Detection of neuronal interactions using correlation analysis

Dual effects of ARX poly-alanine mutations in human cortical and interneuron development

Infantile spasms, with an incidence of 1.6 to 4.5 per 10,000 live births, are a relentless and devastating childhood epilepsy marked by severe seizures but also leads to lifelong intellectual disability. Alarmingly, up to 5% of males with this condition carry a mutation in the Aristaless-related homeobox ( ARX ) gene. Our current lack of human-specific models for developmental epilepsy, coupled with discrepancies between animal studies and human data, underscores the gap in knowledge and urgent need for innovative human models, organoids being one of the best available. Here, we used human neural organoid models, cortical organoids (CO) and ganglionic eminences organoids (GEO) which mimic cortical and interneuron development respectively, to study the consequences of PAE mutations, one of the most prevalent mutation in ARX . ARX PAE produces a decrease expression of ARX in GEOs, and an enhancement in interneuron migration. That accelerated migration is cell autonomously driven, and it can be rescued by inhibiting CXCR4. We also found that PAE mutations result in an early increase in radial glia cells and intermediate progenitor cells, followed by a subsequent loss of cortical neurons at later timepoints. Moreover, ARX expression is upregulated in COs derived from patients at 30 DIV and is associated with alterations in the expression of CDKN1C . Furthermore, ARX PAE assembloids had hyperactivity which were evident at early stages of development. With effective treatments for infantile spasms and developmental epilepsies still elusive, delving into the role of ARX PAE mutations in human brain organoids represents a pivotal step toward uncovering groundbreaking therapeutic strategies.

Fast whole-brain imaging of seizures in zebrafish larvae by two-photon light-sheet microscopy

Light-sheet fluorescence microscopy (LSFM) enables real-time whole-brain functional imaging in zebrafish larvae. Conventional one-photon LSFM can however induce undesirable visual stimulation due to the use of visible excitation light. The use of two-photon (2P) excitation, employing near-infrared invisible light, provides unbiased investigation of neuronal circuit dynamics. However, due to the low efficiency of the 2P absorption process, the imaging speed of this technique is typically limited by the signal-to-noise-ratio. Here, we describe a 2P LSFM setup designed for non-invasive imaging that enables quintuplicating state-of-the-art volumetric acquisition rate of the larval zebrafish brain (5 Hz) while keeping low the laser intensity on the specimen. We applied our system to the study of pharmacologically-induced acute seizures, characterizing the spatial-temporal dynamics of pathological activity and describing for the first time the appearance of caudo-rostral ictal waves (CRIWs).

MEAnalyzer - a Spike Train Analysis Tool for Multi Electrode Arrays

Despite a multitude of commercially available multi-electrode array (MEA) systems that are each capable of rapid data acquisition from cultured neurons or slice cultures, there is a general lack of available analysis tools. These analysis gaps restrict the efficient extraction of meaningful physiological features from data sets, and limit interpretation of how experimental manipulations modify neural network activity. Here, we present the development of a user-friendly, publicly-available software called MEAnalyzer. This software contains several spike train analysis methods including relevant statistical calculations, periodicity analysis, functional connectivity analysis, and advanced data visualizations in a user-friendly graphical user interface that requires no coding from the user. Widespread availability of this user friendly and mathematically advanced program will stimulate and enhance the use of MEA technologies.

The effect of pharmacological inhibition of Serine Proteases on neuronal networks in vitro

Neurons are embedded in an extracellular matrix (ECM), which functions both as a scaffold and as a regulator of neuronal function. The ECM is in turn dynamically altered through the action of serine proteases, which break down its constituents. This pathway has been implicated in the regulation of synaptic plasticity and of neuronal intrinsic excitability. In this study, we determined the short-term effects of interfering with proteolytic processes in the ECM, with a newly developed serine protease inhibitor. We monitored the spontaneous electrophysiological activity of in vitro primary rat cortical cultures, using microelectrode arrays. While pharmacological inhibition at a low dosage had no significant effect, at elevated concentrations it altered significantly network synchronization and functional connectivity but left unaltered single-cell electrical properties. These results suggest that serine protease inhibition affects synaptic properties, likely through its actions on the ECM.

Connectivity inference from neural recording data: Challenges, mathematical bases and research directions

This article presents a review of computational methods for connectivity inference from neural activity data derived from multi-electrode recordings or fluorescence imaging. We first identify biophysical and technical challenges in connectivity inference along the data processing pipeline. We then review connectivity inference methods based on two major mathematical foundations, namely, descriptive model-free approaches and generative model-based approaches. We investigate representative studies in both categories and clarify which challenges have been addressed by which method. We further identify critical open issues and possible research directions.

