Wortha SM, Bloechle J, Ninaus M, Kiili K, Lindstedt A, Bahnmueller J et al. Neurofunctional plasticity in fraction learning: An fMRI training study. Trends in Neuroscience and Education. 2020 joulu 1;21. 100141. https://doi.org/10.1016/j.tine.2020.100141

Lolicato F, Juhola H, Zak A, Postila PA, Saukko A, Rissanen S et al. Membrane-Dependent Binding and Entry Mechanism of Dopamine into Its Receptor. ACS Chemical Neuroscience. 2020;11(13):1914–1924. https://doi.org/10.1021/acschemneuro.9b00656

Rimpiläinen V, Koulouri A, Lucka F, Kaipio JP, Wolters CH. Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity. NeuroImage. 2019 maalis 1;188:252-260. https://doi.org/10.1016/j.neuroimage.2018.11.058

Miinalainen T, Rezaei A, Us D, Nüßing A, Engwer C, Wolters CH et al. A realistic, accurate and fast source modeling approach for the EEG forward problem. NeuroImage. 2019;184(1):56-67. https://doi.org/10.1016/j.neuroimage.2018.08.054

Angleraud A, Houbre Q, Pieters R. Teaching semantics and skills for human-robot collaboration. Paladyn. 2019;10(1):318-329. https://doi.org/10.1515/pjbr-2019-0025

Gavas RD, Tripathy SR, Chatterjee D, Sinha A. Cognitive load and metacognitive confidence extraction from pupillary response. Cognitive Systems Research. 2018 joulu 1;52:325-334. https://doi.org/10.1016/j.cogsys.2018.07.021

Angleraud A, Houbre Q, Kyrki V, Pieters R. Human-robot interactive learning architecture using ontologies and symbol manipulation. julkaisussa RO-MAN 2018 - 27th IEEE International Symposium on Robot and Human Interactive Communication: August 27-31, 2018, Nanjing, China.. IEEE. 2018. s. 384-389. (IEEE RO-MAN). https://doi.org/10.1109/ROMAN.2018.8525580

Tran DT, Iosifidis A, Gabbouj M. Improving efficiency in convolutional neural networks with multilinear filters. Neural Networks. 2018 syys 1;105:328-339. https://doi.org/10.1016/j.neunet.2018.05.017

Xiao L, Liao B, Li S, Chen K. Nonlinear recurrent neural networks for finite-time solution of general time-varying linear matrix equations. Neural Networks. 2018 helmi;98:102-113. https://doi.org/10.1016/j.neunet.2017.11.011

Chen K, Zhang Z. A Primal Neural Network for Online Equality-Constrained Quadratic Programming. Cognitive Computation. 2018;10(2):381–388. https://doi.org/10.1007/s12559-017-9510-4

Iantovics LB, Emmert-Streib F, Arik S. MetrIntMeas a novel metric for measuring the intelligence of a swarm of cooperating agents. Cognitive Systems Research. 2017 loka 1;45:17-29. https://doi.org/10.1016/j.cogsys.2017.04.006

Sciacca MFM, Romanucci V, Zarrelli A, Monaco I, Lolicato F, Spinella N et al. Inhibition of Aβ Amyloid Growth and Toxicity by Silybins: The Crucial Role of Stereochemistry. ACS Chemical Neuroscience. 2017 elo 16;8(8):1767-1778. https://doi.org/10.1021/acschemneuro.7b00110

Mokkila S, Postila PA, Rissanen S, Juhola H, Vattulainen I, Róg T. Calcium Assists Dopamine Release by Preventing Aggregation on the Inner Leaflet of Presynaptic Vesicles. ACS Chemical Neuroscience. 2017 kesä 21;8(6):1242-1250. https://doi.org/10.1021/acschemneuro.6b00395

Waris MA, Iosifidis A, Gabbouj M. CNN-based edge filtering for object proposals. Neurocomputing. 2017 kesä 2;266:631-640. https://doi.org/10.1016/j.neucom.2017.05.071

Moradi E, Khundrakpam B, Lewis JD, Evans AC, Tohka J. Predicting symptom severity in autism spectrum disorder based on cortical thickness measures in agglomerative data. NeuroImage. 2017;144(A):128–141. https://doi.org/10.1016/j.neuroimage.2016.09.049

Sun L, Peräkylä J, Polvivaara M, Öhman J, Peltola J, Lehtimäki K et al. Human anterior thalamic nuclei are involved in emotion-attention interaction. NEUROPSYCHOLOGIA. 2015 marras 1;78:88-94. https://doi.org/10.1016/j.neuropsychologia.2015.10.001

Iosifidis A, Tefas A, Pitas I. DropELM: Fast neural network regularization with Dropout and DropConnect. Neurocomputing. 2015 elo 25;162:57-66. https://doi.org/10.1016/j.neucom.2015.04.006

Iosifidis A, Tefas A, Pitas I. Distance-based human action recognition using optimized class representations. Neurocomputing. 2015 elo 5;161:47-55. https://doi.org/10.1016/j.neucom.2014.10.088

Bron EE, Smits M, van der Flier WM, Vrenken H, Barkhof F, Scheltens P et al. Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge. NeuroImage. 2015 touko 1;111:562-579. https://doi.org/10.1016/j.neuroimage.2015.01.048

Möttönen T, Katisko J, Haapasalo J, Tähtinen T, Kiekara T, Kähärä V et al. Defining the anterior nucleus of the thalamus (ANT) as a deep brain stimulation target in refractory epilepsy: Delineation using 3 T MRI and intraoperative microelectrode recording. NeuroImage: Clinical. 2015;7:823-829. https://doi.org/10.1016/j.nicl.2015.03.001

Iosifidis A. Extreme learning machine based supervised subspace learning. Neurocomputing. 2015;167:158–164. https://doi.org/10.1016/j.neucom.2015.04.083

Iosifidis A, Tefas A, Pitas I. Regularized extreme learning machine for multi-view semi-supervised action recognition. Neurocomputing. 2014 joulu 5;145:250-262. https://doi.org/10.1016/j.neucom.2014.05.036

Iosifidis A, Tefas A, Pitas I. Learning sparse representations for view-independent human action recognition based on fuzzy distances. Neurocomputing. 2013 joulu 9;121:344-353. https://doi.org/10.1016/j.neucom.2013.05.021

Faisal A, Gillberg J, Leen G, Peltonen J. Transfer learning using a nonparametric sparse topic model. Neurocomputing. 2013 heinä 18;112:124-137. https://doi.org/10.1016/j.neucom.2012.12.038

Pajarinen J, Peltonen J, Uusitalo MA. Fault tolerant machine learning for nanoscale cognitive radio. Neurocomputing. 2011 helmi;74(5):753-764. https://doi.org/10.1016/j.neucom.2010.10.007