Intermediate Connectivity Research Articles

Reducing a cortical network to a Potts model yields storage capacity estimates

An autoassociative network of Potts units, coupled via tensor connections, has been proposed and analysed as an effective model of an extensive cortical network with distinct short- and long-range synaptic connections, but it has not been clarified in what sense it can be regarded as an effective model. We draw here the correspondence between the two, which indicates the need to introduce a local feedback term in the reduced model, i.e. in the Potts network. An effective model allows the study of phase transitions. As an example, we study the storage capacity of the Potts network with this additional term, the local feedback w, which contributes to drive the activity of the network towards one of the stored patterns. The storage capacity calculation, performed using replica tools, is limited to fully connected networks, for which a Hamiltonian can be defined. To extend the results to the case of intermediate partial connectivity, we also derive the self-consistent signal-to-noise analysis for the Potts network; and finally we discuss the implications for semantic memory in humans.

Identifying functional network changing patterns in individuals at clinical high-risk for psychosis and patients with early illness schizophrenia: A group ICA study.

Although individuals at clinical high risk (CHR) for psychosis exhibit a psychosis-risk syndrome involving attenuated forms of the positive symptoms typical of schizophrenia (SZ), it remains unclear whether their resting-state brain intrinsic functional networks (INs) show attenuated or qualitatively distinct patterns of functional dysconnectivity relative to SZ patients. Based on resting-state functional magnetic imaging data from 70 healthy controls (HCs), 53 CHR individuals (among which 41 subjects were antipsychotic medication-naive), and 58 early illness SZ (ESZ) patients (among which 53 patients took antipsychotic medication) within five years of illness onset, we estimated subject-specific INs using a novel group information guided independent component analysis (GIG-ICA) and investigated group differences in INs. We found that when compared to HCs, both CHR and ESZ groups showed significant differences, primarily in default mode, salience, auditory-related, visuospatial, sensory-motor, and parietal INs. Our findings suggest that widespread INs were diversely impacted. More than 25% of voxels in the identified significant discriminative regions (obtained using all 19 possible changing patterns excepting the no-difference pattern) from six of the 15 interrogated INs exhibited monotonically decreasing Z-scores (in INs) from the HC to CHR to ESZ, and the related regions included the left lingual gyrus of two vision-related networks, the right postcentral cortex of the visuospatial network, the left thalamus region of the salience network, the left calcarine region of the fronto-occipital network and fronto-parieto-occipital network. Compared to HCs and CHR individuals, ESZ patients showed both increasing and decreasing connectivity, mainly hypo-connectivity involving 15% of the altered voxels from four INs. The left supplementary motor area from the sensory-motor network and the right inferior occipital gyrus in the vision-related network showed a common abnormality in CHR and ESZ groups. Some brain regions also showed a CHR-unique alteration (primarily the CHR-increasing connectivity). In summary, CHR individuals generally showed intermediate connectivity between HCs and ESZ patients across multiple INs, suggesting that some dysconnectivity patterns evident in ESZ predate psychosis in attenuated form during the psychosis risk stage. Hence, these connectivity measures may serve as possible biomarkers to predict schizophrenia progression.

Dynamic functional connectivity impairments in early schizophrenia and clinical high-risk for psychosis