ToolConnect: A Functional Connectivity Toolbox for In vitro Networks

Nowadays, the use of in vitro reduced models of neuronal networks to investigate the interplay between structural-functional connectivity and the emerging collective dynamics is a widely accepted approach. In this respect, a relevant advance for this kind of studies has been given by the recent introduction of high-density large-scale Micro-Electrode Arrays (MEAs) which have favored the mapping of functional connections and the recordings of the neuronal electrical activity. Although, several toolboxes have been implemented to characterize network dynamics and derive functional links, no specifically dedicated software for the management of huge amount of data and direct estimation of functional connectivity maps has been developed. toolconnect offers the implementation of up to date algorithms and a user-friendly Graphical User Interface (GUI) to analyze recorded data from large scale networks. It has been specifically conceived as a computationally efficient open-source software tailored to infer functional connectivity by analyzing the spike trains acquired from in vitro networks coupled to MEAs. In the current version, toolconnect implements correlation- (cross-correlation, partial-correlation) and information theory (joint entropy, transfer entropy) based core algorithms, as well as useful and practical add-ons to visualize functional connectivity graphs and extract some topological features. In this work, we present the software, its main features and capabilities together with some demonstrative applications on hippocampal recordings.

From functional to structural connectivity using partial correlation in neuronal assemblies

OBJECTIVE

Our goal is to re-introduce an optimized version of the partial correlation to infer structural connections from functional-effective ones in dissociated neuronal cultures coupled to microelectrode arrays.

APPROACH

We first validate our partialization procedure on in silico networks, mimicking different experimental conditions (i.e., different connectivity degrees and number of nodes) and comparing the partial correlation's performance with two gold-standard methods: cross-correlation and transfer entropy. Afterwards, to infer the structural connections in in vitro neuronal networks where the ground truth is unknown, we propose a thresholding heuristic approach. Then, to validate whether the partialization process correctly reconstructs macroscopic features of the network structure, we extract a modularity index from segregated in silico and in vitro models. Finally, as a case study, we apply our partialization procedure to analyze connectivity and topology on spontaneous developing and electrically stimulated in vitro cultures.

MAIN RESULTS

In simulated networks, partial correlation outperforms cross-correlation and transfer entropy at low and medium connectivity degrees, not only in relatively small (60 nodes) but also in larger (120-240 nodes) assemblies. Furthermore, partial correlation correctly identifies interconnected neuronal sub-populations and allows one to derive network topology in in vitro cortical networks.

SIGNIFICANCE

Our results support the idea that partial correlation is a good method for connectivity studies and can be applied to derive topological and structural features of neuronal assemblies.

Functional connectivity in in vitro neuronal assemblies

Complex network topologies represent the necessary substrate to support complex brain functions. In this work, we reviewed in vitro neuronal networks coupled to Micro-Electrode Arrays (MEAs) as biological substrate. Networks of dissociated neurons developing in vitro and coupled to MEAs, represent a valid experimental model for studying the mechanisms governing the formation, organization and conservation of neuronal cell assemblies. In this review, we present some examples of the use of statistical Cluster Coefficients and Small World indices to infer topological rules underlying the dynamics exhibited by homogeneous and engineered neuronal networks.

Selective pharmacological manipulation of cortical-thalamic co-cultures in a dual-compartment device

In this study, we demonstrate capabilities to selectively manipulate dissociated co-cultures of neurons plated in dual-compartment devices. Synaptic receptor antagonists and tetrodotoxin solutions were used to selectively control and study the network-wide burst propagation and cell firing in cortical-cortical and cortical-thalamic co-culture systems. The results show that in cortical-thalamic dissociated co-cultures, burst events initiate in the cortical region and propagate to the thalamic region and the burst events in thalamic region can be controlled by blocking the synaptic receptors in the cortical region. Whereas, in cortical-cortical co-culture system, one of the region acts as a site of burst initiation and facilitate propagation of bursts in the entire network. Tetrodotoxin, a sodium channel blocker, when applied to either of the regions blocks the firing of neurons in that particular region with significant influence on the firing of neurons in the other region. The results demonstrate selective pharmacological manipulation capabilities of co-cultures in a dual compartment device and helps understand the effects of neuroactive compounds on networks derived from specific CNS tissues and the dynamic interaction between them.

