John M. Beggs

• PhD
• Professor (Full) at Indiana University Bloomington

Most of the recent work in psychedelic neuroscience has been done using noninvasive neuroimaging, with data recorded from the brains of adult volunteers under the influence of a variety of drugs. While these data provide holistic insights into the effects of psychedelics on whole-brain dynamics, the effects of psychedelics on the mesoscale dynamics...

A simple model is used to simulate seizures in a population of spiking excitatory neurons experiencing a uniform effect from inhibitory neurons. A key feature is introduced into the model, i.e., a mechanism that weakens the firing thresholds. This weakening mechanism adds memory to the dynamics. We find a seizure-prone state in a “mode-switching” p...

Motivated by the unexplored potential of in vitro neural systems for computing and by the corresponding need of versatile, scalable interfaces for multimodal interaction, an accurate, modular, fully customizable, and portable recording/stimulation solution that can be easily fabricated, robustly operated, and broadly disseminated is presented. This...

A new statistical analysis of large neuronal avalanches observed in mouse and rat brain tissues reveals a substantial degree of recurrent activity and cyclic patterns of activation not seen in smaller avalanches. To explain these observations, we adapted a model of structural weakening in materials. In this model, dynamical weakening of neuron firi...

Aging impacts the brain's structural and functional organization and over time leads to various disorders, such as Alzheimer's disease and cognitive impairment. The process also impacts sensory function, bringing about a general slowing in various perceptual and cognitive functions. Here, we analyze the Cambridge Centre for Ageing and Neuroscience...

The hypothesis that living neural networks operate near a critical phase transition point has received substantial discussion. This “criticality hypothesis” is potentially important because experiments and theory show that optimal information processing and health are associated with operating near the critical point. Despite the promise of this id...

Ageing impacts the brain's structural and functional organization and over time leads to various disorders, such as Alzheimer's disease and cognitive impairment. The process also impacts sensory function, bringing about a general slowing in various perceptual and cognitive functions. Here, we analyze the Cambridge Centre for Ageing and Neuroscience...

How the cerebral cortex operates near a critical phase transition point for optimum performance. Individual neurons have limited computational powers, but when they work together, it is almost like magic. Firing synchronously and then breaking off to improvise by themselves, they can be paradoxically both independent and interdependent. This happen...

The varied cognitive abilities and rich adaptive behaviors enabled by the animal nervous system are often described in terms of information processing. This framing raises the issue of how biological neural circuits actually process information, and some of the most fundamental outstanding questions in neuroscience center on understanding the mecha...

Activity-dependent self-organization plays an important role in the formation of specific and stereotyped connectivity patterns in neural circuits. By combining neuronal cultures, and tools with approaches from network neuroscience and information theory, we can study how complex network topology emerges from local neuronal interactions. We constru...

Activity-dependent self-organization plays an important role in the formation of specific and stereotyped connectivity patterns in neural circuits. By combining neuronal cultures, tools with approaches from network neuroscience and information theory, we can study how complex network topology emerges from local neuronal interactions. We constructed...

The directionality of network information flow dictates how networks process information. A central component of information processing in both biological and artificial neural networks is their ability to perform synergistic integration–a type of computation. We established previously that synergistic integration varies directly with the strength...

Functional networks of cortical neurons contain highly interconnected hubs, forming a rich-club structure. However, the cell type composition within this distinct subnetwork and how it influences large-scale network dynamics is unclear. Using spontaneous activity recorded from hundreds of cortical neurons in orbitofrontal cortex of awake behaving m...

Much evidence seems to suggest the cortex operates near a critical point, yet a single set of exponents defining its universality class has not been found. In fact, when critical exponents are estimated from data, they widely differ across species, individuals of the same species, and even over time, or depending on stimulus. Interestingly, these e...

Whether the brain operates at a critical “tipping” point is a long standing scientific question, with evidence from both cellular and systems-scale studies suggesting that the brain does sit in, or near, a critical regime. Neuroimaging studies of humans in altered states of consciousness have prompted the suggestion that maintenance of critical dyn...

