Individual Subject Analyses Research Articles

Forensic classification of crimes and misdemeanours related to unlawful encroachments on the assets of business entities

The article substantiates the thesis that criminal offences aimed at unlawful alienation of tangible and intangible assets of a business entity or otherwise related thereto are quite numerous and are enshrined in various sections of the Special Part of the Criminal Code of Ukraine. It is noted that this makes it difficult for the prosecution to recognise these criminal offences during the pre-trial investigation. It is determined that the cognitive activity of an investigator is impossible without a systematic analysis of individual objects and subjects which may be of investigative interest, and therefore, it necessitates the division of the relevant objects into groups. The analogy is drawn and it is determined that such approaches are implemented both in practical law enforcement activities and in scientific activities, in particular, in terms of identifying and developing tested recommendations for investigating criminal offences. It is emphasized that it is the forensic classification of criminal offences which is the method of forensic cognition of crimes and criminal offences which aims at solving a number of other tasks and is therefore necessary to be applied. Based on the results of the scientific research, the study develops a forensic classification of criminal offences related to misappropriation of assets of business entities. It is based on the following classification criteria: 1) peculiarities of the direct object of the encroachment; 2) subject matter of the criminal encroachment; 3) type of economic activity which was subject to criminal influence; 4) nature and form of external expression of traces of criminal activity; 5) nature of the criminal result obtained; 6) peculiarities of the subject composition involved in the implementation of the criminal intent; 7) nature of the actions committed by the raiders. Prospects for future research are identified.

The molecular landscape of sepsis severity in infants: enhanced coagulation, innate immunity, and T cell repression.

Sepsis remains a major cause of mortality and morbidity in infants. In recent years, several gene marker strategies for the early identification of sepsis have been proposed but only a few have been independently validated for adult cohorts and applicability to infant sepsis remains unclear. Biomarkers to assess disease severity and risks of shock also represent an important unmet need. To elucidate characteristics driving sepsis in infants, we assembled a multi-transcriptomic dataset from public microarray datasets originating from five independent studies pertaining to bacterial sepsis in infant < 6-months of age (total n=335). We utilized a COmbat co-normalization strategy to enable comparative evaluation across multiple studies while preserving the relationship between cases and controls. We found good concordance with only two out of seven of the published adult sepsis gene signatures (accuracy > 80%), highlighting the narrow utility of adult-derived signatures for infant diagnosis. Pseudotime analysis of individual subjects' gene expression profiles showed a continuum of molecular changes forming tight clusters concurrent with disease progression between healthy controls and septic shock cases. In depth gene expression analyses between bacteremia, septic shock, and healthy controls characterized lymphocyte activity, hemostatic processes, and heightened innate immunity during the molecular transition toward a state of shock. Our analysis revealed the presence of multiple significant transcriptomic perturbations that occur during the progression to septic shock in infants that are characterized by late-stage induction of clotting factors, in parallel with a heightened innate immune response and a suppression of adaptive cell functionality.

Scene Perception and Visuospatial Memory Converge at the Anterior Edge of Visually Responsive Cortex.

To fluidly engage with the world, our brains must simultaneously represent both the scene in front of us and our memory of the immediate surrounding environment (i.e., local visuospatial context). How does the brain's functional architecture enable sensory and mnemonic representations to closely interface while also avoiding sensory-mnemonic interference? Here, we asked this question using first-person, head-mounted virtual reality and fMRI. Using virtual reality, human participants of both sexes learned a set of immersive, real-world visuospatial environments in which we systematically manipulated the extent of visuospatial context associated with a scene image in memory across three learning conditions, spanning from a single FOV to a city street. We used individualized, within-subject fMRI to determine which brain areas support memory of the visuospatial context associated with a scene during recall (Experiment 1) and recognition (Experiment 2). Across the whole brain, activity in three patches of cortex was modulated by the amount of known visuospatial context, each located immediately anterior to one of the three scene perception areas of high-level visual cortex. Individual subject analyses revealed that these anterior patches corresponded to three functionally defined place memory areas, which selectively respond when visually recalling personally familiar places. In addition to showing activity levels that were modulated by the amount of visuospatial context, multivariate analyses showed that these anterior areas represented the identity of the specific environment being recalled. Together, these results suggest a convergence zone for scene perception and memory of the local visuospatial context at the anterior edge of high-level visual cortex.SIGNIFICANCE STATEMENT As we move through the world, the visual scene around us is integrated with our memory of the wider visuospatial context. Here, we sought to understand how the functional architecture of the brain enables coexisting representations of the current visual scene and memory of the surrounding environment. Using a combination of immersive virtual reality and fMRI, we show that memory of visuospatial context outside the current FOV is represented in a distinct set of brain areas immediately anterior and adjacent to the perceptually oriented scene-selective areas of high-level visual cortex. This functional architecture would allow efficient interaction between immediately adjacent mnemonic and perceptual areas while also minimizing interference between mnemonic and perceptual representations.