Individuals at clinical high-risk (CHR) for psychosis are characterized by attenuated psychotic symptoms. Only a minority of CHR individuals convert to full-blown psychosis. Therefore, there is a strong interest in identifying neurobiological abnormalities underlying the psychosis risk syndrome. Dynamic functional connectivity (DFC) captures time-varying connectivity over short time scales, and has the potential to reveal complex brain functional organization. Based on resting-state functional magnetic resonance imaging (fMRI) data from 70 healthy controls (HCs), 53 CHR individuals, and 58 early illness schizophrenia (ESZ) patients, we applied a novel group information guided ICA (GIG-ICA) to estimate inherent connectivity states from DFC, and then investigated group differences. We found that ESZ patients showed more aberrant connectivities and greater alterations than CHR individuals. Results also suggested that disease-related connectivity states occurred in CHR and ESZ groups. Regarding the dominant state with the highest contribution to dynamic connectivity, ESZ patients exhibited greater impairments than CHR individuals primarily in the cerebellum, frontal cortex, thalamus and temporal cortex, while CHR and ESZ populations shared common aberrances mainly in the supplementary motor area, parahippocampal gyrus and postcentral cortex. CHR-specific changes were also found in the connections between the superior frontal gyrus and calcarine cortex in the dominant state. Our findings suggest that CHR individuals generally show an intermediate functional connectivity pattern between HCs and SZ patients but also have unique connectivity alterations.

Evaluación de la conectividad del paisaje en la región Puuc-Chenes, México, con base en los requerimientos de hábitat del jaguar (Panthera onca)

The Yucatan Peninsula is included as part of the initiative for the Mesoamerican Biological Corridor. In its central area, are located three Protected Natural Areas (PNA): the Biocultural Puuc Reserve (RBP, by its Spanish acronym), the Bala’an K’aax flora and fauna protected area (APB, by its Spanish acronym), Quintana Roo, and the Calakmul Biosphere Reserve (RBC, by its Spanish acronym), Campeche. The Puuc-Chenes region is located in the center of the Yucatan Peninsula - among these PNAs - which included important fragments of vegetation that in the past formed a continuum through the forests of the Yucatan Peninsula, constituting an important link to keep the connectivity of the Mayan forest. However, the expansion of the agricultural frontier is causing the fragmentation of the habitat. In the present study, the structural and functional connectivity of the Puuc-Chenes region is analyzed, based on habitat requirements of the Panthera onca (jaguar) by sex. Both, male and female, prefer tropical forest, however, P. onca males dare to transit in secondary vegetation and inclusively in agricultural areas. Males make inroads to villages more often than females, coming close to, and even crossing roads. P. onca males have a home range of 60 km2. In the present study, the ArcMap, FRAGSTATS and IDRISI software were used to analyses the structural and functional connectivity of the landscape, based on the known differences of habitat requirements for P. onca males and females. A vegetation and land use map of the studied area was elaborated, based on Landsat 7 ETM+ images, with 30 m size pixels. The following cover classes were differentiated: tropical forest, secondary forest, agriculture, urban, and water polls, which were validated in the fields. The Puuc-Chenes has an extension of 972 578 ha. Tropical forest was the dominant vegetation cover (49.8%) with the largest patch index covering 19.7% of the total landscape. The landscape had 2 509 fragments, from which 1 254 y 935 corresponded to secondary forest and anthropic patches, respectively. The contagion index was 62.5%, which indicates the existence oflarge and contiguous fragments. The total edge contrast index indicates the degree of landscape connectivity was 43.7%, meaning a medium contrast among the different class fragments. Likewise, forest had the highest area-weighted mean proximity index (PROX_AM de 8 701), confirming that the forest had bigger and less isolated fragments than the rest of the classes. The area of study, still have high value for the conservation of the habitat of the P onca. According to the results, we conclude that the Puuc-Chenes region has intermediate structural landscape connectivity, since a suitable corridor was identified for males and three corridors for both, males and females. Four priority fragments of forest were identified in the Puuc-Chenes landscape to be protected: the Puuc fragment with 1 916 km2, the Chenes fragment with 1 380 km2, the X’Panzil fragment with 679 km2 and the Noh-Ha fragment with 88.5 km2, which in total adds 4 063 km2 of identified landscape for the conservation of the jaguar. It is important to stress that the Puuc fragment — which has the largest extension — presents a high degree of perforation, this means, it does not conform a continuum forest mass, since other class of patches are immerse in it, which affects its connectivity and quality as a jaguar habitat. It was found that the habitat extension for the P. onca in the Puuc-Chenes landscape added to the adjacent ANPs’ area conform 15 943 km2, this ensure the persistence of the jaguar in the region. However, this zone has strong anthropic pressures, due to the expansion of ethnic groups and the establishment of new agricultural colonies in the Hopelchén municipality, resulting in extensive agriculture and use of heavy machinery, application of inorganic fertilizer and pesticides, which have detrimental effects in soil restoration and therefore in forest restoration. These changes are producing a cascade of negative effects for the habitat and game of the jaguar. For the reason that the jaguar is a cryptic organism, it is suggested to carry out more research in order to validate the identified corridors in the present study, utilizing field methods that enable to determine the presence and absence of the P. onca. It is also important, to elaborate habitat quality maps using variables such as game density, ecological conditions of the fragments and minor water sources, among them provisioning of minor water sources. This study provides robust elements based on scientific evidences that justified the conservation of four forest fragments in the Puuc-Chenes region that will help to preserve the habitat of the Panthera onca in this region.

