Lenk K, Satuvuori E, Lallouette J, Ladrón-de-Guevara A, Berry H, Hyttinen JAK. 2020. A Computational Model of Interactions Between Neuronal and Astrocytic Networks: The Role of Astrocytes in the Stability of the Neuronal Firing Rate. Frontiers in Computational Neuroscience. 13. https://doi.org/10.3389/fncom.2019.00092

Otterpohl JR, Emmert-Streib F, Pawelzik K. 2001. A constrained HMM-based approach to the estimation of perceptual switching dynamics in pigeons. Neurocomputing. 38-40:1495-1501. https://doi.org/10.1016/S0925-2312(01)00511-2

Pursiainen S, Agsten B, Wagner S, Wolters CH. 2017. Advanced boundary electrode modeling for tES and parallel tES/EEG. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 26(1):37-44. https://doi.org/10.1109/TNSRE.2017.2748930

Ylä-Outinen L, Tanskanen JMA, Kapucu FE, Hyysalo A, Hyttinen JAK, Narkilahti S. 2019. Advances in Human Stem Cell-Derived Neuronal Cell Culturing and Analysis. In In Vitro Neuronal Networks: From Culturing Methods to Neuro-Technological Applications. Springer New York LLC. pp. 299-329. (Advances in Neurobiology). https://doi.org/10.1007/978-3-030-11135-9_13

Hagman S, Kolasa M, Basnyat P, Helminen M, Kähönen M, Dastidar P, Lehtimäki T, Elovaara I. 2015. Analysis of apoptosis-related genes in patients with clinically isolated syndrome and their association with conversion to multiple sclerosis. JOURNAL OF NEUROIMMUNOLOGY. 280:43-48. https://doi.org/10.1016/j.jneuroim.2015.02.006

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

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

Pantsar T, Rissanen S, Dauch D, Laitinen T, Vattulainen I, Poso A. 2018. Assessment of mutation probabilities of KRAS G12 missense mutants and their long-timescale dynamics by atomistic molecular simulations and Markov state modeling. PLoS Computational Biology. 14(9). https://doi.org/10.1371/journal.pcbi.1006458

Ormiskangas J, Valtonen O, Kivekäs I, Dean M, Poe D, Järnstedt J, Lekkala J, Harju T, Saarenrinne P, Rautiainen M. 2020. Assessment of PIV performance in validating CFD models from nasal cavity CBCT scans. Respiratory Physiology and Neurobiology. 282. https://doi.org/10.1016/j.resp.2020.103508

Tenhunen M, Hasan J, Himanen SL. 2015. Assessment of respiratory effort during sleep with noninvasive techniques. Sleep Medicine Reviews. 24:103-104. https://doi.org/10.1016/j.smrv.2015.08.010

Basnyat P, Hagman S, Kolasa M, Koivisto K, Verkkoniemi-Ahola A, Airas L, Elovaara I. 2015. Association between soluble L-selectin and anti-JCV antibodies in natalizumab-treated relapsing-remitting MS patients. Multiple Sclerosis and Related Disorders. 4(4):334-338. https://doi.org/10.1016/j.msard.2015.06.008

Klapper SD, Garg P, Dagar S, Lenk K, Gottmann K, Nieweg K. 2019. Astrocyte lineage cells are essential for functional neuronal differentiation and synapse maturation in human iPSC-derived neural networks. Glia. 67(10):1893-1909. https://doi.org/10.1002/glia.23666

Vuorio J, Vattulainen I, Martinez-Seara H. 2017. Atomistic fingerprint of hyaluronan–CD44 binding. PLoS Computational Biology. 13(7). https://doi.org/10.1371/journal.pcbi.1005663

Nevalainen O, Auvinen A, Ansakorpi H, Raitanen J, Isojärvi J. 2014. Autoimmunity-related immunological serum markers and survival in a tertiary care cohort of adult patients with epilepsy. EPILEPSY RESEARCH. 108(9):1675-1679. https://doi.org/10.1016/j.eplepsyres.2014.08.014