A265 TEMPORAL DYNAMICS OF SYMPTOMS AND GUT MICROBIOTA IN EPISODES OF IRRITABLE BOWEL SYNDROME

Abstract Background Irritable bowel syndrome (IBS) is a disorder of gut-brain axis that manifests with chronic abdominal pain, altered bowel habits, and frequent psychiatric comorbidities. Despite mounting evidence showing gut microbiota composition and associated metabolites being altered in IBS, the mechanisms by which they drive the symptoms are unclear. We have previously shown that several IBS symptoms co-occur, that their severity vary among IBS subtypes (10.1093/jcag/gwab049.050), and that several bacterial taxa are differentially modulated during periods of symptom flares and remission. Here we investigate whether the changes in gut microbiome and bacterial metabolites are linked to symptom occurrence and severity. Purpose To investigate temporal associations of IBS symptoms with gut microbiota profiles and metabolites. Method 16S rRNA gene sequencing was performed on stool samples of 28 IBS patients (IBS-D n=20, IBS-C n=8) and 10 healthy controls (HC), collected weekly over a period of 25 weeks, during which gut and mood symptoms were recorded (total of 950 samples). Correlations between principal ordinates obtained from symptom scores and microbiota beta diversity were studied using Procrustes analysis in R. Metabolomics was performed by Mass Spectrometry and analysed using MetaboAnalyst 5.0. Statistical significance was set at p&amp;lt;0.05. Result(s) Significant correlation was found between the symptom scores and microbiota beta diversity ordinates over time in 7 patients (5 IBS-D and 2 IBS-C subjects) out of 28 IBS patients. Metabolomics performed on samples selected based on Procrustes analysis and symptom severity scores of individual subjects showed that several pathways are altered in IBS patients (both subtypes) compared to HC, including primary bile acid biosynthesis, beta alanine metabolism, pyrimidine and histidine metabolism. Furthermore, during symptom flares, ornithine, citrulline and gluconic acid vary in IBS-D, while amino acids cysteine, methionine, threonine, and glycine vary in IBS-C subjects. Conclusion(s) Our results suggest that IBS symptoms and changes in gut microbiota composition and metabolites must be studied in conjunction, in order to understand the mechanisms underlying IBS pathophysiology. We found that same pathways are altered in IBS subjects irrespective of their subtype, suggestive of a basal metabolic shift in IBS patients. This shift may make them sensitive to further gut microbial modulation of carbohydrate and protein metabolism in IBS-D and IBS-C subjects, respectively, leading to symptom flares. Further analyses are needed to investigate these metabolites and associated bacteria, as they can help identifying subsets of patients with specific disease mechanisms. This will be a steppingstone in moving away from symptom-based subtyping towards mechanism-based grouping and developing effective treatment strategies accordingly. Disclosure of Interest None Declared

How robustly do multivariate EEG patterns track individual-subject lexico-semantic processing of visual stimuli?

