Publications

The catalytic cycle involves internal motions and conformational changes that allow enzymes to specifically bind to substrates, reach the transition state and release the product. Such mechanical interactions and motions are often long ranged so that mutations of residues far from the active site can modulate the enzymatic cycle. In particular, regions that undergo high strain during the cycle give mechanical flexibility to the protein, which is crucial for protein motion. Here we directly probe the connection between strain, flexibility and functionality, and we quantify how distant high-strain residues modulate the catalytic function via long-ranged force transduction. We measure the rheological and catalytic properties of wild-type guanylate kinase and of its mutants with a single amino acid replacement in low-/high-strain regions and in binding/non-binding regions. The rheological response of the protein to an applied oscillating force fits a continuum model of a viscoelastic material whose mechanical properties are significantly affected by mutations in high-strain regions, as opposed to mutations in control regions. Furthermore, catalytic activity assays show that mutations in high-strain or binding regions tend to reduce activity, whereas mutations in low-strain, non-binding regions are neutral. These findings suggest that enzymes act as viscoelastic catalytic machines with sequence-encoded mechanical specifications.

Prosody, the musical facet of speech, is pivotal in human communication, and its structure and meaning remain subjects of ongoing research. In this study, we introduce a data-driven model for English prosody, based on large-scale analysis of spontaneous conversations. As a first step, we identify approximately 200 discernible prosodic patternswhich we view as building blocks of the prosodic vocabularyand outline their properties and range of meanings. Next, we reveal a Markovian logic, akin to a syntax, for concatenating these elementary building blocks into coherent utterances. We identify distinct compound functions associated with pairs of consecutive patterns and show that the Markovian syntax is more prevalent in spontaneous prosody, as compared to scripted speech. These findings offer invaluable insights into the underlying mechanisms of conversational prosody: They empirically inform and refine existing theoretical concepts. The methodology we present, combining unsupervised analysis of large datasets of spontaneous speech with manual sampling of the results, could guide future research aimed at refining our model and expanding it to other languages.

Ultrasonic neurostimulation is a potentially potent noninvasive therapy, whose mechanism has yet to be elucidated. We designed a system capable of applying ultrasound with minimal reflections to neuronal cultures. Synaptic transmission was pharmacologically controlled, eliminating network effects, enabling examination of single-cell processes. Short single pulses of low-intensity ultrasound were applied, and time-locked responses were examined using calcium imaging. Low-pressure (0.35 MPa) ultrasound directly stimulated ∼20% of pharmacologically disconnected neurons, regardless of membrane poration. Stimulation was resistant to the blockade of several purinergic receptor and mechanosensitive ion channel types. Stimulation was blocked, however, by suppression of action potentials. Surprisingly, even extremely short (4 μs) pulses were effective, stimulating ∼8% of the neurons. Lower-pressure pulses (0.35 MPa) were less effective than higher-pressure ones (0.65 MPa). Attrition effects dominated, with no indication of compromised viability. Our results detract from theories implicating cavitation, heating, non-transient membrane pores >1.5 nm, pre-synaptic release, or gradual effects. They implicate a post-synaptic mechanism upstream of the action potential, and narrow down the list of possible targets involved.

Although previous research in alcohol dependent populations identified alterations within local structures of the addiction reward circuitry, there is limited research into global features of this network, especially in early recovery. Transcranial magnetic stimulation (TMS) is capable of non-invasively perturbing the brain network while electroencephalography (EEG) measures the network response. The current study is the first to apply a TMS inhibitory paradigm while utilising network science (graph theory) to quantify network anomalies associated with alcohol dependence. Eleven individuals with alcohol-dependence (ALD) in early recovery and 16 healthy controls (HC) were administered 75 single pulses and 75 paired-pulses (inhibitory paradigm) to both the left and right prefrontal cortex (PFC). For each participant, Pearson cross-correlation was applied to the EEG data and correlation matrices constructed. Global network measures (mean degree, clustering coefficient, local efficiency and global efficiency) were extracted for comparison between groups. Following administration of the inhibitory paired-pulse TMS to the left PFC, the ALD group exhibited altered mean degree, clustering coefficient, local efficiency and global efficiency compared to HC. Decreases in local efficiency increased the prediction of being in the ALD group, while all network metrics (following paired-pulse left TMS) were able to adequately discriminate between the groups. In the ALD group, reduced mean degree and global clustering was associated with increased severity of past alcohol use. Our study provides preliminary evidence of altered network topology in patients with alcohol dependence in early recovery. Network anomalies were predictive of high alcohol use and correlated with clinical features of alcohol dependence. Further research using this novel brain mapping technique may identify useful network biomarkers of alcohol dependence and recovery.

Automatic speech recognition (ASR) and natural language processing (NLP) are expected to benefit from an effective, simple, and reliable method to automatically parse conversational speech. The ability to parse conversational speech depends crucially on the ability to identify boundaries between prosodic phrases. This is done naturally by the human ear, yet has proved surprisingly difficult to achieve reliably and simply in an automatic manner. Efforts to date have focused on detecting phrase boundaries using a variety of linguistic and acoustic cues. We propose a method which does not require model training and utilizes two prosodic cues that are based on ASR output. Boundaries are identified using discontinuities in speech rate (pre-boundary lengthening and phrase-initial acceleration) and silent pauses. The resulting phrases preserve syntactic validity, exhibit pitch reset, and compare well with manual tagging of prosodic boundaries. Collectively, our findings support the notion of prosodic phrases that represent coherent patterns across textual and acoustic parameters.

The interplay between excitation and inhibition is crucial for neuronal circuitry in the brain. Inhibitory cell fractions in the neocortex and hippocampus are typically maintained at 15 to 30%, which is assumed to be important for stable dynamics. We have studied systematically the role of precisely controlled excitatory/inhibitory (E/I) cellular ratios on network activity using mice hippocampal cultures. Surprisingly, networks with varying E/I ratios maintain stable bursting dynamics. Interburst intervals remain constant for most ratios, except in the extremes of 0 to 10% and 90 to 100% inhibitory cells. Single-cell recordings and modeling suggest that networks adapt to chronic alterations of E/I compositions by balancing E/I connectivity. Gradual blockade of inhibition substantiates the agreement between the model and experiment and defines its limits. Combining measurements of population and single-cell activity with theoretical modeling, we provide a clearer picture of how E/I balance is preserved and where it fails in living neuronal networks.

Studies have shown that Methylphenidate (MPH) affects cognitive performance on the neuropsychological tests and clinical symptoms of individuals diagnosed with attention deficit/hyperactivity disorder (ADHD). This study investigated the acute effects of MPH on neuropsychological tests to explore the interaction between MPH and test-retest effects. Twenty youths with ADHD were tested before and after MPH intake in a double-blind placebo-controlled crossover design and compared to twenty matched controls. Participants were tested on a range of standardized tasks including sustained attention to response, N-Back, and Word/Color Stroop. Identical tasks were administered twice each testing day, before and 1 hour after MPH/Placebo administration. Healthy controls were tested similarly with no intervention. Decreases in response time (RT) variability across tasks and in commission errors were found in ADHD after MPH. Conversely, a significant increase in RT variability and increase in omission errors were observed after the placebo. In the control group, RT variability and omission errors increased whereas commission errors decreased, suggesting fatigue and practice effects, respectively. Test-retest reliability was higher in controls than ADHD. It is suggested that cognitive tests are sensitive objective measures for the assessment of responses to MPH in ADHD but are also affected by repetition and fatigue.

Background Altered stimuli processing is a key feature of schizophrenia. Application of concurrent transcranial magnetic stimulation (TMS) with electroencephalography (TMS-EEG) is an effective stimulus which allows direct measurement of the cortical response within a millisecond time resolution. Test-retest TMS-EEG studies present evidence of high reproducibility in healthy controls (HC), however, this stability of response has not been examined in schizophrenia.

Background: Transcranial magnetic stimulation (TMS) is a rapidly expanding technology utilized in research and neuropsychiatric treatments. Yet, conventional TMS configurations affect primarily neurons that are aligned parallel to the induced electric field by a fixed coil, making the activation orientation-specific. A novel method termed rotational field TMS (rfTMS), where two orthogonal coils are operated with a 90° phase shift, produces rotation of the electric field vector over almost a complete cycle, and may stimulate larger portion of the neuronal population within a given brain area. Objective: To compare the physiological effects of rfTMS and conventional unidirectional TMS (udTMS) in the motor cortex. Methods: Hand and leg resting motor thresholds (rMT), and motor evoked potential (MEP) amplitudes and latencies (at 120% of rMT), were measured using a dual-coil array based on the H7-coil, in 8 healthy volunteers following stimulation at different orientations of either udTMS or rfTMS. Results: For both target areas rfTMS produced significantly lower rMTs and much higher MEPs than those induced by udTMS, for comparable induced electric field amplitude. Both hand and leg rMTs were orientation-dependent. Conclusions: rfTMS induces stronger physiologic effects in targeted brain regions at significantly lower intensities. Importantly, given the activation of a much larger population of neurons within a certain brain area, repeated application of rfTMS may induce different neuroplastic effects in neural networks, opening novel research and clinical opportunities.

