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Meszena, D.

Publications and source records attributed to Meszena, D..

7 recordsLinked to original sources

Thermoplastic polyurethane as a base material for soft, high-density neural interfaces

Polymers used as substrate and encapsulation for implantable devices are typically deposited layer-by-layer, leaving polymer-polymer interfaces that adhere poorly and become a critical failure point. Thermoplastic polyurethane (TPU) elastomers combine four properties not found together in any other candidate: decades of clinical use in long-term implants and availability in medical grade, a stiffness well below that of polyimide and parylene C, compatibility with microfabrication, and thermoplastic self-fusion, which removes the polymer-polymer interface entirely. This work introduces TPU as a base material for soft, high-density neural interfaces and demonstrates one route to realizing them. Gold is patterned on a sacrificial copper sheet by maskless lithography and transferred into TPU by vacuum lamination, giving conformally coated tracks down to 15 um at 30 um pitch within a single, merged polymer body. An additional electroplating step produces a nanostructured pinecone gold surface that increases the electrochemically active area of the electrodes, approximately doubling the charge injection capacity. Daisy-chain silicon chips were also embedded within the soft polymer body. The films transmit up to 88% at 470 nm, a wavelength commonly used for optogenetics. TPU showed no cytotoxicity towards differentiated SH-SY5Y cells and only a mild tissue response after 9.5 months of subcutaneous implantation in rats.

bioengineering↗

Optimal inter-electrode distances for maximizing single unit yield per electrode in neural recordings

State-of-the-art high-density multielectrode arrays enable the recording of simultaneous spiking activity from hundreds of neurons. Although significant efforts have been dedicated to enhancing neural recording devices and developing more efficient sorting algorithms, there has been relatively less focus on the allocation of microelectrodes--a factor that undeniably affects spike sorting effectiveness and ultimately the total number of detected neurons. Here, we systematically examined the relationship between optimal electrode spacing and spike sorting efficiency by creating virtual sparser layouts from high-density recordings through spatial downsampling. We assessed spike sorting performance by comparing the quantity of well-isolated single units per electrode in sparse configurations across various brain regions (neocortex and thalamus) and species (rat, mouse, and human). Enabling the theoretical estimation of optimal electrode arrangements, we complement experimental results with a geometrical modeling framework. Contrary to the general assumption that higher electrode density inherently leads to more efficient sorting, both our theoretical and experimental results reveal a clear optimum for electrode spacing specific to species and regions. We demonstrate that carefully choosing optimal electrode distances could yield a total of 1.7 to 3 times increase in spike sorting efficiency. These findings emphasize the necessity of species- and region-specific microelectrode design optimization.

neuroscience↗

DREDge: robust motion correction for high-density extracellular recordings across species

High-density microelectrode arrays (MEAs) have opened new possibilities for systems neuroscience in human and non-human animals, but brain tissue motion relative to the array poses a challenge for downstream analyses, particularly in human recordings. We introduce DREDge (Decentralized Registration of Electrophysiology Data), a robust algorithm which is well suited for the registration of noisy, nonstationary extracellular electrophysiology recordings. In addition to estimating motion from spikes in the action potential (AP) frequency band, DREDge enables automated tracking of motion at high temporal resolution in the local field potential (LFP) frequency band. In human intraoperative recordings, which often feature fast (period <1s) motion, DREDge correction in the LFP band enabled reliable recovery of evoked potentials, and significantly reduced single-unit spike shape variability and spike sorting error. Applying DREDge to recordings made during deep probe insertions in nonhuman primates demonstrated the possibility of tracking probe motion of centimeters across several brain regions while simultaneously mapping single unit electrophysiological features. DREDge reliably delivered improved motion correction in acute mouse recordings, especially in those made with an recent ultra-high density probe. We also implemented a procedure for applying DREDge to recordings made across tens of days in chronic implantations in mice, reliably yielding stable motion tracking despite changes in neural activity across experimental sessions. Together, these advances enable automated, scalable registration of electrophysiological data across multiple species, probe types, and drift cases, providing a stable foundation for downstream scientific analyses of these rich datasets.

