Open datasets and code for multi-scale relations on structure, function and neuro-genetics in the human brain.

The human brain is an extremely complex network of structural and functional connections that operate at multiple spatial and temporal scales. Investigating the relationship between these multi-scale connections is critical to advancing our comprehension of brain function and disorders. However, accurately predicting structural connectivity from its functional counterpart remains a challenging pursuit. One of the major impediments is the lack of public repositories that integrate structural and functional networks at diverse resolutions, in conjunction with modular transcriptomic profiles, which are essential for comprehensive biological interpretation. To mitigate this limitation, our contribution encompasses the provision of an open-access dataset consisting of derivative matrices of functional and structural connectivity across multiple scales, accompanied by code that facilitates the investigation of their interrelations. We also provide additional resources focused on neuro-genetic associations of module-level network metrics, which present promising opportunities to further advance research in the field of network neuroscience, particularly concerning brain disorders.

Blockage of STAT3 during epileptogenesis prevents GABAergic loss and imprinting of the epileptic state.

Epilepsy, characterized by recurrent unprovoked seizures resulting from a wide variety of causes, is one of the world's most prominent neurological disabilities. Seizures, which are an expression of neuronal network dysfunction, occur in a positive feedback loop of concomitant factors, including neuro-inflammatory responses, where seizures generate more seizures. Among other pathways involved in inflammatory responses, the JAK/STAT signalling pathway has been proposed to participate in epilepsy. Here, we tested an in vitro model of temporal lobe epilepsy, with the hypothesis that acute blockage of STAT3-phosphorylation during epileptogenesis would prevent structural damage in the hippocampal circuitry and the imprinting of both neural epileptic activity and inflammatory glial states. We performed calcium imaging of spontaneous circuit dynamics in organotypic hippocampal slices previously exposed to epileptogenic conditions through the blockage of GABAergic synaptic transmission. Epileptogenic conditions lead to epileptic dynamics imprinted on circuits in terms of increased neuronal firing and circuit synchronization, increased correlated activity in neuronal pairs and decreased complexity in synchronization patterns. Acute blockage of the STAT3-phosphorylation during epileptogenesis prevented the imprinting of epileptic activity patterns, general cell loss, loss of GABAergic neurons and the persistence of reactive glial states. This work provides mechanistic evidence that blocking the STAT3 signalling pathway during epileptogenesis can prevent patho-topological persistent reorganization of neuro-glial circuits.

Neuromorphic-Based Neuroprostheses for Brain Rewiring: State-of-the-Art and Perspectives in Neuroengineering.

Neuroprostheses are neuroengineering devices that have an interface with the nervous system and supplement or substitute functionality in people with disabilities. In the collective imagination, neuroprostheses are mostly used to restore sensory or motor capabilities, but in recent years, new devices directly acting at the brain level have been proposed. In order to design the next-generation of neuroprosthetic devices for brain repair, we foresee the increasing exploitation of closed-loop systems enabled with neuromorphic elements due to their intrinsic energy efficiency, their capability to perform real-time data processing, and of mimicking neurobiological computation for an improved synergy between the technological and biological counterparts. In this manuscript, after providing definitions of key concepts, we reviewed the first exploitation of a real-time hardware neuromorphic prosthesis to restore the bidirectional communication between two neuronal populations in vitro. Starting from that 'case-study', we provide perspectives on the technological improvements for real-time interfacing and processing of neural signals and their potential usage for novel in vitro and in vivo experimental designs. The development of innovative neuroprosthetics for translational purposes is also presented and discussed. In our understanding, the pursuit of neuromorphic-based closed-loop neuroprostheses may spur the development of novel powerful technologies, such as 'brain-prostheses', capable of rewiring and/or substituting the injured nervous system.

Brain Mapping of Behavioral Domains Using Multi-Scale Networks and Canonical Correlation Analysis.

