Every year, 1 out of 3 people experiences a neuropsychiatric disorder. When these become chronic, they represent the most frequent and debilitating illness type, more than heart disease or cancer. There is a need for their timely and accurate diagnosis such that treatment can start earlier, disease progression can be delayed, patient quality­of­life improved, and disease management more cost­ effective.Descrição:


Period: January 2019 - September 2021
Team: Diana Prata, Hugo Ferreira
Partners:

EPE (CHLN)
Hospital Professor Doutor Fernando Fonseca, EPE (HFF, EPE)
Serviços Partilhados do Ministério da Saúde, E.P.E. (SPMS)
NEUROPSYAI – SERVIÇOS E INVESTIGAÇÃO EM NEUROCIÊNCIAS, Lda (NeuroPsyAI)
Hospital da Senhora da Oliveira, Guimarães EPE (HSOG)

Amount: 299 925€

Mental illness is by far the largest contributor to chronic illness in Europe, entailing half of all social welfare expenditure (WHO, 2008). However, neuropsychiatry lags behind other fields of medicine, both in the understanding of disease mechanisms and in the prediction of treatment response. This severely limits symptom recovery and people?s quality of life. With the present proposal, focused on the neuropeptide oxytocin (OT) and its promising pharmacological use, we aim to improve both the pathophysiological and the therapeutic models of SCZ, with a focus on (the much neglected) social cognitive symptomatology. We also promote an alternative to the black-box, and one-size-fits-all clinical tradition. We will answer 2 questions:
1) What is the impact of intranasal oxytocin (OT) on the SCZ patient?s social cognition neurocorrelates - and how is this influenced by dopamine(DA)-ergic pharmacotherapies and relevant genetic variability?
2) Can we predict in advance how much will a SCZ patient?s striatal function respond to intranasal OT, by applying artificial intelligence (AI) to genetic, DAergic medication and neuroimaging data collected previous to administration? This interdisciplinary project, unique in Portugal, is a double-blind and randomised-controlled pharmacological manipulation of OT (with naturalistic DAergic medication), and a pharmacogenetic assessment of DA and OT genetic influence, on brain function during a social game (the Prisoner?s Dilemma) which elicits social reward and trust processing. Apart from a hypothesis-driven approach to characterize the OT and DA pathway overlap, we also employ a hypothesis-free AI approach towards a predictive biomarker for OT ? of translational, cost-efficient potential.
This endeavour stems from: 1) the PI?s current pioneering work at iMM where she, as an award-winning Marie Curie Fellow, started characterizing the OT and DA interplay on social cognition in healthy subjects; 2) her previous work on the etiology, DA antagonists treatment response and onset prediction biomarkers of SCZ combining genetics and neuroimaging, at the Institute of Psychiatry (King?s College London, KCL), and 3) the co-PI?s development of novel neuroimaging tools and AI models to serve as biomarkers, and 4) the recent creation of NeuroPsyCAD, founded a result of their highly complementary lines of work.
Team-wise, this project offers a triangulation between: 1) a peer-to-peer academic collaboration between an applied and a technical academic biomedical institution of (iMM and IBEB, respectively) 1) a novel academic-clinical collaboration with Psychiatric wards in 3 Lisbon hospitals, and 3) an academic-industrial joint-venture with a newly founded company NeurPsyCAD; notwithstanding international collaborations with KCL and Emory University (US) ? in sum, an extremely valuable opportunity for students and researchers in Portugal to train in, and advance cutting interdisciplinary neuroscience and psychiatry.
Descrição:


Period: July 2018 - June 2020
Team: Diana Prata, Hugo Ferreira
Amount: 239 788,40€

(PT) EMERALD is the coherent action of leading European engineering groups involved in electromagnetic (EM) technology for medical imaging to form a cohort of highly skilled researchers capable of accelerating the translation of this technology “from research bench to patient bedside”.Descrição:


Period: May 2018 - April 2022
Team: Raquel Cruz Conceição
Partners:

Czech Technical University in Prague, Czech Republic; University of Belgrade, Serbia; Neurent Medical, Ireland; Institute of Telecommunications – Lisboa, Portugal; MEDIWISE, United Kingdom; University of Rome Sapienza, Italy; Italian National Agency for New Technologies, Energies and Sustainable Economic Development, Italy; Istanbul Technical University, Turkey; Johannes Kepler University Linz, Austria; European Association on Antennas and Propagation (European); University Hospital Bern, Switzerland; Hadassah Hebrew University Medical Center, Israel; University of Trento, Italy; Lariboisière University Hospital, Paris 7 University, France; Luz Saúde, S.A., Sociedade Aberta, Hospital da Luz, Portugal; Faculdade de Ciências da Universidade de Lisboa, Portugal; Sorbonne Université, France.

Amount: 238 356,36€

Over a third of the European population suffers from brain diseases, with estimated yearly costs of about 800
billion euros, 35% of Europe?s total disease burden (DiLuca & Olesen, 2014). Synaptic networks are a key
diagnostic and/or therapeutic target in the vast majority of neurobehavioural disorders across the lifespan. The
pathophysiological involvement of various neurotransmitter systems is increasingly recognized, with a central role
for dopamine, glutamate, GABA and serotonin. Evidence from multiple disciplines supports a pivotal role for these
synaptic neurotransmitters both in the disease mechanisms and at least as targets for pharmacological therapy.
However, the knowledge thus far available is still not translated into useful disease biomarkers and personalized
drug therapies. Focusing at the same processes across diseases where the same synaptic networks are affected
in distinct manners, within the scope of a consortium, as is the goal of this call, will provide new perspectives and
cross-fertilizing approaches.
A promising approach for 'biomarker' discovery has been based on pattern recognition methods applied to
neuroimaging data, which are already showing potential for clinical application. Neuroimaging/neurophysiology
provide rich multivariate functional and structural information, and helped demonstrating a common brain network
linking brain development, brain ageing, and vulnerability to disease. They are also important tools to associate
individual differences in the human genome, proteome and metabolome to structure and functional variation in brain
diseases. The link between genetic variation and behaviour is indirect and very complex. Because one needs to
consider molecular to network to functional effects, genomic studies require huge sample sizes for determination
of true associations. Focusing on the synapse and neurotransmission and combining neuroimaging methods with
genetic data and intermediate level molecular function information, provided by RNA, protein and metabolite analysis,
Formulário Portugal 2020 Página 19 de 111
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is a more effective and powerful approach to overcome the need of very large sample sizes to link individual disease
susceptibility with structural and functional outcomes. We propose to use neuroimaging, genetic and biochemical
analysis tools and combine hypothesis-driven, data mining and modelling approaches to further understand the
biological disease mechanisms and to identify diagnostic and therapeutic biomarkers of clinical utility.
The consortium is well suited to integrate multimodal approaches across a biological systems level. Multimodal
approaches - genetics, proteomics/metabolomics, neuroimaging, and clinical predictors ? will help explore potential
predictor and mediator/moderator biomarkers for treatment response profiles in autism, schizophrenia and
neurodegenerative disorders. This strategy will improve pathophysiological understanding, and help personalize
treatment selection.Descrição:


Period: March 2017 - September 2020
Team: Pedro Almeida, Alexandre Andrade, Hugo Alexandre Ferreira
Partners:

Amount: 191 308 €

The creation of the Schengen area has been one of the major achievements of the EU. However, this agreement requires countries to cooperate tightly in order to keep a high level of security at their internal borders, as well as to share the responsibility of managing external borders. Such a variety of borders (land, sea and air) and current challenges requires a consistent approach to border surveillance, based on a plethora of heterogeneous assets. These can be manned or unmanned, ranging from sensors (optical, radar, IR) to unmanned platforms (UAV, UGV, USV or UUV), and need to be combined to offer an integrated situational picture of the area under surveillance and of their location. In order to effectively control their operation and manage the large amounts of data collected by them, new approaches for command and control need to be considered, allowing efficient interaction between the operator and the different assets in the field. CAMELOT proposes to develop and demonstrate different advanced command and control service modules for multiple platform domains, based on a SOA architecture that specifies internal and external interfaces, allowing the development of a modular and scalable command and control station, customisable to the user needs. This architecture can be based on results of previous studies and work or open architectures that may prove more suitable and the interfaces can take advantage of the standardisation work that has been done already. After the definition, CAMELOT partners will prototype service modules according to their expertise, background individual technologies and practitioner needs. These will be integrated progressively in specific testing along the project. This prototype development approach will culminate in 2 final demonstrations involving end users and relevant stakeholders, to achieve a maturity of TRL6 (for most individual technologies supporting the functionalities for border surveillance) and an IRL of 7 for CAMELOT.Descrição:


Period: May 2017 - April 2020
Team: Hugo Alexandre Ferreira

Positron Emission Tomography is among the best examples of the contribution of medical imaging systems to clinical research. The development of PET systems adequate for small animal imaging has been an active area of research in the last two decades, with important applications in drug development and imaging of gene expression. This allowed a better understanding of human diseases and the development of more effective ways for disease diagnosis and treatment, through the translation of pre-clinical molecular imaging discoveries in small animals, to medical practice. In the case of research-dedicated PET scanners for small animal imaging, size adequacy is essential. In fact, for instance, a rat’s heart is more than 100 times smaller than the human heart.
This work aims at developing a small PET scanner with improved spatial resolution using depth-of-interaction (DOI) information. The system combines scintillator-photodetector cells with a new DOI determination method, based on light guides (optical fibres) with silicon photomultiplier readout (SiPM).
The method requires a small number of components to obtain DOI; therefore, it allows producing a high-performance PET system at acceptable cost, presenting state-of-the-art characteristics.
The foreseen system comprises one ring of 128 1.5 x 1.5 x 20 mm3 LYSO crystals radially distributed. Each single LYSO crystal is read out on both ends by silicon photomultipliers (SiPMs), but using wavelength-shifting (WLS) fibers/bars and a reduced number of SiPMs on one end. The DRIM-PET can be modulated for axial capability by using several rings modules placed side-by-side.
Two different signal readout systems will be considered. A simpler one that uses only a few readout channels for readout of the entire 128 detector cells, being the position determination obtained by a resistive chain method. The more complex one, with improved capabilities in terms of reduction of false coincidences, sensitivity and position resolution, will use individual channels for each cell.
Experimental and simulation studies will be performed in order to optimize the system’s parameters the aim of building and characterizing a prototype for its interest as new PET scanner for pre-clinical research.
Dedicated image reconstruction methods and imaging software will be developed taking into account the characteristics of the system and in order to optimize the image quality as a function of produced signals.
Prototype characterization, using beta+ emitters, will be done, first with 22-Na calibration sources and after with phantoms filled with 18-F. Finally, in order to demonstrate the potential of the developed PET scanner, small animals with different pathologies of interest (e.g. oncologic) and radio-tracers will be used as final evaluation task.
Principal Investigator: João Veloso (UA)Descrição:


Period: June 2016 - May 2019
Team: Pedro Almeida; Nuno Matela
Partners:

Instituto de Nanoestruturas, Nanomodelação e Nanofabricação (Aveiro) (I3N) (http://www.i3n.org/)

CNC.IBILI (Coimbra) (http://www.uc.pt/en/fmuc/ibili)

IBEB – Instituto de Biofísica e Engenharia Biomédica (www.ibeb.fc.ul.pt)