Hyppönen J, Hakala A, Annala K, Zhang H, Peltola J, Mervaala E, Kälviäinen R. 2020. Automatic assessment of the myoclonus severity from videos recorded according to standardized Unified Myoclonus Rating Scale protocol and using human pose and body movement analysis. Seizure. 76:72-78. https://doi.org/10.1016/j.seizure.2020.01.014

Tanskanen JMA, Kapucu FE, Välkki I, Hyttinen JAK. 2016. Automatic objective thresholding to detect neuronal action potentials. In Proceedings of 2016 24th European Signal Processing Conference (EUSIPCO). pp. 662-666. https://doi.org/10.1109/EUSIPCO.2016.7760331

Spruijt-Metz D, Hekler E, Saranummi N, Intille S, Korhonen I, Nilsen W, Rivera DE, Spring B, Michie S, Asch DA, Sanna A, Salcedo VT, Kukakfa R, Pavel M. 2015. Building new computational models to support health behavior change and maintenance: new opportunities in behavioral research. Translational Behavioral Medicine. 5(3):335-346. https://doi.org/10.1007/s13142-015-0324-1

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

Kreutzer J, Ylä-Outinen L, Mäki A, Ristola M, Narkilahti S, Kallio P. 2017. Cell culture chamber with gas supply for prolonged recording of human neuronal cells on microelectrode array. Journal of Neuroscience Methods. 280:27-35. https://doi.org/10.1016/j.jneumeth.2017.01.019

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

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

Špakov O. 2012. Comparison of eye movement filters used in HCI. In Proceedings - ETRA 2012: Eye Tracking Research and Applications Symposium. pp. 281-284. https://doi.org/10.1145/2168556.2168616

Tohka J, Moradi E, Huttunen H, Alzheimer’s Disease Neuroimaging Initiative, Alzheimer’s Disease Neuroimaging Initiative 2. 2016. Comparison of Feature Selection Techniques in Machine Learning for Anatomical Brain MRI in Dementia. Neuroinformatics. 14(3):279-296. https://doi.org/10.1007/s12021-015-9292-3

Acar GO, Kivekäs I, Hanna BM, Huang L, Gopen Q, Poe DS. 2014. Comparison of stapedotomy minus prosthesis, circumferential stapes mobilization, and small fenestra stapedotomy for stapes fixation. OTOLOGY AND NEUROTOLOGY. 35(4). https://doi.org/10.1097/MAO.0000000000000280

Acimovic J, Mäki-Marttunen T, Linne M-L. 2010. Computational modeling of growth in cortial cultures using the NETMORPH simulation tool. In Neuroscience 2010, 40th Annual Meeting, San Diego, USA, 13-17 November 2010. pp. 2 p.

Acimovic J, Mäki-Marttunen T, Linne M-L. 2011. Computational study of structural changes in neuronal networks during growth: a model of dissociated neocortical cultures. Fellous J-M, Prinz A, editors. In Twentieth Annual Computational Neuroscience Meeting: CNS*2011. Stockholm: BioMed Central. pp. P203. (Annual Computational Neuroscience Meeting CNS). https://doi.org/10.1186/1471-2202-12-S1-P203

Acimovic J, Teppola H, Selinummi JJ, Linne M-L. 2009. Computational tools for assessing the properties of 2D neural cell cultures. Johnson D, editor. In Eighteenth Annual Computational Neuroscience Meeting: CNS*2009. Berlin: BioMed Central. pp. P170.

Enkavi G, Mikkolainen H, Güngör B, Ikonen E, Vattulainen I. 2017. Concerted regulation of npc2 binding to endosomal/lysosomal membranes by bis(monoacylglycero)phosphate and sphingomyelin. PLoS Computational Biology. 13(10). https://doi.org/10.1371/journal.pcbi.1005831

Pelkonen A, Yavich L. 2012. Cortical spreading depression in alpha-synuclein knockout mice. SYNAPSE. 66(1):81-84. https://doi.org/10.1002/syn.20980

Malmivaara K, Ohman J, Kivisaari R, Hernesniemi J, Siironen J. 2011. Cost-effectiveness of decompressive craniectomy in non-traumatic neurological emergencies. European Journal of Neurology. 18(3):402-409. https://doi.org/10.1111/j.1468-1331.2010.03162.x

Sharma V, Dixit D, Ghosh S, Sen E. 2011. COX-2 regulates the proliferation of glioma stem like cells. NEUROCHEMISTRY INTERNATIONAL. 59(5):567-571. https://doi.org/10.1016/j.neuint.2011.06.018

Acimovic J, Teppola H, Mäki-Marttunen TM, Linne M-L. 2018. Data-driven study of synchronous popula on ac vity in generic spiking neuronal networks: How much do we capture using the minimal model for the considered phenomena?. Paper presented at Brain and Mind Symposium 2018, Helsinki, Finland.

