Emotions, Not Just Decision-Making Processes, Are Critical to an Evolutionary Model of Human Behavior

An evolutionary model of human behavior should privilege emotions: essential, phylogenetically ancient behaviors that learning and decision making only subserve. Infants and non-mammals lack advanced cognitive powers but still survive. Decision making is only a means to emotional ends, which organize and prioritize behavior. The emotion of pride/shame, or dominance striving, bridges the social and biological sciences via internalization of cultural norms.

A LAPLACE TRANSFORM PAIR MODEL TO DETERMINE BREMSSTRAHLUNG SPECTRA FROM ATTENUATION DATA (RADIATION, X-RAY, SPECTRAL MODELING)

Every x-ray attenuation curve inherently contains all the information necessary to extract the complete energy spectrum of a beam. To date, attempts to obtain accurate spectral information from attenuation data have been inadequate.^ This investigation presents a mathematical pair model, grounded in physical reality by the Laplace Transformation, to describe the attenuation of a photon beam and the corresponding bremsstrahlung spectral distribution. In addition the Laplace model has been mathematically extended to include characteristic radiation in a physically meaningful way. A method to determine the fraction of characteristic radiation in any diagnostic x-ray beam was introduced for use with the extended model.^ This work has examined the reconstructive capability of the Laplace pair model for a photon beam range of from 50 kVp to 25 MV, using both theoretical and experimental methods.^ In the diagnostic region, excellent agreement between a wide variety of experimental spectra and those reconstructed with the Laplace model was obtained when the atomic composition of the attenuators was accurately known. The model successfully reproduced a 2 MV spectrum but demonstrated difficulty in accurately reconstructing orthovoltage and 6 MV spectra. The 25 MV spectrum was successfully reconstructed although poor agreement with the spectrum obtained by Levy was found.^ The analysis of errors, performed with diagnostic energy data, demonstrated the relative insensitivity of the model to typical experimental errors and confirmed that the model can be successfully used to theoretically derive accurate spectral information from experimental attenuation data. ^

Bayesian generalized linear models for meta-analysis of diagnostic tests

With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

The diagnostic value of a 12-lead electrocardiogram in patients with cardiac tamponade due to a malignant pericardial effusion

Background. Cardiac tamponade can occur when a large amount of fluid, gas, singly or in combination, accumulating within the pericardium, compresses the heart causing circulatory compromise. Although previous investigators have found the 12-lead ECG to have a poor predictive value in diagnosing cardiac tamponade, very few studies have evaluated it as a follow up tool for ruling in or ruling out tamponade in patients with previously diagnosed malignant pericardial effusions. ^ Methods. 127 patients with malignant pericardial effusions at the MD Anderson Cancer Center were included in this retrospective study. While 83 of these patients had a cardiac tamponade diagnosed by echocardiographic criteria (Gold standard), 44 did not. We computed the sensitivity (Se), specificity (Sp), positive (PPV) and negative predictive values (NPV) for individual and combinations of ECG abnormalities. Individual ECG abnormalities were also entered singly into a univariate logistic regression model to predict tamponade. ^ Results. For patients with effusions of all sizes, electrical alternans had a Se, Sp, PPV and NPV of 22.61%, 97.61%, 95% and 39.25% respectively. These parameters for low voltage complexes were 55.95%, 74.44%, 81.03%, 46.37% respectively. The presence of all three ECG abnormalities had a Se = 8.33%, Sp = 100%, PPV = 100% and NPV = 35.83% while the presence of at least one of the three ECG abnormalities had a Se = 89.28%, Sp = 46.51%, PPV = 76.53%, NPV = 68.96%. For patients with effusions of all sizes electrical alternans had an OR of 12.28 (1.58–95.17, p = 0.016), while the presence of at least one ECG abnormality had an OR of 7.25 (2.9–18.1, p = 0.000) in predicting tamponade. ^ Conclusions. Although individual ECG abnormalities had low sensitivities, specificities, NPVs and PPVs with the exception of electrical alternans, the presence of at least one of the three ECG abnormalities had a high sensitivity in diagnosing cardiac tamponade. This could point to its potential use as a screening test with a correspondingly high NPV to rule out a diagnosis of tamponade in patients with malignant pericardial effusions. This could save expensive echocardiographic assessments in patients with previously diagnosed pericardial effusions. ^

