Striatal oscillatory activity associated with movement, reward, and decision-making is observed in several interacting frequency bands. Rodent striatal local field potential recordings show dopamine- and reward-dependent transitions between a 'spontaneous' state involving beta (15-30 Hz) and low gamma (40-60 Hz) and a 'dopaminergic' state involving theta (4-8 Hz) and high gamma (60-100 Hz) activity. The mechanisms underlying these rhythmic dynamics and their functional consequences are not well understood. In this thesis, I construct a biophysical model of striatal microcircuits that comprehensively describes the generation and interaction of these rhythms as well as their modulation by dopamine and rhythmic inputs, and test its predictions using human electroencephalography (EEG) data. Chapter 1 describes the striatal model and its dopaminergic modulation. Building on previous work suggesting striatal projection neuron (SPN) networks can generate beta oscillations, I construct a model network of striatal fast-spiking interneurons (FSIs) capable of generating delta/theta (2-6 Hz) and gamma rhythms. This FSI network produces low gamma oscillations under low (simulated) dopaminergic tone, and high gamma activity nested within a delta/theta oscillation under high dopaminergic tone. In a combined model under high dopaminergic tone SPN network beta oscillations are interrupted by delta/theta-periodic bursts of gamma-frequency FSI inhibition. This high dopamine-induced periodic inhibition may enable switching between beta-rhythmic SPN cell assemblies representing motor programs, suggesting that dopamine facilitates movement in part by allowing for rapid, periodic changes in motor program execution. Chapter 2 describes the model's response to square-wave periodic cortical inputs. Comparing models with and without FSIs reveals that the FSI network: (i) prevents the SPN network's generation of phase-locked beta oscillations in response to beta's harmonic frequencies, ensuring fidelity of transmission of cortical beta rhythms; and (ii) limits or entrains SPN activity in response to certain gamma frequency inputs. Chapter 3 describes an analysis of phase-amplitude coupling at cortical electrodes in human EEG data during a reward task. The alternating rhythms predicted by the model appear in response to positive feedback. While the origins of these rhythms remain unclear, if they represent striatal signals, they provide a direct link between human behavior and striatal cellular function.

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abstract: Many existing applications of machine learning (ML) to cybersecurity are focused on detecting malicious activity already present in an enterprise. However, recent high-profile cyberattacks proved that certain threats could have been avoided. The speed of contemporary attacks along with the high costs of remediation incentivizes avoidance over response. Yet, avoidance implies the ability to predict - a notoriously difficult task due to high rates of false positives, difficulty in finding data that is indicative of future events, and the unexplainable results from machine learning algorithms. In this dissertation, these challenges are addressed by presenting three artificial intelligence (AI) approaches to support prioritizing defense measures. The first two approaches leverage ML on cyberthreat intelligence data to predict if exploits are going to be used in the wild. The first work focuses on what data feeds are generated after vulnerability disclosures. The developed ML models outperform the current industry-standard method with F1 score more than doubled. Then, an approach to derive features about who generated the said data feeds is developed. The addition of these features increase recall by over 19% while maintaining precision. Finally, frequent itemset mining is combined with a variant of a probabilistic temporal logic framework to predict when attacks are likely to occur. In this approach, rules correlating malicious activity in the hacking community platforms with real-world cyberattacks are mined. They are then used in a deductive reasoning approach to generate predictions. The developed approach predicted unseen real-world attacks with an average increase in the value of F1 score by over 45%, compared to a baseline approach. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2019

Maria Lucia Miotto Master Thesis Abstract in English Although more and more works are showing convergence between the many documents regarding the ethics of artificial intelligence, none of them has tried to explain the reasons for this convergence. The thesis here proposed is that the diffusion of these principles is due to the underlying action of an epistemic community that has promoted the spread and the adoption of these values. Then, through network analysis, this thesis describes the AI ethics epistemic community and its methods of value diffusion, testing for the most effective. Then, to test the first result, two case studies, representative of political opposites, the United States and the People Republic of China have been analysed to see which method of diffusion has worked the most. What seems evident is that scientific conferences remain a primary factor in the transmission of knowledge. However, particular attention must also be given to the role played by universities and research labs (also those of big tech-companies) because they have revealed to be great aggregators for the epistemic community and are increasing their centrality in the network.