The electroencephalogram (EEG) of schizophrenia patients is known to exhibit a reduction of signal-to-noise ratio and of phase locking, as well as a facilitation of excitability, in response to a variety of external stimuli. Here we demonstrate these effects in transcranial magnetic stimulation (TMS)-evoked potentials and in the resting-state EEG. To ensure veracity we used three weekly sessions and analyzed both resting state and TMS-EEG data. For the TMS responses our analysis verifies known results. For the resting state we introduce the methodology of mean-normalized variation to the EEG analysis (quartile-based coefficient of variation), which allows for a comparison of narrow-band EEG amplitude fluctuations to narrow-band Gaussian noise. This reveals that amplitude fluctuations in the delta, alpha and beta bands of healthy controls are different from those in schizophrenia patients, on time scales of tens of seconds. We conclude that the EEG-measured cortical activity patterns of schizophrenia patients are more similar to noise, both in alpha and beta resting state and in TMS responses. Our results suggest that the ability of neuronal populations to form stable, locally and temporally correlated activity is reduced in schizophrenia, a conclusion that is in accord with previous experiments on TMS-EEG and on resting-state EEG.

Methylphenidate (MPH) is the leading drug for treatment of attention deficit/hyperactivity disorder (ADHD), yet its underlying neuronal mechanisms are still unclear. Here, we use a dynamical brain networks approach to explore the effects of cognitive effort and MPH on ADHD subjects. Electroencephalography data were recorded from 19 ADHD subjects and 18 controls during a Go/No-Go Task. ADHD subjects completed the task twice a day over 2 days. The second session was administered post-ingestion of placebo/MPH (alternately). Controls performed two tasks in 1 day. The data were divided into 300 ms windows from -300 pre-stimulus until 1200 ms post-stimulus. Brain networks were constructed per subject and window, from which network metrics were extracted and compared across the experimental conditions. We identified an immediate shift of global connectivity and of network segregation after the stimulus for both groups, followed by a gradual return to baseline. Decreased global connectivity was found to be 400-700 ms post-stimulus in ADHD compared with controls, and it was normalized post-MPH. An increase of the networks' segregation occurred post-placebo at 100-400 and 400-700 ms post-stimulus, yet it was inhibited post-MPH. These global alterations resulted mainly from changes in task-relevant frontal and parietal regions. The networks of medicated ADHD subjects and controls exhibited a more significant and lasting change, relative to baseline, compared with those of nonmedicated ADHD. These results suggest impaired network flexibility in ADHD, corrected by MPH.

Methylphenidate (MPH) is a first line drug for attention-deficit/hyperactivity disorder (ADHD), yet the neuronal mechanisms underlying the condition and the treatment are still not fully understood. Previous EEG studies on the effect of MPH in ADHD found changes in evoked response potential (ERP) components that were inconsistent between studies. These inconsistencies highlight the need for a well-designed study which includes multiple baseline sessions and controls for possible fatigue, learning effects and between-days variability. To this end, we employ a double-blind placebo-controlled cross-over study and explore the effect of MPH on the ERP response of subjects with ADHD during a Go/No-Go cognitive task. Our ERP analysis revealed significant differences in ADHD subjects between the placebo and MPH conditions in the frontal-parietal region at 250ms-400ms post stimulus (P3). Additionally, a decrease in the late 650ms-800ms ERP component (LC) is observed in frontal electrodes of ADHD subjects compared to controls. The standard deviation of response time of ADHD subjects was significantly smaller in the MPH condition compared to placebo and correlated with the increased P3 ERP response in the frontoparietal electrodes. We suggest that mental fatigue plays a role in the decrease of the P3 response in the placebo condition compared to pre-placebo, a phenomenon that is significant in ADHD subjects but not in controls, and which is interestingly rectified by MPH.

Introduction: The effect of unidirectional TMS is limited to neurons that are parallel to the induced electric field. With rotational field TMS (rfTMS), two orthogonal coils are operated with a 90° phase shift between them. The electric field vector is circularly polarized and rotates affecting neurons in various orientations.

Background: Down syndrome remains the main genetic cause of intellectual disability, with an incidence rate of about 1 in 700 live births. The Ts65Dn mouse strain, with an extra murine chromosome that includes genes from chromosomes 10, 16 and 17 of the mouse and the Tc1 strain with an extra human chromosome 21, are currently accepted as informative and well-studied models for Down Syndrome. Using whole cell patch clamp we recently showed changes in several types of transmembrane currents in hippocampal neuronal cultures of Ts65Dn and Tc1 embryos. The associated genetic changes responsible for these changes in physiology were yet to be studied.Methods: We used qPCR to measure RNA expression level of a few of the channel genes that we suspect are implicated in the previously reported changes of measured currents, and performed statistical analysis using Matlab procedures for the standard t-test and ANOVA and for calculating correlations between the RNA expression levels of several channel genes.Results: We present differential gene expression levels measured using qPCR of the potassium channel regulators KCNE1 and KCNE2 in both Ts65Dn and Tc1 embryos and pups compared to controls. In Tc1, the human genes KCNJ6 and KCNJ15 are expressed in addition to a statistically insignificant increase of expression in the mouse genes KCNJ6 and KCNJ15. All channel genes that we have measured with large replication, have the same up-regulation or down-regulation in both mouse models, indicating that the transcription mechanism acts similarly in these two mouse models. The large dataset furthermore allows us to observe correlations between different channel genes. We find that, despite the significant changes in expression levels, channels that are known to interact have a high and significant correlation in expression both in controls and in the Down syndrome mouse model.Conclusions: We suggest the differential expression of KCNE1 and KCNE2 as a possible cause for our previously reported changes in potassium currents. We report a KCNJ6 and KCNJ15 overexpression, which plays a role in the increased input conductance and the reduced cell excitability that we previously reported in the Tc1 mouse model. The large and significant positive (KCNQ2-KCNQ3, KCNE1-KCNE2, KCNQ3-KCNE1, KCNQ2-KCNE1, KCNQ2-KCNE2, KCNQ3-KCNE2) and negative correlations (KCNE1-KCNJ15, KCNE2-KCNJ15) that we find between channel genes indicate that these genes probably work in a cooperative or in a mutually exclusive manner.

The combination of Transcranial Magnetic Stimulation (TMS) with Electroencephalography (EEG) exposes the brain's global response to localized and abrupt stimulations. However, large electric artifacts are induced in the EEG by the TMS, obscuring crucial stages of the brain's response. Artifact removal is commonly performed by data processing techniques. However, an experimentally verified physical model for the origin and structure of the TMS-induced discharge artifacts, by which these methods can be justified or evaluated, is still lacking. We re-examine the known contribution of the skin in creating the artifacts, and outline a detailed model for the relaxation of the charge accumulated at the electrode-gel-skin interface due to the TMS pulse. We then experimentally validate implications set forth by the model. We find that the artifacts decay like a power law in time rather than the commonly assumed exponential. In fact, the skin creates a power-law decay of order 1 at each electrode, which is turned into a power law of order 2 by the reference electrode. We suggest an artifact removal method based on the model which can be applied from times after the pulse as short as 2 milliseconds onwards to expose the full EEG from the brain. The method can separate the capacitive discharge artifacts from those resulting from cranial muscle activation, demonstrating that the capacitive effect dominates at short times. Overall, our insight into the physical process allows us to accurately access TMS-evoked EEG responses that directly follow the TMS pulse, possibly opening new opportunities in TMS-EEG research.

BACKGROUND: Alterations in the dynamic coordination of widespread brain networks are proposed to underlie cognitive symptoms of schizophrenia. However, there is limited understanding of the temporal evolution of these networks and how they relate to cognitive impairment. The current study was designed to explore dynamic patterns of network connectivity underlying cognitive features of schizophrenia.METHODS: In total, 21 inpatients with schizophrenia and 28 healthy control participants completed a cognitive task while electroencephalography data were simultaneously acquired. For each participant, Pearson cross-correlation was applied to electroencephalography data to construct correlation matrices that represent the static network (averaged over 1200 ms) and dynamic network (1200 ms divided into four windows of 300 ms) in response to cognitive stimuli. Global and regional network measures were extracted for comparison between groups.RESULTS: Dynamic network analysis identified increased global efficiency; decreased clustering (globally and locally); reduced strength (weighted connectivity) around the frontal, parietal, and sensory-motor areas; and increased strength around the occipital lobes (a peripheral hub) in patients with schizophrenia. Regional network measures also correlated with clinical features of schizophrenia. Network differences were prominent 900 ms following the cognitive stimuli before returning to levels comparable to those of healthy control participants.CONCLUSIONS: Patients with schizophrenia exhibited altered dynamic patterns of network connectivity across both global and regional measures. These network differences were time sensitive and may reflect abnormalities in the flexibility of the network that underlies aspects of cognitive function. Further research into network dynamics is critical to better understanding cognitive features of schizophrenia and identification of network biomarkers to improve diagnosis and treatment models.