Objective. Many neural systems display spontaneous, spatiotemporal patterns of neural activity that are crucial for information processing. While these cascading patterns presumably arise from the underlying network of synaptic connections between neurons, the precise contribution of the network’s local and global connectivity to these patterns and...

Much evidence seems to suggest cortex operates near a critical point, yet a single set of exponents defining its universality class has not been found. In fact, when critical exponents are estimated from data, they widely differ across species, individuals of the same species, and even over time, or depending on stimulus. Interestingly, these expon...

Detecting synaptic connections using large-scale extracellular spike recordings presents a statistical challenge. While previous methods often treat the detection of each putative connection as a separate hypothesis test, here we develop a modeling approach that infers synaptic connections while incorporating circuit properties learned from the who...

The directionality of network information flow dictates how networks process information. A central component of information processing in both biological and artificial neural networks is their ability to perform synergistic integration–a type of computation. We established previously that synergistic integration varies directly with the strength...

Neural information processing is widely understood to depend on correlations in neuronal activity. However, whether correlation is favorable or not is contentious. Here, we sought to determine how correlated activity and information processing are related in cortical circuits. Using recordings of hundreds of spiking neurons in organotypic cultures...

Whether the brain operates at a critical ‘‘tipping” point is a long standing scientific question, with evidence from both cellular and systems-scale studies suggesting that the brain does sit in, or near, a critical regime. Neuroimaging studies of humans in altered states of consciousness have prompted the suggestion that maintenance of critical dy...

Prenatal cannabis exposure (PCE) influences human brain development, but it is challenging to model PCE using animals and current cell culture techniques. Here, we developed a one-stop microfluidic platform to assemble and culture human cerebral organoids from human embryonic stem cells (hESC) to investigate the effect of PCE on early human brain d...

Detecting synaptic connections using large-scale extracellular spike recordings presents a statistical challenge. While previous methods often treat the detection of each putative connection as a separate hypothesis test, here we develop a modeling approach that infers synaptic connections while incorporating circuit properties learned from the who...

Prenatal cannabis exposure (PCE) influences human brain development, but it is challenging to model PCE using animals and current cell culture techniques. Here, we developed a one-stop microfluidic platform to assemble and culture human cerebral organoids from human embryonic stem cells (hESC) to investigate the effect of PCE on early human brain d...

The criticality hypothesis predicts that cortex operates near a critical point for optimum information processing. In this issue of Neuron, Ma et al. (2019) find evidence consistent with a mechanism that tunes cortex to criticality, even in the face of a strong perturbation over several days.

Neural information processing is widely understood to depend on correlations in neuronal activity. However, whether correlation is favorable or not is contentious. Here, we sought to determine how correlated activity and information processing are related in cortical circuits. Using recordings of hundreds of spiking neurons in organotypic cultures...

To understand how neural circuits process information, it is essential to identify the relationship between computation and circuit organization. Rich clubs, highly interconnected sets of neurons, are known to propagate a disproportionate amount of information within cortical circuits. Here, we test the hypothesis that rich clubs also perform a dis...

To understand how neural circuits process information, it is essential to identify the relationship between computation and circuit organization. Rich-clubs, highly interconnected sets of neurons, are known to propagate a disproportionate amount of information within cortical circuits. Here, we test the hypothesis that rich-clubs also perform a dis...

We introduce a novel tool for analyzing complex network dynamics, allowing for cascades of causally-related events, which we call causal webs (c-webs), to be separated from other non-causally-related events. This tool shows that traditionally-conceived avalanches may contain mixtures of spatially-distinct but temporally-overlapping cascades of even...

The analysis of neural systems leverages tools from many different fields. Drawing on techniques from the study of critical phenomena in statistical mechanics, several studies have reported signatures of criticality in neural systems, including power-law distributions, shape collapses, and optimized quantities under tuning. Independently, neural co...

