Biomedical subjects

Eshel Ben-Jacob

Publications and source records attributed to Eshel Ben-Jacob.

At least 19 recordsLinked to original sources

PubMed2007

The astrocyte as a gatekeeper of synaptic information transfer.

We present a simple biophysical model for the coupling between synaptic transmission and the local calcium concentration on an enveloping astrocytic domain. This interaction enables the astrocyte to modulate the information flow from presynaptic to postsynaptic cells in a manner dependent on previous activity at this and other nearby synapses. Our model suggests a novel, testable hypothesis for the spike timing statistics measured for rapidly firing cells in culture experiments.

Animals↗

PubMed2006

Study of hypothermia on cultured neuronal networks using multi-electrode arrays.

Efficient and safe use of hypothermia during various neuro-medical procedures requires sound understanding of low temperature effects on the neuronal network's activity. In this report, we introduce the use of cultivated dissociated neuronal networks on temperature controlled multi-electrode arrays (MEAs) as a simple methodology for studying the long-term effects of hypothermia. The networks exhibit spontaneous activity in the form of synchronized bursting events (SBEs), followed by long intervals of sporadic firing. Through the use of our correlation method, these SBEs can be clustered into sub-groups of similar spatio-temporal patterns. Application of hypothermia to the network resulted in a reduction in the SBE rate, the spike intensity and an increase in inter-neuronal correlations. Within 2h following the cessation of hypothermia, the cultured network returned to its initial spatio-temporal SBE structure. These results suggest that the network survived cold exposure and demonstrate the feasibility of long-term continuous neural network recording during hypothermic conditions.

Action Potentials↗

PubMed2006

Adult, sex-specific behavior characterized by elevated neuronal functional complexity.

Adult, sex-specific behaviors are good models for context-specific behavioral patterns. Here, we focus on a unique example: locust oviposition. The neural network's rhythmic output can be activated at all life stages, including embryonic, in both females and males. All recorded patterns, independent of age and sex, showed similar basic statistics. Activity density plots and spectral analysis, however, revealed that oscillations in burst rates recorded from females show greater variation quantities than those recorded from males. Furthermore, only the neural output recorded from sexually mature females was characterized by significantly elevated functional complexity. Thus, while the neural network has inherent potential to generate motor activities at different levels of complexity, only the proper internal-environmental and behavioral context triggers expression of its full potential of information capacity.

Action Potentials↗

PubMed2006

Time-invariant person-specific frequency templates in human brain activity.

The various human brain tasks are performed at different locations and time scales. Yet, we discovered the existence of time-invariant (above an essential time scale) partitioning of the brain activity into personal state-specific frequency bands. For that, we perform temporal and ensemble averaging of best wavelet packet bases from multielectrode electroencephalogram recordings. These personal frequency bands provide new templates for quantitative analyses of brain function, e.g., normal versus epileptic activity.

Algorithms↗

PubMed2006

Noise resistance in the spindle assembly checkpoint.

Genetically identical cells vary in the amount of expressed proteins even when growing under the same conditions. It is not yet clear how cellular information processing copes with such stochastic fluctuations in protein levels. Here we examine the capacity of the spindle assembly checkpoint to buffer temporal fluctuations in the expression of Cdc20, a critical checkpoint target whose activity is inhibited to prevent premature cell cycle progression. Using mathematical modeling, we demonstrate that the checkpoint can buffer significant fluctuations in Cdc20 production rate. Critical to this buffering capacity is the use of sequestering-based mechanism for inhibiting Cdc20, as apposed to inhibition by enhancing protein degradation. We propose that the design of biological networks is limited by the need to overcome noise in gene expression.

Cdc20 Proteins↗

PubMed2006

Self-engineering capabilities of bacteria.

Under natural growth conditions, bacteria can utilize intricate communication capabilities (e.g. quorum-sensing, chemotactic signalling and plasmid exchange) to cooperatively form (self-organize) complex colonies with elevated adaptability-the colonial pattern is collectively engineered according to the encountered environmental conditions. Bacteria do not genetically store all the information required for creating all possible patterns. Instead, additional information is cooperatively generated as required for the colonial self-organization to proceed. We describe how complex colonial forms (patterns) emerge through the communication-based singular interplay between individual bacteria and the colony. Each bacterium is, by itself, a biotic autonomous system with its own internal cellular informatics capabilities (storage, processing and assessment of information). These afford the cell plasticity to select its response to biochemical messages it receives, including self-alteration and the broadcasting of messages to initiate alterations in other bacteria. Hence, new features can collectively emerge during self-organization from the intracellular level to the whole colony. The cells thus assume newly co-generated traits and abilities that are not explicitly stored in the genetic information of the individuals.

