Specific Connectivity Patterns Research Articles

Resting-state functional connectome predicts sleep quality two months after the first negative COVID-19 antigen test

BackgroundThe COVID-19 pandemic has led to long-term neurological and psychological effects, including sleep disturbances. While prior studies have identified altered brain function post-COVID-19, specific functional connectivity (FC) patterns predicting sleep quality after recovery remain unclear. This study aims to identify FC patterns associated with sleep quality two months after the first negative COVID-19 antigen test. MethodsUsing a connectome-based predictive modeling (CPM) approach, we identified the functional connectome regulating sleep quality based on a 164-region parcellation. Significant connections were analyzed using mediation models to examine their role in the relationship between anxiety, depression, and sleep. ResultsFC between the right cerebellar peduncle and the left VIII of the cerebellum, and between the left middle temporal pole (MTP) and left ventral tegmental area (VTA), significantly predicted Pittsburgh Sleep Quality Index (PSQI) scores for sleep disturbances two months post-recovery (q2 = 0.059, MSE = 0.154, p = 0.017, r = 0.350). Mediation analysis showed a significant indirect effect of FC between the left MTP and VTA on the relationship between generalized anxiety and sleep disturbances (indirect effect = 0.013, 95% CI = [0.002, 0.03], pfdr <0.05). FC between the right dorsal raphe nucleus and ipsilateral regions—including occipital, parietal, and temporal areas—predicted PSQI scores for daytime dysfunction (q2 = 0.092, MSE = 0.678, p = 0.025, r = 0.342). ConclusionPost-COVID-19 brain connectivity and anxiety predict sleep quality. These findings highlight the potential for targeted therapeutic strategies to improve sleep and identify patients at risk for prolonged disturbances through FC biomarkers.

Mapping Functional Connectivity Signatures of Pharmacoresistant Focal Cortical Dysplasia-Related Epilepsy.

To determine common network alterations in focal cortical dysplasia pharmacoresistant epilepsy (FCD-PRE) using functional connectivity analysis of resting-state functional magnetic resonance imaging (rsfMRI). This is a retrospective imaging cohort from Children's National Hospital (Washington, DC, USA) from January, 2011 to January, 2022. Patients with 3-T MRI-confirmed FCD-PRE underwent rsfMRI as part of routine clinical care. Patients were included if they were age 5-22 years at the time of the scan, and had a minimum of 18 months of follow-up. Healthy, typically-developing controls were included from Children's National Hospital (n = 16) and matched from Human Connectome Project-Development public dataset (n = 100). A total of 42 FCD-PRE patients (20 M:22 F, aged 14.2 ± 4.1 years) and 116 healthy controls (56 M:60 F, aged 13.7 ± 3.3 years) with rsfMRI were included. Seed-based functional connectivity maps were generated for each FCD, and each seed was used to generate a patient-specific z-scored connectivity map on 116 controls. FCD-PRE patients had mutual altered connectivity in regions of dorsal attention, default mode, and control networks. Functional connectivity was diminished within the FCD dominant functional network, as well as in homotopic regions. Cluster specific connectivity patterns varied by pathological subtype. Higher FCD connectivity to the limbic network was associated with increased odds of Engel I outcome. This study demonstrates diminished functional connectivity patterns in FCD-PRE, which may represent a neuromarker for the disease, independent of FCD location, involving the dorsal attention, default mode, and control functional networks. Higher connectivity to the limbic network is associated with a seizure-free outcome. Future multicenter, prospective studies are needed to allow for much earlier detection of signatures of treatment-resistant epilepsy. ANN NEUROL 2024.