Simultaneous mapping of multiple behavioral domains into brain networks remains a major challenge. Here, we shed some light on this problem by employing a combination of machine learning, structural and functional brain networks at different spatial resolutions (also known as scales), together with performance scores across multiple neurobehavioral domains, including sensation, motor skills, and cognition. Provided by the Human Connectome Project, we make use of three cohorts: 640 participants for model training, 160 subjects for validation, and 200 subjects for model performance testing thus enhancing prediction generalization. Our modeling consists of two main stages, namely dimensionality reduction in brain network features at multiple scales, followed by canonical correlation analysis, which determines an optimal linear combination of connectivity features to predict multiple behavioral performance scores. To assess the differences in the predictive power of each modality, we separately applied three different strategies: structural unimodal, functional unimodal, and multimodal, that is, structural in combination with functional features of the brain network. Our results show that the multimodal association outperforms any of the unimodal analyses. Then, to answer which human brain structures were most involved in predicting multiple behavioral scores, we simulated different synthetic scenarios in which in each case we completely deleted a brain structure or a complete resting state network, and recalculated performance in its absence. In deletions, we found critical structures to affect performance when predicting single behavioral domains, but this occurred in a lesser manner for prediction of multi-domain behavior. Overall, our results confirm that although there are synergistic contributions between brain structure and function that enhance behavioral prediction, brain networks may also be mutually redundant in predicting multidomain behavior, such that even after deletion of a structure, the connectivity of the others can compensate for its lack in predicting behavior.

Microglial phagocytosis dysfunction in the dentate gyrus is related to local neuronal activity in a genetic model of epilepsy.

OBJECTIVE: Microglial phagocytosis of apoptotic cells is an essential component of the brain regenerative response during neurodegeneration. Whereas it is very efficient in physiological conditions, it is impaired in mouse and human mesial temporal lobe epilepsy, and now we extend our studies to a model of progressive myoclonus epilepsy type 1 in mice lacking cystatin B (CSTB). METHODS: We used confocal imaging and stereology-based quantification of apoptosis and phagocytosis of the hippocampus of Cstb knockout (KO) mice, an in vitro model of phagocytosis and siRNAs to acutely reduce Cstb expression, and a virtual three-dimensional (3D) model to analyze the physical relationship between apoptosis, phagocytosis, and active hippocampal neurons. RESULTS: Microglial phagocytosis was impaired in the hippocampus of Cstb KO mice at 1 month of age, when seizures arise and hippocampal atrophy begins. This impairment was not related to the lack of Cstb in microglia alone, as shown by in vitro experiments with microglial Cstb depletion. The phagocytosis impairment was also unrelated to seizures, as it was also present in Cstb KO mice at postnatal day 14, before seizures begin. Importantly, phagocytosis impairment was restricted to the granule cell layer and spared the subgranular zone, where there are no active neurons. Furthermore, apoptotic cells (both phagocytosed and not phagocytosed) in Cstb-deficient mice were at close proximity to active cFos+ neurons, and a virtual 3D model demonstrated that the physical relationship between apoptotic cells and cFos+ neurons was specific for Cstb KO mice. SIGNIFICANCE: These results suggest a complex crosstalk between apoptosis, phagocytosis, and neuronal activity, hinting that local neuronal activity could be related to phagocytosis dysfunction in Cstb KO mice. Overall, these data suggest that phagocytosis impairment is an early feature of hippocampal damage in epilepsy and opens novel therapeutic approaches for epileptic patients based on targeting microglial phagocytosis.

Structure-Function Connectomics Reveals Aberrant Developmental Trajectory Occurring at Preadolescence in the Autistic Brain.

Accumulating neuroimaging evidence shows that age estimation obtained from brain connectomics reflects the level of brain maturation along with neural development. It is well known that autism spectrum disorder (ASD) alters neurodevelopmental trajectories of brain connectomics, but the precise relationship between chronological age (ChA) and brain connectome age (BCA) during development in ASD has not been addressed. This study uses neuroimaging data collected from 50 individuals with ASD and 47 age- and gender-matched typically developing controls (TDCs; age range: 5-18 years). Both functional and structural connectomics were assessed using resting-state functional magnetic resonance imaging and diffusion tensor imaging data from the Autism Brain Imaging Data Exchange repository. For each participant, BCA was estimated from structure-function connectomics through linear support vector regression. We found that BCA matched well with ChA in TDC children and adolescents, but not in ASD. In particular, our findings revealed that individuals with ASD exhibited accelerated brain maturation in youth, followed by a delay of brain development starting at preadolescence. Our results highlight the critical role of BCA in understanding aberrant developmental trajectories in ASD and provide the new insights into the pathophysiological mechanisms of this disorder.

Toward neuroprosthetic real-time communication from in silico to biological neuronal network via patterned optogenetic stimulation.

