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Active High-Density Electrode Arrays: Technology and Applications in Neuronal Cell Cultures. ADVANCES IN NEUROBIOLOGY 2019. [PMID: 31073940 DOI: 10.1007/978-3-030-11135-9_11] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/02/2023]
Abstract
Active high-density electrode arrays realized with complementary metal-oxide-semiconductor (CMOS) technology provide electrophysiological recordings from several thousands of closely spaced microelectrodes. This has drastically advanced the spatiotemporal recording resolution of conventional multielectrode arrays (MEAs). Thus, today's electrophysiology in neuronal cultures can exploit label-free electrical readouts from a large number of single neurons within the same network. This provides advanced capabilities to investigate the properties of self-assembling neuronal networks, to advance studies on neurotoxicity and neurodevelopmental alterations associated with human brain diseases, and to develop cell culture models for testing drug- or cell-based strategies for therapies.Here, after introducing the reader to this neurotechnology, we summarize the results of different recent studies demonstrating the potential of active high-density electrode arrays for experimental applications. We also discuss ongoing and possible future research directions that might allow for moving these platforms forward for screening applications.
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Nieus T, D'Andrea V, Amin H, Di Marco S, Safaai H, Maccione A, Berdondini L, Panzeri S. State-dependent representation of stimulus-evoked activity in high-density recordings of neural cultures. Sci Rep 2018; 8:5578. [PMID: 29615719 PMCID: PMC5882875 DOI: 10.1038/s41598-018-23853-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2018] [Accepted: 03/21/2018] [Indexed: 01/01/2023] Open
Abstract
Neuronal responses to external stimuli vary from trial to trial partly because they depend on continuous spontaneous variations of the state of neural circuits, reflected in variations of ongoing activity prior to stimulus presentation. Understanding how post-stimulus responses relate to the pre-stimulus spontaneous activity is thus important to understand how state dependence affects information processing and neural coding, and how state variations can be discounted to better decode single-trial neural responses. Here we exploited high-resolution CMOS electrode arrays to record simultaneously from thousands of electrodes in in-vitro cultures stimulated at specific sites. We used information-theoretic analyses to study how ongoing activity affects the information that neuronal responses carry about the location of the stimuli. We found that responses exhibited state dependence on the time between the last spontaneous burst and the stimulus presentation and that the dependence could be described with a linear model. Importantly, we found that a small number of selected neurons carry most of the stimulus information and contribute to the state-dependent information gain. This suggests that a major value of large-scale recording is that it individuates the small subset of neurons that carry most information and that benefit the most from knowledge of its state dependence.
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Affiliation(s)
- Thierry Nieus
- NetS3 Laboratory, Neuroscience and Brain Technologies Department, Istituto Italiano di Tecnologia, Genova, Italy. .,Department of Biomedical and Clinical Sciences "Luigi Sacco", Università di Milano, Milano, Italy.
| | - Valeria D'Andrea
- Neural Computation Laboratory, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - Hayder Amin
- NetS3 Laboratory, Neuroscience and Brain Technologies Department, Istituto Italiano di Tecnologia, Genova, Italy
| | - Stefano Di Marco
- NetS3 Laboratory, Neuroscience and Brain Technologies Department, Istituto Italiano di Tecnologia, Genova, Italy.,Scienze cliniche applicate e biotecnologiche, Università dell'Aquila, L'Aquila, Italy
| | - Houman Safaai
- Neural Computation Laboratory, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy.,Department of Neurobiology, Harvard Medical School, 02115, Boston, Massachusetts, USA
| | - Alessandro Maccione
- NetS3 Laboratory, Neuroscience and Brain Technologies Department, Istituto Italiano di Tecnologia, Genova, Italy
| | - Luca Berdondini
- NetS3 Laboratory, Neuroscience and Brain Technologies Department, Istituto Italiano di Tecnologia, Genova, Italy
| | - Stefano Panzeri
- Neural Computation Laboratory, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy.
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