The impact of insomnia on brain networks topology in depressed patients: A resting-state fMRI study

ObjectiveDepression and insomnia frequently co-occur, but the neural mechanisms between patients with varying degrees of these conditions are not fully understood. The specific topological features and connectivity patterns of this co-morbidity have not been extensively studied. This study aimed to investigate the topological characteristics of topological characteristics and functional connectivity of brain networks in depressed patients with insomnia. MethodsResting-state functional magnetic resonance imaging data from 32 depressed patients with a high level of insomnia (D-HI), 35 depressed patients with a low level of insomnia (D-LI), and 81 healthy controls (HC) were used to investigate alterations in brain topological organization functional networks. Nodal and global properties were analyzed using graph-theoretic techniques, and network-based statistical analysis was employed to identify changes in brain network functional connectivity. ResultsCompared to the HC group, both the D-HI and D-LI groups showed an increase in the global efficiency (Eglob) values, local efficiency (Eloc) was decreased in the D-HI group, and Lambda and shortest path length (Lp) values were decreased in the D-LI group. At the nodal level, the right parietal nodal clustering coefficient (NCp) values were reduced in D-HI and D-LI groups compared to those in HC. The functional connectivity of brain networks in patients with D-HI mainly involves default mode network (DMN)-cingulo-opercular network (CON), DMN-visual network (VN), DMN-sensorimotor network (SMN), and DMN-cerebellar network (CN), while that in patients with D-LI mainly involves SMN-CON, SMN-SMN, SMN-VN, and SMN-CN. The values of the connection between the midinsula and postoccipital gyrus was negatively correlated with scores for early awakening in D-HI. ConclusionThese findings may contribute to our understanding of the underlying neuropsychological mechanisms in depressed patients with insomnia.

Whole-brain model replicates sleep-like slow-wave dynamics generated by stroke lesions

Focal brain injuries, such as stroke, cause local structural damage as well as alteration of neuronal activity in distant brain regions. Experimental evidence suggests that one of these changes is the appearance of sleep-like slow waves in the otherwise awake individual. This pattern is prominent in areas surrounding the damaged region and can extend to connected brain regions in a way consistent with the individual's specific long-range connectivity patterns. In this paper we present a generative whole-brain model based on (f)MRI data that, in combination with the disconnection mask associated with a given patient, explains the effects of the sleep-like slow waves originated in the vicinity of the lesion area on the distant brain activity. Our model reveals new aspects of their interaction, being able to reproduce functional connectivity patterns of stroke patients and offering a detailed, causal understanding of how stroke-related effects, in particular slow waves, spread throughout the brain. The presented findings demonstrate that the model effectively captures the links between stroke occurrences, sleep-like slow waves, and their subsequent spread across the human brain.

Distinct dynamic connectivity profiles promote enhanced conscious perception of auditory stimuli

The neuroscience of consciousness aims to identify neural markers that distinguish brain dynamics in healthy individuals from those in unconscious conditions. Recent research has revealed that specific brain connectivity patterns correlate with conscious states and diminish with loss of consciousness. However, the contribution of these patterns to shaping conscious processing remains unclear. Our study investigates the functional significance of these neural dynamics by examining their impact on participants’ ability to process external information during wakefulness. Using fMRI recordings during an auditory detection task and rest, we show that ongoing dynamics are underpinned by brain patterns consistent with those identified in previous research. Detection of auditory stimuli at threshold is specifically improved when the connectivity pattern at stimulus presentation corresponds to patterns characteristic of conscious states. Conversely, the occurrence of these conscious state-associated patterns increases after detection, indicating a mutual influence between ongoing brain dynamics and conscious perception. Our findings suggest that certain brain configurations are more favorable to the conscious processing of external stimuli. Targeting these favorable patterns in patients with consciousness disorders may help identify windows of greater receptivity to the external world, guiding personalized treatments.

A connectome-wide association study of altered functional connectivity in schizophrenia based on resting-state fMRI

