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Manzotti Pepperell New Mind
Draft: AI & Society “A Faustian Exchange: What is to be human in the era of Ubiquitous Technology The New Mind: Thinking Beyond the Head Riccardo MANZOTTI*, Robert PEPPERELL** *Institute of Consumption, Communication and Behavior IULM University, Via Carlo Bo, 8, 16033 Milano [email protected] **Cardiff School of Art & Design Howard Gardens, Cardiff CF24 0SP, UK [email protected] Abstract Throughout much of the modern period the human mind has been regarded as a property of the brain, and therefore something confined to the inside of the head — a view commonly known as 'internalism'. But recent works in cognitive science, philosophy, and anthropology, as well as certain trends in the development of technology, suggest an emerging view of the mind as a process not confined to the brain but spread through the body and world — an outlook covered by a family of views labeled 'externalism'. In this paper we will suggest there is now sufficient momentum in favour of externalism of various kinds to mark a historical shift in the way the mind is understood. We dub this emerging externalist tendency the 'New Mind'. Key properties of the New Mind will be summarized and some of its implications considered in areas such as art and culture, technology, and the science of consciousness. 1 Introduction For much of recorded human history, in both the European and Asian traditions, the question of how to understand that most ever present yet elusive properties of our existence — that fact that we have conscious minds — has occupied some of our greatest thinkers and provoked endless controversy. -
Imaging the Genetics of Brain Structure and Function Biological Psychology
Biological Psychology 79 (2008) 1–8 Contents lists available at ScienceDirect Biological Psychology journal homepage: www.elsevier.com/locate/biopsycho Editorial Imaging the genetics of brain structure and function ARTICLE INFO ABSTRACT Article history: Imaging genetics combines brain imaging and genetics to detect genetic variation in brain structure and Available online 11 April 2008 function related to behavioral traits, including psychiatric endpoints, cognition, and affective regulation. This special issue features extensive reviews of the current state-of-the-art of the field and adds new findings from twin and candidate gene studies on functional MRI. Here we present a brief overview and discuss a number of desirable future developments which include more specific a priori hypotheses, more standardization of MRI measurements within and across laboratories, and larger sample sizes that allows testing of multiple genes and their interactions up to a scale that allows genetic whole genome association studies. Based on the overall tenet of the contributions to this special issue we predict that imaging genetics will increasingly impact on the classification systems for psychiatric disorders and the early detection and treatment of vulnerable individuals. ß 2008 Elsevier B.V. All rights reserved. Biological Psychology, quite literally, deals with the connection 1. Imaging genetics between the body and the mind. In the past two decades two specific instances of body-mind connections have captured the What exactly is imaging genetics? In the -
Sparse Deep Neural Networks on Imaging Genetics for Schizophrenia Case-Control Classification
medRxiv preprint doi: https://doi.org/10.1101/2020.06.11.20128975; this version posted June 12, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission. Sparse Deep Neural Networks on Imaging Genetics for Schizophrenia Case-Control Classification Jiayu Chen1,*, Xiang Li2,*, Vince D. Calhoun1,2,3, Jessica A. Turner1,3, Theo G. M. van Erp4,5, Lei Wang6, Ole A. Andreassen7, Ingrid Agartz7,8,9, Lars T. Westlye7,10 , Erik Jönsson7,9, Judith M. Ford11,12, Daniel H. Mathalon11,12, Fabio Macciardi4, Daniel S. O’Leary13, Jingyu Liu1,2, †, Shihao Ji2, † 1Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS): (Georgia State University, Georgia Institute of Technology, and Emory University), Atlanta, GA, USA; 2Department of Computer Science, Georgia State University, Atlanta, GA, USA; 3Psychology Department and Neuroscience Institute, Georgia State University, Atlanta, GA, USA; 4Department of Psychiatry and Human Behavior, School of Medicine, University of California, Irvine, Irvine, CA, USA; 5Center for the Neurobiology of Learning and Memory, University of California, Irvine, Irvine, CA, 92697, USA; 6Department of Psychiatry and Behavioral Sciences, Northwestern University, Chicago, IL, USA; 7Norwegian Centre for Mental Disorders Research (NORMENT), Division of Mental Health and Addiction, Institute of Clinical Medicine, University -