Bayesian and survival model for tumor relapse status and disease-specific survival, with applications to breast cancer

Breast cancer is the most common non-skin cancer and the second leading cause of cancer-related death in women in the United States. Studies on ipsilateral breast tumor relapse (IBTR) status and disease-specific survival will help guide clinic treatment and predict patient prognosis.^ After breast conservation therapy, patients with breast cancer may experience breast tumor relapse. This relapse is classified into two distinct types: true local recurrence (TR) and new ipsilateral primary tumor (NP). However, the methods used to classify the relapse types are imperfect and are prone to misclassification. In addition, some observed survival data (e.g., time to relapse and time from relapse to death)are strongly correlated with relapse types. The first part of this dissertation presents a Bayesian approach to (1) modeling the potentially misclassified relapse status and the correlated survival information, (2) estimating the sensitivity and specificity of the diagnostic methods, and (3) quantify the covariate effects on event probabilities. A shared frailty was used to account for the within-subject correlation between survival times. The inference was conducted using a Bayesian framework via Markov Chain Monte Carlo simulation implemented in softwareWinBUGS. Simulation was used to validate the Bayesian method and assess its frequentist properties. The new model has two important innovations: (1) it utilizes the additional survival times correlated with the relapse status to improve the parameter estimation, and (2) it provides tools to address the correlation between the two diagnostic methods conditional to the true relapse types.^ Prediction of patients at highest risk for IBTR after local excision of ductal carcinoma in situ (DCIS) remains a clinical concern. The goals of the second part of this dissertation were to evaluate a published nomogram from Memorial Sloan-Kettering Cancer Center, to determine the risk of IBTR in patients with DCIS treated with local excision, and to determine whether there is a subset of patients at low risk of IBTR. Patients who had undergone local excision from 1990 through 2007 at MD Anderson Cancer Center with a final diagnosis of DCIS (n=794) were included in this part. Clinicopathologic factors and the performance of the Memorial Sloan-Kettering Cancer Center nomogram for prediction of IBTR were assessed for 734 patients with complete data. Nomogram for prediction of 5- and 10-year IBTR probabilities were found to demonstrate imperfect calibration and discrimination, with an area under the receiver operating characteristic curve of .63 and a concordance index of .63. In conclusion, predictive models for IBTR in DCIS patients treated with local excision are imperfect. Our current ability to accurately predict recurrence based on clinical parameters is limited.^ The American Joint Committee on Cancer (AJCC) staging of breast cancer is widely used to determine prognosis, yet survival within each AJCC stage shows wide variation and remains unpredictable. For the third part of this dissertation, biologic markers were hypothesized to be responsible for some of this variation, and the addition of biologic markers to current AJCC staging were examined for possibly provide improved prognostication. The initial cohort included patients treated with surgery as first intervention at MDACC from 1997 to 2006. Cox proportional hazards models were used to create prognostic scoring systems. AJCC pathologic staging parameters and biologic tumor markers were investigated to devise the scoring systems. Surveillance Epidemiology and End Results (SEER) data was used as the external cohort to validate the scoring systems. Binary indicators for pathologic stage (PS), estrogen receptor status (E), and tumor grade (G) were summed to create PS+EG scoring systems devised to predict 5-year patient outcomes. These scoring systems facilitated separation of the study population into more refined subgroups than the current AJCC staging system. The ability of the PS+EG score to stratify outcomes was confirmed in both internal and external validation cohorts. The current study proposes and validates a new staging system by incorporating tumor grade and ER status into current AJCC staging. We recommend that biologic markers be incorporating into revised versions of the AJCC staging system for patients receiving surgery as the first intervention.^ Chapter 1 focuses on developing a Bayesian method to solve misclassified relapse status and application to breast cancer data. Chapter 2 focuses on evaluation of a breast cancer nomogram for predicting risk of IBTR in patients with DCIS after local excision gives the statement of the problem in the clinical research. Chapter 3 focuses on validation of a novel staging system for disease-specific survival in patients with breast cancer treated with surgery as the first intervention. ^