Acimovic J, Teppola H, Mäki-Marttunen TM, Linne M-L. 2018. Data-driven study of synchronous population activity in generic spiking neuronal networks: How much do we capture using the minimal model for the considered phenomena?. BMC Neuroscience. 19(Suppl 2):68-69.

Tavakoli HR, Borji A, Kannala J, Rahtu E. 2020. Deep audio-visual saliency: Baseline model and data. Spencer SN, editor. In Proceedings ETRA 2020 Short Papers - ACM Symposium on Eye Tracking Research and Applications, ETRA 2020. ACM. https://doi.org/10.1145/3379156.3391337

Möttönen T, Katisko J, Haapasalo J, Tähtinen T, Kiekara T, Kähärä V, Peltola J, Öhman J, Lehtimäki K. 2015. 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. 7:823-829. https://doi.org/10.1016/j.nicl.2015.03.001

Kolasa M, Hakulinen U, Brander A, Hagman S, Dastidar P, Elovaara I, Sumelahti M-L. 2019. Diffusion tensor imaging and disability progression in multiple sclerosis: A 4-year follow-up study. Brain and Behavior. 9(1). https://doi.org/10.1002/brb3.1194

Salminen AV, Manconi M, Rimpilä V, Luoto TM, Koskinen E, Ferri R, Öhman J, Polo O. 2013. Disconnection between periodic leg movements and cortical arousals in spinal cord injury. JOURNAL OF CLINICAL SLEEP MEDICINE. 9(11):1207-1209. https://doi.org/10.5664/jcsm.3174

Hagman S, Raunio M, Rossi M, Dastidar P, Elovaara I. 2011. Disease-associated inflammatory biomarker profiles in blood in different subtypes of multiple sclerosis: Prospective clinical and MRI follow-up study. JOURNAL OF NEUROIMMUNOLOGY. 234(1-2):141-147. https://doi.org/10.1016/j.jneuroim.2011.02.009

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

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

Berry J, Frederiksen R, Yao Y, Nymark S, Chen J, Cornwall C. 2016. Effect of rhodopsin phosphorylation on dark adaptation in mouse rods. Journal of Neuroscience. 36(26):6973-6987. https://doi.org/10.1523/JNEUROSCI.3544-15.2016

Juuti-Uusitalo K, Nieminen M, Treumer F, Ampuja M, Kallioniemi A, Klettner A, Skottman H. 2015. Effects of cytokine activation and oxidative stress on the function of the human embryonic stem cell–derived retinal pigment epithelial cells. Investigative Ophthalmology and Visual Science. 56(11):6265-6274. https://doi.org/10.1167/iovs.15-17333

Pelkonen A, Kallunki P, Yavich L. 2013. Effects of exogenous alpha-synuclein on stimulated dopamine overflow in dorsal striatum. Neuroscience Letters. 554:141-145. https://doi.org/10.1016/j.neulet.2013.08.072

Mäki-Marttunen TM, Acimovic J, Ruohonen KP, Linne M-L. 2011. Effects of local structure of neuronal networks on spiking activity in silico. Fellous J-M, Prinz A, editors. In Twentieth Annual Computational Neuroscience Meeting: CNS*2011. Stockholm: BioMed Central. pp. P202.

Mäki-Marttunen T, Acimovic J, Ruohonen K, Linne M-L. 2011. Effects of structure on spontaneous activity in simulated neuronal networks. In Proceedings of Mathematical Neuroscience (ICMS 2011), April 11-13, 2011, Edinburgh, Scotland.