A fundamental issue in the dynamics of complex systems is the resilience of the network in response to targeted attacks. This paper explores the local dynamics of the network attack process by investigating the order of removal of the nodes that have maximal degree, and shows that this dynamic network response can be predicted from the graph's initial connectivity. We demonstrate numerically that the maximal degree M(τ) of the network at time step τ decays exponentially with τ via a topology-dependent exponent. Moreover, the order in which sites are removed can be approximated by considering the network's "hierarchy" function h, which measures for each node Vi how many of its initial nearest neighbors have lower degree versus those that have a higher one. Finally, we show that the exponents we identified for the attack dynamics are related to the exponential behavior of spreading activation dynamics. The results suggest that the function h, which has both local and global properties, is a novel nodal measurement for network dynamics and structure.

A neuron will fire an action potential when its membrane potential exceeds a certain threshold. In typical activity of the brain, this occurs as a result of chemical inputs to its synapses. However, neurons can also be excited by an imposed electric field. In particular, recent clinical applications activate neurons by creating an electric field externally. It is therefore of interest to investigate how the neuron responds to the external field and what causes the action potential. Fortunately, precise and controlled application of an external electric field is possible for embryonic neuronal cells that are excised, dissociated and grown in cultures. This allows the investigation of these questions in a highly reproducible system. In this paper some of the techniques used for controlled application of external electric field on neuronal cultures are reviewed. The networks can be either one dimensional, i.e. patterned in linear forms or allowed to grow on the whole plane of the substrate, and thus two dimensional. Furthermore, the excitation can be created by the direct application of electric field via electrodes immersed in the fluid (bath electrodes) or by inducing the electric field using the remote creation of magnetic pulses.

Background: Schizophrenia has been long considered a disease of brain dysconnectivity. Until recently, it was difficult to quantify global and emergent features of the brain. To address this, topological measures which apply Network Analysis (based on Graph theory) to neuroimaging data are now able to identify global network connectivity properties of the brain. In the current study, we administer Transcranial Magnetic Stimulation (TMS) pulses to elicit a transient change in network organization (i.e. perturb the network), while electroencephalography (EEG) simultaneously measures network response. This novel approach allows us to examine global and emergent features of the schizophrenia network and assess whether network anomalies relate to clinical aspects of schizophrenia.Methods: One hundred TMS pulses (perturbations) were applied at a threshold of 80% to the frontal regions of schizophrenia patients (n = 14) and healthy controls (n = 12) while EEG was simultaneously recorded. For each participant, Pearson cross-correlation was applied to averaged EEG data to construct correlation matrices which represent the network response to the TMS stimuli. Global network measures were then extracted from these matrices for comparison between the groups. The relationship between the network metrics and clinical aspects (negative/positive/neurological symptoms) of schizophrenia were then examined.Results: Following the network perturbation (TMS pulse), schizophrenia patients presented with a more random network response, altered connectivity (number of links) and reduced segregation (clustering co-efficient) when compared to healthy controls. These altered network connectivity metrics were correlated with both clinical and neurological features of schizophrenia.Discussion: Schizophrenia patients presented with altered patterns of global network connectivity in response to the TMS perturbation of the frontal regions. Moreover, these network abnormalities were related to clinical aspects of schizophrenia. We anticipate that future combined TMS and network analysis studies will contribute to further mapping global network features of schizophrenia and identifying potential network biomarkers.

Using transcranial magnetic stimulation (TMS) in combination with electroencephalography (EEG) permits the measurement of the brain's global response to localized and abrupt stimulations. However, TMS induces large artifacts in the EEG recordings which are unrelated to brain activity and obscure the response of the brain. These artifacts can be removed algorithmically, and various methods have been suggested. Furthermore, several skin preparation methods have been demonstrated to reduce the artifacts. However, the lack of a theoretical model for the physical processes underlying the artifacts and their dynamics hampers an assessment of the performance of these algorithms and an evaluation of their validity.We find that, contrary to expectation, the decay of the electrode voltage after the TMS pulse follows a power law in time rather than an exponential. Based on this observation, we re-examine the role of the skin in creating the artifacts. We find that the artifact originates from a dual effect: The skin creates a first power law and this is coupled with the effect of the reference electrode that changes the order of the power law.We present a theoretical model for diffusion of the accumulated charge from the high electric fields of the TMS in the skin. This model reproduces the artifact precisely, including the many artifact shapes that are seen on the different electrodes. Based on this model, a removal method is derived, which exposes the full EEG from the brain, as validated by reconstructing 50Hz signals that are the same magnitude as the brain signals. Our insight of the physical process allows to accurately access TMS evoked potentials after 1.5 milliseconds following the TMS pulse.

Background: Down syndrome incidence in humans increases dramatically with maternal age. This is mainly the result of increased meiotic errors, but factors such as differences in abortion rate may play a role as well. Since the meiotic error rate increases almost exponentially after a certain age, its contribution to the overall incidence aneuploidy may mask the contribution of other processes. Results: To focus on such selection mechanisms we investigated transmission in trisomic females, using data from mouse models and from Down syndrome humans. In trisomic females the a-priori probability for trisomy is independent of meiotic errors and thus approximately constant in the early embryo. Despite this, the rate of transmission of the extra chromosome decreases with age in females of the Ts65Dn and, as we show, for the Tc1 mouse models for Down syndrome. Evaluating progeny of 73 Tc1 births and 112 Ts65Dn births from females aged 130 days to 250 days old showed that both models exhibit a 3-fold reduction of the probability to transmit the trisomy with increased maternal ageing. This is concurrent with a 2-fold reduction of litter size with maternal ageing. Furthermore, analysis of previously reported 30 births in Down syndrome women shows a similar tendency with an almost three fold reduction in the probability to have a Down syndrome child between a 20 and 30 years old Down syndrome woman. Conclusions: In the two types of mice models for Down syndrome that were used for this study, and in human Down syndrome, older females have significantly lower probability to transmit the trisomy to the offspring. Our findings, taken together with previous reports of decreased supportive environment of the older uterus, add support to the notion that an older uterus negatively selects the less fit trisomic embryos.

Oscillatory activity is widespread in dynamic neuronal networks. The main paradigm for the origin of periodicity consists of specialized pacemaking elements that synchronize and drive the rest of the network; however, other models exist. Here, we studied the spontaneous emergence of synchronized periodic bursting in a network of cultured dissociated neurons from rat hippocampus and cortex. Surprisingly, about 60% of all active neurons were self-sustained oscillators when disconnected, each with its own natural frequency. The individual neuron's tendency to oscillate and the corresponding oscillation frequency are controlled by its excitability. The single neuron intrinsic oscillations were blocked by riluzole, and are thus dependent on persistent sodium leak currents. Upon a gradual retrieval of connectivity, the synchrony evolves: Loose synchrony appears already at weak connectivity, with the oscillators converging to one common oscillation frequency, yet shifted in phase across the population. Further strengthening of the connectivity causes a reduction in the mean phase shifts until zerolag is achieved, manifested by synchronous periodic network bursts. Interestingly, the frequency of network bursting matches the average of the intrinsic frequencies. Overall, the network behaves like other universal systems, where order emerges spontaneously by entrainment of independent rhythmic units. Although simplified with respect to circuitry in the brain, our results attribute a basic functional role for intrinsic single neuron excitability mechanisms in driving the network's activity and dynamics, contributing to our understanding of developing neural circuits.

Down syndrome (DS) mouse models exhibit cognitive deficits, and are used for studying the neuronal basis of DS pathology. To understand the differences in the physiology of DS model neurons, we used dissociated neuronal cultures from the hippocampi of Ts65Dn and Tc1 DS mice. Imaging of [Ca²⁺]i and whole cell patch clamp recordings were used to analyze network activity and single neuron properties, respectively. We found a decrease of ~30% in both fast (A-type) and slow (delayed rectifier) outward potassium currents. Depolarization of Ts65Dn and Tc1 cells produced fewer spikes than diploid cells. Their network bursts were smaller and slower than diploids, displaying a 40% reduction in δf/f₀ of the calcium signals, and a 30% reduction in propagation velocity. Additionally, Ts65Dn and Tc1 neurons exhibited changes in the action potential shape compared to diploid neurons, with an increase in the amplitude of the action potential, a lower threshold for spiking, and a sharp decrease of about 65% in the after-hyperpolarization amplitude.Numerical simulations reproduced the DS measured phenotype by variations in the conductance of the delayed rectifier and A-type, but necessitated also changes in inward rectifying and M-type potassium channels and in the hyperpolarization-activated cyclic nucleotide-gated (HCN) channels. We therefore conducted whole cell patch clamp measurements of M-type potassium currents, which showed a ~90% decrease in Ts65Dn neurons, while HCN measurements displayed an increase of ~65% in Ts65Dn cells. Quantitative real-time PCR analysis indicates overexpression of 40% of KCNJ15, an inward rectifying potassium channel, contributing to the increased inhibition. We thus find that changes in several types of potassium channels dominate the observed DS model phenotype.

