Pairwise Discrimination Research Articles

Quantitative characterization of breast lesions and normal fibroglandular tissue using compartmentalized diffusion-weighted model: comparison of intravoxel incoherent motion and restriction spectrum imaging

BackgroundTo compare the compartmentalized diffusion-weighted models, intravoxel incoherent motion (IVIM) and restriction spectrum imaging (RSI), in characterizing breast lesions and normal fibroglandular tissue.MethodsThis prospective study enrolled 152 patients with 157 histopathologically verified breast lesions (41 benign and 116 malignant). All patients underwent a full-protocol preoperative breast MRI, including a multi-b-value DWI sequence. The diffusion parameters derived from the mono-exponential model (ADC), IVIM model (Dt, Dp, f), and RSI model (C1, C2, C3, C1C2, F1, F2, F3, F1F2) were quantitatively measured and then compared among malignant lesions, benign lesions and normal fibroglandular tissues using Kruskal-Wallis test. The Mann-Whitney U-test was used for the pairwise comparisons. Diagnostic models were built by logistic regression analysis. The ROC analysis was performed using five-fold cross-validation and the mean AUC values were calculated and compared to evaluate the discriminative ability of each parameter or model.ResultsAlmost all quantitative diffusion parameters showed significant differences in distinguishing malignant breast lesions from both benign lesions (other than C2) and normal fibroglandular tissue (all parameters) (all P < 0.0167). In terms of the comparisons of benign lesions and normal fibroglandular tissues, the parameters derived from IVIM (Dp, f) and RSI (C1, C2, C1C2, F1, F2, F3) showed significant differences (all P < 0.005). When using individual parameters, RSI-derived parameters-F1, C1C2, and C2 values yielded the highest AUCs for the comparisons of malignant vs. benign, malignant vs. normal tissue and benign vs. normal tissue (AUCs = 0.871, 0.982, and 0.863, respectively). Furthermore, the combined diagnostic model (IVIM + RSI) exhibited the highest diagnostic efficacy for the pairwise discriminations (AUCs = 0.893, 0.991, and 0.928, respectively).ConclusionsQuantitative parameters derived from the three-compartment RSI model have great promise as imaging indicators for the differential diagnosis of breast lesions compared with the bi-exponential IVIM model. Additionally, the combined model of IVIM and RSI achieves superior diagnostic performance in characterizing breast lesions.

Calculating the distance between languages with deep learning

Artificial intelligence (AI) has been implemented in various fields, including speech recognition. In this paper, a computational method is proposed for calculating the similarity between different languages or language varieties, with their similarity represented in terms of distance. In this process, we extracted mel spectrogram features from speech signals to provide the feature vectors and derived pairs of signal tokens based on vectors. Then, we trained a Siamese time-delay neural network to calculate the distance between two signal tokens. If the token pairs are from the same language group, the distance obtained using this Siamese network model is zero. In this preliminary experiment, three types of regional Mandarin Chinese (BJ, FJ, GD) were used as the dataset. The results gave the F1-score of 0.794, 0.623, and 0.715 for the classification task with respect to BJ, FJ, and GD dataset. In addition, 10 Taiwan Mandarin (TM) native speakers participated in identification and a pair-wise discrimination experiment to allow comparison with the Siamese network model. The 10 TM natives tended to misidentify GD-accented Mandarin as FJ-accented Mandarin resulting in a much greater distance between the two in the FJ-GD discrimination task compared to the Siamese network model. Overall, the results show that the performance of our model is better than the comparative experiment in completing the identification task, with the distance between the Siamese network model and the experiment having a mean absolute error (MAE) of 0.35. The familiarity might be the reason why the 10 TM natives displayed a bias towards BJ-accented Mandarin Chinese. To sum up, we provide a computational method to calculate the distance between two languages or language varieties, which can help linguists pre-classify sound files.

Repeated Exposure to High-THC Cannabis Smoke during Gestation Alters Sex Ratio, Behavior, and Amygdala Gene Expression of Sprague Dawley Rat Offspring.