(Title of the Thesis)*
THE OPTIMALITY OF DECISION MAKING DURING MOTOR LEARNING by Joshua Brent Moskowitz A thesis submitted to the Department of Psychology in conformity with the requirements for the degree of Master of Science Queen’s University Kingston, Ontario, Canada (June, 2016) Copyright ©Joshua B. Moskowitz, 2016 Abstract In our daily lives, we often must predict how well we are going to perform in the future based on an evaluation of our current performance and an assessment of how much we will improve with practice. Such predictions can be used to decide whether to invest our time and energy in learning and, if we opt to invest, what rewards we may gain. This thesis investigated whether people are capable of tracking their own learning (i.e. current and future motor ability) and exploiting that information to make decisions related to task reward. In experiment one, participants performed a target aiming task under a visuomotor rotation such that they initially missed the target but gradually improved. After briefly practicing the task, they were asked to selected rewards for hits and misses applied to subsequent performance in the task, where selecting a higher reward for hits came at a cost of receiving a lower reward for misses. We found that participants made decisions that were in the direction of optimal and therefore demonstrated knowledge of future task performance. In experiment two, participants learned a novel target aiming task in which they were rewarded for target hits. Every five trials, they could choose a target size which varied inversely with reward value. Although participants’ decisions deviated from optimal, a model suggested that they took into account both past performance, and predicted future performance, when making their decisions. -
Are Systems Neuroscience Explanations Mechanistic?
Are Systems Neuroscience Explanations Mechanistic? Carlos Zednik [email protected] Institute of Cognitive Science, University of Osnabrück 49069 Osnabrück, Germany Paper to be presented at: Philosophy of Science Association 24th Biennial Meeting (Chicago, IL), November 2014 Abstract Whereas most branches of neuroscience are thought to provide mechanistic explanations, systems neuroscience is not. Two reasons are traditionally cited in support of this conclusion. First, systems neuroscientists rarely, if ever, rely on the dual strategies of decomposition and localization. Second, they typically emphasize organizational properties over the properties of individual components. In this paper, I argue that neither reason is conclusive: researchers might rely on alternative strategies for mechanism discovery, and focusing on organization is often appropriate and consistent with the norms of mechanistic explanation. Thus, many explanations in systems neuroscience can also be viewed as mechanistic explanations. 1 1. Introduction There is a widespread consensus in philosophy of science that neuroscientists provide mechanistic explanations. That is, they seek the discovery and description of the mechanisms responsible for the behavioral and neurological phenomena being explained. This consensus is supported by a growing philosophical literature on past and present examples from various branches of neuroscience, including molecular (Craver 2007; Machamer, Darden, and Craver 2000), cognitive (Bechtel 2008; Kaplan and Craver 2011), and computational -
Imaging Genetics Approach to Parkinson's Disease and Its
