Project description:Many studies have aimed to understand food webs by investigating components such as trophic links (one consumer taxon eats one resource taxon), tritrophic interactions (one consumer eats an intermediate taxon, which eats a resource), or longer chains of links. We show here that none of these components (links, tritrophic interactions, and longer chains), individually or as an ensemble, accounts fully for the properties of the next higher level of organization. As a cell is more than its molecules, as an organ is more than its cells, and as an organism is more than its organs, in a food web, new structure emerges at every organizational level up to and including the whole web. We demonstrate the emergence of properties at progressively higher levels of structure by using all of the directly observed, appropriately organized, publicly available food web datasets with relatively complete trophic link data and with average body mass and population density data for each taxon. There are only three such webs, those of Tuesday Lake, Michigan, in 1984 and 1986, and Ythan Estuary, Scotland. We make the data freely available online with this report. Differences in web patterns between Tuesday Lake and Ythan Estuary, and similarities of Tuesday Lake in 1984 and 1986 despite 50% turnover of species, suggest that the patterns we describe respond to major differences between ecosystem types.
Project description:Familiarity incrementally improves our ability to identify faces. It has been hypothesized that this improvement reflects the refinement of memory representations which incorporate variation in appearance across encounters. Although it is established that exposure to variation improves face identification accuracy, it is not clear how variation is assimilated into internal face representations. To address this, we used a novel approach to isolate the effect of integrating separate exposures into a single-identity representation. Participants (n?=?113) were exposed to either a single video clip or a pair of video clips of target identities. Pairs of video clips were presented as either a single identity (associated with a single name, e.g. Betty-Sue) or dual identities (associated with two names, e.g. Betty and Sue). Results show that participants exposed to pairs of video clips showed better matching performance compared with participants trained with a single clip. More importantly, identification accuracy was higher for faces presented as single identities compared to faces presented as dual identities. This provides the first direct evidence that the integration of information across separate exposures benefits face matching, thereby establishing a mechanism that may explain people's impressive ability to recognize familiar faces.
Project description:Understanding human-object interactions is critical for extracting meaning from everyday visual scenes and requires integrating complex relationships between human pose and object identity into a new percept. To understand how the brain builds these representations, we conducted 2 fMRI experiments in which subjects viewed humans interacting with objects, noninteracting human-object pairs, and isolated humans and objects. A number of visual regions process features of human-object interactions, including object identity information in the lateral occipital complex (LOC) and parahippocampal place area (PPA), and human pose information in the extrastriate body area (EBA) and posterior superior temporal sulcus (pSTS). Representations of human-object interactions in some regions, such as the posterior PPA (retinotopic maps PHC1 and PHC2) are well predicted by a simple linear combination of the response to object and pose information. Other regions, however, especially pSTS, exhibit representations for human-object interaction categories that are not predicted by their individual components, indicating that they encode human-object interactions as more than the sum of their parts. These results reveal the distributed networks underlying the emergent representation of human-object interactions necessary for social perception.
Project description:In interpreting attention-deficit/hyperactivity disorder (ADHD) symptoms, categorical and dimensional approaches are commonly used. Both employ binary symptom counts which give equal weighting, with little attention to the combinations and relative contributions of individual symptoms. Alternatively, symptoms can be viewed as an interacting network, revealing the complex relationship between symptoms. Using a novel network modelling approach, this study explores the relationships between the 18 symptoms in the Diagnostic Statistical Manual (DSM-5) criteria and whether network measures are useful in predicting outcomes. Participants were from a community cohort, the Children's Attention Project. DSM ADHD symptoms were recorded in a face-to-face structured parent interview for 146 medication naïve children with ADHD and 209 controls (aged 6-8 years). Analyses indicated that not all symptoms are equal. Frequencies of endorsement and configurations of symptoms varied, with certain symptoms playing a more important role within the ADHD symptom network. In total, 116,220 combinations of symptoms within a diagnosis of ADHD were identified, with 92% demonstrating a unique symptom configuration. Symptom association networks highlighted the relative importance of hyperactive/impulsive symptoms in the symptom network. In particular, the 'motoric'-type symptoms as well as interrupts as a marker of impulsivity in the hyperactive domain, as well as loses things and does not follow instructions in the inattentive domain, had high measures of centrality. Centrality-measure weighted symptom counts showed significant association with clinical but not cognitive outcomes, however the relationships were not significantly stronger than symptom count alone. The finding may help to explain heterogeneity in the ADHD phenotype.
