2023 / Connectome Fingerprinting (CF) and Connectome-Based Predictive Modeling (CPM) are emerging data science approaches within cognitive neuroscience that utilize brain connectivity data to predict the functional organization of the brain and behavior. Here, I examined the robustness and data needs of these approaches and developed applications for specific clinical populations, including neurosurgical glioma patients and early-stage Alzheimer’s Disease (AD) patients.In the first study, I utilized the Human Connectome Project dataset (n=208) to understand the relationship between function and connectivity using CF across cognitive tasks, and functional connectivity paradigms of fixation and movie-watching. I benchmarked the CF method to establish the quantity and quality of connectivity and task activation data required to build robust models across different cortical regions, cognitive tasks, scan quality, learning algorithms, and scanners. I also modeled the link of cerebellar-cortical connectivity with function, suggesting an integrated role of the cerebellum across cognitive domains. Neurosurgeons routinely use task fMRI protocols to map out motor and language networks to aid in presurgical planning for brain tumor resection to minimize cognitive damage. In the second study, I investigated the possibility of using CF models to help neurosurgeons predict motor and language networks in presurgical patients with gliomas (n=16), who are unable to perform complex tasks in the scanner. I tested the model validity across healthy control adults (n=16) from different scanners with varying data quality and quantity. The deposition of tau and amyloid-β plaques in AD results in brain degeneration, memory loss, and behavioral changes. Resting-state functional connectivity gets affected due to the progression of AD. In the third study, I analyzed the relationship between functional connectivity and tau/amyloid depositions and tested the predictive ability of CPM across two different cohorts: Autosomal Dominant with Presenilin1 mutation from the Colombia-Boston study with early-onset AD (n=32) and late-onset sporadic AD with APOE4 marker from the Harvard Aging Brain Study (n=78) and compared them with healthy age-matched adults (n=35/n=206) and healthy young adults (n=1570) from the Genomic Superstruct Project. Combined, these studies highlight the potential of data-driven approaches to model human brain function and connectivity, facilitating fMRI's translational applications. / 2027-02-04T00:00:00Z

Threatening events influence memory systems in complex ways. While it was once believed that emotion enhanced all aspects of memory, recent evidence suggests that it improves recall of emotional central features, but not neutral peripheral details (Payne & Kensinger, 2011). Other studies show that emotion can enhance context, retroactively benefiting related neutral events over time (Dunsmoor et al., 2015). Notably, both effects emerge after sleep, indicating a role for memory consolidation. Recently, Cowan et al. (2021) proposed that consolidation not only strengthens salient information but also adaptively transforms memories via semanticization and integration. In this dissertation, we adopt this adaptive memory framework to investigate behavioral and neural markers of threat memory transformation. First, using free recall changes over a week as a behavioral measure of memory transformation, we show that higher subjective arousal predicts greater semanticization, with fewer episodic details retained over time. Next, functional connectivity analyses reveal a division between anterior and posterior hippocampus: the posterior hippocampus, in conjunction with the basolateral amygdala and sensory cortex during encoding, is linked to less memory semanticization, while the anterior hippocampus, coupled with the lateral occipital cortex and precuneus during post-encoding, predicts greater semanticization. Moreover, representational similarity analyses reveal that long-term memory reinstatement is strongest in the precuneus, resembling early encoding patterns, with both hippocampal regions shifting over time towards gist representations, albeit with varying granularity. Finally, we report a negative relationship between neural reinstatement in the lateral occipital cortex and memory semanticization, suggesting that detailed cortical representations help preserve event details over time. These findings support the adaptive memory model (Cowan et al., 2021), emphasizing the dynamic roles of the hippocampus, amygdala and cortex in threat memory transformation. / Psychology / Accompanied by 1 .zip Archive file: 1) Supplementary Material : (Tanriverdi_temple_0225E_15946_Supplementary_Materials (1))

