Cingulo-Opercular Subnetworks Motivate Frontoparietal Subnetworks during Distinct Cognitive Control Demands

Cognitive control is the ability to flexibly adapt behavior in a goal-directed manner when habit will not suffice. Control can be separated into distinct forms based on the timescale (present-future) and/or medium (external-internal) over which it operates. Both the frontoparietal network (FPN) and cingulo-opercular network (CON) are engaged during control, but their respective functions and interactions remain unclear. Here, we examined activations in the FPN and CON with fMRI in humans (male and female) during a task that manipulated control across timescales/mediums. The findings show that the CON can be distinguished into the following two separable subnetworks mirroring the FPN: a rostral/ventral subnetwork sensitive to future-oriented control involving internal representations, and a caudal/dorsal subnetwork sensitive to present-oriented control involving external representations. Relative to the FPN, activation in the CON was particularly pronounced during transitions into and out of particular control demands. Moreover, the relationship of each CON subnetwork to behavior was mediated by a respective FPN subnetwork. Such data are consistent with the idea that the CON motivates the FPN, which, in turn, drives behavior. Within the CON, the dorsomedial prefrontal cortex (dmPFC) mediated the relationship between the anterior insula and FPN, suggesting that the dmPFC acts as the crux that links the CON to the FPN. Collectively, these data indicate that parallel CON-FPN subnetworks mediate controlled behaviors at distinct timescales/mediums.SIGNIFICANCE STATEMENT The cingulo-opercular network (CON) and frontoparietal network (FPN) are engaged in diverse, demanding tasks. A functional model describing how areas within these networks can be distinguished, and also interact, would facilitate understanding of how the brain adapts to demanding situations. During a comprehensive control task, fMRI data revealed that the FPN and CON can be fractionated into subnetworks based on control demands that are either externally oriented for use in the present, or control demands that operate internally to guide future behavior. Moreover, we found evidence for a chain of relationships from the CON to FPN to behavior consistent with the idea that the CON drives the FPN to adapt behavior.

Eukaryotic rather than prokaryotic microbiomes change over seasons in rewetted fen peatlands

In the last decades, rewetting of drained peatlands is on the rise worldwide, to restore their significant carbon sink function. Despite the increasing understanding of peat microbiomes, little is known about the seasonal dynamics and network interactions of the microbial communities in these ecosystems, especially in rewetted fens (groundwater-fed peatlands). Here, we investigated the seasonal dynamics in both prokaryotic and eukaryotic microbiomes in three common fen types in Northern Germany. The eukaryotic microbiomes, including fungi, protists and microbial metazoa, showed significant changes in their community structures across the seasons in contrast to largely unaffected prokaryotic microbiomes. Furthermore, our results proved that the dynamics in eukaryotic microbiomes in the rewetted sites differed between fen types, specifically in terms of saprotrophs, arbuscular mycorrhiza and grazers of bacteria. The co-occurrence networks also exhibited strong seasonal dynamics that differed between rewetted and drained sites, and the correlations involving protists and prokaryotes were the major contributors to these dynamics. Our study provides the insight that microbial eukaryotes mainly define the seasonal dynamics of microbiomes in rewetted fen peatlands. Accordingly, future research should unravel the importance of eukaryotes for biogeochemical processes, especially the under-characterized protists and metazoa, in these poorly understood ecosystems.

Tomato Cultivars With Variable Tolerances to Water Deficit Differentially Modulate the Composition and Interaction Patterns of Their Rhizosphere Microbial Communities

Since drought is the leading environmental factor limiting crop productivity, and plants have a significant impact in defining the assembly of plant-specific microbial communities associated with roots, we aimed to determine the effect of thoroughly selected water deficit tolerant and susceptible Solanum lycopersicum cultivars on their rhizosphere microbiome and compared their response with plant-free soil microbial communities. We identified a total of 4,248 bacterial and 276 fungal different operational taxonomic units (OTUs) in soils by massive sequencing. We observed that tomato cultivars significantly affected the alpha and beta diversity of their bacterial rhizosphere communities but not their fungal communities compared with bulk soils (BSs), showing a plant effect exclusively on the bacterial soil community. Also, an increase in alpha diversity in response to water deficit of both bacteria and fungi was observed in the susceptible rhizosphere (SRz) but not in the tolerant rhizosphere (TRz) cultivar, implying a buffering effect of the tolerant cultivar on its rhizosphere microbial communities. Even though water deficit did not affect the microbial diversity of the tolerant cultivar, the interaction network analysis revealed that the TRz microbiota displayed the smallest and least complex soil network in response to water deficit with the least number of connected components, nodes, and edges. This reduction of the TRz network also correlated with a more efficient community, reflected in increased cooperation within kingdoms. Furthermore, we identified some specific bacteria and fungi in the TRz in response to water deficit, which, given that they belong to taxa with known beneficial characteristics for plants, could be contributing to the tolerant phenotype, highlighting the metabolic bidirectionality of the holobiont system. Future assays involving characterization of root exudates and exchange of rhizospheres between drought-tolerant and susceptible cultivars could determine the effect of specific metabolites on the microbiome community and may elucidate their functional contribution to the tolerance of plants to water deficit.