Domoic acid is a neurotoxin produced by algae and is found in seafood during harmful algal blooms. As a glutamate agonist, domoic acid inappropriately stimulates excitatory activity in neurons.At high doses, this leads to seizures and brain lesions, but it is unclear how lower, asymptomatic exposures disrupt neuronal activity. Domoic acid has been...

Neural systems include interactions that occur across many scales. Two divergent methods for characterizing such interactions have drawn on the physical analysis of critical phenomena and the mathematical study of information. Inferring criticality in neural systems has traditionally rested on fitting power laws to the property distributions of “ne...

Recent work has shown that functional connectivity among cortical neurons is highly varied, with a small percentage of neurons having many more connections than others. Also, recent theoretical developments now make it possible to quantify how neurons modify information from the connections they receive. Therefore, it is now possible to investigate...

Large feedforward model network results. All subfigures in this panel correspond to the subfigures in Fig 7. This model contained 40 neurons per layer (double the original network size), but otherwise matched the smaller model in terms of set parameters and equations. Note that the larger model produced connectivity diagrams and computation correla...

Background: Cross-frequency coupling (CFC) occurs when orthogonal frequency components entrain one another. A ubiquitous example from neuroscience is low frequency phase to high frequency amplitude coupling in electrophysiological signals. Seminal work by Canolty revealed CFC in human ECoG data. Established methods band-pass the data into componen...

We introduce a novel tool for analyzing complex network dynamics, allowing for cascades of causally-related events, which we call causal webs (c-webs), to be separated from other non-causally-related events. This tool shows that traditionally-conceived avalanches may contain mixtures of spatially-distinct but temporally-overlapping cascades of even...

The performance of complex networks, like the brain, depends on how effectively their elements communicate. Despite the importance of communication, it is virtually unknown how information is transferred in local cortical networks, consisting of hundreds of closely spaced neurons. To address this, it is important to record simultaneously from hundr...

Acute brain slices are an important model for the electrophysiological study of neural connectivity in vitro. A technological approach to bypassing the intrinsically damaged surface layer of these freshly cut slices, to record simultaneously from many connected neurons in the in tact interior volume of the slice, is to use of arrays of penetrating...

DOI:https://doi.org/10.1103/PhysRevLett.114.220001

Recent studies have emphasized the importance of multiplex networks - interdependent networks with shared nodes and different types of connections - in systems primarily outside of neuroscience. Though the multiplex properties of networks are frequently not considered, most networks are actually multiplex networks and the multiplex specific feature...

Although relationships between networks of different scales have been observed in macroscopic brain studies, relationships between structures of different scales in networks of neurons are unknown. To address this, we recorded from up to 500 neurons simultaneously from slice cultures of rodent somatosensory cortex. We then measured directed effecti...

Understanding the detailed circuitry of functioning neuronal networks is one of the major goals of neuroscience. Recent improvements in neuronal recording techniques have made it possible to record the spiking activity from hundreds of neurons simultaneously with sub-millisecond temporal resolution. Here we used a 512-channel multielectrode array s...

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Is the brain really operating at a critical point? We study the non-equilibrium properties of a neural network which models the dynamics of the neocortex and argue for optimal quasi-critical dynamics on the Widom line where the correlation length is maximal. We simulate the network and introduce an analytical mean-field approximation, characterize...

1 news & views A t first glance, the brain can seem random. Neuron branches look tangled, the voltage across the membrane of a single neuron follows a random walk and groups of neurons that become simultaneously active seem to be scattered with no particular pattern. One of the chief tasks in biophysics is to find regularities that could reveal ord...

It has been notoriously difficult to understand interactions in the basal ganglia because of multiple recurrent loops. Another complication is that activity there is strongly dependent on behavior, suggesting that directional interactions, or effective connections, can dynamically change. A simplifying approach would be to examine just the direct,...

