Implementing statistical learning methods through Bayesian networks (Part 2): bayesian evaluations for results of black toner analyses in forensic document examination

This paper presents and discusses the use of Bayesian procedures - introduced through the use of Bayesian networks in Part I of this series of papers - for 'learning' probabilities from data. The discussion will relate to a set of real data on characteristics of black toners commonly used in printing and copying devices. Particular attention is drawn to the incorporation of the proposed procedures as an integral part in probabilistic inference schemes (notably in the form of Bayesian networks) that are intended to address uncertainties related to particular propositions of interest (e.g., whether or not a sample originates from a particular source). The conceptual tenets of the proposed methodologies are presented along with aspects of their practical implementation using currently available Bayesian network software.

Learning spatial filters for multispectral image segmentation

We present a novel filtering method for multispectral satellite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments carried out on multiclass one-against-all classification and target detection show the capabilities of the learned spatial filters.

Decoding sequence learning from single-trial intracranial EEG in humans.

We propose and validate a multivariate classification algorithm for characterizing changes in human intracranial electroencephalographic data (iEEG) after learning motor sequences. The algorithm is based on a Hidden Markov Model (HMM) that captures spatio-temporal properties of the iEEG at the level of single trials. Continuous intracranial iEEG was acquired during two sessions (one before and one after a night of sleep) in two patients with depth electrodes implanted in several brain areas. They performed a visuomotor sequence (serial reaction time task, SRTT) using the fingers of their non-dominant hand. Our results show that the decoding algorithm correctly classified single iEEG trials from the trained sequence as belonging to either the initial training phase (day 1, before sleep) or a later consolidated phase (day 2, after sleep), whereas it failed to do so for trials belonging to a control condition (pseudo-random sequence). Accurate single-trial classification was achieved by taking advantage of the distributed pattern of neural activity. However, across all the contacts the hippocampus contributed most significantly to the classification accuracy for both patients, and one fronto-striatal contact for one patient. Together, these human intracranial findings demonstrate that a multivariate decoding approach can detect learning-related changes at the level of single-trial iEEG. Because it allows an unbiased identification of brain sites contributing to a behavioral effect (or experimental condition) at the level of single subject, this approach could be usefully applied to assess the neural correlates of other complex cognitive functions in patients implanted with multiple electrodes.

Sex differences: From mental rotation to object location memory, an ERP study

Sex differences in cognition have been largely investigated. The most consistent sex differences favoring females are observed in object location memory involving the left hemisphere whereas the most consistent sex differences favoring males are observed in tasks that require mental rotation involving the right hemisphere. Here we used a task involving these two abilities to see the impact of mental rotation on object location memory. To that end we used a combination of behavioral and event-related potential (ERP) electroencephalography (EEG) measures.A computer screen displayed a square frame of 4 pairs of images (a "teddy" bear, a shoe, an umbrella and a lamp) randomly arranged around a central fixation cross. After a 10-second interval for memorization, images disappeared and were replaced by a test frame with no image but a random pair of two locations marked in black. In addition, this test frame was randomly displayed either in the original orientation (0° rotation) or in the rotated one (90° clockwise - CW - or 90° counterclockwise - CCW). Preceding the test frame, an arrow indicating the presence or the absence of rotation of the frame was displayed on the screen. The task of the participants (15 females and 15 males) was to determine if two marked locations corresponded or not to a pair of identical images. Each response was followed by feedback.Findings showed no significant sex differences in the performance of the original orientation. In comparison with this position, the rotation of the frame produced an equal decrease of male and female performance. In addition, this decrease was significantly higher when the rotation of the frame was in a CCW direction. We further assessed the ERP when the arrow indicated the direction of rotation as stimulus-onset, during four time windows representing major components C1, P1, N1 and N2. Although no sex differences were observed in performance, brain activities differed according to sex. Enhanced amplitudes were found for the CCW compared to CW rotation over the right posterior areas for the P1, N1 and N2 components for men as well as for women. Major topographical differences related to sex were measured for the CW rotation condition as marked lateralized amplitude: left-hemisphere amplitude larger than right one was measured during P1 time range for men. These similar patterns prolonged from P1 to N1 for women. Early distinctions were found in interaction with sex between CCW and CW waveform amplitudes, expressing over anterior electrode sites during C1 time range (0-50 ms post-stimulus).In conclusion (i) women do not outperform men in object location memory in this study (absence of rotation condition); (ii) mental rotation, in particular the direction of rotation, influences performance on object location memory; (iii) CCW rotation is associated with activity in the right parietal hemisphere whereas the CW rotation involves the left parietal hemisphere; (iv) this last effect is less pronounced in males, which could explain why greater involvement of right parietal areas in men and of bilateral posterior areas in women is generally reported in mental rotation tasks; and (v) the early distinctions between both directions of rotation located over anterior sites could be related to sex differences in their respective involvement of control mechanisms.

