Artificial Neural Networks in Action for an Automated Cell-Type Classification of Biological Neural Networks
Troullinou E., Tsagkatakis G., Chavlis S., Turi G.F., Li W., Losonczy A., Tsakalides P, and Poirazi P.
IEEE TETCI, 13 October 2020 | DOI: https://doi.org/10.1109/TETCI.2020.3028581
Large-Scale 3D Two-Photon Imaging of Molecularly Identified CA1 Interneuron Dynamics in Behaving Mice
Geiller, T, Vancura, V, …, Chavlis, …, S, Tsakalides, P, …, Poirazi, P Rózsa, BJ Losonczy, A
Neuron, 05 Oct 2020 | DOI: 10.1016/j.neuron.2020.09.013
Reflections on the past two decades of neuroscience
Bassett, DS, Cullen, KE, …, Poirazi P, …, Sur M, Ueda HR
Nature Reviews Neuroscience, 02 Sep 2020 | DOI: 10.1038/s41583-020-0363-6
Illuminating dendritic function with computational models
Panayiota Poirazi* & Athanasia Papoutsi
Nature Reviews Neuroscience, 11 May 2020 | DOI: 10.1038/s41583-020-0301-7
Breakdown of spatial coding and interneuron synchronization in epileptic mice
Shuman T*, …, Chavlis S, … Pandi I, …, Poirazi P*, Silva AJ, Golshani P*
Nature Neuroscience, 06 Jan 2020 | DOI: 10.1038/s41593-019-0559-0
Synaptic Clustering and Memory Formation
Kastellakis G. & Poirazi P.
Front. Mol. Neurosci., 2019 Dec 6 | https://doi.org/10.3389/fnmol.2019.00300
Dendritic action potentials and computation in human layer 2/3 cortical neurons
Gidon A, Zolnik TA, Fidzinski P, Bolduan F, Papoutsi A, Poirazi P, Holtkamp M, Vida I, Larkum ME
Science, 03 Jan 2020 | DOI: 10.1126/science.aax6239
[Podcast at Quanta Magazine]
A deep learning framework for neuroscience
Richards B.A., Lillicrap T.P., … Poirazi P. … Kording K.P.
Nature Neuroscience, 2019 | DOI: http://dx.doi.org/10.1038/s41593-019-0520-2
Vasoactive Intestinal Polypeptide-Expressing Interneurons in the Hippocampus Support Goal-Oriented Spatial Learning
Turi G.F., Li W.K., Chavlis S., Pandi I., O’Hare J., Priestley J.B., Grosmark A.D., Liao Z., Ladow M., Zhang J.F., Zemelman B.V., Poirazi P.*, Losonczy A*.
Neuron. 2019 Jan 31 | DOI: https://doi.org/10.1016/j.neuron.2019.01.009
Contribution of apical and basal dendrites to orientation encoding in mouse V1 L2/3 pyramidal neurons
Park, J., Papoutsi, A., Ash, R. T., Marin, M. A., Poirazi, P*., Smirnakis, S. M.*
Nat. Commu., 26 November 2019. | DOI: https://doi.org/10.1038/s41467-019-13029-0
Optically Induced Calcium-Dependent Gene Activation and Labeling of Active Neurons Using CaMPARI and Cal-Light
Ebner C, Ledderose J, Zolnik TA, Dominiak SE, Turko P, Papoutsi A, Poirazi P, Eickholt BJ, Vida I, Larkum ME, Sachdev RNS
Front Synaptic Neurosci., 2019 May 24 | DOI: https://doi.org/10.3389/fnsyn.2019.00016
Challenging the point neuron dogma: FS basket cells as 2-stage nonlinear integrators
Tzilivaki A., Kastellakis G., Poirazi P.
Nat Commun, 2019 Aug 14 | DOI: https://doi.org/10.1038/s41467-019-11537-7
Two distinct sets of Ca2+ and K+ channels are activated at different membrane potentials by the climbing fibre synaptic potential in Purkinje neuron dendrites
Ouares K.A., Filipis L., Tzilivaki A., Poirazi P., Canepari M.
