The computational brain: Patricia S. Churchland and Terrence J. Sejnowski (MIT Press, Cambridge, MA, 1992); xi, 544 pages, $39.95

All-optical electrophysiology—spatially resolved simultaneous optical perturbation and measurement of membrane voltage—would open new vistas in neuroscience research. We evolved two archaerhodopsin-based voltage indicators, QuasAr1 and QuasAr2, which show improved brightness and voltage sensitivity, have microsecond response times and produce no photocurrent. We engineered a channelrhodopsin actuator, CheRiff, which shows high light sensitivity and rapid kinetics and is spectrally orthogonal to the QuasArs. A coexpression vector, Optopatch, enabled cross-talk–free genetically targeted all-optical electrophysiology. In cultured rat neurons, we combined Optopatch with patterned optical excitation to probe back-propagating action potentials (APs) in dendritic spines, synaptic transmission, subcellular microsecond-timescale details of AP propagation, and simultaneous firing of many neurons in a network. Optopatch measurements revealed homeostatic tuning of intrinsic excitability in human stem cell–derived neurons. In rat brain slices, Optopatch induced and reported APs and subthreshold events with high signal-to-noise ratios. The Optopatch platform enables high-throughput, spatially resolved electrophysiology without the use of conventional electrodes.

All-optical electrophysiology in mammalian neurons using engineered microbial rhodopsins

Abstract. This paper introduces a new frequency-domain approach to describe the relationships (direction of information flow) between multivariate time series based on the decomposition of multivariate partial coherences computed from multivariate autoregressive models. We discuss its application and compare its performance to other approaches to the problem of determining neural structure relations from the simultaneous measurement of neural electrophysiological signals. The new concept is shown to reflect a frequency-domain representation of the concept of Granger causality.

Partial directed coherence: a new concept in neural structure determination

The brain is the most sophisticated and complex organ that nature has devised. Neurons are the functional basic component of the nervous system. Cell bodies of cortical neurons are arranged in layers and each layer has complex diversity of neuronal subtypes. This complex specialization follows a coordinated temporal pattern that emerges through the specification of different subtypes of cortical neurons. This in turn populates the various cortical layers, where these neurons exhibit specific patterns of gene expression and connectivity.

An organoid is a three-dimensional organ-bud that is grown in vitro. There are various types of organoid, one of which is cerebral organoid, which is a miniature organ resembling the brain. These organoid are created using human pluripotent stem cells (cells that have ability to form any adult cell type). The purpose of creating these organoids is to be able to study various disease models in a simple, variable space, free of various in-vivo limitations (especially working with humans).

Some basic steps to creating cerebral organoid start with taking human pluripotent stem cells, cultivating them, inducing various nerve growth factors, fixating in a gel environment and then using bioreactor to spin. There are variety of ways to do testing of these organoid, using gene expression and functional characterization.

The first demonstration of efficient generation of cortical neurons in vitro took place in 2008, where authors presented the evidence that a complex self-organized cytoarchitecture can emerge in a purely in vitro setting3,4. There has been amazing progress in the field of organoids over past few years.

In a recent Nature methods paper relating to “Brains in a petri dish”, the authors developed a new streamlined method for inducing pluripotent stem cells to form cortex-like organoids (Figure 1), which include neurons supported by network of glial cells. Authors used an in vitro neural differentiation approach, where human cortical spheroids (hCSs) are maintained in floating conditions on low-attachment plates with biweekly changes of regular serum-free media. This system can be easily maintained for up to 9 months in vitro. Thus, authors were able to create functional and realistic layers of neurons that talk to each other in complex networks.



Figure 1

Generation of human cortical spheroids [Image courtesy of Dr. Pasca2]



Figure 1 is the schematic representation of the main stages during the process of creation of hCS. Authors used low attachment plates for the suspended colonies. Authors used both BMP and TGF signaling pathways to achieve rapid and efficient neural induction. At 6th day, EGF was added and at 25th day, BDNF was added. Medium was changed very frequently. These hCS grew to 300 microns in diameter by 2 weeks of culture and then reached 45 mm in diameter by 2.5 months. To help characterize these hCS, the authors used many functional classification techniques2. They studied the functional characterization of the neurons by using fura-2 (calcium) imaging and panels of antibodies in the human fetal cortex. This system of 3D network was also amenable to slice physiology techniques. The authors performed whole cell recordings and found that almost 80% of the cells fired action potentials in response to depolarizing current steps.

There have been other techniques used in the past for developing differentiating pluripotent stem cells into cortical neurons. Some examples include neural induction in high-density monolayer cultures, embedding clusters of hiPSCs in gelatinous protein mixtures (such as Matrigel) and later culturing them in a spinning bioreactor, using embryoid bodies derived from hiPSCs that are plated on coated surfaces to generate neural progenitors2,5–7.