Basnyat P, Natarajan R, Vistbakka J, Lehtikangas M, Airas L, Matinlauri I, Elovaara I, Hagman S. 2015. Elevated levels of soluble CD26 and CD30 in multiple sclerosis. Clinical and Experimental Neuroimmunology. 6(4):419-425. https://doi.org/10.1111/cen3.12253

Acimovic J. 2011. Emergence of global and local structural features during development of neuronal networks. In Proceedings of the Eighth International Workshop on Computational Systems Biology, WCSB 2011, June 6-8, 2011, Zürich, Switzerland . Tampere: TICSP. (TICSP Series ).

Sonkajärvi E, Rytky S, Alahuhta S, Suominen K, Kumpulainen T, Ohtonen P, Karvonen E, Jäntti V. 2018. Epileptiform and periodic EEG activities induced by rapid sevoflurane anaesthesia induction. Clinical Neurophysiology. 129(3):638-645. https://doi.org/10.1016/j.clinph.2017.12.037

Otterpohl JR, Haynes JD, Emmert-Streib F, Vetter G, Pawelzik K. 2001. Erratum: Extracting the dynamics of perceptual switching from 'noisy' behaviour: An application of hidden Markov modelling to pecking data from pigeons (Journal of Physiology Paris (2000) 94:5-6 (555-567) PII: S0928425700010950). Journal of Physiology: Paris. 95(1-6):497. https://doi.org/10.1016/S0928-4257(01)00091-2

Kivekäs I, Pöyhönen L, Aarnisalo A, Rautiainen M, Poe D. 2015. Eustachian tube mucosal inflammation scale validation based on digital video images. OTOLOGY AND NEUROTOLOGY. 36(10):1748-1752. https://doi.org/10.1097/MAO.0000000000000895

Tenhunen M, Huupponen E, Hasan J, Heino O, Himanen SL. 2015. Evaluation of the different sleep-disordered breathing patterns of the compressed tracheal sound. Clinical Neurophysiology. 126(8):1557-1563. https://doi.org/10.1016/j.clinph.2014.11.003

Franco P, Värri A. 2015. Experiments of the sonification of the sleep electroencephalogram. Finnish Journal of eHealth and eWelfare. 7(2-3):65-74.

Melkas S, Sibolt G, Oksala NKJ, Putaala J, Pohjasvaara T, Kaste M, Karhunen PJ, Erkinjuntti T. 2012. Extensive white matter changes predict stroke recurrence up to 5 years after a first-ever ischemic stroke. CEREBROVASCULAR DISEASES. 34(3):191-198. https://doi.org/10.1159/000341404

Otterpohl JR, Haynes JD, Emmert-Streib F, Vetter G, Pawelzik K. 2000. Extracting the dynamics of perceptual switching from 'noisy' behaviour: An application of hidden Markov modelling to pecking data from pigeons. Journal of Physiology: Paris. 94(5-6):555-567. https://doi.org/10.1016/S0928-4257(00)01095-0

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

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

Mäkinen M, Joki T, Ylä-Outinen L, Skottman H, Narkilahti S, Äänismaa R. 2013. Fluorescent probes as a tool for cell population tracking in spontaneously active neural networks derived from human pluripotent stem cells. Journal of Neuroscience Methods. 215(1):88-96. https://doi.org/10.1016/j.jneumeth.2013.02.019

Oschmann F, Berry H, Obermayer K, Lenk K. 2018. From in silico astrocyte cell models to neuron-astrocyte network models: A review. BRAIN RESEARCH BULLETIN. 136:76-84. https://doi.org/10.1016/j.brainresbull.2017.01.027

Kauppi J-P, Pajula J, Niemi J, Hari R, Tohka J. 2017. Functional brain segmentation using inter-subject correlation in fMRI. Human Brain Mapping. 38(5):2643-2665. https://doi.org/10.1002/hbm.23549

Hyrskykari A, Istance H, Vickers S. 2012. Gaze gestures or dwell-based interaction?. In Proceedings - ETRA 2012: Eye Tracking Research and Applications Symposium. pp. 229-232. https://doi.org/10.1145/2168556.2168602

Kangas J, Rantala J, Majaranta P, Isokoski P, Raisamo R. 2014. Haptic feedback to gaze events. In Proceedings of the Symposium on Eye Tracking Research and Applications, ETRA 2014. Association for Computing Machinery. pp. 11-18. https://doi.org/10.1145/2578153.2578154

