• Assessing the coupling between local neural activity and global connectivity fluctuations: application to human intracranial electroencephalography during a cognitive task

  Deco, Gustavo (Wiley, 2023)
• Toward naturalistic neuroscience: Mechanisms underlying the flattening of brain hierarchy in movie-watching compared to rest and task

  Deco, Gustavo (American Association for the Advancement of Science (AAAS), 2023)
• Lung function in young adults born small for gestational age at term

  Bernardino, Gabriel (Wiley, 2023)
• Distributed harmonic patterns of structure-function dependence orchestrate human consciousness

  Luppi, Andrea I.; Vohryzek, Jakub; Kringelbach, Morten L.; Martinez Mediano, Pedro Antonio; Adapa, Ram; Carhart-Harris, Robin L.; Roseman, Leor; Pappas, Ioannis; Peattie, Alexander R. D.; Manktelow, Anne E.; Sahakian, Barbara J.; Finoia, Paola; Williams, Guy B.; Allanson, Judith; Pickard, John D.; Menon, David K.; Atasoy, Selen; Stamatakis, Emmanuel A. (Nature Research, 2023)

  A central question in neuroscience is how consciousness arises from the dynamic interplay of brain structure and function. Here we decompose functional MRI signals from pathological and pharmacologically-induced perturbations ...
• Towards assisted electrocardiogram interpretation using an AI-enabled Augmented Reality headset

  Lampreave, Paula; Jimenez-Perez, Guillermo; Sanz-Pérez, Isidro; Gomez, Alberto; Camara, Oscar (Taylor & Francis, 2021)

  The interpretation of electrocardiograms (ECGs) is key for the diagnosis and monitoring of cardiovascular health. Despite the progressive digital transformation in healthcare, it is still common for clinicians to analyse ...
• Network-based modelling of mechano-inflammatory chondrocyte regulation in early osteoarthritis

  Segarra-Queralt, Maria; Piella Fenoy, Gemma; Noailly, Jérôme (Frontiers, 2023)

  Osteoarthritis (OA) is a debilitating joint disease characterized by articular cartilage degradation, inflammation and pain. An extensive range of in vivo and in vitro studies evidences that mechanical loads induce changes ...
• A deep-learning based framework for source separation, analysis, and synthesis of choral ensembles

  Chandna, Pritish; Cuesta, Helena; Petermann, Darius; Gómez Gutiérrez, Emilia, 1975- (Frontiers, 2022)

  Choral singing in the soprano, alto, tenor and bass (SATB) format is a widely practiced and studied art form with significant cultural importance. Despite the popularity of the choral setting, it has received little attention ...
• Iconicity in sign language production: task matters

  Gimeno-Martínez, Marc; Baus, Cristina (Elsevier, 2022)

  The present study explored the influence of iconicity on sign lexical retrieval and whether it is modulated by the task at hand. Lexical frequency was also manipulated to have an index of lexical processing during sign ...
• Interactive VPL-based global illumination on the GPU using fuzzy clustering

  Colom, Arnau; Marques, Ricardo; Santos, Luís Paulo (Elsevier, 2022)

  Physically-based synthesis of high quality imagery, including global illumination light transport phenomena, results in a significant workload, which makes interactive rendering a very challenging task. We propose a VPL-based ...
• Smoothing policies and safe policy gradients

  Papini, Matteo; Pirotta, Matteo; Restelli, Marcello (Springer, 2022)

  Policy gradient (PG) algorithms are among the best candidates for the much-anticipated applications of reinforcement learning to real-world control tasks, such as robotics. However, the trial-and-error nature of these ...
• Multilabel prototype generation for data reduction in k-nearest neighbour classification

  Valero-Mas, Jose J.; Gallego, Antonio Javier; Alonso-Jiménez, Pablo; Serra, Xavier (Elsevier, 2023)

  Prototype Generation (PG) methods are typically considered for improving the efficiency of the k-Nearest Neighbour (kNN) classifier when tackling high-size corpora. Such approaches aim at generating a reduced version of ...
• Infants’ representation of asymmetric social influence

  Bas, Jesús, 1990-; Sebastián Gallés, Núria; Csibra, Gergely; Mascaro, Olivier (Elsevier, 2023)