EP 61. Coactivation-based parcellation of the posterior medial frontal cortex

Introduction The posterior medial frontal cortex (pMFC) is part of the so-called salience network ( Seeley, 2007 ) and involvement of this region has been reported in a number of different tasks. Although usually referred to as dorsal anterior cingulate cortex, pMFC activation found in most studies is not restricted to the (middle) cingulate cortex, but also extends onto the dorsally abutting superior frontal gyrus, which in turn encompasses the pre-supplementary motor area and parts of the supplementary motor area. Using a connectivity-based parcellation approach, we aimed to investigate whether the pMFC can be subdivided with regard to its functional connectivity (FC) profiles and function. Methods A volume of interest (VOI) corresponding to the pMFC was derived by the conjunction of three previous meta-analyses of attention, working memory and action inhibition ( Muller, 2015 ). The whole-brain co-activation patterns for each voxel within the VOI were computed. Based on those co-activation patterns, all voxels of the VOI were grouped into distinct clusters using k-means clustering, and the most stable clustering solution identified. Meta-analytic and resting state FC approaches were then combined to examine the derived clusters’ brain-wide connectivity. Finally, quantitative functional characterization was performed on each cluster in order to identify differentiable functions of the sub-clusters. Results Results supported the segregation of the pMFC-VOI into five clusters: dorsal-anterior (C1), dorsal-posterior (C2), dorsal-middle (C3), ventral-anterior (C4) and ventral-posterior (C5). Importantly, results demonstrate a clustering into cingulate (C4, C5) and non-cingulate clusters (C1, C2, C3). Posterior cingulate cluster C5 was found to be mainly involved in pain processing and strongly connected to regions of the “pain matrix”, while cingulate C4 more strongly relates to behavioral inhibition. Furthermore, within the non-cingulate pMFC, our results reveal an anterior higher order cognitive (C1) and a posterior action (C2) related cluster. Additionally, we found a central cluster (C3) revealing an intermediate connectivity profile and associated with working memory and cognitive flexibility tasks. Conclusion Thus, our results show that, based on their connectivity patterns, cingulate and non-cingulate regions of the pMFC can be distinguished and further demonstrate a motor to cognitive clustering within non-cingulate pMFC and two cingulate clusters differently involved in pain processing and behavioral inhibition.

The relevance of socioeconomic interactions for the resilience of protected area networks

Ecological theory suggests that intermediate connectivity between protected areas will increase their resilience by facilitating dispersal, recolonisation, and genetic mixing. Conversely, over‐connectivity may make areas less resilient to contagious perturbations such as pathogen outbreaks. In a similar manner, socioeconomic connectivity should enhance the spread of effective management strategies and the sharing of scarce resources, but over‐connectivity carries the risks associated with one‐size‐fits‐all strategies. We used network analysis to examine the topology of management collaborations and related exchanges of information and equipment in two protected area networks in South Africa using the Eastern and Western Cape Provinces as study sites. National protected areas displayed the highest degree of centrality in the Western Cape, while provincial protected areas occupied the central role in the Eastern Cape. Managers in the Western Cape were more concerned about establishing ecological connectivity between protected areas whereas tourism emerged as an important driver in the Eastern Cape protected area network. Our results support the argument that both location and network membership are important for the socioeconomic resilience of protected areas. As with ecological corridors, deliberate fostering of particular socioeconomic corridors may make the protected areas more resilient to perturbations.