Adaptation, Physiological↗

PubMed2006

Functional holography analysis: simplifying the complexity of dynamical networks.

We present a novel functional holography (FH) analysis devised to study the dynamics of task-performing dynamical networks. The latter term refers to networks composed of dynamical systems or elements, like gene networks or neural networks. The new approach is based on the realization that task-performing networks follow some underlying principles that are reflected in their activity. Therefore, the analysis is designed to decipher the existence of simple causal motives that are expected to be embedded in the observed complex activity of the networks under study. First we evaluate the matrix of similarities (correlations) between the activities of the network's components. We then perform collective normalization of the similarities (or affinity transformation) to construct a matrix of functional correlations. Using dimension reduction algorithms on the affinity matrix, the matrix is projected onto a principal three-dimensional space of the leading eigenvectors computed by the algorithm. To retrieve back information that is lost in the dimension reduction, we connect the nodes by colored lines that represent the level of the similarities to construct a holographic network in the principal space. Next we calculate the activity propagation in the network (temporal ordering) using different methods like temporal center of mass and cross correlations. The causal information is superimposed on the holographic network by coloring the nodes locations according to the temporal ordering of their activities. First, we illustrate the analysis for simple, artificially constructed examples. Then we demonstrate that by applying the FH analysis to modeled and real neural networks as well as recorded brain activity, hidden causal manifolds with simple yet characteristic geometrical and topological features are deciphered in the complex activity. The term "functional holography" is used to indicate that the goal of the analysis is to extract the maximum amount of functional information about the dynamical network as a whole unit.

Algorithms↗

PubMed2005

Evaluating putative mechanisms of the mitotic spindle checkpoint.

The mitotic spindle checkpoint halts the cell cycle until all chromosomes are attached to the mitotic spindles. Evidence suggests that the checkpoint prevents cell-cycle progression by inhibiting the activity of the APC-Cdc20 complex, but the precise mechanism underlying this inhibition is not yet known. Here, we use mathematical modeling to compare several mechanisms that could account for this inhibition. We describe the interplay between the capacities to strongly inhibit cell-cycle progression before spindle attachment on one hand and to rapidly resume cell-cycle progression once the last kinetochore is attached on the other hand. We find that inhibition that is restricted to the kinetochore region is not sufficient for supporting both requirements when realistic diffusion constants are considered. A mechanism that amplifies the checkpoint signal through autocatalyzed inhibition is also insufficient. In contrast, amplifying the signal through the release of a diffusible inhibitory complex can support reliable checkpoint function. Our results suggest that the design of the spindle checkpoint network is limited by physical constraints imposed by realistic diffusion constants and the relevant spatial and temporal dimensions where computation is performed.

Anaphase-Promoting Complex-Cyclosome↗

PubMed2005

A two-phase growth strategy in cultured neuronal networks as reflected by the distribution of neurite branching angles.

Neurite outgrowth and branching patterns are instrumental in dictating the wiring diagram of developing neuronal networks. We study the self-organization of single cultured neurons into complex networks focusing on factors governing the branching of a neurite into its daughter branches. Neurite branching angles of insect ganglion neurons in vitro were comparatively measured in two neuronal categories: neurons in dense cultures that bifurcated under the presence of extrinsic (cellular environment) cues versus neurons in practical isolation that developed their neurites following predominantly intrinsic cues. Our experimental results were complemented by theoretical modeling and computer simulations. A preferred regime of branching angles was found in isolated neurons. A model based on biophysical constraints predicted a preferred bifurcation angle that was consistent with this range shown by our real neurons. In order to examine the origin of the preferred regime of angles we constructed simulations of neurite outgrowth in a developing network and compared the simulated developing neurons with our experimental results. We tested cost functions for neuronal growth that would be optimized at a specific regime of angles. Our results suggest two phases in the process of neuronal development. In the first, reflected by our isolated neurons, neurons are tuned to make first contact with a target cell as soon as possible, to minimize the time of growth. After contact is made, that is, after neuronal interconnections are formed, a second branching strategy is adopted, favoring higher efficiency in neurite length and volume. The two-phase development theory is discussed in relation to previous results.