Territorial quality and sustainable development : Indicators of performance in the context of a model for participatory rural tourism certification

El turismo rural ha sido incorporado por pequeños establecimientos agropecuarios del partido de Cnel. Suárez, provincia de Buenos Aires, Argentina, como actividad alternativa para mejorar la calidad de vida de sus miembros y superar situaciones de crisis agravadas por la marginalidad productiva del SO bonaerense, región a la que pertenecen. Bajo el programa Cambio Rural del INTA (Instituto Nacional de Tecnología Agropecuaria) conforman el Grupo 'Cortaderas II', junto a otros emprendedores interesados en valorar el medio rural. Han avanzado en el proceso de reconocimiento de su identidad y puesta en valor de recursos específicos con anclaje en el territorio. Esta identidad comienza a apreciarse internamente, a raíz de la dinámica grupal lograda y la incipiente articulación con otros actores para la construcción de un partenariado público y privado que genere sinergias y contribuya al desarrollo sustentable del territorio. Sin embargo, aún no es claramente percibida por el turista, cada vez más exigente. Por lo tanto, el presente trabajo persigue proponer indicadores para evaluar el desempeño de un Sistema de Gestión de Calidad con enfoque territorial que, adaptando el modelo europeo 'Marca de Calidad Territorial', sustente una estrategia comercial de diferenciación del servicio y simultáneamente, mida el progreso hacia una mejor calidad de vida y fortalecimiento de vínculos con la cultura local y el entorno físico-natural en el marco del desarrollo sustentable. La investigación se plantea para la micro escala, ya que se trata de un estudio de caso, relevándose información primaria mediante observación directa y entrevistas semi-estructuradas, complementada con información secundaria diagnóstica utilizada por INTA. Las características del grupo y su dinámica de funcionamiento bajo el programa Cambio Rural revelan que es posible adoptar un proceso de certificación participativa propuesto para cuatro pilares de la calidad: de Bienes y Servicios, Institucional, Social y Ambiental. El modelo se integra con indicadores de evaluación de desempeño, agrupados en áreas clave para cada una de las dimensiones de la sustentabilidad, que contemplan el paisaje y la gestión de los recursos naturales; el impacto económico de la actividad, la calidad de la oferta y satisfacción del turista; así como las relaciones sociales internas y los vínculos con otros actores del territorio. Principalmente se encontraron fortalezas en la búsqueda de partenariados y debilidades en aspectos de comunicación y promoción. Se considera que este sistema de herramientas de gestión sustentable permitiría superar las dificultades de una certificación individual, pudiendo aplicarse a emprendimientos con otra ubicación geográfica

Territorial quality and sustainable development : Indicators of performance in the context of a model for participatory rural tourism certification