www.nature.com/scientificreports OPEN Imaging genetics approach to Parkinson’s disease and its correlation with clinical score Received: 07 November 2016 Mansu Kim1,2, Jonghoon Kim1,2, Seung-Hak Lee1,2 & Hyunjin Park2,3 Accepted: 24 March 2017 Parkinson’s disease (PD) is a progressive neurodegenerative disorder associated with both underlying Published: 21 April 2017 genetic factors and neuroimaging findings. Existing neuroimaging studies related to the genome in PD have mostly focused on certain candidate genes. The aim of our study was to construct a linear regression model using both genetic and neuroimaging features to better predict clinical scores compared to conventional approaches. We obtained neuroimaging and DNA genotyping data from a research database. Connectivity analysis was applied to identify neuroimaging features that could differentiate between healthy control (HC) and PD groups. A joint analysis of genetic and imaging information known as imaging genetics was applied to investigate genetic variants. We then compared the utility of combining different genetic variants and neuroimaging features for predicting the Movement Disorder Society-sponsored unified Parkinson’s disease rating scale (MDS-UPDRS) in a regression framework. The associative cortex, motor cortex, thalamus, and pallidum showed significantly different connectivity between the HC and PD groups. Imaging genetics analysis identified PARK2, PARK7, HtrA2, GIGYRF2, and SNCA as genetic variants that are significantly associated with imaging phenotypes. A linear regression model combining genetic and neuroimaging features predicted the MDS-UPDRS with lower error and higher correlation with the actual MDS-UPDRS compared to other models using only genetic or neuroimaging information alone. Parkinson’s disease (PD) is a progressive neurodegenerative disorder characterized by bradykinesia, resting trem- ors, rigidity, and difficulty with voluntary movement1. -
Hypertext Semiotics in the Commercialized Internet
Hypertext Semiotics in the Commercialized Internet Moritz Neumüller Wien, Oktober 2001 DOKTORAT DER SOZIAL- UND WIRTSCHAFTSWISSENSCHAFTEN 1. Beurteiler: Univ. Prof. Dipl.-Ing. Dr. Wolfgang Panny, Institut für Informationsver- arbeitung und Informationswirtschaft der Wirtschaftsuniversität Wien, Abteilung für Angewandte Informatik. 2. Beurteiler: Univ. Prof. Dr. Herbert Hrachovec, Institut für Philosophie der Universität Wien. Betreuer: Gastprofessor Univ. Doz. Dipl.-Ing. Dr. Veith Risak Eingereicht am: Hypertext Semiotics in the Commercialized Internet Dissertation zur Erlangung des akademischen Grades eines Doktors der Sozial- und Wirtschaftswissenschaften an der Wirtschaftsuniversität Wien eingereicht bei 1. Beurteiler: Univ. Prof. Dr. Wolfgang Panny, Institut für Informationsverarbeitung und Informationswirtschaft der Wirtschaftsuniversität Wien, Abteilung für Angewandte Informatik 2. Beurteiler: Univ. Prof. Dr. Herbert Hrachovec, Institut für Philosophie der Universität Wien Betreuer: Gastprofessor Univ. Doz. Dipl.-Ing. Dr. Veith Risak Fachgebiet: Informationswirtschaft von MMag. Moritz Neumüller Wien, im Oktober 2001 Ich versichere: 1. daß ich die Dissertation selbständig verfaßt, andere als die angegebenen Quellen und Hilfsmittel nicht benutzt und mich auch sonst keiner unerlaubten Hilfe bedient habe. 2. daß ich diese Dissertation bisher weder im In- noch im Ausland (einer Beurteilerin / einem Beurteiler zur Begutachtung) in irgendeiner Form als Prüfungsarbeit vorgelegt habe. 3. daß dieses Exemplar mit der beurteilten Arbeit überein -
Systems Neuroscience of Mathematical Cognition and Learning
CHAPTER 15 Systems Neuroscience of Mathematical Cognition and Learning: Basic Organization and Neural Sources of Heterogeneity in Typical and Atypical Development Teresa Iuculano, Aarthi Padmanabhan, Vinod Menon Stanford University, Stanford, CA, United States OUTLINE Introduction 288 Ventral and Dorsal Visual Streams: Neural Building Blocks of Mathematical Cognition 292 Basic Organization 292 Heterogeneity in Typical and Atypical Development 295 Parietal-Frontal Systems: Short-Term and Working Memory 296 Basic Organization 296 Heterogeneity in Typical and Atypical Development 299 Lateral Frontotemporal Cortices: Language-Mediated Systems 302 Basic Organization 302 Heterogeneity in Typical and Atypical Development 302 Heterogeneity of Function in Numerical Cognition 287 https://doi.org/10.1016/B978-0-12-811529-9.00015-7 © 2018 Elsevier Inc. All rights reserved. 