Miracle-dz/UniFAR-FTUs huggingface dataset:
Examining the neural antecedents of tics in Tourette syndrome using electroencephalography

Tourette syndrome (TS) is a neurological disorder of childhood onset that is characterised by the occurrence of motor and vocal tics. TS is associated with cortical-striatal-thalamic-cortical circuit [CSTC] dysfunction and hyper-excitability of cortical limbic and motor regions that are thought to lead to the occurrence of tics. Importantly, individuals with TS often report that their tics are preceded by ‘premonitory sensory/urge phenomena’ (PU) that are described as uncomfortable bodily sensations that precede the execution of a tic and are experienced as a strong urge for motor discharge. While tics are most often referred to as involuntary movements, it has been argued that tics should be viewed as voluntary movements that are executed in response to the presence of PU and bring temporary relief from the uncomfortable bodily sensations that are associated with PU. This issue remains unresolved but has very important implications for the design of clinical interventions for TS. To investigate this issue further, we conducted a study using electroencephalography (EEG). Specifically, we recorded movement-related EEG (mu and beta band oscillations) during (a) the immediate period leading up to the execution of voluntary movements by a group of individuals with TS and a group of matched healthy control participants, and (b) the immediate period leading up to the execution of a tic in a group of individuals with TS. We demonstrate that movement-related mu and beta band oscillations are not observed prior to tics in individuals with TS. We interpret this effect as reflecting the greater involvement of a network of brain areas, including the insular and cingulate cortices, basal ganglia nuclei, and the cerebellum, in the generation of tics in TS. We also show that beta-band desynchronization does occur when individuals with TS initiate voluntary movements, but, in contrast to healthy controls, desynchronization of mu-band oscillations is not observed during the execution of voluntary movements for individuals with TS. We interpret this finding as reflecting a dysfunction of physiological inhibition in TS, thereby contributing to an impaired ability to suppress neuronal populations that may compete with movement preparation processes.
Adult-born granule cells support pathological microcircuits in the chronically epileptic dentate gyrus

Temporal lobe epilepsy (TLE) is characterized by recurrent seizures driven by synchronous neuronal activity. The dentate gyrus (DG) region of the hippocampal formation is highly reorganized in chronic TLE; in particular, pathological remodeling of the “dentate gate” is thought to open up pathological conduction pathways for synchronous discharges and seizures in the mesial temporal lobe. However, this pathophysiological framework lacks a mechanistic explanation of how macroscale synchronous dynamics emerge from alterations of the DG at the microcircuit level. In particular, the relative contribution of developmentally defined subpopulations of adult-born (abGCs) and mature (mGCs) granule cells to epileptiform network events remains unknown. To address this question, we optically recorded activity dynamics of identified populations of abGCs and mGCs during interictal epileptiform discharges (IEDs) in mice with chronic TLE. We find that disjoint subsets of IEDs differentially recruit abGC and mGC populations. We used these observations to develop a neural topic modeling framework, under which we find that the epileptic DG network organizes into disjoint, cell-type specific pathological ensembles, a subset of which are recruited by each IED. We found that statistics of this ensemble structure are highly conserved across animals, with abGCs disproportionately driving network activity in the epileptic DG during IEDs. Our results provide the first in vivo characterization of activity dynamics of identified GC subpopulations in the epileptic DG, the first microcircuit-level correlates of IEDs in vivo, and reveal a specific contribution of abGCs to interictal epileptic events. Highlights We relate electrographic signatures of epilepsy to microcircuit dynamics at single-cell resolution The chronically epileptic dentate gyrus granule cell network is organized in lineage-specific pathological ensembles A novel generative model framework for ensemble recruitment relates local field potential signatures to microcircuit activation during interictal epileptiform discharges Adult-born granule cell-dominated ensembles are disproportionately represented among the inferred ensembles The most active ensemble during an interictal epileptiform discharge can be decoded directly from the local field potential spectrum This Latent Ensemble Recruitment model of cell recruitment by interictal events is the first application of Bayesian topic modeling to in vivo two-photon calcium imaging data
Structural alterations in the macaque frontoparietal white matter network after recovery from prefrontal cortex lesions

Unilateral damage to the frontoparietal network typically impairs saccade target selection within the contralesional visual hemifield. Severity of deficits and the degree of recovery have been associated with widespread network dysfunction, yet it is not clear how these behavioural and functional changes relate with the underlying structural white matter pathways. Here, we investigated whether recovery after unilateral prefrontal cortex (PFC) lesions was associated with structural white matter remodeling in the distributed frontoparietal network. Diffusion-weighted MRI was acquired in four macaque monkeys before the lesions and at 2-4 months post-lesion, after recovery of deficits in saccade selection of contralesional targets. Probabilistic tractography was used to reconstruct inter- and intra-hemispheric frontoparietal fiber tracts: bilateral superior longitudinal fasciculus (SLF) and transcallosal fibers connecting bilateral PFC or bilateral posterior parietal cortex (PPC). After behavioural recovery, tract-specific fractional anisotropy in contralesional SLF and transcallosal PPC increased after small lesions and decreased after larger lesions compared to pre-lesion. These findings indicate that remote fiber tracts may provide optimal compensation after small PFC lesions. However, larger lesions may have induced widespread structural damage and hindered compensatory remodeling in the structural frontoparietal network.
Causal roles of frontoparietal cortical areas in feedback control of the limb

