Driven by Compression Progress: A Simple Principle Explains Essential Aspects of Subjective Beauty, Novelty, Surprise, Interestingness, Attention, Curiosity, Creativity, Art, Science, Music, Jokes

I argue that data becomes temporarily interesting by itself to some self-improving, but computationally limited, subjective observer once he learns to predict or compress the data in a better way, thus making it subjectively simpler and more beautiful. Curiosity is the desire to create or discover more non-random, non-arbitrary, regular data that is novel and surprising not in the traditional sense of Boltzmann and Shannon but in the sense that it allows for compression progress because its regularity was not yet known. This drive maximizes interestingness, the first derivative of subjective beauty or compressibility, that is, the steepness of the learning curve. It motivates exploring infants, pure mathematicians, composers, artists, dancers, comedians, yourself, and (since 1990) artificial systems.Comment: 35 pages, 3 figures, based on KES 2008 keynote and ALT 2007 / DS 2007 joint invited lectur

Time Preference and Its Relationship with Age, Health, and Survival Probability

Although theories from economics and evolutionary biology predict that one’s age, health, and survival probability should be associated with one’s subjective discount rate (SDR), few studies have empirically tested for these links. Our study analyzes in detail how the SDR is related to age, health, and survival probability, by surveying a sample of individuals in townships around Durban, South Africa. In contrast to previous studies, we find that age is not significantly related to the SDR, but both physical health and survival expectations have a U-shaped relationship with the SDR. Individuals in very poor health have high discount rates, and those in very good health also have high discount rates. Similarly, those with expected survival probability on the extremes have high discount rates. Therefore, health and survival probability, and not age, seem to be predictors of one’s SDR in an area of the world with high morbidity and mortality.subjective discount rate; delay discounting; expected survival probability; health; age; South Africa

Neuropsychiatric and cognitive symptoms in Parkinson’s disease: the contribution to subtype classification, to differential diagnosis, their clinical and instrumental correlations

Il piano di ricerca è volto ad approfondire il contributo dei sintomi neuropsichiatrici e cognitivi nelle diverse fasi della Malattia di Parkinson (MP). In particolare, l’argomento di studio è focalizzato sull’analisi dei sintomi cognitivi e neuropsichiatrici nella MP, affrontando queste tematiche anche mediante l’utilizzo di tecniche di neuroimaging, in pazienti drug-naïve, in fase precoce di malattia ed in fase avanzata. Nei pazienti drug-naïve, la ricerca è stata finalizzata alla caratterizzazione dei sintomi neuropsichiatrici e cognitivi nei sottotipi motori (i.e., tremorigeni vs acinetico-rigidi) e rispetto alla lateralità di esordio degli stessi (i.e., lateralità destra vs lateralità sinistra). Nei pazienti in fase precoce di malattia, è stato indagato il contributo dei sintomi neuropsichiatrici e cognitivi nella diagnosi differenziale tra MP e Paralisi Sopranucleare Progressiva (PSP) in pazienti valutati entro i 24 mesi dall’esordio motorio, finestra temporale in cui spesso si assiste ad un overlapping dei sintomi motori. Nei pazienti in fase avanzata di malattia, la ricerca è stata finalizzata alla caratterizzazione, mediante i sintomi neuropsichiatrici e cognitivi, del Gioco D’Azzardo Patologico (gambling) rispetto agli altri tipi di Disturbi del controllo degli Impulsi (ICDs). Ancora nell’ambito dell’ICDs, è stato sviluppato uno studio di neuroimaging, volto ad identificare i correlati morfostrutturali (spessori corticali e volumi dei nuclei sottocorticali) di tali disturbi. Infine, si sono identificati i sintomi neuropsichiatrici e cognitivi che possono impedire l’esecuzione di un esame di Risonanza Magnetica (RM), al fine, in ambito clinico, di preparare adeguatamente all’esame i pazienti più a rischio di mancato svolgimento e con l’intento di indagare, in ambito di ricerca, la reale rappresentatività campionaria dei pazienti inseriti in studi di RM

Abnormal approach-related motivation but spared reinforcement learning in MDD : evidence from fronto-midline Theta oscillations and frontal Alpha asymmetry

Major depression is characterized by abnormal reward processing and reinforcement learning (RL). This impairment might stem from deficient motivation processes, in addition to reduced reward sensitivity. In this study, we recorded 64-channel EEG in a large cohort of major depressive disorder (MDD) patients and matched healthy controls (HC) while they performed a standard RL task. Participants were asked to discover, by trial and error, several hidden stimulus-response associations having different reward probabilities, as enforced using evaluative feedback. We extracted induced fronto-midline Theta (FMT) power time-locked to the response and feedback as neurophysiological index of RL. Furthermore, we assessed approach-related motivation by measuring frontal alpha asymmetry concurrently. At the behavioral level, MDD patients and HCs showed comparable RL. At the EEG level, FMT power systematically varied as a function of reward probability, with opposing effects found at the response and feedback levels. Although this global pattern was spared in MDD, at the feedback level these patients showed however a steep FMT power decrease across trials when reward probability was low. Moreover, they showed impaired approach-related motivation during task execution, as reflected by frontal Alpha asymmetry. These results suggest a dissociation between (globally spared) RL and (impaired) approach motivation in MDD

