Amygdala electrical stimulation for operant conditioning in rat navigation

There have been several attempts to navigate the locomotion of animals by neuromodulation. The most common method is animal training with electrical brain stimulation for directional cues and rewards; the basic principle is to activate dopamine-mediated neural reward pathways such as the medial forebrain bundle (MFB) when the animal correctly follows the external commands. In this study, the amygdala, which is the brain region responsible for fear modulation, was targeted for punishment training. The brain regions of MFB, amygdala, and barrel cortex were electrically stimulated for reward, punishment, and directional cues, respectively. Electrical stimulation was applied to the amygdala of rats when they failed to follow directional commands. First, two different amygdala regions, i.e., basolateral amygdala (BLA) and central amygdala (CeA), were stimulated and compared in terms of behavior responses, success and correction rates for training, and gene expression for learning and memory. Then, the training was performed in three groups: group R (MFB stimulation for reward), group P (BLA stimulation for punishment), and group RP (both MFB and BLA stimulation for reward and punishment). In group P, after the training, RNA sequencing was conducted to detect gene expression and demonstrate the effect of punishment learning. Group P showed higher success rates than group R, and group RP exhibited the most effective locomotion control among the three groups. Gene expression results imply that BLA stimulation can be more effective as a punishment in the learning process than CeA stimulation. We developed a new method to navigate rat locomotion behaviors by applying amygdala stimulation.

Fabrication and validation of flexible neural electrodes based on polyimide tape and gold sheet

This research was conducted to apply polyimide tape, which has the advantages of low price ans strong adhesive strength, to the neural electrode process. In addition, to maximize the low-cost characteristics, a fabrication process based on UV laser patterning rather than a photolithography process was introduced. The fabrication process started by attaching the gold sheet on the conductive double-sided tape without being torn or crushed. Then, the gold sheet and the double-sided tape were patterned together using UV laser. The patterned layer was transferred to the single-side polyimide tape. For insulation layer, electrode site opened single-sided polyimide tape was prepared. Polydimethylsiloxane was used as an adhesion layer, and alignment between electrode sites and opening sites was processed manually. The minimum line width achieved through the proposed fabrication process was approximately 100 μ m, and the sheet resistance of the conductive layer was 0.635 Ω /sq. Measured cathodal charge storage capacity was 0.72 mC/cm2 and impedance at 1 kHz was 4.07 kΩ /cm2. Validation of fabricated electrode was confirmed by conducting 30 days accelerated soak test, flexibility test, adhesion test and ex vivo stimulation test. The novel flexible neural electrodes based on single-sided polyimide tape and UV laser patterned gold sheet was fabricated successfully. Conventional neural electrode fabrication processes based on polyimide substrate has a disadvantages such as long fabrication time, expensive costs, and probability of delamination between layers. However, the novel fabrication process which we introduced can overcome many shortcomings of existing processes, and offers great advantages such as simplicity of fabrication, inexpensiveness, flexibility and long-term reliability.

Pupillometry as a window to detect cognitive aging in the brain

This study investigated whether there are aging-related differences in pupil dilation (pupillometry) while the cognitive load is manipulated using digit- and word-span tasks. A group of 17 younger and 15 cognitively healthy older adults performed digit- and word-span tasks. Each task comprised three levels of cognitive loads with 10 trials for each level. For each task, the recall accuracy and the slope of pupil dilation were calculated and analyzed. The raw signal of measured pupil size was low-pass filtered and interpolated to eliminate blinking artifacts and spike noises. Two-way ANOVA was used for statistical analyses. For the recall accuracy, the significant group differences emerged as the span increases in digit-span (5- vs. 7-digit) and word-span (4- vs. 5-word) tasks, while the group differences were not significant on 3-digit- and 3-word-span tasks with lower cognitive load. In digit-span tasks, there was no aging-related difference in the slope of pupil dilation. However, in word-span tasks, the slope of pupil dilation differed significantly between two groups as cognitive load increased, indicating that older adults presented a higher pupil dilation slope than younger adults especially under the conditions with higher cognitive load. The current study found significant aging effects in the pupil dilations under the more cognitive demanding span tasks when the types of span tasks varied (e.g., digit vs. word). The manipulations successfully elicited differential aging effects, given that the aging effects became most salient under word-span tasks with greater cognitive load especially under the maximum length.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13534-023-00315-6.

Implantable Neural Electrodes Fabrication Based on Perfluoroalkoxyalkane Film

OBJECTIVE

In this paper, the fabrication of perfluoro-alkoxy alkane (PFA) film-based planar neural electrodes was proposed.

METHODS

The fabrication of PFA-based electrodes started with cleaning of PFA film. The argon plasma pretreatment was performed on the PFA film surface and attached to a dummy silicon wafer. Metal layers were deposited and patterned using the standard Micro Electro Mechanical Systems (MEMS) process. Electrode-sites and pads were opened using reactive ion etching (RIE). Lastly, the electrode patterned PFA substrate film was thermally laminated with the other bare PFA film. Electrical-physical evaluation tests were conducted along with in vitro tests, ex vivo tests and soak tests to evaluate the electrode performance and biocompatibility.

RESULTS

The electrical and physical performance of PFA-based electrodes had better performances compared to other biocompatible polymer-based electrodes. Also, the biocompatibility and longevity were verified by cytotoxicity test, elution test, and accelerated life test.

CONCLUSION

The PFA film-based planar neural electrode fabrication was established and evaluated. The PFA based electrodes showed excellent benefits such as long-term reliability, low water absorption rate, and flexibility using the neural electrode.

SIGNIFICANCE

For implantable neural electrodes, hermetic sealing is required for in vivo durability. PFA fulfilled a low water absorption rate with relatively low Young's modulus to increase the longevity and biocompatibility of the devices.

Ultrasound neuromodulation of cultured hippocampal neurons

Ultrasound is becoming an emerging and promising method for neuromodulation due to its advantage of noninvasiveness and its high spatial resolution. However, the underlying principles of ultrasound neuromodulation have not yet been elucidated. We have herein developed a new in vitro setup to study the ultrasonic neuromodulation, and examined various parameters of ultrasound to verify the effective conditions to evoke the neural activity. Neurons were stimulated with 0.5 MHz center frequency ultrasound, and the action potentials were recorded from rat hippocampal neural cells cultured on microelectrode arrays. As the intensity of ultrasound increased, the neuronal activity also increased. There was a notable and significant increase in both the spike rate and the number of bursts at 50% duty cycle, 1 kHz pulse repetition frequency, and the acoustic intensities of 7.6 W/cm2 and 3.8 W/cm2 in terms of spatial-peak pulse-average intensity and spatial-peak temporal-average intensity, respectively. In addition, the impact of ultrasonic neuromodulation was assessed in the presence of a gamma-aminobutyric acid A (GABAA) receptor antagonist to exclude the effect of activated inhibitory neurons. Interestingly, it is noteworthy that the predominant neuromodulatory effects of ultrasound disappeared when the GABAA blocker was introduced, suggesting the potential of ultrasonic stimulation specifically targeting inhibitory neurons. The experimental setup proposed herein could serve as a useful tool for the clarification of the mechanisms underlying the electrophysiological effects of ultrasound.

