Home Company R&D&iMost important Milestones

Major Technical Milestones Achieved

The following are the major milestones achieved along our scientific career . For this we collect and analyze a wide variety of modalities for both structural and functional brain studies applied to a large number of subjects. , Of which a number of variables that influence one way or another in the structure and activity are known brain such as age, sex, handedness , native language, etc. .

Additionally the activity related to the development of algorithms ( systematic reviews, new algorithms, etc. ), the creation of population maps, information visualization , databases, genomic and proteomic data, etc. , are also particularly important for the proper development our knowledge of the Human System Manager . .

Finally , note that as explained in the following is only a summary to have a rough idea as possible about our project. The full description is accessible only by users with a subscription to our services.

Neuropharmacogenomics information added

on 01 May 2012.

Integración de información neurofamacogenómica

A relationship between genes, diseases and drugs is added to our database.

The goal is to provide the necessary evidence so that they can elucidate the molecular mechanisms by which drugs affect the function of certain genes, and their role in different pathologies.

Creating a Neurogenomic Database

on 15 September 2011.

Creating a Neurogenomic Database

Currently there are a variety of genomic databases, each providing data that are often contradictory, incomplete and sometimes even misleading.This is due to, on one hand, the heterogeneity of the data, and on the other hand, just as with the creation of ontologies, to automatically generate this information without further verification.

Using a variety of databases, among which are the most widely accepted by the scientific community, we have compiled the most relevant data of genes expressed in brain, always providing the scientific evidence of knowledge shown.In order to provide robustness to our knowledge base, different data were collated in a semi-manual way.

Use of gestural recognition technology using Kinect

on 18 May 2011.

Use of gestural recognition technology using kinect in our products. This new use is based on the recognition of the movement when interacting with the various interfaces that the company is developing.

This development can be applied in different fields ranging from improving human-computer interaction, create therapeutic systems, etc..

Integration of OpenSource Proteomics Ontologies to our knowledge base

on 12 January 2011.

Integración de Ontologías proteómicas opensource a nuestra base de conocimiento

Completing with the corresponding genomic information is essential if we wanted proteomics complete our base of knowledge about the human brain.

Based on ontologies and databases, we describe the roles and relationships of the proteins expressed in the human brain, always providing scientific evidence that corroborates our data.

Correlation between biological and functional connectivity in fMRI and DTI

on 11 January 2011.

Estudio de la Correlación entre conectividad biológica y funcional en DTI y fMRI

We have indirectly established a connection between the population study of activation foci for each cognitive domain and subdomain covered, and population-based study based on diffusion tensor imaging (DTI ), with the aim of establishing a population model of connections between the different foci of activation in order to better understand the various networks of connections between different brain areas for each cognitive activity.

Thus, it is possible to infer the possible cause-effectrelationships in the activation of specific brain areas.

Resting state fMRI functional connectivity

on 23 December 2010.

Conectividad funcional en estudios de RMf en estado de reposo Based in the Connectome project, that include more than 1200 estudios de fMRIrs studies (Functional Magnetic Resonance Image in Resting State), an optimal methodology was selected for extracting information and it´s transformation into knowledge.

Analysis was performed "ROI-to-ROI" (ROI, region of interest) on fMRI at resting state, yielding a population model of coactivated brain structures, which includes the probability that two specific brain structures are simultaneously activated at rest.

These data have been incorporated into our database of functional activity on specific cognitive domains as BrainMap database and compared with each other to try to

determine the nature of these activities, their relationship to classical cognitive domains.

Tracts classification in DTI

on 19 November 2010.

Clasificación de tractos en DTI

We have developed a series of algorithms in order to perform grouping or classification of neural tracts from DTI studies (diffusion tensor imaging).

The importance of this grouping of tracts is that we can establish connectivity between different brain areas, and thus, once you define the meaning of this connection to infer the sequence of activations for each cognitive domain.That is, determine what "way" the information uses in the brain due to a cognitive task, or even figure out what cause-effect relationship between activations of different brain areas related to different cognitive tasks.