288 15. SYSTEMS NEUROSCIENCE OF MATHEMATICAL COGNITION AND LEARNING The Medial Temporal Lobe: Declarative Memory 306 Basic Organization 306 Heterogeneity in Typical and Atypical Development 306 The Circuit View: Attention and Control Processes and Dynamic Circuits Orchestrating Mathematical Learning 310 Basic Organization 310 Heterogeneity in Typical and Atypical Development 312 Plasticity in Multiple Brain Systems: Relation to Learning 314 Basic Organization 314 Heterogeneity in Typical and Atypical Development 315 Conclusions and Future Directions 320 References 324 INTRODUCTION Mathematical skill acquisition is hierarchical in nature, and each iteration of increased proficiency builds on knowledge of a lower-level primitive. For example, learning to solve arithmetical operations such as “3 + 4” requires first an understanding of what numbers mean and rep- resent (e.g., the symbol “3” refers to the quantity of three items, which derives from the ability to attend to discrete items in the environment). -
The Speculative Neuroscience of the Future Human Brain
Humanities 2013, 2, 209–252; doi:10.3390/h2020209 OPEN ACCESS humanities ISSN 2076-0787 www.mdpi.com/journal/humanities Article The Speculative Neuroscience of the Future Human Brain Robert A. Dielenberg Freelance Neuroscientist, 15 Parry Street, Cooks Hill, NSW, 2300, Australia; E-Mail: [email protected]; Tel.: +61-423-057-977 Received: 3 March 2013; in revised form: 23 April 2013 / Accepted: 27 April 2013 / Published: 21 May 2013 Abstract: The hallmark of our species is our ability to hybridize symbolic thinking with behavioral output. We began with the symmetrical hand axe around 1.7 mya and have progressed, slowly at first, then with greater rapidity, to producing increasingly more complex hybridized products. We now live in the age where our drive to hybridize has pushed us to the brink of a neuroscientific revolution, where for the first time we are in a position to willfully alter the brain and hence, our behavior and evolution. Nootropics, transcranial direct current stimulation (tDCS), transcranial magnetic stimulation (TMS), deep brain stimulation (DBS) and invasive brain mind interface (BMI) technology are allowing humans to treat previously inaccessible diseases as well as open up potential vistas for cognitive enhancement. In the future, the possibility exists for humans to hybridize with BMIs and mobile architectures. The notion of self is becoming increasingly extended. All of this to say: are we in control of our brains, or are they in control of us? Keywords: hybridization; BMI; tDCS; TMS; DBS; optogenetics; nootropic; radiotelepathy Introduction Newtonian systems aside, futurecasting is a risky enterprise at the best of times. -
Flexible Corticospinal Control of Muscles
Flexible Corticospinal Control of Muscles Najja J. Marshall Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2021 © 2021 Najja J. Marshall All Rights Reserved Abstract Flexible Corticospinal Control of Muscles Najja J. Marshall The exceptional abilities of top-tier athletes – from Simone Biles’ dizzying gymnastics to LeBron James’ gravity-defying bounds – can easily lead one to forget to marvel at the exceptional breadth of everyday movements. Whether holding a cup of coffee, reaching out to grab a falling object, or cycling at a quick clip, every motor action requires activating multiple muscles with the appropriate intensity and timing to move each limb or counteract the weight of an object. These actions are planned and executed by the motor cortex, which transmits its intentions to motoneurons in the spinal cord, which ultimately drive muscle contractions. A central problem in neuroscience is precisely how neural activity in cortex and the spinal cord gives rise to this diverse range of behaviors. At the level of spinal cord, this problem is considered to be well understood. A foundational tenet in motor control asserts that motoneurons are controlled by a single input to which they respond in a reliable and predictable manner to drive muscle activity, akin to the way that depressing a gas pedal by the same degree accelerates a car to a predictable speed. Theories of how motor cortex flexibly generates different behaviors are less firmly developed, but the available evidence indicates that cortical neurons are coordinated in a similarly simplistic, well-preserved manner. -