Pajula J, Tohka J. 2016. How Many Is Enough? Effect of Sample Size in Inter-Subject Correlation Analysis of fMRI. Computational Intelligence and Neuroscience. 2016. https://doi.org/10.1155/2016/2094601

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

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

Hartikainen KM, Sun L, Polvivaara M, Brause M, Lehtimäki K, Haapasalo J, Möttönen T, Väyrynen K, Ogawa KH, Öhman J, Peltola J. 2014. Immediate effects of deep brain stimulation of anterior thalamic nuclei on executive functions and emotion-attention interaction in humans. JOURNAL OF CLINICAL AND EXPERIMENTAL NEUROPSYCHOLOGY. 36(5):540-550. https://doi.org/10.1080/13803395.2014.913554

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

Lehtimäki M, Paunonen L, Linne M-L. 2018. Improvement of computational efficiency of a biochemical plasticity model. BMC Neuroscience. 19(Suppl 2):66-66. https://doi.org/10.1186/s12868-018-0452-x#Sec613

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

Emmert-Streib F. 2013. Influence of the experimental design of gene expression studies on the inference of gene regulatory networks: Environmental factors. PeerJ. 2013(1). https://doi.org/10.7717/peerj.10

Emmert-Streib F. 2006. Influence of the neural network topology on the learning dynamics. Neurocomputing. 69(10-12):1179-1182. https://doi.org/10.1016/j.neucom.2005.12.070

Sciacca MFM, Romanucci V, Zarrelli A, Monaco I, Lolicato F, Spinella N, Galati C, Grasso G, D'Urso L, Romeo M, Diomede L, Salmona M, Bongiorno C, Di Fabio G, La Rosa C, Milardi D. 2017. Inhibition of Aβ Amyloid Growth and Toxicity by Silybins: The Crucial Role of Stereochemistry. ACS Chemical Neuroscience. 8(8):1767-1778. https://doi.org/10.1021/acschemneuro.7b00110

Dixit D, Sharma V, Ghosh S, Mehta VS, Sen E. 2012. Inhibition of Casein kinase-2 induces p53-dependent cell cycle arrest and sensitizes glioblastoma cells to tumor necrosis factor (TNFα)-induced apoptosis through SIRT1 inhibition. CELL DEATH AND DISEASE. 3(2). https://doi.org/10.1038/cddis.2012.10

Mäki-Marttunen TM, Acimovic J, Ruohonen KP, Linne M-L. 2012. In silico study on structure and dynamics in bursting neuronal networks. In Neuroscience 2012; 42nd Annual Meeting, New Orleans, USA, October 14-18, 2012. Society for Neuroscience (SfN).

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

Špakov O, Isokoski P, Majaranta P. 2014. Look and lean: Accurate head-assisted eye pointing. In Proceedings of the Symposium on Eye Tracking Research and Applications, ETRA 2014. Association for Computing Machinery. pp. 35-42. https://doi.org/10.1145/2578153.2578157

Satuvuori E, Mulansky M, Bozanic N, Malvestio I, Zeldenrust F, Lenk K, Kreuz T. 2017. Measures of spike train synchrony for data with multiple time scales. Journal of Neuroscience Methods. 287:25-38. https://doi.org/10.1016/j.jneumeth.2017.05.028

Natarajan R, Einarsdottir E, Riutta A, Hagman S, Raunio M, Mononen N, Lehtimäki T, Elovaara I. 2012. Melatonin pathway genes are associated with progressive subtypes and disability status in multiple sclerosis among Finnish patients. JOURNAL OF NEUROIMMUNOLOGY. 250(1-2):106-110. https://doi.org/10.1016/j.jneuroim.2012.05.014

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

Heikkinen H, Vinberg F, Nymark S, Koskelainen A. 2011. Mesopic background lights enhance dark-adapted cone ERG flash responses in the intact mouse retina: A possible role for gap junctional decoupling. Journal of Neurophysiology. 105(5):2309-2318. https://doi.org/10.1152/jn.00536.2010