In this thesis, we consider the k-edge connected L-hop-constrained network design problem. Given a weighted graph G=(N,E), a set D of pairs of terminal nodes, and two integers k,L > 1, it consists in finding in G the minimum cost subgraph containing at least k edge-disjoint paths of at most L edges between each pair in D. This problem is of great interest in today's telecommunication industry, where highly survivable networks need to be constructed. We first study the particular case where the set of demands D is reduced to a single pair {s,t}. We propose an integer programming formulation for the problem, which consists in the st-cut and trivial inequalities, along with the so-called L-st-path-cut inequalities. We show that these three classes of inequalities completely describe the associated polytope when k=2 and L=2 or 3, and give necessary and sufficient conditions for them to be facet-defining. We also consider the dominant of the associated polytope, and discuss how the previous inequalities can be separated in polynomial time. We then extend the complete and minimal description obtained above to any number k of required edge-disjoint L-st-paths, but when L=2 only. We devise a cutting plane algorithm to solve the problem, using the previous polynomial separations, and present some computational results. After that, we consider the case where there is more than one demand in D. We first show that the problem is strongly NP-hard, for all L fixed, even when all the demands in D have one root node in common. For k=2 and L=2,3, we give an integer programming formulation, based on the previous constraints written for all pairs {s,t} in D. We then proceed by giving several new classes of facet-defining inequalities, valid for the problem in general, but more adapted to the rooted case. We propose separation procedures for these inequalities, which are embedded within a Branch-and-Cut algorithm to solve the problem when L=2,3. Extensive computational results from it are given and analyzed for both random and real instances. Since those results appear less satisfactory in the case of arbitrary demands (non necessarily rooted), we present additional families of valid inequalites in that situation. Again, separation procedures are devised for them, and added to our previous Branch-and-Cut algorithm, in order to see the practical improvement granted by them. Finally, we study the problem for greater values of L. In particular, when L=4, we propose new families of constraints for the problem of finding a subgraph that contains at least two L-st-paths either node-disjoint, or edge-disjoint. Using these, we obtain an integer programming formulation in the space of the design variables for each case. ------------------------------------------------ Dans cette thèse, nous considérons le problème de conception de réseau k-arete connexe à chemins L-bornés. Etant donné un graphe pondéré G=(N,E), un ensemble D de paires de noeuds terminaux, et deux entiers k,L > 1, ce problème consiste à trouver, dans G, un sous-graphe de cout minimum tel que, entre chaque paire dans D, il existe au moins k chemins arete-disjoints de longueur au plus L. Ce problème est d'un grand intéret dans l'industrie des télécommunications, où des réseaux hautement fiables doivent etre construits. Nous étudions tout d'abord le cas particulier où l'ensemble des demandes D est réduit à une seule paire de noeuds. Nous proposons une formulation du problème sous forme de programme linéaire en nombres entiers, laquelle consiste en les inégalités triviales et de coupe, ainsi que les inégalités dites de L-chemin-coupe. Nous montrons que ces trois types d'inégalités décrivent complètement le polytope associé lorsque k=2 et L=2,3, et donnons des conditions nécessaires et suffisantes pour que celles-ci en définissent des facettes. Nous considérons également le dominant du polytope associé et discutons de la séparation polynomiale des trois classes précédentes. Nous étendons alors cette description complète et minimale à tout nombre k de chemins arete-disjoints de longueur au plus 2. De plus, nous proposons un algorithme de plans coupants utilisant les précédentes séparations polynomiales, et en présentons quelques résultats calculatoires, pour tout k>1 et L=2,3. Nous considérons ensuite le cas où plusieurs demandes se trouvent dans D. Nous montrons d'abord que le problème est fortement NP-dur, pour tout L fixé et ce, meme si les demandes sont toutes enracinées en un noeud. Pour k=2 et L=2,3, nous donnons une formulation du problème sous forme de programme linéaire en nombres entiers. Nous proposons également de nouvelles classes d'inégalités valides, pour lesquelles nous réalisons une étude faciale. Celles-ci sont alors séparées dans le cadre d'un algorithme de coupes et branchements pour résoudre des instances aléatoires et réelles du problème. Enfin, nous étudions le problème pour de plus grandes valeurs de L. En particulier, lorsque L=4, nous donnons de nouvelles familles de contraintes pour le problème consistant à déterminer un sous-graphe contenant entre deux noeuds fixés au moins deux chemins de longueur au plus 4, que ceux-ci doivent etre arete-disjoints ou noeud-disjoints. Grace à ces dernières, nous parvenons à donner une formulation naturelle du problème dans chacun de ces deux cas.