Excitation of neurons by an externally induced electric field is a long standing question that has recently attracted attention due to its relevance in novel clinical intervention systems for the brain. Here we use patterned quasi one-dimensional neuronal cultures from rat hippocampus, exploiting the alignment of axons along the linear patterned culture to separate the contribution of dendrites to the excitation of the neuron from that of axons. Network disconnection by channel blockers, along with rotation of the electric field direction, allows the derivation of strength-duration (SD) curves that characterize the statistical ensemble of a population of cells. SD curves with the electric field aligned either parallel or perpendicular to the axons yield the chronaxie and rheobase of axons and dendrites respectively, and these differ considerably. Dendritic chronaxie is measured to be about 1 ms, while that of axons is on the order of 0.1 ms. Axons are thus more excitable at short time scales, but at longer time scales dendrites are more easily excited. We complement these studies with experiments on fully connected cultures. An explanation for the chronaxie of dendrites is found in the numerical simulations of passive, realistically structured dendritic trees under external stimulation. The much shorter chronaxie of axons is not captured in the passive model and may be related to active processes. The lower rheobase of dendrites at longer durations can improve brain stimulation protocols, since in the brain dendrites are less specifically oriented than axonal bundles, and the requirement for precise directional stimulation may be circumvented by using longer duration fields.

In this paper we report the combination of microfluidics, optogenetics and calcium imaging as a cheap and convenient platform to study synaptic communication between neuronal populations in vitro. We first show that Calcium Orange indicator is compatible in vitro with a commonly used Channelrhodopsine-2 (ChR2) variant, as standard calcium imaging conditions did not alter significantly the activity of transduced cultures of rodent primary neurons. A fast, robust and scalable process for micro-chip fabrication was developed in parallel to build micro-compartmented cultures. Coupling optical fibers to each micro-compartment allowed for the independent control of ChR2 activation in the different populations without crosstalk. By analyzing the post-stimuli activity across the different populations, we finally show how this platform can be used to evaluate quantitatively the effective connectivity between connected neuronal populations.

Background: Down Syndrome (DS) is the most common chromosomal abnormality in humans, with many phenotypic characteristics-mental retardation is probably the most prominent one. Embryonic hippocampal neuronal cultures from two mouse models (TC1 and Ts65Dn) for DS were compared to control littermate cultures to detect possible cellular phenotypes of DS. Network behaviour was assessed using calcium imaging, and whole cell patch clamp technique was used to measure differences in single cell properties. Results: Calcium imaging, measured with fluo4, revealed smaller amplitude, shorter duration network bursts, with no change in basal calcium level, which was measured using Fura-2. Baclofen, a GABA-B agonist, suppressed network bursts with lower concentration in DS networks than in control networks. In patch clamped neurons, the threshold for excitation, after-hyperpolarization (AHP) amplitude and input resistance were reduced, while spike height was increased in DS cells compared to controls. Following blockage of sodium currents we found that potassium currents (slow and fast) are reduced in DS cells. Network activity was different with electrophysiological tools as well: bursts were shorter, the total amount of time the network spent bursting was shorter, and network bursts were less synchronized. Most of the differences appeared in both mouse models. Conclusions: DS cells were different both in the basic cell properties and in the assembly into a network. The changes in spike properties, along with reduced potassium currents all point to changes in potassium channels. We speculate that this may be due to possible overexpression of two potassium channel regulators, KCNE1 and KCNE2, whose genes reside on chromosome 21. The altered network activity along with baclofen experiments may be caused by increased inhibition. Two types of inwardly rectifying potassium channels genes reside on chromosome 21: KCNJ6, KCNJ15, and may be the cause of this increased network inhibition.

Transcranial Magnetic Stimulation (TMS) is a promising technology for both neurology and psychiatry. Positive treatment outcome has been reported, for instance in double blind, multi-center studies on depression. Nonetheless, the application of TMS towards studying and treating brain disorders is still limited by inter-subject variability and lack of model systems accessible to TMS. The latter are required to obtain a deeper understanding of the biophysical foundations of TMS so that the stimulus protocol can be optimized for maximal brain response, while inter-subject variability hinders precise and reliable delivery of stimuli across subjects. Recent studies showed that both of these limitations are in part due to the angular sensitivity of TMS. Thus, a technique that would eradicate the need for precise angular orientation of the coil would improve both the inter-subject reliability of TMS and its effectiveness in model systems. We show here how rotation of the stimulating field relieves the angular sensitivity of TMS and provides improvements in both issues. Field rotation is attained by superposing the fields of two coils positioned orthogonal to each other and operated with a relative phase shift in time. Rotating field TMS (rfTMS) efficiently stimulates both cultured hippocampal networks and rat motor cortex, two neuronal systems that are notoriously difficult to excite magnetically. This opens the possibility of pharmacological and invasive TMS experiments in these model systems. Application of rfTMS to human subjects overcomes the orientation dependence of standard TMS. Thus, rfTMS yields optimal targeting of brain regions where correct orientation cannot be determined (e.g., via motor feedback) and will enable stimulation in brain regions where a preferred axonal orientation does not exist.

Dictionaries link a given word to a set of alternative words (the definition) which in turn point to further descendants. Iterating through definitions in this way, one typically finds that definitions loop back upon themselves. We demonstrate that such definitional loops are created in order to introduce new concepts into a language. In contrast to the expectations for a random lexical network, in graphs of the dictionary, meaningful loops are quite short, although they are often linked to form larger, strongly connected components. These components are found to represent distinct semantic ideas. This observation can be quantified by a singular value decomposition, which uncovers a set of conceptual relationships arising in the global structure of the dictionary. Finally, we use etymological data to show that elements of loops tend to be added to the English lexicon simultaneously and incorporate our results into a simple model for language evolution that falls within the "rich-get-richer"class of network growth.

Neurotrophins are known to promote synapse development as well as to regulate the efficacy of mature synapses. We have previously reported that in two-dimensional rat hippocampal cultures, brain-derived neurotrophic factor (BDNF) and neurotrophin-3 significantly increase the number of excitatory input connections. Here we measure the effect of these neurotrophic agents on propagating fronts that arise spontaneously in quasi-one-dimensional rat hippocampal cultures. We observe that chronic treatment with BDNF increased the velocity of the propagation front by about 30%. This change is attributed to an increase in the excitatory input connectivity. We analyze the experiment using the Feinerman-Golomb/Ermentrout-Jacobi/Moses-Osan model for the propagation of fronts in a one-dimensional neuronal network with synaptic delay and introduce the synaptic connection probability between adjacent neurons as a new parameter of the model. We conclude that BDNF increases the number of excitatory connections by favoring the probability to form connections between neurons, but without significantly modifying the range of the connections (connectivity footprint).

We present a theoretical framework using quorum percolation for describing the initiation of activity in a neural culture. The cultures are modeled as random graphs, whose nodes are excitatory neurons with k_in inputs and k_out outputs, and whose input degrees k_in = k obey given distribution functions p_k. We examine the firing activity of the population of neurons according to their input degree (k) classes and calculate for each class its firing probability Φ_k(t) as a function of t. The probability of a node to fire is found to be determined by its in-degree k, and the first-to-fire neurons are those that have a high k. A small minority of high-k-classes may be called "Leaders," as they form an interconnected sub-network that consistently fires much before the rest of the culture. Once initiated, the activity spreads from the Leaders to the less connected majority of the culture. We then use the distribution of in-degree of the Leaders to study the growth rate of the number of neurons active in a burst, which was experimentally measured to be initially exponential. We find that this kind of growth rate is best described by a population that has an in-degree distribution that is a Gaussian centered around k = 75 with width σ = 31 for the majority of the neurons, but also has a power law tail with exponent -2 for 10% of the population. Neurons in the tail may have as many as k = 4,700 inputs. We explore and discuss the correspondence between the degree distribution and a dynamic neuronal threshold, showing that from the functional point of view, structure and elementary dynamics are interchangeable. We discuss possible geometric origins of this distribution, and comment on the importance of size, or of having a large number of neurons, in the culture.

Objective: The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) has been hampered by the large artifact that the TMS generates in the EEG. Using TMS with EEG necessitates a sophisticated artifact-resistant EEG system that can acquire reliable signals in the crucial several tens of milliseconds immediately following the TMS pulse. Here, we demonstrate the use of a novel artifact removal algorithm together with a 24-bit EEG system to achieve similar recordings as those obtained with the dedicated TMS-compatible EEG system. Methods: This setup was used to compare TMS-evoked responses between a group of healthy controls and a group of patients with schizophrenia, a condition in which effective neural connectivity is thought to be compromised. Results: We observe differences in TMS-evoked responses between the two groups, similar to those recently reported in a study that used a dedicated TMS-compatible EEG system. Conclusions: The standard 24-bit EEG system combined with an artifact removal algorithm produces results similar to the dedicated TMS-compatible system. Significance: This paves the way for more researchers and clinicians to use TMS-evoked responses for research and diagnosis of a wide spectrum of disorders.

Cooperative effects in neural networks appear because a neuron fires only if a minimal number m>1 of its inputs are excited. The multiple inputs requirement leads to a percolation model termed quorum percolation. The connectivity undergoes a phase transition as m grows, from a network-spanning cluster at low m to a set of disconnected clusters above a critical m. Both numerical simulations and the model reproduce the experimental results well. This allows a robust quantification of biologically relevant quantities such as the average connectivity and the distribution of connections p_k from different neural densities.