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

Kaipio ML, Cheour M, Öhman J, Salonen O, Näätänen R. 2013. Mismatch negativity abnormality in traumatic brain injury without macroscopic lesions on conventional MRI. NeuroReport. 24(8):440-444. https://doi.org/10.1097/WNR.0b013e32836164b4

Teppola H, Sarkanen JR, Jalonen TO, Linne M-L. 2016. Morphological Differentiation Towards Neuronal Phenotype of SH-SY5Y Neuroblastoma Cells by Estradiol, Retinoic Acid and Cholesterol. Neurochemical Research. 41(4):731-747. https://doi.org/10.1007/s11064-015-1743-6

Nevalainen O, Auvinen A, Ansakorpi H, Artama M, Raitanen J, Isojärvi J. 2012. Mortality by clinical characteristics in a tertiary care cohort of adult patients with chronic epilepsy. EPILEPSIA. 53(12). https://doi.org/10.1111/epi.12006

Juhola H, Postila PA, Rissanen S, Lolicato F, Vattulainen I, Róg T. 2018. Negatively Charged Gangliosides Promote Membrane Association of Amphipathic Neurotransmitters. Neuroscience. 384:214-223. https://doi.org/10.1016/j.neuroscience.2018.05.035

Välkki IA, Lenk K, Mikkonen JE, Kapucu FE, Hyttinen JAK. 2017. Network-wide adaptive burst detection depicts neuronal activity with improved accuracy. Frontiers in Computational Neuroscience. 11. https://doi.org/10.3389/fncom.2017.00040

Acimovic J. 2009. Neural networks, cell cultures and some older work on data analysis. Paper presented at Okinawa Computational Neuroscience Course 2009, Japan.

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

Pelkonen A, Yavich L. 2011. Neuromuscular pathology in mice lacking alpha-synuclein. Neuroscience Letters. 487(3):350-353. https://doi.org/10.1016/j.neulet.2010.10.054

Sharma V, Bala A, Deshmukh R, Bedi KL, Sharma PL. 2012. Neuroprotective effect of RO-20-1724-a phosphodiesterase4 inhibitor against intracerebroventricular streptozotocin induced cognitive deficit and oxidative stress in rats. PHARMACOLOGY BIOCHEMISTRY AND BEHAVIOR. 101(2):239-245. https://doi.org/10.1016/j.pbb.2012.01.004

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

Iosifidis A, Mygdalis V, Tefas A, Pitas I. 2016. One-Class Classification based on Extreme Learning and Geometric Class Information. Neural Processing Letters. 1-16. https://doi.org/10.1007/s11063-016-9541-y

Mäki-Marttunen TM, Acimovic J, Ruohonen KP, Linne M-L. 2013. On the effect of network structure and synaptic mechanisms on sustained bursting activity. Cymbalyuk G, Prinz A, editors. In Twenty Second Annual Computational Neuroscience Meeting: CNS*2013. Paris, France: BioMed Central. pp. P247.

Ju YSE, Alexandrov LB, Gerstung M, Martincorena I, Nik-Zainal S, Ramakrishna M, Davies HR, Papaemmanuil E, Gundem G, Shlien A, Bolli N, Behjati S, Tarpey PS, Nangalia J, Massie CE, Butler AP, Teague JW, Vassiliou GS, Green AR, Du MQ, Unnikrishnan A, Pimanda JE, Teh BTE, Munshi N, Greaves M, Vyas P, El-Naggar AK, Santarius T, Collins VP, Grundy R, Taylor JA, Hayes DN, Malkin D, Foster CS, Warren AY, Whitaker HC, Brewer D, Eeles R, Cooper C, Neal D, Visakorpi T, Isaacs WB, Bova GS, Flanagan AM, Futreal PA, Lynch AG, Chinnery PF, McDermott U, Stratton MR, Campbell PJ. 2014. Origins and functional consequences of somatic mitochondrial DNA mutations in human cancer. eLIFE. 3. https://doi.org/10.7554/eLife.02935

Rönkkö T, Timonen H. 2019. Overview of Sources and Characteristics of Nanoparticles in Urban Traffic-Influenced Areas. Journal of Alzheimer's Disease. 72(1):15-28. https://doi.org/10.3233/JAD-190170