Liquid Crystal Polymer-Based Miniaturized Fully Implantable Deep Brain Stimulator

A significant challenge in improving the deep brain stimulation (DBS) system is the miniaturization of the device, aiming to integrate both the stimulator and the electrode into a compact unit with a wireless charging capability to reduce invasiveness. We present a miniaturized, fully implantable, and battery-free DBS system designed for rats, using a liquid crystal polymer (LCP), a biocompatible and long-term reliable material. The system integrates the simulator circuit, the receiver coil, and a 20 mm long depth-type microelectrode array in a dome-shaped LCP package that is 13 mm in diameter and 5 mm in height. Wireless powering and control via an inductive link enable device miniaturization, allowing for full implantation and, thus, the free behavior of untethered animals. The eight-channel stimulation electrode array was microfabricated on an LCP substrate to form a multilayered system substrate, which was monolithically encapsulated by a domed LCP lid using a specialized spot-welding process. The device functionality was validated via an in vivo animal experiment using a neuropathic pain model in rats. This experiment demonstrated an increase in the mechanical withdrawal threshold of the rats with microelectrical stimulation delivered using the fully implanted device, highlighting the effectiveness of the system.

Effects of cochlear implantation on cognitive decline in older adults: A systematic review and meta-analysis

Background

Hearing loss has been reported as the most significant modifiable risk factor for dementia, but it is still unknown whether auditory rehabilitation can practically prevent cognitive decline. We aim to systematically analyze the longitudinal effects of auditory rehabilitation via cochlear implants (CIs).

Methods

In this systematic review and meta-analysis, we searched relevant literature published from January 1, 2000 to April 30, 2022, using electronic databases, and selected studies in which CIs were performed mainly on older adults and follow-up assessments were conducted in both domains: speech perception and cognitive function. A random-effects meta-analysis was conducted for each domain and for each timepoint comparison (pre-CI vs. six months post-CI; six months post-CI vs. 12 months post-CI; pre-CI vs. 12 months post-CI), and heterogeneity was assessed using Cochran's Q test.

Findings

Of the 1918 retrieved articles, 20 research papers (648 CI subjects) were included. The results demonstrated that speech perception was rapidly enhanced after CI, whereas cognitive function had different speeds of improvement for different subtypes: executive function steadily improved significantly up to 12 months post-CI (g = 0.281, p < 0.001; g = 0.115, p = 0.003; g = 0.260, p < 0.001 in the order of timepoint comparison); verbal memory was significantly enhanced at six months post-CI and was maintained until 12 months post-CI (g = 0.296, p = 0.002; g = 0.095, p = 0.427; g = 0.401, p < 0.001); non-verbal memory showed no considerable progress at six months post-CI, but significant improvement at 12 months post-CI (g = -0.053, p = 0.723; g = 0.112, p = 0.089; g = 0.214, p = 0.023).

Interpretation

The outcomes demonstrate that auditory rehabilitation via CIs could have a long-term positive impact on cognitive abilities. Given that older adults' cognitive abilities are on the trajectory of progressive decline with age, these results highlight the need to increase the adoption of CIs among this population.

Cortical astrocytes modulate dominance behavior in male mice by regulating synaptic excitatory and inhibitory balance

Social hierarchy is established as an outcome of individual social behaviors, such as dominance behavior during long-term interactions with others. Astrocytes are implicated in optimizing the balance between excitatory and inhibitory (E/I) neuronal activity, which may influence social behavior. However, the contribution of astrocytes in the prefrontal cortex to dominance behavior is unclear. Here we show that dorsomedial prefrontal cortical (dmPFC) astrocytes modulate E/I balance and dominance behavior in adult male mice using in vivo fiber photometry and two-photon microscopy. Optogenetic and chemogenetic activation or inhibition of dmPFC astrocytes show that astrocytes bidirectionally control male mouse dominance behavior, affecting social rank. Dominant and subordinate male mice present distinct prefrontal synaptic E/I balance, regulated by astrocyte activity. Mechanistically, we show that dmPFC astrocytes control cortical E/I balance by simultaneously enhancing presynaptic-excitatory and reducing postsynaptic-inhibitory transmission via astrocyte-derived glutamate and ATP release, respectively. Our findings show how dmPFC astrocyte-neuron communication can be involved in the establishment of social hierarchy in adult male mice.

Fast Reconfigurable Electrode Array Based on Titanium Oxide for Localized Stimulation of Cultured Neural Network

Planar microelectrode arrays have become standard tools for in vitro neural-network analysis. However, these predefined micropatterned devices lack adaptability to target-specific cells within a cultured network. Herein, we fabricated a reconfigurable TiO₂ electrode array with an anatase-brookite bicrystalline polymorphous mesoporous layer. Because of its selective absorption of ultraviolet (UV) light and corresponding photoconductivity, TiO₂ electrode array was identified as a promising tool for high-resolution light-addressing. The TiO₂ film was used as a semitransparent semiconductor with a high R_off/R_on ratio of 10⁵ and a fast response time of 400 ms. In addition, the effect of UV radiation on the resistance of the TiO₂ film over 30 d in an aqueous environment was analyzed, with the film exhibiting high stability. An arbitrary UV pattern was applied to a reconfigurable TiO₂ electrode using a digital micromirror device (DMD), affording highly localized neural stimulation at the single-cell level. The reconfigurable TiO₂ electrode with a patterned indium tin oxide (ITO) substrate enabled the independent connection of up to 60 points with external stimulators and signal recorders. We believe this technique would be helpful for electrophysiological research requiring the analysis of cell and neural-network features using a highly localized neural interface.

