI resolves canonical brain-wide cortical and subcortical networks with high spatial concordance to fMRI, including a default-mode (DMN) and a laterocortical network. Notably, fUSI networks are robustly embedded within the structural connectome, with structure-function coupling being parsimoniously described by four dominant axes that differentially relate functional systems to known anatomical substrates. We also show that, beyond static organization, fUSI reproduces hallmark resting state fMRI dynamics, including dominant anti-correlated coactivation patterns (CAPs) and a structured transition architecture that converges onto three stable attractor modes. Together, these results establish transcranial fUSI as a portable and scalable complement to fMRI for connectome-scale mapping of mouse brain networks.

neuroscience↗

bioRxiv2025

Developmental excitation-inhibition imbalance permanently reprograms autism-relevant social brain circuits

An influential theory proposes that an imbalance between excitation and inhibition (E:I) plays a central role in the etiology of autism and related developmental disorders. However, controversy exists as to whether this imbalance is a direct causal mechanism for autism, or a compensatory response to other primary etiological factors. Using chemogenetic manipulations in neonatal mice, we show that a transient E:I imbalance during development is sufficient to permanently reprogram autism-relevant social brain circuits. Chemogenetically manipulated mice exhibit lifelong impairments in sociability, persistent dysregulation of multiple autism-risk synaptic genes, and sustained cortical hyperexcitability in adulthood. Importantly, these social impairments are robustly rescued by pharmacological inhibition of neuronal excitability. Developmental E:I imbalance also disrupts functional connectivity in social brain regions enriched for transcriptionally dysregulated genes, suggesting a convergence of transcriptional and circuit-level pathology. Finally, multivariate modelling shows that behavioral dysfunction in chemogenetically manipulated animals closely associates with disrupted connectivity between prefrontal and mesolimbic dopaminergic regions. Collectively, our findings reconcile conflicting theories in the field and point to activity-dependent transcriptional remodeling as a foundational mechanism by which transient E:I imbalance during development can cause lasting, autism-relevant circuit dysfunction.

neuroscience↗

bioRxiv2025

The cost of cognition: Measuring the energy consumption of non-equilibrium computation

In biological systems, survival is predicated on an animal being able to perform computations quickly on a minimal energy budget. What is the energy consumption of non-equilibrium brain computation, i.e., what is the cost of cognition? Previous literature has estimated the metabolic cost using neuroimaging measures of glucose consumption but complementary to these findings, here we directly estimate the computational costs by combining the new field of stochastic thermodynamics with whole-brain modelling. We developed the COCO (COst of COgnition) framework using an analytical expression quantifying the links between energy cost, non-equilibrium and information processing for any given brain state measured with neuroimaging. Importantly, this key relationship also holds at the level of individual brain regions. We used this to quantify the benefits of information processing on the highly anatomically, interconnected hierarchical systems of the brain. Crucially, in empirical neuroimaging data we demonstrate that the human brain uses significantly less energy overall than other mammals (including non-human primates and mice), suggestive of an evolutionary optimisation of the effectiveness of computation. Focusing on the cost of cognition, using large-scale human neuroimaging data of 970 healthy human participants, we show that the resting state uses significantly less energy that seven different cognitive tasks. Furthermore, different kinds of tasks require different amounts of non-equilibrium, information processing and energy consumption. We found that tasks requiring more distributed computation also use more energy. Overall, these results directly quantify the cost of cognition, i.e., the non-equilibrium and energetic demands of information processing, allowing a deeper understanding of how the brain compute in a way that is far more energy efficient than current generations of digital computers and artificial intelligence.

neuroscience↗

bioRxiv2025

Comprehensive profiling of anaesthetised brain dynamics across phylogeny

Intrinsic dynamics of neuronal circuits shape information processing. Combining neuroimaging with causal perturbation offers the opportunity to understand how local dynamics mediate the link between neurobiology and functional repertoire. We compile a unique dataset of multi-scale neural activity during wakefulness and anaesthetic-induced suppression of information processing encompassing human, macaque, marmoset, mouse, zebrafish and nematode. Applying massive feature extraction, we comprehensively characterise local neural dynamics across >6,000 time-series features. Using dynamics as a common space for cross-species comparison reveals a conserved dynamical profile of anaesthesia across species, characterised by shorter intrinsic timescales of neural activity and dampened interregional synchrony. This dynamical regime is experimentally reversed in vivo by deep-brain stimulation of the macaque centromedian thalamus, restoring behavioural responsiveness. Spatially, this conserved dynamical phenotype covaries with conserved transcriptional profiles of excitatory and inhibitory neurotransmission across human, macaque, marmoset and mouse cortex. Biophysical modelling provides a mechanistic link between the macroscale dynamical phenotype of anaesthesia, and microscale effects of key molecular targets on the timescales of synaptic excitation and inhibition. Altogether, comprehensive dynamical phenotyping reveals a shared neural endpoint of anaesthesia: across species and scales, anaesthetics induce spatio-temporal isolation of local neural activity.