ABSTRACT Electroencephalography may be a valuable tool for assessing lexico-semantic processing in conditions where behavioural measures are unreliable. Detecting and quantifying effects in individuals is crucial for clinical applications, but individual-subject analyses are frequently not reported, and are hampered by low signal-to-noise. Multivariate analyses (MVPA) may be more sensitive than traditional approaches, so we asked how robustly they could detect differential neural responses to semantically matched and mismatched word/picture pairs in individuals. With clinical application in mind, we compared data from a research-grade EEG system to concurrently recorded data from the wireless Emotiv EPOC + . In both EEG systems, despite robust group-level effects, we only detected statistically significant processing of lexico-semantic condition in 50% of individuals. Surprisingly, detection rates were similar for MVPA and univariate analyses. MVPA may be advantageous when individual responses are heterogeneous, but in this simple paradigm, lexico-semantic processing could not be reliably detected at the individual level.

Precision fMRI reveals that the language-selective network supports both phrase-structure building and lexical access during language production.

A fronto-temporal brain network has long been implicated in language comprehension. However, this network's role in language production remains debated. In particular, it remains unclear whether all or only some language regions contribute to production, and which aspects of production these regions support. Across 3 functional magnetic resonance imaging experiments that rely on robust individual-subject analyses, we characterize the language network's response to high-level production demands. We report 3 novel results. First, sentence production, spoken or typed, elicits a strong response throughout the language network. Second, the language network responds to both phrase-structure building and lexical access demands, although the response to phrase-structure building is stronger and more spatially extensive, present in every language region. Finally, contra some proposals, we find no evidence of brain regions-within or outside the language network-that selectively support phrase-structure building in production relative to comprehension. Instead, all language regions respond more strongly during production than comprehension, suggesting that production incurs a greater cost for the language network. Together, these results align with the idea that language comprehension and production draw on the same knowledge representations, which are stored in a distributed manner within the language-selective network and are used to both interpret and generate linguistic utterances.

Abstract TMP106: Pooled Analysis Of Five Randomized Trials Comparing Device Closure Of Patent Foramen Ovale After Stroke To Medical Treatment: Impact Of Residual Shunt On Stroke Outcomes

Introduction: Patent foramen ovale (PFO) closure is effective for secondary stroke prevention in well selected patients. After device implantation some patients have residual shunting. There was no impact of incomplete closure on recurrent stroke risk in any of the trials but outcome rates are low with little power to detect an effect. Hypothesis: Patients with residual shunts after PFO closure have more recurrent strokes than those with complete elimination of shunting. Methods: We pooled individual patient data from 5 of 6 randomized clinical trials comparing medical therapy to PFO closure + medical therapy. Residual shunt data were not available for 1 trial. This analysis only includes PFO closure subjects. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated with Cox proportional hazards regression, adjusted for age, sex, coronary disease, diabetes, hypertension, hyperlipidemia, prior stroke/TIA, smoking, index event (stroke vs TIA), hypermobile septum, shunt size (large vs small) and infarct location (superficial vs deep). Multiple imputation of missing values for adjusted variables was used. Results: Among 1475 patients treated with PFO closure and with non-missing residual shunt data, 149 (10%) had incomplete closure. The median time from procedure to shunt measurement was 204 days (25 th -75 th percentile, 181-722). In the complete closure group the primary endpoint of recurrent ischemic stroke occurred in 30 patients (2.3%; 95% CI 1.5-3.2%) compared to 4 (2.7%; 95% CI 0.7-6.7%) with incomplete closure. Unadjusted and adjusted HRs comparing incomplete vs complete closure were 1.37 (0.48, 3.92) and 1.69 (0.37, 4.95) respectively. The secondary endpoint of recurrent ischemic stroke, TIA, or vascular death occurred in 66 (5.0%; 95% CI 3.9-6.3%) patients with complete closure compared to 9 (6.0%; 95% CI 2.8-11.2%) without. Unadjusted and adjusted HRs were 1.26 (0.63, 2.54) and 1.39 (0.68, 2.83) respectively. Conclusions: Our pooled analysis of individual subjects after PFO closure from 5 of 6 relevant randomized clinical trials, showed no association between residual shunt and recurrent stroke events. This analysis was limited by low rates of residual shunt and recurrent events even in this large, combined dataset.

Isolation and Proteomic Analysis of Mouse Serum Small Extracellular Vesicles for Individual Subject Analysis.