El turismo rural ha sido incorporado por pequeños establecimientos agropecuarios del partido de Cnel. Suárez, provincia de Buenos Aires, Argentina, como actividad alternativa para mejorar la calidad de vida de sus miembros y superar situaciones de crisis agravadas por la marginalidad productiva del SO bonaerense, región a la que pertenecen. Bajo el programa Cambio Rural del INTA (Instituto Nacional de Tecnología Agropecuaria) conforman el Grupo 'Cortaderas II', junto a otros emprendedores interesados en valorar el medio rural. Han avanzado en el proceso de reconocimiento de su identidad y puesta en valor de recursos específicos con anclaje en el territorio. Esta identidad comienza a apreciarse internamente, a raíz de la dinámica grupal lograda y la incipiente articulación con otros actores para la construcción de un partenariado público y privado que genere sinergias y contribuya al desarrollo sustentable del territorio. Sin embargo, aún no es claramente percibida por el turista, cada vez más exigente. Por lo tanto, el presente trabajo persigue proponer indicadores para evaluar el desempeño de un Sistema de Gestión de Calidad con enfoque territorial que, adaptando el modelo europeo 'Marca de Calidad Territorial', sustente una estrategia comercial de diferenciación del servicio y simultáneamente, mida el progreso hacia una mejor calidad de vida y fortalecimiento de vínculos con la cultura local y el entorno físico-natural en el marco del desarrollo sustentable. La investigación se plantea para la micro escala, ya que se trata de un estudio de caso, relevándose información primaria mediante observación directa y entrevistas semi-estructuradas, complementada con información secundaria diagnóstica utilizada por INTA. Las características del grupo y su dinámica de funcionamiento bajo el programa Cambio Rural revelan que es posible adoptar un proceso de certificación participativa propuesto para cuatro pilares de la calidad: de Bienes y Servicios, Institucional, Social y Ambiental. El modelo se integra con indicadores de evaluación de desempeño, agrupados en áreas clave para cada una de las dimensiones de la sustentabilidad, que contemplan el paisaje y la gestión de los recursos naturales; el impacto económico de la actividad, la calidad de la oferta y satisfacción del turista; así como las relaciones sociales internas y los vínculos con otros actores del territorio. Principalmente se encontraron fortalezas en la búsqueda de partenariados y debilidades en aspectos de comunicación y promoción. Se considera que este sistema de herramientas de gestión sustentable permitiría superar las dificultades de una certificación individual, pudiendo aplicarse a emprendimientos con otra ubicación geográfica

Territorial quality and sustainable development : Indicators of performance in the context of a model for participatory rural tourism certification

El turismo rural ha sido incorporado por pequeños establecimientos agropecuarios del partido de Cnel. Suárez, provincia de Buenos Aires, Argentina, como actividad alternativa para mejorar la calidad de vida de sus miembros y superar situaciones de crisis agravadas por la marginalidad productiva del SO bonaerense, región a la que pertenecen. Bajo el programa Cambio Rural del INTA (Instituto Nacional de Tecnología Agropecuaria) conforman el Grupo 'Cortaderas II', junto a otros emprendedores interesados en valorar el medio rural. Han avanzado en el proceso de reconocimiento de su identidad y puesta en valor de recursos específicos con anclaje en el territorio. Esta identidad comienza a apreciarse internamente, a raíz de la dinámica grupal lograda y la incipiente articulación con otros actores para la construcción de un partenariado público y privado que genere sinergias y contribuya al desarrollo sustentable del territorio. Sin embargo, aún no es claramente percibida por el turista, cada vez más exigente. Por lo tanto, el presente trabajo persigue proponer indicadores para evaluar el desempeño de un Sistema de Gestión de Calidad con enfoque territorial que, adaptando el modelo europeo 'Marca de Calidad Territorial', sustente una estrategia comercial de diferenciación del servicio y simultáneamente, mida el progreso hacia una mejor calidad de vida y fortalecimiento de vínculos con la cultura local y el entorno físico-natural en el marco del desarrollo sustentable. La investigación se plantea para la micro escala, ya que se trata de un estudio de caso, relevándose información primaria mediante observación directa y entrevistas semi-estructuradas, complementada con información secundaria diagnóstica utilizada por INTA. Las características del grupo y su dinámica de funcionamiento bajo el programa Cambio Rural revelan que es posible adoptar un proceso de certificación participativa propuesto para cuatro pilares de la calidad: de Bienes y Servicios, Institucional, Social y Ambiental. El modelo se integra con indicadores de evaluación de desempeño, agrupados en áreas clave para cada una de las dimensiones de la sustentabilidad, que contemplan el paisaje y la gestión de los recursos naturales; el impacto económico de la actividad, la calidad de la oferta y satisfacción del turista; así como las relaciones sociales internas y los vínculos con otros actores del territorio. Principalmente se encontraron fortalezas en la búsqueda de partenariados y debilidades en aspectos de comunicación y promoción. Se considera que este sistema de herramientas de gestión sustentable permitiría superar las dificultades de una certificación individual, pudiendo aplicarse a emprendimientos con otra ubicación geográfica