Muitas operações cognitivas requerem velocidade de processamento de informação (VPI) suficiente para serem executadas dentro do prazo permitido, sendo que VPI retardada geralmente está subjacente a déficits atencionais. A desaceleração no tempo de resposta é particularmente evidente em pacientes com traumatismo crânio-encefálico, doença de Parkinson, depressão, demência e esclerose múltipla (EM). A importância de compreender os déficits de VPI e o desenvolvimento de programas efetivos de reabilitação é, portanto, crítico. Devido à sua alta validade preditiva e à sua fácil administração, o Symbol Digit Modalities Test (SDMT) é um dos testes clínicos mais amplamente utilizados para a avaliação cognitiva de pacientes com menor VPI. No entanto, além de avaliar a presença e gravidade de seus déficits, é interessante determinar as regiões cerebrais responsáveis por essa função e sua integração. Devido à sua não invasividade e ao seu bom nível de confiabilidade, a técnica de Imagem de Ressonância Magnética Funcional Dependente do Nível de Oxigenação no Sangue (BOLD-fMRI) é a ferramenta mais apropriada para esse fim. Logo, o objetivo do presente estudo foi o mapeamento funcional cerebral de VPI durante o desempenho de uma tarefa (SDMT) adaptada para o ambiente da ressonância em um grupo de voluntários saudáveis jovens. 16 controles saudáveis destros foram recrutados e submetidos à avaliação cognitiva com a versão oral do SDMT antes da aquisição de imagens. IRM foi adquirida em um sistema de 3T (Philips Achieva). Imagens funcionais (BOLD) foram adquiridas com uma sequência EPI. O experimento consistiu de seis blocos de 30 s de controle intercalados com cinco blocos de 30 segundos de tarefa (SDMT). Durante os blocos de tarefa, um símbolo foi apresentado a cada 2 segundos e ao participante foi requerido que associasse o número correspondente ao símbolo apresentado baseando-se em uma chave de resposta. Durante os blocos de controle, um número foi apresentado a cada 2 segundos e ao participante foi requerido que lesse silenciosamente o número em questão. Mapas paramétricos estatísticos foram obtidos para estudo de localização funcional utilizando o Modelo Linear Geral com um regressor boxcar convoluído com uma função de resposta hemodinâmica canônica (p-FDR < 0,01). Foi realizada a correlação bivariada entre as séries temporais médias das regiões associadas à tarefa para estudo de integração funcional (p-FDR < 0.0001). As informações de localização e integração funcionais foram inseridas em analise de conectividade efetiva. Ativações foram observadas na rede frontoparietal e no córtex occipital para análises individual e em grupo. Análise de conectividade efetiva para a arquitetura do sistema revelou o declive em posição serial com o giro lingual, o cúneo e duas regiões paralelas (pré-cúneo e lóbulo parietal superior), a partir do qual a informação converge para o giro frontal inferior e se bifurca para os giros frontais médios esquerdo e direito. Um modelo de rede envolvendo áreas relacionadas à VPI foi obtido e pode servir como referência para investigações futuras deste processo cognitivo em grupos clínicos, combinadas com estudos de neuroplasticidade cerebral. / Many cognitive operations require sufficient information processing speed (IPS) to be executed within the allowed time frame, with delayed IPS often underlining attentional deficits. The deceleration in response time is particularly evident in patients with traumatic brain injury, Parkinson\'s disease, depression, dementia and multiple sclerosis (MS). The importance of understanding IPS deficits and developing effective rehabilitation programs is therefore critical. Because of its high predictive validity and easy administration, the Symbol Digit Modalities Test (SDMT) is one of the most widely used clinical tests for the cognitive assessment of patients with lower IPS. However, in addition to evaluating the presence and severity of its deficits, it is interesting to determine the brain regions responsible for this function and its integration. Because of its non-invasiveness and its good level of reliability, the BOLD-fMRI technique is the most appropriate tool for this purpose. Therefore, the aim of the present study was the functional brain function mapping of IPS during the performance of a task (SDMT) adapted to the resonance environment in a group of healthy young volunteers. 