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Dive into the research topics where Ian L. Jones is active.

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Featured researches published by Ian L. Jones.


Analytical and Bioanalytical Chemistry | 2011

The potential of microelectrode arrays and microelectronics for biomedical research and diagnostics

Ian L. Jones; Paolo Livi; Marta K. Lewandowska; Michele Fiscella; Branka Roscic; Andreas Hierlemann

Planar microelectrode arrays (MEAs) are devices that can be used in biomedical and basic in vitro research to provide extracellular electrophysiological information about biological systems at high spatial and temporal resolution. Complementary metal oxide semiconductor (CMOS) is a technology with which MEAs can be produced on a microscale featuring high spatial resolution and excellent signal-to-noise characteristics. CMOS MEAs are specialized for the analysis of complete electrogenic cellular networks at the cellular or subcellular level in dissociated cultures, organotypic cultures, and acute tissue slices; they can also function as biosensors to detect biochemical events. Models of disease or the response of cellular networks to pharmacological compounds can be studied in vitro, allowing one to investigate pathologies, such as cardiac arrhythmias, memory impairment due to Alzheimer’s disease, or vision impairment caused by ganglion cell degeneration in the retina.


IEEE Journal of Solid-state Circuits | 2014

A 1024-Channel CMOS Microelectrode Array With 26,400 Electrodes for Recording and Stimulation of Electrogenic Cells In Vitro

Marco Ballini; Jan Müller; Paolo Livi; Yihui Chen; Urs Frey; Alexander Stettler; Amir Shadmani; Vijay Viswam; Ian L. Jones; David Jäckel; Milos Radivojevic; Marta K. Lewandowska; Wei Gong; Michele Fiscella; Douglas J. Bakkum; Flavio Heer; Andreas Hierlemann

To advance our understanding of the functioning of neuronal ensembles, systems are needed to enable simultaneous recording from a large number of individual neurons at high spatiotemporal resolution and good signal-to-noise ratio. Moreover, stimulation capability is highly desirable for investigating, for example, plasticity and learning processes. Here, we present a microelectrode array (MEA) system on a single CMOS die for in vitro recording and stimulation. The system incorporates 26,400 platinum electrodes, fabricated by in-house post-processing, over a large sensing area (3.85 2.10 mm ) with sub-cellular spatial resolution (pitch of 17.5 μm). Owing to an area and power efficient implementation, we were able to integrate 1024 readout channels on chip to record extracellular signals from a user-specified selection of electrodes. These channels feature noise values of 2.4 μV in the action-potential band (300 Hz-10 kHz) and 5.4 μV in the local-field-potential band (1 Hz-300 Hz), and provide programmable gain (up to 78 dB) to accommodate various biological preparations. Amplified and filtered signals are digitized by 10 bit parallel single-slope ADCs at 20 kSamples/s. The system also includes 32 stimulation units, which can elicit neural spikes through either current or voltage pulses. The chip consumes only 75 mW in total, which obviates the need of active cooling even for sensitive cell cultures.


Journal of Neuroscience Methods | 2012

Recording from defined populations of retinal ganglion cells using a high-density CMOS-integrated microelectrode array with real-time switchable electrode selection.

Michele Fiscella; Karl Farrow; Ian L. Jones; David Jäckel; Jan Müller; Urs Frey; Douglas J. Bakkum; Péter Hantz; Botond Roska; Andreas Hierlemann

In order to understand how retinal circuits encode visual scenes, the neural activity of defined populations of retinal ganglion cells (RGCs) has to be investigated. Here we report on a method for stimulating, detecting, and subsequently targeting defined populations of RGCs. The possibility to select a distinct population of RGCs for extracellular recording enables the design of experiments that can increase our understanding of how these neurons extract precise spatio-temporal features from the visual scene, and how the brain interprets retinal signals. We used light stimulation to elicit a response from physiologically distinct types of RGCs and then utilized the dynamic-configurability capabilities of a microelectronics-based high-density microelectrode array (MEA) to record their synchronous action potentials. The layout characteristics of the MEA made it possible to stimulate and record from multiple, highly overlapping RGCs simultaneously without light-induced artifacts. The high-density of electrodes and the high signal-to-noise ratio of the MEA circuitry allowed for recording of the activity of each RGC on 14±7 electrodes. The spatial features of the electrical activity of each RGC greatly facilitated spike sorting. We were thus able to localize, identify and record from defined RGCs within a region of mouse retina. In addition, we stimulated and recorded from genetically modified RGCs to demonstrate the applicability of optogenetic methods, which introduces an additional feature to target a defined cell type. The developed methodologies can likewise be applied to other neuronal preparations including brain slices or cultured neurons.


