Nanofabricated high turn-density spiral coils for on-chip electromagneto-optical conversion.

Circuit-integrated electromagnets are fundamental building blocks for on-chip signal transduction, modulation, and tunability, with specific applications in environmental and biomedical micromagnetometry. A primary challenge for improving performance is pushing quality limitations while minimizing size and fabrication complexity and retaining spatial capabilities. Recent efforts have exploited highly involved three-dimensional synthesis, advanced insulation, and exotic material compositions. Here, we present a rapid nanofabrication process that employs electron beam dose control for high-turn-density diamond-embedded flat spiral coils; these coils achieve efficient on-chip electromagnetic-to-optical signal conversion. Our fabrication process relies on fast 12.3 s direct writing on standard poly(methyl methacrylate) as a basis for the metal lift-off process. Prototypes with 70 micrometer overall diameters and 49-470 nm interturn spacings with corresponding inductances of 12.3-12.8 nH are developed. We utilize optical micromagnetometry to demonstrate that magnetic field generation at the center of the structure effectively correlates with finite element modeling predictions. Further designs based on our process can be integrated with photolithography to broadly enable optical magnetic sensing and spin-based computation.

Inference of network connectivity from temporally binned spike trains.

BACKGROUND: Processing neural activity to reconstruct network connectivity is a central focus of neuroscience, yet the spatiotemporal requisites of biological nervous systems are challenging for current neuronal sensing modalities. Consequently, methods that leverage limited data to successfully infer synaptic connections, predict activity at single unit resolution, and decipher their effect on whole systems, can uncover critical information about neural processing. Despite the emergence of powerful methods for inferring connectivity, network reconstruction based on temporally subsampled data remains insufficiently unexplored. NEW METHOD: We infer synaptic weights by processing firing rates within variable time bins for a heterogeneous feed-forward network of excitatory, inhibitory, and unconnected units. We assess classification and optimize model parameters for postsynaptic spike train reconstruction. We test our method on a physiological network of leaky integrate-and-fire neurons displaying bursting patterns and assess prediction of postsynaptic activity from microelectrode array data. RESULTS: Results reveal parameters for improved prediction and performance and suggest that lower resolution data and limited access to neurons can be preferred. COMPARISON WITH EXISTING METHOD(S): Recent computational methods demonstrate highly improved reconstruction of connectivity from networks of parallel spike trains by considering spike lag, time-varying firing rates, and other underlying dynamics. However, these methods insufficiently explore temporal subsampling representative of novel data types. CONCLUSIONS: We provide a framework for reverse engineering neural networks from data with limited temporal quality, describing optimal parameters for each bin size, which can be further improved using non-linear methods and applied to more complicated readouts and connectivity distributions in multiple brain circuits.

Wireless agents for brain recording and stimulation modalities.

New sensors and modulators that interact wirelessly with medical modalities unlock uncharted avenues for in situ brain recording and stimulation. Ongoing miniaturization, material refinement, and sensitization to specific neurophysiological and neurochemical processes are spurring new capabilities that begin to transcend the constraints of traditional bulky and invasive wired probes. Here we survey current state-of-the-art agents across diverse realms of operation and evaluate possibilities depending on size, delivery, specificity and spatiotemporal resolution. We begin by describing implantable and injectable micro- and nano-scale electronic devices operating at or below the radio frequency (RF) regime with simple near field transmission, and continue with more sophisticated devices, nanoparticles and biochemical molecular conjugates acting as dynamic contrast agents in magnetic resonance imaging (MRI), ultrasound (US) transduction and other functional tomographic modalities. We assess the ability of some of these technologies to deliver stimulation and neuromodulation with emerging probes and materials that provide minimally invasive magnetic, electrical, thermal and optogenetic stimulation. These methodologies are transforming the repertoire of readily available technologies paired with compatible imaging systems and hold promise toward broadening the expanse of neurological and neuroscientific diagnostics and therapeutics.

Stimulation-mediated reverse engineering of silent neural networks.