J Neurosci., 2019 Jan 10 | doi: 10.1523/JNEUROSCI.2155-18.2018
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Hotspots of dendritic spine turnover facilitate clustered spine addition and learning and memory
Frank A.C., Huang S., Zhou M., Gdalyahu A., Kastellakis G., Silva T.K., Lu E., Wen X., Poirazi P.*, Trachtenberg J.T., Silva A.J.
Nat Commun. 2018 January. | DOI: 10.1038/s41467-017-02751-2
Pattern separation in the Hippocampus through the eyes of computational modeling
Chavlis S., Poirazi P.
Synapse. 2017 Mar 18. doi: 10.1002/syn.21972.
Synaptic plasticity in dendrites: complications and coping strategies
Bartlett W Mel, Jackie Schiller and Panayiota Poirazi
Current Opinion in Neurobiology. 2017 May | DOI: 10.1016/j.conb.2017.03.012
In Vivo Imaging of Dentate Gyrus Mossy Cells in Behaving Mice
Danielson, N. B., Turi, G. F., Ladow, M., Chavlis, S., Petrantonakis, P. C., Poirazi, P.*, & Losonczy, A.*
Neuron. 2017 Feb., DOI: http://dx.doi.org/10.1016/j.neuron.2016.12.019
…with Love, from Post to Pre
Panayiota Poirazi, George Kastellakis
Neuron. 2017 September | DOI: 10.1016/j.neuron.2017.09.02
A novel and simple spike sorting implementation
Petrantonakis P.C., Poirazi P.
IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2016 Dec., DOI: 10.1109/TNSRE.2016.2640858
REMOD: A Tool for Analyzing and Remodeling the Dendritic Architecture of Neural Cells
Bozelos, P., Stefanou, S.S., Bouloukakis, G., Melachrinos, C., Poirazi, P.
Front. Neuroanat., 06 January 2016 | doi: http://dx.doi.org/10.3389/fnana.2015.00156
Linking Memories across Time via Neuronal and Dendritic Overlaps in Model Neurons with Active Dendrites
Kastellakis, G., Silva, A.J., Poirazi, P.
Cell Reports. 2016 Nov | http://dx.doi.org/10.1016/j.celrep.2016.10.015
Dendrites of dentate gyrus granule cells contribute to pattern separation by controlling sparsity
Chavlis, S., Petrantonakis, C.P., Poirazi, P.
Hippocampus. 2016 Oct, DOI: http://dx.doi.org/10.1002/hipo.22675
Opening Up: open access publishing, data sharing, and how they can influence your neuroscience career
Spires-Jones, T.L., Poirazi, P., Grubb, M.S.
European Journal of Neuroscience, 04 March 2016 | doi: http://dx.doi.org/10.1111/ejn.13234
Balancing family with a successful career in neuroscience.
Poirazi, P., Belin, D., Gräff, J., Hanganu‐Opatz, I., and López‐Bendito, G.
European Journal of Neuroscience, 2016. | http://dx.doi.org/10.1111/ejn.13280
The road to independence: how to get funding in neuroscience
Yaksi, E., Poirazi, P., Hanganu-Opatz, I.
Eur J Neurosci. 10 January 2016 | doi: https://doi: 10.1111/ejn.13169.
Emerging applications of read profiles towards the functional annotation of the genome
Pundhir, S., Poirazi, P., Gorodkin, J.
Front Genet. 2015 May 19;6:188. doi: 10.3389/fgene.2015.00188. eCollection 2015.
A Simple Method to Simultaneously Detect and Identify Spikes from Raw Extracellular Recordings
Petrantonakis, P.C., and Poirazi, P.
Front. Neurosci., 02 December 2015 | doi: https://doi.org/10.3389/fnins.2015.00452
MiRduplexSVM: A High-Performing MiRNA-Duplex Prediction and Evaluation Methodology.
Karathanasis, N., Tsamardinos, I., Poirazi, P.
PLoS One. 2015 May 11;10(5):e0126151. doi: 10.1371/journal.pone.0126151
A computational study on how theta modulated inhibition can account for the long temporal windows in the entorhinal-hippocampal loop
Cutsuridis, V., Poirazi, P.
