A Formulation for Active Learning with Applications to Object Detection

We discuss a formulation for active example selection for function learning problems. This formulation is obtained by adapting Fedorov's optimal experiment design to the learning problem. We specifically show how to analytically derive example selection algorithms for certain well defined function classes. We then explore the behavior and sample complexity of such active learning algorithms. Finally, we view object detection as a special case of function learning and show how our formulation reduces to a useful heuristic to choose examples to reduce the generalization error.

Regulation of topographic projection in the brain: Elf-1 in the hippocamposeptal system.

The hippocampus and septum play central roles in one of the most important spheres of brain function: learning and memory. Although their topographic connections have been known for two decades and topography may be critical for cognitive functions, the basis for hippocamposeptal topographic projection is unknown. We now report for the first time that Elf-1, a membrane-bound eph family ligand, is a candidate molecular tag for the genesis of the hippocamposeptal topographic projection. Elf-1 is expressed in an increasing gradient from dorsal to ventral septum. Furthermore, Elf-1 selectively allows growth of neurites from topographically appropriate lateral hippocampal neurons, while inhibiting neurite outgrowth by medial hippocampal neurons. Complementary to the expression of Elf-1, an eph family receptor, Bsk, is expressed in the hippocampus in a lateral to medial gradient, consistent with a function as a receptor for Elf-1. Further, Elf-1 specifically bound Bsk, eliciting tyrosine kinase activity. We conclude that the Elf-1/Bsk ligand-receptor pair exhibits traits of a chemoaffinity system for the organization of hippocamposeptal topographic projections.

A comparison of picture description abilities in individuals with vascular subcortical lesions and Huntington's Disease

The lexical-semantic and syntactic abilities of a group of individuals with chronic nonthalamic subcortical (NS) lesions following stroke (n = 6) were investigated using the Western Aphasia Battery (WAB) picture description task [Kertesz, A. (1982). The Western aphasia battery. New York: Grune and Stratton] and compared with those of a group of subjects with Huntington's Disease (HD) (n = 6) and a nonneurologically impaired control group (n = 6) matched for age, sex, and educational level. The performance of the NS and HD subjects did not differ significantly from the well controls on measures of lexical-semantic abilities. NS and HD subjects provided as much information about the target picture as control subjects, but produced fewer action information units. Analysis of syntactic abilities revealed that the HD subjects produced significantly more grammatical errors than both the NS and control subjects and that the NS group performed in a similar manner to control subjects. These findings are considered in terms of current theories of subcortical language function Learning outcomes: As a result of this activity, the reader will obtain information about the debate surrounding the role of subcortical language mechanisms and be provided with new information on the comparative picture description abilities of individuals with known vascular and degenerative subcortical pathologies and healthy control participants. (c) 2005 Elsevier Inc. All rights reserved.

Why people underestimate y when extrapolating in linear functions

E. L. DeLosh, J. R. Busemeyer, and M. A. McDaniel (1997) found that when learning a positive, linear relationship between a continuous predictor (x) and a continuous criterion (y), trainees tend to underestimate y on items that ask the trainee to extrapolate. In 3 experiments, the authors examined the phenomenon and found that the tendency to underestimate y is reliable only in the so-called lower extrapolation region-that is, new values of x that lie between zero and the edge of the training region. Existing models of function learning, such as the extrapolation-association model (DeLosh et al., 1997) and the population of linear experts model (M. L. Kalish, S. Lewandowsky, & J. Kruschke, 2004), cannot account for these results. The authors show that with minor changes, both models can predict the correct pattern of results.

