Optimal navigability of weighted human brain connectomes in physical space.

Communication protocols in the brain connectome describe how to transfer information from one region to another. Typically, these protocols hinge on either the spatial distances between brain regions or the intensity of their connections. Yet, none of them combine both factors to achieve optimal efficiency. Here, we introduce a continuous spectrum of decentralized routing strategies that integrates link weights and the spatial embedding of connectomes to route signal transmission. We implemented the protocols on connectomes from individuals in two cohorts and on group-representative connectomes designed to capture weighted connectivity properties. We identified an intermediate domain of routing strategies, a sweet spot, where navigation achieves maximum communication efficiency at low transmission cost. This phenomenon is robust and independent of the particular configuration of weights. Our findings suggest an interplay between the intensity of neural connections and their topology and geometry that amplifies communicability, where weights play the role of noise in a stochastic resonance phenomenon. Such enhancement may support more effective responses to external and internal stimuli, underscoring the intricate diversity of brain functions.

Integrated information decomposition unveils major structural traits of in silico and in vitro neuronal networks.

The properties of complex networked systems arise from the interplay between the dynamics of their elements and the underlying topology. Thus, to understand their behavior, it is crucial to convene as much information as possible about their topological organization. However, in large systems, such as neuronal networks, the reconstruction of such topology is usually carried out from the information encoded in the dynamics on the network, such as spike train time series, and by measuring the transfer entropy between system elements. The topological information recovered by these methods does not necessarily capture the connectivity layout, but rather the causal flow of information between elements. New theoretical frameworks, such as Integrated Information Decomposition (Φ-ID), allow one to explore the modes in which information can flow between parts of a system, opening a rich landscape of interactions between network topology, dynamics, and information. Here, we apply Φ-ID on in silico and in vitro data to decompose the usual transfer entropy measure into different modes of information transfer, namely, synergistic, redundant, or unique. We demonstrate that the unique information transfer is the most relevant measure to uncover structural topological details from network activity data, while redundant information only introduces residual information for this application. Although the retrieved network connectivity is still functional, it captures more details of the underlying structural topology by avoiding to take into account emergent high-order interactions and information redundancy between elements, which are important for the functional behavior, but mask the detection of direct simple interactions between elements constituted by the structural network topology.

7,8-dihydroxyflavone ameliorates cognitive and motor deficits in a Huntington's disease mouse model through specific activation of the PLCγ1 pathway.

Huntington's disease (HD) is a fatal neurodegenerative disease with motor, cognitive and psychiatric impairment. Dysfunctions in HD models have been related to reduced levels of striatal brain-derived neurotrophic factor (BDNF) and imbalance between its receptors TrkB and p75(NTR). Thus, molecules with activity on the BDNF/TrkB/p75 system can have therapeutic potential. 7,8-Dihydroxyflavone (7,8-DHF) was described as a TrkB agonist in several models of neuro-degenerative diseases, however, its TrkB activation profile needs further investigation due to its pleiotropic properties and divergence from BDNF effect. To investigate this, we used in vitro and in vivo models of HD to dissect TrkB activation upon 7,8-DHF treatment. 7,8-DHF treatment in primary cultures showed phosphorylation of TrkBY816 but not TrkBY515 with activation of the PLCγ1 pathway leading to morphological and functional improvements. Chronic administration of 7,8-DHF delayed motor deficits in R6/1 mice and reversed deficits on the Novel Object Recognition Test (NORT) at 17 weeks. Morphological and biochemical analyses revealed improved striatal levels of enkephalin, and prevention of striatal volume loss. We found a TrkBY816 but not TrkBY515 phosphorylation recovery in striatum concordant with in vitro results. Additionally, 7,8-DHF normalized striatal levels of induced and neuronal nitric oxide synthase (iNOS and nNOS, respectively) and ameliorated the imbalance of p75/TrkB. Our results provide new insights into the mechanism of action of 7,8-DHF suggesting that its effect through the TrkB receptor in striatum is via selective phosphorylation of its Y816 residue and activation of PLCγ1 pathway, but pleiotropic effects of the drug also contribute to its therapeutic potential.

Impact of targeted attack on the spontaneous activity in spatial and biologically-inspired neuronal networks.