Restoration of the communication between brain circuitry is a crucial step in the recovery of brain damage induced by traumatic injuries or neurological insults. In this work we present a study of real-time unidirectional communication between a spiking neuronal network (SNN) implemented on digital platform and an in-vitro biological neuronal network (BNN), generating similar spontaneous patterns of activity both spatial and temporal. The communication between the networks was established using patterned optogenetic stimulation via a modified digital light projector (DLP) receiving real-time input dictated by the spiking neurons' state. Each stimulation consisted of a binary image composed of 8 × 8 squares, representing the state of 64 excitatory neurons. The spontaneous and evoked activity of the biological neuronal network was recorded using a multi-electrode array in conjunction with calcium imaging. The image was projected in a sub-portion of the cultured network covered by a subset of the all electrodes. The unidirectional information transmission (SNN to BNN) is estimated using the similarity matrix of the input stimuli and output firing. Information transmission was studied in relation to the distribution of stimulus frequency and stimulus intensity, both regulated by the spontaneous dynamics of the SNN, and to the entrainment of the biological networks. We demonstrate that high information transfer from SNN to BNN is possible and identify a set of conditions under which such transfer can occur, namely when the spiking network synchronizations drive the biological synchronizations (entrainment) and in a linear regime response to the stimuli. This research provides further evidence of possible application of miniaturized SNN in future neuro-prosthetic devices for local replacement of injured micro-circuitries capable to communicate within larger brain networks.

A Neuromorphic Prosthesis to Restore Communication in Neuronal Networks.

Recent advances in bioelectronics and neural engineering allowed the development of brain machine interfaces and neuroprostheses, capable of facilitating or recovering functionality in people with neurological disability. To realize energy-efficient and real-time capable devices, neuromorphic computing systems are envisaged as the core of next-generation systems for brain repair. We demonstrate here a real-time hardware neuromorphic prosthesis to restore bidirectional interactions between two neuronal populations, even when one is damaged or missing. We used in vitro modular cell cultures to mimic the mutual interaction between neuronal assemblies and created a focal lesion to functionally disconnect the two populations. Then, we employed our neuromorphic prosthesis for bidirectional bridging to artificially reconnect two disconnected neuronal modules and for hybrid bidirectional bridging to replace the activity of one module with a real-time hardware neuromorphic Spiking Neural Network. Our neuroprosthetic system opens avenues for the exploitation of neuromorphic-based devices in bioelectrical therapeutics for health care.

A role of the Trx-G complex in Cid/CENP-A deposition at Drosophila melanogaster centromeres.

Centromeres are epigenetically determined chromatin structures that specify the assembly site of the kinetochore, the multiprotein machinery that binds microtubules and mediates chromosome segregation during mitosis and meiosis. The centromeric protein A (CENP-A) and its Drosophila orthologue centromere identifier (Cid) are H3 histone variants that replace the canonical H3 histone in centromeric nucleosomes of eukaryotes. CENP-A/Cid is required for recruitment of other centromere and kinetochore proteins and its deficiency disrupts chromosome segregation. Despite the many components that are known to cooperate in centromere function, the complete network of factors involved in CENP-A recruitment remains to be defined. In Drosophila, the Trx-G proteins localize along the heterochromatin with specific patterns and some of them localize to the centromeres of all chromosomes. Here, we show that the Trx, Ash1, and CBP proteins are required for the correct chromosome segregation and that Ash1 and CBP mediate for Cid/CENP-A recruitment at centromeres through post-translational histone modifications. We found that centromeric H3 histone is consistently acetylated in K27 by CBP and that nej and ash1 silencing respectively causes a decrease in H3K27 acetylation and H3K4 methylation along with an impairment of Cid loading.

Reconstruction of Functional Connectivity from Multielectrode Recordings and Calcium Imaging.

In the last two decades, increasing research efforts in neuroscience have been focused on determining both structural and functional connectivity of brain circuits, with the main goal of relating the wiring diagram of neuronal systems to their emerging properties, from the microscale to the macroscale. While combining multisite parallel recordings with structural circuits' reconstruction in vivo is still very challenging, the reductionist in vitro approach based on neuronal cultures offers lower technical difficulties and is much more stable under control conditions. In this chapter, we present different approaches to infer the connectivity of cultured neuronal networks using multielectrode array or calcium imaging recordings. We first formally introduce the used methods, and then we will describe into details how those methods were applied in case studies. Since multielectrode array and calcium imaging recordings provide distinct and complementary spatiotemporal features of neuronal activity, in this chapter we present the strategies implemented with the two different methodologies in distinct sections.