Goal-directed motor corrections are surprisingly fast and complex, but little is known on how they are generated by the central nervous system. Here we show that temporary cooling of dorsal premotor cortex (PMd) or parietal area 5 (A5) in behaving monkeys caused impairments in corrective responses to mechanical perturbations of the forelimb. Deactivation of PMd impaired both spatial accuracy and response speed, whereas deactivation of A5 impaired spatial accuracy, but not response speed. Simulations based on optimal feedback control demonstrated that ‘deactivation’ of the control policy (reduction of feedback gain) impaired both spatial accuracy and response speed, whereas ‘deactivation’ in state estimation (reduction of Kalman gain) impaired spatial accuracy but not response speed, paralleling the impairments observed from deactivation of PMd and A5, respectively. Furthermore, combined deactivation of both cortical regions led to additive impairments of individual deactivations, whereas reducing the amount of cooling (i.e. milder cooling) to PMd led to impairments in response speed, but not spatial accuracy, both also predicted by the model simulations. These results provide causal support that higher order motor and somatosensory regions beyond primary somatosensory and primary motor cortex are involved in generating goal-directed motor responses. As well, the computational models suggest that the distinct patterns of impairments associated with these cortical regions reflect their unique functional roles in goal-directed feedback control.
Positive selection pressure on rice blast resistance allele Piz-t makes it divergent in Indian land races

Abstract Allelic variants of the broad-spectrum blast resistance gene, Piz-t, have been analyzed in 48 rice lines selected after phenotyping across three blast hot-spot regions of India. Single Nucleotide Polymorhisms in the form of transitions were more frequent than the transversions in the alleles. On the basis of nucleotide polymorphism, 46 haplotypes have been identified, with major haplotypes forming three main haplogroups. The Piz-t alleles formed mostly region-specific clusters. Resistant and susceptible Piz-t alleles were grouped into separate sub-clusters. The value of Tajima's D was negative indicating positive selection on Piz-t locus. Sequence variations were more abundant in the leucine rich repeats (LRR) region than in the NB-ARC (nucleotide-binding adaptor shared by APAF-1,R proteins, and CED-4) region, indicating that the LRR region has played a more important role in the evolution of this allele. The detailed molecular analysis of the Piz-t locus provide insights to high degree of inter-and intra-specific relationship among the Indian land races of rice which will help in the selection of better alleles for future rice breeding programs.
On the Bioactivity and Mechanical Properties of Gehlenite Nanobioceramic: A Comparative Study

Background: For a new biomaterial which is going to be applied in bone tissue regeneration, bioactivity (bone bonding ability) and desirable mechanical properties are very essential parameters to take into consideration. In the present study, the gehlenite's mechanical properties and bioactivity are assessed and compared with hydroxyapatite (HA) for bone tissue regeneration. Method: Gehlenite and HA nanoparticles are synthesized through sol–gel method and coprecipitation technique, respectively, and their physical and chemical properties are characterized through X-ray diffraction, Fourier transform infrared spectroscopy, and transmission electron microscopy. Results: The results prove that the gehlenite and HA phases without any undesirable phase are obtained, and the particles of both compounds are in the nanometer range with spherical morphology. The compressive strength of both compounds are assessed, and the values for gehlenite and HA disks are 144 ± 5 and 150 ± 4.8 MPa, respectively. Next, their bioactivity potential is assessed into simulated body fluid (SBF) up to 21 days, and the results show that after 14 days, gehlenite disk's surface is completely covered with newly formed Ca-P particles. However, some sporadic precipitations after 21 days soaking into SBF are formed onto the HA disk's surface. Conclusion: This comparative study shows that nanostructured gehlenite disk with desirable mechanical properties and faster bioactivity kinetic than HA can be considered as a promising bioceramic for bone tissue regeneration.
Authors' Responses to the Comments on “Pattern and Correlates of Depression among Medical Students: An 18-Month Follow-Up Study”

314 Indian Journal of Psychological Medicine | Volume 42 | Issue 3 | May-June 2020 This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. Access this article online
Serum Lipids among Drug Naïve or Drug-Free Patients with Obsessive Compulsive Disorder and their Association with Impulsivity: A Comparative Study