Hippocampal astrocytes modulate anxiety-like behavior

Astrocytes can affect animal behavior by regulating tripartite synaptic transmission, yet their influence on affective behavior remains largely unclear. Here we showed that hippocampal astrocyte calcium activity reflects mouse affective state during virtual elevated plus maze test using two-photon calcium imaging in vivo. Furthermore, optogenetic hippocampal astrocyte activation elevating intracellular calcium induced anxiolytic behaviors in astrocyte-specific channelrhodopsin 2 (ChR2) transgenic mice (hGFAP-ChR2 mice). As underlying mechanisms, we found ATP released from the activated hippocampal astrocytes increased excitatory synaptic transmission in dentate gyrus (DG) granule cells, which exerted anxiolytic effects. Our data uncover a role of hippocampal astrocytes in modulating mice anxiety-like behaviors by regulating ATP-mediated synaptic homeostasis in hippocampal DG granule cells. Thus, manipulating hippocampal astrocytes activity can be a therapeutic strategy to treat anxiety.

Co-culture platform for neuron-astrocyte interaction using optogenetic modulation

For decades, the role of glial cells has attracted attention in the neuroscience field. Particularly, although the astrocyte is the most abundant glial cell type, it was believed to function as a passive support cell. However, recent evidence suggests that astrocytes actively release various gliotransmitters and signaling entities that regulate the excitability of pre-and post-synaptic neurons in the brain. In this study, we optimized the ratio of astrocytes and neurons to investigate the interaction between astrocytes and neurons. To this end, postnatal day 0-1 rodent hippocampi were dissociated and cultured. The neuron-astrocyte ratio was monitored for up to 3 weeks after treating the cultures with 0, 1, and 5 µM of cytosine arabinoside (Ara-C) at DIV 2. Subsequently, from postnatal transgenic (TG) mouse expressing ChR2 on astrocytes, hippocampi were cultured on the microelectrode array (MEA) with the desired neuron-astrocyte ratio. The astrocyte was irradiated using a 473 nm blue laser for 30 s in a cycle of 10 Hz and electrophysiological recording was performed to verify the activities of neurons induced by the stimulated astrocytes. Astrocytes and neurons in both co-cultures increased at an identical ratio when treated with 1 µM Ara-C, whereas they decreased significantly when treated with 5 µM Ara-C. Particularly, the laser-stimulated astrocytes induced an increase in the frequency of neuronal activities and lasted after illumination. The proposed co-culture platform is expected to be used in experiments to investigate the network between astrocytes and neurons in vitro.

Development of a miniaturized, reconnectable, and implantable multichannel connector

Objective. Connectors for implantable neural prosthetic systems provide several advantages such as simplification of surgery, safe replacement of implanted devices, and modular design of the implant systems. With the rapid advancement of technologies for neural implants, miniaturized multichannel implantable connectors are also required. In this study, we propose a reconnectable and area-efficient multichannel implantable connector.Approach. A female-to-female adapter was fabricated using the thermal-press bonding of micropatterned liquid crystal polymer films. A bump inside the adapter enabled a reliable electrical connection by increasing the contact pressure between the contact pads of the adapter and the inserted cable. After connection, the adapter is enclosed in a metal case sealed with silicone elastomer packing. With different sizes of the packings, leakage current tests were performed under accelerated conditions to determine the optimal design for long-term reliability. Repeated connection tests were performed to verify the durability and reconnectability of the fabricated connector. The connector was implanted in rats, and the leakage currents were monitored to evaluate the stability of the connectorin vivo. Main results. The fabricated four- and eight-channel implantable connectors, assembled with the metal cases, had a diameter and length of 6 and 17 mm, respectively. Further, the contact resistances of the four- and eight-channel connectors were 53.2 and 75.2 mΩ, respectively. The electrical contact remained stable during repeated connection tests (50 times). The fabricated connectors with packings having 125%, 137%, and 150% volume ratios to the internal space of the metal case failed after 14, 88, and 14 d, respectively, in a 75 °C saline environment. In animal tests with rats, the connector maintained low leakage current levels for up to 92 d.Significance. An implantable and reconnectable multichannel connector was developed and evaluated. The feasibility of the proposed connector was evaluated in terms of electrical and mechanical characteristics as well as sealing performance. The proposed connector is expected to have potential applications in implantable neural prosthetic systems.

Silicon optrode array with monolithically integrated SU-8 waveguide and single LED light source

This paper presents a conventional LED (light emitting diode) and polymer waveguide coupled silicon optrode array. Unique lens design at the waveguide inlet enables a high light coupling efficiency with a single LED light source, and provides small power consumption compatible with a wireless optogenetic neuromodulation system. To increase the light intensity at the waveguide tip, a lensed waveguide is fabricated with epoxy-based photoresist SU-8, which has a plano-convex lens shape at the waveguide inlet to focus the light in the horizontal direction. In addition, a cylindrical lens is assembled in front of the waveguide inlet to focus the source light in the vertical direction. The glass cylindrical lens and SU-8 plano-convex lens increased the light coupling efficiency by 6.7 dB and 6.6 dB, respectively. The fabricated 1×4 array of optrodes is assembled with a single LED with 465 nm wavelength, which produces a light intensity of approximately 2.7 mW/mm2 at the SU-8 waveguide outlet when 50 mA input current is applied to the LED. Each optrode has four recording electrodes at the SU-8 waveguide outlet. The average impedance of the iridium oxide (IrOx) electroplated recording electrodes is 43.6 kΩ. In-vivo experiment at the hippocampus region CA1 and CA2 demonstrated the capability of optical stimulation and neural signal recording through the LED and SU-8 waveguide coupled silicon optrode array.

Aging-Related Dissociation of Spatial and Temporal N400 in Sentence-Level Semantic Processing: Evidence From Source Analyses

Age-related differences in sentence-level lexical-semantic processes have been extensively studied, based on the N400 component of event-related potential (ERP). However, there is still a lack of understanding in this regard at the brain-region level. This study explores aging effects on sentence-level semantic processing by comparing the characteristics of the N400 ERP component and brain engagement patterns within individual N400 time windows for two age groups (16 younger adults aged 24.38 ± 3.88 years and 15 older adults aged 67.00 ± 5.04 years) during sentence processing with different plausibility conditions. Our results demonstrated that the N400 effect according to the plausibility condition occurred in different temporal windows in the two age groups, with a delay in the older group. Moreover, it was identified that there was a distinct difference between the groups in terms of the source location of the condition-dependent N400 effect even though no significant difference was derived in its magnitude itself at the sensor-level. Interestingly, the source analysis results indicated that the two groups involved different functional networks to resolve the same semantic violations: the younger group activated the regions corresponding to the typical lexical-semantic network more, whereas the older group recruited the regions belonging to the multiple-demand network more. The findings of this study could be used as a basis for understanding the aging brain in a linguistic context.