Proteomics characterization of blood and circulating material has been extensively explored for the study of pathological states. In particular, circulating small extracellular vesicles (sEV, diameter: 30-150nm) are known to play an important role in intercellular communication processes, and proteomics profiling has been explored to develop minimally invasive assays for disease monitoring and diagnosis. Due to the genetic and physiological similarities between the two species, and also on account of their shorter life span and rapid disease progression, rodent models are the most commonly used animal model for many human diseases. Such models have provided invaluable insight into the molecular mechanisms of disease progression, candidate drug efficacy, therapy monitoring, and biomarkers research.Longitudinal investigations, in which individuals are monitored over periods of time, are more able to resolve molecular changes during disease progression because they circumvent the inter-individual variation. Longitudinal investigations of rodent models are challenging because of the limited amount of blood that can be withdrawn at each time; the American Association of Veterinary Science stipulates that fortnightly sampling should be limited to a maximum of 10% of the total blood volume. For adult mice this corresponds to approximately 75μL of serum. We developed an approach for the isolation and characterization of serum sEV proteins from just 50μL of serum, for longitudinal studies of disease mouse models. This chapter describes in detail the steps and considerations involved in the sEV isolation, morphological characterization, and proteome profiling by mass spectrometry.

The Virtual City ParadigmTM for Testing Visuo-Spatial Memory, Executive Functions and Cognitive Strategies in Children With ADHD: A Feasibility Study.

Navigation is a complex process, requiring target localization, route planning or retrieval, and physical displacement. Executive functions (EFs) such as working memory, inhibition and planning are fundamental for succeeding in this complex activity and are often impaired in Attention Deficit and Hyperactivity Disorder (ADHD). Our aim was to analyze the feasibility of a new ecological navigation task, the Virtual City paradigm™ (VC™) to test visuo-spatial memory and EFs in children with ADHD. Visuo-spatial short and working memory, inhibition and planning skills were tested with standardized tasks. The VC™, a new paradigm developed by our group, used the Virtual CarpetTM technology, consisting of a virtual town with houses, streets and crossroads projected on the ground. It includes a motion capture system, tracking body movement in 3D in real time. In one condition, children were required to walk through the city and reach a sequence of houses. In the other, before walking, they had to plan the shortest path to reach the houses, inhibiting the prepotent response to start walking. The results show a good feasibility of the paradigm (feasibility checklist and ad hoc questionnaire), being ecological and motivating. VC™ measures of span positively correlated with visuo-spatial short and working memory measures, suggesting that VC™ heavily relies on efficient spatial memory. Individual subject analyses suggested that children with ADHD may approach this task differently from typically developing children. Larger samples of ADHD and healthy children may further explore the specific role of EFs and memory, potentially opening new avenues for intervention.

Unconstrained multivariate EEG decoding can help detect lexical-semantic processing in individual children

In conditions such as minimally-verbal autism, standard assessments of language comprehension are often unreliable. Given the known heterogeneity within the autistic population, it is crucial to design tests of semantic comprehension that are sensitive in individuals. Recent efforts to develop neural signals of language comprehension have focused on the N400, a robust marker of lexical-semantic violation at the group level. However, homogeneity of response in individual neurotypical children has not been established. Here, we presented 20 neurotypical children with congruent and incongruent visual animations and spoken sentences while measuring their neural response using electroencephalography (EEG). Despite robust group-level responses, we found high inter-individual variability in response to lexico-semantic anomalies. To overcome this, we analysed our data using temporally and spatially unconstrained multivariate pattern analyses (MVPA), supplemented by descriptive analyses to examine the timecourse, topography, and strength of the effect. Our results show that neurotypical children exhibit heterogenous responses to lexical-semantic violation, implying that any application to heterogenous disorders such as autism spectrum disorder will require individual-subject analyses that are robust to variation in topology and timecourse of neural responses.

Detecting change in stochastic sound sequences.

