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
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
P. Bozelos and P. Poirazi.
Impact of Structural Plasticity on Memory Capacity. In: van Ooyen A., Butz-Ostendorf M. (eds) The Rewiring Brain: A computational approach to structural plasticity in the adult brain, pp. 319-341. Academic Press (2017). doi: https://doi.org/10.1016/B978-0-12-803784-3.00015-9
An Architecture for the Acceleration of a Hybrid Leaky Integrate and Fire SNN on the Convey HC-2ex FPGA-Based Processor
E. Kousanakis, A. Dollas, E. Sotiriadis, I. Papaeustathiou, D.N. Pnevmatikakos, A. Papoutsi, S. Chavlis, P.C. Petrantonakis, P. Poirazi
IEEE 25th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM) – 2017, Napa, CA, USA. DOI: 10.1109/FCCM.2017.51
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
S.S. Stefanou, G. Kastellakis, and P. Poirazi
Creating and constraining compartmental models of neurons using experimental data. In: Korngreen A. (eds) Advanced patch-clamp analysis for neuroscientists, vol. 113, pp. 325-343. Humana Press, New York, NY (2016). doi: https://doi.org/10.1007/978-1-4939-3411-9_15
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.
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
Dendrites 2014
4th NAMASEN Training Workshop, Heraklion, Crete, July 1-4, 2014
Book of Abstracts
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
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.
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
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.
Poirazi P.
Dendritic Computation. In: Jaeger D., Jung R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY (2014). doi: https://doi.org/10.1007/978-1-4614-7320-6_125-1
Kastellakis G. and Poirazi P.
Cellular and dendritic memory allocation. In: Cuntz H., Remme M., Torben-Nielsen B. (eds) The Computing Dendrite, Springer Series in Computational Neuroscience, vol. 11, pp. 415-432. Springer, New York, NY (2014). doi: https://doi.org/10.1007/978-1-4614-8094-5_25
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Towards predicting persistent activity of neurons by statistical and fractal dimension-based features
Petrantonakis, P.C., Papoutsi, A., Poirazi, P.
The 2013 International Joint Conference on Neural Networks (IJCNN), Dallas, TX, 4-9 August, 2013. doi: 10.1109/IJCNN.2013.6707083
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
Papoutsi A., Sidiropoulou K. and Poirazi P.
Memory beyond synaptic plasticity: The role of intrinsic neuronal excitability. In: Memory Mechanisms in Health and Disease: Mechanistic basis of memory, pp. 53-80. World Scientific Publishing Co (2012). doi: https://doi.org/10.1142/9789814366700_0003
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
Poirazi P. and Pissadaki E.
The making of a detailed CA1 pyramidal neuron model. In: Cutsuridis, V., Graham, B.P., Cobb, S., Vida, I. (Eds.) Hippocampal Microcircuits. Springer Series in Computational Neuroscience, vol. 5, pp. 317-352. Springer, New York, NY (2010). doi: https://doi.org/10.1007/978-1-4419-0996-1_11
[Link to Book]
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
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
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
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
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
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
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