Implantable Optrode Array for Optogenetic Modulation and Electrical Neural Recording

During the last decade, optogenetics has become an essential tool for neuroscience research due to its unrivaled feature of cell-type-specific neuromodulation. There have been several technological advances in light delivery devices. Among them, the combination of optogenetics and electrophysiology provides an opportunity for facilitating optogenetic approaches. In this study, a novel design of an optrode array was proposed for realizing optical modulation and electrophysiological recording. A 4 × 4 optrode array and five-channel recording electrodes were assembled as a disposable part, while a reusable part comprised an LED (light-emitting diode) source and a power line. After the characterization of the intensity of the light delivered at the fiber tips, in vivo animal experiment was performed with transgenic mice expressing channelrhodopsin, showing the effectiveness of optical activation and neural recording.

Ethanol induces persistent potentiation of 5-HT3 receptor-stimulated GABA release at synapses on rat hippocampal CA1 neurons

Several studies have shown that ethanol (EtOH) can enhance the activity of GABAergic synapses via presynaptic mechanisms, including in hippocampal CA1 neurons. The serotonin type 3 receptor (5-HT3-R) has been implicated in the neural actions of ethanol (EtOH) and in modulation of GABA release from presynaptic terminals. In the present study, we investigated EtOH modulation of GABA release induced by 5-HT3-R activation using the mechanically isolated neuron/bouton preparation from the rat CA1 hippocampal subregion. EtOH application before and during exposure to the selective 5-HT3 receptor agonist, m-chlorophenylbiguanide (mCPBG) potentiated the mCPBG-induced increases in the peak frequency and charge transfer of spontaneous GABAergic inhibitory postsynaptic currents. Interestingly, the potentiation was maintained even after EtOH was removed from the preparation. A protein kinase A inhibitor reduced the magnitude of EtOH potentiation. Fluorescent Ca2+ imaging showed that Ca2+ transients in the presynaptic terminals increased during EtOH exposure. These findings indicate that EtOH produces long-lasting potentiation of 5-HT3-induced GABA release by modulating calcium levels, via a process involving cAMP-mediated signaling in presynaptic terminals.

Correction: Ha, Y. et al. Hemispherical Microelectrode Array for Ex Vivo Retinal Neural Recording. Micromachines 2020, 11, 538

The authors would like to make the following changes to the published paper [...].

Hemispherical Microelectrode Array for Ex Vivo Retinal Neural Recording

To investigate the neuronal visual encoding process in the retina, researchers have performed in vitro and ex vivo electrophysiological experiments using animal retinal tissues. The microelectrode array (MEA) has become a key component in retinal experiments because it enables simultaneous neural recording from a population of retinal neurons. However, in most retinal experiments, it is inevitable that the retinal tissue is flattened on the planar MEA, becoming deformed from the original hemispherical shape. During the tissue deforming process, the retina is subjected to mechanical stress, which can induce abnormal physiological conditions. To overcome this problem, in this study, we propose a hemispherical MEA with a curvature that allows retinal tissues to adhere closely to electrodes without tissue deformation. The electrode array is fabricated by stretching a thin, flexible polydimethylsiloxane (PDMS) electrode layer onto a hemispherical substrate. To form micro patterns of electrodes, laser processing is employed instead of conventional thin-film microfabrication processes. The feasibility for neural recording from retinal tissues using this array is shown by conducting ex vivo retinal experiments. We anticipate that the proposed techniques for hemispherical MEAs can be utilized not only for ex vivo retinal studies but also for various flexible electronics.

Multi-wavelength light emitting diode-based disposable optrode array for in vivo optogenetic modulation

We present a light emitting diode (LED)-based optical waveguide array that can optogenetically modulate genetically targeted neurons in the brain. The reusable part of the system consists of control electronics and conventional multi-wavelength LED. The disposable part comprises optical fibers assembled with microlens array fabricated on a silicon die. Both parts can be easily assembled and separated by snap fit structure. Measured light intensity is 3.35 mW/mm² at 469 nm and 0.29 mW/mm² at 590 nm when the applied current is 80 mA. In all the tested conditions, the light-induced temperature rise is under 0.5°C and over 90% of the relative light intensity is maintained at 2 mm-distance from the fiber tips. We further tested the efficiency of the optical array in vivo at 469 nm. When the optical array delivers light stimulation on to the visual cortex of a mouse expressing channelrhodopsin-2, the neural activity is significantly increased. The light-driven neural activity is successfully transformed into a percept of the mouse, showing significant learning of the task detecting the cortical stimulation. Our results demonstrate that the proposed optical array interfaces well with the neural circuits in vivo and the system is applicable to guide animal behaviors.

Brain Microglial Activation in Chronic Pain-Associated Affective Disorder

A growing body of evidence from both clinical and animal studies indicates that chronic neuropathic pain is associated with comorbid affective disorders. Spinal cord microglial activation is involved in nerve injury-induced pain hypersensitivity characterizing neuropathic pain. However, there is a lack of thorough assessments of microglial activation in the brain after nerve injury. In the present study, we characterized microglial activation in brain sub-regions of CX3CR1^GFP/+ mice after chronic constriction injury (CCI) of the sciatic nerve, including observations at delayed time points when affective brain dysfunctions such as depressive-like behaviors typically develop. Mice manifested chronic mechanical hypersensitivity immediately after CCI and developed depressive-like behaviors 8 weeks post-injury. Concurrently, significant increases of soma size and microglial cell number were observed in the medial prefrontal cortex (mPFC), hippocampus, and amygdala 8 weeks post-injury. Transcripts of CD11b, and TNF-α, genes associated with microglial activation or depressive-like behaviors, are correspondingly upregulated in these brain areas. Our results demonstrate that microglia are activated in specific brain sub-regions after CCI at delayed time points and imply that brain microglial activation plays a role in chronic pain-associated affective disorders.

Carbon-Fiber Based Microelectrode Array Embedded with a Biodegradable Silk Support for In Vivo Neural Recording

BACKGROUND

Recently, carbon fibers have been utilized to develop a depth-type microelectrode array for chronic neural recording. Since the diameter of carbon fibers is smaller than the conventional electrodes made of metal wires or microfabricated silicon, the carbon fiber electrodes showed an improved capability for chronic neural recording with less tissue damages. However, the carbon fiber based microelectrodes have a limitation of short insertion depth due to a low stiffness.

METHODS

We proposed a carbon fiber based microelectrode array embedded with a mechanical support structure to facilitate the penetration into the deeper brain. The support is made of biodegradable silk fibroin to reduce the reactive tissue responses. The 4-channel carbon fiber based microelectrode arrays were fabricated and accessed in terms of electrochemical impedance, recording capability for 1-month implantation in rat hippocampi. The electrodes with tungsten supports were fabricated and tested as a control group. Immunohistochemical analysis was performed to identify the reactive glial responses.