Organização nuclear do sistema serotonérgico no encéfalo de morcegos Artibeus planirostris

Serotonin or 5-hydroxytryptamine (5-HT) is a substance found in many tissues of the body, including the nervous system acting as a neurotransmitter. Within the neuro-axis, the location of the majority of the 5-HT neurons is superimposed with raphe nuclei of the brain stem, in the median line or its vicinity, so that neuronal 5-HT can be considered a marker of the raphe nuclei. Serotonergic neurons are projected to almost all areas of the brain. Studies show the participation of serotonin in regulating the temperature, feeding behavior, sexual behavior, biological rhythms, sleep, locomotor function, learning, among others. The anatomy of these groups has been revised in many species, including mouse, rabbit, cat and primates, but never before in a bat species from South America. This study aimed to characterize the serotonergic clusters in the brain of the bat Artibeus planirostris through immunohistochemistry for serotonin. Seven adult bat males of Artibeus planirostris species (Microchiroptera, Mammalia) were used in this study. The animals were anesthetized, transcardially perfused and their brains were removed. Coronal sections of the frozen brain of bats were obtained in sliding microtome and subjected to immunohistochemistry for 5-HT. Delimit the caudal linear (CLi), dorsal (DR), median (MnR), paramedian (PMnR), pontine (PNR), magnus (MgR), pallidus (RPA) and obscurus (ROb) raphe nucleus, in addition to the groups B9 and rostral and caudal ventrolateral (RVL/CVL). The serotonergic groups of this kind of cheiroptera present morphology and cytoarchitecture relatively similar to that described in rodents and primates, confirming the phylogenetic stability of these cell clusters.

Modulation of Mediotemporal and Ventrostriatal Function in Humans by Delta 9-Tetrahydrocannabinol A Neural Basis for the Effects of Cannabis sativa on Learning and Psychosis

Context: Cannabis sativa use can impair verbal learning, provoke acute psychosis, and increase the risk of schizophrenia. It is unclear where C sativa acts in the human brain to modulate verbal learning and to induce psychotic symptoms. Objectives: To investigate the effects of 2 main psychoactive constituents of C sativa, Delta 9-tetrahydrocannabinol (Delta 9-THC) and cannabidiol, on regional brain function during verbal paired associate learning. Design: Subjects were studied on 3 separate occasions using a block design functional magnetic resonance imaging paradigm while performing a verbal paired associate learning task. Each imaging session was preceded by the ingestion of Delta 9-THC (10 mg), cannabidiol (600 mg), or placebo in a double-blind, randomized, placebo-controlled, repeated-measures, within-subject design. Setting: University research center. Participants: Fifteen healthy, native English-speaking, right-handed men of white race/ethnicity who had used C sativa 15 times or less and had minimal exposure to other illicit drugs in their lifetime. Main Outcome Measures: Regional brain activation ( blood oxygen level-dependent response), performance in a verbal learning task, and objective and subjective ratings of psychotic symptoms, anxiety, intoxication, and sedation. Results: Delta 9-Tetrahydrocannabinol increased psychotic symptoms and levels of anxiety, intoxication, and sedation, whereas no significant effect was noted on these parameters following administration of cannabidiol. Performance in the verbal learning task was not significantly modulated by either drug. Administration of Delta 9-THC augmented activation in the parahippocampal gyrus during blocks 2 and 3 such that the normal linear decrement in activation across repeated encoding blocks was no longer evident. Delta 9-Tetrahydrocannabinol also attenuated the normal time-dependent change in ventrostriatal activation during retrieval of word pairs, which was directly correlated with concurrently induced psychotic symptoms. In contrast, administration of cannabidiol had no such effect. Conclusion: The modulation of mediotemporal and ventrostriatal function by Delta 9-THC may underlie the effects of C sativa on verbal learning and psychotic symptoms, respectively.

Examining peer-controlled KR schedules during the learning of a movement-timing task as a function of task experience.

Learners can be provided with feedback in the form of knowledge of results (KR), under self-controlled and peer-controlled schedules. Recently, McRae, Hansen, and Patterson (2015), identified that inexperienced peers can provide KR that can facilitate motor skill acquisition. However, it is currently unknown whether previous task experience differentially impacts how peers present learners with KR and whether this KR impacts motor skill acquisition. In the present study, participants were randomly assigned to become inexperienced peer facilitators, learners with an inexperienced peer, learners with self-control who later became experienced peers, learners with an experienced peer, or learners in a control group. During acquisition learners completed a serial-timing task with a goal of 2500ms and returned approximately twenty four hours later for a delayed retention, time transfer, and pattern transfer test. We predicted that during the delayed tests, learners with self-control would outperform all other groups. Furthermore, we predicted that learners who received KR from experienced peers would outperform learners who received KR from inexperienced peers. However, our results indicated that participants who received peer-controlled and self-controlled KR schedules learned the task in an equivalent manner. Thus, our results are novel as they identify that inexperienced peers can provide KR that is as effective as KR provided by experienced peers and KR requested under self-controlled conditions.