Because of the legalization of Cannabis in many jurisdictions and the trend of increasing Δ9-tetrahydrocannabinol (THC) content in Cannabis products, an urgent need exists to understand the impact of Cannabis use during pregnancy on fetal neurodevelopment and behavior. To this end, we exposed female Sprague Dawley rats to Cannabis smoke daily from gestational day 6 to 20 or room air. Maternal reproductive parameters, offspring behavior, and gene expression in the offspring amygdala were assessed. Body temperature was decreased in dams following smoke exposure and more fecal boli were observed in the chambers before and after smoke exposure in dams exposed to smoke. Maternal weight gain, food intake, gestational length, litter number, and litter weight were not altered by exposure to Cannabis smoke. A significant increase in the male-to-female ratio was noted in the Cannabis-exposed litters. In adulthood, male and female Cannabis smoke-exposed offspring explored the inner zone of an open field significantly less than control offspring. Gestational Cannabis smoke exposure did not affect behavior on the elevated plus maze test or social interaction test in the offspring. Cannabis offspring were better at visual pairwise discrimination and reversal learning tasks conducted in touchscreen-equipped operant conditioning chambers. Analysis of gene expression in the adult amygdala using RNA sequencing revealed subtle changes in genes related to development, cellular function, and nervous system disease in a subset of the male offspring. These results demonstrate that repeated exposure to high-THC Cannabis smoke during gestation alters maternal physiological parameters, sex ratio, and anxiety-like behaviors in the adulthood offspring.

Gasoline discrimination using infrared spectroscopy and virtual samples based on measurement uncertainty

In a previous work, we proposed a methodology for pair-wise discrimination of gasoline samples by creating virtual samples based on physicochemical assays or distillation curves. Satisfactory results were achieved, although specialist and specific apparatus (not commonly available at police laboratories) were required. The present study goes a step further and for the first time investigates the possibility of infrared (IR) spectroscopy to enable a virtual samples-based methodology for comparison of gasoline samples in pairs. IR spectroscopy feasibility for in situ applications is attractive for forensic investigations. The performances of one handheld NIR device and one dual-range (FT-NIR and FT-IR) benchtop spectrometer were evaluated. The estimation of uncertainty in infrared spectral measurement (needed to generate virtual samples) is barely discussed in literature. So far, there are no literature reports describing quantification and comparison of measurement uncertainties for the spectral acquisitions evaluated here, especially regarding their use for generating virtual samples. A stepwise procedure to quantify uncertainties associated with IR spectral acquisition, at each wavenumber, is described. This method can be useful for understanding both the sources of variability in IR measurements and the system under investigation. Uncertainty estimation was based on experimental data and considered intermediate precision, repeatability and variations in sample temperature as sources of variability. Virtual samples were employed in a discrimination approach using SIMCA models. Results for portable NIR, FT-NIR and FT-IR data sets showed complete discrimination for 96.3%, 93.4% and 93.7% of the 1431 pairs of gasoline samples evaluated, respectively. These results were comparable and similar to those obtained for the physicochemical properties data set (95.7%), although slightly inferior to the result obtained for distillation curves (99.2%). Using IR non-destructive methods in this case could enable faster investigations and simpler analysis, especially for the low-cost handheld spectrometer. In a screening approach, atmospheric distillation assays can be employed only if infrared techniques are not capable of distinguishing the samples subject to comparison. In this work, a pair of samples was considered to be completely discriminated only when a null false positive error (FPR) was achieved, although a more flexible criterium may be acceptable in practice. Finally, the methodology could be extended to other applications where sample comparison is important.