BackgroundAberrant resting-state functional connectivity is a neuropathological feature of schizophrenia (SCZ). Prior investigations into functional connectivity abnormalities have primarily employed seed-based connectivity analysis, necessitating predefined seed locations. To address this limitation, a data-driven multivariate method known as connectome-wide association study (CWAS) has been proposed for exploring whole-brain functional connectivity. MethodsWe conducted a CWAS analysis involving 46 patients with SCZ and 40 age- and sex-matched healthy controls. Multivariate distance matrix regression (MDMR) was utilized to identify key nodes in the brain. Subsequently, we conducted a follow-up seed-based connectivity analysis to elucidate specific connectivity patterns between regions of interest (ROIs). Additionally, we explored the spatial correlation between changes in functional connectivity and underlying molecular architectures by examining correlations between neurotransmitter/transporter distribution densities and functional connectivity. ResultsMDMR revealed the right medial frontal gyrus and the left calcarine sulcus as two key nodes. Follow-up analysis unveiled hypoconnectivity between the right medial frontal superior gyrus and the right fusiform gyrus, as well as hypoconnectivity between the left calcarine sulcus and the right lingual gyrus in SCZ. Notably, a significant association between functional connectivity strength and positive symptom severity was identified. Furthermore, altered functional connectivity patterns suggested potential dysfunctions in the dopamine, serotonin, and gamma-aminobutyric acid systems. ConclusionsThis study elucidated reduced functional connectivity both within and between the medial frontal regions and the occipital cortex in patients with SCZ. Moreover, it indicated potential alterations in molecular architecture, thereby expanding current knowledge regarding neurobiological changes associated with SCZ.

Altered intra- and inter-network connectivity in autism spectrum disorder.

A neurodevelopmental illness termed as the autism spectrum disorder (ASD) is described by social interaction impairments. Previous studies employing resting-state functional imaging (rs-fMRI) identified both hyperconnectivity and hypoconnectivity patterns in ASD people. However, specific patterns of connectivity within and between networks linked to ASD remain largely unexplored. We utilized a meticulously selected subset of high-quality data, comprising 45 individuals diagnosed with ASD and 47 HCs, obtained from the ABIDE dataset. The pre-processed rs-fMRI time series signals were partitioned into ninety regions of interest. We focused on eight intrinsic connectivity networks and further performed intra- and inter-network analysis. Finally, support vector machine was used to discriminate ASD from HC. Through different sparsities, ASD exhibited significantly decreased intra-network connectivity within default mode network and dorsal attention network, increased connectivity between limbic network and subcortical network, and decreased connectivity between default mode network and limbic network. Using the classifier trained on altered intra- and inter-network connectivity, multivariate pattern analyses classified the ASD from HC with 71.74% accuracy, 70.21% specificity and 75.56% sensitivity in 10% sparsity of functional connectivity. ASD showed characteristic reorganization of the brain networks and this provided new insight into the underlying process of the functional connectome dysfunction in ASD.

Small World derived index to distinguish Alzheimer’s type dementia and healthy subjects

Abstract Background This article introduces a novel index aimed at uncovering specific brain connectivity patterns associated with Alzheimer's disease (AD), defined according to neuropsychological patterns. Methods Electroencephalographic (EEG) recordings of 370 people, including 170 healthy subjects and 200 mild-AD patients, were acquired in different clinical centres using different acquisition equipment by harmonising acquisition settings. The study employed a new derived Small World (SW) index, SWcomb, that serves as a comprehensive metric designed to integrate the seven SW parameters, computed across the typical EEG frequency bands. The objective is to create a unified index that effectively distinguishes individuals with a neuropsychological pattern compatible with AD from healthy ones. Results Results showed that the healthy group exhibited the lowest SWcomb values, while the AD group displayed the highest SWcomb ones. Conclusions These findings suggest that SWcomb index represents an easy-to-perform, low-cost, widely available and non-invasive biomarker for distinguishing between healthy individuals and AD patients.

HyGAnno: hybrid graph neural network-based cell type annotation for single-cell ATAC sequencing data.

Reliable cell type annotations are crucial for investigating cellular heterogeneity in single-cell omics data. Although various computational approaches have been proposed for single-cell RNA sequencing (scRNA-seq) annotation, high-quality cell labels are still lacking in single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) data, because of extreme sparsity and inconsistent chromatin accessibility between datasets. Here, we present a novel automated cell annotation method that transfers cell type information from a well-labeled scRNA-seq reference to an unlabeled scATAC-seq target, via a parallel graph neural network, in a semi-supervised manner. Unlike existing methods that utilize only gene expression or gene activity features, HyGAnno leverages genome-wide accessibility peak features to facilitate the training process. In addition, HyGAnno reconstructs a reference-target cell graph to detect cells with low prediction reliability, according to their specific graph connectivity patterns. HyGAnno was assessed across various datasets, showcasing its strengths in precise cell annotation, generating interpretable cell embeddings, robustness to noisy reference data and adaptability to tumor tissues.