Hybrid Incompatibilities and Transgressive Gene Expression Between Two Closely Related Subspecies of Drosophila

Genome-wide assays of expression between species and their hybrids have identified genes that become either over- or underexpressed relative to the parental species (i.e., transgressive). Transgressive expression in hybrids is of interest because it highlights possible changes in gene regulation linked to hybrid dysfunction. Previous studies in Drosophila that used long-diverged species pairs with complete or nearly complete isolation (i.e., full sterility and partial inviability of hybrids) and high-levels of genome misregulation have found correlations between expression and coding sequence divergence. The work highlighted the possible effects of directional selection driving sequence divergence and transgressive expression. Whether the same is true for taxa at early stages of divergence that have only achieved partial isolation remains untested. Here, we reanalyze previously published genome expression data and available genome sequence reads from a pair of partially isolated subspecies of Drosophila to compare expression and sequence divergence. We find a significant correlation in rates of expression and sequence evolution, but no support for directional selection driving transgressive expression in hybrids. We find that most transgressive genes in hybrids show no differential expression between parental subspecies and used SNP data to explore the role of stabilizing selection through compensatory mutations. We also examine possible misregulation through cascade effects that could be driven by interacting gene networks or co-option of off-target cis-regulatory elements.

Flexible Coordinator and Switcher Hubs for Adaptive Task Control

Functional connectivity (FC) studies have identified at least two large-scale neural systems that constitute cognitive control networks, the frontoparietal network (FPN) and cingulo-opercular network (CON). Control networks are thought to support goal-directed cognition and behavior. It was previously shown that the FPN flexibly shifts its global connectivity pattern according to task goal, consistent with a "flexible hub" mechanism for cognitive control. Our aim was to build on this finding to develop a functional cartography (a multimetric profile) of control networks in terms of dynamic network properties. We quantified network properties in (male and female) humans using a high-control-demand cognitive paradigm involving switching among 64 task sets. We hypothesized that cognitive control is enacted by the FPN and CON via distinct but complementary roles reflected in network dynamics. Consistent with a flexible "coordinator" mechanism, FPN connections were varied across tasks, while maintaining within-network connectivity to aid cross-region coordination. Consistent with a flexible "switcher" mechanism, CON regions switched to other networks in a task-dependent manner, driven primarily by reduced within-network connections to other CON regions. This pattern of results suggests FPN acts as a dynamic, global coordinator of goal-relevant information, while CON transiently disbands to lend processing resources to other goal-relevant networks. This cartography of network dynamics reveals a dissociation between two prominent cognitive control networks, suggesting complementary mechanisms underlying goal-directed cognition.SIGNIFICANCE STATEMENT Cognitive control supports a variety of behaviors requiring flexible cognition, such as rapidly switching between tasks. Furthermore, cognitive control is negatively impacted in a variety of mental illnesses. We used tools from network science to characterize the implementation of cognitive control by large-scale brain systems. This revealed that two systems, the frontoparietal (FPN) and cingulo-opercular (CON) networks, have distinct but complementary roles in controlling global network reconfigurations. The FPN exhibited properties of a flexible coordinator (orchestrating task changes), while CON acted as a flexible switcher (switching specific regions to other systems to lend processing resources). These findings reveal an underlying distinction in cognitive processes that may be applicable to clinical, educational, and machine learning work targeting cognitive flexibility.