The neurotrophic factors brain-derived neurotrophic factor (BDNF) and neurotrophin-3 (NT-3) have been shown to promote excitatory and inhibitory synapse development. However, a quantitative analysis of their influence on connectivity has proven in general difficult to achieve. In this work we use a novel experimental approach based on percolation concepts that provides a quantification of the average number of connections per neuron. In combination with electrophysiological measurements, we characterize the changes in network connectivity induced by BDNF and NT-3 in rat hippocampal cultures. We show that, on the one hand, BDNF and NT-3 accelerate the maturation of connectivity in the network by about 17 h. On the other hand, BDNF and NT-3 increase the number of excitatory input connections by a factor of about two, but without modifying the number of inhibitory input connections. This scenario of a dominant effect on the excitation is supported by the analysis of spontaneous population bursts in cultures treated with either BDNF or NT-3, which show burst amplitudes that are insensitive to the blockade of inhibition. A leaky integrate-and-fire model reproduces the experimental results well.

We analyze the characteristics of front propagation in activity of 1-D neuronal cultures by numerical simulations, using only excitatory dynamics. Experimental results in 1-D cultures of hippocampal neurons from rats have shown the spontaneous generation of a slow, low amplitude pulse that precedes a high amplitude, fast pulse that propagates through all the system. Notably, this transition appears both with and without the presence of functioning inhibitory synapses. In accordance with previous work, we demonstrate that purely excitatory integrate and fire neurons with depression in the synapses suffice to produce fast and uniform pulses but cannot explain the appearance of slow, weak pulses. We propose to explain the slow pulses by increasing the complexity of the neuron model in a purely excitatory network with connectivity as close to the experiments as possible. This approach allows us to show that spike frequency adaptation is a fundamental ingredient for the initiation process of the pulse. The introduction of a slow variable that mimics the presence of the slow K⁺ channels in the soma and produces spike frequency adaptation increases strongly the persistence of the transient activity before the emergence of the fast pulse up to temporal and spatial scales comparable with the experiments. Finally, we demonstrate that proper levels of additive white noisy currents generate such pulses spontaneously, fully reproducing the experimental results.

Functional logical microcircuits are an essential building block of computation in the brain. However, single neuronal connections are unreliable, and it is unclear how neuronal ensembles can be constructed to achieve high response fidelity. Here, we show that reliable, mesoscale logical devices can be created in vitro by geometrical design of neural cultures. We control the connections and activity by assembling living neural networks on quasi-one-dimensional configurations. The linear geometry yields reliable transmission lines. Incorporating thin lines creates 'threshold' devices and logical 'AND gates'. Breaking the symmetry of transmission makes neuronal 'diodes'. All of these function with error rates well below that of a single connection. The von Neumann model of redundancy and error correction accounts well for all of the devices, giving a quantitative estimate for the reliability of a neuronal connection and of threshold devices. These neuronal devices may contribute to the implementation of computation in vitro and, ultimately, to its understanding in vivo.

We introduce an approach for the quantitative assessment of the connectivity in neuronal cultures, based on the statistical mechanics of percolation on a graph. This allows us to monitor the development of the culture and to see the emergence of connectivity in the network. The culture becomes fully connected at a time equivalent to the expected time of birth. The spontaneous bursting activity that characterizes cultures develops in parallel with the connectivity. The average number of inputs per neuron can be quantitatively determined in units of m₀, the number of activated inputs needed to excite the neuron. For m₀ ≃ 15 we find that hippocampal neurons have on average ≈60-120 inputs, whereas cortical neurons have ≈75-150, depending on neuronal density. The ratio of excitatory to inhibitory neurons is determined by using the GABA_A antagonist bicuculine. This ratio changes during development and reaches the final value at day 7-8, coinciding with the expected time of the GABA switch. For hippocampal cultures the inhibitory cells comprise ≈30% of the neurons in the culture whereas for cortical cultures they are ≈20%. Such detailed global information on the connectivity of networks in neuronal cultures is at present inaccessible by any electrophysiological or other technique.

Transcranial magnetic stimulation is a remarkable tool for neuroscience research, with a multitude of diagnostic and therapeutic applications. Surprisingly, application of the same magnetic stimulation directly to neurons that are dissected from the brain and grown in vitro was not reported to activate them to date. Here we report that central nervous system neurons patterned on large enough one-dimensional rings can be magnetically stimulated in vitro. In contrast, two-dimensional cultures with comparable size do not respond to excitation. This happens because the one-dimensional pattern enforces an ordering of the axons along the ring, which is designed to follow the lines of the magnetically induced electric field. A small group of sensitive (i.e., initiating) neurons respond even when the network is disconnected, and are presumed to excite the entire network when it is connected. This implies that morphological and electrophysiological properties of single neurons are crucial for magnetic stimulation. We conjecture that the existence of a select group of neurons with higher sensitivity may occur in the brain in vivo as well, with consequences for transcranial magnetic stimulation.

Eytan and Marom (2006 J. Neurosci. 26 8465-76) recently showed that the spontaneous bursting activity of rat neuron cultures includes 'first-to-fire' cells that consistently fire earlier than others. Here, we analyze the behavior of these neurons in long-term recordings of spontaneous activity of rat hippocampal and rat cortical neuron cultures from three different laboratories. We identify precursor events that may either subside ('aborted bursts') or can lead to a full-blown burst ('pre-bursts'). We find that the activation in the preburst typically has a first neuron ('leader'), followed by a localized response in its neighborhood. Locality is diminished in the bursts themselves. The long-term dynamics of the leaders is relatively robust, evolving with a half-life of 23-34 h. Stimulation of the culture alters the leader distribution, but the distribution stabilizes within about 1 h. We show that the leaders carry information about the identity of the burst, as measured by the signature of the number of spikes per neuron in a burst. The number of spikes from leaders in the first few spikes of a precursor event is furthermore shown to be predictive with regard to the transition into a burst (pre-burst versus aborted burst). We conclude that the leaders play a role in the development of the bursts and conjecture that they are part of an underlying sub-network that is excited first and then acts as a nucleation center for the burst.

Improvements in technique in conjunction with an evolution of the theoretical and conceptual approach to neuronal networks provide a new perspective on living neurons in culture. Organization and connectivity are being measured quantitatively along with other physical quantities such as information, and are being related to function. In this review we first discuss some of these advances, which enable elucidation of structural aspects. We then discuss two recent experimental models that yield some conceptual simplicity. A one-dimensional network enables precise quantitative comparison to analytic models, for example of propagation and information transport. A two-dimensional percolating network gives quantitative information on connectivity of cultured neurons. The physical quantities that emerge as essential characteristics of the network in vitro are propagation speeds, synaptic transmission, information creation and capacity. Potential application to neuronal devices is discussed.

Transcranial Magnetic Stimulation (TMS) is rapidly gaining acceptance as a non-invasive probe into brain functionality. We utilize TMS to study the connectivity of a simple motor network in patients of schizophrenia (N = 19), and in healthy control subjects (N = 9). TMS was used in an externally paced finger tapping task, perturbing the internal network oscillations invoked by the finger motion as it keeps pace with a metronome. TMS perturbations were synchronized to the metronome and applied to the network at the level of the primary motor cortex (M1). Contrary to initial expectations, TMS did not affect the sensorimotor synchronization of subjects with schizophrenia or their tapping accuracy. TMS did cause extreme deviations in the finger's trajectory, and altered the timing perceptions of subjects with schizophrenia. Additionally, it invoked high-level deficiencies related to attention and volition in the form of lapses, implying that the connectivity between modules in the brain that underlie motor control, sensorimotor synchronization, timing perception and awareness of action, can be disrupted by TMS in subjects with schizophrenia, but not in healthy subjects. The ability to disrupt high level network functions with perturbations to the lower level of M1 supports models describing deficits in connectivity of distributed networks in the brains of schizophrenia patients. It also demonstrates the use of TMS to probe connectivity between components of such networks.

We investigate the propagation of neural activity along one-dimensional rat hippocampal cultures patterned in lines over multielectrode arrays. Activity occurs spontaneously or is evoked by local electrical or chemical stimuli, with different resulting propagation velocities and firing rate amplitudes. A variability of an order of magnitude in velocity and amplitude is observed in spontaneous activity. A linear relation between velocity and amplitude is identified. We define a measure for neuron activation synchrony and find that it correlates with front velocity and is higher for electrically evoked fronts. We present a model that explains the linear relation between amplitude and velocity, which highlights the role of synchrony. The relation to current models for signal propagation in neural media is discussed.

Spontaneous activity is typical of in vitro neural networks, often in the form of large population bursts. The origins of this activity are attributed to intrinsically bursting neurons and to noisy backgrounds as well as to recurrent network connections. Spontaneous activity is often observed to emanate from localized sources or initiation zones, propagating from there to excite large populations of neurons. In this study, we use unidimensional cultures to overcome experimental difficulties in identifying initiation zones in vivo and in dissociated two-dimensional cultures. We found that spontaneous activity in these cultures is initiated exclusively in localized zones that are characterized by high neuronal density but also by recurrent and inhibitory network connections. We demonstrate that initiation zones compete in driving network activity in a winner-takes-most scenario.