We study the structural and dynamical consequences of damage in spatial neuronal networks. Inspired by real in vitro networks, we construct directed networks embedded in a two-dimensional space and follow biological rules for designing the wiring of the system. As a result, synthetic cultures display strong metric correlations similar to those observed in real experiments. In its turn, neuronal dynamics is incorporated through the Izhikevich model adopting the parameters derived from observation in real cultures. We consider two scenarios for damage, targeted attacks on those neurons with the highest out-degree and random failures. By analyzing the evolution of both the giant connected component and the dynamical patterns of the neurons as nodes are removed, we observe that network activity halts for a removal of 50% of the nodes in targeted attacks, much lower than the 70% node removal required in the case of random failures. Notably, the decrease of neuronal activity is not gradual. Both damage scenarios portray "boosts" of activity just before full silencing that are not present in equivalent random (Erdös-Rényi) graphs. These boosts correspond to small, spatially compact subnetworks that are able to maintain high levels of activity. Since these subnetworks are absent in the equivalent random graphs, we hypothesize that metric correlations facilitate the existence of local circuits sufficiently integrated to maintain activity, shaping an intrinsic mechanism for resilience.

Dominance of Metric Correlations in Two-Dimensional Neuronal Cultures Described through a Random Field Ising Model.

We introduce a novel random field Ising model, grounded on experimental observations, to assess the importance of metric correlations in cortical circuits in vitro. Metric correlations arise from both the finite axonal length and the heterogeneity in the spatial arrangement of neurons. The experiments consider the response of neuronal cultures to an external electric stimulation for a gradually weaker connectivity strength between neurons, and in cultures with different spatial configurations. The model can be analytically solved in the metric-free, mean-field scenario. The presence of metric correlations precipitates a strong deviation from the mean field. Null models of the same networks that preserve the distribution of connections recover the mean field. Our results show that metric-inherited correlations in spatial networks dominate the connectivity blueprint, mask the actual distribution of connections, and may emerge as the asset that shapes network dynamics.

Emergence of assortative mixing between clusters of cultured neurons.

The analysis of the activity of neuronal cultures is considered to be a good proxy of the functional connectivity of in vivo neuronal tissues. Thus, the functional complex network inferred from activity patterns is a promising way to unravel the interplay between structure and functionality of neuronal systems. Here, we monitor the spontaneous self-sustained dynamics in neuronal cultures formed by interconnected aggregates of neurons (clusters). Dynamics is characterized by the fast activation of groups of clusters in sequences termed bursts. The analysis of the time delays between clusters' activations within the bursts allows the reconstruction of the directed functional connectivity of the network. We propose a method to statistically infer this connectivity and analyze the resulting properties of the associated complex networks. Surprisingly enough, in contrast to what has been reported for many biological networks, the clustered neuronal cultures present assortative mixing connectivity values, meaning that there is a preference for clusters to link to other clusters that share similar functional connectivity, as well as a rich-club core, which shapes a 'connectivity backbone' in the network. These results point out that the grouping of neurons and the assortative connectivity between clusters are intrinsic survival mechanisms of the culture.

Preparation and Mechano-Functional Characterization of PEGylated Fibrin Hydrogels: Impact of Thrombin Concentration.

Three-dimensional (3D) neuronal cultures grown in hydrogels are promising platforms to design brain-like neuronal networks in vitro. However, the optimal properties of such cultures must be tuned to ensure a hydrogel matrix sufficiently porous to promote healthy development but also sufficiently rigid for structural support. Such an optimization is difficult since it implies the exploration of different hydrogel compositions and, at the same time, a functional analysis to validate neuronal culture viability. To advance in this quest, here we present a combination of a rheological protocol and a network-based functional analysis to investigate PEGylated fibrin hydrogel networks with gradually higher stiffness, achieved by increasing the concentration of thrombin. We observed that moderate thrombin concentrations of 10% and 25% in volume shaped healthy networks, although the functional traits depended on the hydrogel stiffness, which was much higher for the latter concentration. Thrombin concentrations of 65% or higher led to networks that did not survive. Our results illustrate the difficulties and limitations in preparing 3D neuronal networks, and stress the importance of combining a mechano-structural characterization of a biomaterial with a functional one.

Real-time hardware emulation of neural cultures: A comparative study of in vitro, in silico and in duris silico models.

