Why not record from every channel with a CMOS scanning probe? Dimitriadis*, G., Neto, J. P., Aarts, A., Alexandru, A., Ballini, M., Battaglia, F., … Kampff, A. R. (2018). biorxiv

Recording from the same neuron with high-density CMOS probes and patch-clamp: a ground-truth dataset and an experiment in collaboration. Marques-Smith, A., Neto, J. P., Lopes, G., Nogueira, J., Calcaterra, L., Frazão, J., … Kampff, A. (2018). biorxiv


Transparent and Flexible Electrocorticography Electrode Arrays Based on Silver Nanowire Networks for Neural Recordings. Neto, J. P., Costa, A., Pinto, J. V., Marques-Smith, A., Costa, J., Martins, R., … Barquinha, P. (2021). ACS Applied Nano Materials,4 (6), 5737-5747.

Validating silicon polytrodes with paired juxtacellular recordings: method and dataset. Neto, J. P., Lopes, G., Frazão, J., Nogueira, J., Lacerda, P., Baião, P., … Kampff, A. R. (2016). Journal of Neurophysiology, 116(2), 892–903.

Does impedance matter when recording spikes with polytrodes? Neto, J. P., Baião, P., Lopes, G., Frazão, J., Nogueira, J., Fortunato, E., … Kampff, A. R. (2018). Frontiers in Neuroscience, 12, 715.

t-SNE Visualization of Large-Scale Neural Recordings. Dimitriadis*, G., Neto, J. P., & Kampff, A. R. (2018). Neural Computation, 1–25.

Bonsai: an event-based framework for processing and controlling data streams. Lopes, G., Bonacchi, N., Frazão, J., Neto, J. P., Atallah, B. V, Soares, S., … Kampff, A. R. (2015). Frontiers in Neuroinformatics, 9, 7.

Electrodeposition of WO3 Nanoparticles for Sensing Applications. Santos, L., Neto, J. P., Crespo, A., Baião, P., Barquinha, P., Pereira, L., … Fortunato, E. (2015). In Electroplating of Nanostructures. InTech.

WO 3 Nanoparticle-Based Conformable pH Sensor. Santos*, L., Neto, J. P., Crespo, A., Nunes, D., Costa, N., Fonseca, I. M., … Fortunato, E. (2014).
ACS Applied Materials & Interfaces, 6(15), 12226–12234.

Synthesis of WO3 nanoparticles for biosensing applications. Santos, L., Silveira, C. M., Elangovan, E., Neto, J. P., Nunes, D., Pereira, L., … Fortunato, E. (2016).
Sensors and Actuators B: Chemical, 223, 186–194.

*co-first authors


CMOS scanning probe

Widely used technology for fabricating modern devices, the CMOS technology, was used to fabricate a neural probe with 1344 electrodes arranged along 8 mm of a thin shaft. In vivo recordings with the highest density and number of electrodes ever achieved in the history of neuroscience are now available here

Polytrode impedance

To help resolve whether the impedance of an electrode matters for recording neural activity with a modern silicon probe, we collected a dataset in which neighboring electrodes within a dense array had a 10-fold difference in impedance. These recordings allow direct comparison of the same neural signal measured with a low and high impedance electrode. The dataset, as well as basic analysis scripts, can be downloaded here and here

Ultra Dense Extracellular Survey

CMOS technology allows the fabrication of electrodes with sub-cellular dimensions, smaller than a neuron’s soma (< 10 µm). How small and closely-packed must one make extracellular electrodes? Does the optimal size and density of electrodes depend on the brain region recorded? To help address these questions, we collected a survey of recordings from different brain areas using an ultra-high density array of small extracellular electrodes (5 µm electrodes packed into a 17x15 array). The survey data is available here or here

Validating electrodes

“Ground-Truth” data from silicon polytrodes (32 and 128 electrodes). To gather validation data, for which we know when a neuron nearby the extracellular probe is active, we developed a technique for “paired recordings”. We use high accuracy, optically-calibrated mechanical manipulators to position two probes, the extracellular device and a glass micro-pipette capable of isolating a single neuron, at the same location in the brain. The signals recorded with both probes can then be used to cross-validate one another. The pipette (juxtacellular) recording tells us exactly when one neuron is active and the challenge is to detect and isolate (i.e. “sort”) this neuron’s signal from all of the others seen by the extracellular polytrode. A summary of the current is available here or here. Moreover, the most recent “Ground-Truth” dataset using Neuropixel probes is also available here