The Functional Role of Thalamocortical Coupling in the Human Motor Network

The amplitude of high broadband activity in human cortical field potentials indicates local processing and has repeatedly been shown to reflect motor control in the primary motor cortex. In a group of male and female subjects affected by essential tremor and undergoing deep brain stimulation surgery, ventral intermediate nucleus low-frequency oscillations (<30 Hz) entrain the corticomotor high broadband activity (>40 Hz) during rest, relinquishing that role during movement execution. This finding suggests that there is significant cross-rhythm communication between thalamocortical regions, and motor behavior corresponds to changes in thalamocortical phase-amplitude coupling profiles. Herein, we demonstrate that thalamocortical coupling is a crucial mechanism for gating motor behavior.SIGNIFICANCE STATEMENT We demonstrate, for the first time, how thalamocortical coupling is mediating movement execution in humans. We show how the low-frequency oscillation from the ventral intermediate nucleus, known as the motor nucleus of the thalamus, entrains the excitability of the primary motor cortex, as reflected by the phase-amplitude coupling between the two regions. We show that thalamocortical phase-amplitude coupling is a manifestation of a gating mechanism for movement execution mediated by the thalamus. These findings highlight the importance of incorporating cross-frequency relationship in models of motor behavior; and given the spatial specificity of this mechanism, this work could be used to improve functional targeting during surgical implantations in subcortical regions.

Link Definition Ameliorating Community Detection in Collaboration Networks

Collaboration networks are defined as a set of individuals who come together and collaborate on particular tasks such as publishing a paper. The analysis of such networks permits to extract knowledge on the structure and patterns of communities. The link definition and network extraction have a high impact on the analysis of collaboration networks. Previous studies model the connectivity in a network considering it as a binomial problem with respect to the existence of a collaboration between individuals. However, such a data consists of a high diversity of features that describe the quality of the interaction such as the contribution amount of each individual. In this paper, we have determined a solution to extract collaboration networks using corresponding features in a dataset. We define collaboration score to quantify the collaboration between collaborators. In order to validate our proposed method, we benefit from a scientific research institute dataset in which researchers are co–authors who are involved in the production of papers, prototypes, and intellectual properties (IP). We evaluated the generated networks, produced through different thresholds of collaboration score, by employing a set of network analysis metrics such as clustering coefficient, network density, and centrality measures. We investigated more the obtained networks using a community detection algorithm to further discuss the impact of our model on community detection. The outcome shows that the quality of resulted communities on the extracted collaboration networks can differ significantly based on the choice of the linkage threshold.

Disrupted interactions among the hippocampal, dorsal attention, and central-executive networks in amnestic mild cognitive impairment

Neuroimaging investigations consistently demonstrate that the neural processes involve complex interactions between the large-scale networks. Among those networks, the dorsal attention network (DAN) and the central-executive network (CEN) have been previously shown to exhibit anti-correlated activity with the default-mode network (DMN) in cognitively normal people. In amnestic mild cognitive impairment (MCI) and Alzheimer's disease, the hippocampal network (HCN)-a key memory processing system-and its interactions with other networks have gathered central interest. The current study aims to evaluate the patterns of functional architectures of the HCN with the three networks-DAN, CEN, and DMN-in amnestic MCI and normal controls (NC) to test the hypothesis that the interactions of HCN with other networks alter in MCI. We recorded the resting state functional MRI, assessed patterns of functional architectures between the four networks using dynamical causal modeling, and compared between NC and MCI. Our analysis showed that the DAN modulates the activity between the HCN and the DMN in both MCI and NC. We further uncovered that the DAN modulates the activity between the HCN and the CEN in NC, but such modulation is impaired in MCI. We found an association between impaired modulation and Montreal cognitive assessment (R = 0.349). Overall, our findings provide important insight in understanding the neuroimaging signature of amnestic MCI and/or Alzheimer's disease.

Gut region influences the diversity and interactions of bacterial communities in pikas (Ochotona curzoniae and Ochotona daurica)

The mammalian microbial communities in the gastrointestinal tract (GIT) play important roles in host nutrition and health. However, we still lack an understanding of how these communities are organized across GIT in natural environments. Here, using 16S rRNA gene sequencing, we analyzed the bacterial community diversity, network interactions and ecosystem stability across five gut regions (mouth, stomach, small intestine, cecum and colon) emanating from two common pika species in China, including Plateau pikas (Ochotona curzoniae) inhabiting high-altitude regions, as well as Daurian pikas (O. daurica) occupying low-altitude areas. The relative abundances of dominant Bacteroidetes and Firmicutes exhibited an increasing trend from mouth to colon. Cecum and colon harbored higher bacterial diversity compared with other anatomical regions. Gut region significantly influenced the structure of bacterial communities in the GIT. Network analysis indicated that topological features showed marked variations among gut regions. Interestingly, the ecosystem stability of bacterial communities increased gradually from mouth to colon. Our results suggest that gut region influences the diversity, structure and network interactions of bacterial communities in pikas. For hindgut-fermenting herbivorous mammals, relatively higher bacterial diversity and ecosystem stability in the cecum may provide a favorable condition for the fermentation of indigestible plant polysaccharides.