Intermediate disturbance in experimental landscapes improves persistence of beetle metapopulations.

Human-dominated landscapes often feature patches that fluctuate in suitability through space and time, but there is little experimental evidence relating the consequences of dynamic patches for species persistence. We used a spatially and temporally dynamic metapopulation model to assess and compare metapopulation capacity and persistence for red flour beetles (Tribolium castaneum) in experimental landscapes differentiated by resource structure, patch dynamics (destruction and restoration), and connectivity. High connectivity increased the colonization rate of beetles, but this effect was less pronounced in heterogeneous relative to homogeneous landscapes. Higher connectivity and faster patch dynamics increased extinction rates in landscapes. Lower connectivity promoted density-dependent emigration. Heterogeneous landscapes containing patches of different carrying capacity enhanced landscape-level occupancy probability. The highest metapopulation capacity and persistence was observed in landscapes with heterogeneous patches, low connectivity, and slow patch dynamics. Control landscapes with no patch dynamics exhibited rapid declines in abundance and approached extinction due to increased adult mortality in the matrix, higher pupal cannibalism by adults, and extremely low rates of exchange between remaining habitable patches. Our results highlight the role of intermediate patch dynamics, intermediate connectivity, and the nature of density dependence of emigration for persistence of species in heterogeneous landscapes. Our results also demonstrate the importance of incorporating local dynamics into the estimation of metapopulation capacity for conservation planning.

Resting-state theta-band connectivity and verbal memory in schizophrenia and in the high-risk state

BackgroundDisturbed functional connectivity is assumed to underlie neurocognitive deficits in patients with schizophrenia. As neurocognitive deficits are already present in the high-risk state, identification of the neural networks involved in this core feature of schizophrenia is essential to our understanding of the disorder. Resting-state studies enable such investigations, while at the same time avoiding the known confounder of impaired task performance in patients. The aim of the present study was to investigate EEG resting-state connectivity in high-risk individuals (HR) compared to first episode patients with schizophrenia (SZ) and to healthy controls (HC), and its association with cognitive deficits. Methods64-channel resting-state EEG recordings (eyes closed) were obtained for 28 HR, 19 stable SZ, and 23 HC, matched for age, education, and parental education. The imaginary coherence-based multivariate interaction measure (MIM) was used as a measure of connectivity across 80 cortical regions and six frequency bands. Mean connectivity at each region was compared across groups using the non-parametric randomization approach. Additionally, the network-based statistic was applied to identify affected networks in patients. ResultsSZ displayed increased theta-band resting-state MIM connectivity across midline, sensorimotor, orbitofrontal regions and the left temporoparietal junction. HR displayed intermediate theta-band connectivity patterns that did not differ from either SZ or HC. Mean theta-band connectivity within the above network partially mediated verbal memory deficits in SZ and HR. ConclusionsAberrant theta-band connectivity may represent a trait characteristic of schizophrenia associated with neurocognitive deficits. As such, it might constitute a promising target for novel treatment applications.

Therapygenetics: anterior cingulate cortex-amygdala coupling is associated with 5-HTTLPR and treatment response in panic disorder with agoraphobia.