A Learning Function for Parameter Reduction in Spiking Neural Networks with Radial Basis Function

Spiking neural networks - networks that encode information in the timing of spikes - are arising as a new approach in the artificial neural networks paradigm, emergent from cognitive science. One of these new models is the pulsed neural network with radial basis function, a network able to store information in the axonal propagation delay of neurons. Learning algorithms have been proposed to this model looking for mapping input pulses into output pulses. Recently, a new method was proposed to encode constant data into a temporal sequence of spikes, stimulating deeper studies in order to establish abilities and frontiers of this new approach. However, a well known problem of this kind of network is the high number of free parameters - more that 15 - to be properly configured or tuned in order to allow network convergence. This work presents for the first time a new learning function for this network training that allow the automatic configuration of one of the key network parameters: the synaptic weight decreasing factor.

Performance of children with learning difficulties in fine motor function and handwriting

This study aimed to compare and characterize the fine, sensory and perceptive function performance and handwriting quality between students with learning difficulties and students with good academic performance. Methods: This study comprised 192 students from 2nd to 4th grades, both genders, whose ages ranged from 7 to 11 years old. The students were distributed into: GI, GII, GIII and GIV, comprising 96 students with learning difficulties, and groups GV, GVI, GVII, GVIII comprising 96 students with good academic performance. The students were submitted to evaluation of fine motor, sensorial and perception functions and handwriting evaluation under dictation. Results: The results showed that the students with learning difficulties, from 1st to 3rd grade, had lower performance on tests of fine motor, sensory and perceptive function, when compared to the students with good academic performance in the same grade; the students from 4th grade, both groups, did not show changes on fine motor, sensory and perceptive function; and only the students of GII showed dysgraphia. Conclusions: the results presented in this study suggest that the qualitative aspects of fine motor, sensory and perceptive skills reflect the integrity and maturity of central nervous system and can probably play an important role in early diagnosis of development disorders and consequently prevent academic disorders such as handwriting performance.

Learning with Kernels on Graphs: DAG-based kernels, data streams and RNA function prediction.

In many application domains data can be naturally represented as graphs. When the application of analytical solutions for a given problem is unfeasible, machine learning techniques could be a viable way to solve the problem. Classical machine learning techniques are defined for data represented in a vectorial form. Recently some of them have been extended to deal directly with structured data. Among those techniques, kernel methods have shown promising results both from the computational complexity and the predictive performance point of view. Kernel methods allow to avoid an explicit mapping in a vectorial form relying on kernel functions, which informally are functions calculating a similarity measure between two entities. However, the definition of good kernels for graphs is a challenging problem because of the difficulty to find a good tradeoff between computational complexity and expressiveness. Another problem we face is learning on data streams, where a potentially unbounded sequence of data is generated by some sources. There are three main contributions in this thesis. The first contribution is the definition of a new family of kernels for graphs based on Directed Acyclic Graphs (DAGs). We analyzed two kernels from this family, achieving state-of-the-art results from both the computational and the classification point of view on real-world datasets. The second contribution consists in making the application of learning algorithms for streams of graphs feasible. Moreover,we defined a principled way for the memory management. The third contribution is the application of machine learning techniques for structured data to non-coding RNA function prediction. In this setting, the secondary structure is thought to carry relevant information. However, existing methods considering the secondary structure have prohibitively high computational complexity. We propose to apply kernel methods on this domain, obtaining state-of-the-art results.