In 2013, Lancaster et. al. in order to recapitulate features of human cortical development, namely characteristic progenitor zone organization with abundant outer radial glial stem cells, developed cerebral organoids that had similar development as in human brain6. The authors also used these cerebral organoid to model microcephaly defect (which has been difficult in model in mice) that could help explain various disease phenotypes.

In 2015, Maguruma and colleagues developed a method to generate neurons of the cerebellum by 3D culture of human embryonic stem cells with sequential addition of growth factors7.

In the paper on Cortical Neurogenesis (complexity emerging from simplicity)5, authors modeled spatial and temporal patterns of corticogenesis (see figure 2). These 3 D models could recapitulate similarity to in-vivo organization of cortical structure. Following paragraphs talk about the potential applications of organoid for various disease models.



Figure 2

Temporal and Spatial modeling cortical neuron neurogenesis [Image courtesy of Dr. Anderson5]



Timothy syndrome (TS), a development delay disorder caused by a mutation in a L-type voltage-gated calcium channel, can cause autism. The iPSC derived cortical cells from TS patient led to revelation about defects in calcium signaling and neuronal activity, and defects in the generation of specific types of neurons8.

Pluripotent stem cells were used to identify the lysosomal alterations in Gaucher disease (GD) neurons (genetic disease in which fatty substances accumulate in cells and certain organs). It was found that the lysosomal alterations described were caused by the GBA1-associated neurodegeneration9.

Anand and his group have already taken the application of these corticoids to Alzheimer’s and Autism research1. Authors have filed an invention disclosure and are seeking an IP, so they were unable to disclose the methods. Figure 3 shows an image of an organoid. When, I asked the author about the potential of this work and timeline, his response was “Potential is enormous. The models will accelerate research and drug discovery and more accurately predict efficacy of drugs in human clinical trials, and a lot lower cost. Timelines will vary based on the subtype of a disease under consideration (most brain diseases and disorders are syndromes with different causes, though some may converge on a pathway)”.



Figure 3

Image of an organoid [Courtesy of The Ohio State University1]



Gulf War illness is considered to be the outcome of the use of organophosphate pesticides [permethrin (PM) and N,Ndiethyl-m-toluamide (DEET)], daily prophylactic anti-cholinesterase pyridostigmine bromide (PB), and stress. It is also shown to cause reduction of hippocampal column and brain gray matter. Organoid can be used to evaluate the pathobiology of these noxious chemical on human brain development.

A Brain in a Dish.

Recent advancements have been made in the development of cell-based in-vitro neuronal networks, or organoids. In order to better understand the network structure of these organoids, [6] propose a method for inferring effective connectivity networks from multi-electrode array data. In this paper, a novel statistical method called spectral mirror estimation [2] is applied to a time series of inferred effective connectivity organoid networks. This method produces a one-dimensional iso-mirror representation of the dynamics of the time series of the networks. A classical change point algorithm is then applied to this representation, which successfully detects a neuroscientiﬁcally signiﬁcant change point coinciding with the time inhibitory neurons start appearing and the percentage of astrocytes increases dramatically [9]. This ﬁnding demonstrates the potential utility of applying the iso-mirror dynamic structure discovery method to inferred effective connectivity time series of organoid networks.

Discovering a change point in a time series of organoid networks via the iso-mirror

Despite advancements in the development of cell-based in-vitro neuronal network models, the lack of appropriate computational tools limits their analyses. Methods aimed at deciphering the effective connections between neurons from extracellular spike recordings would increase utility of in-vitro lo- cal neural circuits, especially for studies of human neural development and disease based on induced pluripotent stem cells (hiPSC). Current techniques allow statistical inference of functional couplings in the network but are fundamentally unable to correctly identify indirect and apparent connections between neurons, generating redundant maps with limited ability to model the causal dynamics of the network. In this paper, we describe a novel mathematically rigorous, model-free method to map effective - direct and causal - connectivity of neuronal networks from multi-electrode array data. The inference algorithm uses a combination of statistical and deterministic indicators which, first, enables identification of all existing functional links in the network and then, reconstructs the directed and causal connection diagram via a super-selective rule enabling highly accurate classification of direct, indirect and apparent links. Our method can be generally applied to the functional characterization of any in-vitro neuronal networks. Here, we show that, given its accuracy, it can offer important insights into the functional development of in-vitro iPSC-derived neuronal cultures by reconstructing their effective connectivity, thus facilitating future efforts to generate predictive models for neurological disorders, drug testing and neuronal network modeling.

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Anne Bang

Papers

Super-selective reconstruction of causal and direct connectivity with application to in-vitro iPSC neuronal networks