Our ability to parse our acoustic environment relies on the brain’s capacity to extract statistical regularities from surrounding sounds. Previous work in regularity extraction has predominantly focused on the brain’s sensitivity to predictable patterns in sound sequences. However, natural sound environments are rarely completely predictable, often containing some level of randomness, yet the brain is able to effectively interpret its surroundings by extracting useful information from stochastic sounds. It has been previously shown that the brain is sensitive to the marginal lower-order statistics of sound sequences (i.e., mean and variance). In this work, we investigate the brain’s sensitivity to higher-order statistics describing temporal dependencies between sound events through a series of change detection experiments, where listeners are asked to detect changes in randomness in the pitch of tone sequences. Behavioral data indicate listeners collect statistical estimates to process incoming sounds, and a perceptual model based on Bayesian inference shows a capacity in the brain to track higher-order statistics. Further analysis of individual subjects’ behavior indicates an important role of perceptual constraints in listeners’ ability to track these sensory statistics with high fidelity. In addition, the inference model facilitates analysis of neural electroencephalography (EEG) responses, anchoring the analysis relative to the statistics of each stochastic stimulus. This reveals both a deviance response and a change-related disruption in phase of the stimulus-locked response that follow the higher-order statistics. These results shed light on the brain’s ability to process stochastic sound sequences.

Factors influencing accuracy of cortical thickness in the diagnosis of Alzheimer's disease.

There is great value to use of structural neuroimaging in the assessment of Alzheimer's disease (AD). However, to date, predictive value of structural imaging tend to range between 80% and 90% in accuracy and it is unclear why this is the case given that structural imaging should parallel the pathologic processes of AD. There is a possibility that clinical misdiagnosis relative to the gold standard pathologic diagnosis and/or additional brain pathologies are confounding factors contributing to reduced structural imaging classification accuracy. We examined potential factors contributing to misclassification of individuals with clinically diagnosed AD purely from cortical thickness measures. Correctly classified and incorrectly classified groups were compared across a range of demographic, biological, and neuropsychological data including cerebrospinal fluid biomarkers, amyloid imaging, white matter hyperintensity (WMH) volume, cognitive, and genetic factors. Individual subject analyses suggested that at least a portion of the control individuals misclassified as AD from structural imaging additionally harbor substantial AD biomarker pathology and risk, yet are relatively resistant to cognitive symptoms, likely due to "cognitive reserve," and therefore clinically unimpaired. In contrast, certain clinical control individuals misclassified as AD from cortical thickness had increased WMH volume relative to other controls in the sample, suggesting that vascular conditions may contribute to classification accuracy from cortical thickness measures. These results provide examples of factors that contribute to the accuracy of structural imaging in predicting a clinical diagnosis of AD, and provide important information about considerations for future work aimed at optimizing structural based diagnostic classifiers for AD.

Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms II: A Method to Obtain First-Level Analysis Residuals with Uniform and Gaussian Spatial Autocorrelation Function and Independent and Identically Distributed Time-Series.

In a recent study Eklund et al. have shown that cluster-wise family-wise error (FWE) rate-corrected inferences made in parametric statistical method-based functional magnetic resonance imaging (fMRI) studies over the past couple of decades may have been invalid, particularly for cluster defining thresholds less stringent than p < 0.001; principally because the spatial autocorrelation functions (sACFs) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggest otherwise. Hence, the residuals from general linear model (GLM)-based fMRI activation estimates in these studies may not have possessed a homogenously Gaussian sACF. Here we propose a method based on the assumption that heterogeneity and non-Gaussianity of the sACF of the first-level GLM analysis residuals, as well as temporal autocorrelations in the first-level voxel residual time-series, are caused by unmodeled MRI signal from neuronal and physiological processes as well as motion and other artifacts, which can be approximated by appropriate decompositions of the first-level residuals with principal component analysis (PCA), and removed. We show that application of this method yields GLM residuals with significantly reduced spatial correlation, nearly Gaussian sACF and uniform spatial smoothness across the brain, thereby allowing valid cluster-based FWE-corrected inferences based on assumption of Gaussian spatial noise. We further show that application of this method renders the voxel time-series of first-level GLM residuals independent, and identically distributed across time (which is a necessary condition for appropriate voxel-level GLM inference), without having to fit ad hoc stochastic colored noise models. Furthermore, the detection power of individual subject brain activation analysis is enhanced. This method will be especially useful for case studies, which rely on first-level GLM analysis inferences.

