Neural correlates of knowledge: stable representation of stimulus associations across variations in behavioral performance

Behavioral responses to a sensory stimulus are often guided by associative memories. These associations remain intact even when other factors determine behavior. The substrates of associative memory should therefore be identifiable by neuronal responses that are independent of behavioral choices. We tested this hypothesis using a paired-associates task in which monkeys learned arbitrary associations between pairs of visual stimuli. We examined the activity of neurons in inferior temporal cortex as the animals prepared to choose a remembered stimulus from a visual display. The activity of some neurons (22%) depended on the monkey's behavioral choice; but for a novel class of neurons (54%), activity reflected the stimulus that the monkey was instructed to choose, regardless of the behavioral response. These neurons appear to represent memorized stimulus associations that are stable across variations in behavioral performance. In addition, many neurons (74%) were modulated by the spatial arrangement of the stimuli in the display.     

Evaluation of natural enemies for biological control: A behavioral approach

The success of biological pest control has stimulated the development of analytical models that explore the dynamics of natural enemies and their hosts or prey. These models seek to identify those general characteristics o f the natural enemy, host or prey population that lead to economic pest control. Because the models are strategic in nature, they are of limited value in identifying the specific attributes of an effective biological control agent prior to its introduction. Empirically developed criteria have also been of limited predictive value because they too provide only general guidelines. Behavioral ecology and foraging and sexratio theories may be useful adjuncts to these approaches, by identifying the evolutionary constraints and thus helping to define better the attributes of an effective natural enemy.     

Effects of STN and GPi deep brain stimulation on impulse control disorders and dopamine dysregulation syndrome

Objective

Impulse control disorders (ICDs) and dopamine dysregulation syndrome (DDS) are important behavioral problems that affect a subpopulation of patients with Parkinson''s disease (PD) and typically result in markedly diminished quality of life for patients and their caregivers. We aimed to investigate the effects of subthalamic nucleus (STN) and internal globus pallidus (GPi) deep brain stimulation (DBS) on ICD/DDS frequency and dopaminergic medication usage.

Methods

A retrospective chart review was performed on 159 individuals who underwent unilateral or bilateral PD DBS surgery in either STN or GPi. According to published criteria, pre- and post-operative records were reviewed to categorize patients both pre- and post-operatively as having ICD, DDS, both ICD and DDS, or neither ICD nor DDS. Group differences in patient demographics, clinical presentations, levodopa equivalent dose (LED), and change in diagnosis following unilateral/bilateral by brain target (STN or GPi DBS placement) were examined.

Results

28 patients met diagnostic criteria for ICD or DDS pre- or post-operatively. ICD or DDS classification did not differ by GPi or STN target stimulation. There was no change in DDS diagnosis after unilateral or bilateral stimulation. For ICD, diagnosis resolved in 2 of 7 individuals after unilateral or bilateral DBS. Post-operative development of these syndromes was significant; 17 patients developed ICD diagnoses post-operatively with 2 patients with pre-operative ICD developing DDS post-operatively.

Conclusions

Unilateral or bilateral DBS did not significantly treat DDS or ICD in our sample, even though a few cases of ICD resolved post-operatively. Rather, our study provides preliminary evidence that DDS and ICD diagnoses may emerge following DBS surgery.     

Bright light exposure augments cognitive behavioral therapy for panic and posttraumatic stress disorders: a pilot randomized control trial

Sleep and Biological Rhythms - Bright light (BL) therapy is clinically utilized for treatment of sleep–wake disorders through the manipulation of circadian oscillation. It is also extended to...     

Stereotactic amygdalotomy for convulsive and behavioral disorders. Long-term follow-up study.

58 patients, whose convulsions and behavioral disorders did not respond to nonsurgical therapy, were treated with stereotactic amygdalotomy between 1963 and 1973. A retrospective study was carried out by a psychiatric research team 1--11 years postoperatively. Using reliable objective methods of assessment they found that 50% operated primarily for seizures, 33% for uncontrolled conduct disorders and 50% with both conditions seemed improved after surgery.     

Thalamic stimulation for control of movement disorders

Chronic recurrent thalamic stimulation has been effective in alleviating a variety of movement disorders. In contrast to thalamic lesions, it is preferred for the treatment of intractable motor disorders in low-risk elderly patients and patients with diffuse brain lesions secondary to trauma. Abnormal diencephalic electrical discharges have been observed and thought to be associated, in some way, with either generating or sustaining the movement abnormalities. The beneficial effects are ascribed to an electrophysiologic functional ablation of the discharging systems. This interpretation is based on the observation that the diencephalic discharges are attenuated by the applied stimulation and that the beneficial effects are reversible even after several months of applied therapeutic stimulation.     