An Investigation of Predictors of Information Diffusion in Social Media: Evidence from Sentiment Mining of Twitter Messages

Social media have facilitated information sharing in social networks. Previous research shows that sentiment of text influences its diffusion in social media. Each emotion can be located on a three-dimensional space formed by dimensions of valence (positive–negative), arousal (passive / calm–active / excited), and tension (tense–relaxed). While previous research has investigated the effect of emotional valence on information diffusion in social media, the effect of emotional arousal remains unexplored. This study examines how emotional arousal influences information diffusion in social media using a sentiment mining approach. We propose a research model and test it using data collected from Twitter

Investigating psychobiological mechanisms underlying dysregulated goal-pursuit across psychiatric disorders

This thesis examines the psychobiological mechanisms contributing to dysregulated reward processing differences in two parts: across psychiatric disorders (Part one), and in bipolar disorder (Part two). Part one comprises a systematic review and meta-analysis examining the extent to which four aspects of reward processing, namely the anticipation and evaluation of rewards and losses, exist transdiagnostically at the psychobiological level. 26 functional magnetic resonance imaging (fMRI) studies that examined whole-brain-based activation during a reward task (monetary incentive delay) and compared between patients and matched controls were included. Results showed that compared to controls, clinical groups exhibit shared increases and decreases in dorsal striatal activity during the evaluation of rewarding outcomes and anticipation of negative outcomes respectively. Part two presents an empirical study, which sought to combine computational modelling and fMRI data to investigate whether momentary changes in mood bias the perception of rewards more strongly in individuals with bipolar disorder than matched controls. Region-of-interest analyses in the ventral striatum, anterior insula and ventromedial prefrontal cortex and exploratory whole-brain analyses were conducted. Although results broadly confirmed previous findings that mood-biased influences on reward learning signals are represented in the reward system, preliminary evidence suggests that individuals with bipolar disorder represent them more strongly than controls in visual processing areas. Part three comprises a critical appraisal of the research process. This includes a discussion of the author’s influences on the research, the relevance of understanding mechanisms in psychological research and treatment and potential challenges of fMRI research, concluding with a summary of recommendations

Predictive Modeling of Adolescent Cannabis Use From Multimodal Data

Predicting teenage drug use is key to understanding the etiology of substance abuse. However, classic predictive modeling procedures are prone to overfitting and fail to generalize to independent observations. To mitigate these concerns, cross-validated logistic regression with elastic-net regularization was used to predict cannabis use by age 16 from a large sample of fourteen year olds (N=1,319). High-dimensional data (p = 2,413) including parent and child psychometric data, child structural and functional MRI data, and genetic data (candidate single-nucleotide polymorphisms, SNPs ) collected at age 14 were used to predict the initiation of cannabis use (minimum six occasions) by age 16. Analyses were conducted separately for males and females to uncover sex-specific predictive profiles. The performance of the predictive models were assessed using the area under the receiver-operating characteristic curve ( ROC AUC ). Final models returned high predictive performance (generalization mean ROC AUCmales=.71, mean ROC AUCfemales=.81) and contained psychometric features common to both sexes. These common psychometric predictors included greater stressful life events, novelty-seeking personality traits of both the parent and child, and parental cannabis use. In contrast, males exhibited distinct functional neurobiological predictors related to a response- inhibition fMRI task, whereas females exhibited distinct neurobiological predictors related to a social processing fMRI task. Furthermore, the brain predictors exhibited sex- specific effects as the brain predictors of cannabis use for one sex failed to predict cannabis use for the opposite sex. These sex-specific brain predictors also exhibited drug- specific effects as they failed to predict binge-drinking by age 16 in an independent sample of youths. When collapsed across sex, a gene-specific analysis suggested that opioid receptor genetic variation also predicted cannabis use by age 16. Two SNPs on the gene coding for the primary mu-opioid receptor exhibited genetic risk effects, while one SNP on the gene coding for the primary delta-opioid receptor exhibited genetic protective effects. Taken together, these results demonstrate that adolescent cannabis use is reliably predicted in males and females from shared and unique biobehavioral features. These analyses also underscore the need for refined predictive modeling procedures as well as sex-specific inquiries into the etiology of substance abuse. The sex-specific risk-profiles uncovered from these analyses might inform potential etiological mechanisms contributing to substance abuse in adolescence as all predictors were measured prior to the onset of cannabis use