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Analysis of Inferred Social Networks While the social network analysis (SNA) is not a new science branch, thanks to the boom of social media platforms in recent years new methods and approaches appear with increasing frequency. However, not all datasets have network structure visible at first glance. We believe that every reasonable interconnected system of data hides a social network, which can be inferred using specific methods. In this thesis we examine such social network, inferred from the real-world data of a smaller bank. We also review some of the most commonly used methods in SNA and then apply them on our complex network, expecting to find structures typical for traditional social networks.

This paper is about application of various data mining methods in social networks and social media area. It reveals basic principles of social media with the aim to high information potential of usage of the data from social networks. This is demonstrated on selected data mining methods, especially Social Network Analysis and Sentiment Analysis. Other opportunities of using social media data are shown in chapter about Social Media Monitoring tools. All these chapters are supplemented by practical examples and particular researches. Last chapter reveals visions and threats, which can bring data mining in the future. Keywords Data mining, social networks, social media, social network analysis, sentiment analysis, social media monitoring

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Bakgrund: Fysisk aktivitet främjar hälsa generellt men kan upplevas svårt att få till förpersoner med långvarig smärta. Många utövar fysisk aktivitet trots smärta vilket även kan gesymptomlindring. Enkäten “Självskattade orsaksnätverk för fysisk aktivitet” undersökerunderlättande faktorer för fysisk aktivitet hos personer med långvarig smärta. Enkätensvaliditet är dock inte utforskad ännu. Syfte: För att utveckla enkäten undersöktes ytvaliditet, trovärdighet samt deltagarnas nöjdhet.Dessutom jämfördes resultaten för olika subgrupper hos personer med långvarig smärta. Metod: För att rekrytera deltagare publicerades enkäten i flertalet Facebook-grupper förpersoner med långvarig smärta. Det formulerades nio validitetsfrågor, inspirerat av andrapsykometriskt testade frågeformulär samt eget framtagna för att svara på frågeställningarna.Frågorna utvärderades genom en skattningsskala 0-10 samt ett fritextsvar. Data analyseradesmed deskriptiv statistik samt Mann Whiney U-Test. Resultat: Det inkluderades 48 personer. Genomförbarhet och frågan, om resultatetrepresenterar vardagslivet, skattades 6 till 7 i median. Smärtvariation, hindrande faktorer ochpsykiska faktorer saknades i enkäten enligt deltagarna. Det fanns inga signifikanta skillnaderi skattningen av enkätens egenskaper, varken vid jämförelser hos personer med låg respektivehög genomsnittssmärta eller hos personer som uppfyller respektive inte uppfyllerrekommendationer för fysiska aktivitet. Konklusion: Deltagarnas uppfattning om enkätens tydlighet, genomförbarhet samt relevansvar genomgående ganska bra. Ingen skillnad upptäcktes vid gruppjämförelser. För framtidastudier rekommenderas utvärdering av enkäten hos andra populationer samt vidare test avvaliditet och reliabilitet. / Background: Physical activity promotes health in general, but can be difficult to achieve forpeople with chronic pain. Many people are physically active despite pain. However, physicalactivity can also provide symptom relief. The questionnaire " Självskattade orsaksnätverk förfysisk aktivitet'' investigates facilitating factors for physical activity in people with chronicpain and its validity has not yet been explored. Aim: To develop the questionnaire, face validity, credibility and the participants' satisfactionwere investigated. In addition, the results were compared for different subgroups of peoplewith chronic pain. Method: To recruit participants, the questionnaire was published in several Facebook groupsfor people with chronic pain. Nine validity questions were formulated, including questionsinspired by previous psychometrically tested questionnaires as well as self-developedquestions. These were evaluated using a 0-10 rating scale and a free text answer. Data wereanalysed with descriptive statistics and Mann Whitney U-test. Results: 48 participants were included. Feasibility and the question whether the resultrepresents everyday life was rated 6 till 7 as median. Pain variation, complicating factors andpsychological factors were missing in the questionnaire according to the participants. Therewere no significant differences between people with low or high average pain or those whodid and did not meet recommendations for physical activity. Conclusion: The participants' perception of the questionnaire's clarity, feasibility andrelevance was consistently quite good. No significant differences were found in groupcomparisons. For future studies, evaluation of the questionnaire in other populations andfurther tests of validity and reliability are recommended.

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