Amount: 199.954,00€

Distress screening in cancer patients is internationally recommend as good practice in quality cancer care, since high levels of cancer-related distress may negatively impact on their clinical outcomes, such as survival and quality of life.
Distress involves a range of feelings from vulnerability and sadness to depression, anxiety, adjustment disorders, panic and isolation. As have been shown in studies done by a researcher of our team, Michael Antoni negative affect in breast cancer patients has been associated with flattened diurnal cortisol rhythmicity and dysfunction of immune functioning, namely greater leukocyte inflammatory gene (IL-1, IL-6, TNF) expression which are related to hypothalamic pituitary adrenal axis dysregulation (HPA). HPA dysregulation is relevant in mBC patients since alterations in circulating cortisol interacts with immune cells to upregulate inflammatory signaling, which could promote disease progression. Distress in cancer patients may also
be correlated with objective measures of changes (increase or decrease) in brain glucose metabolism, in regions within the limbic cortical circuit of the brain.
Distress can be measured through simple self-report instruments completed by the patient, which assess patients’ subjective experience. However in many centers and countries this is not yet standard clinical practice and as a consequence most of the psychological suffering in cancer patients goes unrecognized by the clinical staff and untreated. The identification of distress in cancer patients is an important target in clinical care for optimizing patients’ well-being and their outcomes. As such it would be important to have alternative ways in the existing routine clinical practice to detect it and, more important, to have a measure/indicator of patient propensity for distress in response to illness challenges. This study may give a contribution in this
regard.
Studies using positron emission tomography (PET) with non-cancer subjects have demonstrated correlations between depression assessed by self-report measures and alterations in regional cerebral glucose metabolism (rCGM), as well as regional cerebral perfusion/blood flow in some specific brain regions. However, no studies correlating distress (which does not necessarily involve depression) with rCGM in cancer patients have been reported. However, FDG-PET exams are used in clinical practice to assess disease progression and response to treatment in metastatic breast cancer patients (mBC). With this research project we aim to fill in this gap since our primary objective is to examine associations among individual differences in reported depression, anxiety, cortisol levels and rCGM measures (FDG-PET) of baseline activity in specific regions within the limbic-cortical circuit of the brain such as in the amygdala, pulvinar nucleus, dorsolateral prefrontal cortex and subgenual anterior cingulate cortex in mBC patients. We expect to find that increasing levels of distress will be related with increasing or decreasing rCGM measures (FDG-PET) in these same specific regions of the brain. This may allow us to identify one or more specific regions within the limbic-cortical circuit of the brain, which are sensitive to levels of heightened distress and HPA axis alterations and as such could serve as an objective indicator of patient’s affective style. Individual differences in tonic alterations of activity level in specific brain regions could predict differences in propensity for distress in response to illness challenges and therefore will have impact on clinical management of cancer patients facilitating proper and early referral for an adequate psychosocial preventive intervention.
Using this ‘smooth’ way of screening for distress included in a routine clinical exam would benefit patients and professionals and be cost-effective, as it would avoid using additional resources and patients’ time. Having selective ways to target patients’ propensity for distress in the cancer setting is an important objective. The positive impact to have such a measure is significant because it will allow: (1) early screening of patients at higher risk for psychological morbidity (mainly depression); (2) early referral for psychosocial care to prevent and/or reduce distress and psychological morbidity (3) optimize patients’ selection for psychosocial care to those who may benefit more and therefore optimize and reduce healthcare costs; (4) optimize clinical outcomes (by reducing the potential adverse effects in immune function produced by psychological distress and/or morbidity in cancer patients); (5) open the door to future work that can test whether people who receive anti-depressants or Cognitive Behavioral Therapy-based interventions will show objective changes in brain activity and (5) promote cancer care for the whole patient.Descrição:


Period: Jan 2016 - Dec 2018
Team: Pedro Almeida
Amount: 158.710,00 €

The general aim of this project is to investigate the electric field produced in the brain during the application of tumor treating fields for the treatment of Glioblastoma multiforme. The specific aims are
1) To develop analytical and finite element (FE) mesh models describing the distribution of intermediate frequency electric fields within the brain.
2) To develop analytical and finite element models of the electric fields produced within cells in response to an applied AC electric field.
3) To use DTI data to incorporate anisotropy in the electrical conductivity (i.e., the electrical conductivity tensor) in white matter in the FE modeling framework.Descrição:


Period: July 2013
Team: Pedro Cavaleiro Miranda
Partners:

Novocure

Amount: 100 000€

This proposal outlines a R&D programme aiming the study of new methodologies for concentrate light inside turbid biological media, one of the last frontiers in laser biomedical applications. The target: phototherapy by thermal activation and destruction of cancer cells.
The backbone of the proposed research is the development of a phase shaping method based on an iterative algorithm to create wavefronts inverting the diffusion of light. This algorithm will be developed, being the interrogation and phase partitioning strategies critical points to be considered when analysing its performance. Two main types of laser beams will be considered in the study (Gaussian and quasi-Bessel beams) and the potential of low coherence beams to improve the method will be analysed. The core scientific objectives to be pursued are:
- To produce and characterize multifunctional nanoparticles which phototherapeutic potential can be improved by their in-depth activation.
- To develop a new methodology based in phase shaping to concentrate light inside turbid biological media.
- To develop a simulator capable of predict the focusing capability of the methodology for a determined set of parameters.
- To demonstrate the technique by its experimental application under well controlled conditions.
- To demonstrate the technique in vitro and in vivo.
- To evaluate the potential, limitations and future developments of the technique.
Although light has long being used in biomedicine, scattering always limited its application. Superficial (tenths of micron for human epidermis) phototherapy is already a well established application, requiring intrusive methods to deliver light when the target is deeper inside the body. The latter solution removes the major advantage in using light: its non-intrusive potential. This motivates researchers to develop methods to concentrate light inside biological highly scattering media. However, only a few years ago phase shaping approaches have started to be developed for focusing light through turbid media, although not exactly directed to biological media. The idea: to use a phase modulator to produce wavefronts inverting the diffusion of light based on a close-loop approach. In biophysics, the research in this area as been mainly focused in increasing the depth light can propagate, with direct application in imaging techniques like microscopy and tomography. In these fields, scattered light is collected and its analysis allows imaging. In order to increase the observable path, several strategies have been envisaged. A recent one has been developed for optical coherence tomography by using quasi-Bessel beams. These beams have shown the capability of self-reconstruct along the turbid path thus allowing collect scattering at longer paths.
In this work we propose to further develop the phase-shaping principle with a dedicated approach to biomedical applications, in general, and photoactivation in particular. The preconditioning of the incident beam to a quasi-Bessel beam will increase the propagation of the beam, although scattered. Then, the developed phase shaping technique will act, concentrating the light where necessary. The use of these beams is expected to remove computational load of the iterative process and allow a better and faster convergence to a solution. The technique will be developed considering the parameters regarding a set of photosensitize substances identified as potentially relevant for the study.
A simulator will allow overcoming a limitation of the technique: its requirement of feedback information on the intensity distribution in the plane where light concentration is required. By using an optical design and scientific programming software, and by proper experimental validation, it will allow predicting the method’s performance in an open loop process (as in real applications).
A numerical model will be developed to predict the effects of a concentrated light beam on the considered substances and surrounding media.
The institutions proposing this candidature have a combined set of experiences that potentiate the development of this research. From FCUL, IBEB, CFA and LOLS joint forces will use they expertise in biomedical and light-matter interaction. FCTUNL has expertise in the application of optical techniques in the biomedical field, in particular but not exclusively in the area of ophthalmology, aiming the development of new techniques and methodologies for medical application. INL (BioPhotonics Group) will contribute with its expertise in the fields of phototherapy of cancer cells; photochemistry and biophotonics; synthesis, characterization and biofunctionalization of nanoparticles and bioimaging. COFAC, with its BioSciences Center (CBIOS), and INL will contribute with their expertise in the fields of multifunctional nanoparticles development and drug delivery for tumor therapy. In vivo tests will be performed at the Faculty of Pharmacy of the Univ. of Coimbra
Principal Investigator: João Miguel Pinto Coelho (IBEB and LOLS)Descrição:


Period: January 2013 - December 2014
Team: João Miguel Pinto Coelho; Hugo Ferreira
Partners:

IBEB – Instituto de Biofísica e Engenharia Biomédica
Centro de Física Atómica (FC/UL)
Laboratório de Óptica, Lasers e Sistemas, Departamento de Física da Faculdade de Ciências da Universidade de Lisboa (FCUL-DF-LOLS)
Laboratório Ibérico Internacional de Nanotecnologias (INL)
COFAC, Cooperativa de Formação e Animação Cultural, CRL (COFAC)
Fundação da Faculdade de Ciências e Tecnologia (FFCT/FCT/UNL)