Biological neural networks are well known for their capacity to process information with extremely low power consumption. Fields such as Artificial Intelligence, with high computational costs, are seeking for alternatives inspired in biological systems. An inspiring alternative is to implement hardware architectures that replicate the behavior of biological neurons but with the flexibility in programming capabilities of an electronic device, all combined with a relatively low operational cost. To advance in this quest, here we analyze the capacity of the HEENS hardware architecture to operate in a similar manner as an in vitro neuronal network grown in the laboratory. For that, we considered data of spontaneous activity in living neuronal cultures of about 400 neurons and compared their collective dynamics and functional behavior with those obtained from direct numerical simulations (in silico) and hardware implementations (in duris silico). The results show that HEENS is capable to mimic both the in vitro and in silico systems with high efficient-cost ratio, and on different network topological designs. Our work shows that compact low-cost hardware implementations are feasible, opening new avenues for future, highly efficient neuromorphic devices and advanced human-machine interfacing.

Model-free reconstruction of excitatory neuronal connectivity from calcium imaging signals.

A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections are characterized by an elevated level of clustering compared to a random graph (although not extreme) and can be markedly non-local.

Rheological Characterization of Three-Dimensional Neuronal Cultures Embedded in PEGylated Fibrin Hydrogels.

Three-dimensional (3D) neuronal cultures are valuable models for studying brain complexity in vitro, and the choice of the bulk material in which the neurons grow is a crucial factor in establishing successful cultures. Indeed, neuronal development and network functionality are influenced by the mechanical properties of the selected material; in turn, these properties may change due to neuron-matrix interactions that alter the microstructure of the material. To advance our understanding of the interplay between neurons and their environment, here we utilized a PEGylated fibrin hydrogel as a scaffold for mouse primary neuronal cultures and carried out a rheological characterization of the scaffold over a three-week period, both with and without cells. We observed that the hydrogels exhibited an elastic response that could be described in terms of the Young's modulus E. The hydrogels without neurons procured a stable E≃420 Pa, while the neuron-laden hydrogels showed a higher E≃590 Pa during the early stages of development that decreased to E≃340 Pa at maturer stages. Our results suggest that neurons and their processes dynamically modify the hydrogel structure during development, potentially compromising both the stability of the material and the functional traits of the developing neuronal network.

344Laser bioprinting of human iPSC-derived neural stem cells and neurons: Effect on cell survival, multipotency, differentiation, and neuronal activity.

Generation of human neuronal networks by three-dimensional (3D) bioprinting is promising for drug testing and hopefully will allow for the understanding of cellular mechanisms in brain tissue. The application of neural cells derived from human induced-pluripotent stem cells (hiPSCs) is an obvious choice, since hiPSCs provide access to cells unlimited in number and cell types that could be generated by differentiation. The questions in this regard include which neuronal differentiation stage is optimal for printing of such networks, and to what extent the addition of other cell types, especially astrocytes, supports network formation. These aspects are the focus of the present study, in which we applied a laser-based bioprinting technique and compared hiPSC-derived neural stem cells (NSCs) with neuronal differentiated NSCs, with and without the inclusion of co-printed astrocytes. In this study, we investigated in detail the effects of cell types, printed droplet size, and duration of differentiation before and after printing on viability, as well as proliferation, stemness, differentiation potential, formation of dendritic extensions and synapses, and functionality of the generated neuronal networks. We found a significant dependence of cell viability after dissociation on differentiation stage, but no impact of the printing process. Moreover, we observed a dependence of the abundance of neuronal dendrites on droplet size, a marked difference between printed cells and normal cell culture in terms of further differentiation of the cells, especially differentiation into astrocytes, as well as neuronal network formation and activity. Notably, there was a clear effect of admixed astrocytes on NSCs but not on neurons.

Long-term calcium imaging reveals functional development in hiPSC-derived cultures comparable to human but not rat primary cultures.