Selected age-diagnostic datums of ODP Site 184-1148

The 853 m thick sediment sequence recovered at ODP Site 1148 provides an unprecedented record of tectonic and paleoceanographic evolution in the South China Sea over the past 33 Ma. Litho-, bio-, and chemo-stratigraphic studies helped identify six periods of changes marking the major steps of the South China Sea geohistory. Rapid deposition with sedimentation rates of 60 m/Ma or more characterized the early Oligocene rifting. Several unconformities from the slumped unit between 457 and 495 mcd together erased about 3 Ma late Oligocene record, providing solid evidence of tectonic transition from rifting/slow spreading to rapid spreading in the South China Sea. Slow sedimentation of ~20-30 m/Ma signifies stable seafloor spreading in the early Miocene. Dissolution may have affected the completeness of Miocene-Pleistocene succession with short-term hiatuses beyond current biostratigraphical resolution. Five major dissolution events, D-1 to D-5, characterize the stepwise development of deep water masses in close association to post-Oligocene South China Sea basin transformation. The concurrence of local and global dissolution events in the Miocene and Pliocene suggests climatic forcing as the main mechanism causing deep water circulation changes concomitantly in world oceans and in marginal seas. A return of high sedimentation rate of 60 m/Ma to the late Pliocene and Pleistocene South China Sea was caused by intensified down-slope transport due to frequent sea level fluctuations and exposure of a large shelf area during sea level low-stands. The six paleoceanographic stages, respectively corresponding to rifting (~33-28.5 Ma), changing spreading southward (28.5-23 Ma), stable spreading to end of spreading (23-15 Ma), post-spreading balance (15-9 Ma), further modification and monsoon influence (9-5 Ma), and glacial prevalence (5-0 Ma), had transformed the South China Sea from a series of deep grabens to a rapidly expanding open gulf and finally to a semi-enclosed marginal sea in the past 33 Ma.

A note on three factor model of discounting

In Montiel Olea and Strzalecki (2014), authors have axiomatically developed an algorithm to infer the parameters of beta-delta model of cognitive bias (present and future biases). While this is extremely useful, it allows the implied beta to become very large when the response is impatient in the future choices relative to present choices, i.e., when there is a strong future bias. I modify the model to further exponentiate the functional form to get more reasonable beta values.

A Model of Emotion as Patterned Metacontrol

Adaptive systems use feedback as a key strategy to cope with uncertainty and change in their environments. The information fed back from the sensorimotor loop into the control architecture can be used to change different elements of the controller at four different levels: parameters of the control model, the control model itself, the functional organization of the agent and the functional components of the agent. The complexity of such a space of potential configurations is daunting. The only viable alternative for the agent ?in practical, economical, evolutionary terms? is the reduction of the dimensionality of the configuration space. This reduction is achieved both by functionalisation —or, to be more precise, by interface minimization— and by patterning, i.e. the selection among a predefined set of organisational configurations. This last analysis let us state the central problem of how autonomy emerges from the integration of the cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. In this paper we will show a general model of how the emotional biological systems operate following this theoretical analysis and how this model is also of applicability to a wide spectrum of artificial systems.

A Model of Emotion as Patterned Metacontrol

Adaptive agents use feedback as a key strategy to cope with un- certainty and change in their environments. The information fed back from the sensorimotor loop into the control subsystem can be used to change four different elements of the controller: parameters associated to the control model, the control model itself, the functional organization of the agent and the functional realization of the agent. There are many change alternatives and hence the complexity of the agent’s space of potential configurations is daunting. The only viable alternative for space- and time-constrained agents —in practical, economical, evolutionary terms— is to achieve a reduction of the dimensionality of this configuration space. Emotions play a critical role in this reduction. The reduction is achieved by func- tionalization, interface minimization and by patterning, i.e. by selection among a predefined set of organizational configurations. This analysis lets us state how autonomy emerges from the integration of cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. Emotion-based morphofunctional systems are able to exhibit complex adaptation patterns at a reduced cognitive cost. In this article we show a general model of how emotion supports functional adaptation and how the emotional biological systems operate following this theoretical model. We will also show how this model is also of applicability to the construction of a wide spectrum of artificial systems1.