High-resolution imaging of neuronal networks reveals that spontaneous bursts of collective activity are a consequence of an implosive concentration of noise.

Information theory has long been used to quantify interactions between two variables. With the rise of complex systems research, multivariate information measures have been increasingly used to investigate interactions between groups of three or more variables, often with an emphasis on so called synergistic and redundant interactions. While bivari...

We propose a cellular automaton model for neuronal networks that combines short-term synaptic plasticity with long-term metaplasticity. We investigate how these two mechanisms contribute to attaining and maintaining operation at the critical point. We find that short-term plasticity, represented in the model by synaptic depression and synaptic reco...

Objective. This paper describes the design, microfabrication, electrical characterization and biological evaluation of a high-density micro-needle array. The array records from and electrically stimulates individual neurons simultaneously in acute slices of brain tissue. Approach. Acute slices, arguably the closest in-vitro model of the brain, have...

Relatively recent work has reported that networks of neurons can produce avalanches of activity whose sizes follow a power law distribution. This suggests that these networks may be operating near a critical point, poised between a phase where activity rapidly dies out and a phase where activity is amplified over time. The hypothesis that the elect...

Simulation of an Ising model at low temperature.

The tasks of neural computation are remarkably diverse. To function optimally, neuronal networks have been hypothesized to operate near a nonequilibrium critical point. However, experimental evidence for critical dynamics has been inconclusive. Here, we show that the dynamics of cultured cortical networks are critical. We analyze neuronal network d...

In recent years, experiments detecting the electrical firing patterns in slices of in vitro brain tissue have been analyzed to suggest the presence of scale invariance and possibly criticality in the brain. Much of the work done however has been limited in two ways: 1) the data collected is from local field potentials that do not represent the firi...

The tasks of information processing, computation, and response to stimuli require neural computation to be remarkably flexible and diverse. To optimally satisfy the demands of neural computation, neuronal networks have been hypothesized to operate near a non-equilibrium critical point. In spite of their importance for neural dynamics, experimental...

The way in which structure of neuronal network constrains the functional activity of neurons is one of the critical questions in the field of neuroscience. The correspondence between the spatial pattern of structural connectivity and spontaneous activity was recently demonstrated in macroscopic brain. However, the analogical finding about microscop...

Izhikevich's program for cortical network simulation. Copied from [58]. (M)

PDF document of algorithm description of transfer entropy calculation. (PDF)

Transfer entropy toolbox project website address. http://code.google.com/p/transfer-entropy-toolbox/ (TEX)

Transfer entropy (TE) is an information-theoretic measure which has received recent attention in neuroscience for its potential to identify effective connectivity between neurons. Calculating TE for large ensembles of spiking neurons is computationally intensive, and has caused most investigators to probe neural interactions at only a single time d...

The way in which brain structure constrains the brain functional activities is one of the critical questions in the field of neuroscience. In this research, first, we reconstructed causal interactions among neurons using spike trains, which were recorded on 512 channel Multi-Unit system from the hippocampus. Next, we separated the network structure...

Understanding the mechanisms of distributed computation in cellular automata requires techniques for characterizing the emergent structures that underlie information processing in such systems. Recently, techniques from information theory have been brought to bear on this problem. Building on this work, we utilize the new technique of partial infor...

Neurons form a complex network in the brain, where they interact with one another by firing electrical signals. Neurons firing can trigger other neurons to fire, potentially causing avalanches of activity in the network. In many cases these avalanches have been found to be scale independent, similar to critical phenomena in diverse systems such as...

Some forms of epilepsy may arise as a result of pathologic interactions among neurons. Many forms of collective activity have been identified, including waves, spirals, oscillations, synchrony, and neuronal avalanches. All these emergent activity patterns have been hypothesized to show pathologic signatures associated with epilepsy. Here, the autho...

Understanding how ensembles of neurons collectively interact will be a key step in developing a mechanistic theory of cognitive processes. Recent progress in multineuron recording and analysis techniques has generated tremendous excitement over the physiology of living neural networks. One of the key developments driving this interest is a new clas...

