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We present a neural network model that can execute some of the procedures used in the information sciences literature. In particular we offer a simplified notion of topic and how to implement it using neural networks that use the Kronecker tensor product. We show that the topic detecting mechanism is related to Naive Bayes statistical classifiers, and that it is able to disambiguate the meaning of polysemous words. We evaluate our network in a text categorization task, resulting in performance levels comparable to Naive Bayes classifiers, as expected. Hence, we propose a simple scalable neural model capable of dealing with machine learning tasks, while retaining biological plausibility and probabilistic transparency.

Numerous cortical disorders affect language. We explore the connection between the observed language behavior and the underlying substrates by adopting a neurocomputational approach. To represent the observed trajectories of the discourse in patients with disorganized speech and in healthy participants, we design a graphical representation for the discourse as a trajectory that allows us to visualize and measure the degree of order in the discourse as a function of the disorder of the trajectories. Our work assumes that many of the properties of language production and comprehension can be understood in terms of the dynamics of modular networks of neural associative memories. Based upon this assumption, we connect three theoretical and empirical domains: (1) neural models of language processing and production, (2) statistical methods used in the construction of functional brain images, and (3) corpus linguistic tools, such as Latent Semantic Analysis (henceforth LSA), that are used to discover the topic organization of language. We show how the neurocomputational models intertwine with LSA and the mathematical basis of functional neuroimaging. Within this framework we describe the properties of a context-dependent neural model, based on matrix associative memories, that performs goal-oriented linguistic behavior. We link these matrix associative memory models with the mathematics that underlie functional neuroimaging techniques and present the "functional brain images" emerging from the model. This provides us with a completely "transparent box" with which to analyze the implication of some statistical images. Finally, we use these models to explore the possibility that functional synaptic disconnection can lead to an increase in connectivity between the representations of concepts that could explain some of the alterations in discourse displayed by patients with schizophrenia.

Background and aims Several epidemiological studies highlighted the association between folate and B-vitamins low intake and cardiovascular diseases (CVD) risk. Contrasting results were reported on the relationship between folate intake and DNA-methylation. Folate and B-vitamins may modulate DNA-methylation of specific enzymes which are included in the One-Carbon Metabolism (OCM) and in the homocysteine (Hcy) pathways. The aim of the study was to evaluate whether DNA-methylation profiles of OCM and Hcy genes could modulate the myocardial infarction (MI) risk conferred by a low B-vitamins intake. Methods and results Study sample (206 MI cases and 206 matched controls) is a case-control study nested in the prospective EPIC cohort. Methylation levels of 33 candidate genes where extracted by the whole epigenome analysis (Illumina-HumanMethylation450K-BeadChip). We identified three differentially methylated regions in males (TCN2 promoter, CBS 5′UTR, AMT gene-body) and two in females (PON1 gene-body, CBS 5′UTR), each of them characterized by an increased methylation in cases. Functional in silico analysis suggested a decreased expression in cases. A Recursively Partitioned Mixture Model cluster algorithm identified distinct methylation profiles associated to different MI risk: high-risk vs. low-risk methylation profile groups, OR = 3.49, p = 1.87 × 10 − 4 and OR = 3.94, p = 0.0317 in males and females respectively (multivariate logistic regression adjusted for classical CVD risk factors). Moreover, a general inverse relationship between B-vitamins intake and DNA-methylation of the candidate genes was observed. Conclusions Our findings support the hypothesis that DNA-methylation patterns in specific regions of OCM and Hcy pathways genes may modulate the CVD risk conferred by folate and B-vitamins low intake.