RESULTS

The carbon fiber based electrode arrays with silk supports showed about 2-fold impedance increase 2 weeks after implantation while the number of active electrodes decreased simultaneously. However, after 1 month, the electrode impedance decreased back to its initial value and the percentage of active electrodes also increased above 70%. Immunohistochemical staining clearly showed that the electrodes with silk supports induced less reactive glial responses than that with tungsten supports.

CONCLUSION

The proposed carbon fiber based microelectrode array is expected to be used for long-term in vivo neural recording from deep brain regions with the minimized reactive tissue response.

Theoretical Study on Gold-Nanorod-Enhanced Near-Infrared Neural Stimulation

Over the past decade, optical methods have emerged for modulating brain functions as an alternative to electrical stimulation. Among various optical techniques, infrared neural stimulation has been effective via a thermal mechanism enabling focused and noninvasive stimulation without any genetic manipulation, but it results in bulk heating of neural tissue. Recently, it has been shown that neural cells can be activated more efficiently by pulsed near-infrared (NIR) light delivered to gold nanorods (GNRs) near the neural cells. Despite its potential, however, the biophysical mechanism underlying this GNR-enhanced NIR stimulation has not been clearly explained yet. Here, we propose an integrative and quantitative model to elucidate the mechanism by modeling heat generated from interaction between NIR light and GNRs, the temperature-dependent ion channels (transient receptor potential vanilloid 1; TRPV1) in the neuronal membrane, and a heat-induced capacitive current through the membrane. Our results show that NIR pulses induce abrupt temperature elevation near the neuronal membrane and lead to both the TRPV1-channel and capacitive currents. Both current sources synergistically increase the membrane potential and elicit an action potential, and which mechanism is dominant depends on conditions such as the laser pulse duration and TRPV1 channel density. Although the TRPV1 mechanism dominates in most cases we tested, the capacitive current makes a larger contribution when a very short laser pulse is illuminated on neural cells with relatively low TRPV1 channel densities.

Prediction of the Seizure Suppression Effect by Electrical Stimulation via a Computational Modeling Approach

In this paper, we identified factors that can affect seizure suppression via electrical stimulation by an integrative study based on experimental and computational approach. Preferentially, we analyzed the characteristics of seizure-like events (SLEs) using our previous in vitro experimental data. The results were analyzed in two groups classified according to the size of the effective region, in which the SLE was able to be completely suppressed by local stimulation. However, no significant differences were found between these two groups in terms of signal features or propagation characteristics (i.e., propagation delays, frequency spectrum, and phase synchrony). Thus, we further investigated important factors using a computational model that was capable of evaluating specific influences on effective region size. In the proposed model, signal transmission between neurons was based on two different mechanisms: synaptic transmission and the electrical field effect. We were able to induce SLEs having similar characteristics with differentially weighted adjustments for the two transmission methods in various noise environments. Although the SLEs had similar characteristics, their suppression effects differed. First of all, the suppression effect occurred only locally where directly received the stimulation effect in the high noise environment, but it occurred in the entire network in the low noise environment. Interestingly, in the same noise environment, the suppression effect was different depending on SLE propagation mechanism; only a local suppression effect was observed when the influence of the electrical field transmission was very weak, whereas a global effect was observed with a stronger electrical field effect. These results indicate that neuronal activities synchronized by a strong electrical field effect respond more sensitively to partial changes in the entire network. In addition, the proposed model was able to predict that stimulation of a seizure focus region is more effective for suppression. In conclusion, we confirmed the possibility of a computational model as a simulation tool to analyze the efficacy of deep brain stimulation (DBS) and investigated the key factors that determine the size of an effective region in seizure suppression via electrical stimulation.

Low-Affinity Zinc Sensor Showing Fluorescence Responses with Minimal Artifacts

The study of the zinc biology requires molecular probes with proper zinc affinity. We developed a low-affinity zinc probe (HBO-ACR) based on an azacrown ether (ACR) and an 2-(2-hydroxyphenyl)benzoxazole (HBO) fluorophore. This probe design imposed positive charge in the vicinity of a zinc coordination center, which enabled fluorescence turn-on responses to high levels of zinc without being affected by the pH and the presence of other transition-metal ions. Steady-state and transient photophysical investigations suggested that such a high tolerance benefits from orchestrated actions of proton-induced nonradiative and zinc-induced radiative control. The zinc bioimaging utility of HBO-ACR has been fully demonstrated with the use of human pancreas epidermoid carcinoma, PANC-1 cells, and rodent hippocampal neurons from cultures and acute brain slices. The results obtained through our studies established the validity of incorporating positively charged ionophores for the creation of low-affinity probes for the visualization of biometals.

Photothermal activation of astrocyte cells using localized surface plasmon resonance of gold nanorods

Although it has been revealed that astrocytes, generally known as star-shaped glial cells, play critical roles in the functions of central nervous system, there have been few efforts to directly modulate their activities and responses. In this study, an optical stimulation strategy for producing intracellular Ca²⁺ transients of astrocytes is demonstrated using near-infrared (NIR) light and localized surface plasmon resonance. It is presented that NIR stimulation of micro-second duration combined with gold nanorods (GNRs) efficiently produces stronger Ca²⁺ transients of astrocytes, which seems to be associated with a local heat generation by photothermal effects of GNRs. Since the proposed scheme can directly activate astrocytes with a high reliability, it is expected that GNR-mediated NIR stimulation could be utilized to facilitate minimally invasive physiological studies on the astrocyte functions. Photos of intracellular Ca²⁺ transient of astrocytes with membrane-bound GNRs after optical stimulation at 30 s.

25th Annual Computational Neuroscience Meeting: CNS-2016

A1 Functional advantages of cell-type heterogeneity in neural circuits

Tatyana O. Sharpee

A2 Mesoscopic modeling of propagating waves in visual cortex

Alain Destexhe

A3 Dynamics and biomarkers of mental disorders

Mitsuo Kawato

F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons

Vladislav Sekulić, Frances K. Skinner

F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains

Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári

F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks.

Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić

O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators

Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona

O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain

Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi

O3 Modeling auditory stream segregation, build-up and bistability

James Rankin, Pamela Osborn Popp, John Rinzel

O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields

Alejandro Tabas, André Rupp, Emili Balaguer-Ballester

O5 A simple model of retinal response to multi-electrode stimulation

Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin

O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task

Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer

O7 Input-location dependent gain modulation in cerebellar nucleus neurons

Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Nielsen, Volker Steuber

O8 Analytic solution of cable energy function for cortical axons and dendrites

Huiwen Ju, Jiao Yu, Michael L. Hines, Liang Chen, Yuguo Yu

O9 C. elegans interactome: interactive visualization of Caenorhabditis elegans worm neuronal network

Jimin Kim, Will Leahy, Eli Shlizerman

O10 Is the model any good? Objective criteria for computational neuroscience model selection

Justas Birgiolas, Richard C. Gerkin, Sharon M. Crook

O11 Cooperation and competition of gamma oscillation mechanisms

Atthaphon Viriyopase, Raoul-Martin Memmesheimer, Stan Gielen

O12 A discrete structure of the brain waves

Yuri Dabaghian, Justin DeVito, Luca Perotti

O13 Direction-specific silencing of the Drosophila gaze stabilization system

Anmo J. Kim, Lisa M. Fenk, Cheng Lyu, Gaby Maimon

O14 What does the fruit fly think about values? A model of olfactory associative learning

Chang Zhao, Yves Widmer, Simon Sprecher,Walter Senn

O15 Effects of ionic diffusion on power spectra of local field potentials (LFP)

Geir Halnes, Tuomo Mäki-Marttunen, Daniel Keller, Klas H. Pettersen,Ole A. Andreassen, Gaute T. Einevoll

O16 Large-scale cortical models towards understanding relationship between brain structure abnormalities and cognitive deficits

Yasunori Yamada

O17 Spatial coarse-graining the brain: origin of minicolumns

Moira L. Steyn-Ross, D. Alistair Steyn-Ross

O18 Modeling large-scale cortical networks with laminar structure

Jorge F. Mejias, John D. Murray, Henry Kennedy, Xiao-Jing Wang

O19 Information filtering by partial synchronous spikes in a neural population

Alexandra Kruscha, Jan Grewe, Jan Benda, Benjamin Lindner

O20 Decoding context-dependent olfactory valence in Drosophila

Laurent Badel, Kazumi Ohta, Yoshiko Tsuchimoto, Hokto Kazama

P1 Neural network as a scale-free network: the role of a hub

B. Kahng

P2 Hemodynamic responses to emotions and decisions using near-infrared spectroscopy optical imaging

Nicoladie D. Tam

P3 Phase space analysis of hemodynamic responses to intentional movement directions using functional near-infrared spectroscopy (fNIRS) optical imaging technique

Nicoladie D.Tam, Luca Pollonini, George Zouridakis

P4 Modeling jamming avoidance of weakly electric fish

Jaehyun Soh, DaeEun Kim

P5 Synergy and redundancy of retinal ganglion cells in prediction

Minsu Yoo, S. E. Palmer

P6 A neural field model with a third dimension representing cortical depth

Viviana Culmone, Ingo Bojak

P7 Network analysis of a probabilistic connectivity model of the Xenopus tadpole spinal cord

Andrea Ferrario, Robert Merrison-Hort, Roman Borisyuk

P8 The recognition dynamics in the brain

Chang Sub Kim

P9 Multivariate spike train analysis using a positive definite kernel

Taro Tezuka

P10 Synchronization of burst periods may govern slow brain dynamics during general anesthesia

Pangyu Joo

P11 The ionic basis of heterogeneity affects stochastic synchrony

Young-Ah Rho, Shawn D. Burton, G. Bard Ermentrout, Jaeseung Jeong, Nathaniel N. Urban

P12 Circular statistics of noise in spike trains with a periodic component

Petr Marsalek

P14 Representations of directions in EEG-BCI using Gaussian readouts

Hoon-Hee Kim, Seok-hyun Moon, Do-won Lee, Sung-beom Lee, Ji-yong Lee, Jaeseung Jeong

P15 Action selection and reinforcement learning in basal ganglia during reaching movements

Yaroslav I. Molkov, Khaldoun Hamade, Wondimu Teka, William H. Barnett, Taegyo Kim, Sergey Markin, Ilya A. Rybak

P17 Axon guidance: modeling axonal growth in T-Junction assay

Csaba Forro, Harald Dermutz, László Demkó, János Vörös

P19 Transient cell assembly networks encode persistent spatial memories

Yuri Dabaghian, Andrey Babichev

P20 Theory of population coupling and applications to describe high order correlations in large populations of interacting neurons

Haiping Huang

P21 Design of biologically-realistic simulations for motor control

Sergio Verduzco-Flores

P22 Towards understanding the functional impact of the behavioural variability of neurons

Filipa Dos Santos, Peter Andras

P23 Different oscillatory dynamics underlying gamma entrainment deficits in schizophrenia

Christoph Metzner, Achim Schweikard, Bartosz Zurowski

P24 Memory recall and spike frequency adaptation

James P. Roach, Leonard M. Sander, Michal R. Zochowski

P25 Stability of neural networks and memory consolidation preferentially occur near criticality

Quinton M. Skilling, Nicolette Ognjanovski, Sara J. Aton, Michal Zochowski

P26 Stochastic Oscillation in Self-Organized Critical States of Small Systems: Sensitive Resting State in Neural Systems

Sheng-Jun Wang, Guang Ouyang, Jing Guang, Mingsha Zhang, K. Y. Michael Wong, Changsong Zhou

P27 Neurofield: a C++ library for fast simulation of 2D neural field models

Peter A. Robinson, Paula Sanz-Leon, Peter M. Drysdale, Felix Fung, Romesh G. Abeysuriya, Chris J. Rennie, Xuelong Zhao

P28 Action-based grounding: Beyond encoding/decoding in neural code

Yoonsuck Choe, Huei-Fang Yang

P29 Neural computation in a dynamical system with multiple time scales

Yuanyuan Mi, Xiaohan Lin, Si Wu

P30 Maximum entropy models for 3D layouts of orientation selectivity

Joscha Liedtke, Manuel Schottdorf, Fred Wolf

P31 A behavioral assay for probing computations underlying curiosity in rodents

Yoriko Yamamura, Jeffery R. Wickens

P32 Using statistical sampling to balance error function contributions to optimization of conductance-based models

Timothy Rumbell, Julia Ramsey, Amy Reyes, Danel Draguljić, Patrick R. Hof, Jennifer Luebke, Christina M. Weaver

P33 Exploration and implementation of a self-growing and self-organizing neuron network building algorithm

Hu He, Xu Yang, Hailin Ma, Zhiheng Xu, Yuzhe Wang

P34 Disrupted resting state brain network in obese subjects: a data-driven graph theory analysis

Kwangyeol Baek, Laurel S. Morris, Prantik Kundu, Valerie Voon

P35 Dynamics of cooperative excitatory and inhibitory plasticity

Everton J. Agnes, Tim P. Vogels

P36 Frequency-dependent oscillatory signal gating in feed-forward networks of integrate-and-fire neurons