Moreover, this grouping provides a connective brain atlas, so as to identify "anomalous" tracts, and by population studies, to establish the correlation of these anomalous tracts with different pathologies.

Anatomical-Functional correlation in fMRI studies

on 02 October 2010.

Correlación anatómico-funcional en estudios de RMf

We performed a statistical meta-analysis of fMRI studies to infer the correlation between anatomical structure and cognitive function. By conducting this study, it was possible to filter the large volume of information contained in BrainMap, resulting in a final database that stores the following information: (1) The probability of activation of each brain structure for each cognitive domain , (2) The probability that each cognitive domain is related to the activation of each brain structure and, (3) The probability that two structures are activated simultaneously by each cognitive domain.

Longitudinal studies. Effects of treatment with drugs and/or rehabilitation

on 01 July 2010.

Estudios Longitudinales. Efectos de tratamientos farmacológicos y/o rehabilitación

We have developed a specific processing sequence for longitudinal studies, which quantify structural or functional changes in control subjects over a period of time.This type of study has become a standard for quantifying the structural changes as explained in the previous section.

Thus, by measuring various structural brain parameters of the same subject (with a given pathology) at various time points between the different treatments which are incorporated, we can evaluate their effectiveness objectively, besides providing data specific about what areas of the brain are modified.

With this evaluation, treatment (pharmacological or not) gets an objective validation of its operation compared to the corresponding pathology.

Decision making support for Mild Cognitive Impairment

on 01 April 2010.

Decision making support for Mild Cognitive Impairment

In some cases, it is difficult to diagnose dementia without evidence.

We need to develop tools to support decision making which, without replacing the criterion of the specialist, help in the diagnosis presenting evidence.In this regard we have developed a tool to aid decision making (based on objective data obtained from

a study focused on cases with CDR = 0.5), detecting structural changes consistent with mild cognitive impairment, and to classify subjects whose accuracy exceeds 90%.

However, this classification should be viewed with caution as it is possible to find significant structural damage in asymptomatic patients or with initial and

nonspecific symptoms.

Conducting a population study

on 08 January 2010.

Realización de un estudio poblacional

We performed a population based study in order to find a model of evolution/degeneration of the brain (both normal subjects and with pathologies), to assist the

specialist in the early diagnosis of neurodegenerative diseases.The population study includes more than 2900 processed brains grouped by age, sex, educational level, among other parameters.

Comparison of algorithms for image registration

on 09 December 2009.

Comparison of algorithms for imagen registration

Fundamental for population studies, to be able to compare the data obtained from a given subject with a certain population segment. We have developed a new implementation of the Thirion algorithm, which unlike other methods registers the entire volume (producing a lot more information and more accurate than using only the surface).

The results show that quality is at least comparable to other alternatives with a number of advantages: (1) does not need a preprocessing of the cerebral cortex to reduce the differences among subjects and others, (2) it is possible to register brain volumes of two different subjects, and (3), execution time is less than 5 minutes, 10 times faster than FreeSurfer and 30 times more than SPM.

Creation of a Brain Anatomy Ontology

on 04 December 2009.

Creación de una Ontología Anatómica del Cerebro

Based on anatomical Ontologies, anatomical atlas and research articles, there has been a complete review of the anatomy of the human brain, establishing the relationships between the different elements that compose it.The manual review of the hierarchy of structures, relationships established between them, and synonyms, avoids the potential ambiguities.

Development of a new segmentation algorithm for MRI

on 10 November 2009.

Development of a new segmentation algorithm for MRI

After analyzing various segmentation methods considered as standards in neuroimaging, we developed a new fully automated algorithm without the participation of the user for parameter setting.Based on the mathematical theory of the evolution of level sets and classical works on segmentation, get an extension of previous work in threedimensional volumes, without increasing the running time: processing a volume of 256x256x128 voxels in less than 10 seconds, whereas fastest existing segmentation methods take a minimum of 5 or 6 minutes.