Impact of Physical Obstacles on the Structural and Effective Connectivity of in silico Neuronal Circuits

Electrophysiological features of cortical 3D networks are deeply modulated by scaffold properties

Three-dimensionality (3D) was proven essential for developing reliable models for different anatomical compartments and many diseases. However, the neuronal compartment still poses a great challenge as we still do not understand precisely how the brain computes information and how the complex chain of neuronal events can generate conscious behavior. Therefore, a comprehensive model of neuronal tissue has not yet been found. The present work was conceived in this framework: we aimed to contribute to what must be a collective effort by filling in some information on possible 3D strategies to pursue. We compared directly different kinds of scaffolds (i.e., PDMS sponges, thermally crosslinked hydrogels, and glass microbeads) in their effect on neuronal network activity recorded using micro-electrode arrays. While the overall rate of spiking activity remained consistent, the type of scaffold had a notable impact on bursting dynamics. The frequency, density of bursts, and occurrence of random spikes were all affected. The examination of inter-burst intervals revealed distinct burst generation patterns unique to different scaffold types. Network burst propagation unveiled divergent trends among configurations. Notably, it showed the most differences, underlying that functional variations may arise from a different 3D spatial organization. This evidence suggests that not all 3D neuronal constructs can sustain the same level of richness of activity. Furthermore, we commented on the reproducibility, efficacy, and scalability of the methods, where the beads still offer superior performances. By comparing different 3D scaffolds, our results move toward understanding the best strategies to develop functional 3D neuronal units for reliable pre-clinical studies.

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.

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.

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.

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.

Neuronal Cultures: Exploring Biophysics, Complex Systems, and Medicine in a Dish

Neuronal cultures are one of the most important experimental models in modern interdisciplinary neuroscience, allowing to investigate in a control environment the emergence of complex behavior from an ensemble of interconnected neurons. Here, I review the research that we have conducted at the neurophysics laboratory at the University of Barcelona over the last 15 years, describing first the neuronal cultures that we prepare and the associated tools to acquire and analyze data, to next delve into the different research projects in which we actively participated to progress in the understanding of open questions, extend neuroscience research on new paradigms, and advance the treatment of neurological disorders. I finish the review by discussing the drawbacks and limitations of neuronal cultures, particularly in the context of brain-like models and biomedicine.

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.

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.

In Vitro Development of Human iPSC-Derived Functional Neuronal Networks on Laser-Fabricated 3D Scaffolds

Neural progenitor cells generated from human induced pluripotent stem cells (hiPSCs) are the forefront of ″brain-on-chip″ investigations. Viable and functional hiPSC-derived neuronal networks are shaping powerful in vitro models for evaluating the normal and abnormal formation of cortical circuits, understanding the underlying disease mechanisms, and investigating the response to drugs. They therefore represent a desirable instrument for both the scientific community and the pharmacological industry. However, culture conditions required for the full functional maturation of individual neurons and networks are still unidentified. It has been recognized that three-dimensional (3D) culture conditions can better emulate in vivo neuronal tissue development compared to 2D cultures and thus provide a more desirable in vitro approach. In this paper, we present the design and implementation of a 3D scaffold platform that supports and promotes intricate neuronal network development. 3D scaffolds were produced through direct laser writing by two-photon polymerization (2PP), a high-resolution 3D laser microstructuring technology, using the biocompatible and nondegradable photoreactive resin Dental LT Clear (DClear). Neurons developed and interconnected on a 3D environment shaped by vertically stacked scaffold layers. The developed networks could support different cell types. Starting at the day 50 of 3D culture, neuronal progenitor cells could develop into cortical projection neurons (CNPs) of all six layers, different types of inhibitory neurons, and glia. Additionally and in contrast to 2D conditions, 3D scaffolds supported the long-term culturing of neuronal networks over the course of 120 days. Network health and functionality were probed through calcium imaging, which revealed a strong spontaneous neuronal activity that combined individual and collective events. Taken together, our results highlight advanced microstructured 3D scaffolds as a reliable platform for the 3D in vitro modeling of neuronal functions.