neuroscience↗

Robust online multiband drift estimation in electrophysiology data

High-density electrophysiology probes have opened new possibilities for systems neuroscience in human and non-human animals, but probe motion (or drift) while recording poses a challenge for downstream analyses, particularly in human recordings. Here, we improve on the state of the art for tracking this drift with an algorithm termed DREDge (Decentralized Registration of Electrophysiology Data) with four major contributions. First, we extend previous decentralized methods to exploit multiband information, leveraging the local field potential (LFP), in addition to spikes detected from the action potentials (AP). Second, we show that the LFP-based approach enables registration at sub-second temporal resolution. Third, we introduce an efficient online motion tracking algorithm, allowing the method to scale up to longer and higher spatial resolution recordings, which could facilitate real-time applications. Finally, we improve the robustness of the approach by accounting for the nonstationarities that occur in real data and by automating parameter selection. Together, these advances enable fully automated scalable registration of challenging datasets from both humans and mice.

neuroscience↗

Recording site placement on planar silicon-based probes affects neural signal quality: edge sites enhance acute recording performance

ObjectiveMultisite, silicon-based probes are widely used tools to record the electrical activity of neuronal populations. Several physical features of these devices (e.g. shank thickness, tip geometry) are designed to improve their recording performance. Here, our goal was to investigate whether the position of recording sites on the silicon shank might affect the quality of the recorded neural signal in acute experiments. ApproachNeural recordings obtained with five different types of high-density, single-shank, planar silicon probes from anesthetized rats were analyzed. Wideband data were filtered (500 - 5000 Hz) to extract spiking activity, then various quantitative properties (e.g. amplitude distribution of the filtered potential, single unit yield) of the recorded cortical and thalamic activity were compared between sites located at different positions of the silicon shank, focusing particularly on edge and center sites. Main resultsEdge sites outperformed center sites: mean values of the examined properties of the spiking activity were in most cases higher for edge sites (~94%, 33/35) and a large fraction of these differences were also statistically significant (~45%, 15/33) with effect sizes ranging from small to large. Although the single unit yield was similar between site positions, the difference in signal quality was remarkable in the range corresponding to high-amplitude spikes. Furthermore, the advantage of edge sites slightly decreased for probes having a narrower shank. SignificanceThe better signal quality on edge sites might be the result of the reduced shielding effect of the silicon shank providing a larger field of view for edge sites to detect spikes, or the less tissue damage caused near the edges of the shank. Our results might aid the design of novel neural implants in enhancing their recording performance by identifying more efficient recording site placements.

neuroscience↗

Why not record from every channel with a CMOS scanning probe?

It is an uninformative truism to state that the brain operates at multiple spatial and temporal scales, each with each own set of emergent phenomena. More worthy of attention is the point that our current understanding of it cannot clearly indicate which of these phenomenological scales are the significant contributors to the brains function and primary output (i.e. behaviour). Apart from the sheer complexity of the problem, a major contributing factor to this state of affairs is the lack of instrumentation that can simultaneously address these multiple scales without causing function altering damages to the underlying tissue. One important facet of this problem is that standard neural recording devices normally require one output connection per electrode. This limits the number of electrodes that can fit along the thin shafts of implantable probes generating a limiting balance between density and spread. Sharing a single output connection between multiple electrodes relaxes this constraint and permits designs of ultra-high density probes. Here we report the design and in-vivo validation of such a device, a complementary metal-oxide-semiconductor (CMOS) scanning probe with 1344 electrodes; the outcome of the European research project NeuroSeeker. We show that this design targets both local and global spatial scales by allowing the simultaneous recording of more than 1000 neurons spanning 7 functional regions with a single shaft. The neurons show similar recording longevity and signal to noise ratio to passive probes of comparable size and no adverse effects in awake or anesthetized animals. Addressing the data management of this device we also present novel visualization and monitoring methods. Using the probe with freely moving animals we show how accessing a number of cortical and subcortical brain regions offers a novel perspective on how the brain operates around salient behavioural events. Finally, we compare this probe with lower density, non CMOS designs (which have to adhere to the one electrode per output line rule). We show that an increase in density results in capturing neural firing patterns, undetectable by lower density devices, which correlate to self-similar structures inherent in complex naturalistic behaviour. To help design electrode configurations for future, even higher density, CMOS probes, recordings from many different brain regions were obtained with an ultra-dense passive probe.

neuroscience↗

Revealing The Distribution Of Transmembrane Currents Along The Dendritic Tree Of A Neuron With Known Morphology From Extracellular Recordings

Revealing the membrane current source distribution of neurons is a key step on the way to understanding neural computations, however, the experimental and theoretical tools to achieve sufficient spatiotemporal resolution for the estimation remain to be established. Here we address this problem using extracellularly recorded potentials with arbitrarily distributed electrodes in a neuron of known morphology. We use simulations of models with varying complexity to validate the proposed method and to give recommendations for experimental applications. The method is applied to in vitro data from rat hippocampus.

neuroscience↗