The GABA Developmental Shift Is Abolished by Maternal Immune Activation Already at Birth.

Epidemiological and experimental studies suggest that maternal immune activation (MIA) leads to developmental brain disorders, but whether the pathogenic mechanism impacts neurons already at birth is not known. We now report that MIA abolishes in mice the oxytocin-mediated delivery γ-aminobutyric acid (GABA) shift from depolarizing to hyperpolarizing in CA3 pyramidal neurons, and this is restored by the NKCC1 chloride importer antagonist bumetanide. Furthermore, MIA hippocampal pyramidal neurons at birth have a more exuberant apical arbor organization and increased apical dendritic length than age-matched controls. The frequency of spontaneous glutamatergic postsynaptic currents is also increased in MIA offspring, as well as the pairwise correlation of the synchronized firing of active cells in CA3. These alterations produced by MIA persist, since at P14-15 GABA action remains depolarizing, produces excitatory action, and network activity remains elevated with a higher frequency of spontaneous glutamatergic postsynaptic currents. Therefore, the pathogenic actions of MIA lead to important morphophysiological and network alterations in the hippocampus already at birth.

Modeling driver cells in developing neuronal networks.

Spontaneous emergence of synchronized population activity is a characteristic feature of developing brain circuits. Recent experiments in the developing neo-cortex showed the existence of driver cells able to impact the synchronization dynamics when single-handedly stimulated. We have developed a spiking network model capable to reproduce the experimental results, thus identifying two classes of driver cells: functional hubs and low functionally connected (LC) neurons. The functional hubs arranged in a clique orchestrated the synchronization build-up, while the LC drivers were lately or not at all recruited in the synchronization process. Notwithstanding, they were able to alter the network state when stimulated by modifying the temporal activation of the functional clique or even its composition. LC drivers can lead either to higher population synchrony or even to the arrest of population dynamics, upon stimulation. Noticeably, some LC driver can display both effects depending on the received stimulus. We show that in the model the presence of inhibitory neurons together with the assumption that younger cells are more excitable and less connected is crucial for the emergence of LC drivers. These results provide a further understanding of the structural-functional mechanisms underlying synchronized firings in developing circuits possibly related to the coordinated activity of cell assemblies in the adult brain.

Astrocytes restore connectivity and synchronization in dysfunctional cerebellar networks.

Evidence suggests that astrocytes play key roles in structural and functional organization of neuronal circuits. To understand how astrocytes influence the physiopathology of cerebellar circuits, we cultured cells from cerebella of mice that lack the ATM gene. Mutations in ATM are causative of the human cerebellar degenerative disease ataxia-telangiectasia. Cerebellar cultures grown from Atm-/- mice had disrupted network synchronization, atrophied astrocytic arborizations, reduced autophagy levels, and higher numbers of synapses per neuron than wild-type cultures. Chimeric circuitries composed of wild-type astrocytes and Atm-/- neurons were indistinguishable from wild-type cultures. Adult cerebellar characterizations confirmed disrupted astrocyte morphology, increased GABAergic synaptic markers, and reduced autophagy in Atm-/- compared with wild-type mice. These results indicate that astrocytes can impact neuronal circuits at levels ranging from synaptic expression to global dynamics.

Structure-function multi-scale connectomics reveals a major role of the fronto-striato-thalamic circuit in brain aging.

Physiological aging affects brain structure and function impacting morphology, connectivity, and performance. However, whether some brain connectivity metrics might reflect the age of an individual is still unclear. Here, we collected brain images from healthy participants (N = 155) ranging from 10 to 80 years to build functional (resting state) and structural (tractography) connectivity matrices, both data sets combined to obtain different connectivity features. We then calculated the brain connectome age-an age estimator resulting from a multi-scale methodology applied to the structure-function connectome, and compared it to the chronological age (ChA). Our results were twofold. First, we found that aging widely affects the connectivity of multiple structures, such as anterior cingulate and medial prefrontal cortices, basal ganglia, thalamus, insula, cingulum, hippocampus, parahippocampus, occipital cortex, fusiform, precuneus, and temporal pole. Second, we found that the connectivity between basal ganglia and thalamus to frontal areas, also known as the fronto-striato-thalamic (FST) circuit, makes the major contribution to age estimation. In conclusion, our results highlight the key role played by the FST circuit in the process of healthy aging. Notably, the same methodology can be generally applied to identify the structural-functional connectivity patterns correlating to other biomarkers than ChA.

