Evaluación neuropsicológica en pacientes bipolares eutímicos: un estudio comparativo con pacientes esquizofrénicos estabilizados

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid. Facultad de Medicina. Departamento de Psiquiatría. Fecha de lectura: 21 de Febrero de 200

Morphosedimentary and phytogeography reconstruction of the middle section of the river Jarama (Madrid, Spain) during the second half of the Holocene.

[Abstract] Two sites located on the alluvial plain of the Jarama River, near Madrid, Spain, have been studied using geological, palynological and xylological techniques. Uniquely for this region, numerous wood subfossils of Alnus and Ulmus have been found together with an strobile of Pinus halepensis. This has allowed the stablishment of a coherent radiocarbon chronology, which demonstrates that these sedimentary environments began to develop during the mid Holocene. The dated sediments, which also contains appreciable amounts of pollen, have been deposited upon older palaeosols which has in turn developed directly on the geological substrate. Palynological analyses of these levels have provided valuable insights into the floristic composition of the communities associated with the different biotopes present in the area. As a result of these multiproxy analyses an interpretation of Holocene landscape history and vegetation dynamics is presente

Estudio paleobotánico de estróbilos y maderas subfósiles holocenas en el yacimiento de Cevico Navero (Palencia, España)

This paper reports results of work at the Cevico Navero site in Palencia, Spain. Macro- and microscopic study of the subfossil cones and trunks found at the site has permitted their identification to the species Pinus nigra. Radiocarbon dating of the wood indicates that this pine species was present in the región 3,500 years ago. The results are discussed in the context of other relevant literature. The dynamics of vegetation cover in the study área and the paleochorology of P. nigra are considered.Se exponen en este artículo los resultados del trabajo llevado a cabo en el yacimiento de Cevico Navero (Palencia, España) en el que han sido hallados restos subfósiles de estróbilos y troncos. El estudio mediante anatomía comparada -macro y microscópica- de dichos materiales ha permitido asignarlos a la especie Pinus nigra. La datación radiocarbónica de la madera revela la presencia de esta especie de pino en esa zona de la provincia de Palencia hace unos 3.500 años. Con estos datos y otros bibliográficos se hace una discusión acerca de la posible dinámica de la cubierta vegetal en el ámbito geográfico considerado, así como de la paleocorología del propio P. nigr

Computer-aided diagnosis of multiple sclerosis using a support vector machine and optical coherence tomography features

The purpose of this paper is to evaluate the feasibility of diagnosing multiple sclerosis (MS) using optical coherence tomography (OCT) data and a support vector machine (SVM) as an automatic classifier. Forty-eight MS patients without symptoms of optic neuritis and forty-eight healthy control subjects were selected. Swept-source optical coherence tomography (SS-OCT) was performed using a DRI (deep-range imaging) Triton OCT device (Topcon Corp., Tokyo, Japan). Mean values (right and left eye) for macular thickness (retinal and choroidal layers) and peripapillary area (retinal nerve fibre layer, retinal, ganglion cell layer—GCL, and choroidal layers) were compared between both groups. Based on the analysis of the area under the receiver operator characteristic curve (AUC), the 3 variables with the greatest discriminant capacity were selected to form the feature vector. A SVM was used as an automatic classifier, obtaining the confusion matrix using leave-one-out cross-validation. Classification performance was assessed with Matthew’s correlation coefficient (MCC) and the AUCCLASSIFIER. The most discriminant variables were found to be the total GCL++ thickness (between inner limiting membrane to inner nuclear layer boundaries), evaluated in the peripapillary area and macular retina thickness in the nasal quadrant of the outer and inner rings. Using the SVM classifier, we obtained the following values: MCC = 0.81, sensitivity = 0.89, specificity = 0.92, accuracy = 0.91, and AUCCLASSIFIER = 0.97. Our findings suggest that it is possible to classify control subjects and MS patients without previous optic neuritis by applying machine-learning techniques to study the structural neurodegeneration in the retina

Identification of clusters in multifocal electrophysiology recordings to maximize discriminant capacity (patients vs. control subjects)

Purpose To propose a new method of identifying clusters in multifocal electrophysiology (multifocal electroretinogram: mfERG; multifocal visual-evoked potential: mfVEP) that conserve the maximum capacity to discriminate between patients and control subjects. Methods The theoretical framework proposed creates arbitrary N-size clusters of sectors. The capacity to discriminate between patients and control subjects is assessed by analysing the area under the receiver operator characteristic curve (AUC). As proof of concept, the method is validated using mfERG recordings taken from both eyes of control subjects (n = 6) and from patients with multiple sclerosis (n = 15). Results Considering the amplitude of wave P1 as the analysis parameter, the maximum value of AUC = 0.7042 is obtained with N = 9 sectors. Taking into account the AUC of the amplitudes and latencies of waves N1 and P1, the maximum value of the AUC = 0.6917 with N = 8 clustered sectors. The greatest discriminant capacity is obtained by analysing the latency of wave P1: AUC = 0.8854 with a cluster of N = 12 sectors. Conclusion This paper demonstrates the effectiveness of a method able to determine the arbitrary clustering of multifocal responses that possesses the greatest capacity to discriminate between control subjects and patients when applied to the visual field of mfERG or mfVEP recordings. The method may prove helpful in diagnosing any disease that is identifiable in patients’ mfERG or mfVEP recordings and is extensible to other clinical tests, such as optical coherence tomography