Variation in the 5'-flanking promoter region of the serotonin transporter gene SLC6A4, the 5-HTT-linked polymorphic region (5-HTTLPR) has been inconclusively associated with response to cognitive-behavioural therapy (CBT). As genomic functions are stronger related to neural than to behavioural markers, we investigated the association of treatment response, 5-HTTLPR and functional brain connectivity in patients with panic disorder with agoraphobia (PD/AG). Within the national research network PANIC-NET 231 PD/AG patients who provided genetic information underwent a manualized exposure-based CBT. A subset of 41 patients participated in a functional magnetic resonance imaging (fMRI) add-on study prior to treatment applying a differential fear conditioning task. Neither the treatment nor the reduced fMRI sample showed a direct effect of 5-HTTLPR on treatment response as defined by a reduction in the Hamilton Anxiety Scale score ≥50% from baseline to post assessment. On a neural level, inhibitory anterior cingulate cortex (ACC)-amygdala coupling during fear conditioning that had previously been shown to characterize treatment response in this sample was driven by responders with the L/L genotype. Building upon conclusive evidence from basic and preclinical findings on the association of the 5-HTTLPR polymorphism with emotion regulation and related brain connectivity patterns, present findings translate these to a clinical sample of PD/AG patients and point towards a potential intermediate connectivity phenotype modulating response to exposure-based CBT.

Determinism of bacterial metacommunity dynamics in the southern East China Sea varies depending on hydrography

Spatial variation of communities composition (metacommunities) results from multiple assembly mechanisms, including environmental filtering and dispersal; however, whether and why the relative importance of the assembly mechanisms in shaping bacterial metacommunity changes through time in marine pelagic systems remains poorly studied. Here, we applied the elements of metacommunity structure framework and the variation partitioning framework to examine whether temporal variation of hydrographic conditions influences bacterioplankton metacommunity dynamics in the southern East China Sea (ECS). The spatiotemporal variation of bacterial communities composition was revealed using 454 pyrosequencing of 16S rDNA. In addition to the whole bacterial community, we analyzed four dominant taxonomic groups (Cyanobacteria, Alphaproteobacteria, Gammaproteobacteria, and Actinobacteria) separately. Our analyses indicate that, considering the whole community level, the determinism of metacommunity structure varied among seasons. When the degree of connectivity was low (December), the metacommunity exhibited random distribution and was explained mainly by the environmental component. However, Clementsian metacommunity was found at intermediate connectivity (May), during which the environmental and spatial predictors were both significant. When connectivity was high (August), a random distribution pattern was found and no significant effect of environmental filtering or dispersal limitation was detected. Nevertheless, when considering different taxonomic groups, the differences in metacommunity dynamics among groups were found. Our results suggest that the driving forces of metacommunity dynamics varied depending on hydrography, as the degrees of environmental heterogeneity and connectivity among habitat patches were determined by circulation pattern. Moreover, mechanisms varied among different taxonomic groups, suggesting that differential dispersal capacity among taxonomic groups should be integrated into community assembly studies.

A gradual depth-dependent change in connectivity features of supragranular pyramidal cells in rat barrel cortex.

Recent experimental evidence suggests a finer genetic, structural and functional subdivision of the layers which form a cortical column. The classical layer II/III (LII/III) of rodent neocortex integrates ascending sensory information with contextual cortical information for behavioral read-out. We systematically investigated to which extent regular-spiking supragranular pyramidal neurons, located at different depths within the cortex, show different input–output connectivity patterns. Combining glutamate uncaging with whole-cell recordings and biocytin filling, we revealed a novel cellular organization of LII/III: (1) “Lower LII/III” pyramidal cells receive a very strong excitatory input from lemniscal LIV and much fewer inputs from paralemniscal LVa. They project to all layers of the home column, including a feedback projection to LIV, whereas transcolumnar projections are relatively sparse. (2) “Upper LII/III” pyramidal cells also receive their strongest input from LIV, but in addition, a very strong and dense excitatory input from LVa. They project extensively to LII/III as well as LVa and Vb of their home and neighboring columns. (3) “Middle LII/III” pyramidal cell shows an intermediate connectivity phenotype that stands in many ways in between the features described for lower versus upper LII/III. “Lower LII/III” intracolumnarly segregates and transcolumnarly integrates lemniscal information, whereas “upper LII/III” seems to integrate lemniscal with paralemniscal information. This suggests a fine-grained functional subdivision of the supragranular compartment containing multiple circuits without any obvious cytoarchitectonic, other structural or functional correlate of a laminar border in rodent barrel cortex.

