Skip to main content
×
Home
    • Aa
    • Aa
  • Get access
    Check if you have access via personal or institutional login
  • Cited by 147
  • Cited by
    This article has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Colombi, Ilaria Tinarelli, Federico Pasquale, Valentina Tucci, Valter and Chiappalone, Michela 2016. A Simplified In vitro Experimental Model Encompasses the Essential Features of Sleep. Frontiers in Neuroscience, Vol. 10,


    Gafarov, F.M. 2016. Emergence of the small-world architecture in neural networks by activity dependent growth. Physica A: Statistical Mechanics and its Applications, Vol. 461, p. 409.


    Mendis, G D C Morrisroe, E Petrou, S and Halgamuge, S K 2016. Use of adaptive network burst detection methods for multielectrode array data and the generation of artificial spike patterns for method evaluation. Journal of Neural Engineering, Vol. 13, Issue. 2, p. 026009.


    Napoli, Alessandro and Obeid, Iyad 2016. Comparative Analysis of Human and Rodent Brain Primary Neuronal Culture Spontaneous Activity Using Micro-Electrode Array Technology. Journal of Cellular Biochemistry, Vol. 117, Issue. 3, p. 559.


    Pastore, Vito Paolo Poli, Daniele Godjoski, Aleksandar Martinoia, Sergio and Massobrio, Paolo 2016. ToolConnect: A Functional Connectivity Toolbox for In vitro Networks. Frontiers in Neuroinformatics, Vol. 10,


    Pimashkin, Alexey Gladkov, Arseniy Agrba, Ekaterina Mukhina, Irina and Kazantsev, Victor 2016. Selectivity of stimulus induced responses in cultured hippocampal networks on microelectrode arrays. Cognitive Neurodynamics, Vol. 10, Issue. 4, p. 287.


    Poli, Daniele Pastore, Vito Paolo Martinoia, Sergio and Massobrio, Paolo 2016. From functional to structural connectivity using partial correlation in neuronal assemblies. Journal of Neural Engineering, Vol. 13, Issue. 2, p. 026023.


    Pulizzi, Rocco Musumeci, Gabriele Van den Haute, Chris Van De Vijver, Sebastiaan Baekelandt, Veerle and Giugliano, Michele 2016. Brief wide-field photostimuli evoke and modulate oscillatory reverberating activity in cortical networks. Scientific Reports, Vol. 6, p. 24701.


    Ambroise, M. Levi, T. and Saïghi, S. 2015. Biomimetic Technologies.


    Baltz, Thomas and Voigt, Thomas 2015. Interaction of electrically evoked activity with intrinsic dynamics of cultured cortical networks with and without functional fast GABAergic synaptic transmission. Frontiers in Cellular Neuroscience, Vol. 9,


    Bikbaev, Arthur Frischknecht, Renato and Heine, Martin 2015. Brain extracellular matrix retains connectivity in neuronal networks. Scientific Reports, Vol. 5, p. 14527.


    Braun, Erez and Marom, Shimon 2015. Universality, complexity and the praxis of biology: Two case studies. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences, Vol. 53, p. 68.


    Bruzzone, Arianna Pasquale, Valentina Nowak, Przemyslaw Tessadori, Jacopo Massobrio, Paolo and Chiappalone, Michela 2015. 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). p. 3391.

    de Santos-Sierra, Daniel Sendiña-Nadal, Irene Leyva, Inmaculada Almendral, Juan A. Ayali, Amir Anava, Sarit Sánchez-Ávila, Carmen and Boccaletti, Stefano 2015. Graph-based unsupervised segmentation algorithm for cultured neuronal networks' structure characterization and modeling. Cytometry Part A, Vol. 87, Issue. 6, p. 513.


    Haroush, Netta and Marom, Shimon 2015. Slow dynamics in features of synchronized neural network responses. Frontiers in Computational Neuroscience, Vol. 9,


    Harrill, Joshua A Chen, Hao Streifel, Karin M Yang, Dongren Mundy, William R and Lein, Pamela J 2015. Ontogeny of biochemical, morphological and functional parameters of synaptogenesis in primary cultures of rat hippocampal and cortical neurons. Molecular Brain, Vol. 8, Issue. 1, p. 10.