16 healthy right controls were recruited and submitted to cognitive assessment with the oral version of SDMT prior to image acquisition. MRI was acquired in a 3T system (Philips Achieva). Functional images (BOLD) were acquired with an EPI sequence. The experiment consisted of six blocks of 30 s of control intercalated with five blocks of 30 seconds of task (SDMT). During the task blocks, a symbol was displayed every 2 seconds and the participant was required to associate the number corresponding to the displayed symbol based on a response key. During the control blocks, a number was displayed every 2 seconds and the participant was required to silently read the number in question. Statistical parametric maps were obtained for functional localization study using the General Linear Model with a boxcar regressor convolved with a canonical hemodynamic response function (p-FDR <0.01). The bivariate correlation between the mean time series of the regions associated with the task for functional integration study (p-FDR <0.0001) was performed. The functional location and integration information was inserted into effective connectivity analysis. Activations were observed in the frontoparietal network and in the occipital cortex for individual and group analyzes. Effective connectivity analysis for the system architecture revealed the declive in serial position with the lingual gyrus, the cuneus and two parallel regions (precuneus and superior parietal lobule), from which the information converges to the inferior frontal gyrus and bifurcates to the left and right middle turns. A network model involving areas related to IPS has been obtained and may serve as a reference for future investigations of this cognitive process in clinical groups, combined with studies of cerebral neuroplasticity.

A evolução da computação móvel melhora a capacidade de comunicação e colaboração das pessoas. Os principais pilares desta transformação são: o desenvolvimento e produção de dispositivos móveis com capacidade multimídia e equipados com duas ou mais interfaces de rede, a disponibilidade de conectividade sem fio ubíqua e a popularização de aplicações sociais online. As redes sociais online merecem destaque pelas funcionalidades que permitem a criação e compartilhamento de conteúdo digital dentro de círculos sociais, também chamado de mídia social. Serviços na web anexam a localização geográfica do dispositivo ao conteúdo digital, criando as chamadas mídias sociais baseadas em localização. Equipadas com seus telefones e tablets, as pessoas estão criando e consumindo mídias sociais em qualquer lugar. Entretanto, é um desafio manter tais dispositivos móveis conectados nos ambientes de rede sem fio atuais e de próxima geração e.g., múltiplos provedores de acesso e múltiplas tecnologias de comunicação. Pesquisas recentes propõem componentes para o gerenciamento de conectividade sem fio que fazem uso simultâneo do contexto de conectividade atual e de um conjunto destes dados coletados no passado. Tais componentes são preditores de mobilidade, mecanismos de handover ou gerenciadores de mobilidade que utilizam dados de contexto de conectividade de forma particular para atingir seus propósitos. Na presente investigação, propomos uma metodologia que orquestra os principais componentes de gerenciamento de conectividade em um laço retro alimentado. Argumentamos que a coleta de dados de contexto de conectividade pode ser projetada como um sistema de sensoreamento, cujo sensores são as interfaces de rede sem fio. Como parte deste sistema de sensoriamento, os círculos sociais podem assistir o gerenciamento de conectividade compartilhando dados de contexto de conectividade. A ideia central é utilizar serviços baseados em localização para compartilhar dados de contexto de conectividade dentro dos círculos sociais. Desta forma, as redes sociais online adicionam escala para o sistema e permite colaboração em volta de dados de contexto recentes, locais, personalizados e sociais. O objetivo é melhorar experiências de conectividade sem fio e.g., métricas de QoS (Quality of Service) como: vazão, latência e qualidade do sinal. Relatamos como os dados de contexto de conectividade são manipulados com um modelo baseado em grafos e métricas como: intensidade do vértice e grau centralidade. Com isso, identificamos áreas com alta densidade de handovers, definimos a reputação dos usuários e revelamos a cobertura das redes. Resultados de experimentos mostram que a colaboração pode melhorar métricas de QoS de ~18 a ~30% se comparado ao uso de um preditor de mobilidade ou um sistema operacional moderno, respectivamente. Esta discussão se desdobra com foco na viabilidade da solução em termos de sobrecarga de armazenamento e consumo de energia. Os promissores resultados experimentais indicam que nossa solução pode melhorar experiências de conectividade sem fio de usuários móveis / The evolution of mobile computing improves communication and collaboration among people. The main pillars of this transformation are: the development and production of mobile devices with multimedia capabilities and equipped with two or more network interfaces, the availability of ubiquitous wireless connectivity and the popularity of online social applications. Online social networks noteworthy features that allow for the creation and sharing of digital content within social circles, also called textit Social Media. Web Services attach the geographic location of the device to the digital content, creating the so-called textit location-based social media. Equipped with their phones and tablets, people are creating and consuming social media anywhere. However, it is a challenge to keep such