Hierarchical distinctions in the production and perception of nuclear tunes in American English

In Autosegmental-Metrical models of intonational phonology, different types of pitch accents, phrase accents, and boundary tones concatenate to create a set of phonologically distinct phrase-final nuclear tunes. This study asks if an eight-way distinction in nuclear tune shape in American English, predicted from the combination of two (monotonal) pitch accents, two phrase accents, and two boundary tones, is evident in speech production and in speech perception. F0 trajectories from a large-scale imitative speech production experiment were analyzed using bottom-up(k-means) clustering, neural net classification, GAMM modeling, and modeling of turning point alignment. Listeners’ perception of the same tunes is tested in a perceptual discrimination task and related to the imitation results. Emergent grouping of tunes in the clustering analysis, and related classification accuracy from the neural net, show a merging of some of the predicted distinctions among tunes whereby tune shapes that vary primarily in the scaling of final f0 are not reliably distinguished. Within five emergent clusters, subtler distinctions among tunes are evident in GAMMs and f0 turning point modeling. Clustering of individual participants’ production data shows a range of partitions of the data, with nearly all participants making a primary distinction between a class of High-Rising and Non-High-Rising tunes, and with up to four secondary distinctions among the non-Rising class. Perception results show a similar pattern, with poor pairwise discrimination for tunes that differ primarily, but by a small degree, in final f0, and highly accurate discrimination when just one member of a pair is in the High-Rising tune class. Together, the results suggest a hierarchy of distinctiveness among nuclear tunes, with a robust distinction based on holistic tune shape and poorly differentiated distinctions between tunes with the same holistic shape but small differences in final f0. The observed distinctions from clustering, classification, and perception analyses align with the tonal specification of a binary pitch accent contrast {H*, L*} and a maximally ternary {H%, M%, L%} boundary tone contrast; the findings do not support distinct tonal specifications for the phrase accent and boundary tone from the AM model.&amp;nbsp;

Male DAT Val559 Mice Exhibit Compulsive Behavior under Devalued Reward Conditions Accompanied by Cellular and Pharmacological Changes.

Identified across multiple psychiatric disorders, the dopamine (DA) transporter (DAT) Ala559Val substitution triggers non-vesicular, anomalous DA efflux (ADE), perturbing DA neurotransmission and behavior. We have shown that DAT Val559 mice display a waiting impulsivity and changes in cognitive performance associated with enhanced reward motivation. Here, utilizing a within-subject, lever-pressing paradigm designed to bias the formation of goal-directed or habitual behavior, we demonstrate that DAT Val559 mice modulate their nose poke behavior appropriately to match context, but demonstrate a perseverative checking behavior. Although DAT Val559 mice display no issues with the cognitive flexibility required to acquire and re-learn a visual pairwise discrimination task, devaluation of reward evoked habitual reward seeking in DAT Val559 mutants in operant tasks regardless of reinforcement schedule. The direct DA agonist apomorphine also elicits locomotor stereotypies in DAT Val559, but not WT mice. Our observation that dendritic spine density is increased in the dorsal medial striatum (DMS) of DAT Val559 mice speaks to an imbalance in striatal circuitry that might underlie the propensity of DAT Val559 mutants to exhibit compulsive behaviors when reward is devalued. Thus, DAT Val559 mice represent a model for dissection of how altered DA signaling perturbs circuits that normally balance habitual and goal-directed behaviors.

Performance of the intracerebroventricularly injected streptozotocin Alzheimer’s disease model in a translationally relevant, aged and experienced rat population

The intracerebroventricularly (icv) injected streptozotocin (STZ) induced brain state is a widely used model of sporadic Alzheimer-disease (AD). However, data have been generated in young, naive albino rats. We postulate that the translationally most relevant animal population of an AD model should be that of aged rats with substantial learning history. The objective of the study was thus to probe the model in old rats with knowledge in various cognitive domains. Long-Evans rats of 23 and 10 months age with acquired knowledge in five-choice serial reaction time task (5-CSRTT), a cooperation task, Morris water-maze (MWM) and “pot-jumping” exercise were treated with 3 × 1.5 mg/kg icv. STZ and their performance were followed for 3 months in the above and additional behavioral assays. Both STZ-treated age groups showed significant impairment in the MWM (spatial learning) and novel object recognition test (recognition memory) but not in passive avoidance and fear conditioning paradigms (fear memory). In young STZ treated rats, significant differences were also found in the 5CSRTT (attention) and pot jumping test (procedural learning) while in old rats a significant increase in hippocampal phospho-tau/tau protein ratio was observed. No significant difference was found in the cooperation (social cognition) and pairwise discrimination (visual memory) assays and hippocampal β-amyloid levels. STZ treated old animals showed impulsivity-like behavior in several tests. Our results partly coincide with partly deviate from those published on young, albino, unexperienced rats. Beside the age, strain and experience level of the animals differences can also be attributed to the increased dose of STZ, and the applied food restriction regime. The observed cognitive and non-cognitive activity pattern of icv. STZ in aged experienced rats call for more extensive studies with the STZ model to further strengthen and specify its translational validity.

