Network-level Effects Research Articles

Functional Connectivity between Anatomically Unconnected Areas Is Shaped by Collective Network-Level Effects in the Macaque Cortex

Coherent spontaneous blood oxygen level-dependent (BOLD) fluctuations have been intensely investigated as a measure of functional connectivity (FC) in the primate neocortex. BOLD-FC is commonly assumed to be constrained by the underlying anatomical connectivity (AC); however, cortical area pairs with no direct AC can also have strong BOLD-FC. On the mechanism generating FC in the absence of direct AC, there are 2 possibilities: 1) FC is determined by signal flows via short connection patterns, such as serial relays and common afferents mediated by a third area; 2) FC is shaped by collective effects governed by network properties of the cortex. In this study, we conducted functional magnetic resonance imaging in anesthetized macaque monkeys and found that BOLD-FC between unconnected areas depends less on serial relays through a third area than on common afferents and, unexpectedly, common efferents, which does not match the first possibility. By utilizing a computational model for interareal BOLD-FC network, we show that the empirically detected AC-FC relationships reflect the configuration of network building blocks (motifs) in the cortical anatomical network, which supports the second possibility. Our findings indicate that FC is not determined solely by interareal short connection patterns but instead is substantially influenced by the network-level cortical architecture.

Mini-coil for magnetic stimulation in the behaving primate

Transcranial magnetic stimulation (TMS) is rapidly becoming a leading method in both cognitive neuroscience and clinical neurology. However, the cellular and network level effects of stimulation are still unclear and their study relies heavily on indirect physiological measurements in humans. Direct electrophysiological studies of the effect of magnetic stimulation on neuronal activity in behaving animals are severely limited by both the size of the stimulating coils, which affect large regions of the animal brain, and the large artifacts generated on the recording electrodes. We present a novel mini-coil which is specifically aimed at studying the neurophysiological mechanism of magnetic stimulation in behaving primates. The mini-coil fits into a chronic recording chamber and provides focal activation of brain areas while enabling simultaneous extracellular multi-electrode recordings. We present a comparison of this coil to a commercial coil based on the theoretical and recorded magnetic fields and induced electric fields they generate. Subsequently, we present the signal recorded in the behaving primate during stimulation and demonstrate the ability to extract the spike trains of multiple single units from each of the electrodes with minimal periods affected by the stimulus artifact (median period <2.5ms). The directly recorded effect of the magnetic stimulation on cortical neurons is in line with peripheral recordings obtained in humans. This novel mini-coil is a key part of the infrastructure for studying the neurophysiological basis of magnetic stimulation, thereby enabling the development and testing of better magnetic stimulation tools and protocols for both neuroscientists and clinicians.

Phosphotyrosine signaling analysis of site-specific mutations on EGFRvIII identifies determinants governing glioblastoma cell growth

To evaluate the role of individual EGFR phosphorylation sites in activating components of the cellular signaling network we have performed a mass spectrometry-based analysis of the phosphotyrosine network downstream of site-specific EGFRvIII mutants, enabling quantification of network-level effects of site-specific point mutations. Mutation at Y845, Y1068 or Y1148 resulted in diminished receptor phosphorylation, while mutation at Y1173 led to increased phosphorylation on multiple EGFRvIII residues. Altered phosphorylation at the receptor was recapitulated in downstream signaling network activation levels, with Y1173F mutation leading to increased phosphorylation throughout the network. Computational modeling of GBM cell growth as a function of network phosphorylation levels highlights the Erk pathway as crucial for regulating EGFRvIII-driven U87MG GBM cell behavior, with the unexpected finding that Erk1/2 is negatively correlated to GBM cell growth. Genetic manipulation of this pathway supports the model, demonstrating that EGFRvIII-expressing U87MG GBM cells are sensitive to Erk activation levels. Additionally, we developed a model describing glioblastoma cell growth based on a reduced set of phosphoproteins, which represent potential candidates for future development as therapeutic targets for EGFRvIII-positive glioblastoma patients.

Clonidine and guanfacine attenuate phencyclidine-induced dopamine overflow in rat prefrontal cortex: Mediating influence of the alpha-2A adrenoceptor subtype

N-methyl-D-aspartic acid/glutamate receptor antagonists induce psychotomimetic effects in humans and animals, and much research has focused on the neurochemical and network-level effects that mediate those behavioral changes. For example, a reduction in NMDA-dependent glutamatergic transmission triggers increased release of the monoamine transmitters, and some of these changes are implicated in the cognitive, behavioral and neuroanatomical effects of phencyclidine (PCP). Alpha-2 adrenoceptor agonists (e.g., clonidine) are effective at preventing many of the behavioral, neurochemical and anatomical effects of NMDA antagonists. Evidence has indicated that a key mechanism of the clonidine-induced reversal of the effects of NMDA antagonists is an attenuation of enhanced dopamine release. We have pursued these findings by investigating the effects of alpha-2 agonists on PCP-evoked dopamine efflux in the prefrontal cortex of freely moving rats. Clonidine (0.003–0.1 mg/kg, i.p.) dose-dependently attenuated the ability of PCP (2.5 mg/kg, i.p.) to increase cortical dopamine output. The effects of clonidine were prevented by the alpha-2A subtype selective antagonist BRL-44408 (1 mg/kg, i.p.). Guanfacine, which is an alpha-2 agonist with a higher affinity for the 2A, compared with 2B or 2C, subtypes, also blocked the ability of PCP to increase dopamine efflux in the prefrontal cortex. These data indicate that alpha-2A agonists are effective at counteracting the hyperdopaminergic state induced by PCP and may play a role in their neurobehavioral effects in this putative animal model for schizophrenia.