Neurobiol Learn Mem. 2015 Apr;120:69-83. doi: 10.1016/j.nlm.2015.02.002
Dentate Gyrus Circuitry Features Improve Performance of Sparse Approximation Algorithms
Petrantonakis, P.C. and Poirazi, P.
PLoS One. 2015; 10(1): e0117023. doi: 10.1371/journal.pone.0117023
Synaptic clustering within dendrites: An emerging theory of memory formation
Kastellakis, G., Cai, D.J., Mednick, S.C., Silva, A.J., Poirazi, P.
Prog Neurobiol. 2015 Mar;126:19-35. doi: 10.1016/j.pneurobio.2014.12.002.
A Simulation Study on the Effects of Dendritic Morphology on Layer V Prefontal Pyramidal Cell Firing Behavior
Psarrou, M., Stefanou, S.S., Papoutsi, A., Tzilivaki, A., Cutsuridis, V., Poirazi, P.
Front Cell Neurosci. 2014 Sep 16;8:287. doi: 10.3389/fncel.2014.00287
A compressed sensing perspective of hippocampal function
Petrantonakis, P.C. and Poirazi, P.
Front Syst Neurosci. 2014; 8: 141. doi: 10.3389/fnsys.2014.00141
Dendritic Nonlinearities Reduce Network Size Requirements and Mediate ON and OFF States of Persistent Activity in a PFC Microcircuit Model
Papoutsi, A., Sidiropoulou, K., Poirazi, P.
PLoS Comput Biol. 2014 Jul 31;10(7):e1003764. doi: 10.1371/journal.pcbi.1003764
GluA2 mRNA distribution and regulation by miR-124 in hippocampal neurons
Ho, V.M., Dallalzadeh, L.O., Karathanasis, N., Keles, M.F., Vangala, S., Grogan, T., Poirazi, P., Martin, K.C.
Mol Cell Neurosci. 2014 Jul;61:1-12. doi: 10.1016/j.mcn.2014.04.006.
Don’t use a cannon to kill the … miRNA mosquito.
Karathanasis, N., Tsamardinos, I., Poirazi, P.
Bioinformatics. 2014 Apr 1;30(7):1047-8. doi: 10.1093/bioinformatics/btu100.
Modulatory effects of inhibition on persistent activity in a cortical microcircuit model
Konstantoudaki, X., Papoutsi, A., Chalkiadaki, K., Poirazi, P., Sidiropoulou, K.
Front Neural Circuits. 2014 Jan 31;8:7. doi: 10.3389/fncir.2014.00007
Induction and modulation of persistent activity in a layer V PFC microcircuit model.
Papoutsi, A., Sidiropoulou, K., Cutsuridis, V., Poirazi, P.
Front Neural Circuits. 2013 Oct 9;7:161. doi: 10.3389/fncir.2013.00161
Coding and Decoding with Dendrites
Papoutsi, A., Kastellakis, G., Psarrou, M., Anastasakis, S., Poirazi, P.
J. Physiol Paris. 2014 Feb;108(1):18-27. doi: 10.1016/j.jphysparis.2013.05.003
Improved grading and survival prediction of human astrocytic brain tumors by artificial neural network analysis of gene expression microarray data
Petalidis, L.P., Oulas, A., Backlund, M., Wayland, M.T., Liu, L., Plant, K., Happerfield, L., Freeman, T.C., Poirazi, P., Collins, V.P.
Mol Cancer Ther. 2008 May;7(5):1013-24. doi: 10.1158/1535-7163.MCT-07-0177
The Hitchhiker’s Guide to a Neuroscience Career
Joëls, M., Hoogenraad, C.C., Poirazi, P., Di Luca, M.
Neuron. 2015 May 6;86(3):613-6. doi: 10.1016/j.neuron.2015.04.002.
Modeling regulatory cascades using Artificial Neural Networks: the case of transcriptional regulatory networks shaped during the yeast stress response
Manioudaki, M.E., Poirazi, P.