Exploring the potential of combining transcranial magnetic stimulation and electroencephalography to investigate mild cognitive impairment and Alzheimer's disease: a systematic review.

Transcranial magnetic stimulation (TMS) and electroencephalography (EEG) are non-invasive techniques used for neuromodulation and recording brain electrical activity, respectively. The integration of TMS-EEG has emerged as a valuable tool for investigating the complex mechanisms involved in age-related disorders, such as mild cognitive impairment (MCI) and Alzheimer's disease (AD). By systematically synthesizing TMS-EEG studies, this review aims to shed light on the neurophysiological mechanisms underlying MCI and AD, while also exploring the practical applications of TMS-EEG in clinical settings. PubMed, ScienceDirect, and PsychInfo were selected as the databases for this review. The 22 eligible studies included a total of 592 individuals with MCI or AD as well as 301 cognitively normal adults. TMS-EEG assessments unveiled specific patterns of corticospinal excitability, plasticity, and brain connectivity that distinguished individuals on the AD spectrum from cognitively normal older adults. Moreover, the TMS-induced EEG features were observed to be correlated with cognitive performance and the presence of AD pathological biomarkers. The comprehensive examination of the existing studies demonstrates that the combination of TMS and EEG has yielded valuable insights into the neurophysiology of MCI and AD. This integration shows great potential for early detection, monitoring disease progression, and anticipating response to treatment. Future research is of paramount importance to delve into the potential utilization of TMS-EEG for treatment optimization in individuals with MCI and AD.

Specific Patterns of Endogenous Functional Connectivity Are Associated With Harm Avoidance in Obsessive-Compulsive Disorder

BackgroundIndividuals with obsessive-compulsive disorder (OCD) show persistent avoidance behaviors, often in the absence of actual threat. Quality-of-life costs and heterogeneity support the need for novel brain-behavior intervention targets. Informed by mechanistic and anatomical studies of persistent avoidance in rodents and nonhuman primates, our goal was to test whether connections within a hypothesized persistent avoidance–related network predicted OCD-related harm avoidance (HA), a trait measure of persistent avoidance. We hypothesized that 1) HA, not an OCD diagnosis, would be associated with altered endogenous connectivity in at least one connection in the network; 2) HA-specific findings would be robust to comorbid symptoms; and 3) reliable findings would replicate in a holdout testing subsample. MethodsUsing resting-state functional connectivity magnetic resonance imaging, cross-validated elastic net for feature selection, and Poisson generalized linear models, we tested which connections significantly predicted HA in our training subsample (n = 73; 71.8% female; healthy control group n = 36, OCD group n = 37); robustness to comorbidities; and replicability in a testing subsample (n = 30; 56.7% female; healthy control group n = 15, OCD group n = 15). ResultsStronger inverse connectivity between the right dorsal anterior cingulate cortex and right basolateral amygdala and stronger positive connectivity between the right ventral anterior insula and left ventral striatum were associated with greater HA across groups. Network connections did not discriminate OCD diagnostic status or predict HA-correlated traits, suggesting sensitivity to trait HA. The dorsal anterior cingulate cortex–basolateral amygdala relationship was robust to controlling for comorbidities and medication in individuals with OCD and was also predictive of HA in our testing subsample. ConclusionsStronger inverse dorsal anterior cingulate cortex–basolateral amygdala connectivity was robustly and reliably associated with HA across groups and in OCD. Results support the relevance of a cross-species persistent avoidance–related network to OCD, with implications for precision-based approaches and treatment.

