Paolo Bonifazi

GABAergic Hub Neurons Orchestrate Synchrony in Developing Hippocampal Networks

Coordinating Neuronal Assemblies Theoretical models predict the existence of so-called hub neurons—highly connected cells that strongly influence the synchronization of spiking activity in a large group of neurons. However, experimental evidence for the existence of these neuronal hubs is lacking. Bonifazi et al. (p. 1419) used high-resolution, two-photon calcium imaging to measure spontaneous calcium fluctuations in hundreds of neurons simultaneously and determined the relative timing of these fluctuations. Examination of functional connectivity maps, based on temporal correlation measurements, revealed a subpopulation of GABAergic hub neurons displaying a remarkably widespread axonal arborization that orchestrated network synchrony in developing hippocampal networks. Spontaneous network synchronizations in developing hippocampus caused giant depolarizing potentials in individual neurons, and manipulating the spike activity in potential hub cells influenced network activity. A model for the topology of brain networks incorporates a morpho-functional description of neuronal hubs. Brain function operates through the coordinated activation of neuronal assemblies. Graph theory predicts that scale-free topologies, which include “hubs” (superconnected nodes), are an effective design to orchestrate synchronization. Whether hubs are present in neuronal assemblies and coordinate network activity remains unknown. Using network dynamics imaging, online reconstruction of functional connectivity, and targeted whole-cell recordings in rats and mice, we found that developing hippocampal networks follow a scale-free topology, and we demonstrated the existence of functional hubs. Perturbation of a single hub influenced the entire network dynamics. Morphophysiological analysis revealed that hub cells are a subpopulation of γ-aminobutyric acid–releasing (GABAergic) interneurons possessing widespread axonal arborizations. These findings establish a central role for GABAergic interneurons in shaping developing networks and help provide a conceptual framework for studying neuronal synchrony.

Sequential Generation of Two Distinct Synapse-Driven Network Patterns in Developing Neocortex

Developing cortical networks generate a variety of coherent activity patterns that participate in circuit refinement. Early network oscillations (ENOs) are the dominant network pattern in the rodent neocortex for a short period after birth. These large-scale calcium waves were shown to be largely driven by glutamatergic synapses albeit GABA is a major excitatory neurotransmitter in the cortex at such early stages, mediating synapse-driven giant depolarizing potentials (GDPs) in the hippocampus. Using functional multineuron calcium imaging together with single-cell and field potential recordings to clarify distinct network dynamics in rat cortical slices, we now report that the developing somatosensory cortex generates first ENOs then GDPs, both patterns coexisting for a restricted time period. These patterns markedly differ by their developmental profile, dynamics, and mechanisms: ENOs are generated before cortical GDPs (cGDPs) by the activation of glutamatergic synapses mostly through NMDARs; cENOs are low-frequency oscillations (∼0.01 Hz) displaying slow kinetics and gradually involving the entire network. At the end of the first postnatal week, GABA-driven cortical GDPs can be reliably monitored; cGDPs are recurrent oscillations (∼0.1 Hz) that repetitively synchronize localized neuronal assemblies. Contrary to cGDPs, cENOs were unexpectedly facilitated by short anoxic conditions suggesting a contribution of glutamate accumulation to their generation. In keeping with this, alterations of extracellular glutamate levels significantly affected cENOs, which are blocked by an enzymatic glutamate scavenger. Moreover, we show that a tonic glutamate current contributes to the neuronal membrane excitability when cENOs dominate network patterns. Therefore, cENOs and cGDPs are two separate aspects of neocortical network maturation that may be differentially engaged in physiological and pathological processes.

Dissecting functional connectivity of neuronal microcircuits: experimental and theoretical insights

Structure-function studies of neuronal networks have recently benefited from considerable progress in different areas of investigation. Advances in molecular genetics and imaging have allowed for the dissection of neuronal connectivity with unprecedented detail whereas in vivo recordings are providing much needed clues as to how sensory, motor and cognitive function is encoded in neuronal firing. However, bridging the gap between the cellular and behavioral levels will ultimately require an understanding of the functional organization of the underlying neuronal circuits. One way to unravel the complexity of neuronal networks is to understand how their connectivity emerges during brain maturation. In this review, we will describe how graph theory provides experimentalists with novel concepts that can be used to describe and interpret these developing connectivity schemes.

In vitro large-scale experimental and theoretical studies for the realization of bi-directional brain-prostheses.

Brain-machine interfaces (BMI) were born to control “actions from thoughts” in order to recover motor capability of patients with impaired functional connectivity between the central and peripheral nervous system. The final goal of our studies is the development of a new proof-of-concept BMI—a neuromorphic chip for brain repair—to reproduce the functional organization of a damaged part of the central nervous system. To reach this ambitious goal, we implemented a multidisciplinary “bottom-up” approach in which in vitro networks are the paradigm for the development of an in silico model to be incorporated into a neuromorphic device. In this paper we present the overall strategy and focus on the different building blocks of our studies: (i) the experimental characterization and modeling of “finite size networks” which represent the smallest and most general self-organized circuits capable of generating spontaneous collective dynamics; (ii) the induction of lesions in neuronal networks and the whole brain preparation with special attention on the impact on the functional organization of the circuits; (iii) the first production of a neuromorphic chip able to implement a real-time model of neuronal networks. A dynamical characterization of the finite size circuits with single cell resolution is provided. A neural network model based on Izhikevich neurons was able to replicate the experimental observations. Changes in the dynamics of the neuronal circuits induced by optical and ischemic lesions are presented respectively for in vitro neuronal networks and for a whole brain preparation. Finally the implementation of a neuromorphic chip reproducing the network dynamics in quasi-real time (10 ns precision) is presented.