Front Genet. 2013 Jun 20;4:110. doi: 10.3389/fgene.2013.00110
Computational modeling of the effects of amyloid-beta on release probability at hippocampal synapses
Romani, A., Marchetti, C., Bianchi, D., Leinekugel, X., Poirazi, P., Migliore, M., Marie, H.
Front Comput Neurosci. 2013 Jan 25;7:1. doi: 10.3389/fncom.2013.00001
A new microRNA target prediction tool identifies a novel interaction of a putative miRNA with CCND2
Oulas, A., Karathanasis, N., Louloupi, A., Iliopoulos, I., Kalantidis, K., Poirazi, P..
RNA Biol. 2012 Sep;9(9):1196-207. doi: 10.4161/rna.21725
Predictive Features of Persistent Activity Emergence in Regular Spiking and Intrinsic Bursting Model Neurons.
Sidiropoulou, K., Poirazi, P.
PLoS Comput Biol. 2012;8(4):e1002489. doi: 10.1371/journal.pcbi.1002489
Distinguishing Linear vs. Non-Linear Integration in CA1 Radial Oblique Dendrites: It’s about Time
Gómez González, J.F., Mel, B.W., Poirazi, P.
Front Comput Neurosci. 2011 Nov 14;5:44. doi: 10.3389/fncom.2011.00044
A computational exploration of bacterial metabolic diversity identifying metabolic interactions and growth-efficient strain communities
Tzamali, E., Poirazi, P., Tollis, I.G., Reczko, M.
BMC Syst Biol. 2011 Oct 18;5:167. doi: 10.1186/1752-0509-5-167
Finding cancer-associated miRNAs: methods and tools
Oulas, A., Karathanasis, N., Louloupi, A., Poirazi, P.
Mol Biotechnol. 2011 Sep;49(1):97-107. doi: 10.1007/s12033-011-9416-4
Encoding of Spatio-temporal Input Characteristics by a CA1 Pyramidal Neuron Model
Pissadaki, E.K., Sidiropoulou, K., Reczko, M., Poirazi, P.
PLoS Comput Biol. 2010 Dec 16;6(12):e1001038. doi: 10.1371/journal.pcbi.1001038
MatureBayes: a probabilistic algorithm for identifying the mature miRNA within novel precursors
Gkirtzou, K., Tsamardinos, I., Tsakalides, P., Poirazi, P.
PLoS One. 2010 Aug 6;5(8):e11843. doi: 10.1371/journal.pone.0011843
Neurofibromin regulates corticostriatal inhibitory networks during working memory performance
Shilyansky, C., Karlsgodt, K.H., Cummings, D.M., Sidiropoulou, K., Hardt, M., James, A.S., Ehninger, D., Bearden, C.E., Poirazi, P., Jentsch, J.D., Cannon, T.D., Levine, M.S., Silva, A.J.
Proc Natl Acad Sci U S A. 2010 Jul 20;107(29):13141-6. doi: 10.1073/pnas.1004829107
CREB regulates excitability and the allocation of memory to subsets of neurons in the amygdala
Zhou, Y., Won, J., Karlsson, M.G., Zhou, M., Rogerson, T., Balaji, J., Neve, R., Poirazi, P., Silva, A.J.
Nat Neurosci. 2009 Nov;12(11):1438-43. doi: 10.1038/nn.2405
Prediction of novel microRNA genes in cancer-associated genomic regions–a combined computational and experimental approach
Oulas, A., Boutla, A., Gkirtzou, K., Reczko, M., Kalantidis, K., Poirazi, P.
Nucleic Acids Res. 2009 Jun;37(10):3276-87. doi: 10.1093/nar/gkp120
MicroRNAs and Cancer-the search begins!
Oulas, A., Reczko, M., Poirazi, P.
IEEE Trans Inf Technol Biomed. 2009 Jan;13(1):67-77. doi: 10.1109/TITB.2008.2007086
Differential effects of corticosterone on the slow afterhyperpolarization in the basolateral amygdala and CA1 region: possible role of calcium channel subunits
Liebmann, L., Karst, H., Sidiropoulou, K., van Gemert, N., Meijer, O.C., Poirazi, P., Joëls, M.