Deconstructing atypical eye gaze perception in autism spectrum disorder

The ability to discern the target of another person’s gaze is critical for social and linguistic development, but functions atypically in autism spectrum disorder (ASD). A multi-pronged approach allowed us to deconstruct this complex ability, to uncover the fundamental bases of this impairment. We analyzed performance on a novel gaze perception task with classical psychophysical metrics (precision and accuracy), principal component analysis (in the analysis of spatial biases), and Bayesian computational modeling (in the analysis of individual subjects’ use of contextual salience cues). Compared to controls, adults with ASD were less precise and less accurate in their judgments of gaze direction. Further, although nearly all controls exhibited a prototypical pattern of spatial bias in their judgments, this spatial prior was severely disrupted among a large subset of ASD participants. By contrast, Bayesian computational modeling revealed that both groups exploited contextual salience cues in their gaze judgments, and that the average strength of this contextual prior was similar for both groups. This comprehensive study revealed that although most ASD participants performed atypically in at least one aspect of gaze perception, the particular aspects disrupted varied idiosyncratically across individuals. Impairment in gaze perception in ASD likely arises via heterogeneous underlying mechanisms.

Stable Scalp EEG Spatiospectral Patterns Across Paradigms Estimated by Group ICA.

Electroencephalography (EEG) oscillations reflect the superposition of different cortical sources with potentially different frequencies. Various blind source separation (BSS) approaches have been developed and implemented in order to decompose these oscillations, and a subset of approaches have been developed for decomposition of multi-subject data. Group independent component analysis (Group ICA) is one such approach, revealing spatiospectral maps at the group level with distinct frequency and spatial characteristics. The reproducibility of these distinct maps across subjects and paradigms is relatively unexplored domain, and the topic of the present study. To address this, we conducted separate group ICA decompositions of EEG spatiospectral patterns on data collected during three different paradigms or tasks (resting-state, semantic decision task and visual oddball task). K-means clustering analysis of back-reconstructed individual subject maps demonstrates that fourteen different independent spatiospectral maps are present across the different paradigms/tasks, i.e. they are generally stable.

Does dexamethasone have a perineural mechanism of action? A paired, blinded, randomized, controlled study in healthy volunteers

BackgroundDexamethasone prolongs block duration. Whether this is achieved via a peripheral or a central mechanism of action is unknown. We hypothesized that perineural dexamethasone added as an adjuvant to ropivacaine prolongs block duration compared with ropivacaine alone, by a locally mediated effect when controlled for a systemic action. MethodsWe performed a paired, blinded, randomized trial, including healthy men. All subjects received bilateral blocks of the saphenous nerve with ropivacaine 0.5%, 20 ml mixed with dexamethasone 2 mg in one leg and saline in the other, according to randomization. The primary outcome was the duration of sensory block assessed by temperature discrimination in the saphenous nerve distribution. Secondary outcomes were sensory block assessed by mechanical discrimination, pain response to tonic heat stimulation, and warmth and heat pain detection thresholds. ResultsWe included 20 subjects; one had a failed block and was excluded from the paired analysis. Block duration was not statistically significantly longer in the leg receiving dexamethasone when assessed by temperature discrimination (primary outcome, estimated median difference 1.5 h, 95% confidence interval −3.5 to 0, P=0.050). For all other outcomes, the duration was statistically significantly longer in the leg receiving dexamethasone, but the median differences were <2.0 h. Individual subject analysis revealed that only eight subjects had a block prolongation of at least 2 h in the leg receiving dexamethasone perineurally. ConclusionPerineural administration of dexamethasone 2 mg showed a modest and inconsistent effect of questionable clinical relevance on block duration. Clinical trial registrationNCT01981746.

Uses, misuses, new uses and fundamental limitations of magnetic resonance imaging in cognitive science.