We study neural connectivity in cultures of rat hippocampal neurons. We measure the neurons' response to an electric stimulation for gradual lower connectivity, and characterize the size of the giant cluster in the network. The connectivity undergoes a percolation transition described by the critical exponent beta similar or equal to 0.65. We use a theoretic approach based on bond-percolation on a graph to describe the process of disintegration of the network and extract its statistical properties. Together with numerical simulations we show that the connectivity in the neural culture is local, characterized by a gaussian degree distribution and not a power law one.

Thoughts and ideas are multidimensional and often concurrent, yet they can be expressed surprisingly well sequentially by the translation into language. This reduction of dimensions occurs naturally but requires memory and necessitates the existence of correlations, e.g., in written text. However, correlations in word appearance decay quickly, while previous observations of long-range correlations using random walk approaches yield little insight on memory or on semantic context. Instead, we study combinations of words that a reader is exposed to within a "window of attention," spanning about 100 words. We define a vector space of such word combinations by looking at words that co-occur within the window of attention, and analyze its structure. Singular value decomposition of the co-occurrence matrix identifies a basis whose vectors correspond to specific topics, or "concepts" that are relevant to the text. As the reader follows a text, the "vector of attention" traces out a trajectory of directions in this "concept space." We find that memory of the direction is retained over long times, forming power-law correlations. The appearance of power laws hints at the existence of an underlying hierarchical network. Indeed, imposing a hierarchy similar to that defined by volumes, chapters, paragraphs, etc. succeeds in creating correlations in a surrogate random text that are identical to those of the original text. We conclude that hierarchical structures in text serve to create long-range correlations, and use the reader's memory in reenacting some of the multidimensionality of the thoughts being expressed.

Magnetic stimulation of nerves is attracting increased attention recently, as it has been found to be useful in therapy of neural disorders in humans. In an effort to explain the mechanisms of magnetic stimulation, we focus in this paper on the dependence of magnetic stimulation on neuronal morphology and in particular on the importance of curvature of axonal bundles. Using the theory of passive membrane dynamics, we predict the threshold power (the minimum stimulation power required to initiate an action potential) of specific axonal morphologies. In the experimental section, we show that magnetic stimulation of the frog sciatic nerve follows our theoretical predictions. Furthermore, the voltage length constant of the nerve can be measured based on these results alone.

We show that the exponential length distribution that is typical of actin filaments under physiological conditions dramatically narrows in the presence of i) crosslinker proteins or ii) polyvalent counterions or iii) depletion-mediated attractions. A simple theoretical model shows that, at equilibrium, short-range attractions that are known to enhance the tendency of filaments to align parallel to each other, lead to an increase in the average filament length and a decrease in the relative width of the distribution of filament lengths.

The ability of synchronous population activity in layered networks to transmit a rate code is a focus of recent debate. We investigate these issues using a patterned unidimensional hippocampal culture. The network exhibits population bursts that travel its full length, with the advantage that signals propagate along a clearly defined path. The amplitudes of activity are measured using calcium imaging, a good approximate of population rate code, and the distortion of the signal as it travels is analyzed. We demonstrate that propagation along the line is precisely described by information theory as a chain of Gaussian communication channels. The balance of excitatory and inhibitory synapses is crucial for this transmission. However, amplitude information carried along this layered neuronal structure fails within 3 mm, ∼10 mean axon lengths, and is limited by noise in the synaptic transmission. We conclude that rate codes cannot be reliably transmitted through long layered networks.

We study living neural networks by measuring the neurons' response to a global electrical stimulation. Neural connectivity is lowered by reducing the synaptic strength, chemically blocking neurotransmitter receptors. We use a graph-theoretic approach to show that the connectivity undergoes a percolation transition. This occurs as the giant component disintegrates, characterized by a power law with an exponent β 0.65. β is independent of the balance between excitatory and inhibitory neurons and indicates that the degree distribution is Gaussian rather than scale free.

Dissociated neurons were cultured on lines of various lengths covered with adhesive material to obtain an experimental model system of linear signal transmission. The neuronal connectivity in the linear culture is characterized, and it is demonstrated that local spiking activity is relayed by synaptic transmission along the line of neurons to develop into a large-scale population burst. Formally, this can be treated as a one-dimensional information channel. Directional propagation of both spontaneous and stimulated bursts along the line, imaged with the calcium indicator Fluo-4, revealed the existence of two different propagation velocities. Initially, a small number of neighboring neurons fire, leading to a slow, small and presumably asynchronous wave of activity. The signal then spontaneously develops to encompass much larger and further populations, and is characterized by fast propagation of high-amplitude activity, which is presumed to be synchronous. These results are well described by an existing theoretical framework for propagation based on an integrate-and-fire model.

We present a model for the actin contractile ring of adherent animal cells. The model suggests that the actin concentration within the ring and consequently the power that the ring exerts both increase during contraction. We demonstrate the crucial role of actin polymerization and depolymerization throughout cytokinesis, and the dominance of viscous dissipation in the dynamics. The physical origin of two phases in cytokinesis dynamics ("biphasic cytokinesis") follows from a limitation on the actin density. The model is consistent with a wide range of measurements of the midzone of dividing animal cells.

We study the dynamic network of e-mail traffic and find that it develops self-organized coherent structures similar to those appearing in many nonlinear dynamic systems. Such structures are uncovered by a general information theoretic approach to dynamic networks based on the analysis of synchronization among trios of users. In the e-mail network, coherent structures arise from temporal correlations when users act in a synchronized manner. These temporally linked structures turn out to be functional, goal-oriented aggregates that must react in real time to changing objectives and challenges (e.g., committees at a university). In contrast, static structures turn out to be related to organizational units (e.g., departments).

The development of a technique for imaging liquids, cells and other wet samples in scanning electron microscopy (SEM) was discussed. The system was based on the isolation of the fluid sample from the vacuum by the introduction of a membranous partition. The membrane was thin enough for energetic electron beams to go through and interact with the sample. The properties required for the membrane for imaging of samples were described. For low contrast sample, the image resolution for the system was found to be better than optical microscopy. The resolution was found to be better when the particle in the sample was closer to the membrane.

Actin filament length distribution in cells is often regulated to fit specific tasks. In comparison to the well-studied regulation of the average filament length (e.g., using capping proteins), controlling the width of the distribution is less well understood. We utilize two complementary methods to measure the effect of α-actinin on the width of the distribution of lengths of F-actin in vitro. Analyzing transmission electron micrographs shows that crosslinking by α-actinin reduces the width of the length distribution of F-actin, decreasing the coefficient of variation by two- to threefold. Analysis of fluorescence data from depolymerization assays confirms this observation. We suggest a mechanistic molecular model in which a local (weak) stabilization of crosslinked monomers in the filament is the physical origin of the decrease in the variance of lengths. Although α-actinin is known to bind reversibly to F-actin, our model shows that even weak binding can produce this effect, and that in fact it persists throughout a wide range of binding strengths.

A capability for scanning electron microscopy of wet biological specimens is presented. A membrane that is transparent to electrons protects the fully hydrated sample from the vacuum. The result is a hybrid technique combining the ease of use and ability to see into cells of optical microscopy with the higher resolution of electron microscopy. The resolution of low-contrast materials is ≈100 nm, whereas in high-contrast materials the resolution can reach 10 nm. Standard immunogold techniques and heavy-metal stains can be applied and viewed in the fluid to improve the contrast. Images present a striking combination of whole-cell morphology with a wealth of internal details. A possibility for direct inspection of tissue slices transpires, imaging only the external layer of cells. Simultaneous imaging with photons excited by the electrons incorporates data on material distribution, indicating a potential for multilabeling and specific scintillating markers.

We investigate the final stage of cytokinesis in two types of amoeba, pointing out the existence of biphasic furrow contraction. The first phase is characterized by a constant contraction rate, is better studied, and seems universal to a large extent. The second phase is more diverse. In Dictyostelium discoideum the transition involves a change in the rate of contraction, and occurs when the width of the cleavage furrow is comparable to the height of the cell. In Entamoeba invadens the contractile ring carries the cell through the first phase, but cannot complete the second stage of cytokinesis. As a result, a cooperative mechanism has evolved in that organism, where a neighboring amoeba performs directed motion towards the dividing cell, and physically causes separation by means of extending a pseudopod. We expand here on a previous report of this novel chemotactic signaling mechanism.

A double pipette system for local, controlled drug infusion is presented. Two concentric pipettes can be manipulated separately and pressurized independently by a designated double holder. The inner pipette is loaded with the desirable solution (drug), and functions as a source, while the outer one is a sink. This gives a flow of the solution between the two pipettes that protrudes only a small distance into the surrounding fluid and does not diffuse away. Time resolution of the infusion is highly controllable, and oscillatory flow can be generated. Three implementations of the double pipette system are demonstrated. We show that local application of neurotransmitters in neuronal networks is an efficient way of stimulating activity in the network. We then present a wet micro lithography technique using topical application of proteins onto the substrate. Finally, we show that we can localize a given drug on a small targeted part of a cell.

