kLog: A Language for Logical and Relational Learning with Kernels

We introduce kLog, a novel approach to statistical relational learning. Unlike standard approaches, kLog does not represent a probability distribution directly. It is rather a language to perform kernel-based learning on expressive logical and relational representations. kLog allows users to specify learning problems declaratively. It builds on simple but powerful concepts: learning from interpretations, entity/relationship data modeling, logic programming, and deductive databases. Access by the kernel to the rich representation is mediated by a technique we call graphicalization: the relational representation is first transformed into a graph --- in particular, a grounded entity/relationship diagram. Subsequently, a choice of graph kernel defines the feature space. kLog supports mixed numerical and symbolic data, as well as background knowledge in the form of Prolog or Datalog programs as in inductive logic programming systems. The kLog framework can be applied to tackle the same range of tasks that has made statistical relational learning so popular, including classification, regression, multitask learning, and collective classification. We also report about empirical comparisons, showing that kLog can be either more accurate, or much faster at the same level of accuracy, than Tilde and Alchemy. kLog is GPLv3 licensed and is available at http://klog.dinfo.unifi.it along with tutorials

Neural Correlate of Filtering of Irrelevant Information from Visual Working Memory

In a dynamic environment stimulus task relevancy could be altered through time and it is not always possible to dissociate relevant and irrelevant objects from the very first moment they come to our sight. In such conditions, subjects need to retain maximum possible information in their WM until it is clear which items should be eliminated from WM to free attention and memory resources. Here, we examined the neural basis of irrelevant information filtering from WM by recording human ERP during a visual change detection task in which the stimulus irrelevancy was revealed in a later stage of the task forcing the subjects to keep all of the information in WM until test object set was presented. Assessing subjects' behaviour we found that subjects' RT was highly correlated with the number of irrelevant objects and not the relevant one, pointing to the notion that filtering, and not selection, process was used to handle the distracting effect of irrelevant objects. In addition we found that frontal N150 and parietal N200 peak latencies increased systematically as the amount of irrelevancy load increased. Interestingly, the peak latency of parietal N200, and not frontal N150, better correlated with subjects' RT. The difference between frontal N150 and parietal N200 peak latencies varied with the amount of irrelevancy load suggesting that functional connectivity between modules underlying fronto-parietal potentials vary concomitant with the irrelevancy load. These findings suggest the existence of two neural modules, responsible for irrelevant objects elimination, whose activity latency and functional connectivity depend on the number of irrelevant object

Pre-Stimulus Activity Predicts the Winner of Top-Down vs. Bottom-Up Attentional Selection

Our ability to process visual information is fundamentally limited. This leads to competition between sensory information that is relevant for top-down goals and sensory information that is perceptually salient, but task-irrelevant. The aim of the present study was to identify, from EEG recordings, pre-stimulus and pre-saccadic neural activity that could predict whether top-down or bottom-up processes would win the competition for attention on a trial-by-trial basis. We employed a visual search paradigm in which a lateralized low contrast target appeared alone, or with a low (i.e., non-salient) or high contrast (i.e., salient) distractor. Trials with a salient distractor were of primary interest due to the strong competition between top-down knowledge and bottom-up attentional capture. Our results demonstrated that 1) in the 1-sec pre-stimulus interval, frontal alpha (8–12 Hz) activity was higher on trials where the salient distractor captured attention and the first saccade (bottom-up win); and 2) there was a transient pre-saccadic increase in posterior-parietal alpha (7–8 Hz) activity on trials where the first saccade went to the target (top-down win). We propose that the high frontal alpha reflects a disengagement of attentional control whereas the transient posterior alpha time-locked to the saccade indicates sensory inhibition of the salient distractor and suppression of bottom-up oculomotor capture

