Biomedical subjects

Ronen Segev

Publications and source records attributed to Ronen Segev.

12 recordsLinked to original sources

PubMed2006

How much the eye tells the brain.

In the classic "What the frog's eye tells the frog's brain," Lettvin and colleagues showed that different types of retinal ganglion cell send specific kinds of information. For example, one type responds best to a dark, convex form moving centripetally (a fly). Here we consider a complementary question: how much information does the retina send and how is it apportioned among different cell types? Recording from guinea pig retina on a multi-electrode array and presenting various types of motion in natural scenes, we measured information rates for seven types of ganglion cell. Mean rates varied across cell types (6-13 bits . s(-1)) more than across stimuli. Sluggish cells transmitted information at lower rates than brisk cells, but because of trade-offs between noise and temporal correlation, all types had the same coding efficiency. Calculating the proportions of each cell type from receptive field size and coverage factor, we conclude (assuming independence) that the approximately 10(5) ganglion cells transmit on the order of 875,000 bits . s(-1). Because sluggish cells are equally efficient but more numerous, they account for most of the information. With approximately 10(6) ganglion cells, the human retina would transmit data at roughly the rate of an Ethernet connection.

Action Potentials↗

PubMed2006

Weak pairwise correlations imply strongly correlated network states in a neural population.

Biological networks have so many possible states that exhaustive sampling is impossible. Successful analysis thus depends on simplifying hypotheses, but experiments on many systems hint that complicated, higher-order interactions among large groups of elements have an important role. Here we show, in the vertebrate retina, that weak correlations between pairs of neurons coexist with strongly collective behaviour in the responses of ten or more neurons. We find that this collective behaviour is described quantitatively by models that capture the observed pairwise correlations but assume no higher-order interactions. These maximum entropy models are equivalent to Ising models, and predict that larger networks are completely dominated by correlation effects. This suggests that the neural code has associative or error-correcting properties, and we provide preliminary evidence for such behaviour. As a first test for the generality of these ideas, we show that similar results are obtained from networks of cultured cortical neurons.

Action Potentials↗

PubMed2006

How silent is the brain: is there a "dark matter" problem in neuroscience?

Evidence from a variety of recording methods suggests that many areas of the brain are far more sparsely active than commonly thought. Here, we review experimental findings pointing to the existence of neurons which fire action potentials rarely or only to very specific stimuli. Because such neurons would be difficult to detect with the most common method of monitoring neural activity in vivo-extracellular electrode recording-they could be referred to as "dark neurons," in analogy to the astrophysical observation that much of the matter in the universe is undetectable, or dark. In addition to discussing the evidence for largely silent neurons, we review technical advances that will ultimately answer the question: how silent is the brain?

Action Potentials↗

PubMed2005

Functional organization of ganglion cells in the salamander retina.

Recently, we reported a novel technique for recording all of the ganglion cells in a retinal patch and showed that their receptive fields cover visual space roughly 60 times over in the tiger salamander. Here, we carry this analysis further and divide the population of ganglion cells into functional classes using quantitative clustering algorithms that combine several response characteristics. Using only the receptive field to classify ganglion cells revealed six cell types, in agreement with anatomical studies. Adding other response measures served to blur the distinctions between these cell types rather than resolve further classes. Only the biphasic off type had receptive fields that tiled the retina. Even when we attempted to split these classes more finely, ganglion cells with almost identical functional properties were found to have strongly overlapping spatial receptive fields. A territorial spatial organization, where ganglion cell receptive fields tend to avoid those of other cells of the same type, was only found for the biphasic off cell. We further studied the functional segregation of the ganglion cell population by computing the amount of visual information shared between pairs of cells under natural movie stimulation. This analysis revealed an extensive mixing of visual information among cells of different functional type. Together, our results indicate that the salamander retina uses a population code in which every point in visual space is represented by multiple neurons with subtly different visual sensitivities.

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

Recording spikes from a large fraction of the ganglion cells in a retinal patch.

To understand a neural circuit completely requires simultaneous recording from most of the neurons in that circuit. Here we report recording and spike sorting techniques that enable us to record from all or nearly all of the ganglion cells in a patch of the retina. With a dense multi-electrode array, each ganglion cell produces a unique pattern of activity on many electrodes when it fires an action potential. Signals from all of the electrodes are combined with an iterative spike sorting algorithm to resolve ambiguities arising from overlapping spike waveforms. We verify that we are recording from a large fraction of ganglion cells over the array by labeling the ganglion cells with a retrogradely transported dye and by comparing the number of labeled and recorded cells. Using these methods, we show that about 60 receptive fields of ganglion cells cover each point in visual space in the salamander, consistent with anatomical findings.

Action Potentials↗

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↗

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↗

PubMed2002

A method for spike sorting and detection based on wavelet packets and Shannon's mutual information.

Studying the dynamics of neural activity via electrical recording, relies on the ability to detect and sort neural spikes recorded from a number of neurons by the same electrode. We suggest the wavelet packets decomposition (WPD) as a tool to analyze neural spikes and extract their main features. The unique quality of the wavelet packets-adaptive coverage of both time and frequency domains using a set of localized packets, facilitate the task. The best basis algorithm utilizing the Shannon's information cost function and local discriminant basis (LDB) using mutual information are employed to select a few packets that are sufficient for both detection and sorting of spikes. The efficiency of the method is demonstrated on data recorded from in vitro 2D neural networks, placed on electrodes that read data from as many as five neurons. Comparison between our method and the widely used principal components method and a sorting technique based on the ordinary wavelet transform (WT) shows that our method is more efficient both in separating spikes from noise and in resolving overlapping spikes.

Action Potentials↗

PubMed2002

Long term behavior of lithographically prepared in vitro neuronal networks.

We measured the long term spontaneous electrical activity of neuronal networks with different sizes, grown on lithographically prepared substrates and recorded with multi-electrode-array technology. The time sequences of synchronized bursting events were used to characterize network dynamics. All networks exhibit scale-invariant Lévy distributions and long-range correlations. These observations suggest that different-size networks self-organize to adjust their activities over many time scales. As predictions of current models differ from our observations, this calls for revised models.

Electrodes↗