The influence of learning on evolution: a mathematical framework.

The Baldwin effect can be observed if phenotypic learning influences the evolutionary fitness of individuals, which can in turn accelerate or decelerate evolutionary change. Evidence for both learning-induced acceleration and deceleration can be found in the literature. Although the results for both outcomes were supported by specific mathematical or simulation models, no general predictions have been achieved so far. Here we propose a general framework to predict whether evolution benefits from learning or not. It is formulated in terms of the gain function, which quantifies the proportional change of fitness due to learning depending on the genotype value. With an inductive proof we show that a positive gain-function derivative implies that learning accelerates evolution, and a negative one implies deceleration under the condition that the population is distributed on a monotonic part of the fitness landscape. We show that the gain-function framework explains the results of several specific simulation models. We also use the gain-function framework to shed some light on the results of a recent biological experiment with fruit flies.

Time Series Input Selection using Multiple Kernel Learning

In this paper we study the relevance of multiple kernel learning (MKL) for the automatic selection of time series inputs. Recently, MKL has gained great attention in the machine learning community due to its flexibility in modelling complex patterns and performing feature selection. In general, MKL constructs the kernel as a weighted linear combination of basis kernels, exploiting different sources of information. An efficient algorithm wrapping a Support Vector Regression model for optimizing the MKL weights, named SimpleMKL, is used for the analysis. In this sense, MKL performs feature selection by discarding inputs/kernels with low or null weights. The approach proposed is tested with simulated linear and nonlinear time series (AutoRegressive, Henon and Lorenz series).

Sex differences: From mental rotation to object location memory, an ERP study

Sex differences in cognition have been largely investigated. The most consistent sex differences favoring females are observed in object location memory involving the left hemisphere whereas the most consistent sex differences favoring males are observed in tasks that require mental rotation involving the right hemisphere. Here we used a task involving these two abilities to see the impact of mental rotation on object location memory. To that end we used a combination of behavioral and event-related potential (ERP) electroencephalography (EEG) measures.A computer screen displayed a square frame of 4 pairs of images (a "teddy" bear, a shoe, an umbrella and a lamp) randomly arranged around a central fixation cross. After a 10-second interval for memorization, images disappeared and were replaced by a test frame with no image but a random pair of two locations marked in black. In addition, this test frame was randomly displayed either in the original orientation (0° rotation) or in the rotated one (90° clockwise - CW - or 90° counterclockwise - CCW). Preceding the test frame, an arrow indicating the presence or the absence of rotation of the frame was displayed on the screen. The task of the participants (15 females and 15 males) was to determine if two marked locations corresponded or not to a pair of identical images. Each response was followed by feedback.Findings showed no significant sex differences in the performance of the original orientation. In comparison with this position, the rotation of the frame produced an equal decrease of male and female performance. In addition, this decrease was significantly higher when the rotation of the frame was in a CCW direction. We further assessed the ERP when the arrow indicated the direction of rotation as stimulus-onset, during four time windows representing major components C1, P1, N1 and N2. Although no sex differences were observed in performance, brain activities differed according to sex. Enhanced amplitudes were found for the CCW compared to CW rotation over the right posterior areas for the P1, N1 and N2 components for men as well as for women. Major topographical differences related to sex were measured for the CW rotation condition as marked lateralized amplitude: left-hemisphere amplitude larger than right one was measured during P1 time range for men. These similar patterns prolonged from P1 to N1 for women. Early distinctions were found in interaction with sex between CCW and CW waveform amplitudes, expressing over anterior electrode sites during C1 time range (0-50 ms post-stimulus).In conclusion (i) women do not outperform men in object location memory in this study (absence of rotation condition); (ii) mental rotation, in particular the direction of rotation, influences performance on object location memory; (iii) CCW rotation is associated with activity in the right parietal hemisphere whereas the CW rotation involves the left parietal hemisphere; (iv) this last effect is less pronounced in males, which could explain why greater involvement of right parietal areas in men and of bilateral posterior areas in women is generally reported in mental rotation tasks; and (v) the early distinctions between both directions of rotation located over anterior sites could be related to sex differences in their respective involvement of control mechanisms.