Frontiers in Neuroscience | 2015

A method for electrophysiological characterization of hamster retinal ganglion cells using a high-density CMOS microelectrode array.

Ian L. Jones; Thomas L. Russell; Karl Farrow; Michele Fiscella; Felix Franke; Jan Müller; David Jäckel; Andreas Hierlemann

Knowledge of neuronal cell types in the mammalian retina is important for the understanding of human retinal disease and the advancement of sight-restoring technology, such as retinal prosthetic devices. A somewhat less utilized animal model for retinal research is the hamster, which has a visual system that is characterized by an area centralis and a wide visual field with a broad binocular component. The hamster retina is optimally suited for recording on the microelectrode array (MEA), because it intrinsically lies flat on the MEA surface and yields robust, large-amplitude signals. However, information in the literature about hamster retinal ganglion cell functional types is scarce. The goal of our work is to develop a method featuring a high-density (HD) complementary metal-oxide-semiconductor (CMOS) MEA technology along with a sequence of standardized visual stimuli in order to categorize ganglion cells in isolated Syrian Hamster (Mesocricetus auratus) retina. Since the HD-MEA is capable of recording at a higher spatial resolution than most MEA systems (17.5 μm electrode pitch), we were able to record from a large proportion of RGCs within a selected region. Secondly, we chose our stimuli so that they could be run during the experiment without intervention or computation steps. The visual stimulus set was designed to activate the receptive fields of most ganglion cells in parallel and to incorporate various visual features to which different cell types respond uniquely. Based on the ganglion cell responses, basic cell properties were determined: direction selectivity, speed tuning, width tuning, transience, and latency. These properties were clustered to identify ganglion cell types in the hamster retina. Ultimately, we recorded up to a cell density of 2780 cells/mm2 at 2 mm (42°) from the optic nerve head. Using five parameters extracted from the responses to visual stimuli, we obtained seven ganglion cell types.


international conference on solid-state sensors, actuators and microsystems | 2011

Recording of neural activity of mouse retinal ganglion cells by means of an integrated high-density microelectrode array

Ian L. Jones; Michele Fiscella; Urs Frey; David Jäckel; Jan Müller; B. Roscic; R. Streichan; Andreas Hierlemann

The retina is responsible for the processing and encoding of visual stimuli into neural spike trains. The output module of the retina is composed of a single layer of retinal ganglion cells (RGCs) that transmit the encoded information to higher centers in the brain. Using a high-density complementary metal-oxide-semiconductor (CMOS)-based microelectrode array (MEA) to scan the RGC layer, we have shown that it is possible to record and sort the spikes produced by selected RGCs. This technique provides a high spatio-temporal-resolution readout of the neural circuitry and function of the retina.


Lab on a Chip | 2015

High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels

Jan Müller; Marco Ballini; Paolo Livi; Yihui Chen; Milos Radivojevic; Amir Shadmani; Vijay Viswam; Ian L. Jones; Michele Fiscella; Roland Diggelmann; Alexander Stettler; Urs Frey; Douglas J. Bakkum; Andreas Hierlemann


symposium on vlsi circuits | 2013

A 1024-channel CMOS microelectrode-array system with 26'400 electrodes for recording and stimulation of electro-active cells in-vitro

Marco Ballini; Jan Müller; Paolo Livi; Yihui Chen; Urs Frey; Amir Shadmani; Ian L. Jones; Wei Gong; Michele Fiscella; Milos Radivojevic; Douglas J. Bakkum; Alexander Stettler; Flavio Heer; Andreas Hierlemann


international conference on solid state sensors actuators and microsystems | 2013

Conferring flexibility and reconfigurability to a 26,400 microelectrode CMOS array for high throughput neural recordings

Johannes Muller; Marco Ballini; Paolo Livi; Yuanfeng Chen; Amir Shadmani; Urs Frey; Ian L. Jones; Michele Fiscella; Milos Radivojevic; Douglas J. Bakkum; Alexander Stettler; Flavio Heer; Andreas Hierlemann


Conference Proceedings of the 8th International Meeting on Substrate-Integrated Microelectrode Arrays | 2012

Targeting defined populations of retinal ganglion cells with CMOS microelectrode arrays

Michele Fiscella; Karl Farrow; Ian L. Jones; David Jäckel; Jan Müller; Urs Frey; Douglas J. Bakkum; Botond Roska; Andreas Hierlemann


Conference Proceedings of the 8th International Meeting on Substrate-Integrated Microelectrode Arrays | 2012

Light response patterns in silenced rd1 mouse retinal ganglion cells

Kosmas Deligkaris; Jun Kaneko; Michele Fiscella; Jan Müller; Ian L. Jones; Andreas Hierlemann; Masayo Takahashi; Urs Frey

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