The Inhuman Overhang: On Differential Heterogenesis and Multi-Scalar Modeling

As a philosophical paradigm, differential heterogenesis offers us a novel descriptive vantage with which to inscribe Deleuze’s virtuality within the terrain of “differential becoming,” conjugating “pure saliences” so as to parse economies, microhistories, insurgencies, and epistemological evolutionary processes that can be conceived of independently from their representational form. Unlike Gestalt theory’s oppositional constructions, the advantage of this aperture is that it posits a dynamic context to both media and its analysis, rendering them functionally tractable and set in relation to other objects, rather than as sedentary identities. Surveying the genealogy of differential heterogenesis with particular interest in the legacy of Lautman’s dialectic, I make the case for a reading of the Deleuzean virtual that departs from an event-oriented approach, galvanizing Sarti and Citti’s dynamic a priori vis-à-vis Deleuze’s philosophy of difference. Specifically, I posit differential heterogenesis as frame with which to examine our contemporaneous epistemic shift as it relates to multi-scalar computational modeling while paying particular attention to neuro-inferential modes of inductive learning and homologous cognitive architecture. Carving a bricolage between Mark Wilson’s work on the “greediness of scales” and Deleuze’s “scales of reality”, this project threads between static ecologies and active externalism vis-à-vis endocentric frames of reference and syntactical scaffolding

Consciousness Regained: Disentangling Mechanisms, Brain Systems, and Behavioral Responses

How consciousness (experience) arises from and relates to material brain processes (the "mind-body problem") has been pondered by thinkers for centuries, and is regarded as among the deepest unsolved problems in science, with wide-ranging theoretical, clinical, and ethical implications. Until the last few decades, this was largely seen as a philosophical topic, but not widely accepted in mainstream neuroscience. Since the 1980s, however, novel methods and theoretical advances have yielded remarkable results, opening up the field for scientific and clinical progress. Since a seminal paper by Crick and Koch (1998) claimed that a science of consciousness should first search for its neural correlates (NCC), a variety of correlates have been suggested, including both content-specific NCCs, determining particular phenomenal components within an experience, and the full NCC, the neural substrates supporting entire conscious experiences. In this review, we present recent progress on theoretical, experimental, and clinical issues. Specifically, we (1) review methodological advances that are important for dissociating conscious experience from related enabling and executive functions, (2) suggest how critically reconsidering the role of the frontal cortex may further delineate NCCs, (3) advocate the need for general, objective, brain-based measures of the capacity for consciousness that are independent of sensory processing and executive functions, and (4) show how animal studies can reveal population and network phenomena of relevance for understanding mechanisms of consciousness.European Union's Horizon 2020 Research and Innovation ProgrammeHermann and Lilly Schilling FoundationGerman Research FoundationCenter for Nanoscale Microscopy and Molecular Physiology of the BrainNational Institutes of Health/National Institute of Neurological Disorders and StrokeSao Paulo Research FoundationJames S. McDonnell Foundation Scholar AwardEU Grant H2020-FETOPENCanadian Institute for Advanced ResearchAzrieli Program in Brain, Mind and ConsciousnessFLAG-ERA JTC project CANONNorwegian Research CouncilNetherlands Organization for Scientific ResearchUniv Oslo, Inst Basal Med Sci, Div Physiol, Dept Mol Med, POB 1103 Blindern, N-0317 Oslo, NorwayUniv Wisconsin, Dept Neurol, Madison, WI 53705 USAUniv Wisconsin, Dept Psychiat, Madison, WI 53719 USAUniv Fed Sao Paulo, Inst Sci & Technol, BR-12231280 Sao Jose Dos Campos, SP, BrazilUniv Milan, Dept Biomed & Clin Sci Luigi Sacco, I-20157 Milan, ItalyFdn Don Carlo Gnocchi ONLUS, Ist Ricovero & Cura Carattere Sci, I-20162 Milan, ItalyUniv Amsterdam, Swammerdam Inst Life Sci, Cognit & Syst Neurosci Grp, NL-1098 XH Amsterdam, NetherlandsUniv Amsterdam, Res Prior Program Brain & Cognit, NL-1098 XH Amsterdam, NetherlandsUniv Med Goettingen, Dept Cognit Neurol, D-37075 Gottingen, GermanyLeibniz Inst Primate Res, German Primate Ctr, D-37077 Gottingen, GermanyLeibniz Sci Campus Primate Cognit, D-37077 Gottingen, GermanyUniv Fed Sao Paulo, Inst Sci & Technol, BR-12231280 Sao Jose Dos Campos, SP, BrazilEuropean Union's Horizon 2020 Research and Innovation Programme: 720270German Research Foundation: WI 4046/1-1National Institutes of Health/National Institute of Neurological Disorders and Stroke: 1R03NS096379FAPESP: 2016/08263-9EU Grant H2020-FETOPEN: RIA 686764Web of Scienc