A scalable approach for discovering conserved active subnetworks across species

Overlaying differential changes in gene expression on protein interaction networks has proven to be a useful approach to interpreting the cell's dynamic response to a changing environment. Despite successes in finding active subnetworks in the context of a single species, the idea of overlaying lists of differentially expressed genes on networks has not yet been extended to support the analysis of multiple species' interaction networks. To address this problem, we designed a scalable, cross-species network search algorithm, neXus (Network-cross(X)-species-Search), that discovers conserved, active subnetworks based on parallel differential expression studies in multiple species. Our approach leverages functional linkage networks, which provide more comprehensive coverage of functional relationships than physical interaction networks by combining heterogeneous types of genomic data. We applied our cross-species approach to identify conserved modules that are differentially active in stem cells relative to differentiated cells based on parallel gene expression studies and functional linkage networks from mouse and human. We find hundreds of conserved active subnetworks enriched for stem cell-associated functions such as cell cycle, DNA repair, and chromatin modification processes. Using a variation of this approach, we also find a number of species-specific networks, which likely reflect mechanisms of stem cell function that have diverged between mouse and human. We assess the statistical significance of the subnetworks by comparing them with subnetworks discovered on random permutations of the differential expression data. We also describe several case examples that illustrate the utility of comparative analysis of active subnetworks.     

Linkage disequilibrium pattern and age-at-diagnosis are critical for replicating genetic associations across ethnic groups in leprosy

One of the persistent challenges of genetic association studies is the replication of genetic marker-disease associations across ethnic groups. Here, we conducted high-density association mapping of PARK2/PACRG SNPs with leprosy and identified 69 SNPs significantly associated with leprosy in 198 single-case Vietnamese leprosy families. A total of 56 associated SNPs localized to the overlapping promoter regions of PARK2/PACRG. For this region, multivariate analysis identified four SNPs belonging to two major SNP bins (rs1333955, rs7744433) and two single SNP bins (rs2023004, rs6936895) that capture the combined statistical evidence (P = 1.1 × 10^?5) for association among Vietnamese patients. Next, we enrolled a case–control sample of 364 leprosy cases and 370 controls from Northern India. We genotyped all subjects for 149 SNPs that capture >80 % of the genetic variation in the Vietnamese sample and found 24 SNPs significantly associated with leprosy. Multivariate analysis identified three SNPs (rs1333955, rs9356058 and rs2023004) that capture the association with leprosy (P < 10^?8). Hence, two SNPs (rs1333955 and rs2023004) were replicated by multivariate analysis between both ethnic groups. Marked differences in the linkage disequilibrium pattern explained some of the differences in univariate analysis between the two ethnic groups. In addition, the strength of association for two promoter region SNP bins was significantly stronger among young leprosy patients in the Vietnamese sample. The same trend was observed in the Indian sample, but due to the higher age-at-diagnosis of the patients the age effect was less pronounced.     

Multi-scale approach for predicting fish species distributions across coral reef seascapes

Two of the major limitations to effective management of coral reef ecosystems are a lack of information on the spatial distribution of marine species and a paucity of data on the interacting environmental variables that drive distributional patterns. Advances in marine remote sensing, together with the novel integration of landscape ecology and advanced niche modelling techniques provide an unprecedented opportunity to reliably model and map marine species distributions across many kilometres of coral reef ecosystems. We developed a multi-scale approach using three-dimensional seafloor morphology and across-shelf location to predict spatial distributions for five common Caribbean fish species. Seascape topography was quantified from high resolution bathymetry at five spatial scales (5–300 m radii) surrounding fish survey sites. Model performance and map accuracy was assessed for two high performing machine-learning algorithms: Boosted Regression Trees (BRT) and Maximum Entropy Species Distribution Modelling (MaxEnt). The three most important predictors were geographical location across the shelf, followed by a measure of topographic complexity. Predictor contribution differed among species, yet rarely changed across spatial scales. BRT provided ‘outstanding’ model predictions (AUC = >0.9) for three of five fish species. MaxEnt provided ‘outstanding’ model predictions for two of five species, with the remaining three models considered ‘excellent’ (AUC = 0.8–0.9). In contrast, MaxEnt spatial predictions were markedly more accurate (92% map accuracy) than BRT (68% map accuracy). We demonstrate that reliable spatial predictions for a range of key fish species can be achieved by modelling the interaction between the geographical location across the shelf and the topographic heterogeneity of seafloor structure. This multi-scale, analytic approach is an important new cost-effective tool to accurately delineate essential fish habitat and support conservation prioritization in marine protected area design, zoning in marine spatial planning, and ecosystem-based fisheries management.     

