Mauro Gandolfo
Istituto Italiano di Tecnologia
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Featured researches published by Mauro Gandolfo.
Journal of Neuroscience Methods | 2009
Alessandro Maccione; Mauro Gandolfo; Paolo Massobrio; Antonio Novellino; Sergio Martinoia; Michela Chiappalone
The spike represents the fundamental bit of information transmitted by the neurons within a network in order to communicate. Then, given the importance of the spike rate as well as the spike time for coding the activity generated at the level of a cell assembly, a relevant issue in extracellular electrophysiology is the correct identification of the spike in multisite recordings from brain areas or neuronal networks. In this paper, we present a novel spike detection algorithm, named Precise Timing Spike Detection (PTSD), aimed at (i) reducing the number of false positives and false negatives, in order to optimize the rate code, and (ii) improving the time precision of the identified spike, in order to optimize the spike timing. The PTSD algorithm considers consecutive portions of the signal and looks for the Relative Maximum/Minimum whose peak-to-peak amplitude is above a defined differential threshold and responds to specific requirements. To validate the algorithm, the presented spike detection has been compared with other methods either commercially available or proposed in the literature by using two benchmarking procedures: (i) visual inspection by a group of experts of a portion of signal recorded from a rat cortical culture and (ii) detection of the spikes generated by a realistic neuronal network model. In both cases our algorithm produced the best performances in terms of efficiency and precision. The ROC curve analysis further proved that the best results are reached by the application of the PTSD.
The Journal of Physiology | 2014
Alessandro Maccione; Matthias H. Hennig; Mauro Gandolfo; Oliver Muthmann; James van Coppenhagen; Stephen J. Eglen; Luca Berdondini; Evelyne Sernagor
Novel pan‐retinal recordings of mouse retinal waves were obtained at near cellular resolution using a large‐scale, high‐density array of 4096 electrodes to investigate changes in wave spatiotemporal properties from postnatal day 2 to eye opening. Early cholinergic waves are large, slow and random, with low cellular recruitment. A developmental shift in GABAA signalling from depolarizing to hyperpolarizing influences the dynamics of cholinergic waves. Glutamatergic waves that occur just before eye opening are focused, faster, denser, non‐random and repetitive. These results provide a new, deeper understanding of developmental changes in retinal spontaneous activity patterns, which will help researchers in the investigation of the role of early retinal activity during wiring of the visual system.
Journal of Neuroscience Methods | 2009
Luca Berdondini; Paolo Massobrio; Michela Chiappalone; Mariateresa Tedesco; Kilian Imfeld; Alessandro Maccione; Mauro Gandolfo; M. Koudelka-Hep; Sergio Martinoia
High-density microelectrode arrays (MEAs) enabled by recent developments of microelectronic circuits (CMOS-MEA) and providing spatial resolutions down to the cellular level open the perspective to access simultaneously local and overall neuronal network activities expressed by in vitro preparations. The short inter-electrode separation results in a gain of information on the micro-circuit neuronal dynamics and signal propagation, but requires the careful evaluation of the time resolution as well as the assessment of possible cross-talk artifacts. In this respect, we have realized and tested Pt high-density (HD)-MEAs featuring four local areas with 10microm inter-electrode spacing and providing a suitable noise level for the assessment of the high-density approach. First, simulated results show how possible artifacts (duplicated spikes) can be theoretically observed on nearby microelectrodes only for very high-shunt resistance values (e.g. R(sh)=50 kOmega generates up to 60% of false positives). This limiting condition is not compatible with typical experimental conditions (i.e. dense but not confluent cultures). Experiments performed on spontaneously active cortical neuronal networks show that spike synchronicity decreases by increasing the time resolution and analysis results show that the detected synchronous spikes on nearby electrodes are likely to be unresolved (in time) fast local propagations. Finally, functional connectivity analysis results show stronger local connections than long connections spread homogeneously over the whole network demonstrating the expected gain in detail provided by the spatial resolution.