William F. Podlaski, Tim P. Vogels

P37 Phenomenological neural model for adaptation of neurons in area IT

Martin Giese, Pradeep Kuravi, Rufin Vogels

P38 ICGenealogy: towards a common topology of neuronal ion channel function and genealogy in model and experiment

Alexander Seeholzer, William Podlaski, Rajnish Ranjan, Tim Vogels

P39 Temporal input discrimination from the interaction between dynamic synapses and neural subthreshold oscillations

Joaquin J. Torres, Fabiano Baroni, Roberto Latorre, Pablo Varona

P40 Different roles for transient and sustained activity during active visual processing

Bart Gips, Eric Lowet, Mark J. Roberts, Peter de Weerd, Ole Jensen, Jan van der Eerden

P41 Scale-free functional networks of 2D Ising model are highly robust against structural defects: neuroscience implications

Abdorreza Goodarzinick, Mohammad D. Niry, Alireza Valizadeh

P42 High frequency neuron can facilitate propagation of signal in neural networks

Aref Pariz, Shervin S. Parsi, Alireza Valizadeh

P43 Investigating the effect of Alzheimer’s disease related amyloidopathy on gamma oscillations in the CA1 region of the hippocampus

Julia M. Warburton, Lucia Marucci, Francesco Tamagnini, Jon Brown, Krasimira Tsaneva-Atanasova

P44 Long-tailed distributions of inhibitory and excitatory weights in a balanced network with eSTDP and iSTDP

Florence I. Kleberg, Jochen Triesch

P45 Simulation of EMG recording from hand muscle due to TMS of motor cortex

Bahar Moezzi, Nicolangelo Iannella, Natalie Schaworonkow, Lukas Plogmacher, Mitchell R. Goldsworthy, Brenton Hordacre, Mark D. McDonnell, Michael C. Ridding, Jochen Triesch

P46 Structure and dynamics of axon network formed in primary cell culture

Martin Zapotocky, Daniel Smit, Coralie Fouquet, Alain Trembleau

P47 Efficient signal processing and sampling in random networks that generate variability

Sakyasingha Dasgupta, Isao Nishikawa, Kazuyuki Aihara, Taro Toyoizumi

P48 Modeling the effect of riluzole on bursting in respiratory neural networks

Daniel T. Robb, Nick Mellen, Natalia Toporikova

P49 Mapping relaxation training using effective connectivity analysis

Rongxiang Tang, Yi-Yuan Tang

P50 Modeling neuron oscillation of implicit sequence learning

Guangsheng Liang, Seth A. Kiser, James H. Howard, Jr., Yi-Yuan Tang

P51 The role of cerebellar short-term synaptic plasticity in the pathology and medication of downbeat nystagmus

Julia Goncharenko, Neil Davey, Maria Schilstra, Volker Steuber

P52 Nonlinear response of noisy neurons

Sergej O. Voronenko, Benjamin Lindner

P53 Behavioral embedding suggests multiple chaotic dimensions underlie C. elegans locomotion

Tosif Ahamed, Greg Stephens

P54 Fast and scalable spike sorting for large and dense multi-electrodes recordings

Pierre Yger, Baptiste Lefebvre, Giulia Lia Beatrice Spampinato, Elric Esposito, Marcel Stimberg et Olivier Marre

P55 Sufficient sampling rates for fast hand motion tracking

Hansol Choi, Min-Ho Song

P56 Linear readout of object manifolds

SueYeon Chung, Dan D. Lee, Haim Sompolinsky

P57 Differentiating models of intrinsic bursting and rhythm generation of the respiratory pre-Bötzinger complex using phase response curves

Ryan S. Phillips, Jeffrey Smith

P58 The effect of inhibitory cell network interactions during theta rhythms on extracellular field potentials in CA1 hippocampus

Alexandra Pierri Chatzikalymniou, Katie Ferguson, Frances K. Skinner

P59 Expansion recoding through sparse sampling in the cerebellar input layer speeds learning

N. Alex Cayco Gajic, Claudia Clopath, R. Angus Silver

P60 A set of curated cortical models at multiple scales on Open Source Brain

Padraig Gleeson, Boris Marin, Sadra Sadeh, Adrian Quintana, Matteo Cantarelli, Salvador Dura-Bernal, William W. Lytton, Andrew Davison, R. Angus Silver

P61 A synaptic story of dynamical information encoding in neural adaptation

Luozheng Li, Wenhao Zhang, Yuanyuan Mi, Dahui Wang, Si Wu

P62 Physical modeling of rule-observant rodent behavior

Youngjo Song, Sol Park, Ilhwan Choi, Jaeseung Jeong, Hee-sup Shin

P64 Predictive coding in area V4 and prefrontal cortex explains dynamic discrimination of partially occluded shapes

Hannah Choi, Anitha Pasupathy, Eric Shea-Brown

P65 Stability of FORCE learning on spiking and rate-based networks

Dongsung Huh, Terrence J. Sejnowski

P66 Stabilising STDP in striatal neurons for reliable fast state recognition in noisy environments

Simon M. Vogt, Arvind Kumar, Robert Schmidt

P67 Electrodiffusion in one- and two-compartment neuron models for characterizing cellular effects of electrical stimulation

Stephen Van Wert, Steven J. Schiff

P68 STDP improves speech recognition capabilities in spiking recurrent circuits parameterized via differential evolution Markov Chain Monte Carlo

Richard Veale, Matthias Scheutz

P69 Bidirectional transformation between dominant cortical neural activities and phase difference distributions

Sang Wan Lee

P70 Maturation of sensory networks through homeostatic structural plasticity

Júlia Gallinaro, Stefan Rotter

P71 Corticothalamic dynamics: structure, number of solutions and stability of steady-state solutions in the space of synaptic couplings

Paula Sanz-Leon, Peter A. Robinson

P72 Optogenetic versus electrical stimulation of the parkinsonian basal ganglia. Computational study

Leonid L. Rubchinsky, Chung Ching Cheung, Shivakeshavan Ratnadurai-Giridharan

P73 Exact spike-timing distribution reveals higher-order interactions of neurons

Safura Rashid Shomali, Majid Nili Ahmadabadi, Hideaki Shimazaki, S. Nader Rasuli

P74 Neural mechanism of visual perceptual learning using a multi-layered neural network

Xiaochen Zhao, Malte J. Rasch

P75 Inferring collective spiking dynamics from mostly unobserved systems

Jens Wilting, Viola Priesemann

P76 How to infer distributions in the brain from subsampled observations

Anna Levina, Viola Priesemann

P77 Influences of embedding and estimation strategies on the inferred memory of single spiking neurons