A genetics‐based approach confirms immune associations with life history across multiple populations of an aquatic vertebrate (Gasterosteus aculeatus)

Understanding how wild immune variation covaries with other traits can reveal how costs and trade‐offs shape immune evolution in the wild. Divergent life history strategies may increase or alleviate immune costs, helping shape immune variation in a consistent, testable way. Contrasting hypotheses suggest that shorter life histories may alleviate costs by offsetting them against increased mortality, or increase the effect of costs if immune responses are traded off against development or reproduction. We investigated the evolutionary relationship between life history and immune responses within an island radiation of three‐spined stickleback, with discrete populations of varying life histories and parasitism. We sampled two short‐lived, two long‐lived and an anadromous population using qPCR to quantify current immune profile and RAD‐seq data to study the distribution of immune variants within our assay genes and across the genome. Short‐lived populations exhibited significantly increased expression of all assay genes, which was accompanied by a strong association with population‐level variation in local alleles and divergence in a gene that may be involved in complement pathways. In addition, divergence around the eda gene in anadromous fish is likely associated with increased inflammation. A wider analysis of 15 populations across the island revealed that immune genes across the genome show evidence of having diverged alongside life history strategies. Parasitism and reproductive investment were also important sources of variation for expression, highlighting the caution required when assaying immune responses in the wild. These results provide strong, gene‐based support for current hypotheses linking life history and immune variation across multiple populations of a vertebrate model.     

A network approach for inferring species associations from co‐occurrence data

Positive and negative associations between species are a key outcome of community assembly from regional species pools. These associations are difficult to detect and can be caused by a range of processes such as species interactions, local environmental constraints and dispersal. We integrate new ideas around species distribution modeling, covariance matrix estimation, and network analysis to provide an approach to inferring non‐random species associations from local‐ and regional‐scale occurrence data. Specifically, we provide a novel framework for identifying species associations that overcomes three challenges: 1) correcting for indirect effects from other species, 2) avoiding spurious associations driven by regional‐scale distributions, and 3) describing these associations in a multi‐species context. We highlight a range of research questions and analyses that this framework is able to address. We show that the approach is statistically robust using simulated data. In addition, we present an empirical analysis of > 1000 North American tree communities that gives evidence for weak positive associations among small groups of species. Finally, we discuss several possible extensions for identifying drivers of associations, predicting community assembly, and better linking biogeography and community ecology.     

Evidence for facilitation among avian army‐ant attendants: specialization and species associations across elevations

Mixed‐species assemblages can involve positive and negative interactions, but uncertainty about high‐value patchy resources can increase the value of information sharing among heterospecific co‐foragers. I sampled species composition of bird‐flocks attending army‐ant raids in three adjacent elevation zones in Costa Rica, across multiple years, to test for positive and negative associations among raid‐attending bird species. My goal was to test whether the most frequent and specialized raid‐attending species showed evidence of facilitating or excluding other bird species. I quantified elevational variation in avian community composition at raids, then asked whether species composition was associated with variation in flock characteristics (flock size and species richness). I identified the most frequent raid‐attending species (those that attended raids most frequently relative to their mist‐net capture rates), and bird species that performed specialized army ant‐following behavior (bivouac‐checking, which allows birds to memorize and track mobile army‐ant colonies). There was significant turnover of bird species among zones (including the frequent and specialized attendants); patterns of species overlap suggested a gradual transition from a Pacific‐slope to an Atlantic‐slope raid‐attending bird fauna. Raid‐attendance frequency was positively correlated with bivouac‐checking behavior. With few exceptions, the most frequent raid‐attending bird species, and the bivouac‐checking species, also participated in the most species‐rich flocks. High species‐gregariousness suggests many of the frequently attending and/or bivouac‐checking species functioned as core flock members. However, some bird species pairs were significantly negatively associated at raids. Despite species turnover, per‐flock numbers of birds at raids did not differ among geographic zones, but flocks on the Pacific‐slope were heavier because larger bodied bird species attended raids. Previous studies showed that the size (biomass) of bird‐flocks corresponds to the amount of food the birds kleptoparasitize from ant raids, and the heavier Pacific‐slope bird‐flocks could have greater negative kleptoparasitic impacts.     