Reconstructing connectivity of neuronal networks from single-cell activity is essential to understanding brain function, but the challenge of deciphering connections from populations of silent neurons has been largely unmet. We demonstrate a protocol for deriving connectivity of simulated silent neuronal networks using stimulation combined with a supervised learning algorithm, which enables inferring connection weights with high fidelity and predicting spike trains at the single-spike and single-cell levels with high accuracy. We apply our method on rat cortical recordings fed through a circuit of heterogeneously connected leaky integrate-and-fire neurons firing at typical lognormal distributions and demonstrate improved performance during stimulation for multiple subpopulations. These testable predictions about the number and protocol of the required stimulations are expected to enhance future efforts for deriving neuronal connectivity and drive new experiments to better understand brain function.NEW & NOTEWORTHY We introduce a new concept for reverse engineering silent neuronal networks using a supervised learning algorithm combined with stimulation. We quantify the performance of the algorithm and the precision of deriving synaptic weights in inhibitory and excitatory subpopulations. We then show that stimulation enables deciphering connectivity of heterogeneous circuits fed with real electrode array recordings, which could extend in the future to deciphering connectivity in broad biological and artificial neural networks.

Wireless in vivo Recording of Cortical Activity by an Ion-Sensitive Field Effect Transistor.

Wireless brain technologies are empowering basic neuroscience and clinical neurology by offering new platforms that minimize invasiveness and refine possibilities during electrophysiological recording and stimulation. Despite their advantages, most systems require on-board power supply and sizeable transmission circuitry, enforcing a lower bound for miniaturization. Designing new minimalistic architectures that can efficiently sense neurophysiological events will open the door to standalone microscale sensors and minimally invasive delivery of multiple sensors. Here we present a circuit for sensing ionic fluctuations in the brain by an ion-sensitive field effect transistor that detunes a single radiofrequency resonator in parallel. We establish sensitivity of the sensor by electromagnetic analysis and quantify response to ionic fluctuations in vitro. We validate this new architecture in vivo during hindpaw stimulation in rodents and verify correlation with local field potential recordings. This new approach can be implemented as an integrated circuit for wireless in situ recording of brain electrophysiology.

Wireless in vivo Recording of Cortical Activity by an Ion-Sensitive Field Effect Transistor.

Wireless brain technologies are empowering basic neuroscience and clinical neurology by offering new platforms that minimize invasiveness and refine possibilities during electrophysiological recording and stimulation. Despite their advantages, most systems require on-board power supply and sizeable transmission circuitry, enforcing a lower bound for miniaturization. Designing new minimalistic architectures that can efficiently sense neurophysiological events will open the door to standalone microscale sensors and minimally invasive delivery of multiple sensors. Here we present a circuit for sensing ionic fluctuations in the brain by an ion-sensitive field effect transistor that detunes a single radiofrequency resonator in parallel. We establish sensitivity of the sensor by electromagnetic analysis and quantify response to ionic fluctuations in vitro . We validate this new architecture in vivo during hindpaw stimulation in rodents and verify correlation with local field potential recordings. This new approach can be implemented as an integrated circuit for wireless in situ recording of brain electrophysiology.

Enhanced magnetic transduction of neuronal activity by nanofabricated inductors quantified via finite element analysis.

Objective.Methods for the detection of neural signals involve a compromise between invasiveness, spatiotemporal resolution, and the number of neurons or brain regions recorded. Electrode-based probes provide excellent response but usually require transcranial wiring and capture activity from limited neuronal populations. Noninvasive methods such as electroencephalography and magnetoencephalography offer fast readouts of field potentials or biomagnetic signals, respectively, but have spatial constraints that prohibit recording from single neurons. A cell-sized device that enhances neurogenic magnetic fields can be used as anin situsensor for magnetic-based modalities and increase the ability to detect diverse signals across multiple brain regions.Approach.We designed and modeled a device capable of forming a tight electromagnetic junction with single neurons, thereby transducing changes in cellular potential to magnetic field perturbations by driving current through a nanofabricated inductor element.Main results.We present detailed quantification of the device performance using realistic finite element simulations with signals and geometries acquired from patch-clamped neuronsin vitroand demonstrate the capability of the device to produce magnetic signals readable via existing modalities. We compare the magnetic output of the device to intrinsic neuronal magnetic fields (NMFs) and show that the transduced magnetic field intensity from a single neuron is more than three-fold higher at its peak (1.62 nT vs 0.51 nT). Importantly, we report on a large spatial enhancement of the transduced magnetic field output within a typical voxel (40 × 40 × 10µm) over 250 times higher than the intrinsic NMF strength (0.64 nT vs 2.5 pT). We use this framework to perform optimizations of device performance based on nanofabrication constraints and material choices.Significance.Our quantifications institute a foundation for synthesizing and applying electromagnetic sensors for detecting brain activity and can serve as a general method for quantifying recording devices at the single cell level.