Response of benthic macroinvertebrates to gradients in hydrological connectivity: a comparison of temperate, subtropical, Mediterranean and semiarid river floodplains

Summary Despite a general recognition that benthic macroinvertebrates respond to changes in hydrological connectivity within floodplain ecosystems, no consensus about patterns in community structure and ecosystem processes across large scales and different climates has yet been established. Such knowledge is necessary since anthropogenic activities continue to alter the natural hydrogeomorphology of large floodplains, with most consequences for aquatic communities remaining unknown. Using information from six large rivers located in four different climate regions (humid subtropical, maritime temperate, Mediterranean and dry semi‐arid), we compared benthic macroinvertebrate responses along lateral gradients of hydrological connectivity. We tested hypotheses related to differences among climate regions and to similar hydrological constraints within any one climate. The large geographical scale covered by this study provides the first comprehensive comparison of aquatic community patterns across hydrological gradients under different climatic settings. Multivariate ordinations demonstrated a higher overlap of trait community composition (50% variance explained by the first two axes) than taxonomic composition (15%) among floodplains, displaying high interclimate trait stability. The taxonomy‐based ordination separated the subtropical floodplain, with an average 86% of non‐insect taxa, from the insect‐dominated temperate, Mediterranean and semi‐arid floodplains (with >50% insect abundance). In the trait‐based ordination, large body size (60% of organisms >4 cm) and long lifespan duration (80% of organisms) discriminated the subtropical from the other five studied floodplains. Across a gradient of lateral connectivity, linear mixed effect (LME) models supported seven of 15 hypotheses, which suggests remarkably consistent macroinvertebrate patterns in floodplains regardless of the climate regime. Taxon and trait richness were positively related and peaked at sites of intermediate hydrological connectivity. Our predictions about the feeding guilds of macroinvertebrates (e.g. that shredders and scrapers would be more abundant in connected channels, and predators and deposit feeders at isolated sites) were more strongly supported by the data than those about life history (e.g. plurivoltinism and short lifespan would be better represented in connected channels). This difference was related to the influence of extended periods of hydrological disconnection as disturbance in addition to flooding. Trait stability across hydrological connectivity provides a meaningful ecological context for the comparison of the macroinvertebrate benthos among climatic zones, where taxonomic composition differs strongly. In addition, trait similarities and dissimilarities found in this study suggest that large‐scale biogeographical filters do operate on communities, resulting in different trait combinations in temperate and Mediterranean floodplains when compared to semi‐arid and subtropical environments. The extent to which global macroecological factors (i.e. climate, dispersal history) and local biotic and abiotic factors (i.e. drought frequency, habitat structure, water chemistry) contribute to this difference requires further investigation.

Towards understanding the behavior of physical systems using information theory

One of the goals of complex network analysis is to identify the most influential nodes, i.e., the nodes that dictate the dynamics of other nodes. In the case of autonomous systems or transportation networks, highly connected hubs play a preeminent role in diffusing the flow of information and viruses; in contrast, in language evolution most linguistic norms come from the peripheral nodes who have only few contacts. Clearly a topological analysis of the interactions alone is not sufficient to identify the nodes that drive the state of the network. Here we show how information theory can be used to quantify how the dynamics of individual nodes propagate through a system. We interpret the state of a node as a storage of information about the state of other nodes, which is quantified in terms of Shannon information. This information is transferred through interactions and lost due to noise, and we calculate how far it can travel through a network. We apply this concept to a model of opinion formation in a complex social network to calculate the impact of each node by measuring how long its opinion is remembered by the network. Counter-intuitively we find that the dynamics of opinions are not determined by the hubs or peripheral nodes, but rather by nodes with an intermediate connectivity.