Image discrimination reversal learning is impaired by sleep deprivation in rats: Cognitive rigidity or fatigue?

Insufficient sleep is pervasive worldwide, and its toll on health and safety is recapitulated in many settings. It is thus important to understand how poor sleep affects the brain and decision making. A robust literature documents the adverse effects of sleep deprivation on cognitive processes including cognitive flexibility, which is the capacity to appraise new feedback and make behavioral adjustments to respond appropriately. Animal models are often used to unravel the molecules, genes and neural circuits that are altered by sleep loss. Herein we take a translational approach to model the effects of sleep deprivation on cognitive rigidity, i.e., impaired cognitive flexibility in rats. There are several approaches to assess cognitive rigidity; in the present study, we employ a pairwise discrimination reversal task. To our knowledge this is the first time this paradigm has been used to investigate sleep deprivation. In this touchscreen operant platform, we trained rats to select one of two images to claim a sucrose pellet reward. If the non-rewarded image was selected the rats proceeded to a correction trial where both images were presented in the same position as before. This image presentation continued until the rat selected the correct image. Once rats reached performance criteria, the reward contingencies were reversed. In one group of rats the initial reversal session was preceded by 10 h of sleep deprivation. We compared those rats to controls with undisturbed sleep on the number of sessions to reach performance criteria, number of trials per session, response latencies, correct responses, errors, perseverative errors and perseveration bouts in the initial training and reversal phases. We report that on reversal session one, sleep deprived rats completed a fraction of the trials completed by controls. On subsequent reversal sessions, the sleep deprived rats struggled to adapt to the reversed contingencies despite completing a similar number of trials, suggesting an effect of cognitive rigidity separate from fatigue. We discuss the delayed performance dynamics incurred by sleep loss in the context of fatigue and the implications of using pairwise discrimination reversal as a model to further examine the effects of sleep loss on adaptive decision making.

Hippocampal and medial prefrontal cortices encode structural task representations following progressive and interleaved training schedules.

Memory generalisations may be underpinned by either encoding- or retrieval-based generalisation mechanisms and different training schedules may bias some learners to favour one of these mechanisms over the other. We used a transitive inference task to investigate whether generalisation is influenced by progressive vs randomly interleaved training, and overnight consolidation. On consecutive days, participants learnt pairwise discriminations from two transitive hierarchies before being tested during fMRI. Inference performance was consistently better following progressive training, and for pairs further apart in the transitive hierarchy. BOLD pattern similarity correlated with hierarchical distances in the left hippocampus (HIP) and medial prefrontal cortex (MPFC) following both training schedules. These results are consistent with the use of structural representations that directly encode hierarchical relationships between task features. However, such effects were only observed in the MPFC for recently learnt relationships. Furthermore, the MPFC appeared to maintain structural representations in participants who performed at chance on the inference task. We conclude that humans preferentially employ encoding-based mechanisms to store map-like relational codes that can be used for memory generalisation. These codes are expressed in the HIP and MPFC following both progressive and interleaved training but are not sufficient for accurate inference.

A touchscreen-based paradigm to measure visual pattern separation and pattern completion in mice.