Background: The derangement of serum lipids is well documented in psychiatric disorders like schizophrenia, mania, and depression but not in obsessive compulsive disorder (OCD), where it has been inadequately examined. Also, serum lipid abnormalities are increasingly found in “impulsivity,” an important sub-construct of OCD. Our study aimed to examine serum lipid profile among patients with OCD and its association with clinical profile and impulsivity among them. Methods: Forty drug naïve or drug-free (four weeks for oral and eight weeks for any depot psychotropics) patients with OCD according to International Classification of Disease -10th version (ICD-10): Diagnostic Criteria for Research (DCR) by the World Health Organization (WHO), from outpatient and inpatient departments of a tertiary care psychiatric hospital were recruited. Measures like Yale–Brown Obsessive Compulsive Scale (Y-BOCS), Hamliton Rating Scale for Depression (HAM-D), Barratt's Impulsivity Scale (BIS-11), and Hamilton Rating Scale for Anxiety (HAM-A) were administered. Forty age and sex-matched healthy controls (HC) were recruited after screening with General Health Questionnaire 12 (GHQ-12). Serum lipids were assessed in both the groups. Results: Serum high density lipoproteins (HDL) (P < 0.001; partial η2 = 0.176) and apolipoprotein B (P < 0.001; partial η2 = 0.531) were significantly higher in OCD group than age- and sex-matched HC. A trend toward lower serum HDL (P = 0.06; partial η2 = 0.060) was observed among patients of OCD with high impulsivity. Serum HDL was negatively correlated with BIS attention (rs=-0.32; p = 0.03), BIS motor (rs= 0.40; P = 0.01), BIS non-planning (rs= -0.36; P = 0.02), and BIS total (rs= -0.36; P = 0.01) scores. Serum triglycerides (TG) (rs= 0.34; P = 0.03) and apolipoprotein B (rs= -0.32; P = 0.04) were negatively correlated with Y-BOCS compulsion score. Serum TG (rs= -0.45, P < 0.01) and serum very low density lipoprotein (VLDL) was negatively (rs= -0.39; P = 0.01) correlated with Y-BOCS total scores. Serum VLDL was positively (rs= 0.34; P = 0.03) correlated with BIS motor scores. Conclusions: Serum lipid fractions are deranged among patients with OCD. Different lipid fractions have different associations with clinical profiles of OCD. Impulsivity among patients with OCD may have a specific association with serum lipids. A small sample size, use of self-report measure without adaptation for impulsivity, a lack of metabolic profile assessment among participants, and a lack of assessment of impulsivity among HC were the limitations of our tudy.
Topical Neural Theorem Prover that Induces Rules

Various sub-symbolic approaches for reasoning and learning have been proposed in the literature. Among these approaches, the neural theorem prover ( NTP ) approach uses a backward chaining reasoning mechanism to guide a machine learning architecture to learn vector embedding representations of predicates and to induce ﬁrst-order clauses from a given knowledge base. NTP is however known for being not scalable, as the computation trees generated by the backward chaining process can grow exponentially with the size of the given knowledge base. In this paper we address this limitation by extending the NTP approach with a topic-based method for controlling the induction of ﬁrst-order clauses. Our proposed approach, called TNTP for Topical NTP , identiﬁes topic-based clusters over a large knowledge-base and uses these clusters to control the soft uniﬁcation of predicates during the learning process with the eﬀect of reducing the size of the computation tree needed to induce ﬁrst-order clauses. Our TNTP framework is capable of learning a diverse set of induced rules that have improved predictive accuracy, whilst reducing the computational time by several orders of magnitude. We demonstrated this by evaluating our approach on three diﬀerent datasets (UMLS, Kinship and Nations) and comparing our results with that of the NTP method, chosen here as our baseline.
WinoReg: A New Faster and More Accurate Metric of Hardness for Winograd Schemas

The Winograd Schema Challenge (WSC), the task of resolving pronouns in certain carefully-structured sentences, has received considerable interest in the past few years as an alternative to the Turing Test. In our recent work we demonstrated the plausibility of using commonsense knowledge, automatically acquired from raw text in English Wikipedia, towards computing a metric of hardness for a limited number of Winograd Schemas. In this work we present WinoReg , a new system to compute hardness of Winograd Schemas, by training a Random Forest classiﬁer over a rich set of features identiﬁed in relevant WSC works in the literature. Our empirical study shows that this new system is considerably faster and more accurate compared to the system proposed in our earlier work, making its use as part of other WSC-based systems feasible.
Feature representations using the reflected rectified linear unit (RReLU) activation