Multiscale functional connectivity estimation on low-density neuronal cultures recorded by high-density CMOS Micro Electrode Arrays

We used electrophysiological signals recorded by CMOS Micro Electrode Arrays (MEAs) at high spatial resolution to estimate the functional-effective connectivity of sparse hippocampal neuronal networks in vitro by applying a cross-correlation (CC) based method and ad hoc developed spatio-temporal filtering. Low-density cultures were recorded by a recently introduced CMOS-MEA device providing simultaneous multi-site acquisition at high-spatial (21 μm inter-electrode separation) as well as high-temporal resolution (8 kHz per channel). The method is applied to estimate functional connections in different cultures and it is refined by applying spatio-temporal filters that allow pruning of those functional connections not compatible with signal propagation. This approach permits to discriminate between possible causal influence and spurious co-activation, and to obtain detailed maps down to cellular resolution. Further, a thorough analysis of the links strength and time delays (i.e., amplitude and peak position of the CC function) allows characterizing the inferred interconnected networks and supports a possible discrimination of fast mono-synaptic propagations, and slow poly-synaptic pathways. By focusing on specific regions of interest we could observe and analyze microcircuits involving connections among a few cells. Finally, the use of the high-density MEA with low density cultures analyzed with the proposed approach enables to compare the inferred effective links with the network structure obtained by staining procedures.

NETWORK DYNAMICS AND SYNCHRONOUS ACTIVITY IN CULTURED CORTICAL NEURONS

Neurons extracted from specific areas of the Central Nervous System (CNS), such as the hippocampus, the cortex and the spinal cord, can be cultured in vitro and coupled with a micro-electrode array (MEA) for months. After a few days, neurons connect each other with functionally active synapses, forming a random network and displaying spontaneous electrophysiological activity. In spite of their simplified level of organization, they represent an useful framework to study general information processing properties and specific basic learning mechanisms in the nervous system. These experimental preparations show patterns of collective rhythmic activity characterized by burst and spike firing. The patterns of electrophysiological activity may change as a consequence of external stimulation (i.e., chemical and/or electrical inputs) and by partly modifying the "randomness" of the network architecture (i.e., confining neuronal sub-populations in clusters with micro-machined barriers). In particular we investigated how the spontaneous rhythmic and synchronous activity can be modulated or drastically changed by focal electrical stimulation, pharmacological manipulation and network segregation. Our results show that burst firing and global synchronization can be enhanced or reduced; and that the degree of synchronous activity in the network can be characterized by simple parameters such as cross-correlation on burst events.

A new cross-correlation algorithm for the analysis of "in vitro" neuronal network activity aimed at pharmacological studies

Modern drug discovery for Central Nervous System pathologies has recently focused its attention to in vitro neuronal networks as models for the study of neuronal activities. Micro Electrode Arrays (MEAs), a widely recognized tool for pharmacological investigations, enable the simultaneous study of the spiking activity of discrete regions of a neuronal culture, providing an insight into the dynamics of networks. Taking advantage of MEAs features and making the most of the cross-correlation analysis to assess internal parameters of a neuronal system, we provide an efficient method for the evaluation of comprehensive neuronal network activity. We developed an intra network burst correlation algorithm, we evaluated its sensitivity and we explored its potential use in pharmacological studies. Our results demonstrate the high sensitivity of this algorithm and the efficacy of this methodology in pharmacological dose-response studies, with the advantage of analyzing the effect of drugs on the comprehensive correlative properties of integrated neuronal networks.

Evaluation of the performance of information theory-based methods and cross-correlation to estimate the functional connectivity in cortical networks

Functional connectivity of in vitro neuronal networks was estimated by applying different statistical algorithms on data collected by Micro-Electrode Arrays (MEAs). First we tested these "connectivity methods" on neuronal network models at an increasing level of complexity and evaluated the performance in terms of ROC (Receiver Operating Characteristic) and PPC (Positive Precision Curve), a new defined complementary method specifically developed for functional links identification. Then, the algorithms better estimated the actual connectivity of the network models, were used to extract functional connectivity from cultured cortical networks coupled to MEAs. Among the proposed approaches, Transfer Entropy and Joint-Entropy showed the best results suggesting those methods as good candidates to extract functional links in actual neuronal networks from multi-site recordings.