Pollination by the locally endangered island flying fox (Pteropus hypomelanus) enhances fruit production of the economically important durian (Durio zibethinus)

Fruit bats provide valuable pollination services to humans through a unique coevolutionary relationship with chiropterophilous plants. However, chiropterophily in the Old World and the pollination roles of large bats, such as flying foxes (Pteropus spp., Acerodon spp., Desmalopex spp.), are still poorly understood and require further elucidation. Efforts to protect these bats have been hampered by a lack of basic quantitative information on their role as ecosystem service providers. Here, we investigate the role of the locally endangered island flying fox Pteropus hypomelanus in the pollination ecology of durian (Durio zibethinus), an economically important crop in Southeast Asia. On Tioman Island, Peninsular Malaysia, we deployed 19 stations of paired infrared camera and video traps across varying heights at four individual flowering trees in a durian orchard. We detected at least nine species of animal visitors, but only bats had mutualistic interactions with durian flowers. There was a clear vertical stratification in the feeding niches of flying foxes and nectar bats, with flying foxes feeding at greater heights in the trees. Flying foxes had a positive effect on mature fruit set and therefore serve as important pollinators for durian trees. As such, semi-wild durian trees-particularly tall ones-may be dependent on flying foxes for enhancing reproductive success. Our study is the first to quantify the role of flying foxes in durian pollination, demonstrating that these giant fruit bats may have far more important ecological, evolutionary, and economic roles than previously thought. This has important implications and can aid efforts to promote flying fox conservation, especially in Southeast Asian countries.

Beyond the Status Quo: A Role for Beta Oscillations in Endogenous Content (Re)Activation

Among the rhythms of the brain, oscillations in the beta frequency range (∼13-30 Hz) have been considered the most enigmatic. Traditionally associated with sensorimotor functions, beta oscillations have recently become more broadly implicated in top-down processing, long-range communication, and preservation of the current brain state. Here, we extend and refine these views based on accumulating new findings of content-specific beta-synchronization during endogenous information processing in working memory (WM) and decision making. We characterize such content-specific beta activity as short-lived, flexible network dynamics supporting the endogenous (re)activation of cortical representations. Specifically, we suggest that beta-mediated ensemble formation within and between cortical areas may awake, rather than merely preserve, an endogenous cognitive set in the service of current task demands. This proposal accommodates key aspects of content-specific beta modulations in monkeys and humans, integrates with timely computational models, and outlines a functional role for beta that fits its transient temporal characteristics.

Resting State fMRI in Mice Reveals Anesthesia Specific Signatures of Brain Functional Networks and Their Interactions

fMRI studies in mice typically require the use of anesthetics. Yet, it is known that anesthesia alters responses to stimuli or functional networks at rest. In this work, we have used Dual Regression analysis Network Modeling to investigate the effects of two commonly used anesthetics, isoflurane and medetomidine, on rs-fMRI derived functional networks, and in particular to what extent anesthesia affected the interaction within and between these networks. Experimental data have been used from a previous study (Grandjean et al., 2014). We applied multivariate ICA analysis and Dual Regression to infer the differences in functional connectivity between isoflurane- and medetomidine-anesthetized mice. Further network analysis was performed to investigate within- and between-network connectivity differences between these anesthetic regimens. The results revealed five major networks in the mouse brain: lateral cortical, associative cortical, default mode, subcortical, and thalamic network. The anesthesia regime had a profound effect both on within- and between-network interactions. Under isoflurane anesthesia predominantly intra- and inter-cortical interactions have been observed, with only minor interactions involving subcortical structures and in particular attenuated cortico-thalamic connectivity. In contrast, medetomidine-anesthetized mice displayed subcortical functional connectivity including interactions between cortical and thalamic ICA components. Combining the two anesthetics at low dose resulted in network interaction that constituted the superposition of the interaction observed for each anesthetic alone. The study demonstrated that network modeling is a promising tool for analyzing the brain functional architecture in mice and comparing alterations therein caused by different physiological or pathological states. Understanding the differential effects of anesthetics on brain networks and their interaction is essential when interpreting fMRI data recorded under specific physiological and pathological conditions.