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 355)

This bibliography lists 147 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during October, 1991. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

The unity and diversity of executive functions: A systematic review and re-analysis of latent variable studies.

Confirmatory factor analysis (CFA) has been frequently applied to executive function measurement since first used to identify a three-factor model of inhibition, updating, and shifting; however, subsequent CFAs have supported inconsistent models across the life span, ranging from unidimensional to nested-factor models (i.e., bifactor without inhibition). This systematic review summarized CFAs on performance-based tests of executive functions and reanalyzed summary data to identify best-fitting models. Eligible CFAs involved 46 samples (N = 9,756). The most frequently accepted models varied by age (i.e., preschool = one/two-factor; school-age = three-factor; adolescent/adult = three/nested-factor; older adult = two/three-factor), and most often included updating/working memory, inhibition, and shifting factors. A bootstrap reanalysis simulated 5,000 samples from 21 correlation matrices (11 child/adolescent; 10 adult) from studies including the three most common factors, fitting seven competing models. Model results were summarized as the mean percent accepted (i.e., average rate at which models converged and met fit thresholds: CFI ≥ .90/RMSEA ≤ .08) and mean percent selected (i.e., average rate at which a model showed superior fit to other models: ΔCFI ≥ .005/.010/ΔRMSEA ≤ -.010/-.015). No model consistently converged and met fit criteria in all samples. Among adult samples, the nested-factor was accepted (41-42%) and selected (8-30%) most often. Among child/adolescent samples, the unidimensional model was accepted (32-36%) and selected (21-53%) most often, with some support for two-factor models without a differentiated shifting factor. Results show some evidence for greater unidimensionality of executive function among child/adolescent samples and both unity and diversity among adult samples. However, low rates of model acceptance/selection suggest possible bias toward the publication of well-fitting but potentially nonreplicable models with underpowered samples. (PsycINFO Database Record (c) 2018 APA, all rights reserved)

Increased Functional Connectivity in the Default Mode Network in Mild Cognitive Impairment: A Maladaptive Compensatory Mechanism Associated with Poor Semantic Memory Performance

Semantic memory decline and changes of default mode network (DMN) connectivity have been reported in mild cognitive impairment (MCI). Only a few studies, however, have investigated the role of changes of activity in the DMN on semantic memory in this clinical condition. The present study aimed to investigate more extensively the relationship between semantic memory impairment and DMN intrinsic connectivity in MCI. Twenty-one MCI patients and 21 healthy elderly controls matched for demographic variables took part in this study. All participants underwent a comprehensive semantic battery including tasks of category fluency, visual naming and naming from definition for objects, actions and famous people, word-association for early and late acquired words and reading. A subgroup of the original sample (16 MCI patients and 20 healthy elderly controls) was also scanned with resting state functional magnetic resonance imaging and DMN connectivity was estimated using a seed-based approach. Compared with healthy elderly, patients showed an extensive semantic memory decline in category fluency, visual naming, naming from definition, words-association, and reading tasks. Patients presented increased DMN connectivity between the medial prefrontal regions and the posterior cingulate and between the posterior cingulate and the parahippocampus and anterior hippocampus. MCI patients also showed a significant negative correlation of medial prefrontal gyrus connectivity with parahippocampus and posterior hippocampus and visual naming performance. Our findings suggest that increasing DMN connectivity may contribute to semantic memory deficits in MCI, specifically in visual naming. Increased DMN connectivity with posterior cingulate and medio-temporal regions seems to represent a maladaptive reorganization of brain functions in MCI, which detrimentally contributes to cognitive impairment in this clinical population