J Neurophysiol. 2008 Feb;99(2):958-68. doi: https://doi.org/10.1152/jn.01137.2007
Use of artificial neural networks and a gamma-concept-based approach to model growth of and bacteriocin production by Streptococcus macedonicus ACA-DC 198 under conditions simulating Kasseri cheese technology.
Poirazi, P., Leroy, F., Georgalaki, M.D., Aktypis, A., De Vuyst, L., Tsakalidou, E.
Appl Environ Microbiol. 2007 Feb;73(3):768-76. doi: https://doi.org/10.1128/aem.01721-06
Modulation of excitability in CA1 pyramidal neurons via the interplay of EC and CA3 inputs
Pissadaki, E.K. and Poirazi, P.
Neurocomputing, Special Issue for CNS 2006, vol. 70, No 11-12, pg. 1640-1644, June 2007. doi: https://doi.org/10.1016/j.neucom.2006.10.098
Modeling stress-induced adaptations in Ca2+ dynamics
Sidiropoulou, K., Joels M., and Poirazi, P.
Neurocomputing, Special Issue for CNS 2006, vol. 70, No 11-12, pg. 1640-1644, June 2007. doi: https://doi.org/10.1016/j.neucom.2006.10.068
Individualized markers optimize class prediction of microarray data
Pavlidis, P., Poirazi, P.
BMC Bioinformatics. 2006 Jul 14;7:345. DOI: 10.1186/1471-2105-7-345
Tags: 2006 , Bioinformatics
Inside the brain of a neuron
Sidiropoulou, K., Pissadaki, E.K., Poirazi, P.
EMBO Reports, 2006 Sep;7(9):886-92. DOI: 10.1038/sj.embor.7400789
Tags: 2006 , Dendrites , Dendritic Computations , Neural Computations , Neuroscience , Review
Modelling reduced excitability in aged CA1 neurons as a calcium-dependent process
Markaki, M., Orphanoudakis, S. and Poirazi, P.
Neurocomputing, vol. 65-66, pg. 305-314, June 2005. DOI: https://doi.org/10.1016/j.neucom.2004.10.023
Classification Capacity of a Modular Neural Network Implementing Neurally Inspired Architecture and Training
Poirazi, P., Neocleous, C., Pattichis, C.S., Schizas, C.N.
IEEE Trans Neural Netw. 2004 May;15(3):597-612. DOI: 10.1109/TNN.2004.826225
Arithmetic of Subthreshold Synaptic Summation in a Model CA1 Pyramidal Cell.
Poirazi, P., Brannon, T., Mel, B.W.
Neuron. 2003 Mar 27;37(6):977-87. DOI: 10.1016/s0896-6273(03)00148-x
Tags: 2003 , Biophysical Model , CA1 , Dendritic Computations , Hippocampus , Neural Computations , Neuroscience , Single Neuron Model
Pyramidal Neuron as 2-Layer Neural Network.
Poirazi, P., Brannon, T., Mel, B.W.
Neuron. 2003 Mar 27;37(6):989-99. DOI: 10.1016/s0896-6273(03)00149-1
Tags: 2003 , Biophysical Model , CA1 , Dendritic Computations , Hippocampus , Machine Learning , Neural Computations , Neuroscience , Single Neuron Model
Impact of Active Dendritic Processing and Structural Plasticity on Learning and Memory
Poirazi, P., Mel, B.W.
Neuron. 2001 Mar;29(3):779-96. DOI: 10.1016/s0896-6273(01)00252-5
Tags: 2001 , Dendrites , Dendritic Computations , Dendritic Plasticity , Learning and Memory , Machine Learning , Neural Computations , Structure-Function
Choice and value flexibility jointly contribute to the capacity of a subsampled quadratic classifier.
Poirazi, P, Mel, B.W.
Neural Comput. 2000 May;12(5):1189-205. DOI: 10.1162/089976600300015556
Towards the Memory Capacity of Neurons with Active Dendrites.
Poirazi, P. and Mel, B.W.
Neurocomputing, vol. 26-27, pg. 237-245, 1999. doi: https://doi.org/10.1016/S0925-2312(99)00078-8