Memory accuracy involves two major processes: pattern separation and pattern completion. Pattern separation refers to the ability to reduce overlap among similar inputs to avoid interference, and pattern completion refers to the ability to retrieve the whole information from partial or degraded cues. Impairments in pattern separation/pattern completion contribute to cognitive deficits in several diseases of the nervous system. Therefore, it is better to evaluate both pattern separation and pattern completion in one apparatus. However, few tools are available to assess pattern separation and pattern completion within the same apparatus for rodents. In this study, we designed a series of images with varying degrees of similarity to the correct image to evaluate pattern separation and pattern completion. First, mice were trained to discriminate between two totally different images, and once the correct percentage reached above 77% for two consecutive days, the images with different degrees of similarity were used to measure pattern separation and pattern completion. The results showed the mice performed progressively worse from S0 to S4 (increasing similarity) when discriminating similar images in pattern separation, and the mice performed progressively worse from C0 to C4 (decreasing cues information) when recalling the correct image according to partial cues in pattern completion, implying a good image similarity-dependent manner for memory accuracy evaluation. In sum, we designed a convenient, effective paradigm to evaluate pattern separation and pattern completion based on a touchscreen pairwise discrimination task, which may provide a new method for the studies of the effects and mechanisms of memory accuracy enhancing drugs.

Psychophysical Studies of Interleaving Narrowband Tactile Stimuli to Achieve Broadband Perceptual Effects

Despite the ubiquitous presence of tactile actuators (tactors) in mobile devices, there is a continuing need for more advanced tactors that can cover the entire frequency range of human tactile perception. Broadband tactors can increase information transmission and enrich sensory experience. The engineering challenges are multifold in that the ideal tactors should exhibit an effective bandwidth of at least 300 Hz, small form factor, robustness, power efficiency and low cost. For wearable applications, there are the additional challenges of ease of mounting and maintaining adequate skin contact during body movements. We propose an approach to interleave narrowband tactile stimuli to achieve broadband effects, taking advantage of the limited spatial resolution of the skin on the torso and limbs. Three psychophysical experiments were conducted to assess the validity of this approach. Participants performed pairwise discriminations of two broadband stimuli delivered using one or two tactors. The broadband stimuli consisted of one mid-frequency and one high-frequency component delivered through one tactor by mixing the two components, or through two tactors (one component per tactor). The first two experiments revealed extraneous cues such as localization and mutual masking of mid- and high-frequency components that were subsequently eliminated in the third experiment. Results from 12 participants confirmed that performance on pairwise comparisons was below the discrimination threshold, confirming that broadband haptic effects can be achieved through narrowband tactors placed within the skin’s two-point limen.

Multi-Level View Associative Convolution Network for View-Based 3D Model Retrieval

With the continuous improvement of image processing capabilities, a three-dimensional (3D) model that can contain rich information is becoming the fourth type of multimedia data (in addition to sound, image, and video). Moreover, since there is a wide range of applications of 3D models, how to quickly and effectively obtain the correct target model from the massive data has become a key issue. To date, 3D model retrieval approaches have been proposed, and in these approaches, view-based 3D model retrieval methods can achieve satisfactory performance. In the 3D model retrieval task, the latent relationship mining of all images in a 3D model, the adaptive fusion of different images, and the discriminative feature extraction are the main challenges, but in most existing solutions, these issues are separately performed and they are not explored in an end-to-end network architecture. To solve these issues, in this work, we propose a novel and effective multi-level view associative convolution network ( <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MLVACN</b> ) to realize view-based 3D model retrieval, where the relationship exploration of multiple-view images, the fusion of different images, and the feature discrimination learning are realized in a unified end-to-end framework. Specifically, we design the group association layer and the block association layer to study the latent relationships among different views from the view-level and the block-level, respectively. Moreover, the weight fusion layer is further designed to adaptively fuse different views in a 3D model. In addition, these three layers are embedded into the <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MLVACN</b> . Finally, the pairwise discrimination loss function is proposed to learn the discriminative features of the 3D model. Extensive experimental results on three 3D model retrieval datasets including ModelNet40, ModelNet10, and ShapeNetCore55 demonstrate that <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MLVACN</b> can outperform state-of-the-art methods in term of mAP. When the ModelNet40 dataset is used, the mAP of <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MLVACN</b> is improved by 13.25%, 7.75%, 3.95%, and 0.61% as compared to those of the MVCNN, GVCNN, PVNet, and MLVCNN methods, respectively.