Multimodal MRI characterization of visual word recognition: an integrative view

228 p.The ventral occipito-temporal (vOT) association cortex contributes significantly to recognize different types of visual patterns. It is widely accepted that a subset of this circuitry, including the visual word form area (VWFA), becomes trained to perform the task of rapidly identifying word forms. An important open question is the computational role of this circuitry: To what extent is part of a bottom-up hierarchical processing of information on visual word recognition and/or is involved in processing top-down signals from higher-level language regions. This doctoral dissertation thesis proposal is aimed at characterizing the vOT reading circuitry using behavioral, functional, structural and quantitative MRI indexes, and linking its computations to the other two important regions within the language network: the posterior parietal cortex (pPC) and the inferior frontal gyrus (IFG). Results revealed that two distinct word-responsive areas can be segregated in the vOT: one responsible for visual feature extraction that is connected to the intraparietal sulcus via the vertical occipital fasciculus and a second one responsible for semantic processing that is connected to the angular gyrus via the posterior arcuate fasciculus and to the IFG via the anterior arcuate fasciculus. Importantly, reading behavior was predicted by functional activation in regions identified along the vOT, pPC and IFG, as well as by structural properties of the white matter fiber tracts linking them. The present work constitutes a critical step in the creation of a highly detailed characterization of the early stages of reading at the individual-subject level and to establish a baseline model and parameter range that might serve to clarify functional and structural differences between typical, poor and atypical readers.BCBL: basque center on cognition, brain and languag

Cognitive Control in Adolescence: Neural Underpinnings and Relation to Self-Report Behaviors

Adolescence is commonly characterized by impulsivity, poor decision-making, and lack of foresight. However, the developmental neural underpinnings of these characteristics are not well established.To test the hypothesis that these adolescent behaviors are linked to under-developed proactive control mechanisms, the present study employed a hybrid block/event-related functional Magnetic Resonance Imaging (fMRI) Stroop paradigm combined with self-report questionnaires in a large sample of adolescents and adults, ranging in age from 14 to 25. Compared to adults, adolescents under-activated a set of brain regions implicated in proactive top-down control across task blocks comprised of difficult and easy trials. Moreover, the magnitude of lateral prefrontal activity in adolescents predicted self-report measures of impulse control, foresight, and resistance to peer pressure. Consistent with reactive compensatory mechanisms to reduced proactive control, older adolescents exhibited elevated transient activity in regions implicated in response-related interference resolution.Collectively, these results suggest that maturation of cognitive control may be partly mediated by earlier development of neural systems supporting reactive control and delayed development of systems supporting proactive control. Importantly, the development of these mechanisms is associated with cognitive control in real-life behaviors

Parsing neurocognitive heterogeneity in pediatric traumatic brain injury

Traumatic brain injuries (TBI) occur quite frequently in children and adolescents. One difficulty in understanding and treating TBI lies in the heterogeneous nature of its acquisition and mechanism of injury, and the resulting neurocognitive impairment. While there are instruments that exist to identify such impairment, they typically are divided into very broad domains of academic performance. Tests such as the Wechsler Intelligence Scale for Children (WISC) and the Woodcock Johnson are helpful in identifying impairment within the realm of academic aptitude, but have thus far not provided specific enough information as to the impairment of the underlying neurocognitive process that may be causing the degraded performance. In recent years, however, there has been an increase in tests specifically to assess neurocognitive functioning in children. One such test, the Test of Memory and Learning (Reynolds & Bigler, 1994), includes both nonverbal and verbal components, similar to the WISC, as well as indices of performance that measure broader underlying neurocognitive processes such as memory, learning, and attention/concentration factors. The purpose of the current study was to investigate the heterogeneity in neurocognitive function demonstrated by children who have sustained a TBI. Understanding the profiles of neurocognitive impairment that occur in child TBI may assist in predicting outcomes and treatment planning. From a theoretical perspective, patterns of performance on neuropsychological tests may provide unique insights into the type of injury sustained and the brain structures that are most susceptible to injury. In the present investigation, heterogeneity in neurocognitive function was investigated using cluster analysis of neuropsychological domains assessed by the Test of Memory and Learning (TOMAL). A five-cluster solution for the TOMAL, data was selected as the optimal cluster solution. It best exhibited differences in level and pattern of performance, as well as differences on important clinical and behavioral variables. Empirical support for the identification of clusters based upon TOMAL scores, Intelligence scores (IQ) and behaviors reported on the Behavior Assessment System for Children (BASC) further supported the selected cluster solution, and should assist clinicians in providing both a more informed prognosis and a more prescriptive treatment intervention