mobile devices connected in current and next generation wireless network environments textit e.g., multiple ISPs (Internet Service Provider) and multiple communication technologies. Recent researches proposes components for managing wireless connectivity that make simultaneous use of the current and past connectivity context data. Such components are mobility predictors, handovers mechanisms or mobility managers that use connectivity context data in a particular way to achieve its purposes. In this research, we propose feasiable a methodology that orchestrates the main components of the connectivity management in a feedback loop. We argue that the process of gathering connectivity context data can be designed as a sensing system, whose sensors are wireless network interfaces. As part of this sensing system, the social circles may assist the management of connectivity by sharing connectivity context data. The main idea is to use location-based services to share connectivity context data within social circles. Thus, online social networks add scale to the system and enables collaboration around recent, local, and social context data. The goal is to enhance wireless connectivity experiences in terms of QoS ( textit Quality of Service) metrics textit e.g., throughput, latency and signal quality. We report how this data is handled using complex networks metrics e.g., vertexs strength and centrality degree, to identify high density handover areas, define the mobile users reputation and to reveal the networks coverage. Real experiments showed that collaboration can improve QoS metrics from ~18 to ~30% if compared to just use a mobility predictor or a modern operational system, respectively. The discussion unfolds with focus on the collaborations efficiency as function of time, number of users, discovered area size and mobility patterns. The promising experimental results indicate that our solution can enhance mobile users wireless connectivity experiences

Topographic depressions are naturally occurring low land areas surrounded by areas of high elevations, also known as “pits” or “sinks”, on terrain surfaces. Traditional watershed modeling often neglects the potential effects of depressions by implementing removal (mostly filling) procedures on the digital elevation model (DEM) prior to the simulation of physical processes. The assumption is that all the depressions are either spurious in the DEM or of negligible importance for modeling results. However, studies suggested that naturally occurring depressions can change runoff response and connectivity in a watershed based on storage conditions and their spatial arrangement, e.g., shift active contributing areas and soil moisture distributions, and timing and magnitude of flow discharge at the watershed outlet. In addition, recent advances in remote sensing techniques, such as LiDAR, allow us to examine this modeling assumption because naturally occurring depressions can be represented using high-resolution DEM. This dissertation provides insights on the effects of depressions on overland flow processes at multiple spatial scales, from internal depression areas to the watershed scale, based on hydrologic connectivity metrics. Connectivity describes flow pathway connectedness and is assessed using geostatistical measures of heterogeneity in overland flow patterns, i.e., connectivity function and integral connectivity scale lengths. A new algorithm is introduced here to upscale connectivity metrics to large gridded patterns (i.e., with > 1,000,000 cells) using GPU-accelerated computing. This new algorithm is sensitive to changes of connectivity directions and magnitudes in spatial patterns and is robust for large DEM grids with depressions. Implementation of the connectivity metrics to overland flow patterns generated from original and depression filled DEMs for a study watershed indicates that depressions typically decrease overland flow connectivity. A series of macro connectivity stages based on spatial distances are identified, which represent changes in the interaction mechanisms between overland flow and depressions, i.e., the relative dominance of fill and spill, and the relative speed of fill and formation of connected pathways. In addition, to study the role of spatial resolutions on such interaction mechanisms at watershed scale, two revised functional connectivity metrics are also introduced, based on depressions that are hydraulically connected to the watershed outlet and runoff response to rainfall. These two functional connectivity metrics are sensitive to connectivity changes in overland flow patterns because of depression removal (filling) for DEMs at different grid resolutions. Results show that these two metrics indicate the spatial and statistical characteristics of depressions and their implications on overland flow connectivity, and may also relate to storage and infiltration conditions. In addition, grid resolutions have a more significant impact on overland flow connectivity than depression removal (filling).