Emmert-Streib F, Glazko GV. 2011. Pathway analysis of expression data: Deciphering functional building blocks of complex diseases. PLoS Computational Biology. 7(5). https://doi.org/10.1371/journal.pcbi.1002053

Polinati PP, Ilmarinen T, Trokovic R, Hyotylainen T, Otonkoski T, Suomalainen A, Skottman H, Tynitiina T. 2015. Patient-specific induced pluripotent stem cell—derived RPE cells: Understanding the pathogenesis of retinopathy in long-chain 3-hydroxyacyl-CoA dehydrogenase deiciency. Investigative Ophthalmology and Visual Science. 56(5):3371-3382. https://doi.org/10.1167/iovs.14-14007

Saurus P, Kuusela S, Lehtonen E, Hyvönen ME, Ristola M, Fogarty CL, Tienari J, Lassenius MI, Forsblom C, Lehto M, Saleem MA, Groop PH, Holthöfer H, Lehtonen S. 2015. Podocyte apoptosis is prevented by blocking the Toll-like receptor pathway. CELL DEATH AND DISEASE. 6(5). https://doi.org/10.1038/cddis.2015.125

Sibolt G, Curtze S, Melkas S, Pohjasvaara T, Kaste M, Karhunen PJ, Oksala NKJ, Vataja R, Erkinjuntti T. 2013. Post-stroke depression and depression-executive dysfunction syndrome are associated with recurrence of ischaemic stroke. CEREBROVASCULAR DISEASES. 36(5-6):336-343. https://doi.org/10.1159/000355145

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

Rezaei A, Koulouri A, Pursiainen S. 2020. Randomized Multiresolution Scanning in Focal and Fast E/MEG Sensing of Brain Activity with a Variable Depth. Brain Topography. 33(2):161-175. https://doi.org/10.1007/s10548-020-00755-8

Špakov O, Gizatdinova Y. 2014. Real-time hidden gaze point correction. In Proceedings of the Symposium on Eye Tracking Research and Applications, ETRA 2014. Association for Computing Machinery. pp. 291-294. https://doi.org/10.1145/2578153.2578200

Javanainen M, Enkavi G, Guixà-Gonzaléz R, Kulig W, Martinez-Seara H, Levental I, Vattulainen I. 2019. Reduced level of docosahexaenoic acid shifts GPCR neuroreceptors to less ordered membrane regions. PLoS Computational Biology. 15(5). https://doi.org/10.1371/journal.pcbi.1007033

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

Puhakka IJA, Peltola MJ. 2020. Salivary cortisol reactivity to psychological stressors in infancy: A meta-analysis. PSYCHONEUROENDOCRINOLOGY. 115. https://doi.org/10.1016/j.psyneuen.2020.104603

Sibolt G, Curtze S, Melkas S, Pohjasvaara T, Kaste M, Karhunen PJ, Oksala NKJ, Erkinjuntti T. 2015. Severe cerebral white matter lesions in ischemic stroke patients are associated with less time spent at home and early institutionalization. INTERNATIONAL JOURNAL OF STROKE. 10(8):1192-1196. https://doi.org/10.1111/ijs.12578

Mäki-Marttunen TM, Acimovic J, Ruohonen KP, Linne M-L. 2012. Significance of graph theoretic measures in predicting neuronal network activity. In Proceedings of The 9th annual Computational and Systems Neuroscience meeting (COSYNE 2012). Salt Lake City. pp. 55-55.

Heikkilä H, Räihä KJ. 2012. Simple gaze gestures and the closure of the eyes as an interaction technique. In Proceedings - ETRA 2012: Eye Tracking Research and Applications Symposium. pp. 147-154. https://doi.org/10.1145/2168556.2168579

Ilvesmäki T, Koskinen E, Brander A, Luoto T, Öhman J, Eskola H. 2017. Spinal cord injury induces widespread chronic changes in cerebral white matter. Human Brain Mapping. 38(7):3637-3647. https://doi.org/10.1002/hbm.23619