Unsupervised learning for vascular heterogeneity assessment of glioblastoma based on magnetic resonance imaging: The Hemodynamic Tissue Signature

[ES] El futuro de la imagen médica está ligado a la inteligencia artificial. El análisis manual de imágenes médicas es hoy en día una tarea ardua, propensa a errores y a menudo inasequible para los humanos, que ha llamado la atención de la comunidad de Aprendizaje Automático (AA). La Imagen por Resonancia Magnética (IRM) nos proporciona una rica variedad de representaciones de la morfología y el comportamiento de lesiones inaccesibles sin una intervención invasiva arriesgada. Sin embargo, explotar la potente pero a menudo latente información contenida en la IRM es una tarea muy complicada, que requiere técnicas de análisis computacional inteligente. Los tumores del sistema nervioso central son una de las enfermedades más críticas estudiadas a través de IRM. Específicamente, el glioblastoma representa un gran desafío, ya que, hasta la fecha, continua siendo un cáncer letal que carece de una terapia satisfactoria. Del conjunto de características que hacen del glioblastoma un tumor tan agresivo, un aspecto particular que ha sido ampliamente estudiado es su heterogeneidad vascular. La fuerte proliferación vascular del glioblastoma, así como su robusta angiogénesis han sido consideradas responsables de la alta letalidad de esta neoplasia. Esta tesis se centra en la investigación y desarrollo del método Hemodynamic Tissue Signature (HTS): un método de AA no supervisado para describir la heterogeneidad vascular de los glioblastomas mediante el análisis de perfusión por IRM. El método HTS se basa en el concepto de hábitat, que se define como una subregión de la lesión con un perfil de IRM que describe un comportamiento fisiológico concreto. El método HTS delinea cuatro hábitats en el glioblastoma: el hábitat HAT, como la región más perfundida del tumor con captación de contraste; el hábitat LAT, como la región del tumor con un perfil angiogénico más bajo; el hábitat IPE, como la región adyacente al tumor con índices de perfusión elevados; y el hábitat VPE, como el edema restante de la lesión con el perfil de perfusión más bajo. La investigación y desarrollo de este método ha originado una serie de contribuciones enmarcadas en esta tesis. Primero, para verificar la fiabilidad de los métodos de AA no supervisados en la extracción de patrones de IRM, se realizó una comparativa para la tarea de segmentación de gliomas de grado alto. Segundo, se propuso un algoritmo de AA no supervisado dentro de la familia de los Spatially Varying Finite Mixture Models. El algoritmo propone una densidad a priori basada en un Markov Random Field combinado con la función probabilística Non-Local Means, para codificar la idea de que píxeles vecinos tienden a pertenecer al mismo objeto. Tercero, se presenta el método HTS para describir la heterogeneidad vascular del glioblastoma. El método se ha aplicado a casos reales en una cohorte local de un solo centro y en una cohorte internacional de más de 180 pacientes de 7 centros europeos. Se llevó a cabo una evaluación exhaustiva del método para medir el potencial pronóstico de los hábitats HTS. Finalmente, la tecnología desarrollada en la tesis se ha integrado en la plataforma online ONCOhabitats (https://www.oncohabitats.upv.es). La plataforma ofrece dos servicios: 1) segmentación de tejidos de glioblastoma, y 2) evaluación de la heterogeneidad vascular del tumor mediante el método HTS. Los resultados de esta tesis han sido publicados en diez contribuciones científicas, incluyendo revistas y conferencias de alto impacto en las áreas de Informática Médica, Estadística y Probabilidad, Radiología y Medicina Nuclear y Aprendizaje Automático. También se emitió una patente industrial registrada en España, Europa y EEUU. Finalmente, las ideas originales concebidas en esta tesis dieron lugar a la creación de ONCOANALYTICS CDX, una empresa enmarcada en el modelo de negocio de los companion diagnostics de compuestos farmacéuticos.