Models for human brain-oriented research are often established on primary cultures from rodents, which fails to recapitulate cellular specificity and molecular cues of the human brain. Here we investigated whether neuronal cultures derived from human induced pluripotent stem cells (hiPSCs) feature key advantages compared with rodent primary cultures. Using calcium fluorescence imaging, we tracked spontaneous neuronal activity in hiPSC-derived, human, and rat primary cultures and compared their dynamic and functional behavior as they matured. We observed that hiPSC-derived cultures progressively changed upon development, exhibiting gradually richer activity patterns and functional traits. By contrast, rat primary cultures were locked in the same dynamic state since activity onset. Human primary cultures exhibited features in between hiPSC-derived and rat primary cultures, although traits from the former predominated. Our study demonstrates that hiPSC-derived cultures are excellent models to investigate development in neuronal assemblies, a hallmark for applications that monitor alterations caused by damage or neurodegeneration.

Modular architecture facilitates noise-driven control of synchrony in neuronal networks.

High-level information processing in the mammalian cortex requires both segregated processing in specialized circuits and integration across multiple circuits. One possible way to implement these seemingly opposing demands is by flexibly switching between states with different levels of synchrony. However, the mechanisms behind the control of complex synchronization patterns in neuronal networks remain elusive. Here, we use precision neuroengineering to manipulate and stimulate networks of cortical neurons in vitro, in combination with an in silico model of spiking neurons and a mesoscopic model of stochastically coupled modules to show that (i) a modular architecture enhances the sensitivity of the network to noise delivered as external asynchronous stimulation and that (ii) the persistent depletion of synaptic resources in stimulated neurons is the underlying mechanism for this effect. Together, our results demonstrate that the inherent dynamical state in structured networks of excitable units is determined by both its modular architecture and the properties of the external inputs.

Neuron-derived extracellular vesicles contain synaptic proteins, promote spine formation, activate TrkB-mediated signalling and preserve neuronal complexity.

Extracellular vesicles (EVs) play an important role in intercellular communication as carriers of signalling molecules such as bioactive miRNAs, proteins and lipids. EVs are key players in the functioning of the central nervous system (CNS) by influencing synaptic events and modulating recipient neurons. However, the specific role of neuron-to-neuron communication via EVs is still not well understood. Here, we provide evidence that primary neurons uptake neuron-derived EVs in the soma, dendrites, and even in the dendritic spines, and carry synaptic proteins. Neuron-derived EVs increased spine density and promoted the phosphorylation of Akt and ribosomal protein S6 (RPS6), via TrkB-signalling, without impairing the neuronal network activity. Strikingly, EVs exerted a trophic effect on challenged nutrient-deprived neurons. Altogether, our results place EVs in the spotlight for synaptic plasticity modulation as well as a possible therapeutic tool to fight neurodegeneration.

Astrocyte dysfunction and neuronal network hyperactivity in a CRISPR engineered pluripotent stem cell model of frontotemporal dementia.

Frontotemporal dementia (FTD) is the second most prevalent type of early-onset dementia and up to 40% of cases are familial forms. One of the genes mutated in patients is CHMP2B, which encodes a protein found in a complex important for maturation of late endosomes, an essential process for recycling membrane proteins through the endolysosomal system. Here, we have generated a CHMP2B-mutated human embryonic stem cell line using genome editing with the purpose to create a human in vitro FTD disease model. To date, most studies have focused on neuronal alterations; however, we present a new co-culture system in which neurons and astrocytes are independently generated from human embryonic stem cells and combined in co-cultures. With this approach, we have identified alterations in the endolysosomal system of FTD astrocytes, a higher capacity of astrocytes to uptake and respond to glutamate, and a neuronal network hyperactivity as well as excessive synchronization. Overall, our data indicates that astrocyte alterations precede neuronal impairments and could potentially trigger neuronal network changes, indicating the important and specific role of astrocytes in disease development.

Critical behavior and axis defining symmetry breaking in Hydra embryonic development.

The formation of a hollow cellular sphere is often one of the first steps of multicellular embryonic development. In the case of Hydra, the sphere breaks its initial symmetry to form a foot-head axis. During this process a gene, ks1, is increasingly expressed in localized cell domains whose size distribution becomes scale-free at the axis-locking moment. We show that a physical model based solely on the production and exchange of ks1-promoting factors among neighboring cells robustly reproduces the scaling behavior as well as the experimentally observed spontaneous and temperature-directed symmetry breaking.

Dynamic and Functional Alterations of Neuronal Networks In Vitro upon Physical Damage: A Proof of Concept.