Dissociated cortical networks show spontaneously correlated activity patterns during in vitro development

In vitro cultured neuronal networks coupled to microelectrode arrays (MEAs) constitute a valuable experimental model for studying changes in the neuronal dynamics at different stages of development. After a few days in culture, neurons start to connect each other with functionally active synapses, forming a random network and displaying spontaneous electrophysiological activity. The patterns of collective rhythmic activity change in time spontaneously during in vitro development. Such activity-dependent modifications play a key role in the maturation of the network and reflect changes in the synaptic efficacy, fact widely recognized as a cellular basis of learning, memory and developmental plasticity. Getting advantage from the possibilities offered by the MEAs, the aim of our study is to analyze and characterize the natural changes in dynamics of the electrophysiological activity at different ages of the culture, identifying peculiar steps of the spontaneous evolution of the network. The main finding is that between the second and the third week of culture, the network completely changes its electrophysiological patterns, both in terms of spiking and bursting activity and in terms of cross-correlation between pairs of active channels. Then the maturation process can be characterized by two main phases: modulation and shaping in the synaptic functional connectivity of the network (within the first and second week) and general moderate correlated activity, spread over the entire network, with connections properly formed and stabilized (within the fourth and fifth week).

Physiological aspects of information processing in the basal ganglia of normal and parkinsonian primates

There are two views as to the character of basal-ganglia processing - processing by segregated parallel circuits or by information sharing. To distinguish between these views, we studied the simultaneous activity of neurons in the output stage of the basal ganglia with cross-correlation techniques. The firing of neurons in the globus pallidus of normal monkeys is almost always uncorrelated. However, after dopamine depletion and induction of parkinsonism by treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), oscillatory activity appeared and the firing of many neurons became correlated. We conclude that the normal dopaminergic system supports segregation of the functional subcircuits of the basal ganglia, and that a breakdown of this independent processing is a hallmark of Parkinson's disease.

NEUROLAB, a comprehensive program for the analysis of neurophysiological and behavioural data

A comprehensive and versatile computer software for IBM-compatible microcomputers has been developed. It is designed for quantitative off-line analysis of A/D-sampled intracellular or extracellular recordings and behavioural or stimulus data. The program works with single files or file sets. It supports data to be viewed on the monitor and allows sectioning of interesting data for common analysis. It offers 19 filters/operators for data processing and comprehensive possibilities to set and calculate trigger points. Data of trigger points can be exported as ASCII files. Standard neurophysiological histograms like interval-, PST-, phase histograms or auto- and cross-correlograms can be obtained. Time-dependent and phase-dependent averaging is possible for all original and filtered data. All graphical output on the display can directly be copied to a plotter/laser printer or HP-GL file by keyboard commands.

Separation of synaptic and spike activity in intracellular recordings for selective analysis

A software spike filter has been developed which allows the separation of synaptic activity and action potentials in intracellular recordings. The algorithm uses the different velocities of the membrane potential during synaptic and spike activity and a time window to identify action potentials. When spikes are recognized, they are removed and the membrane potential is substituted by interpolated values. The spike filter makes possible a separate quantitative evaluation of postsynaptic potentials and spike activity. Thus a comprehensive characterization of neuron activity can be obtained. The spike filter is part of a modular software package designed for the evaluation of neurobiological data.

Effect of harmaline on cells of the inferior olive in the absence of tremor: differential response of genetically dystonic and harmaline-tolerant rats

The genetically dystonic rat is insensitive to the tremorogenic effects of harmaline. This behavioral deficit has been linked to a defect in the olivocerebellar pathway, since few Purkinje cells of dystonic rats show a normal increase in rhythmic complex spike activity following harmaline. In normal rats, the Purkinje cell response to harmaline and tremor are initiated by a rhythmic increase in neuronal firing in the caudal inferior olive. The present single unit recording study was conducted, therefore, to determine if the inferior olive of the dystonic rat is activated by harmaline. Olivary unit responses to harmaline were also examined in normal rats made tolerant to harmaline tremor. These rats are behaviorally insensitive to harmaline and also fail to display rhythmic complex spike activity but do not have the motor deficits of the mutant rats. The spontaneous firing rate of neurons in the caudal and rostral inferior olive of the dystonic rat was significantly slower than that of phenotypically normal littermates. Despite this, all cells recorded in the caudal portion of the medial accessory olive of both dystonic and normal rats showed increased rhythmic activity following harmaline injection. Thus, the failure of the mutants to show harmaline tremor is not due to a failure of the drug to activate cells in the olive. Rather, the data suggest a defect in the subsequent transmission of this information. Unlike the control and dystonic rats, harmaline-tolerant rats failed to show sustained rhythmic activity in the inferior olive. These findings suggest that chronic treatment with harmaline may interfere with harmaline tremor at the level of the inferior olive.