Transcranial Magnetic Stimulation Intensities in Cognitive Paradigms

BACKGROUND: Transcranial magnetic stimulation (TMS) has become an important experimental tool for exploring the brain's functional anatomy. As TMS interferes with neural activity, the hypothetical function of the stimulated area can thus be tested. One unresolved methodological issue in TMS experiments is the question of how to adequately calibrate stimulation intensities. The motor threshold (MT) is often taken as a reference for individually adapted stimulation intensities in TMS experiments, even if they do not involve the motor system. The aim of the present study was to evaluate whether it is reasonable to adjust stimulation intensities in each subject to the individual MT if prefrontal regions are stimulated prior to the performance of a cognitive paradigm. METHODS AND FINDINGS: Repetitive TMS (rTMS) was applied prior to a working memory task, either at the 'fixed' intensity of 40% maximum stimulator output (MSO), or individually adapted at 90% of the subject's MT. Stimulation was applied to a target region in the left posterior middle frontal gyrus (pMFG), as indicated by a functional magnetic resonance imaging (fMRI) localizer acquired beforehand, or to a control site (vertex). Results show that MT predicted the effect size after stimulating subjects with the fixed intensity (i.e., subjects with a low MT showed a greater behavioral effect). Nevertheless, the individual adaptation of intensities did not lead to stable effects. CONCLUSION: Therefore, we suggest assessing MT and account for it as a measure for general cortical TMS susceptibility, even if TMS is applied outside the motor domain

The effects of rTMS on impulsivity in normal adults: a systematic review and meta-analysis

Background: Impulsivity is a multi-dimensional construct that is regarded as a symptom of many psychiatric disorders. Harm resulting from impulsive behaviour can be substantial for the individuals concerned, people around them and the society they live in. Therefore, the importance of developing therapeutic interventions to target impulsivity is paramount. Aims and methods: We conducted a systematic review and meta-analysis of the literature from AMED, Embase, Medline, and PsycINFO databases on the use of repetitive transcranial magnetic stimulation (rTMS) in healthy adults to modulate different subdomains (motor, temporal and reflection) of impulsivity. Results: The results indicated that rTMS has distinct effects on different impulsivity subdomains. It has a significant, albeit small, effect on modulating motor impulsivity (g = 0.30, 95% CI, 0.17 to 0.43, p < .001) and a moderate effect on temporal impulsivity (g = 0.59, 95% CI, 0.32 to 0.86, p < .001). Subgroup analyses (e.g., excitatory vs. inhibitory rTMS, conventional rTMS vs. theta burst stimulation, analyses by stimulation sites, and type of outcome measure used) identified key parameters associated with the effects of rTMS on motor and temporal impulsivity. Age, sex, stimulation intensity and the number of pulses were not significant moderators for effects of rTMS on motor impulsivity. Due to lack of sufficient data to inform a meta-analysis, it has not been possible to assess the effects of rTMS on reflection impulsivity. Conclusions: The present findings provide preliminary evidence that rTMS can be used to modulate motor and temporal impulsivity in healthy individuals. Further studies are required to extend the use of rTMS to modulate impulsivity in those at most risk of engaging in harmful behaviour as a result of impulsivity, such as patients with offending histories and those with a history of self-harming behaviour

Autonomous Agents Modelling Other Agents: A Comprehensive Survey and Open Problems

Much research in artificial intelligence is concerned with the development of autonomous agents that can interact effectively with other agents. An important aspect of such agents is the ability to reason about the behaviours of other agents, by constructing models which make predictions about various properties of interest (such as actions, goals, beliefs) of the modelled agents. A variety of modelling approaches now exist which vary widely in their methodology and underlying assumptions, catering to the needs of the different sub-communities within which they were developed and reflecting the different practical uses for which they are intended. The purpose of the present article is to provide a comprehensive survey of the salient modelling methods which can be found in the literature. The article concludes with a discussion of open problems which may form the basis for fruitful future research.Comment: Final manuscript (46 pages), published in Artificial Intelligence Journal. The arXiv version also contains a table of contents after the abstract, but is otherwise identical to the AIJ version. Keywords: autonomous agents, multiagent systems, modelling other agents, opponent modellin

The role of the angular gyrus in visual conjunction search investigated using signal detection analysis and transcranial magnetic stimulation.

Transcranial magnetic stimulation (TMS) delivered over the posterior parietal cortex increases choice reaction times in visual search for a target defined by a conjunction of features. Some recent studies of visual search have taken an approach based on signal detection theory, the findings of which are not addressed by studying the disruptive effects of TMS on reaction time. Here we investigated the role of the posterior parietal cortex in visual search by applying TMS while subjects performed unspeeded feature and conjunction visual search tasks matched for level of difficulty. TMS over the right, but not the left angular gyrus (AG) in the parietal cortex, nor vertex decreased subjects' sensitivity on the conjunction but not the feature search task, as measured by the signal detection measure, d'. Changes in bias, specifically the tendency to make false positive responses, were less clear. We consider the findings in terms of four possible explanation: binding, attentional control, spatial localisation and visuomotor co-ordinate transformations