Information sharing in quantum complex networks

We introduce the use of entanglement entropy as a tool for studying the amount of information shared between the nodes of quantum complex networks. By considering the ground state of a network of coupled quantum harmonic oscillators, we compute the information that each node has on the rest of the system. We show that the nodes storing the largest amount of information are not the ones with the highest connectivity, but those with intermediate connectivity thus breaking down the usual hierarchical picture of classical networks. We show both numerically and analytically that the mutual information characterizes the network topology. As a byproduct, our results point out that the amount of information available for an external node connecting to a quantum network allows to determine the network topology.

Application of High-Frequency Repetitive Transcranial Magnetic Stimulation to the DLPFC Alters Human Prefrontal–Hippocampal Functional Interaction

Neural plasticity is crucial for understanding the experience-dependent reorganization of brain regulatory circuits and the pathophysiology of schizophrenia. An important circuit-level feature derived from functional magnetic resonance imaging (fMRI) is prefrontal-hippocampal seeded connectivity during working memory, the best established intermediate connectivity phenotype of schizophrenia risk to date. The phenotype is a promising marker for the effects of plasticity-enhancing interventions, such as high-frequency repetitive transcranial magnetic stimulation (rTMS), and can be studied in healthy volunteers in the absence of illness-related confounds, but the relationship to brain plasticity is unexplored. We recruited 39 healthy volunteers to investigate the effects of 5 Hz rTMS on prefrontal-hippocampal coupling during working memory and rest. In a randomized and sham-controlled experiment, neuronavigation-guided rTMS was applied to the right dorsolateral prefrontal cortex (DLPFC), and fMRI and functional connectivity analyses [seeded connectivity and psychophysiological interaction (PPI)] were used as readouts. Moreover, the test-retest reliability of working-memory related connectivity markers was evaluated. rTMS provoked a significant decrease in seeded functional connectivity of the right DLPFC and left hippocampus during working memory that proved to be relatively time-invariant and robust. PPI analyses provided evidence for a nominal effect of rTMS and poor test-retest reliability. No effects on n-back-related activation and DLPFC-hippocampus resting-state connectivity were observed. These data provide the first in vivo evidence for the effects of plasticity induction on human prefrontal-hippocampal network dynamics, offer insights into the biological mechanisms of a well established intermediate phenotype linked to schizophrenia, and underscores the importance of the choice of outcome measures in test-retest designs.

Algorithmic requirements for swarm intelligence in differently coupled collective systems

Swarm systems are based on intermediate connectivity between individuals and dynamic neighborhoods. In natural swarms self-organizing principles bring their agents to that favorable level of connectivity. They serve as interesting sources of inspiration for control algorithms in swarm robotics on the one hand, and in modular robotics on the other hand. In this paper we demonstrate and compare a set of bio-inspired algorithms that are used to control the collective behavior of swarms and modular systems: BEECLUST, AHHS (hormone controllers), FGRN (fractal genetic regulatory networks), and VE (virtual embryogenesis). We demonstrate how such bio-inspired control paradigms bring their host systems to a level of intermediate connectivity, what delivers sufficient robustness to these systems for collective decentralized control. In parallel, these algorithms allow sufficient volatility of shared information within these systems to help preventing local optima and deadlock situations, this way keeping those systems flexible and adaptive in dynamic non-deterministic environments.

Modelling dispersal of eggs and quantifying connectivity among Norwegian coastal cod subpopulations

Abstract The Norwegian coast is populated by two cod populations: Northeast Arctic cod and Norwegian Coastal cod. In this paper, we use a further division based on life history: oceanic cod, coastal cod, and fjord cod. A numerical ocean model was implemented for the northern Norwegian coast where all these populations have spawning areas. The model results were used to simulate connectivity and retention of cod eggs from the different subpopulations. The model reproduced the observed variability and mesoscale activity in the Norwegian Coastal Current. Eggs released at an oceanic spawning area were transported northwards along the coastline. Coastal cod eggs had intermediate connectivity with each other and fjord cod eggs had high local retention. Although the high retention of eggs in fjord areas is mainly caused by a subsurface distribution of eggs, the intermediate retention of eggs from coastal spawning areas is caused by small-scale eddies in-between many small islands. The high-resolution ocean model made it possible to reveal these specific dispersal patterns. The high retention of early life stages in fjords combined with strong homing to spawning areas indicates that fjord subpopulations may be described as a metapopulation.