A novel method for detection of noble-metal nanoparticles by their nonlinear optical properties is presented and applied for specific labeling of cellular organelles. When illuminated by laser light in resonance with their plasmon frequency these nanoparticles generate an enhanced multiphoton signal. This enhanced signal is measured to obtain a depth-resolved image in a laser scanning microscope setup. Plasmon-resonance images of both live and fixed cells, showing specific labeling of cellular organelles and membranes, either by two-photon autofluorescence or by third-harmonic generation, are presented.

We introduce a quantitative method that utilizes scanning electron microscopy for the analysis of protein chips (SEMPC). SEMPC is based upon counting target-coated gold particles interacting specifically with ligands or proteins arrayed on a derivative microscope glass slide by utilizing backscattering electron detection. As model systems, we quantified the interactions of biotin and streptavidin and of an antibody with its cognate hapten. Our method gives quantitative molecule-counting capabilities with an excellent signal-to-noise ratio and demonstrates a broad dynamic range while retaining easy sample preparation and realistic automation capability. Increased sensitivity and dynamic range are achieved in comparison to currently used array detection methods such as fluorescence, with no signal bleaching, affording high reproducibility and compatibility with miniaturization. Thus, our approach facilitates the determination of the absolute number of molecules bound to the chip rather than their relative amounts, as well as the use of smaller samples.

Keywords: Biophysics

Beyond the information stored in pages of the World Wide Web, novel types of "meta-information" are created when pages connect to each other. Such meta-information is a collective effect of independent agents writing and linking pages, hidden from the casual user. Accessing it and understanding the interrelation between connectivity and content in the World Wide Web is a challenging problem [Botafogo, R. A. & Shneiderman, B. (1991) in Proceedings of Hypertext (Assoc. Comput. Mach., New York), pp. 63-77 and Albert, R. & Barabási, A.-L. (2002) Rev. Mod. Phys. 74, 47-97]. We demonstrate here how thematic relationships can be located precisely by looking only at the graph of hyperlinks, gleaning content and context from the Web without having to read what is in the pages. We begin by noting that reciprocal links (co-links) between pages signal a mutual recognition of authors and then focus on triangles containing such links, because triangles indicate a transitive relation. The importance of triangles is quantified by the clustering coefficient [Watts, D. J. & Strogatz, S. H. (1999) Nature (London) 393, 440-442], which we interpret as a curvature [Bridson, M. R. & Haefliger, A. (1999) Metric Spaces of Non-Positive Curvature (Springer, Berlin)]. This curvature defines a World Wide Web landscape whose connected regions of high curvature characterize a common topic. We show experimentally that reciprocity and curvature, when combined, accurately capture this meta-information for a wide variety of topics. As an example of future directions we analyze the neural network of Caenorhabditis elegans, using the same methods.

Asexual cells are normally able to reproduce entirely by themselves. But we have discovered that in about one-third of the dividing cells of Entamoeba invadens contraction of the cleavage furrow1 may stop before separation is complete. We show here that the connected daughter cells overcome this problem by calling upon a neighbouring amoeba to help them achieve the final stage of division. The 'midwife' cell is chemotactically recruited for this mechanical intervention in what is a surprising example of primitive cooperation.

Gradual disruption of the actin cytoskeleton induces a series of structural shape changes in cells leading to a transformation of cylindrical cell extensions into a periodic chain of 'pearls.' Quantitative measurements of the pearling instability give a square-root behavior for the wavelength as a function of drug concentration. We present a theory that explains these observations in terms of the interplay between rigidity of the submembranous actin shell and tension that is induced by boundary conditions set by adhesion points. The theory allows estimation of the rigidity and thickness of this supporting shell. The same theoretical considerations explain the shape of nonadherent edges in the general case of untreated cells.

In the mid-l7th century Galileo Galilei dropped two metal balls from the Leaning Tower of Pisa and showed that they fall at the same rate despite their different masses. In a later version of the experiment, astronaut David Scott dropped a hammer and a feather on the Moon and saw that they hit the surface at the same time. Why did Galileo not choose this more dramatic combination of objects to drop from the Leaning Tower?

We detail the experimental situation concerning the fingering instability that occurs when a solid fuel is forced to burn against a horizontal oxidizing wind. The instability appears when the Rayleigh number for convection is below criticality. The focus is on the developed fingering state. We present direct measurements of the depletion of oxygen by the front as well as new results that connect heat losses to the characteristic scale of the instability. In addition, we detail the experimental system, elaborate (qualitatively and quantitatively) on the results that were previously presented, and discuss new observations. We also show that the same phenomenological model applies to electrochemical deposition.

A thin solid, burning against an oxidizing wind, develops a fingering instability. The effect is observed in a narrow gap geometry, where free convection is suppressed. Focusing on the developed nonlinear state, we find that two length scales coexist. The spacing between fingers is determined by the Péclet number, and the finger width is determined by heat losses. Dense fingers develop by tip splitting. A phenomenological model accurately predicts the fingers spacing, and is generally applicable to diffusion limited systems. We suggest that the effect is a new, accurately controllable, version of the thermal-diffusive instability.

In an experiment on thin flat strips falling through a fluid in a vertical cell, two fundamental motions are observed: side-to-side oscillation (flutter) and end-over-end rotation (tumble). At high Reynolds number, the dimensionless similarity variable describing the dynamics is the Froude number Fr, being the ratio of characteristic times for downward motion and pendular oscillations. The transition from flutter to tumble occurs at Fr_c=0.67±0.05. We propose a phenomenological model including inertial drag and lift which reproduces this motion, and directly yields the Froude similarity.

We present the phenomenology of transformations in lipid bilayers that are excited by laser tweezers. A variety of dynamic instabilities and shape transformations are observed, including the pearling instability, expulsion of vesicles, and more exotic ones, such as the formation of passages. Our physical picture of the laser-membrane interaction is based on the generation of tension in the bilayer and loss of surface area. Although tension is the origin of the pearling instability, it does not suffice to explain expulsion of vesicles, where we observe opening of giant pores and creeping motion of bilayers. We present a quantitative theoretical framework to understand most of the observed phenomenology. The main hypothesis is that lipid is pulled into the optical trap by the familiar dielectric effect, is disrupted, and finally is repackaged into an optically unresolvable suspension of colloidal particles. This suspension, in turn, can produce osmotic pressure and depletion forces, driving the observed transformations.

We present a new approach to probing single-particle dynamics that uses dynamic light scattering from a localized region. By scattering a focused laser beam from a micron-size particle, we measure its spatial fluctuations via the temporal autocorrelation of the scattered intensity. We demonstrate the applicability of this approach by measuring the three-dimensional force constants of a single bead and a pair of beads trapped by laser tweezers. The scattering equations that relate the scattered intensity autocorrelation to the particle position correlation function are derived. This technique has potential applications for measurement of biomolecular force constants and probing viscoelastic properties of complex media.

We study flow in a porous medium in the presence of a discontinuous perturbation (defect) that perturbs its parameters. The discontinuous perturbation is at the interface between regions of different porosities, produced in the experiment by uniformly depositing black toner with a laser printer. When water propagates in such a medium the wetting front develops a nontrivial, curved steady state solution. We present experimental measurements of the profiles and their propagation rate, as well as the characteristics of the steady state solution. A naive attempt to use perturbation theory fails due to discontinuities at the \u201cdefect.\u201d We proceed to develop a theoretical treatment based on Laplacian flow, that is good to all orders and predicts most of the features that can be observed. We find good quantitative agreement between theory and experiment, without any fit parameters.

We present new results on the fingering instability in solid fuel combustion. The instability occurs when horizontal fuel is forced to burn against an oxidizing wind, under the suppression of vertical flow (natural convection). Focusing on the qualitative behavior of the developed fingering state, we present experimental results that connect the length scales to the two dominant transport processes (transport of reactants and loss of heat). We first elaborate on the relation between reactant transport and the spacing between fingers and proceed to present experimental evidence that relate the characteristic scale (finger width) to the heat losses near the front. The heat losses are varied by three methods: changing the system height, adding nonreacting (cooling) gas to the flow, and changing the heat conductivity of the bottom plate. We discuss the effect of these methods and conclude that the characteristic scale decreases as the heat losses increase. From a practical viewpoint, the results expose a fingering regime in which it is possible that a slow persistent finger will create and maintain a fire hazard that is below conventional detection. A very high degree of experimental control is achieved in the smoldering regime. However, the phenomenon is fuel independent and occurs in other modes of combustion.

We report an experimental and theoretical study of wetting front propagation in anisotropic paper. The height-height correlation function is measured in the presence of large scale biasing and is found to scale with an exponent x = 0.4. Theoretical analysis of this two-dimensional invasion predicts logarithmic scaling for isotropic paper. The observed nonzero roughness is due to correlated randomness and anisotropy in the paper.