Maternal and Postweaning High-Fat Diets Disturb Hippocampal Gene Expression, Learning, and Memory Function

We tested the hypothesis that excess saturated fat consumption during pregnancy, lactation, and/or postweaning alters the expression of genes mediating hippocampal synaptic efficacy and impairs spatial learning and memory in adulthood. Dams were fed control chow or a diet high in saturated fat before mating, during pregnancy, and into lactation. Offspring were weaned to either standard chow or a diet high in saturated fat. The Morris Water Maze was used to evaluate spatial learning and memory. Open field testing was used to evaluate motor activity. Hippocampal gene expression in adult males was measured using RT-PCR and ELISA. Offspring from high fat-fed dams took longer, swam farther, and faster to try and find the hidden platform during the 5-day learning period. Control offspring consuming standard chow spent the most time in memory quadrant during the probe test. Offspring from high fat-fed dams consuming excess saturated fat spent the least. The levels of mRNA and protein for brain-derived neurotrophic factor and activity-regulated cytoskeletal-associated protein were significantly decreased by maternal diet effects. Nerve growth factor mRNA and protein levels were significantly reduced in response to both maternal and postweaning high-fat diets. Expression levels for the N-methyl-D-aspartate receptor (NMDA) receptor subunit NR2B as well as synaptophysin were significantly decreased in response to both maternal and postweaning diets. Synaptotagmin was significantly increased in offspring from high fat-fed dams. These data support the hypothesis that exposure to excess saturated fat during hippocampal development is associated with complex patterns of gene expression and deficits in learning and memory.

Diffusion Gradient Temporal Difference for Cooperative Reinforcement Learning with Linear Function Approximation

We introduce a diffusion-based algorithm in which multiple agents cooperate to predict a common and global statevalue function by sharing local estimates and local gradient information among neighbors. Our algorithm is a fully distributed implementation of the gradient temporal difference with linear function approximation, to make it applicable to multiagent settings. Simulations illustrate the benefit of cooperation in learning, as made possible by the proposed algorithm.

Students’ understanding of the function-derivative relationship when learning economic concepts

The aim of this study is to characterise students’ understanding of the function-derivative relationship when learning economic concepts. To this end, we use a fuzzy metric (Chang 1968) to identify the development of economic concept understanding that is defined by the function-derivative relationship. The results indicate that the understanding of these economic concepts is linked to students’ capacity to perform conversions and treatments between the algebraic and graphic registers of the function-derivative relationship when extracting the economic meaning of concavity/convexity in graphs of functions using the second derivative.

A misspelt youth: Spelling and orthographic learning in university students as a function of spelling-sound consistency

Pseudowords with inconsistent vs. consistent spellings (e.g., nurch, with rhyme neighbours search, lurch & perch, vs. mish, with neighbours dish, wish) were presented with definitions for naming either twice or 6 times. In an oral spelling test, there were main and interactive effects of consistency and the number of training trials on accuracy and main effects only on response latency, with the improvement in accuracy from 2 to 6 training trials greater for the more poorly learned inconsistent items. Of most interest, the smaller effect of training on accuracy in the consistent condition was reliable; contrary to the most obvious prediction of dual route spelling models that the sublexical procedure should produce correct spellings for consistent items early in training. In a second task students wrote spellings of multisyllabic words containing unstressed indeterminate (schwa) vowels. In their errors on the schwa vowel, students showed sensitivity to the most common spelling overall but also they were influenced by differences in schwa spellings in English words as a function of the number of syllables and schwa position. These results indicate that dual route models of spelling will need to accommodate the consistency of spellings within categories defined by lexical structure variables.

Dynamics of on-line learning in radial basis function networks

On-line learning is examined for the radial basis function network, an important and practical type of neural network. The evolution of generalization error is calculated within a framework which allows the phenomena of the learning process, such as the specialization of the hidden units, to be analyzed. The distinct stages of training are elucidated, and the role of the learning rate described. The three most important stages of training, the symmetric phase, the symmetry-breaking phase, and the convergence phase, are analyzed in detail; the convergence phase analysis allows derivation of maximal and optimal learning rates. As well as finding the evolution of the mean system parameters, the variances of these parameters are derived and shown to be typically small. Finally, the analytic results are strongly confirmed by simulations.