Bron EE, Smits M, van der Flier WM, Vrenken H, Barkhof F, Scheltens P, Papma JM, Steketee RME, Méndez Orellana C, Meijboom R, Pinto M, Meireles JR, Garrett C, Bastos-Leite AJ, Abdulkadir A, Ronneberger O, Amoroso N, Bellotti R, Cárdenas-Peña D, Álvarez-Meza AM, Dolph CV, Iftekharuddin KM, Eskildsen SF, Coupé P, Fonov VS, Franke K, Gaser C, Ledig C, Guerrero R, Tong T, Gray KR, Moradi E, Tohka J, Routier A, Durrleman S, Sarica A, Di Fatta G, Sensi F, Chincarini A, Smith GM, Stoyanov ZV, Sørensen L, Nielsen M, Tangaro S, Inglese P, Wachinger C, Reuter M, van Swieten JC, Niessen WJ, Klein S. 2015. Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge. NeuroImage. 111:562-579. https://doi.org/10.1016/j.neuroimage.2015.01.048

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

Sharmin S, Špakov O, Räihä KJ. 2012. The effect of different text presentation formats on eye movement metrics in reading. JOURNAL OF EYE MOVEMENT RESEARCH. 5(3).

Acimovic J, Mäki-Marttunen T, Linne M-L. 2015. The effects of neuron morphology on graph theoretic measures of network connectivity: The analysis of a two-level statistical model. Frontiers in Neuroanatomy. 9(June). https://doi.org/10.3389/fnana.2015.00076

Saarela C, Karrasch M, Ilvesmäki T, Parkkola R, Rinne JO, Laine M. 2016. The relationship between recognition memory for emotion-laden words and white matter microstructure in normal older individuals. NeuroReport. 27(18):1345-1349. https://doi.org/10.1097/WNR.0000000000000704

Istance H, Vickers S, Hyrskykari A. 2012. The validity of using non-representative users in gaze communication research. In Proceedings - ETRA 2012: Eye Tracking Research and Applications Symposium. pp. 233-236. https://doi.org/10.1145/2168556.2168603

Gracia-Tabuenca J, Seppä V-P, Jauhiainen M, Paassilta M, Viik J, Karjalainen J. 2020. Tidal breathing flow profiles during sleep in wheezing children measured by impedance pneumography. Respiratory Physiology and Neurobiology. 271. https://doi.org/10.1016/j.resp.2019.103312

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

Akkil D, Isokoski P, Kangas J, Rantala J, Raisamo R. 2014. TraQuMe: A tool for measuring the gaze tracking quality. In Proceedings of the Symposium on Eye Tracking Research and Applications, ETRA 2014. Association for Computing Machinery. pp. 327-330. https://doi.org/10.1145/2578153.2578192

Teppola H, Aćimović J, Linne ML. 2019. Unique Features of Network Bursts Emerge From the Complex Interplay of Excitatory and Inhibitory Receptors in Rat Neocortical Networks. FRONTIERS IN CELLULAR NEUROSCIENCE. 13. https://doi.org/10.3389/fncel.2019.00377

Alarautalahti V, Ragauskas S, Hakkarainen JJ, Uusitalo-Järvinen H, Uusitalo H, Hyttinen J, Kalesnykas G, Nymark S. 2019. Viability of Mouse Retinal Explant Cultures Assessed by Preservation of Functionality and Morphology. Investigative ophthalmology & visual science. 60(6):1914-1927. https://doi.org/10.1167/iovs.18-25156

Acimovic J, Mäki-Marttunen TM, Linne M-L. 2015. Whole-cell morphological properties of neurons constrain the nonrandom features of network connectivity. Cymbalyuk G, Burkitt A, editors. In 24th Annual Computational Neuroscience Meeting: CNS*2015. Prague: BioMed Central. pp. P:O7.

Zou J, Hannula M, Lehto K, Feng H, Lähelmä J, Aula AS, Hyttinen J, Pyykkö I. 2015. X-ray microtomographic confirmation of the reliability of CBCT in identifying the scalar location of cochlear implant electrode after round window insertion. Hearing Research. 326:59-65. https://doi.org/10.1016/j.heares.2015.04.005

He Q, Rezaei A, Pursiainen S. 2019. Zeffiro User Interface for Electromagnetic Brain Imaging: a GPU Accelerated FEM Tool for Forward and Inverse Computations in Matlab. Neuroinformatics. https://doi.org/10.1007/s12021-019-09436-9