An open hypothesis: Is epilepsy learned, and can it be unlearned?

Plasticity is central to the ability of a neural system to learn and also to its ability to develop spontaneous seizures. What is the connection between the two? Learning itself is known to be a destabilizing process at the algorithmic level. We have investigated necessary constraints on a spontaneously active Hebbian learning system and find that the ability to learn appears to confer an intrinsic vulnerability to epileptogenesis on that system. We hypothesize that epilepsy arises as an abnormal learned response of such a system to certain repeated provocations. This response is a network-level effect. If epilepsy really is a learned response, then it should be possible to reverse it, that is, to unlearn epilepsy. Unlearning epilepsy may then provide a new approach to its treatment.

The effect of density on the level of bias in the network autocorrelation model

Researchers interested in the effects of social network ties on behavior are increasingly turning to the network autocorrelation model, which allows for the simultaneous computation of individual-level and network-level effects. Earlier research, however, had pointed to the possibility that the maximum likelihood estimates used to compute the network autocorrelation model yielded negatively biased parameter estimates. In this paper we use simulations to examine whether – and the conditions under which – a negative bias exists. We show that the network parameter estimate ρ is negatively biased under nearly all conditions, and that this bias becomes more severe at higher levels of both ρ and network density. We conclude by discussing the implications of these findings for researchers planning to use the network autocorrelation model.

Structural factors leading to changes in persistent activity following focal-trauma and neurodegeneration

Considerable research efforts have focused on the molecular mechanisms of epilepsy following trauma and neurodegeneration. In contrast to this cell-centric approach, we present a range of computational network models demonstrating that architectural factors may be critical to understanding seizure susceptibility and other changes in neural dynamics. The models consisted of large recurrent networks of up to 10,000 spiking neurons that included both inhibitory and excitatory populations with inter-layer and columnar intra-layer connectivity. Layers were toroidal so that initial networks were homogeneous and without edges. We examined the effects of both localized and diffuse cell deletions. In the first case cells were removed at adjacent locations to emulate focal trauma. In the case of diffuse cell deletion we randomly deleted cells throughout the network. In both types of simulations, the properties of remaining cells were held constant in order to establish that changes in dynamics were indeed network-level effects and that the alterations in connectivity were the critical factor in any threshold change. Simulations in the focal model confirmed that confined alterations in structure were sufficient to change the threshold of an entire network. We found that the lesion site acted both as an initiation point of oscillatory activity as well as a locus that increased the probability that existing waves will continue propagating. The localized deletions models thus demonstrate the possibility that structural factors may be sufficient to account for the focal activity seen in early post-traumatic epilepsy. The diffuse cell deletions correspond to changes following cell death in aging and neurodegenerative conditions. Here we found that high levels of diffuse deletions (70–90%), representing extensive cell death, resulted in activity settling to repetitive patterns (limit-cycle oscillations). The changes in activity seen in these diffuse lesion models may thus help explain the increased incidence of epilepsy with aging. That is, such seizures may be caused by structural network changes due to age-related cell death rather than pathology in surviving cell properties. Interestingly, the heterogeneity of connectivity that accompanied lower levels of diffuse deletions (40%) actually encouraged complex persistent activity often associated with healthy cognitive processing suggesting that heterogeneity in structure may play an important role in initiating and maintaining such activity. It is also notable that shifts in population dynamics took place independently of changes to inhibitory-excitatory balance and did not require complex connectivity assumptions (e.g., small-world networks). That is, the propensity for activity to persist could be varied by structural changes as simple as random deletions. The findings suggest that structural considerations may be fundamental to our understanding of trauma and age-related epileptogenesis and that we may need to look beyond intrinsic cell properties or inhibitory-excitatory balance in order to identify potential therapies.

Female rock sparrows (Petronia petronia), not males, respond differently to simulations of different courtship interaction outcomes

AbstractAnimals communicate in networks which spread beyond the classic sender-receiver dyad. Researchers have often concentrated on networks of signalling males, but the network-level effects of male-female signalling interactions are largely unexplored, even though these can contain information when individuals of both sexes have access to a range of mating strategies. We tested whether rock sparrows (Petronia petronia) behave differently after hearing playbacks of vocal interactions simulating a successful courtship as opposed to playback of an unsuccessful courtship. We found no support for our prediction that males which heard a successful courtship simulation would increase the frequency of sexual behaviours compared with those which heard the unsuccessful courtship. Females which heard the successful courtship simulation stayed longer at the nest site and inside the nest box compared with those which heard the unsuccessful courtship simulation. Therefore, females responded to the treatments as if these represented different degrees of competition for either mates or nest sites. This is, to the best of our knowledge, among the first experimental demonstrations that female birds intercept signalling interactions between males and females and suggests that information available through communication networks can be relevant for an animal's choice of breeding strategy.