Interactions between the salience and default-mode networks are disrupted in cocaine addiction

Cocaine dependence is a complex neuropsychiatric disorder manifested as dysregulation of multiple behavioral, emotional, and cognitive constructs. Neuroimaging studies have begun to identify specific neurobiological circuit impairments in cocaine-dependent (CD) individuals that may underlie these symptoms. However, whether, where, and how the interactions within and between these circuits are disrupted remain largely unknown. We used resting-state fMRI and modularity network analysis to identify brain modules of a priori interest (default-mode network [DMN], salience network [SN], executive control network [ECN], medial temporal lobe [MTL], and striatum) in 47 CD and 47 matched healthy control (HC) participants and explored alterations within and between these brain modules as a function of addiction. At the module level, intermodule connectivity decreased between DMN and SN in CD. At the nodal level, several regions showed decreased connections with multiple modules in CD: the rostral anterior cingulate connection strength was reduced with SN and MTL; the posterior cingulate had reduced connections with ECN; and the bilateral insula demonstrated decreased connections with DMN. Furthermore, alexithymia, a personality trait previously associated with addiction, correlated negatively with intramodule connectivity within SN only in cocaine users. Our results indicate that cocaine addiction is associated with disrupted interactions among DMN, MTL, and SN, which have been implicated, respectively, in self-referential functions, emotion and memory, and coordinating between internal and external stimuli, providing novel and important insights into the neurobiological mechanisms of cocaine addiction.

Dynamics of networks during absence seizure's on- and offset in rodents and man

Network mechanisms relevant for the generation, maintenance and termination of spike-wave discharges (SWD), the neurophysiological hallmark of absence epilepsy, are still enigmatic and widely discussed. Within the last years, however, improvements in signal analytical techniques, applied to both animal and human fMRI, EEG, MEG, and ECoG data, greatly increased our understanding and challenged several, dogmatic concepts of SWD. This review will summarize these recent data, demonstrating that SWD are not primary generalized, are not sudden and unpredictable events. It will disentangle different functional contributions of structures within the cortico-thalamo-cortical system, relevant for the generation, generalization, maintenance, and termination of SWD and will present a new “network based” scenario for these oscillations. Similarities and differences between rodent and human data are presented demonstrating that in both species a local cortical onset zone of SWD exists, although with different locations; that in both some forms of cortical and thalamic precursor activity can be found, and that SWD occur through repetitive cyclic activity between cortex and thalamus. The focal onset zone in human data could differ between patients with varying spatial and temporal dynamics; in rats the latter is still poorly investigated.

Perspective: causes and functional significance of temporal variations in attention control

Attention control describes the human ability to selectively modulate the plethora of sensory signals and internal thoughts. The neural systems of attention control have been studied extensively, warranted by the importance of this ability to daily functioning. Here, we consider an emerging theme in the study of attention control-slow temporal fluctuations. We posit that these fluctuations are functionally significant, and may reflect underlying interactions between the neural systems related to attention control. We explore thought experiments to generate different perspectives on landscapes created by the interactions between attention control networks and the sources of input to these control systems. We examine interactions of the fronto-parietal and the default mode networks in the context of internal cognition, and the noradrenergic modulatory projections in the context of arousal, and we consider the implications of these inter-network dynamics on attention states and attention disorders. Through these thought experiments we highlight the breadth of potential knowledge to be gained from the study of slow fluctuations in attention control.

Identification of a gene expression signature common to distinct cancer pathways

Mutations in cancer-causing genes induce changes in gene expression programs critical for malignant cell transformation. Publicly available gene expression profiles produced by modulating the expression of distinct cancer genes may therefore represent a rich resource for the identification of gene signatures common to seemingly unrelated cancer genes. We combined automatic retrieval with manual validation to obtain a data set of high-quality gene microarray profiles. This data set was used to create logical models of the signaling events underlying the observed expression changes produced by various cancer genes and allowed to uncover unknown and verifiable interactions. Data clustering revealed novel sets of gene expression profiles commonly regulated by distinct cancer genes. Our method allows retrieval of significant new information and testable hypotheses from a pool of deposited cancer gene expression experiments that are otherwise not apparent or appear insignificant from single measurements. The complete results are available through a web-application at http://biodata.ethz.ch/cgi-bin/geologic.