Amount: 149 815€

Tomosynthesis is an emerging radiological technique used for breast imaging. It produces a 3D image from a series of views, reducing the problem of overlapping structures in 2D mammography imaging. The clinical benefit of this technique for the diagnosis of breast cancer is still under evaluation. Recent studies show that Digital Breast Tomosynthesis (DBT) presents superior image quality and better cancer visibility, indicating a better sensitivity than digital mammography (DM). Some argue that DBT has not yet proven to result in better clinical performance than using DM, but others suggest that combining both techniques could lead to better overall performance. However, some authors go one step further and consider that DBT can be an alternative to DM in breast cancer screening, particularly for women with dense breasts. Despite these promising results, it is acknowledged that neither the acquisition nor the image reconstruction algorithms of DBT are fully optimized.

The majority of published clinical studies refers the use of analytical algorithms for image reconstruction. However, it is accepted that iterative methods can improve image quality relatively to analytical image reconstruction.

Iterative methods include statistical iterative reconstructions algorithms that incorporate a geometrical model for the transmission/detection process and take into account data statistics and a noise model. The inclusion of this statistical information enables better quantitation than Filtered Backprojection (FBP) in regions of low intensity / low count rates, as demonstrated for emission tomography.

In the proposed work, this characteristic is crucial since the number of photon counts in DBT projections is reduced as a consequence of low dose requirement. Therefore, we anticipate that statistical algorithms can not only lead to better DBT images, but can also play an important role on dose reduction if similar image quality can be obtained at a lower dose, increasing the clinical value of this technique.

Hospital da Luz has installed the first DBT scanner in Portugal and, being a research partner of this project, grants us access to the equipment. This is crucial not only for simulation validation and dosimetry purposes, but also for the development of image reconstruction algorithms, since the access to phantom and real data is mandatory along the way. In addition, radiologists from Hospital da Luz will contribute to the evaluation and optimisation of the new or redesigned algorithms.

In order to evaluate the potential reduction of patient doses, we will develop a Monte Carlo simulation platform, similar to the one that has already been validated for conventional digital mammography. This simulation tool will allow us to test different exposure configurations, for both dose and image quality purposes, without the need to irradiate patients. This simulation platform will be validated with dose measurements made with conventional dosimeters and with a new dosimeter that is currently being developed by LIP, one of the research partners.

Regarding image reconstruction, an important issue that hinders the use iterative image reconstruction algorithms is their computation time, which can amount up to several hours in a standard computer. To overcome this problem, we intend to take advantage of the modern graphic processor units (GPU) that are known to speed up image reconstruction by more than an order of magnitude. Some work has already been done within the IBEB group.

In recent years, this team has published several papers in image reconstruction and processing, Monte Carlo simulation and dosimetry. The two radiologists from Hospital da Luz have a long experience in mammography and are using DBT in clinical routine for more than two years. This background encourages us to address the problem from an integrated perspective. We do believe that there is work to be done in the improvement of image reconstruction algorithms for DBT and that this can have a significant repercussion on dose received by the patients. We also believe that simulation can provide additional information to radiologists and radiographers, so they can optimise on everyday routine each particular exam in respect to dose deliver to patients.

This project congregates academic and clinical expertise. The expected results are due to be fully available to the clinical partner, for the benefit of its patients. The global impact that DBT is expected to achieve in breast cancer diagnosis increases the potential value of the tools developed in this project. In the case of commercial valorisation of these tools, the institutions have already signed an agreement that includes the terms of the sharing of the intellectual property.

Principal Investigator: Pedro Almeida (IBEB)Descrição:


Period: June 2013 – December 2015
Team: Pedro Almeida; Nuno Matela; Ana Margarida Mota; Nuno Oliveira; Pedro Ferreira; Luís Janeiro
Partners:

IBEB – Instituto de Biofísica e Engenharia Biomédica (www.ibeb.fc.ul.pt)
Hospital da Luz, SA (http://www.hospitaldaluz.pt/)
LIP – Laboratório de Instrumentação e Física Experimental de Partículas (www.lip.pt)
C2TN – Centro de Ciências e Tecnologias Nucleares (http://c2tn.tecnico.ulisboa.pt/)