[EN] The future of medical imaging is linked to Artificial Intelligence (AI). The manual analysis of medical images is nowadays an arduous, error-prone and often unaffordable task for humans, which has caught the attention of the Machine Learning (ML) community. Magnetic Resonance Imaging (MRI) provides us with a wide variety of rich representations of the morphology and behavior of lesions completely inaccessible without a risky invasive intervention. Nevertheless, harnessing the powerful but often latent information contained in MRI acquisitions is a very complicated task, which requires computational intelligent analysis techniques. Central nervous system tumors are one of the most critical diseases studied through MRI. Specifically, glioblastoma represents a major challenge, as it remains a lethal cancer that, to date, lacks a satisfactory therapy. Of the entire set of characteristics that make glioblastoma so aggressive, a particular aspect that has been widely studied is its vascular heterogeneity. The strong vascular proliferation of glioblastomas, as well as their robust angiogenesis and extensive microvasculature heterogeneity have been claimed responsible for the high lethality of the neoplasm. This thesis focuses on the research and development of the Hemodynamic Tissue Signature (HTS) method: an unsupervised ML approach to describe the vascular heterogeneity of glioblastomas by means of perfusion MRI analysis. The HTS builds on the concept of habitats. A habitat is defined as a sub-region of the lesion with a particular MRI profile describing a specific physiological behavior. The HTS method delineates four habitats within the glioblastoma: the HAT habitat, as the most perfused region of the enhancing tumor; the LAT habitat, as the region of the enhancing tumor with a lower angiogenic profile; the potentially IPE habitat, as the non-enhancing region adjacent to the tumor with elevated perfusion indexes; and the VPE habitat, as the remaining edema of the lesion with the lowest perfusion profile. The research and development of the HTS method has generated a number of contributions to this thesis. First, in order to verify that unsupervised learning methods are reliable to extract MRI patterns to describe the heterogeneity of a lesion, a comparison among several unsupervised learning methods was conducted for the task of high grade glioma segmentation. Second, a Bayesian unsupervised learning algorithm from the family of Spatially Varying Finite Mixture Models is proposed. The algorithm integrates a Markov Random Field prior density weighted by the probabilistic Non-Local Means function, to codify the idea that neighboring pixels tend to belong to the same semantic object. Third, the HTS method to describe the vascular heterogeneity of glioblastomas is presented. The HTS method has been applied to real cases, both in a local single-center cohort of patients, and in an international retrospective cohort of more than 180 patients from 7 European centers. A comprehensive evaluation of the method was conducted to measure the prognostic potential of the HTS habitats. Finally, the technology developed in this thesis has been integrated into an online open-access platform for its academic use. The ONCOhabitats platform is hosted at https://www.oncohabitats.upv.es, and provides two main services: 1) glioblastoma tissue segmentation, and 2) vascular heterogeneity assessment of glioblastomas by means of the HTS method. The results of this thesis have been published in ten scientific contributions, including top-ranked journals and conferences in the areas of Medical Informatics, Statistics and Probability, Radiology & Nuclear Medicine and Machine Learning. An industrial patent registered in Spain, Europe and EEUU was also issued. Finally, the original ideas conceived in this thesis led to the foundation of ONCOANALYTICS CDX, a company framed into the business model of companion diagnostics for pharmaceutical compounds.