The Emerging Spectrum of Allelic Variation in Schizophrenia
Molecular Psychiatry (2013) 18, 38 -- 52 & 2013 Macmillan Publishers Limited All rights reserved 1359-4184/13 www.nature.com/mp EXPERT REVIEW The emerging spectrum of allelic variation in schizophrenia: current evidence and strategies for the identification and functional characterization of common and rare variants BJ Mowry1,2 and J Gratten1 After decades of halting progress, recent large genome-wide association studies (GWAS) are finally shining light on the genetic architecture of schizophrenia. The picture emerging is one of sobering complexity, involving large numbers of risk alleles across the entire allelic spectrum. The aims of this article are to summarize the key genetic findings to date and to compare and contrast methods for identifying additional risk alleles, including GWAS, targeted genotyping and sequencing. A further aim is to consider the challenges and opportunities involved in determining the functional basis of genetic associations, for instance using functional genomics, cellular models, animal models and imaging genetics. We conclude that diverse approaches will be required to identify and functionally characterize the full spectrum of risk variants for schizophrenia. These efforts should adhere to the stringent standards of statistical association developed for GWAS and are likely to entail very large sample sizes. Nonetheless, now more than any previous time, there are reasons for optimism and the ultimate goal of personalized interventions and therapeutics, although still distant, no longer seems unattainable. Molecular Psychiatry (2013) 18, 38--52; doi:10.1038/mp.2012.34; published online 1 May 2012 Keywords: CNV; functional genomics; GWAS; schizophrenia; sequencing; SNP THE NATURE OF THE PROBLEM complications (obesity, nicotine dependence, metabolic syndrome 13 Schizophrenia is a chronic psychiatric disorder characterized by and premature mortality), low employment and substantial 14 delusional beliefs, auditory hallucinations, disorganized thought homelessness. -
A Meta-Analysis of Functional MRI Results
RESEARCH Cooperating yet distinct brain networks engaged during naturalistic paradigms: A meta-analysis of functional MRI results 1 1 1 2 Katherine L. Bottenhorn , Jessica S. Flannery , Emily R. Boeving , Michael C. Riedel , 3,4 1 2 Simon B. Eickhoff , Matthew T. Sutherland , and Angela R. Laird 1Department of Psychology, Florida International University, Miami, FL, USA 2Department of Physics, Florida International University, Miami, FL, USA 3Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany Downloaded from http://direct.mit.edu/netn/article-pdf/3/1/27/1092290/netn_a_00050.pdf by guest on 01 October 2021 4Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany an open access journal Keywords: Neuroimaging meta-analysis, Naturalistic paradigms, Clustering analysis, Neuro- informatics ABSTRACT Cognitive processes do not occur by pure insertion and instead depend on the full complement of co-occurring mental processes, including perceptual and motor functions. As such, there is limited ecological validity to human neuroimaging experiments that use Citation: Bottenhorn, K. L., Flannery, highly controlled tasks to isolate mental processes of interest. However, a growing literature J. S., Boeving, E. R., Riedel, M. C., Eickhoff, S. B., Sutherland, M. T., & shows how dynamic, interactive tasks have allowed researchers to study cognition as it more Laird, A. R. (2019). Cooperating yet naturally occurs. Collective analysis across such neuroimaging experiments may answer distinct brain networks engaged during naturalistic paradigms: broader questions regarding how naturalistic cognition is biologically distributed throughout A meta-analysis of functional MRI k results. Network Neuroscience, the brain. We applied an unbiased, data-driven, meta-analytic approach that uses -means 3(1), 27–48.