@article{MTMT:30322282,
	title = {Slow insertion of silicon probes improves the quality of acute neuronal recordings},
	url = {https://m2.mtmt.hu/api/publication/30322282},
	author = {Fiáth, Richárd and Márton, AL and Mátyás, Ferenc and Pinke, Domonkos Péter and Márton, Gergely and Tóth, Kinga and Ulbert, István},
	doi = {10.1038/s41598-018-36816-z},
	journal-iso = {SCI REP},
	journal = {SCIENTIFIC REPORTS},
	volume = {9},
	unique-id = {30322282},
	year = {2019},
	eissn = {2045-2322},
	orcid-numbers = {Fiáth, Richárd/0000-0001-8732-2691; Mátyás, Ferenc/0000-0002-3903-8896; Tóth, Kinga/0000-0002-8751-8499; Ulbert, István/0000-0001-9941-9159}
}

@article{MTMT:3326632,
	title = {A silicon-based neural probe with densely-packed low-impedance titanium nitride microelectrodes for ultrahigh-resolution in vivo recordings},
	url = {https://m2.mtmt.hu/api/publication/3326632},
	author = {Fiáth, Richárd and Raducanu, BC and Musa, S and Andrei, A and Lopez, CM and van Hoof, C and Ruther, P and Aarts, A and Horváth, Domonkos and Ulbert, István},
	doi = {10.1016/j.bios.2018.01.060},
	journal-iso = {BIOSENS BIOELECTRON},
	journal = {BIOSENSORS & BIOELECTRONICS},
	volume = {106},
	unique-id = {3326632},
	issn = {0956-5663},
	abstract = {In this study, we developed and validated a single-shank silicon-based neural probe with 128 closely-packed microelectrodes suitable for high-resolution extracellular recordings. The 8-mm-long, 100-mu m-wide and 50-mu m-thick implantable shank of the probe fabricated using a 013-mu m complementary metal-oxide-semiconductor (CMOS) metallization technology contains square-shaped (20 x 20 mu m(2)), low-impedance (similar to 50 k Omega at 1 kHz) recording sites made of rough and porous titanium nitride which are arranged in a 32 x 4 dense array with an inter-electrode pitch of 22.5 mu m. The electrophysiological performance of the probe was tested in in vivo experiments by implanting it acutely into neocortical areas of anesthetized animals (rats, mice and cats). We recorded local field potentials, single- and multi-unit activity with superior quality from all layers of the neocortex of the three animal models, even after reusing the probe in multiple (> 10) experiments. The low-impedance electrodes monitored spiking activity with high signal-to-noise ratio; the peak-to-peak amplitude of extracellularly recorded action potentials of well-separable neurons ranged from 0.1 mV up to 1.1 mV. The high spatial sampling of neuronal activity made it possible to detect action potentials of the same neuron on multiple, adjacent recording sites, allowing a more reliable single unit isolation and the investigation of the spatio-temporal dynamics of extracellular action potential waveforms in greater detail. Moreover, the probe was developed with the specific goal to use it as a tool for the validation of electrophysiological data recorded with high-channel-count, high-density neural probes comprising integrated CMOS circuitry.},
	keywords = {Multi-unit activity; neocortex, single-unit activity; high-density neural recording; CMOS metallization technology; action potential waveform},
	year = {2018},
	eissn = {1873-4235},
	pages = {86-92},
	orcid-numbers = {Fiáth, Richárd/0000-0001-8732-2691; Horváth, Domonkos/0000-0001-7310-2890; Ulbert, István/0000-0001-9941-9159}
}

@article{MTMT:3010856,
	title = {A Multimodal, SU-8-Platinum - Polyimide Microelectrode Array for Chronic In Vivo Neurophysiology},
	url = {https://m2.mtmt.hu/api/publication/3010856},
	author = {Márton, Gergely and Orbán, Gábor and Kiss, Marcell and Fiáth, Richárd and Pongrácz, Anita and Ulbert, István},
	doi = {10.1371/journal.pone.0145307},
	journal-iso = {PLOS ONE},
	journal = {PLOS ONE},
	volume = {10},
	unique-id = {3010856},
	issn = {1932-6203},
	year = {2015},
	eissn = {1932-6203},
	orcid-numbers = {Orbán, Gábor/0000-0002-8513-626X; Fiáth, Richárd/0000-0001-8732-2691; Pongrácz, Anita/0000-0001-6793-8739; Ulbert, István/0000-0001-9941-9159}
}

@article{MTMT:1960292,
	title = {Unsupervised spike detection and sorting with wavelets and superparamagnetic clustering},
	url = {https://m2.mtmt.hu/api/publication/1960292},
	author = {Quiroga, RQ and Nádasdy, Zoltán and Ben-Shaul, Y},
	doi = {10.1162/089976604774201631},
	journal-iso = {NEURAL COMPUT},
	journal = {NEURAL COMPUTATION},
	volume = {16},
	unique-id = {1960292},
	issn = {0899-7667},
	abstract = {This study introduces a new method for detecting and sorting spikes from multiunit recordings. The method combines the wavelet transform, which localizes distinctive spike features, with superparamagnetic clustering, which allows automatic classification of the data without assumptions such as low variance or gaussian distributions. Moreover, an improved method for setting amplitude thresholds for spike detection is proposed. We describe several criteria for implementation that render the algorithm unsupervised and fast. The algorithm is compared to other conventional methods using several simulated data sets whose characteristics closely resemble those of in vivo recordings. For these data sets, we found that the proposed algorithm outperformed conventional methods.},
	keywords = {Neurons/*physiology; Action Potentials/*physiology; computer simulation; Algorithms; *Models, Neurological},
	year = {2004},
	eissn = {1530-888X},
	pages = {1661-1687},
	orcid-numbers = {Nádasdy, Zoltán/0000-0002-6515-9683}
}