  In social groups, some individuals have more influence than others, for example, because they are learned from or because they coordinate collective actions. Identifying these influential individuals is crucial to learn ...
• Dynamic sensitivity analysis: defining personalised strategies to drive brain state transitions via whole brain modelling

  Vohryzek, Jakub; Cabral, Joana; Castaldo, Francesca; Sanz-Perl, Yonatan; Lord, Louis-David; Fernandes, Henrique M.; Litvak, Vladimir; Kringelbach, Morten L.; Deco, Gustavo (Elsevier, 2023)

  Traditionally, in neuroimaging, model-free analyses are used to find significant differences between brain states via signal detection theory. Depending on the a priori assumptions about the underlying data, different ...
• Attri-VAE: attribute-based interpretable representations of medical images with variational autoencoders

  Cetin, Irem; Stephens, Maialen; Camara, Oscar; González Ballester, Miguel Ángel, 1973- (Elsevier, 2023)

  Deep learning (DL) methods where interpretability is intrinsically considered as part of the model are required to better understand the relationship of clinical and imaging-based attributes with DL outcomes, thus facilitating ...
• FFNSL: Feed-Forward Neural-Symbolic Learner

  Cunnington, Daniel; Law, Mark; Lobo, Jorge; Russo, Alessandra (Springer, 2023)

  Logic-based machine learning aims to learn general, interpretable knowledge in a data-efficient manner. However, labelled data must be specified in a structured logical form. To address this limitation, we propose a ...
• The human posterior cingulate, retrosplenial, and medial parietal cortex effective connectome, and implications for memory and navigation

  Rolls, Edmund T.; Wirth, Sylvia; Deco, Gustavo; Huang, Chu-Chung; Feng, Jianfeng (Wiley, 2023)

  The human posterior cingulate, retrosplenial, and medial parietal cortex are involved in memory and navigation. The functional anatomy underlying these cognitive functions was investigated by measuring the effective ...
• Benchmark of deep learning algorithms for the automatic screening in electrocardiograms transmitted by implantable cardiac devices

  Gassa, Narimane; Sacristan, Benjamin; Zemzemi, Nejib; Laborde, Maxime; Garrido Oliver, Juan; Matencio Perabla, Clara; Jimenez-Perez, Guillermo; Camara, Oscar; Ploux, Sylvain; Strik, Marc; Bordachar, Pierre; Dubois, Remi (Institute of Electrical and Electronics Engineers (IEEE), 2021)

  The objective of this work was to benchmark different deep learning architectures for noise detection against cardiac arrhythmia episodes recorded by pacemakers and implantable cardioverter-defibrillators (PM/ICDs) and ...
• Melon playlist dataset: a public dataset for audio-based playlist generation and music tagging

  Ferraro, Andrés; Kim, Yuntae; Lee, Soohyeon; Kim, Biho; Jo, Namjun; Lim, Semi; Lim, Suyon; Jang, Jungtaek; Kim, Sehwan; Serra, Xavier; Bogdanov, Dmitry (Institute of Electrical and Electronics Engineers (IEEE), 2021)

  One of the main limitations in the field of audio signal processing is the lack of large public datasets with audio representations and high-quality annotations due to restrictions of copyrighted commercial music. We present ...
• Self-supervised learning from automatically separated sound scenes

  Fonseca, Eduardo; Jansen, Aren; Ellis, Daniel P. W.; Wisdom, Scott; Tagliasacchi, Marco; Hershey, John R.; Plakal, Manoj; Hershey, Shawn; Moore, R. Channing; Serra, Xavier (Institute of Electrical and Electronics Engineers (IEEE), 2021)

  Real-world sound scenes consist of time-varying collections of sound sources, each generating characteristic sound events that are mixed together in audio recordings. The association of these constituent sound events with ...
• Lightweight UAV-based measurement system for air-to-ground channels at 28 GHz

  Semkin, Vasilii; Kang, Seongjoon; Haarla, Jaakko; Xia, William; Huhtinen, Ismo; Geraci, Giovanni; Lozano Solsona, Angel; Loianno, Giuseppe; Mezzavilla, Marco; Rangan, Sundeep (Institute of Electrical and Electronics Engineers (IEEE), 2021)

  Wireless communication at millimeter wave frequencies is an attractive option for high-bit-rate connectivity to unmanned aerial vehicles (UAVs). However, conducting the channel measurements necessary to assess the communication ...

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