When blood oxygenation level-dependent (BOLD) contrast functional magnetic resonance imaging (fMRI) was discovered in the early 1990s, it provoked an explosion of interest in exploring human cognition, using brain mapping techniques based on MRI. Standards for data acquisition and analysis were rapidly put in place, in order to assist comparison of results across laboratories. Recently, MRI data acquisition capabilities have improved dramatically, inviting a rethink of strategies for relating functional brain activity at the systems level with its neuronal substrates and functional connections. This paper reviews the established capabilities of BOLD contrast fMRI, the perceived weaknesses of major methods of analysis, and current results that may provide insights into improved brain modelling. These results have inspired the use of in vivo myeloarchitecture for localizing brain activity, individual subject analysis without spatial smoothing and mapping of changes in cerebral blood volume instead of BOLD activation changes. The apparent fundamental limitations of all methods based on nuclear magnetic resonance are also discussed.This article is part of the themed issue ‘Interpreting BOLD: a dialogue between cognitive and cellular neuroscience’.

Factors affecting characterization and localization of interindividual differences in functional connectivity using MRI.

Much recent attention has been paid to quantifying anatomic and functional neuroimaging on the individual subject level. For optimal individual subject characterization, specific acquisition and analysis features need to be identified that maximize interindividual variability while concomitantly minimizing intra-subject variability. We delineate the effect of various acquisition parameters (length of acquisition, sampling frequency) and analysis methods (time course extraction, region of interest parcellation, and thresholding of connectivity-derived network graphs) on characterizing individual subject differentiation. We utilize a non-parametric statistical metric that quantifies the degree to which a parameter set allows this individual subject differentiation by both maximizing interindividual variance and minimizing intra-individual variance. We apply this metric to analysis of four publicly available test-retest resting-state fMRI (rs-fMRI) data sets. We find that for the question of maximizing individual differentiation, (i) for increasing sampling, there is a relative tradeoff between increased sampling frequency and increased acquisition time; (ii) for the sizes of the interrogated data sets, only 3-4 min of acquisition time was sufficient to maximally differentiate each subject with an algorithm that utilized no a priori information regarding subject identification; and (iii) brain regions that most contribute to this individual subject characterization lie in the default mode, attention, and executive control networks. These findings may guide optimal rs-fMRI experiment design and may elucidate the neural bases for subject-to-subject differences. Hum Brain Mapp 37:1986-1997, 2016. © 2016 Wiley Periodicals, Inc.

Sentence processing selectivity in Broca's area: evident for structure but not syntactic movement

The role of Broca’s area in sentence processing is hotly debated. Hypotheses include that Broca’s area supports sentence comprehension via syntax-specific processes, hierarchical structure building, or working memory. Here we adopt a within-subject functional magnetic resonance imaging (fMRI) approach using sentence-level contrasts and non-sentential comparison tasks to address these hypotheses. Standard syntactic movement distance effects were replicated, but no difference was found between movement and non-movement sentences in Broca's area in the group or consistently in the individual subject analyses. Group and individual results both identify Broca's area subregions that are selective for sentence structure. Group, but not individual subject results, suggest shared resources for sentence processing and articulation in Broca's area. We conclude that Broca’s area is not selectively processing syntactic movement, but that subregions are selectively responsive to sentence structure. Our findings reinforce Fedorenko and Kanwishser's call for individual subject analyses in Broca's area, as group findings can obscure selective responses.

An assessment of horse (Equus ferus caballus) responding on fixed interval schedules of reinforcement: An individual analysis

We assessed different measures of temporal control of horse (N=16) responding on fixed interval schedules of reinforcement and a peak procedure. Subjects were trained to insert their heads into a response hoop to break an infrared beam in order to receive horse treats from an automatic feeder. We analyzed cumulative response records, binned response levels, quarter life, latency to first response, breakpoint, and inter-response patterns of the fixed interval trials. To analyze the peak procedure trials, we performed a series of bin analyses. To avoid potential pitfalls associated with aggregate analyses, we performed individual trial and subject analyses using an ordinal analysis within Observation Oriented Modeling. Most subjects produced clear indications that responding came under temporal control of the fixed interval schedules for most of our investigated measures, and some subjects’ response levels peaked at half of the peak trial intervals. We provide the first quantitative evidence of equine timing performances using protocols based on fixed interval schedules of reinforcement.