Aberrant high-beta band functional connectivity during reward processing in melancholic major depressive disorder: An MEG study

ObjectiveTo identify the spatial–temporal pattern variation of whole-brain functional connectivity (FC) during reward processing in melancholic major depressive disorder (MDD) patients, and to determine the clinical correlates of connectomic differences. Methods61 MDD patients and 32 healthy controls were enrolled into the study. During magnetoencephalography (MEG) scanning, all participants completed the facial emotion recognition task. The MDD patients were further divided into two groups: melancholic (n = 31) and non-melancholic (n = 30), based on the Mini International Neuropsychiatric Interview (M.I.N.I.) assessment. Melancholic symptoms were examined by using the 6-item melancholia subscale from the Hamilton Depression Rating Scale (HAM-D6). The whole-brain orthogonalized power envelope connections in the high-beta band (20–35 Hz) were constructed in each period after the happy emotional stimuli (0–200 ms, 100–300 ms, 200–400 ms, 300–500 ms, and 400–600 ms). Then, the network-based statistic (NBS) was used to determine the specific abnormal connection patterns in melancholic MDD patients. ResultsThe NBS identified a sub-network difference at the mid-late period (300–500 ms) in response to happy faces among the three groups (corrected P = 0.035). Then, the post hoc and correlation analyses found five FCs were decreased in melancholic MDD patients and were related to HAM-D6 score, including FCs of left fusiform gyrus-right orbital inferior frontal gyrus (r = −0.52, P < 0.001), left fusiform gyrus-left amygdala (r = −0.26, P = 0.049), left posterior cingulate gyrus-right precuneus (r = −0.32, P = 0.025), left precuneus-right precuneus (r = −0.27, P = 0.049), and left precuneus-left inferior occipital gyrus (r = −0.32, P = 0.025). ConclusionIn response to happy faces, melancholic MDD patients demonstrated a disrupted functional connective pattern (20–35 Hz, 300–500 ms), which involved brain regions in visual information processing and the limbic system. The aberrant functional connective pattern in reward processing might be a biomarker of melancholic MDD.

Altered connectivity patterns of medial and lateral orbitofrontal cortex underlie the severity of bulimic symptoms

ObjectiveCompared to clinical bulimia nervosa, sub-threshold bulimic symptoms are becoming more prevalent in non-clinical or general population, which is repeatedly linked with the connectivity in orbitofrontal cortex (OFC), including functionally heterogeneous the medial and lateral OFC (mOFC; lOFC). However, the specific connectivity patterns of the mOFC and lOFC in individuals with severe or mild bulimic symptoms (SB; MB) remain poorly understood. MethodsWe first utilized resting-state functional connectivity (FC) and spectral dynamic causal modeling (spDCM) to investigate abnormal functional and effective connectivity (EC) of OFC subregions in adults with different severity of bulimic. The SB group (n = 21), MB group (n = 114), and healthy controls (HC, n = 91) underwent rs-fMRI scans. A generalized linear model was applied to determine the OFC-seeded whole-brain FC across the three groups. Subsequently, spDCM was used to estimate differences in EC among the three groups based on the FC results. ResultsWe observed a shared neural basis for SB and MB groups (i.e., weaker lOFC-superior parietal lobule connectivity), which may support the role of dysfunctional inhibitory control in general bulimic symptomatology. Whereas, SB group displayed greater lOFC-occipital pole connectivity than MB group, suggesting the specificity of the neural correlates of full-threshold/severe bulimia. The directional links from the mOFC to lOFC and amygdala could further explain the aberrant interactions of reward sensitivity with inhibitory control and homeostatic energy in sub-threshold/mild condition. ConclusionThe current study provides novel evidence that divergent connectivity patterns of the lOFC and mOFC may contribute to different severities of bulimia, which will expands our understanding of the neurobiological substrates underlying bulimia across a spectrum from healthy to unhealthy.