Building Dynamic Capabilities: Innovation Driven by Individual-, Firm-, and Network-Level Effects

Following the dynamic capabilities perspective, we suggest that antecedents to innovation can be found at the individual, firm, and network levels. Thus, we challenge two assumptions common in prior research: (1) that significant variance exists at the focal level of analysis, whereas other levels of analysis are assumed to be homogeneous, and (2) that the focal level of analysis is independent from other levels of analysis. Accordingly, we advance a set of hypotheses to simultaneously assess the direct effects of antecedents at the individual, firm, and network levels on innovation output. We then investigate whether a firm's antecedents to innovation lie across different levels. To accomplish this, we propose two competing interaction hypotheses. We juxtapose the hypothesis that the individual-, firm-, and network-level antecedents to innovation are substitutes versus the proposition that these innovation mechanisms are complements. We test our multilevel theoretical model using an unusually comprehensive and detailed panel data set that documents the innovation attempts of global pharmaceutical companies within biotechnology over a 22-year time period (1980–2001). We find evidence that the antecedents to innovation lie across different levels of analysis and can have compensating or reinforcing effects on firm-level innovative output.

Towards more biological mutation operators in gene regulation studies

Genetic regulation is often viewed as a complex system whose properties emerge from the interaction of regulatory genes. One major paradigm for studying the complex dynamics of gene regulation uses directed graphs to explore structure, behaviour and evolvability. Mutation operators used in such studies typically involve the insertion and deletion of nodes, and the insertion, deletion and rewiring of links at the network level. These network-level mutational operators are sufficient to allow the statistical analysis of network structure, but impose limitations on the way networks are evolved. There are a wide variety of mutations in DNA sequences that have yet to be analysed for their network-level effects. By modelling an artificial genome at the level of nucleotide sequences and mapping it to a regulatory network, biologically grounded mutation operators can be mapped to network-level mutations. This paper analyses five such sequence level mutations (single-point mutation, transposition, inversion, deletion and gene duplication) for their effects at the network level. Using analytic and simulation techniques, we show that it is rarely the case that nodes and links are cleanly added or deleted, with even the simplest point mutation causing a wide variety of network-level modifications. As expected, the vast majority of simple (single-point) mutations are neutral, resulting in a neutral plateau from which a range of functional behaviours can be reached. By analysing the effects of sequence-level mutations at the network level of gene regulation, we aim to stimulate more careful consideration of mutation operators in gene regulation models than has previously been given.

Self-organization of memory activity through spike-timing-dependent plasticity.

We studied the self-organization of memory-related activity through spike-timing-dependent plasticity (STDP). Relatively short time windows (approximately 10 ms) for the plasticity rule give rise to asynchronous persistent activity of low rates (20-30 Hz), which is typically observed in delay periods of working memory task. We demonstrate some network level effects on the activity regulation that cannot be addressed in single-neuron studies. For longer time windows (approximately 20 ms), the layered cell assemblies that propagate synchronized spikes (synfire chain) are self-organized. Synchronous spike propagation was suggested to underlie the precisely timed spikes in the monkey prefrontal cortex. The present results suggest that the two networks for sustained activity are different realizations of the same principle for synaptic wiring.

Modeling of plasticity of the synaptic connections in the lamprey spinal CPG — consequences for network behavior

Consequences of synaptic plasticity in the lamprey spinal CPG are analyzed. This is motivated by the experimentally found effects substance P and 5-hydroxytryptamin (5-HT) have on the inhibitory and excitatory synaptic transmission. The effects can be a change of the amplitude of the postsynaptic potentials as well as induction of an activity-dependent facilitation or depression during repetitive activation. Simulations show that network level effects (i.e. swimming frequency) of substance P and 5-HT can to a substantial part be explained based on their effects on the plasticity of the synaptic transmission.

Analysis of ISP IP/ATM network traffic measurements

This paper presents network traffic measurements collected from a commercial Internet Service Provider (ISP) whose traffic is being carried over an ATM backbone network. Much of the aggregate traffic is Web-related, and thus represents a Web/TCP/IP/AAL-5/ATM protocol stack. Four traces have been collected at the AAL-5 frame level, using a NavTel IW95000 ATM test set. These traces provide a detailed look at protocol-level behaviours, but only for rather short time durations (e.g., 30-40 seconds per trace). Analyses focus on aggregate-level traffic characteristics, as well as host-level and TCP connection-level traffic characteristics.The main workload characteristics observed from the measurements are the burstiness of the aggregate and individual traffic flows, a non-uniform distribution of traffic amongst hosts, a trimodal packet size distribution, and the strong presence of network-level effects (e.g., client modem speed, network Maximum Transmission Unit (MTU), network round trip time, TCP slow start) in the traffic structures seen. The workload characteristics are quite consistent across the four traces studied.