High sucrose diet does not impact spatial cognition in rats using advanced touchscreen technology

IntroductionWestern diets, including those consisting of saturated fats, simple sugars and processed foods, is rising at an unprecedented rate. These lead to obesity and metabolic diseases, and possibly cognitive deficits. Exploring this, recent studies demonstrate marked impairment in spatial learning in rodents exposed to high-sugar diets. We utilised advanced touchscreen technology to assess several spatial and non-spatial components of cognition in rats chronically exposed to a high sucrose diet. MethodsMale Wistar rats received 70 ml of 10% sucrose solution each day, or control tap water, persisting for the experiment duration (total n = 32). After 5 weeks of diet, rats performed Pairwise Discrimination, Location Discrimination, or Progressive Ratio tasks on automated touchscreens, and performance compared between groups. ResultsSucrose rats consumed all the sugar solution provided to them, and had significantly increased caloric intake, compared to controls (p < 0.0001). However, in all tests, we found no significant difference in cognitive performance between Sucrose and Control treated rats. This included the number of trials for acquisition, and reversal, in Pairwise Discrimination, and number of trials required to complete Location Discrimination (p > 0.05 for all outcomes). No differences were observed in perseverative behaviour, motivation levels, or processing speed. ConclusionOur study found no evidence to suggest that chronic consumption of sucrose impairs cognition, including both spatial and non-spatial learning tasks. These findings suggest that not all aspects of spatial cognition are negatively impacted by high sugar diet in rodents, and that particular use of touchscreen technology may probe different aspects of cognition than traditional tasks.

Discriminating Leukemia Cellular Heterogeneity and Screening Metabolite Biomarker Candidates using Label-Free Mass Cytometry.

Discriminating various leukocyte subsets with specific functions is critical due to their important roles in the development of many diseases. Here, we proposed a general strategy to unravel leukocytes heterogeneity and screen differentiated metabolites as biomarker candidates for leukocyte subtypes using the label-free mass cytometry (CyESI-MS) combined with a homemade data processing workflow. Taking leukemia cells as an example, metabolic fingerprints of single leukemia cells were obtained from 472 HL-60, 416 THP-1, 313 U937, 356 Jurkat, and 366 Ramos cells, with throughput up to 40 cells/min. Five leukemia subtypes were clearly distinguished by unsupervised learning t-SNE analysis of the single-cell metabolic fingerprints. Cell discrimination in the mixed leukemia cell samples was also realized by supervised learning of the single-cell metabolic fingerprints with high recovery and good repetition (98.31 ± 0.24%, -102.35 ± 4.82%). Statistical analysis and metabolite assignment were carried out to screen characteristic metabolites for discrimination and 36 metabolites with significant differences were annotated. Then, differentiated metabolites for pairwise discrimination of five leukemia subtypes were further selected as biomarker candidates. Furthermore, discriminating cultured leukemia cells from human normal leukocytes, separated from fresh human peripheral blood, was performed based on single-cell metabolic fingerprints as well as the proposed biomarker candidates, unveiling the potential of this strategy in clinical research. This work makes efforts to realize high-throughput single-leukocyte metabolic analysis and metabolite-based discrimination of leukocytes. It is expected to be a powerful means for the clinical molecular diagnosis of hematological diseases.

Hidden talents: Poly (I:C)-induced maternal immune activation improves mouse visual discrimination performance and reversal learning in a sex-dependent manner.

While there is a strong focus on the negative consequences of maternal immune activation (MIA) on developing brains, very little attention is directed towards potential advantages of early life challenges. In this study, we utilized a polyinosine-polycytidylic acid (poly(I:C)) MIA model to test visual pairwise discrimination (PD) and reversal learning (RL) in mice using touchscreen technology. Significant sex differences emerged in that MIA reduced the latency for males to make a correct choice in the PD task while females reached criterion sooner, made fewer errors, and utilized fewer correction trials in RL compared to saline controls. These surprising improvements were accompanied by the sex-specific upregulation of several genes critical to cognitive functioning, indicative of compensatory plasticity in response to MIA. In contrast, when exposed to a 'two-hit' stress model (MIA + loss of the social component of environmental enrichment [EE]), mice did not display anhedonia but required an increased number of PD and RL correction trials. These animals also had significant reductions of CamK2a mRNA in the prefrontal cortex. Appropriate functioning of synaptic plasticity, via mediators such as this protein kinase and others, are critical for behavioral flexibility. Although EE has been implicated in, delaying the appearance of symptoms associated with certain brain disorders, these findings are in line with evidence that it also makes individuals more vulnerable to its loss. Overall, with the right 'dose', early life stress exposure can confer at least some functional advantages, which are lost when the number or magnitude of these exposures become too great.