Neural connectivity moderators and mechanisms of ketamine treatment among treatment-resistant depressed patients: a randomized controlled trial

Intravenous (IV) ketamine has emerged as a rapid and effective treatment for TRD. However, the specific neural mechanisms of ketamine's effects in humans remains unclear. Although neuroplasticity is implicated as a mechanism of action in animal models, relatively few randomized controlled trials (RCTs) in TRD patients have examined ketamine's impact on functional connectivity, a posited functional marker of neuroplasticity-particularly in the context of a mood-induction paradigm (termed miFC). 152 adults with TRD (63% female; 37% male) were randomly allocated to receive a single infusion of ketamine or saline in a 2:1 ratio. We examined changes in connectivity (from baseline to 24-h post-infusion) that differed by treatment, and whether clinical treatment response at 24-h post-infusion was uniquely related (among patients allocated to ketamine relative to saline) to (1) pre-treatment connectivity and (2) changes in connectivity. We examined both miFC and rsFC, using prefrontal cortex and limbic seed regions. We also conducted a multiverse analysis to examine findings most robust against analytic decisions. Across both miFC and rsFC, ketamine was associated with greater in prefrontal/limbic connectivity compared to saline, and lower baseline connectivity of limbic and prefrontal regions predicted greater treatment response in patients receiving ketamine. Greater connectivity increases in participants receiving ketamine was uniquely related to greater treatment response. In addition, certain findings were identified as being reproducible against different analytic decisions in multiverse analyses. Our findings identify specific neural connectivity patterns impacted by ketamine and were uniquely related to outcomes following ketamine (relative to saline). These findings generally support prominent neuroplasticity models of ketamine's therapeutic efficacy. These findings lay new groundwork for understanding how to enhance and optimize ketamine treatments and develop novel rapid-acting treatments for depression. This research was supported by NIH grant R01MH113857 and by the Clinical and Translational Sciences Institute at the University of Pittsburgh (UL1-TR-001857).

Influences of local and global context on local orientation perception.

Visual context modulates perception of local orientation attributes. These spatially very localised effects are considered to correspond to specific excitatory-inhibitory connectivity patterns of early visual areas as V1, creating perceptual tilt repulsion and attraction effects. Here, orientation misperception of small Gabor stimuli was used as a probe of this computational structure by sampling a large spatio-orientation space to reveal expected asymmetries due to the underlying neuronal processing. Surprisingly, the results showed a regular iso-orientation pattern of nearby location effects whose reference point was globally modulated by the spatial structure, without any complex interactions between local positions and orientation. This pattern of results was confirmed by the two perceptual parameters of bias and discrimination ability. Furthermore, the response times to stimulus configuration displayed variations that further provided evidence of how multiple early visual stages affect perception of simple stimuli.

EEG-based Emotion Recognition Using Sub-Band Time-Delay Correlations.

Emotion recognition is a challenging task with many potential applications in psychology, psychiatry, and human-computer interaction (HCI). The use of time-delay information in the controlled time-delay stability (cTDS) algorithm can help to capture the temporal dynamics of EEG signals, including sub-band information and bi-directional coupling that can aid in emotion recognition and identification of specific connectivity patterns between brain rhythms. Incorporating EEG frequency bands can be used to design better emotion recognition systems. This paper evaluates the cTDS algorithm for binary classification tasks of arousal and valence using EEG sub-band signals. This method achieved a high accuracy of 91.1% for arousal and 91.7% for valence based on one electrode recording site at Fp1. The cTDS algorithm is a promising approach to analyzing brain network interactions. It can be particularly applicable to arousal and valence classification tasks, especially within a complex, multimodal feature space associated with understanding psychiatric disorders and HCI applications.

Network Architecture of Verticality Processing in the Human Thalamus.