neuroscience↗

bioRxiv2025

Biological subtyping of autism via cross-species fMRI

It is frequently assumed that the phenotypic heterogeneity in autism spectrum disorder reflects underlying pathobiological variation. However, direct evidence in support of this hypothesis is lacking. Here, we leverage cross-species functional neuroimaging to examine whether variability in brain functional connectivity reflects distinct biological mechanisms. We find that fMRI connectivity alterations in 20 distinct mouse models of autism (n=549 individual mice) can be clustered into two prominent hypo- and hyperconnectivity subtypes. We show that these connectivity profiles are linked to distinct signaling pathways, with hypoconnectivity being associated with synaptic dysfunction, and hyperconnectivity reflecting transcriptional and immune-related alterations. Extending these findings to humans, we identify analogous hypo- and hyperconnectivity subtypes in a large, multicenter resting state fMRI dataset of n=940 autistic and n=1036 neurotypical individuals. Remarkably, hypo- and hyperconnectivity autism subtypes are replicable across independent cohorts (accounting for 25.1% of all autism data), exhibit distinct functional network architecture, are behaviorally dissociable, and recapitulate synaptic and immune mechanisms identified in corresponding mouse subtypes. Our cross-species investigation, thus, decodes the heterogeneity of fMRI connectivity in autism into distinct pathway-specific etiologies, offering a new empirical framework for targeted subtyping of autism.

neuroscience↗

bioRxiv2025

Synaptome architecture shapes regional dynamics in the mouse brain

Synapses are the connections that transform neurons from simple electrically charged cells into complex circuits that support perception, cognition and action. Recent advances in single-punctum synapse mapping in mice have made it possible to study the diversity of synapses and how these synapse types are differentially expressed across the brain. A salient question is how synapse diversity shapes the spatial patterning of whole-brain dynamics. Here we derive > 6 000 time-series features from fMRI recordings in awake mice to construct a comprehensive macroscale dynamical phenotype of each synapse type. We find that spatial variation in synapse types colocalizes with spatial variation in regional dynamics. Time-series in regions enriched for SAP102-expressing synapses display high-amplitude events while time-series in regions enriched for PSD95-expressing synapses display low stationarity. These regional variations in synapse types and dynamics are associated with patterns of structural and functional connectivity and the placement of hubs. Finally, using two additional fMRI datasets in anaesthetized mice, we show that synapses expressing short- and long-lifetime proteins are differentially engaged across behavioural states. Collectively, this work demonstrates that the spatial organization of microscale synapse types fundamentally shapes whole-brain dynamics.

neuroscience↗

bioRxiv2024

Competitive interactions shape brain dynamics and computation across species

Adaptive cognition relies on cooperation across anatomically distributed brain circuits. However, specialised neural systems are also in constant competition for limited processing resources. How does the brains network architecture enable it to balance these cooperative and competitive tendencies? Here we use computational whole-brain modelling to examine the dynamical and computational relevance of cooperative and competitive interactions in the mammalian connectome. Across human, macaque, and mouse we show that the architecture of the models that most faithfully reproduce brain activity, consistently combines modular cooperative interactions with diffuse, long-range competitive interactions. The model with competitive interactions consistently outperforms the cooperative-only model, with excellent fit to both spatial and dynamical properties of the living brain, which were not explicitly optimised but rather emerge spontaneously. Competitive interactions in the effective connectivity produce greater levels of synergistic information and local-global hierarchy, and lead to superior computational capacity when used for neuromorphic computing. Altogether, this work provides a mechanistic link between network architecture, dynamical properties, and computation in the mammalian brain.

neuroscience↗

bioRxiv2024

Synaptic-dependent developmental dysconnectivity in 22q11.2 deletion syndrome

Chromosome 22q11.2 deletion is among the strongest known genetic risk factors for neuropsychiatric disorders, including autism and schizophrenia. Brain imaging studies have reported disrupted large-scale functional connectivity in people with 22q11 deletion syndrome (22q11DS). However, the significance and biological determinants of these functional alterations remain unclear. Here, we use a cross-species design to investigate the developmental trajectory and neural underpinnings of brain dysconnectivity in 22q11DS. We find that LgDel mice, an established mouse model of 22q11DS, exhibit age-specific patterns of functional MRI (fMRI) dysconnectivity, with widespread fMRI hyper-connectivity in juvenile mice reverting to focal hippocampal hypoconnectivity over puberty. These fMRI connectivity alterations are mirrored by co-occurring developmental alterations in dendritic spine density, and are both transiently normalized by developmental GSK3{beta} inhibition, suggesting a synaptic origin for this phenomenon. Notably, analogous hyper-to hypoconnectivity reconfiguration occurs also in human 22q11DS, where it affects hippocampal and cortical regions spatially enriched for synaptic genes that interact with GSK3{beta}, and autism-relevant transcripts. Functional dysconnectivity in somatomotor components of this network is predictive of age-dependent social alterations in 22q11.2 deletion carriers. Taken together, these findings suggest that synaptic-related mechanisms underlie developmentally mediated functional dysconnectivity in 22q11DS.

neuroscience↗

bioRxiv2021

(Un)common space in infant neuroimaging studies: a systematic review of infant templates

In neuroimaging, spatial normalization is an important step that maps an individuals brain onto a template brain permitting downstream statistical analyses. Yet, in infant neuroimaging, there remain several technical challenges that have prevented the establishment of a standardized template for spatial normalization. Thus, many different approaches are used in the literature. To quantify the popularity and variability of these approaches in infant neuroimaging studies, we performed a systematic review of infant MRI studies from 2000 to 2020. Here, we present results from 833 studies meeting inclusion criteria. Studies were classified into 1) processing data in single subject space, 2) using a predefined, or "off the shelf", template, 3) creating a study specific template or 4) using a hybrid of these methods. We found that across the studies in the systematic review, single subject space was the most used (no common space). This was the most used common space for DWI and structural MRI studies while fMRI studies preferred off the shelf atlases. We found a pattern such that more recently published studies are more commonly using off the shelf atlases. When considering special populations, preterm studies most used single subject space while, when no special populations were being analyzed, an off the shelf template was most common. The most used off the shelf templates were the UNC Infant Atlases (26.1%). Using a systematic review of infant neuroimaging studies, we highlight a lack of an established "standard" template brain in these studies.

neuroscience↗