Testing for personality consistency across naturally occurring behavioral contexts in sanctuary chimpanzees (Pan troglodytes)

Personality is both a reflection of the bio-behavioral profile of individuals and a summary of how they typically interact with their physical and social world. Personality is usually defined as having distinct behavioral characteristics, which are assumed to be consistent over time and across contexts. Like other mammals, primates have individual differences in personality. Although temporal consistency is sometimes measured in primates, and contextual consistency is sometimes measured across experimental contexts, it is rare to measure both in the same individuals and outside of experimental settings. Here, we aim to measure both temporal and contextual consistency in chimpanzees, assessing their personality with behavioral observations from naturally occurring contexts (i.e., real-life settings). We measured personality-based behaviors in 22 sanctuary chimpanzees, in the contexts of feeding, affiliation, resting, and solitude, across two time periods, spanning 4 years. Of the 22 behaviors recorded, about 64% were consistent across two to four contexts and 50% were consistent over time. Ten behaviors loaded significantly onto three trait components: explorativeness, boldness-sociability, and anxiety-sociability, as revealed by factor analysis. Like others, we documented individual differences in the personality of chimpanzees based on reliably measured observations in real-life contexts. Furthermore, we demonstrated relatively strong, but not absolute, temporal, and contextual consistency in personality-based behaviors. We also found another aspect of individual differences in personality, specifically, the extent to which individual chimpanzees show consistency. Some individuals showed contextual and temporal consistency, whereas others show significant variation across behaviors, contexts, and/or time. We speculate that the relative degree of consistency in personality may vary within chimpanzees. It may be that different primate species vary in the extent to which individuals show consistency of personality traits. Our behavioral-based assessment can be used with wild populations, increasing the validity of personality studies, facilitating comparative studies and potentially being applicable to conservation efforts.     

Variable complementary network: a novel approach for identifying biomarkers and their mutual associations

Biological variables involved in a disease process often correlate with each other through for example shared metabolic pathways. In addition to their correlation, these variables contain complementary information that is particularly useful for disease classification and prediction. However, complementary information between variables is rarely explored. Therefore, establishing methods for the investigation of variable??s complementary information is very necessary. We propose a model population analysis approach that aggregates information of a number of classification models obtained with the help of Monte Carlo sampling in variable space for quantitatively calculating the complementary information between variables. We then assemble these complementary information to construct a variable complementary network (VCN) to give an overall visualization of how biological variables complement each other. Using a simulated dataset and two metabolomics datasets, we show that the complementary information is effective in biomarker discovery and that mutual associations of metabolites revealed by this method can provide information for exploring altered metabolic pathways. (The source codes for implementing VCN in MATLAB are freely available at: http://code.google.com/p/vcn2011/.)     

Habitat associations of an insular Wallacean avifauna: A multi-scale approach for biodiversity proxies

The endemic avifauna of Wallacea is of high conservation significance, but remains poorly studied. Identifying priority conservation areas requires a greater understanding of the habitat associations of these bird communities, and of how spatial scale of analysis can influence the interpretation of these associations. This study aims to determine which proxy habitat measures, at which spatial scales of analysis, can provide useful inferential data on the composition of Wallacean forest avifauna. Research was conducted within the Lambusango forest reserve, South-East Sulawesi, using point count surveys to sample avifauna. Habitat properties were characterised in three ways: broad classification of forest type, canopy remotely-sensed response derived from satellite imagery, and in situ measures of vegetation composition and structure. Furthermore, we examined avifauna–habitat relationships at three spatial scales: area (c.400 ha per sample site), transect (c.10 ha) and point (c.0.2 ha). Results demonstrate that broad forest type classifications at an area scale can help to determine conservation value, indicating that primary and old secondary forests are important for supporting many species with lower ecological tolerances, such as large-bodied frugivores. At the transect-scale, significant congruence occurs between bird community composition and several habitat variables derived from vegetation sampling and satellite imagery, particularly tree size, undergrowth density, and Normalised Difference Vegetation Index (NDVI) values; this highlights the importance small scale habitat associations can have on determining α-diversity. Analysis at the point-scale was ineffective in providing proxy indications for avifauna. These findings should be considered when determining future priority conservation areas for Wallacean avifauna.