In silico assessment of electrophysiological neuronal recordings mediated by magnetoelectric nanoparticles.

Magnetoelectric materials hold untapped potential to revolutionize biomedical technologies. Sensing of biophysical processes in the brain is a particularly attractive application, with the prospect of using magnetoelectric nanoparticles (MENPs) as injectable agents for rapid brain-wide modulation and recording. Recent studies have demonstrated wireless brain stimulation in vivo using MENPs synthesized from cobalt ferrite (CFO) cores coated with piezoelectric barium titanate (BTO) shells. CFO-BTO core-shell MENPs have a relatively high magnetoelectric coefficient and have been proposed for direct magnetic particle imaging (MPI) of brain electrophysiology. However, the feasibility of acquiring such readouts has not been demonstrated or methodically quantified. Here we present the results of implementing a strain-based finite element magnetoelectric model of CFO-BTO core-shell MENPs and apply the model to quantify magnetization in response to neural electric fields. We use the model to determine optimal MENPs-mediated electrophysiological readouts both at the single neuron level and for MENPs diffusing in bulk neural tissue for in vivo scenarios. Our results lay the groundwork for MENP recording of electrophysiological signals and provide a broad analytical infrastructure to validate MENPs for biomedical applications.

Image-guided neural activity manipulation with a paramagnetic drug.

Targeted manipulations of neural activity are essential approaches in neuroscience and neurology, but monitoring such procedures in the living brain remains a significant challenge. Here we introduce a paramagnetic analog of the drug muscimol that enables targeted neural inactivation to be performed with feedback from magnetic resonance imaging. We validate pharmacological properties of the compound in vitro, and show that its distribution in vivo reliably predicts perturbations to brain activity.

Wireless resonant circuits for the minimally invasive sensing of biophysical processes in magnetic resonance imaging.

Biological electromagnetic fields arise throughout all tissue depths and types, and correlate with physiological processes and signalling in organs of the body. Most of the methods for monitoring these fields are either highly invasive or spatially coarse. Here, we show that implantable active coil-based transducers that are detectable via magnetic resonance imaging enable the remote sensing of biological fields. These devices consist of inductively coupled resonant circuits that change their properties in response to electrical or photonic cues, thereby modulating the local magnetic resonance imaging signal without the need for onboard power or wired connectivity. We discuss design parameters relevant to the construction of the transducers on millimetre and submillimetre scales, and demonstrate their in vivo functionality for measuring time-resolved bioluminescence in rodent brains. Biophysical sensing via microcircuits that leverage the capabilities of magnetic resonance imaging may enable a wide range of biological and biomedical applications.

Molecular fMRI of Serotonin Transport.

Reuptake of neurotransmitters from the brain interstitium shapes chemical signaling processes and is disrupted in several pathologies. Serotonin reuptake in particular is important for mood regulation and is inhibited by first-line drugs for treatment of depression. Here we introduce a molecular-level fMRI technique for micron-scale mapping of serotonin transport in live animals. Intracranial injection of an MRI-detectable serotonin sensor complexed with serotonin, together with serial imaging and compartmental analysis, permits neurotransmitter transport to be quantified as serotonin dissociates from the probe. Application of this strategy to much of the striatum and surrounding areas reveals widespread nonsaturating serotonin removal with maximal rates in the lateral septum. The serotonin reuptake inhibitor fluoxetine selectively suppresses serotonin removal in septal subregions, whereas both fluoxetine and a dopamine transporter blocker depress reuptake in striatum. These results highlight promiscuous pharmacological influences on the serotonergic system and demonstrate the utility of molecular fMRI for characterization of neurochemical dynamics.

Molecular-level functional magnetic resonance imaging of dopaminergic signaling.