Project description:Why do faces become easier to recognize with repeated exposure? Previous research has suggested that familiarity may induce a qualitative shift in visual processing from an independent analysis of individual facial features to analysis that includes information about the relationships among features (Farah, Wilson, Drain, & Tanaka Psychological Review, 105, 482-498, 1998; Maurer, Grand, & Mondloch Trends in Cognitive Science, 6, 255-260, 2002). We tested this idea by using a "summation-at-threshold" technique (Gold, Mundy, & Tjan Psychological Science, 23, 427-434, 2012; Nandy & Tjan Journal of Vision, 8, 3.1-20, 2008), in which an observer's ability to recognize each individual facial feature shown independently is used to predict their ability to recognize all of the features shown in combination. We find that, although people are better overall at recognizing familiar as opposed to unfamiliar faces, their ability to integrate information across features is similar for unfamiliar and highly familiar faces and is well predicted by their ability to recognize each of the facial features shown in isolation. These results are consistent with the idea that familiarity has a quantitative effect on the efficiency with which information is extracted from individual features, rather than a qualitative effect on the process by which features are combined.
Project description:To withstand the pressures of a rapidly changing world, resilient ecosystems should exhibit compensatory dynamics, including uncorrelated temporal shifts in population sizes. The observation that diversity is maintained through time in many systems is evidence that communities are indeed regulated and stabilized, yet empirical observations suggest that positive covariance in species abundances is widespread. This paradox could be resolved if communities are composed of a number of ecologically relevant sub-units in which the members compete for resources, but whose abundances fluctuate independently. Such modular organization could explain community regulation, even when the community as a whole appears synchronized. To test this hypothesis, we quantified temporal synchronicity in annual population abundances within spatial guilds in an estuarine fish assemblage that has been monitored for 36 years. We detected independent fluctuations in annual abundances within guilds. By contrast, the assemblage as a whole exhibited temporal synchronicity-an outcome linked to the dynamics of guild dominants, which were synchronized with each other. These findings underline the importance of modularity in explaining community regulation and highlight the need to protect assemblage composition and structure as well as species richness.
Project description:We report converging evidence that higher stages of the visual system are critically required for the whole to become more than the sum of its parts by studying patient DF with visual agnosia using a configural superiority paradigm. We demonstrate a clear dissociation between this patient and normal controls such that she could more easily report information about parts, demonstrating a striking reversal of the normal configural superiority effect. Furthermore, by comparing DF's performance to earlier neuroimaging and novel modeling work, we found a compelling consistency between her performance and representations in the early visual areas, which are spared in this patient. The reversed pattern of performance in this patient highlights that in some cases visual Gestalts do not emerge early on without processing in higher visual areas. More broadly, this study demonstrates how neuropsychological patients can be used to unmask representations maintained at early stages of processing.
Project description:People often perceive configurations rather than the elements they comprise, a bias that may emerge because configurations often predict outcomes. But how does the brain learn to associate configurations with outcomes and how does this learning differ from learning about individual elements? We combined behavior, reinforcement learning models, and functional imaging to understand how people learn to associate configurations of cues with outcomes. We found that configural learning depended on the relative predictive strength of elements versus configurations and was related to both the strength of BOLD activity and patterns of BOLD activity in the hippocampus. Configural learning was further related to functional connectivity between the hippocampus and nucleus accumbens. Moreover, configural learning was associated with flexible knowledge about associations and differential eye movements during choice. Together, this suggests that configural learning is associated with a distinct computational, cognitive, and neural profile that is well suited to support flexible and adaptive behavior.
Project description:BACKGROUND:For diagnostic purposes, the nine symptoms that compose the DSM-5 criteria for major depressive disorder (MDD) are assumed to be interchangeable indicators of one underlying disorder, implying that they should all have similar risk factors. The present study investigates this hypothesis, using a population cohort that shifts from low to elevated depression levels. METHOD:We assessed the nine DSM-5 MDD criterion symptoms (using the Patient Health Questionnaire; PHQ-9) and seven depression risk factors (personal and family MDD history, sex, childhood stress, neuroticism, work hours, and stressful life events) in a longitudinal study of medical interns prior to and throughout internship (n = 1289). We tested whether risk factors varied across symptoms, and whether a latent disease model could account for heterogeneity between symptoms. RESULTS:All MDD symptoms increased significantly during residency training. Four risk factors predicted increases in unique subsets of PHQ-9 symptoms over time (depression history, childhood stress, sex, and stressful life events), whereas neuroticism and work hours predicted increases in all symptoms, albeit to varying magnitudes. MDD family history did not predict increases in any symptom. The strong heterogeneity of associations persisted after controlling for a latent depression factor. CONCLUSIONS:The influence of risk factors varies substantially across DSM depression criterion symptoms. As symptoms are etiologically heterogeneous, considering individual symptoms in addition to depression diagnosis might offer important insights obfuscated by symptom sum scores.