Interaction Information Along Lifespan of the Resting Brain Dynamics Reveals a Major Redundant Role of the Default Mode Network.

Interaction Information (II) generalizes the univariate Shannon entropy to triplets of variables, allowing the detection of redundant (R) or synergetic (S) interactions in dynamical networks. Here, we calculated II from functional magnetic resonance imaging data and asked whether R or S vary across brain regions and along lifespan. Preserved along lifespan, we found high overlapping between the pattern of high R and the default mode network, whereas high values of S were overlapping with different cognitive domains, such as spatial and temporal memory, emotion processing and motor skills. Moreover, we have found a robust balance between R and S among different age intervals, indicating informational compensatory mechanisms in brain networks.

Building Bridges through Science.

Science is ideally suited to connect people from different cultures and thereby foster mutual understanding. To promote international life science collaboration, we have launched "The Science Bridge" initiative. Our current project focuses on partnership between Western and Middle Eastern neuroscience communities.

Group-Level Progressive Alterations in Brain Connectivity Patterns Revealed by Diffusion-Tensor Brain Networks across Severity Stages in Alzheimer's Disease.

Alzheimer's disease (AD) is a chronically progressive neurodegenerative disease highly correlated to aging. Whether AD originates by targeting a localized brain area and propagates to the rest of the brain across disease-severity progression is a question with an unknown answer. Here, we aim to provide an answer to this question at the group-level by looking at differences in diffusion-tensor brain networks. In particular, making use of data from Alzheimer's Disease Neuroimaging Initiative (ADNI), four different groups were defined (all of them matched by age, sex and education level): G1 (N1 = 36, healthy control subjects, Control), G2 (N2 = 36, early mild cognitive impairment, EMCI), G3 (N3 = 36, late mild cognitive impairment, LMCI) and G4 (N4 = 36, AD). Diffusion-tensor brain networks were compared across three disease stages: stage I (Control vs. EMCI), stage II (Control vs. LMCI) and stage III (Control vs. AD). The group comparison was performed using the multivariate distance matrix regression analysis, a technique that was born in genomics and was recently proposed to handle brain functional networks, but here applied to diffusion-tensor data. The results were threefold: First, no significant differences were found in stage I. Second, significant differences were found in stage II in the connectivity pattern of a subnetwork strongly associated to memory function (including part of the hippocampus, amygdala, entorhinal cortex, fusiform gyrus, inferior and middle temporal gyrus, parahippocampal gyrus and temporal pole). Third, a widespread disconnection across the entire AD brain was found in stage III, affecting more strongly the same memory subnetwork appearing in stage II, plus the other new subnetworks, including the default mode network, medial visual network, frontoparietal regions and striatum. Our results are consistent with a scenario where progressive alterations of connectivity arise as the disease severity increases and provide the brain areas possibly involved in such a degenerative process. Further studies applying the same strategy to longitudinal data are needed to fully confirm this scenario.

Simultaneous high-speed imaging and optogenetic inhibition in the intact mouse brain.

Genetically encoded calcium indicators and optogenetic actuators can report and manipulate the activity of specific neuronal populations. However, applying imaging and optogenetics simultaneously has been difficult to establish in the mammalian brain, even though combining the techniques would provide a powerful approach to reveal the functional organization of neural circuits. Here, we developed a technique based on patterned two-photon illumination to allow fast scanless imaging of GCaMP6 signals in the intact mouse brain at the same time as single-photon optogenetic inhibition with Archaerhodopsin. Using combined imaging and electrophysiological recording, we demonstrate that single and short bursts of action potentials in pyramidal neurons can be detected in the scanless modality at acquisition frequencies up to 1 kHz. Moreover, we demonstrate that our system strongly reduces the artifacts in the fluorescence detection that are induced by single-photon optogenetic illumination. Finally, we validated our technique investigating the role of parvalbumin-positive (PV) interneurons in the control of spontaneous cortical dynamics. Monitoring the activity of cellular populations on a precise spatiotemporal scale while manipulating neuronal activity with optogenetics provides a powerful tool to causally elucidate the cellular mechanisms underlying circuit function in the intact mammalian brain.