Irradiation of a giant unilamellar lipid bilayer vesicle with a focused laser spot leads to a tense pressurized state which persists indefinitely after laser shutoff. If the vesicle contains another object it can then be gently and continuously expelled from the tense outer vesicle. Remarkably, the inner object can be almost as large as the parent vesicle; its volume is replaced during the exit process. We offer a qualitative theoretical model to explain these and related phenomena. The main hypothesis is that the laser trap pulls in lipid and ejects it in the form of submicron objects, whose osmotic activity then drives the expulsion.

We report quantitative measurements above threshold in the pearling instability of cylindrical membranes. Induced by optical tweezers, the instability propagates outward from the laser trap with well defined wavelength, and velocity. All measured quantities scale with the reduced tension control parameter ε ≡ (Σ - Σ_c)/Σ_c. A critical slowing down for initiation of the instability is observed. The values of the velocity, wavelength, and delay time agree with marginal stability and linear analysis. Measurements very close to threshold are strongly masked by thermal fluctuations.

We developed an experimental technique which probes the dynamics of a single colloidal particle over many decades in time, with spatial resolution of a few nanometers. By scattering a focused laser beam from a particle observed in an optical microscope, we measure its fluctuations via the temporal autocorrelation function of the scattered intensity g\(t\). This technique is demonstrated by applying it to a single Brownian particle in an optical trap of force constant k. The decay times of g\(t\), which are related to the particle position autocorrelation function, scale as k⁻¹, as expected from theory.

We report an experimental study of the morphological phases of zinc electrodeposits. The microscopic morphology is based on two alternative growth mechanisms: tip splitting or dendritic, and is decoupled from the macroscopic structure. The latter is characterized by the density of branches and stability of the front. The key role in the microscopic selection is played by the initial concentration of zinc. The importance of ion availability is manifested again in the Hecker transition, where the departure from dense branching morphology coincides with the exhaustion of zinc from the original solution.

A new apparatus which makes it possible to measure flow smallangle light scattering (\u201cflowSALS\u201d) and to observe the development of the supramolecular structure by an optical microscope (\u201cshear microscopy\u201d) has been developed in our laboratory. It simultaneously provides information on reciprocal space from SALS and on real space from optical microscopy. Therefore, the development of the supramolecular structure in systems such as polymer solutions and polymer mixtures as well as liquid crystals and colloidal systems under shear can be investigated in depth. Shearinduced phase separation and shearinduced homogenization of some polymer solution systems were investigated using this apparatus.

Loosely bound membranes exhibit an unusual elastic response when pinched together by optical tweezers, locally unbinding to a large intermembrane distance. Tweezing a stack of many bound membranes produces extreme local swelling in the vicinity of the tweezing point. We introduce a model that incorporates bending elasticity, fluctuations, and intermembrane interactions to calculate the membrane profiles subject to a local pinch. Theoretically, we find strongly overshooting profiles in agreement with experiment. We predict scaling behavior of the overshoot with the pinch strength and size.

We report experimental observations and theoretical analysis of entropy driven expulsion in giant lipid vesicles, produced by the application of optical tweezers. The tweezers induce tension in membranes by attracting lipid material into the optical trap. This suppresses fluctuations in the vesicles and converts them into tense pressurized spheres. After shutting off the laser, overpressurized vesicles spontaneously expel inner vesicles, releasing their inner pressure.

Transmission light micrographs show that domains in spinodal decomposition are elongated into extremely long strings in steady states of a polymer solution under strong shear flow. The shear flow stabilizes the string against their intrinsic surface tension instabilities. The string diameter decreases with increase in the shear rate and ultimately becomes of the order of the interface thickness, resulting in shear-induced homogenization.

We investigate the stability of tubular fluid membranes by perturbing them with optical tweezers. A peristaltic instability appears, with wavelength on the order of the tube circumference, characterized by tautness and suppression of curvature fluctuations in the membrane. We interpret this in terms of a model that includes a surface tension term in the elastic energy, and describes a transition to stable, finite amplitude peristaltic states. At high amplitudes the experiment reveals new dynamic states of "pearls" interconnected via thin tubes along which they travel and aggregate.

We present an experimental study of the scaling laws for the front (or cap) of an isolated, laminar starting plume. The scaling relations are formulated and measured experimentally over a range of power, fluids, and heaters. The results are that the cap rises at constant velocity, grows diffusively in width, and its temperature depends inversely on height. This extends analytic results by Batchelor (1954) for the column (stem) below the front. The source size determines initial conditions for the cap, but does not affect it in the far field. The shape of the front is fitted by a model of potential flow. The interaction between plume caps is complex, but with simple underlying dynamics. We conjecture that some of our conclusions can be applied to a distribution of plumes, as in soft turbulent convection.

We present an experimental study of the dynamics and interactions of laminar plumes emitted from a localized heat source. The observations are explained by a simple model of the flow structure around a plume. Using sources and sinks in a uniform flow, we reproduce the experimental shapes and extract the scaling behavior of the size of the plume. The model describes the initial stage of the interaction between plumes.

We present an experimental study of stationary convection in a binary mixture at positive values of a separation ratio. The interplay between the Rayleigh-Bénard and the Sorét mechanisms of instability and the corresponding boundary conditions gives us the possibility to observe a transition from large- to small-scale structures as well as a transition between patterns with different symmetries. We also investigate an influence of lateral boundaries and the cell geometry on the pattern selection.

We present a study of oscillatory convection in two experimental systems: ethanol-water mixtures in a rectangular container heated from below and a thin layer of nematic liquid crystals under low frequency ac voltage. In both systems the first bifurcation is the transition to travelling waves (TW) with finite wave vector and frequency. We report experimental observations of a sequence of spatial structures and dynamical behaviour of nonlinear TW in a regime of a weak nonlinearity. Most of the rich variety of spatial and dynamical behaviour which we observe in one-dimensional finite geometries has been reproduced by numerical simulations based on a simple model of coupled Ginzburg-Landau equations which considers only the combination of translation and finite geometry. More complicated spatio-temporal behaviour of TW in cells with two-dimensional geometry which initiated by defect nucleation is attributed to the mechanism of modulational instability of TW.

We present an experimental evidence of the existence of a large-scale global circulation flow in nonlinear traveling wave states in convecting binary mixtures. We covered three of the known TW patterns: linear counter-propagating waves (CPW), spatially and temporally modulated TW and spatially modulated TW. We found that the linear CPW that occur in transient regime do not carry mass while both nonlinear states do, and the mass-transport onset coincides with the transition to nonlinear TW. Using a photochromic technique we were able to show that in the spatially modulated TW state two types of particle trajectories exist: closed one which corresponds to mass transport with TW, and open one which represents mass transfer on average backwards. Good agreement with a simple model for the particle trajectories in TW was found. In spatially and temporally modulated TW state irregular behavior in mass transport probably indicates an existence of chaotic trajectories.

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We investigate the transition from weakly nonlinear to nonlinear traveling-wave states. Pattern selection due to a transition from convective to absolute instability conditions is found, in good agreement with theory. While the linear properties depend on the (boundary-dependent) threshold of convection, the weakly nonlinear properties refer back to the threshold of an infinite system.

We present an experimental observation of convective transport in oscillatory convection of a binary mixture. The results show the existence of mass transfer in the direction of propagation of nonlinear traveling waves (TW) as well as that of a backflow. Good agreement with a simple model for particle trajectories in TW was found. We found that the two previously observed oscillatory states differ in mass transfer. In linear counterpropagating waves no mass transfer is detected, and the mass-transport onset coincides with the transition to nonlinear TW.

A new state composed of quasiperiodic traveling waves has been observed in very close vicinity of the convection onset along a stable branch. This state precedes the recently discovered confined traveling-wave state, and consists of left- and right-going traveling waves which periodically alternate between either side of the cell. A time-dependent wave-number spectrum is a characteristic feature of this pattern. Effects of pattern translation and modulational instability can qualitatively explain the observed dynamical behavior.

Review of recent experimental results on stationary and oscillatory convection in binary mixtures and comparison with theory are presented. Effect of the cell geometry, in particular cell width, and the value of the separation ratio ψ on the onset of spatio-temporal chaotic behaviour above threshold is studied. Possible relation of complex pattern behaviour to the Benjamin-Feir turbulence in 2D cell geometry is discussed.

A novel localized structure of traveling waves (TWs) was observed at convection onset in ethanol-water mixtures. It is one of various possible flow patterns of TWs which were observed. We find that for almost-one-dimensional cell geometry unique dynamics of transient behavior (in the form of two counterpropagating TWs) can lead to various stable states.

We formulate the dynamics of the Little model at T=0 in simple mathematical terms. We use this to prove that no cycles of length greater than 2 exist in the model. For a subset of systems only 1-cycles exist, and an extensive quantity can be defined.

Flow visualization, heat-transprot measurements, and the light-intensity profile as a function of time have been used to study nonlinear propagating waves in ethanol-water mixtures heated from below. The experimental results reveal the main features of the travelling waves predicted by recent theory.

Pattern observations and heat-transport measurements of convection in ethanol-water mixtures at positive values of the separation ratio are presented. Close to onset, the convective flow manifests itself in a stationary square pattern with negligible change in heat transport compared with the conductive state. Far from threshold, convection selects the usual roll structure with a strong change in heat transport. In a crossover region, the competition between square and roll patterns leads to oscillations.