There is a growing technological interest in combining biological neuronal networks with electronic ones, specifically for biological computation, human-machine interfacing and robotic implants. A major challenge for the development of these technologies is the resilience of the biological networks to physical damage, for instance, when used in harsh environments. To tackle this question, here, we investigated the dynamic and functional alterations of rodent cortical networks grown in vitro that were physically damaged, either by sequentially removing groups of neurons that were central for information flow or by applying an incision that cut the network in half. In both cases, we observed a remarkable capacity of the neuronal cultures to cope with damage, maintaining their activity and even reestablishing lost communication pathways. We also observed-particularly for the cultures cut in half-that a reservoir of healthy neurons surrounding the damaged region could boost resilience by providing stimulation and a communication bridge across disconnected areas. Our results show the remarkable capacity of neuronal cultures to sustain and recover from damage, and may be inspirational for the development of future hybrid biological-electronic systems.

Rich dynamics and functional organization on topographically designed neuronal networks in vitro.

Neuronal cultures are a prominent experimental tool to understand complex functional organization in neuronal assemblies. However, neurons grown on flat surfaces exhibit a strongly coherent bursting behavior with limited functionality. To approach the functional richness of naturally formed neuronal circuits, here we studied neuronal networks grown on polydimethylsiloxane (PDMS) topographical patterns shaped as either parallel tracks or square valleys. We followed the evolution of spontaneous activity in these cultures along 20 days in vitro using fluorescence calcium imaging. The networks were characterized by rich spatiotemporal activity patterns that comprised from small regions of the culture to its whole extent. Effective connectivity analysis revealed the emergence of spatially compact functional modules that were associated with both the underpinned topographical features and predominant spatiotemporal activity fronts. Our results show the capacity of spatial constraints to mold activity and functional organization, bringing new opportunities to comprehend the structure-function relationship in living neuronal circuits.

Involvement of Mechanical Cues in the Migration of Cajal-Retzius Cells in the Marginal Zone During Neocortical Development.

Emerging evidence points to coordinated action of chemical and mechanical cues during brain development. At early stages of neocortical development, angiogenic factors and chemokines such as CXCL12, ephrins, and semaphorins assume crucial roles in orchestrating neuronal migration and axon elongation of postmitotic neurons. Here we explore the intrinsic mechanical properties of the developing marginal zone of the pallium in the migratory pathways and brain distribution of the pioneer Cajal-Retzius cells. These neurons are generated in several proliferative regions in the developing brain (e.g., the cortical hem and the pallial subpallial boundary) and migrate tangentially in the preplate/marginal zone covering the upper portion of the developing cortex. These cells play crucial roles in correct neocortical layer formation by secreting several molecules such as Reelin. Our results indicate that the motogenic properties of Cajal-Retzius cells and their perinatal distribution in the marginal zone are modulated by both chemical and mechanical factors, by the specific mechanical properties of Cajal-Retzius cells, and by the differential stiffness of the migratory routes. Indeed, cells originating in the cortical hem display higher migratory capacities than those generated in the pallial subpallial boundary which may be involved in the differential distribution of these cells in the dorsal-lateral axis in the developing marginal zone.

Development of input connections in neural cultures.

We introduce an approach for the quantitative assessment of the connectivity in neuronal cultures, based on the statistical mechanics of percolation on a graph. This allows us to monitor the development of the culture and to see the emergence of connectivity in the network. The culture becomes fully connected at a time equivalent to the expected time of birth. The spontaneous bursting activity that characterizes cultures develops in parallel with the connectivity. The average number of inputs per neuron can be quantitatively determined in units of m(0), the number of activated inputs needed to excite the neuron. For m(0) approximately 15 we find that hippocampal neurons have on average approximately 60-120 inputs, whereas cortical neurons have approximately 75-150, depending on neuronal density. The ratio of excitatory to inhibitory neurons is determined by using the GABA(A) antagonist bicuculine. This ratio changes during development and reaches the final value at day 7-8, coinciding with the expected time of the GABA switch. For hippocampal cultures the inhibitory cells comprise approximately 30% of the neurons in the culture whereas for cortical cultures they are approximately 20%. Such detailed global information on the connectivity of networks in neuronal cultures is at present inaccessible by any electrophysiological or other technique.