    Koutsou, Achilleas Bugmann, Guido and Christodoulou, Chris 2015. On learning time delays between the spikes from different input neurons in a biophysical model of a pyramidal neuron. Biosystems, Vol. 136, p. 80.


    Krohs, Ulrich 2015. Can functionality in evolving networks be explained reductively?. Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences, Vol. 53, p. 94.


    le Feber, Joost Postma, Wybren de Weerd, Eddy Weusthof, Marcel and Rutten, Wim L. C. 2015. Barbed channels enhance unidirectional connectivity between neuronal networks cultured on multi electrode arrays. Frontiers in Neuroscience, Vol. 9,


    Mari, João Fernando Saito, José Hiroki Neves, Amanda Ferreira Lotufo, Celina Monteiro da Cruz Destro-Filho, João-Batista and Nicoletti, Maria do Carmo 2015. Quantitative Analysis of Rat Dorsal Root Ganglion Neurons Cultured on Microelectrode Arrays Based on Fluorescence Microscopy Image Processing. International Journal of Neural Systems, Vol. 25, Issue. 08, p. 1550033.


    ×

Development, learning and memory in large random networks of cortical neurons: lessons beyond anatomy

  • Shimon Marom (a1) and Goded Shahaf (a1)
  • DOI: http://dx.doi.org/10.1017/S0033583501003742
  • Published online: 01 February 2002
Abstract

1. Introduction 63

1.1 Outline 63

1.2 Universals versus realizations in the study of learning and memory 64

2. Large random cortical networks developing ex vivo 65

2.1 Preparation 65

2.2 Measuring electrical activity 67

3. Spontaneous development 69

3.1 Activity 69

3.2 Connectivity 70

4. Consequences of spontaneous activity: pharmacological manipulations 72

4.1 Structural consequences 72

4.2 Functional consequences 73

5. Effects of stimulation 74

5.1 Response to focal stimulation 74

5.2 Stimulation-induced changes in connectivity 74

6. Embedding functionality in real neural networks 77

6.1 Facing the physiological definition of ‘reward’: two classes of theories 78

6.2 Closing the loop 79

7. Concluding remarks 84

8. Acknowledgments 85

9. References 85

The phenomena of learning and memory are inherent to neural systems that differ from each other markedly. The differences, at the molecular, cellular and anatomical levels, reflect the wealth of possible instantiations of two neural learning and memory universals: (i) an extensive functional connectivity that enables a large repertoire of possible responses to stimuli; and (ii) sensitivity of the functional connectivity to activity, allowing for selection of adaptive responses. These universals can now be fully realized in ex-vivo developing neuronal networks due to advances in multi-electrode recording techniques and desktop computing. Applied to the study of ex-vivo networks of neurons, these approaches provide a unique view into learning and memory in networks, over a wide range of spatio-temporal scales. In this review, we summarize experimental data obtained from large random developing ex-vivo cortical networks. We describe how these networks are prepared, their structure, stages of functional development, and the forms of spontaneous activity they exhibit (Sections 2–4). In Section 5 we describe studies that seek to characterize the rules of activity-dependent changes in neural ensembles and their relation to monosynaptic rules. In Section 6, we demonstrate that it is possible to embed functionality into ex-vivo networks, that is, to teach them to perform desired firing patterns in both time and space. This requires ‘closing a loop’ between the network and the environment. Section 7 emphasizes the potential of ex-vivo developing cortical networks in the study of neural learning and memory universals. This may be achieved by combining closed loop experiments and ensemble-defined rules of activity-dependent change.

Copyright
Corresponding author
Author to whom correspondence should be addressed.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Quarterly Reviews of Biophysics
  • ISSN: 0033-5835
  • EISSN: 1469-8994
  • URL: /core/journals/quarterly-reviews-of-biophysics
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
×