Diagnosis of multiple sclerosis using optical coherence tomography supported by artificial intelligence

Background: Current procedures for diagnosing multiple sclerosis (MS) present a series of limitations, making it critically important to identify new biomarkers. The aim of the study was to identify new biomarkers for the early diagnosis of MS using spectral-domain optical coherence tomography (OCT) and artificial intelligence. Methods: Spectral domain OCT was performed on 79 patients with relapsing-remitting multiple sclerosis (RRMS) (disease duration ≤ 2 years, no history of optic neuritis) and on 69 age-matched healthy controls using the posterior pole protocol that incorporates the anatomic Positioning System. Median retinal thickness values in both eyes and inter-eye difference in healthy controls and patients were evaluated by area under the receiver operating characteristic (AUROC) curve analysis in the foveal, parafoveal and perifoveal areas and in the overall area spanned by the three rings. The structures with the greatest discriminant capacity — retinal thickness and inter-eye difference — were used as inputs to a convolutional neural network to assess the diagnostic capability. Results: Analysis of retinal thickness and inter-eye difference in RRMS patients revealed that greatest alteration occurred in the ganglion cell (GCL), inner plexiform (IPL), and inner retinal (IRL) layers. By using the average thickness of the GCL (AUROC = 0.82) and the inter-eye difference in the IPL (AUROC = 0.71) as inputs to a two-layer convolutional neural network, automatic diagnosis attained accuracy = 0.87, sensitivity = 0.82, and specificity = 0.92. Conclusion: This study adds weight to the argument that neuroretinal structure analysis could be incorporated into the diagnostic criteria for MS

Continuous‑wavelet‑transform analysis of the multifocal ERG waveform in glaucoma diagnosis

The vast majority of multifocal electroretinogram (mfERG) signal analyses to detect glaucoma study the signals’ amplitudes and latencies. The purpose of this paper is to investigate application of wavelet analysis of mfERG signals in diagnosis of glaucoma. This analysis method applies the continuous wavelet transform (CWT) to the signals, using the real Morlet wavelet. CWT coefficients resulting from the scale of maximum correlation are used as inputs to a neural network, which acts as a classifier. mfERG recordings are taken from the eyes of 47 subjects diagnosed with chronic open-angle glaucoma and from those of 24 healthy subjects. The high sensitivity in the classification (0.894) provides reliable detection of glaucomatous sectors, while the specificity achieved (0.844) reflects accurate detection of healthy sectors. The results obtained in this paper improve on the previous findings reported by the authors using the same visual stimuli and database.Ministerio de Ciencia e Innovació

Neurocognition and functional outcome in patients with psychotic, non-psychotic bipolar I disorder, and schizophrenia. A five-year follow-up

Bipolar disorder (BD) and schizophrenia (SZ) are characterized by neurocognitive and functional deficits with marked heterogeneity. It has been suggested that BD with a history of psychotic symptoms (BD-P) could constitute a phenotypically homogeneous subtype characterized by greater neurocognitive and functional impairments, or by a distinct trajectory of such deficits. The aim of this study was to compare the neurocognitive and functional course of euthymic BD-P, euthymic BD patients without a history of psychosis (BD-NP), stabilized patients with schizophrenia and healthy subjects, during a five-year follow-up

Bayesian reasoning with emotional material in patients with schizophrenia.

Delusions are one of the most classical symptoms described in schizophrenia. However, despite delusions are often emotionally charged, they have been investigated using tasks involving non-affective material, such as the Beads task. In this study we compared 30 patients with schizophrenia experiencing delusions with 32 matched controls in their pattern of responses to two versions of the Beads task within a Bayesian framework. The two versions of the Beads task consisted of one emotional and one neutral, both with ratios of beads of 60:40 and 80:20, considered, respectively, as the “difficult” and “easy” variants of the task. Results indicate that patients showed a greater deviation from the normative model, especially in the 60:40 ratio, suggesting that more inaccurate probability estimations are more likely to occur under uncertainty conditions. Additionally, both patients and controls showed a greater deviation in the emotional version of the task, providing evidence of a reasoning bias modulated by the content of the stimuli. Finally, a positive correlation between patients’ deviation and delusional symptomatology was found. Impairments in the 60:40 ratio with emotional content was related to the amount of disruption in life caused by delusions. These results contribute to the understanding of how cognitive mechanisms interact with characteristics of the task (i.e., ambiguity and content) in the context of delusional thinking. These findings might be used to inform improved intervention programs in the domain of inferential reasoning.post-print700 K