Frontiers in Neuroengineering | 2010
Alessandro Maccione; Mauro Gandolfo; Mariateresa Tedesco; Thierry Nieus; Kilian Imfeld; Sergio Martinoia; Luca Berdondini
Based on experiments performed with high-resolution Active Pixel Sensor microelectrode arrays (APS-MEAs) coupled with spontaneously active hippocampal cultures, this work investigates the spatial resolution effects of the neuroelectronic interface on the analysis of the recorded electrophysiological signals. The adopted methodology consists, first, in recording the spontaneous activity at the highest spatial resolution (interelectrode separation of 21 μm) from the whole array of 4096 microelectrodes. Then, the full resolution dataset is spatially downsampled in order to evaluate the effects on raster plot representation, array-wide spike rate (AWSR), mean firing rate (MFR) and mean bursting rate (MBR). Furthermore, the effects of the array-to-network relative position are evaluated by shifting a subset of equally spaced electrodes on the entire recorded area. Results highlight that MFR and MBR are particularly influenced by the spatial resolution provided by the neuroelectronic interface. On high-resolution large MEAs, such analysis better represent the time-based parameterization of the network dynamics. Finally, this work suggest interesting capabilities of high-resolution MEAs for spatial-based analysis in dense and low-dense neuronal preparation for investigating signaling at both local and global neuronal circuitries.
Brain Research Bulletin | 2015
Alessandro Maccione; Mauro Gandolfo; Stefano Zordan; Hayder Amin; Stefano Di Marco; Thierry Nieus; Gian Nicola Angotzi; Luca Berdondini
Deciphering neural network function in health and disease requires recording from many active neurons simultaneously. Developing approaches to increase their numbers is a major neurotechnological challenge. Parallel to recent advances in optical Ca(2+) imaging, an emerging approach consists in adopting complementary-metal-oxide-semiconductor (CMOS) technology to realize MultiElectrode Array (MEA) devices. By implementing signal conditioning and multiplexing circuits, these devices allow nowadays to record from several thousands of single neurons at sub-millisecond temporal resolution. At the same time, these recordings generate very large data streams which become challenging to analyze. Here, at first we shortly review the major approaches developed for data management and analysis for conventional, low-resolution MEAs. We highlight how conventional computational tools cannot be easily up-scaled to very large electrode array recordings, and custom bioinformatics tools are an emerging need in this field. We then introduce a novel approach adapted for the acquisition, compression and analysis of extracellular signals acquired simultaneously from 4096 electrodes with CMOS MEAs. Finally, as a case study, we describe how this novel large scale recording platform was used to record and analyze extracellular spikes from the ganglion cell layer in the wholemount retina at pan-retinal scale following patterned light stimulation.
BMC Neuroscience | 2011
Matthias H. Hennig; Alessandro Maccione; Mauro Gandolfo; Matthew Down; Stephen J. Eglen; Luca Berdondini; Evelyne Sernagor
provide a complete characterisation of the dynamics of retinal waves during the first two postnatal weeks, and present several methods for the analysis of such activity patterns. In the mammalian retina, the earliest waves propagate through gap junctions (Stage I, prenatal in mouse), followed by lateral propagation between cholinergic starburst amacrine cells (Stage II) and finally by activity that depends on glutamatergic synaptic transmission (Stage III). Consistent with an earlier analysis of 60 channel MEA recordings [6], we found that Stage II waves exhibit a high degree of randomness with respect to initiation points, trajectories , sizes and durations. Stage III waves, on the other hand, were significantly faster and they were more restricted spatially, following several clear repetitive, non-random propagation patterns that appear to tile the retina, mostly starting from the periphery and propagating towards the centre. This latter effect can not be identified in recordings with conventional 60 channel MEAs, underscoring the importance of probing and analysing neural circuits at a near-cellular resolution.
Neural Networks | 2010
Luca Leonardo Bologna; Valentina Pasquale; Matteo Garofalo; Mauro Gandolfo; Pieter Laurens Baljon; Alessandro Maccione; Sergio Martinoia; Michela Chiappalone
Journal of Neural Engineering | 2010
Mauro Gandolfo; Alessandro Maccione; Mariateresa Tedesco; Sergio Martinoia; Luca Berdondini
international conference on solid state sensors actuators and microsystems | 2013
Alessandro Maccione; Alessandro Simi; Thierry Nieus; Mauro Gandolfo; Kilian Imfeld; Enrico Ferrea; Evelyne Sernagor; Luca Berdondini
Archive | 2010
Matthias H. Hennig; Evelyne Sernagor; Alessandro Maccione; Mauro Gandolfo; Stephen J. Eglen; Luca Berdondini