Animals↗

PubMed2005

Manifestation of function-follow-form in cultured neuronal networks.

We expose hidden function-follow-form schemata in the recorded activity of cultured neuronal networks by comparing the activity with simulation results of a new modeling approach. Cultured networks grown from an arbitrary mixture of neuron and glia cells in the absence of external stimulations and chemical cues spontaneously form networks of different sizes (from 50 to several millions of neurons) that exhibit non-arbitrary complex spatio-temporal patterns of activity. The latter is marked by formation of a sequence of synchronized bursting events (SBEs)--short time windows (approximately 200 ms) of rapid neuron firing, separated by longer time intervals (seconds) of sporadic neuron firing. The new dynamical synapse and soma (DSS) model, used here, has been successful in generating sequences of SBEs with the same statistical scaling properties (over six time decades) as those of the small networks. Large networks generate statistically distinct sub-groups of SBEs, each with its own characteristic pattern of neuronal firing ('fingerprint'). This special function (activity) motif has been proposed to emanate from a structural (form) motif--self-organization of the large networks into a fabric of overlapping sub-networks of about 1 mm in size. Here we test this function-follow-form idea by investigating the influence of the connectivity architecture of a model network (form) on the structure of its spontaneous activity (function). We show that a repertoire of possible activity states similar to the observed ones can be generated by networks with proper underlying architecture. For example, networks composed of two overlapping sub-networks exhibit distinct types of SBEs, each with its own characteristic pattern of neuron activity that starts at a specific sub-network. We further show that it is possible to regulate the temporal appearance of the different sub-groups of SBEs by an additional non-synaptic current fed into the soma of the modeled neurons. The ability to regulate the relative temporal ordering of different SBEs might endow the networks with higher plasticity and complexity. These findings call for additional mechanisms yet to be discovered. Recent experimental observations indicate that glia cells coupled to neuronal soma might generate such non-synaptic regulating currents.

Action Potentials↗

PubMed2004

Self-regulated complexity in cultured neuronal networks.

New quantified observables of complexity are identified and utilized to study sequences (time series) recorded during the spontaneous activity of different size cultured networks. The sequence is mapped into a tiled time-frequency domain that maximizes the information about local time-frequency resolutions. The sequence regularity is associated with the domain homogeneity and its complexity with its local and global variations. Shuffling the recorded sequence lowers its complexity down to artificially constructed ones. The new observables are utilized to identify self-regulation motifs in observed complex network activity.

Animals↗

PubMed2004

Hidden neuronal correlations in cultured networks.

Utilization of a clustering algorithm on neuronal spatiotemporal correlation matrices recorded during a spontaneous activity of in vitro networks revealed the existence of hidden correlations: the sequence of synchronized bursting events (SBEs) is composed of statistically distinguishable subgroups each with its own distinct pattern of interneuron spatiotemporal correlations. These findings hint that each of the SBE subgroups can serve as a template for coding, storage, and retrieval of a specific information.

Algorithms↗

PubMed2004

Physical schemata underlying biological pattern formation-examples, issues and strategies.

Biological systems excel at building spatial structures on scales ranging from nanometers to kilometers and exhibit temporal patterning from milliseconds to years. One approach that nature has taken to accomplish this relies on the harnessing of pattern-forming processes of non-equilibrium physics and chemistry. For these systems, the study of biological pattern formation starts with placing a biological phenomenon of interest within the context of the proper pattern-formation schema and then focusing on the ways in which control is exerted to adapt the pattern to the needs of the organism. This approach is illustrated by several examples, notably bacterial colonies (diffusive-growth schema) and intracellular calcium waves (excitable-media schema).

Animals↗

PubMed2004

Modeling of synchronized bursting events: the importance on inhomogeneity.

Cultured in vitro neuronal networks are known to exhibit synchronized bursting events (SBE), during which most of the neurons in the system spike within a time window of approximately 100 msec. Such phenomena can be obtained in model networks based on Markram-Tsodyks frequency-dependent synapses. In order to account correctly for the detailed behavior of SBEs, several modifications have to be implemented in such models. Random input currents have to be introduced to account for the rising profile of SBEs. Dynamic thresholds and inhomogeneity in the distribution of neuronal resistances enable us to describe the profile of activity within the SBE and the heavy-tailed distributions of interspike intervals and interevent intervals. Thus, we can account for the interesting appearance of Levy distributions in the data.