Thalamic dysfunction in lesions or neurodegeneration may alter verticality perception and lead to postural imbalance and falls. The aim of the current study was to delineate the structural and functional connectivity network architecture of the vestibular representations in the thalamus by multimodal magnetic resonance imaging. Seventy-four patients with acute unilateral isolated thalamic infarcts were studied prospectively with emphasis on the perception of verticality (tilts of the subjective visual vertical [SVV]). We used multivariate lesion-symptom mapping based on support-vector regression to determine the thalamic nuclei associated with ipsiversive and contraversive tilts of the SVV. The lesion maps were used to evaluate the white matter disconnection and whole brain functional connectivity in healthy subjects. Contraversive SVV tilts were associated with lesions of the ventral posterior lateral/medial, ventral lateral, medial pulvinar, and medial central/parafascicular nuclei. Clusters associated with ipsiversive tilts were located inferiorly (ventral posterior inferior nucleus) and laterally (ventral lateral, ventral posterior lateral, and reticular nucleus) to these areas. Distinct ascending vestibular brainstem pathways terminated in the subnuclei for ipsi- or contraversive verticality processing. The functional connectivity analysis showed specific patterns of cortical connections with the somatomotor network for lesions with contraversive tilts, and with the core multisensory vestibular representations (areas Ri, OP2-3, Ig, 3av, 2v) for lesions with ipsiversive tilts. The functional specialization may allow both a stable representation of verticality for sensorimotor integration and flexible adaption to sudden changes in the environment. A targeted modulation of this circuitry could be a novel therapeutic strategy for higher level balance disorders of thalamocortical origin. ANN NEUROL 2023.

Terrestrial food web of the Malpelo Fauna and Flora Sanctuary, Colombia: An analysis from a topological approach

Malpelo Island is the largest marine protected area (MPA) in the Colombian Pacific; however, the lack of information regarding its ecological dynamics suggests that management and conservation strategies are developed from an individual approach (species or groups of species) and not from an ecosystem one. This study analyzes the terrestrial food web of Malpelo Island, Colombia, based on topological analysis (e.g., centrality). The food web was constructed from 27 nodes representing the main trophogroups, which consist of species or functional groups. Malpelo Island had a food web of four steps with a maximum separation among all trophogroups and trophic pathways, with two steps in average length. Furthermore, the food web was divided into three food web compartments, with a recurrence of connectivity patterns dominated by apparent and exploitative competition, followed by tri-trophic chains and omnivory. Five key trophogroups control the energy flow throughout the food web (detritus, the land crab Johngarthia malpilensis, the lizard Anolis agassizi, the Malpelo dotted galliwasp Diploglossus millepunctatus, and the Nazca booby Sula granti). The high importance of detritus suggests that bottom-up processes act as a control and regulation mechanism of trophic flows. The low number of food web compartments and a high recurrence of specific connectivity patterns in the Malpelo Island terrestrial ecosystem evidence different ecological processes centered on five trophogroups, allowing stability against disturbances. In addition, the simulation of trophogroup removal (randomly or directed) suggests that food web can be vulnerable to structural alterations in their properties, which may have consequences on the resilience of this ecosystem. This study contributes to the knowledge of the trophic dynamics of Malpelo Island, providing a potential tool for management and conservation measures from an ecosystemic approach.

A model of decentralized vision in the sea urchin Diadema africanum

Sea urchins can detect light and move in relation to luminous stimuli despite lacking eyes. They presumably detect light through photoreceptor cells distributed on their body surface. However, there is currently no mechanistic explanation of how these animals can process light to detect visual stimuli and produce oriented movement. Here, we present a model of decentralized vision in echinoderms that includes all known processing stages, from photoreceptor cells to radial nerve neurons to neurons contained in the oral nerve ring encircling the mouth of the animals. In the model, light stimuli captured by photoreceptor cells produce neural activity in the radial nerve neurons. In turn, neural activity in the radial nerves is integrated in the oral nerve ring to produce a profile of neural activity reaching spatially across several ambulacra. This neural activity is readout to produce a model of movement. The model captures previously published data on the behavior of sea urchin Diadema africanum probed with a variety of physical stimuli. The specific pattern of neural connections used in the model makes testable predictions on the properties of single neurons and aggregate neural behavior in Diadema africanum and other echinoderms, offering a potential understanding of the mechanism of visual orientation in these animals.

Will digital technology address the challenges of drug development in psychiatry?

Will digital technology address the challenges of drug development in psychiatry?