Classification of first-episode schizophrenia patients, individuals at ultra-high risk for psychosis, and healthy controls using structural mri, eeg, and machine learning

IntroductionMachine learning has increasingly been applied to classification of psychosis spectrum in neuroimaging research. However, a number of multimodal studies using MRI and electroencephalography (EEG) is quite limited.ObjectivesTo assess the power of multimodal structural MRI (sMRI) and EEG data to provide pairwise discrimination between first-episode schizophrenia (FES) patients, individuals at ultra-high-risk of psychosis (UHR), and healthy controls (HC) using machine learning algorithms.Methods46 FES male patients, 39 UHR individuals, and 54 matched HC underwent sMRI (3T Philips scanner) and electroencephalography. T1-weighted images were processed via FreeSurfer to obtain cortical and subcortical measures. L2 regularized logistic regression was used to evaluate the efficacy of diagnostic prediction.ResultsThe accuracies of pairwise discriminations were: 87% for FES vs HC (specificity 83%, sensitivity 91%); 77% for FES vs UHR (specificity 76%, sensitivity 79%); 75% for UHR vs HC (specificity 77%, sensitivity 73%).ConclusionsCurrent findings suggest that the patterns of anatomical and functional variability have potential as biomarkers for discrimination between schizophrenia, UHR, and healthy subjects. Furthermore, results show that the selection and multimodality of feature types are important. Specifically, adding EEG data to morphometric measures improved accuracy rates in FES vs HC and FES vs UHR contrasts, whereas standalone EEG data provided higher accuracy compared with morphometric or multimodal data in UHR vs HC discrimination. Expectedly, predictive power for the UHR was smaller than for the FES due to its intermediate anatomical features, located between those observed in healthy controls and those found in patients. The work was supported by RFBR grant 20-013-00748

Linking cognition to age and amyloid-β burden in the brain of a nonhuman primate (Microcebus murinus)

The gray mouse lemur (Microcebus murinus) is a valuable model in research on age-related proteopathies. This nonhuman primate, comparable to humans, naturally develops tau and amyloid-β proteopathies during aging. Whether these are linked to cognitive alterations is unknown. Here, standardized cognitive testing in pairwise discrimination and reversal learning in a sample of 37 aged (>5 years) subjects was combined with tau and amyloid-β histochemistry in individuals that died naturally. Correlation analyses in successfully tested subjects (n = 22) revealed a significant relation between object discrimination learning and age, strongly influenced by outliers, suggesting pathological cases. Where neuroimmunohistochemistry was possible, as subjects deceased, the naturally developed cortical amyloid-β burden was significantly linked to pretraining success (intraneuronal accumulations) and discrimination learning (extracellular deposits), showing that cognitive (pairwise discrimination) performance in old age predicts the natural accumulation of amyloid-β at death. This is the first description of a direct relation between the cortical amyloid-β burden and cognition in a nonhuman primate.

Differentiation of predominant subtypes of lung adenocarcinoma using a quantitative radiomics approach on CT.