OBJECTIVES: This prospective, randomized, experimental study with rats aimed to investigate the influence of general treatment strategies on the motor recovery of Wistar rats with moderate contusive spinal cord injury. METHODS: A total of 51 Wistar rats were randomized into five groups: control, maze, ramp, runway, and sham (laminectomy only). The rats underwent spinal cord injury at the T9-T10 levels using the NYU-Impactor. Each group was trained for 12 minutes twice a week for two weeks before and five weeks after the spinal cord injury, except for the control group. Functional motor recovery was assessed with the Basso, Beattie, and Bresnahan Scale on the first postoperative day and then once a week for five weeks. The animals were euthanized, and the spinal cords were collected for histological analysis. RESULTS: Ramp and maze groups showed an earlier and greater functional improvement effect than the control and runway groups. However, over time, unexpectedly, all of the groups showed similar effects as the control group, with spontaneous recovery. There were no histological differences in the injured area between the trained and control groups. CONCLUSION: Short-term benefits can be associated with a specific training regime; however, the same training was ineffective at maintaining superior long-term recovery. These results might support new considerations before hospital discharge of patients with spinal cord injuries.

Several psychiatric and neurological conditions affect the semantic organization and content of a patient's speech. Specifically, the discourse of patients with schizophrenia is frequently characterized as lacking coherence. The evaluation of disturbances in discourse is often used in diagnosis and in assessing treatment efficacy, and is an important factor in prognosis. Measuring these deviations, such as “loss of meaning” and incoherence, is difficult and requires substantial human effort. Computational procedures can be employed to characterize the nature of the anomalies in discourse. We present a set of new tools derived from network theory and information science that may assist in empirical and clinical studies of communication patterns in patients, and provide the foundation for future automatic procedures. First we review information science and complex network approaches to measuring semantic coherence, and then we introduce a representation of discourse that allows for the computation of measures of disorganization. Finally we apply these tools to speech transcriptions from patients and a healthy participant, illustrating the implications and potential of this novel framework.

An in situ manipulative experiment was carried out to study the effect of SCUBA diving on the Halocynthia papillosa species and determine its utility as a bioindicator for this activity. Five experimental flapping impact intensities were considered: 0 (control), 3, 90, 270 and 330 flaps. Two experimental units, each with ten individuals, were assigned at random for each treatment. On each experimental unit, ten circular sediment traps were placed and then collected 24 h after the experimental flapping event for subsequent analysis. The total abundance and survival of individuals of each size in each experimental unit were measured at eight time intervals: before the experiment and then 24 h, 1 week, and 1, 3, 6, 9 and 12 months later. Repeated measures ANOVA were used to test the differences between treatments over time. In the three most impacted sites, a reduction in the number of individuals was observed, with higher lethality rates in smaller individuals. Furthermore, in the two most impacted sites, the surviving individuals did not grow. A high negative correlation was observed between the abundance of individuals and the number of flaps (R 2 = 0.96). The general regression model reflected a high correlation between the abundance of individuals and the sediment fractions considered. Our results indicate that the resuspension of sediments produced by flapping may explain the decrease of H. papillosa abundance that has been observed in areas of high diving intensity.

Summary Background On the basis of the published literature, it is still difficult to draw conclusions as to whether picobirnavirus (PBV) circulation is influenced by host species restriction. Objective To provide data regarding the genetic relatedness between porcine and human PBV strains present in Argentina as a means of defining the host range and epidemiology of these viruses. Methods Fecal specimens ( n = 74) collected from kidney transplant patients ( n = 55) and piglets ( n = 19) were analyzed by RT-PCR using primers designed to amplify the porcine PBV genomic segment 2. Amplified sequences were further examined phylogenetically. Results By RT-PCR amplification 14 of 74 samples rendered amplicons of the expected 282 base pair size (8 detected from humans and 6 from pigs). Eleven amplicons (5 from humans and 6 from pigs) were selected for sequencing and subjected to phylogenetic analysis. The eleven amplicons revealed similarities between human and porcine viral sequences that ranged between 94.7 and 100% in identity. Phylogenetic analysis identified these 11 strains as PBV genogroup I-related strains and showed that they grouped as a single separate clade distinct from other PBV strains detected in humans and porcine from other countries. Conclusions The present study suggests that closely related PBV strains infect both pigs and humans in Argentina and that the epidemiology of PBVs is not species restricted.