[CA] El futur de la imatge mèdica està lligat a la intel·ligència artificial. L'anàlisi manual d'imatges mèdiques és hui dia una tasca àrdua, propensa a errors i sovint inassequible per als humans, que ha cridat l'atenció de la comunitat d'Aprenentatge Automàtic (AA). La Imatge per Ressonància Magnètica (IRM) ens proporciona una àmplia varietat de representacions de la morfologia i el comportament de lesions inaccessibles sense una intervenció invasiva arriscada. Tanmateix, explotar la potent però sovint latent informació continguda a les adquisicions de IRM esdevé una tasca molt complicada, que requereix tècniques d'anàlisi computacional intel·ligent. Els tumors del sistema nerviós central són una de les malalties més crítiques estudiades a través de IRM. Específicament, el glioblastoma representa un gran repte, ja que, fins hui, continua siguent un càncer letal que manca d'una teràpia satisfactòria. Del conjunt de característiques que fan del glioblastoma un tumor tan agressiu, un aspecte particular que ha sigut àmpliament estudiat és la seua heterogeneïtat vascular. La forta proliferació vascular dels glioblastomes, així com la seua robusta angiogènesi han sigut considerades responsables de l'alta letalitat d'aquesta neoplàsia. Aquesta tesi es centra en la recerca i desenvolupament del mètode Hemodynamic Tissue Signature (HTS): un mètode d'AA no supervisat per descriure l'heterogeneïtat vascular dels glioblastomas mitjançant l'anàlisi de perfusió per IRM. El mètode HTS es basa en el concepte d'hàbitat, que es defineix com una subregió de la lesió amb un perfil particular d'IRM, que descriu un comportament fisiològic concret. El mètode HTS delinea quatre hàbitats dins del glioblastoma: l'hàbitat HAT, com la regió més perfosa del tumor amb captació de contrast; l'hàbitat LAT, com la regió del tumor amb un perfil angiogènic més baix; l'hàbitat IPE, com la regió adjacent al tumor amb índexs de perfusió elevats, i l'hàbitat VPE, com l'edema restant de la lesió amb el perfil de perfusió més baix. La recerca i desenvolupament del mètode HTS ha originat una sèrie de contribucions emmarcades a aquesta tesi. Primer, per verificar la fiabilitat dels mètodes d'AA no supervisats en l'extracció de patrons d'IRM, es va realitzar una comparativa en la tasca de segmentació de gliomes de grau alt. Segon, s'ha proposat un algorisme d'AA no supervisat dintre de la família dels Spatially Varying Finite Mixture Models. L'algorisme proposa un densitat a priori basada en un Markov Random Field combinat amb la funció probabilística Non-Local Means, per a codificar la idea que els píxels veïns tendeixen a pertànyer al mateix objecte semàntic. Tercer, es presenta el mètode HTS per descriure l'heterogeneïtat vascular dels glioblastomas. El mètode HTS s'ha aplicat a casos reals en una cohort local d'un sol centre i en una cohort internacional de més de 180 pacients de 7 centres europeus. Es va dur a terme una avaluació exhaustiva del mètode per mesurar el potencial pronòstic dels hàbitats HTS. Finalment, la tecnologia desenvolupada en aquesta tesi s'ha integrat en una plataforma online ONCOhabitats (https://www.oncohabitats.upv.es). La plataforma ofereix dos serveis: 1) segmentació dels teixits del glioblastoma, i 2) avaluació de l'heterogeneïtat vascular dels glioblastomes mitjançant el mètode HTS. Els resultats d'aquesta tesi han sigut publicats en deu contribucions científiques, incloent revistes i conferències de primer nivell a les àrees d'Informàtica Mèdica, Estadística i Probabilitat, Radiologia i Medicina Nuclear i Aprenentatge Automàtic. També es va emetre una patent industrial registrada a Espanya, Europa i els EEUU. Finalment, les idees originals concebudes en aquesta tesi van donar lloc a la creació d'ONCOANALYTICS CDX, una empresa emmarcada en el model de negoci dels companion diagnostics de compostos farmacèutics.En este sentido quiero agradecer a las diferentes instituciones y estructuras de financiación de investigación que han contribuido al desarrollo de esta tesis. En especial quiero agradecer a la Universitat Politècnica de València, donde he desarrollado toda mi carrera acadèmica y científica, así como al Ministerio de Ciencia e Innovación, al Ministerio de Economía y Competitividad, a la Comisión Europea, al EIT Health Programme y a la fundación Caixa ImpulseJuan Albarracín, J. (2020). Unsupervised learning for vascular heterogeneity assessment of glioblastoma based on magnetic resonance imaging: The Hemodynamic Tissue Signature [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/149560TESI