How living neural networks retain information is still incompletely understood. Two prominent ideas on this topic have developed in parallel, but have remained somewhat unconnected. The first of these, the "synaptic hypothesis," holds that information can be retained in synaptic connection strengths, or weights, between neurons. Recent work inspire...

We present a design and preliminary tests result of a large-scale MEA-based system for spatio-temporal distributed stimulation and recording of neural activity. The system is based on 512-electrode array with 60 µm inter-electrode spacing and dedicated multichannel integrated circuits for independent stimulation and recording on all the electrodes....

There continues to be widespread interest in 1/f^(alpha) behavior in baseline power spectral densities (PSD's) but its origins remain controversial. Zwanzig-Mori projection operators provide a rigorous, common starting place for building a theory of PSD's from the bottom up. In this approach, one separates out explicit "system" degrees of freedom (...

How does information flow through networks of neurons? The type of network topology revealed could have important consequences for network efficiency and robustness to damage. Several tools, including transfer entropy, Granger causality, and directed information can be applied to this question. Yet indirect connections, connections with various del...

The dynamics found in local cortical networks strongly impact the types of computations they can perform. Major classes of cortical network models assume that spatio-temporal activity evolves with either ultra-stable, chaotic or neutral dynamics. While experimental evidence has demonstrated that repeatable activity states can exist in cortical netw...

Plasticity is central to the ability of a neural system to learn and also to its ability to develop spontaneous seizures. What is the connection between the two? Learning itself is known to be a destabilizing process at the algorithmic level. We have investigated necessary constraints on a spontaneously active Hebbian learning system and find that...

Introduction Epileptogenicity of neuronal tissues requires both altered excitability and altered synchronization of neurons. However, the network-level mechanisms responsible for neuronal hyperexcitability and synchronization remain unknown, and there is much to learn regarding how even small networks of neurons interact. The present study examines...

Multi-neuron firing states are often observed, yet are predicted to be rare by models that assume independent firing. To predict these states, two groups recently applied a second-order maximum entropy model that used only observed firing rates and pairwise interactions as parameters (Schneidman et al., 2006; Shlens et al., 2006). Interestingly, th...

The average cortical neuron makes and receives about 1,000 synaptic contacts. This anatomical information suggests that local cortical networks are connected in a fairly democratic manner, with all nodes having about the same degree. But the physical connections found in the brain do not necessarily reveal how information flows through the network....

Recent experiments demonstrate that activity in neocortical circuits can propagate in the form of avalanches whose sizes follow a power law distribution, suggesting that these circuits operate near a continuous phase transition point. Computational models indicate that this critical point may be optimal for information processing. However, the exis...

Multineuron firing patterns are often observed, yet are predicted to be rare by models that assume independent firing. To explain these correlated network states, two groups recently applied a second-order maximum entropy model that used only observed firing rates and pairwise interactions as parameters (Schneidman et al., 2006; Shlens et al., 2006...

The physics of phase transitions beautifully describes the collective behaviour of many populations of inanimate particles, from water molecules to magnetic spins. But could it also help in understanding ensembles of living neurons?

A spontaneously active neural system that is capable of continual learning should also be capable of homeostasis of both firing rate and connectivity. Experimental evidence suggests that both types of homeostasis exist, and that connectivity is maintained at a state that is optimal for information transmission and storage. This state is referred to...

Recent experimental work has begun to characterize activity in local cortical networks containing thousands of neurons. There has also been an explosion of work on connectivity in networks of all types. It would seem natural then to explore the influence of connectivity on dynamics at the local network level. In this chapter, we will give an overvi...

Early theoretical and simulation work independently undertaken by Packard, Langton and Kauffman suggested that adaptability and computational power would be optimized in systems at the 'edge of chaos', at a critical point in a phase transition between total randomness and boring order. This provocative hypothesis has received much attention, but bi...