To develop a model for differentiating the predominant subtype-based prognostic groups of lung adenocarcinoma using CT radiomic features, and to validate its performance in comparison with radiologists' assessments. A total of 993 patients presenting with invasive lung adenocarcinoma between March 2010 and June 2016 were identified. Predominant histologic subtypes were categorized into three groups according to their prognosis (group 0: lepidic; group 1: acinar/papillary; group 2: solid/micropapillary). Seven hundred eighteen radiomic features were extracted from segmented lung cancers on contrast-enhanced CT. A model-development set was formed from the images of 893 patients, while 100 image sets were reserved for testing. A least absolute shrinkage and selection operator method was used for feature selection. Performance of the radiomic model was evaluated using receiver operating characteristic curve analysis, and accuracy on the test set was compared with that of three radiologists with varying experiences (6, 7, and 19years in chest CT). Our model differentiated the three groups with areas under the curve (AUCs) of 0.892 and 0.895 on the development and test sets, respectively. In pairwise discrimination, the AUC was highest for group 0 vs. 2 (0.984). The accuracy of the model on the test set was higher than the averaged accuracy of the three radiologists without statistical significance (73.0% vs. 61.7%, p = 0.059). For group 2, the model achieved higher PPV than the observers (85.7% vs. 35.0-48.4%). Predominant subtype-based prognostic groups of lung adenocarcinoma were classified by a CT-based radiomic model with comparable performance to radiologists. • A CT-based radiomic model differentiated three prognosis-based subtype groups of lung adenocarcinoma with areas under the curve (AUCs) of 0.892 and 0.895 on development and test sets, respectively. • The CT-based radiomic model showed near perfect discrimination between group 0 and group 2 (AUCs, 0.984-1.000). • The accuracy of the CT-based radiomic model was comparable to the averaged accuracy of the three radiologists with 6, 7, and 19years of clinical experience in chest CT (73.0% vs. 61.7%, p = 0.059), achieving a higher positive predictive value for group 2 than the observers (85.7% vs. 35.0-48.4%).

Sex differences in the effect of maternal immune activation on cognitive and psychosis‐like behaviour in Long Evans rats

Maternal immune activation during pregnancy is associated with increased risk of development of schizophrenia in later life. There are sex differences in schizophrenia, particularly in terms of age of onset, course of illness and severity of symptoms. However, there is limited and inconsistent literature on sex differences in the effects of maternal immune activation on behaviour with relevance to schizophrenia. The aim of this study was therefore to investigate sex differences in the effects of maternal immune activation by treating Long Evans rats with poly(I:C) on gestational day 15. We compared adult male and female offspring on spatial working memory in the touchscreen trial-unique nonmatching-to-location task, pairwise discrimination and reversal learning, as well as on prepulse inhibition and psychotropic drug-induced locomotor hyperactivity. Male, but not female poly(I:C) offspring displayed a deficit in spatial working memory, particularly at the longer delay. Neither pairwise discrimination nor reversal learning showed an effect of poly(I:C), but female controls outperformed male controls in the reversal learning task. Significant reduction of prepulse inhibition and enhancement of acute methamphetamine-induced locomotor hyperactivity was found similarly in male and female poly(I:C) offspring. These results show that maternal immune activation induces a range of behavioural effects in the offspring, with sex specificity in the effects of maternal immune activation on some aspects of cognition, but not psychosis-like behaviour.

A Multimodal Pairwise Discrimination Network for Cross-Domain Action Recognition

In recent years, action recognition has become a hot research topic in the computer vision and machine learning domain. Despite many well-designed action recognition approaches have been proposed, we point out that some limitations still exist including the separated fusion of different Spatio-temporal features and the reconstruction classification model, and the requirement of similar environmental conditions when capturing the training and testing data. Thus, research interest has shifted from traditional action recognition towards cross-domain action recognition. To solve these limitations, in this work, we propose a novel multimodal pairwise discrimination network (short for MPD) for cross-domain action recognition that is an end-to-end network architecture. In MPD, it can jointly fuse different Spatio-temporal features from the video, learn domain invariant features for different action domains (source and target domains), and build the classification model. To characterize the shift between these domains, subnetwork parameters in corresponding layers of MPD are required to be relevant, but not identical. Besides, the domain invariant feature discrimination needs to be improved. Extensive experimental results on two different public benchmarks including indoor environment and outdoor environment demonstrate that our MPD solution can significantly outperform state-of-the-art methods with a 4% to 20% improvement in average accuracy.