No description available.

Women exhibit greater habituation to painful stimuli than men. The neural mechanism underlying this sex difference is unknown. However, pain habituation has been associated with pain-evoked activity of the subgenual anterior cingulate cortex (sgACC), implicating a connection between the sgACC and the descending pain antinociceptive system. Therefore, the thesis hypothesis was that women have stronger connectivity than men between the sgACC and the descending antinociceptive system. Healthy subjects provided informed consent. 3T MRI images included anatomical diffusion-weighted imaging for structural connectivity analyses (SC) with probabilistic tractography and resting-state functional images for functional connectivity (FC) analyses. Women had stronger sgACC FC with nodes of the descending pain modulation system (raphe, PAG) and the medial thalamus. In contrast, men had stronger sgACC FC with nodes of the salience/attention network (anterior insula, TPJ) and stronger sgACC SC with the hypothalamus. These findings implicate a mechanism for pain habituation and its associated sex differences.

Women exhibit greater habituation to painful stimuli than men. The neural mechanism underlying this sex difference is unknown. However, pain habituation has been associated with pain-evoked activity of the subgenual anterior cingulate cortex (sgACC), implicating a connection between the sgACC and the descending pain antinociceptive system. Therefore, the thesis hypothesis was that women have stronger connectivity than men between the sgACC and the descending antinociceptive system. Healthy subjects provided informed consent. 3T MRI images included anatomical diffusion-weighted imaging for structural connectivity analyses (SC) with probabilistic tractography and resting-state functional images for functional connectivity (FC) analyses. Women had stronger sgACC FC with nodes of the descending pain modulation system (raphe, PAG) and the medial thalamus. In contrast, men had stronger sgACC FC with nodes of the salience/attention network (anterior insula, TPJ) and stronger sgACC SC with the hypothalamus. These findings implicate a mechanism for pain habituation and its associated sex differences.

Muitas operações cognitivas requerem velocidade de processamento de informação (VPI) suficiente para serem executadas dentro do prazo permitido, sendo que VPI retardada geralmente está subjacente a déficits atencionais. A desaceleração no tempo de resposta é particularmente evidente em pacientes com traumatismo crânio-encefálico, doença de Parkinson, depressão, demência e esclerose múltipla (EM). A importância de compreender os déficits de VPI e o desenvolvimento de programas efetivos de reabilitação é, portanto, crítico. Devido à sua alta validade preditiva e à sua fácil administração, o Symbol Digit Modalities Test (SDMT) é um dos testes clínicos mais amplamente utilizados para a avaliação cognitiva de pacientes com menor VPI. No entanto, além de avaliar a presença e gravidade de seus déficits, é interessante determinar as regiões cerebrais responsáveis por essa função e sua integração. Devido à sua não invasividade e ao seu bom nível de confiabilidade, a técnica de Imagem de Ressonância Magnética Funcional Dependente do Nível de Oxigenação no Sangue (BOLD-fMRI) é a ferramenta mais apropriada para esse fim. Logo, o objetivo do presente estudo foi o mapeamento funcional cerebral de VPI durante o desempenho de uma tarefa (SDMT) adaptada para o ambiente da ressonância em um grupo de voluntários saudáveis jovens. 16 controles saudáveis destros foram recrutados e submetidos à avaliação cognitiva com a versão oral do SDMT antes da aquisição de imagens. IRM foi adquirida em um sistema de 3T (Philips Achieva). Imagens funcionais (BOLD) foram adquiridas com uma sequência EPI. O experimento consistiu de seis blocos de 30 s de controle intercalados com cinco blocos de 30 segundos de tarefa (SDMT). Durante os blocos de tarefa, um símbolo foi apresentado a cada 2 segundos e ao participante foi requerido que associasse o número correspondente ao símbolo apresentado baseando-se em uma chave de resposta. Durante os blocos de controle, um número foi apresentado a cada 