We demonstrate a technique for mapping brain activity that combines molecular specificity and spatial coverage using a neurotransmitter sensor detectable by magnetic resonance imaging (MRI). This molecular functional MRI (fMRI) method yielded time-resolved volumetric measurements of dopamine release evoked by reward-related lateral hypothalamic brain stimulation of rats injected with the neurotransmitter sensor. Peak dopamine concentrations and release rates were observed in the anterior nucleus accumbens core. Substantial dopamine transients were also present in more caudal areas. Dopamine-release amplitudes correlated with the rostrocaudal stimulation coordinate, suggesting participation of hypothalamic circuitry in modulating dopamine responses. This work provides a foundation for development and application of quantitative molecular fMRI techniques targeted toward numerous components of neural physiology.

Multi-electrode array technologies for neuroscience and cardiology.

At present, the prime methodology for studying neuronal circuit-connectivity, physiology and pathology under in vitro or in vivo conditions is by using substrate-integrated microelectrode arrays. Although this methodology permits simultaneous, cell-non-invasive, long-term recordings of extracellular field potentials generated by action potentials, it is 'blind' to subthreshold synaptic potentials generated by single cells. On the other hand, intracellular recordings of the full electrophysiological repertoire (subthreshold synaptic potentials, membrane oscillations and action potentials) are, at present, obtained only by sharp or patch microelectrodes. These, however, are limited to single cells at a time and for short durations. Recently a number of laboratories began to merge the advantages of extracellular microelectrode arrays and intracellular microelectrodes. This Review describes the novel approaches, identifying their strengths and limitations from the point of view of the end users--with the intention to help steer the bioengineering efforts towards the needs of brain-circuit research.

On-chip electroporation, membrane repair dynamics and transient in-cell recordings by arrays of gold mushroom-shaped microelectrodes.

This study demonstrates the use of on-chip gold mushroom-shaped microelectrodes (gMµEs) to generate localized electropores in the plasma membrane of adhering cultured neurons and to electrophysiologically monitor the ensuing membrane repair dynamics. Delivery of an alternating voltage pulse (0.5-1 V, 100 Hz, 300 ms) through an extracellularly positioned micrometer-sized gMµE electroporates the patch of plasma membrane facing the microelectrode. The repair dynamics of the electropores were analyzed by continuous monitoring of the neuron transmembrane potential, input resistance (R(in)) and action potential (AP) amplitude with an intracellular microelectrode and a number of neighbouring extracellular gMµEs. Electroporation by a gMµE is associated with local elevation of the free intracellular calcium concentration ([Ca(2+)](i)) around the gMµE. The membrane repair kinetics proceeds as an exponential process interrupted by abrupt recovery steps. These abrupt events are consistent with the "membrane patch model" of membrane repair in which patches of intracellular membrane fuse with the plasma membrane at the site of injury. Membrane electroporation by a single gMµE generates a neuron-gMµE configuration that permits recordings of attenuated intracellular action potentials. We conclude that the use of on-chip cultured neurons via a gMµE configuration provides a unique neuroelectronic interface that enables the selection of individual cells for electroporation, generates a confined electroporated membrane patch, monitors membrane repair dynamics and records attenuated intracellular action potentials.

Long-term, multisite, parallel, in-cell recording and stimulation by an array of extracellular microelectrodes.

Here we report on the development of a novel neuroelectronic interface consisting of an array of noninvasive gold-mushroom-shaped microelectrodes (gMmicroEs) that practically provide intracellular recordings and stimulation of many individual neurons, while the electrodes maintain an extracellular position. The development of this interface allows simultaneous, multisite, long-term recordings of action potentials and subthreshold potentials with matching quality and signal-to-noise ratio of conventional intracellular sharp glass microelectrodes or patch electrodes. We refer to the novel approach as "in-cell recording and stimulation by extracellular electrodes" to differentiate it from the classical intracellular recording and stimulation methods. This novel technique is expected to revolutionize the analysis of neuronal networks in relations to learning, information storage and can be used to develop novel drugs as well as high fidelity neural prosthetics and brain-machine systems.

In-cell recordings by extracellular microelectrodes.