Amount: 150 532,00€

The nervous system is constantly changing over the lifespan as a result of development and learning. Such plasticity-related changes occur at multiple levels of neural organization, from molecules and synapses to cortical maps and large-scale networks. Neuroimaging research over the past two decades has already contributed an extensive amount of information on how many sensory and cognitive functions are associated with particular brain structures. Increasing interest in the characterization of plasticity mechanisms in the human brain has posited new challenges to neuroimaging techniques, both of conceptual and methodological nature. In particular, it is thought that great insights will be possible through the conjoint analysis of activity within specific brain regions and functional connectivity between those regions.
In this Project, we propose to address this issue through the development and implementation of the following neuroimaging methodological approaches. Firstly, state-of-the-art acquisition methods for functional magnetic resonance imaging (fMRI) will be implemented in a 1.5 Tesla system in order to allow more quantitative and reliable assessment of learning-related brain activity changes. Secondly, different techniques for the analysis of brain connectivity will be developed and integrated, based on the combination of fMRI with electroencephalography (EEG) measurements for the assessment of both low and high frequency behavior.
Although conventional fMRI techniques using blood oxygenation level dependent (BOLD) contrast have already proved useful in the study of plasticity-related brain activity changes, they present severe constraints when the learning process of interest occurs over minutes or even hours, or when longitudinal designs are chosen to investigate effects over longer periods of time. Arterial spin labelling (ASL) perfusion imaging methods provide a more stable and quantitative measure of brain activity that constitutes an interesting complement to BOLD contrast. Moreover, a recently developed diffusion-weighted imaging (DWI) technique seems to provide an independent, quantitative measure of activation, therefore offering additional information. Protocols for the combined acquisition of BOLD, ASL and DWI fMRI will be implemented and validated using robust visual stimulation paradigms.
Synchronization of neural responses is thought to be modified as a function of learning and represents a possible plasticity mechanism. Functional connectivity investigations of fMRI data provide a way of assessing synchronization between brain regions. Protocols for both model- and data-driven analysis methods of connectivity will be implemented, in order to combine the complementary strengths of each strategy. Correlation-type exploratory approaches will be used to determine networks of functionally connected brain areas and specific causal models will then be tested, based on these networks and available neurophysiological information. Neural synchronization can also be assessed through coherence measures of EEG recordings. The high temporal resolution of this technique allows the investigation of functional connectivity at various frequency oscillation bands, which have previously been hypothesized to have differential cognitive significance. Time-series analysis methods will be implemented and validated for the measurement of phase coherence between EEG channels. Time-frequency decomposition techniques will be employed in order to explicitly access specific frequency bands of interest. Additionally, protocols for the simultaneous EEG and fMRI acquisition will be implemented and appropriate analysis methods developed for the integration of the multimodal data. By combining EEG with fMRI, we hope to enable the investigation of functional connectivity changes during learning over a broad range of frequencies.
Finally, the contextual cueing paradigm used for the study of implicit learning mechanisms will be investigated with the methods developed within this Project. Combined BOLD-ASL fMRI will first be used to determine brain activity changes related to the learning processes under study, testing hypotheses concerning the involvement of specific brain structures, namely the hippocampus and caudate nucleus. Functional connectivity analysis will also be conducted, in order to investigate the interactions between the participating brain regions. Finally, simultaneous EEG-fMRI measures will be used to investigate learning induced neuronal synchronization at different frequency bands.
In summary, with this Project we hope to contribute to the development and validation of valuable acquisition and analysis tools for the investigation of brain mechanisms of learning using neuroimaging techniques. Moreover, we expect that this Project will enable the cooperation between young scientists with expertise in the fields of Biomedical Engineering and Neuroscience, in the context of the National Network for Functional Brain Imaging recently approved by FCT.
Principal Investigator: Patrícia Figueiredo (IST)Descrição:


Period: January 2008 - December 2010
Team: Alexandre Andrade
Partners:

Instituto Superior Técnico (IST/UTL)

Siemens SA (Siemens)

Instituto Biomédico de Investigação de Luz e Imagem (IBILI/FM/UC)

IBEB – Instituto de Biofísica e Engenharia Biomédica

Amount: 172 158€