High-frequency neuronal network modulations encoded in scalp EEG precede the onset of focal seizures

Modulations of neuronal network interactions by seizure precursors are only partially understood and difficult to measure, in part due to inherent intra- and inter-patient seizure heterogeneities and EEG variability. This study investigated preictal neuromodulations associated with seizures originating in the temporal and/or frontal lobes, using information theoretic parameters estimated from awake scalp EEGs in two frequency ranges, ≤100 Hz and >100 Hz, respectively. Seizure-related activity at high frequencies has not been extensively estimated in awake scalp EEGs. Based on the statistical similarity of preictal and ictal information parameters, preictal network interactions appeared to be specifically modulated at frequencies >100 Hz, but not at lower frequencies. The dynamics of these parameters varied distinctly according to the origin of seizure onset (temporal versus frontal). Although preliminary, and based on a small patient sample for which the potential heterogeneity of multiple anticonvulsive medications was difficult to control, these results suggest that preictal modulations may be estimated from high-frequency scalp EEGs using directional information measures with high specificity to ictal events, and may thus be promising for improving seizure prediction.

Neuronal encoding of object and distance information: a model simulation study on naturalistic optic flow processing

We developed a model of the input circuitry of the FD1 cell, an identified motion-sensitive interneuron in the blowfly's visual system. The model circuit successfully reproduces the FD1 cell's most conspicuous property: its larger responses to objects than to spatially extended patterns. The model circuit also mimics the time-dependent responses of FD1 to dynamically complex naturalistic stimuli, shaped by the blowfly's saccadic flight and gaze strategy: the FD1 responses are enhanced when, as a consequence of self-motion, a nearby object crosses the receptive field during intersaccadic intervals. Moreover, the model predicts that these object-induced responses are superimposed by pronounced pattern-dependent fluctuations during movements on virtual test flights in a three-dimensional environment with systematic modifications of the environmental patterns. Hence, the FD1 cell is predicted to detect not unambiguously objects defined by the spatial layout of the environment, but to be also sensitive to objects distinguished by textural features. These ambiguous detection abilities suggest an encoding of information about objects-irrespective of the features by which the objects are defined-by a population of cells, with the FD1 cell presumably playing a prominent role in such an ensemble.

Binocular integration of visual information: a model study on naturalistic optic flow processing

The computation of visual information from both visual hemispheres is often of functional relevance when solving orientation and navigation tasks. The vCH-cell is a motion-sensitive wide-field neuron in the visual system of the blowfly Calliphora, a model system in the field of optic flow processing. The vCH-cell receives input from various other identified wide-field cells, the receptive fields of which are located in both the ipsilateral and the contralateral visual field. The relevance of this connectivity to the processing of naturalistic image sequences, with their peculiar dynamical characteristics, is still unresolved. To disentangle the contributions of the different input components to the cell's overall response, we used electrophysiologically determined responses of the vCH-cell and its various input elements to tune a model of the vCH-circuit. Their impact on the vCH-cell response could be distinguished by stimulating not only extended parts of the visual field of the fly, but also selected regions in the ipsi- and contralateral visual field with behaviorally generated optic flow. We show that a computational model of the vCH-circuit is able to account for the neuronal activities of the counterparts in the blowfly's visual system. Furthermore, we offer an insight into the dendritic integration of binocular visual input.

Recurrent network interactions underlying flow-field selectivity of visual interneurons

Motion-sensitive large-field neurons found at higher processing stages in many species often exhibit a remarkable selectivity for particular flow fields. However, the underlying neural mechanisms are not yet understood. We studied this problem in the so-called lobula plate tangential cells (LPTCs) of the fly. Investigating the connectivity between LPTCs by means of dual recordings, we find two types of connections: (1) heterolateral connections between LPTCs of both hemispheres and (2) ipsilateral connections between LPTCs within one lobula plate. The circuit is suitable to amplify incoming, dendritic signals in the case of rotatory flow fields and to reduce them in the case of other flow-field structures. In addition to feedforward connectivity, thus, the flow-field selectivity of LPTCs may be significantly attributable to recurrent excitation involving the network of large-field neurons in both brain hemispheres.