Purkinje cell activity in rats following chronic treatment with harmaline

Harmaline and related alkaloids produce a fine, generalized motor tremor with a frequency of 8-14 Hz in many mammalian species. The tremor is though to be initiated by the synchronous activation of cells in the inferior olive. Repeated administration of the drug at tremorogenic doses results in the rapid development of tolerance in the rat. Since the generation of cerebellar cyclic 3',5'-guanosine monophosphate by harmaline or apomorphine is reduced in harmaline-tolerant rats, it is possible that the site of tolerance is the olivocerebellar system. The present study used extracellular single unit recording techniques to determine whether harmaline tolerance was associated with changes in the firing patterns of Purkinje cells in the cerebellar vermis of the rat. In non-tolerant animals, the majority (8/13) of Purkinje cells recorded in the vermis responded to harmaline with a rhythmic increase in complex spike rate and a prolonged suppression of simple spikes. In harmaline-tolerant animals, only one cell in 14 could be identified that showed this response. In these animals, a variety of responses not encountered in experimentally naive animals were observed. Since the complex spike activity of Purkinje cells is presumed to reflect the activity of climbing fibers originating in the cells of the inferior olive, the results of the studies reported here support the conclusion that a reduction in the synchronous activation of cells at the olivocerebellar level blocks the appearance of tremor in harmaline-tolerant animals.

Conditional cross-interval correlation analyses with applications to simultaneously recorded cerebellar Purkinje neurons

Two conditional cross-correlation techniques are described for the analysis of two simultaneously recorded neuronal spike trains. The conditional interspike interval histogram describes the distribution of interspike intervals of a neuron conditioned by a preceding spike in another neuron. The conditional cross-interval histogram describes the distribution of cross-intervals of two neurons conditioned by a preceding spike in one of the neurons. These techniques could be used to reveal the temporal coupling in the discharge of two neurons recorded simultaneously. The techniques augment the description of the correlation obtained with conventional cross-correlation measures. When applied to the simple spike discharge of simultaneously recorded cerebellar Purkinje neurons, the methods reveal temporal interactions between neurons that are not readily apparent from conventional cross-correlograms. The patterns observed suggest a tightly coupled, temporal surround-inhibition among nearby Purkinje neurons.

Reticular formation of the lower brainstem. A common system for cardio-respiratory and somatomotor functions. Cross-correlation analysis of discharge patterns of neighbouring neurones

Temporal relations of discharges of 73 pairs of neurones located in the medial parts of the reticular formation of the lower brainstem were studied by cross correlation analyses in chloralose-urethane anaesthetized dogs. The action potentials of 2 or 3 neighbouring neurones were recorded with one electrode simultaneously. Uncorrelated discharges of neurones and 4 different types of correlated discharges were observed in cross correlation histograms: they were: (1) rhythmic couplings with frequencies between 2 and 5 Hz related to the same rhythm in the EEG; (2) strong, non-rhythmic couplings with short latencies up to 5 ms; (3) a combination of strong and rhythmic couplings, and (4) high-frequency oscillation couplings. Most pairs of neurones showed different types of correlation during the recordings. The different forms of correlated discharge behaviour could be related to different types of functional organization of the neuronal network in the reticular formation.

Computer assisted analysis of relations between single-unit activity and spontaneous EEG

Two mutually complementary computer methods are described which can be used for the study of unit-EEG relationships during spontaneous EEG waves. The first one consists of using the unit activity to trigger the averaging of sections of EEG preceding and following each unit; the same unit activity is used for building a histogram of unit firing from another cell. Sections of data subjected to this analysis need not be continuous; they may be chosen interactively on the computer terminal, thus allowing to analyze intermittent phenomena. The second method consists of using a particular point of an EEG wave to trigger EEG averages from other channels as well as unit histograms. Here again the waves are chosen interactively. The unit-triggered EEG averages are more objective and less time consuming. However, they do not describe accurately the characteristics of the individual wave to which a unit firing is associated and also they give no information about inhibitory phenomena. Both these drawbacks are corrected by the wave-triggered unit histograms where the experimenter interactively selects and stores for analysis EEG waves with the appropriate characteristics. Several examples are given from the utilization of these programs in neurophysiological and neuropharmacological experiments, with special emphasis on generalized epilepsy.

Short time scale interactions between brain stem neurons with sympathetic nerve-related activity

Cross-correlation analysis revealed short time scale (ms) interactions between closely adjacent cat brain stem neurons with sympathetic nerve-related activity. The incidence of such interactions was significantly greater for reticular neurons than for raphe neurons. Shared input and/or interconnection via mono- or oligosynaptic pathways are considered as mechanisms for synchronization of the discharges of elements of the brain stem network which controls sympathetic nerve activity.