Deep Neural Networks (DNNs) have become the tool of choice for machine learning practitioners today. One important aspect of designing a neural network is the choice of the activation function to be used at the neurons of the different layers. In this work, we introduce a four-output activation function called the Reflected Rectified Linear Unit (RReLU) activation which considers both a feature and its negation during computation. Our activation function is “sparse”, in that only two of the four possible outputs are active at a given time. We test our activation function on the standard MNIST and CIFAR-10 datasets, which are classification problems, as well as on a novel Computational Fluid Dynamics (CFD) dataset which is posed as a regression problem. On the baseline network for the MNIST dataset, having two hidden layers, our activation function improves the validation accuracy from 0.09 to 0.97 compared to the well-known ReLU activation. For the CIFAR-10 dataset, we use a deep baseline network that achieves 0.78 validation accuracy with 20 epochs but overfits the data. Using the RReLU activation, we can achieve the same accuracy without overfitting the data. For the CFD dataset, we show that the RReLU activation can reduce the number of epochs from 100 (using ReLU) to 10 while obtaining the same levels of performance.
Toxicity of cyanobacteria to mosquito larvae―Screening of active compounds

To study toxicity of 76 laboratory-grown strains of planktonic cyanobacteria to mosquito larvae, hydrophilic and lipophilic cell-free extracts of cyanobacteria were incubated with larvae of the Aedes aegypti mosquito and death percentages were followed during 2 days. Toxicity was clearly associated with hepato - and neurotoxins of the samples. A strain of Microcystis aeruginosa was most effective, and caused death of the larvae due to a single hepatotoxin. Pure mammalian neurotoxin, anatoxin-a, was also toxic, and probably acted as a neurotoxin with the mosquito larvae.
TinyLink 2.0: integrating device, cloud, and client development for IoT applications

The recent years have witnessed the rapid growth of IoT (Internet of Things) applications. A typical IoT application usually consists of three essential parts: the device side, the cloud side, and the client side. The development of a complete IoT application is very difficult for non-expert developers because it involves drastically different technologies and complex interactions between different sides. Unlike traditional IoT development platforms which use separate approaches for these three sides, we present TinyLink 2.0, an integrated IoT development approach with a single coherent language. It achieves high expressiveness for diverse IoT applications by an enhanced IFTTT rule design and a virtual sensor mechanism which helps developers express application logic with machine learning. Moreover, TinyLink 2.0 optimizes the IoT application performance by using both static and dynamic optimizers, especially for resource-constrained IoT devices. We implement TinyLink 2.0 and evaluate it with eight case studies, a user study, and a detailed evaluation of the proposed programming language as well as the performance optimizers. Results show that TinyLink 2.0 can speed up IoT development significantly compared with existing approaches from both industry and academia, while still achieving high expressiveness.
Using a participatory activities toolkit to elicit privacy expectations of adaptive assistive technologies

Individuals whose abilities change over time can benefit from assistive technologies that can detect and adapt to their current needs. While these Adaptive Assistive Technologies (AATs) offer exciting opportunities, their use presents an often-overlooked privacy tradeoff between usability and disclosing ability data. To explore this tradeoff from end-user perspectives, we developed a participatory activities toolkit comprised of tangible low-fidelity physical cards, charts, and two software AAT prototypes. We used the kit in interviews with six older adults who experience pointing and typing difficulties when accessing the Internet. Participants had conflicting views about AATs collecting their data, and strong preferences about what data should be collected, how should it be used, and who should have access to it. The contributions of this paper are twofold: (1) we describe a novel approach to elicit detailed end-user privacy preferences and expectations, and (2) we provide insights from representative users of AATs towards their privacy.
Comparison of SSR and AFLP analysis for genetic diversity assessment of Ethiopian arabica coffee genotypes

Knowledge of genetic diversity within and among genotypes of any crop is fundamental for estimation of the potential genetic gain in a breeding programme and effective conservation of available genetic resources. Currently, different molecular marker techniques are being developed for measuring genetic diversity. Comparison among molecular marker techniques is important for effective marker selection. However such types of efforts are rare for arabica coffee. This study was conducted to compare the efficiency of simple sequence repeat (SSR) analysis for determining genetic relationships of 28 Coffea arabica L. genotypes collected from different parts of Ethiopia with work previously done using amplified fragment length polymorphism (AFLP) analysis. A total of 22 SSR fragments were amplified and compared with 712 previously amplified AFLP fragments. AFLP and SSR markers were positively and significantly correlated (0.217) in estimating genetic similarity among genotypes. The average genetic similarity coefficient calculated using SSR markers was much lower (0.560 with a range of 0.286–1.000) compared to AFLP markers (0.915 with a range of 0.860–0.982) indicating the higher information content of SSR markers. AFLP markers distinguished all genotypes, while SSR markers distinguished 64.3% of the genotypes. Results indicated that AFLP markers were more efficient compared to SSR markers for characterization of the evaluated coffee genotypes.