Algorithms↗

PubMed2004

Functional holography of recorded neuronal networks activity.

We present a new approach for analyzing multi-channel recordings, such as ECoG (electrocorticograph) recordings of cortical brain activity and of individual neuron dynamics, in cultured networks. The latter are used here to illustrate the method and its ability to discover hidden functional connectivity motifs in the recorded activity. The cultured networks are formed from dissociated mixtures of cortical neurons and glia-cells that are homogeneously spread over multi-electrode array for recording of the neuronal activity. Rich, spontaneous dynamical behavior is detected, marked by the formation of temporal sequences of synchronized bursting events (SBEs), partitioned into statistically distinguishable subgroups, each with its own characteristic spatio-temporal pattern of activity.In analogy with coherence connectivity networks for multi-location cortical recordings, we evaluated the inter-neuron correlation-matrix for each subgroup. Ordinarily such matrices are mapped onto a connectivity network between neuron positions in real space. In our functional holography, the correlations are normalized by the correlation distances Euclidian distances between the matrix columns. Then, we project the N-dimensional (for N channels) space spanned by the matrix of the normalized correlations, or correlation affinities, onto a corresponding 3D manifold (3D Cartesian space constructed by the three leading principal vectors of the principal component algorithm). The neurons are located by their principal eigenvalues and linked by their original (not normalized) correlations. By looking at these holograms, hidden causal motifs are revealed: each SBEs subgroup generates its characteristic connectivity diagram (network) in the 3D manifold, where the neuron locations and their links form simple structures. Moreover, the computed temporal ordering of neuron activity, when projected onto the connectivity diagrams, also exhibits simple patterns of causal propagation. We show that the method can expose functional connectivity motifs like the co-existence of subneuronal functional networks in the space of affinities. The method can be directly utilized to construct similar causal holograms for recorded brain activity. We expect that by doing so, hidden functional connectivity motifs with relevance to the understanding of brain activity might be discovered.

Animals↗

PubMed2003

Bacterial self-organization: co-enhancement of complexification and adaptability in a dynamic environment.

During colonial development, bacteria generate a wealth of patterns, some of which are reminiscent of those occurring in abiotic systems. They can exhibit rich behaviour, reflecting informative communication capabilities that include exchange of genetic materials and the fact that the colony's building blocks are biotic. Each has internal degrees of freedom, informatic capabilities and freedom to respond by altering itself and others via emission of signals in a self-regulated manner. To unravel the special secrets of bacterial self-organization, we conducted an integrative (experimental and theoretical) study of abiotic and biotic systems. Guided by the notion of general biotic motives and principles, I propose that the informative communication between individuals makes possible the enhancement of the individuals' regulated freedom, while increasing their cooperation. This process is accomplished via cooperative complexification of the colony through self-organization of hierarchical spatio-temporal patterning. The colonial higher complexity provides the degree of plasticity and flexibility required for better colonial adaptability and endurability in a dynamic environment. The biotic system can modify the environment and obtain environmental information for further self-improvement. I reflect on the potential applications of the new understanding on 'engineered self-organization of systems too complex to design' and other issues.

Adaptation, Physiological↗

PubMed2003

Formation of electrically active clusterized neural networks.

Ordinarily, in vitro neurons self-organize into homogeneous networks of single neurons linked by dendrites and axons. We show that under special conditions they can also self-organize into neuronal clusters, which are linked by bundles of axons. Multielectrode array measurement reveals that the clusterized networks are also electrically active and exhibit synchronized bursting events similar to those observed in the homogeneous networks. From time-lapse recording, we deduced the features required for the neuronal clusterized versus homogeneous self-organization and developed a simple model for testing their validity.

Animals↗

PubMed2002

Morphological characterization of in vitro neuronal networks.

We use in vitro neuronal networks as a model system for studying self-organization processes in the nervous system. We follow the neuronal growth process, from isolated neurons to fully connected two-dimensional networks. The mature networks are mapped into connected graphs and their morphological characteristics are measured. The distributions of segment lengths, node connectivity, and path length between nodes, and the clustering coefficient of the networks are used to characterize network morphology and to demonstrate that our networks fall into the category of small-world networks.

Animals↗