Many lines of evidence indicate that theta rhythm, a prominent neural oscillatory mode found in the mammalian hippocampus, plays a key role in the acquisition, processing, and retrieval of memories. However, a predictive neurophysiological feature of the baseline theta rhythm that correlates with the learning rate across different animals has yet to be identified. Here we show that the mean theta rhythm speed observed during baseline periods of immobility has a strong positive correlation with the rate at which rats learn an operant task. This relationship is observed across rats, during both quiet waking (r=0.82; p

Objective The preliminary results of noninvasive brain stimulation for epilepsy treatment have been encouraging, but mixed. Two important factors may contribute to this heterogeneity: the altered brain physiology of patients with epilepsy and the variable presence of antiepileptic drugs. Therefore, we aimed to study the effects of 1 Hz rTMS on corticospinal excitability in patients with juvenile myoclonic epilepsy (JME) in two different conditions: low- or high-plasma valproate levels. Methods Fifteen patients with JME and 12 age-matched healthy subjects participated in this study. Corticospinal excitability before and after 1 Hz rTMS was assessed in JME patients with low- and high-plasma valproate levels; and these results were compared with those in healthy subjects. Results In patients with chronic use of valproate and low-plasma concentrations, 1 Hz rTMS had a similar significant inhibitory effect on corticospinal excitability as in healthy subjects. However, in the same patients when the serum valproate concentration was high, 1 Hz rTMS increased the corticospinal excitability significantly. In addition, there was a significant positive correlation between plasma valproate levels and the motor threshold changes after 1 Hz rTMS. Conclusions Our findings can be accounted for by mechanisms of homeostatic plasticity and illustrate the dependency of the modulatory effects of rTMS on the physiologic state of the targeted brain cortex. Significance The therapeutic use of rTMS in epilepsy should take into consideration the interaction between rTMS and drugs that change cortical excitability.

The development of neural network models has greatly enhanced the comprehension of cognitive phenomena. Here, we show that models using multiplicative processing of inputs are both powerful and simple to train and understand. We believe they are valuable tools for cognitive explorations. Our model can be viewed as a subclass of networks built on sigma-pi units and we show how to derive the Kronecker product representation from the classical sigma-pi unit. We also show how the connectivity requirements of the Kronecker product can be relaxed considering statistical arguments. We use the multiplicative network to implement what we call an Elman topology, that is, a simple recurrent network (SRN) that supports aspects of language processing. As an application, we model the appearance of hallucinated voices after network damage, and show that we can reproduce results previously obtained with SRNs concerning the pathology of schizophrenia.

Magnetic resonance imaging (MRI) experiments were used to detect and monitor the progression of internal browning (IB) in Fuji apples ( Malus domestica Borkh. ). The apples were stored in two different controlled atmosphere (CA) conditions: 3% CO 2 at 0°C and 18% CO 2 at 20°C. The apples stored under 18% CO 2 , were imaged at 1, 3, 5, 7 and 9 days. Apples stored under 3% CO 2 were imaged once a week for the first 7 weeks and then every 2 weeks until the 12th week. Three distinct regions were identified in the MR images of apples with internal browning: normal, light brown and dark brown tissue. Light brown regions, more prominent in apples stored in 3% CO 2 at 0°C, had a lower signal intensity than normal tissue because of lower proton density (PD) and smaller transverse relaxation times ( T 2 ). Dark brown regions predominated in apples stored in 18% CO 2 at 20°C and displayed higher signal intensity than the normal apple tissue because of larger T 2 values. The speed of image acquisition was improved from 5.5 min to 20 s, by reducing the spatial resolution of the images. Both types of IB were detected by images acquired using coarse spatial resolution and correlated well to the IB detected by the images acquired using fine spatial resolution.