A novel brain partition highlights the modular skeleton shared by structure and function

Elucidating the intricate relationship between brain structure and function, both in healthy and pathological conditions, is a key challenge for modern neuroscience. Recent progress in neuroimaging has helped advance our understanding of this important issue, with diffusion images providing information about structural connectivity (SC) and functional magnetic resonance imaging shedding light on resting state functional connectivity (rsFC). Here, we adopt a systems approach, relying on modular hierarchical clustering, to study together SC and rsFC datasets gathered independently from healthy human subjects. Our novel approach allows us to find a common skeleton shared by structure and function from which a new, optimal, brain partition can be extracted. We describe the emerging common structure-function modules (SFMs) in detail and compare them with commonly employed anatomical or functional parcellations. Our results underline the strong correspondence between brain structure and resting-state dynamics as well as the emerging coherent organization of the human brain.

Pioneer glutamatergic cells develop into a morpho-functionally distinct population in the juvenile CA3 hippocampus

The developing CA3 hippocampus is comprised by highly connected hub neurons that are particularly effective in achieving network synchronization. Functional hub neurons were shown to be exclusively GABAergic, suggesting that the contribution of glutamatergic neurons to physiological synchronization processes at early postnatal stages is minimal. However, without fast GABAergic transmission, a different situation may prevail. In the adult CA3, blocking fast GABAergic transmission induces the generation of network bursts that can be triggered by the stimulation of single pyramidal neurons. Here we revisit the network function of CA3 glutamatergic neurons from a developmental viewpoint, without fast GABAergic transmission. We uncover a sub-population of early-generated glutamatergic neurons that impacts network dynamics when stimulated in the juvenile hippocampus. Additionally, this population displays characteristic morpho-physiological features in the juvenile and adult hippocampus. Therefore, the apparently homogeneous glutamatergic cell population likely displays a morpho-functional diversity rooted in temporal embryonic origins.

Clique of functional hubs orchestrates population bursts in developmentally regulated neural networks

It has recently been discovered that single neuron stimulation can impact network dynamics in immature and adult neuronal circuits. Here we report a novel mechanism which can explain in neuronal circuits, at an early stage of development, the peculiar role played by a few specific neurons in promoting/arresting the population activity. For this purpose, we consider a standard neuronal network model, with short-term synaptic plasticity, whose population activity is characterized by bursting behavior. The addition of developmentally inspired constraints and correlations in the distribution of the neuronal connectivities and excitabilities leads to the emergence of functional hub neurons, whose stimulation/deletion is critical for the network activity. Functional hubs form a clique, where a precise sequential activation of the neurons is essential to ignite collective events without any need for a specific topological architecture. Unsupervised time-lagged firings of supra-threshold cells, in connection with coordinated entrainments of near-threshold neurons, are the key ingredients to orchestrate population activity.

The role of the neuro-astro-vascular unit in the etiology of ataxia telangiectasia.

The growing recognition that brain pathologies do not affect neurons only but rather are, to a large extent, pathologies of glial cells as well as of the vasculature opens to new perspectives in our understanding of genetic disorders of the CNS. To validate the role of the neuron-glial-vascular unit in the etiology of genome instability disorders, we report about cell death and morphological aspects of neuroglia networks and the associated vasculature in a mouse model of Ataxia Telangiectasia (A-T), a human genetic disorder that induces severe motor impairment. We found that A-T-mutated protein deficiency was consistent with aberrant astrocytic morphology and alterations of the vasculature, often accompanied by reactive gliosis. Interestingly similar findings could also be reported in the case of other genetic disorders. These observations bolster the notion that astrocyte-specific pathologies, hampered vascularization and astrocyte-endothelium interactions in the CNS could play a crucial role in the etiology of genome instability brain disorders and could underlie neurodegeneration.

Enhanced pre-frontal functional-structural networks to support postural control deficits after traumatic brain injury in a pediatric population

Traumatic brain injury (TBI) affects structural connectivity, triggering the reorganization of structural–functional circuits in a manner that remains poorly understood. We focus here on brain network reorganization in relation to postural control deficits after TBI. We enrolled young participants who had suffered moderate to severe TBI, comparing them to young, typically developing control participants. TBI patients (but not controls) recruited prefrontal regions to interact with two separated networks: (1) a subcortical network, including parts of the motor network, basal ganglia, cerebellum, hippocampus, amygdala, posterior cingulate gyrus, and precuneus; and (2) a task-positive network, involving regions of the dorsal attention system, together with dorsolateral and ventrolateral prefrontal regions. We also found that the increased prefrontal connectivity in TBI patients was correlated with some postural control indices, such as the amount of body sway, whereby patients with worse balance increased their connectivity in frontal regions more strongly. The increased prefrontal connectivity found in TBI patients may provide the structural scaffolding for stronger cognitive control of certain behavioral functions, consistent with the observations that various motor tasks are performed less automatically following TBI and that more cognitive control is associated with such actions. Author Summary Using a new hierarchical atlas whose modules are relevant for both structure and function, we found increased structural and functional connectivity in prefrontal regions in TBI patients as compared to controls, in addition to a general pattern of overall decreased connectivity across the TBI brain. Although this increased prefrontal connectivity reflected interactions between brain areas when participants were at rest, the enhanced connectivity was found to be negatively correlated with active behavior such as postural control performance. Thus our findings, obtained when the brain was at rest, potentially reflect how TBI patients orchestrate task-related activations to support behavior in everyday life. In particular, our findings of enhanced connectivity in TBI might help these patients overcome deficits in cerebellar and subcortical connections, in addition to compensating for deficits when interacting with the task-positive network. Hence, it appears that greater cognitive control is exerted over certain actions in order to overcome deficits in their automatic processing.

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.