Predicting range shifts under global change: the balance between local adaptation and dispersal

Bioclimate envelope models (BEMs) have often been criticized as being too simplistic due to e.g. not incorporating effects of biotic interactions or evolutionary adaptation. However, BEMs are widely applied and have proven to be often useful. Here we investigate, under which conditions evolution of dispersal, local adaptation or interspecific competition may be of minor importance for forecasting future range shifts. Therefore we use individual‐based simulations of metapopulations under climate change living in spatial temperature gradients. Scenarios incorporate single‐species systems or systems with competing species, respectively. Dispersal rate is evolving and adaptation to local conditions may also evolve in some scenarios. Results show that in single‐species scenarios excluding evolutionary adaptation, species either follow optimal habitat conditions or go extinct if habitat connectivity is too low. These simulations are in close accordance to predictions from BEMs. Including evolutionary adaptation qualitatively changes these results. In the absence of competing species the species either completely invades the world or goes extinct. With competitors, results strongly depend on habitat fragmentation. For highly connected habitats the range border may shift as predicted by BEMs, for intermediate connectivity it will lag behind, while species will go extinct if fragmentation is too high. Our results indicate that (simple) BEMs may work well if habitats are well connected and species will not encounter many difficulties in dispersing to new sites. Selection in this case may promote evolution of even higher dispersal activities. We thus show that the presence of biotic interactions may be ignored for predictions of range shifts when high dispersal can be expected.

Brain connectivity in psychiatric imaging genetics

In the past decade, imaging genetics has evolved into a highly successful neuroimaging discipline with a variety of sophisticated research tools. To date, several neural systems mechanisms have been identified that mediate genetic risk for mental disorders linked to common candidate and genome-wide-supported variants. In particular, the examination of intermediate connectivity phenotypes has recently gained increasing popularity. This paper gives an overview of the scientific methods and evidence that link indices of neural network organization to the genetic susceptibility for mental illness with a focus on the effects of candidate genes and genome-wide supported risk variants on brain structure and function.

Sequentially Switching Cell Assemblies in Random Inhibitory Networks of Spiking Neurons in the Striatum

The striatum is composed of GABAergic medium spiny neurons with inhibitory collaterals forming a sparse random asymmetric network and receiving an excitatory glutamatergic cortical projection. Because the inhibitory collaterals are sparse and weak, their role in striatal network dynamics is puzzling. However, here we show by simulation of a striatal inhibitory network model composed of spiking neurons that cells form assemblies that fire in sequential coherent episodes and display complex identity-temporal spiking patterns even when cortical excitation is simply constant or fluctuating noisily. Strongly correlated large-scale firing rate fluctuations on slow behaviorally relevant timescales of hundreds of milliseconds are shown by members of the same assembly whereas members of different assemblies show strong negative correlation, and we show how randomly connected spiking networks can generate this activity. Cells display highly irregular spiking with high coefficients of variation, broadly distributed low firing rates, and interspike interval distributions that are consistent with exponentially tailed power laws. Although firing rates vary coherently on slow timescales, precise spiking synchronization is absent in general. Our model only requires the minimal but striatally realistic assumptions of sparse to intermediate random connectivity, weak inhibitory synapses, and sufficient cortical excitation so that some cells are depolarized above the firing threshold during up states. Our results are in good qualitative agreement with experimental studies, consistent with recently determined striatal anatomy and physiology, and support a new view of endogenously generated metastable state switching dynamics of the striatal network underlying its information processing operations.