2 segundos e ao participante foi requerido que lesse silenciosamente o número em questão. Mapas paramétricos estatísticos foram obtidos para estudo de localização funcional utilizando o Modelo Linear Geral com um regressor boxcar convoluído com uma função de resposta hemodinâmica canônica (p-FDR < 0,01). Foi realizada a correlação bivariada entre as séries temporais médias das regiões associadas à tarefa para estudo de integração funcional (p-FDR < 0.0001). As informações de localização e integração funcionais foram inseridas em analise de conectividade efetiva. Ativações foram observadas na rede frontoparietal e no córtex occipital para análises individual e em grupo. Análise de conectividade efetiva para a arquitetura do sistema revelou o declive em posição serial com o giro lingual, o cúneo e duas regiões paralelas (pré-cúneo e lóbulo parietal superior), a partir do qual a informação converge para o giro frontal inferior e se bifurca para os giros frontais médios esquerdo e direito. Um modelo de rede envolvendo áreas relacionadas à VPI foi obtido e pode servir como referência para investigações futuras deste processo cognitivo em grupos clínicos, combinadas com estudos de neuroplasticidade cerebral. / Many cognitive operations require sufficient information processing speed (IPS) to be executed within the allowed time frame, with delayed IPS often underlining attentional deficits. The deceleration in response time is particularly evident in patients with traumatic brain injury, Parkinson\'s disease, depression, dementia and multiple sclerosis (MS). The importance of understanding IPS deficits and developing effective rehabilitation programs is therefore critical. Because of its high predictive validity and easy administration, the Symbol Digit Modalities Test (SDMT) is one of the most widely used clinical tests for the cognitive assessment of patients with lower IPS. However, in addition to evaluating the presence and severity of its deficits, it is interesting to determine the brain regions responsible for this function and its integration. Because of its non-invasiveness and its good level of reliability, the BOLD-fMRI technique is the most appropriate tool for this purpose. Therefore, the aim of the present study was the functional brain function mapping of IPS during the performance of a task (SDMT) adapted to the resonance environment in a group of healthy young volunteers. 16 healthy right controls were recruited and submitted to cognitive assessment with the oral version of SDMT prior to image acquisition. MRI was acquired in a 3T system (Philips Achieva). Functional images (BOLD) were acquired with an EPI sequence. The experiment consisted of six blocks of 30 s of control intercalated with five blocks of 30 seconds of task (SDMT). During the task blocks, a symbol was displayed every 2 seconds and the participant was required to associate the number corresponding to the displayed symbol based on a response key. During the control blocks, a number was displayed every 2 seconds and the participant was required to silently read the number in question. Statistical parametric maps were obtained for functional localization study using the General Linear Model with a boxcar regressor convolved with a canonical hemodynamic response function (p-FDR <0.01). The bivariate correlation between the mean time series of the regions associated with the task for functional integration study (p-FDR <0.0001) was performed. The functional location and integration information was inserted into effective connectivity analysis. Activations were observed in the frontoparietal network and in the occipital cortex for individual and group analyzes. Effective connectivity analysis for the system architecture revealed the declive in serial position with the lingual gyrus, the cuneus and two parallel regions (precuneus and superior parietal lobule), from which the information converges to the inferior frontal gyrus and bifurcates to the left and right middle turns. A network model involving areas related to IPS has been obtained and may serve as a reference for future investigations of this cognitive process in clinical groups, combined with studies of cerebral neuroplasticity.