Current extracellular multisite recordings suffer from low signal-to-noise ratio, limiting the monitoring to action potentials, and preclude detection of subthreshold synaptic potentials. Here we report an approach to induce Aplysia californica neurons to actively engulf protruding microelectrodes, providing 'in-cell recordings' of subthreshold synaptic and action potentials with signal-to-noise ratio that matches that of conventional intracellular recordings. Implementation of this approach may open new vistas in neuroscience and biomedical applications.

Changing gears from chemical adhesion of cells to flat substrata toward engulfment of micro-protrusions by active mechanisms.

Microelectrode arrays increasingly serve to extracellularly record in parallel electrical activity from many excitable cells without inflicting damage to the cells by insertion of microelectrodes. Nevertheless, apart from rare cases they suffer from a low signal to noise ratio. The limiting factor for effective electrical coupling is the low seal resistance formed between the plasma membrane and the electronic device. Using transmission electron microscope analysis we recently reported that cultured Aplysia neurons engulf protruding micron size gold spines forming tight apposition which significantly improves the electrical coupling in comparison with flat electrodes (Hai et al 2009 Spine-shaped gold protrusions improve the adherence and electrical coupling of neurons with the surface of micro-electronic devices J. R. Soc. Interface 6 1153-65). However, the use of a transmission electron microscope to measure the extracellular cleft formed between the plasma membrane and the gold-spine surface may be inaccurate as chemical fixation may generate structural artifacts. Using live confocal microscope imaging we report here that cultured Aplysia neurons engulf protruding spine-shaped gold structures functionalized by an RGD-based peptide and to a significantly lesser extent by poly-l-lysine. The cytoskeletal elements actin and associated protein cortactin are shown to organize around the stalks of the engulfed gold spines in the form of rings. Neurons grown on the gold-spine matrix display varying growth patterns but maintain normal electrophysiological properties and form functioning synapses. It is concluded that the matrices of functionalized gold spines provide an improved substrate for the assembly of neuro-electronic hybrids.

Spine-shaped gold protrusions improve the adherence and electrical coupling of neurons with the surface of micro-electronic devices.

Interfacing neurons with micro- and nano-electronic devices has been a subject of intense study over the last decade. One of the major problems in assembling efficient neuro-electronic hybrid systems is the weak electrical coupling between the components. This is mainly attributed to the fundamental property of living cells to form and maintain an extracellular cleft between the plasma membrane and any substrate to which they adhere. This cleft shunts the current generated by propagating action potentials and thus reduces the signal-to-noise ratio. Reducing the cleft thickness, and thereby increasing the seal resistance formed between the neurons and the sensing surface, is thus a challenge and could improve the electrical coupling coefficient. Using electron microscopic analysis and field potential recordings, we examined here the use of gold micro-structures that mimic dendritic spines in their shape and dimensions to improve the adhesion and electrical coupling between neurons and micro-electronic devices. We found that neurons cultured on a gold-spine matrix, functionalized by a cysteine-terminated peptide with a number of RGD repeats, readily engulf the spines, forming tight apposition. The recorded field potentials of cultured Aplysia neurons are significantly larger using gold-spine electrodes in comparison with flat electrodes.

Acetylcholinesterase-ISFET based system for the detection of acetylcholine and acetylcholinesterase inhibitors.

A bioelectronic hybrid system for the detection of acetylcholine esterase (AChE) catalytic activity was assembled by way of immobilizing the enzyme to the gate surface of an ion-sensitive field-effect transistor (ISFET). Photometric methods used to characterize bonded enzyme and linker layers on silicon substrates confirm the existence of a stable amino-cyanurate containing AChE monolayer. The transduction of the enzyme-functionalized ISFET, in ionic solutions, is detected in response to application of acetylcholine (ACh). Recorded sensitivity of the modified ISFET to ACh has reached levels of up to 10(-5)M. The Michaelis-Menten constant of the immobilized AChE is only moderately altered. Nevertheless, the maximum reaction velocity is reduced by over an order of magnitude. The ISFET response time to bath or ionophoretic application of ACh from a micropipette was in the range of a second. The catalytic activity of the immobilized AChE is inhibited in a reversible manner by eserine, a competitive inhibitor of AChE. We conclude that the immobilized enzyme maintains its pharmacological properties, and thus the described bioelectronic hybrid can serve as a detector for reagents that inhibit AChE activity.