Using modular neural networks to model self-consciousness and self-representation for artificial entities

Self-consciousness implies not only self or group recognition, but also real knowledge of one’s own identity. Self-consciousness is only possible if an individual is intelligent enough to formulate an abstract self-representation. Moreover, it necessarily entails the capability of referencing and using this elf-representation in connection with other cognitive features, such as inference, and the anticipation of the consequences of both one’s own and other individuals’ acts. In this paper, a cognitive architecture for self-consciousness is proposed. This cognitive architecture includes several modules: abstraction, self-representation, other individuals'representation, decision and action modules. It includes a learning process of self-representation by direct (self-experience based) and observational learning (based on the observation of other individuals). For model implementation a new approach is taken using Modular Artificial Neural Networks (MANN). For model testing, a virtual environment has been implemented. This virtual environment can be described as a holonic system or holarchy, meaning that it is composed of autonomous entities that behave both as a whole and as part of a greater whole. The system is composed of a certain number of holons interacting. These holons are equipped with cognitive features, such as sensory perception, and a simplified model of personality and self-representation. We explain holons’ cognitive architecture that enables dynamic self-representation. We analyse the effect of holon interaction, focusing on the evolution of the holon’s abstract self-representation. Finally, the results are explained and analysed and conclusions drawn.

Efficiency improvement of HF communications using cognitive radio principles

Cognitive Radio principles can be applied to HF communications to make a more efficient use of the extremely scarce spectrum. In this contribution we focus on analyzing the usage of the available channels done by the legacy users, which are regarded as primary users since they are allowed to transmit without resorting any smart procedure, and consider the possibilities for our stations -over the HFDVL (HF Data+Voice Link) architecture- to participate as secondary users. Our goal is to enhance an efficient use of the HF band by detecting the presence of uncoordinated primary users and avoiding collisions with them while transmitting in different HF channels using our broad-band HF transceiver. A model of the primary user activity dynamics in the HF band is developed in this work. It is based on Hidden Markov Models (HMM) which are a powerful tool for modelling stochastic random processes, and is trained with real measurements from the 14 MHz band.

Analysis of spontaneous MEG activity in mild cognitive impairment and Alzheimer's disease using spectral entropies and statistical complexity measures

Alzheimer's disease (AD) is the most common cause of dementia. Over the last few years, a considerable effort has been devoted to exploring new biomarkers. Nevertheless, a better understanding of brain dynamics is still required to optimize therapeutic strategies. In this regard, the characterization of mild cognitive impairment (MCI) is crucial, due to the high conversion rate from MCI to AD. However, only a few studies have focused on the analysis of magnetoencephalographic (MEG) rhythms to characterize AD and MCI. In this study, we assess the ability of several parameters derived from information theory to describe spontaneous MEG activity from 36 AD patients, 18 MCI subjects and 26 controls. Three entropies (Shannon, Tsallis and Rényi entropies), one disequilibrium measure (based on Euclidean distance ED) and three statistical complexities (based on Lopez Ruiz–Mancini–Calbet complexity LMC) were used to estimate the irregularity and statistical complexity of MEG activity. Statistically significant differences between AD patients and controls were obtained with all parameters (p < 0.01). In addition, statistically significant differences between MCI subjects and controls were achieved by ED and LMC (p < 0.05). In order to assess the diagnostic ability of the parameters, a linear discriminant analysis with a leave-one-out cross-validation procedure was applied. The accuracies reached 83.9% and 65.9% to discriminate AD and MCI subjects from controls, respectively. Our findings suggest that MCI subjects exhibit an intermediate pattern of abnormalities between normal aging and AD. Furthermore, the proposed parameters provide a new description of brain dynamics in AD and MCI.