Lucas Rudelt, Joseph T. Lizier, Viola Priesemann

P78 A nearest-neighbours based estimator for transfer entropy between spike trains

Joseph T. Lizier, Richard E. Spinney, Mikail Rubinov, Michael Wibral, Viola Priesemann

P79 Active learning of psychometric functions with multinomial logistic models

Ji Hyun Bak, Jonathan Pillow

P81 Inferring low-dimensional network dynamics with variational latent Gaussian process

Yuan Zaho, Il Memming Park

P82 Computational investigation of energy landscapes in the resting state subcortical brain network

Jiyoung Kang, Hae-Jeong Park

P83 Local repulsive interaction between retinal ganglion cells can generate a consistent spatial periodicity of orientation map

Jaeson Jang, Se-Bum Paik

P84 Phase duration of bistable perception reveals intrinsic time scale of perceptual decision under noisy condition

Woochul Choi, Se-Bum Paik

P85 Feedforward convergence between retina and primary visual cortex can determine the structure of orientation map

Changju Lee, Jaeson Jang, Se-Bum Paik

P86 Computational method classifying neural network activity patterns for imaging data

Min Song, Hyeonsu Lee, Se-Bum Paik

P87 Symmetry of spike-timing-dependent-plasticity kernels regulates volatility of memory

Youngjin Park, Woochul Choi^, Se-Bum Paik

P88 Effects of time-periodic coupling strength on the first-spike latency dynamics of a scale-free network of stochastic Hodgkin-Huxley neurons

Ergin Yilmaz, Veli Baysal, Mahmut Ozer

P89 Spectral properties of spiking responses in V1 and V4 change within the trial and are highly relevant for behavioral performance

Veronika Koren, Klaus Obermayer

P90 Methods for building accurate models of individual neurons

Daniel Saska, Thomas Nowotny

P91 A full size mathematical model of the early olfactory system of honeybees

Ho Ka Chan, Alan Diamond, Thomas Nowotny

P92 Stimulation-induced tuning of ongoing oscillations in spiking neural networks

Christoph S. Herrmann, Micah M. Murray, Silvio Ionta, Axel Hutt, Jérémie Lefebvre

P93 Decision-specific sequences of neural activity in balanced random networks driven by structured sensory input

Philipp Weidel, Renato Duarte, Abigail Morrison

P94 Modulation of tuning induced by abrupt reduction of SST cell activity

Jung H. Lee, Ramakrishnan Iyer, Stefan Mihalas

P95 The functional role of VIP cell activation during locomotion

Jung H. Lee, Ramakrishnan Iyer, Christof Koch, Stefan Mihalas

P96 Stochastic inference with spiking neural networks

Mihai A. Petrovici, Luziwei Leng, Oliver Breitwieser, David Stöckel, Ilja Bytschok, Roman Martel, Johannes Bill, Johannes Schemmel, Karlheinz Meier

P97 Modeling orientation-selective electrical stimulation with retinal prostheses

Timothy B. Esler, Anthony N. Burkitt, David B. Grayden, Robert R. Kerr, Bahman Tahayori, Hamish Meffin

P98 Ion channel noise can explain firing correlation in auditory nerves

Bahar Moezzi, Nicolangelo Iannella, Mark D. McDonnell

P99 Limits of temporal encoding of thalamocortical inputs in a neocortical microcircuit

Max Nolte, Michael W. Reimann, Eilif Muller, Henry Markram

P100 On the representation of arm reaching movements: a computational model

Antonio Parziale, Rosa Senatore, Angelo Marcelli

P101 A computational model for investigating the role of cerebellum in acquisition and retention of motor behavior

Rosa Senatore, Antonio Parziale, Angelo Marcelli

P102 The emergence of semantic categories from a large-scale brain network of semantic knowledge

K. Skiker, M. Maouene

P103 Multiscale modeling of M1 multitarget pharmacotherapy for dystonia

Samuel A. Neymotin, Salvador Dura-Bernal, Alexandra Seidenstein, Peter Lakatos, Terence D. Sanger, William W. Lytton

P104 Effect of network size on computational capacity

Salvador Dura-Bernal, Rosemary J. Menzies, Campbell McLauchlan, Sacha J. van Albada, David J. Kedziora, Samuel Neymotin, William W. Lytton, Cliff C. Kerr

P105 NetPyNE: a Python package for NEURON to facilitate development and parallel simulation of biological neuronal networks

Salvador Dura-Bernal, Benjamin A. Suter, Samuel A. Neymotin, Cliff C. Kerr, Adrian Quintana, Padraig Gleeson, Gordon M. G. Shepherd, William W. Lytton

P107 Inter-areal and inter-regional inhomogeneity in co-axial anisotropy of Cortical Point Spread in human visual areas

Juhyoung Ryu, Sang-Hun Lee

P108 Two bayesian quanta of uncertainty explain the temporal dynamics of cortical activity in the non-sensory areas during bistable perception

Joonwon Lee, Sang-Hun Lee

P109 Optimal and suboptimal integration of sensory and value information in perceptual decision making

Hyang Jung Lee, Sang-Hun Lee

P110 A Bayesian algorithm for phoneme Perception and its neural implementation

Daeseob Lim, Sang-Hun Lee

P111 Complexity of EEG signals is reduced during unconsciousness induced by ketamine and propofol

Jisung Wang, Heonsoo Lee

P112 Self-organized criticality of neural avalanche in a neural model on complex networks

Nam Jung, Le Anh Quang, Seung Eun Maeng, Tae Ho Lee, Jae Woo Lee

P113 Dynamic alterations in connection topology of the hippocampal network during ictal-like epileptiform activity in an in vitro rat model

Chang-hyun Park, Sora Ahn, Jangsup Moon, Yun Seo Choi, Juhee Kim, Sang Beom Jun, Seungjun Lee, Hyang Woon Lee

P114 Computational model to replicate seizure suppression effect by electrical stimulation

Sora Ahn, Sumin Jo, Eunji Jun, Suin Yu, Hyang Woon Lee, Sang Beom Jun, Seungjun Lee

P115 Identifying excitatory and inhibitory synapses in neuronal networks from spike trains using sorted local transfer entropy

Felix Goetze, Pik-Yin Lai

P116 Neural network model for obstacle avoidance based on neuromorphic computational model of boundary vector cell and head direction cell

Seonghyun Kim, Jeehyun Kwag

P117 Dynamic gating of spike pattern propagation by Hebbian and anti-Hebbian spike timing-dependent plasticity in excitatory feedforward network model

Hyun Jae Jang, Jeehyun Kwag

P118 Inferring characteristics of input correlations of cells exhibiting up-down state transitions in the rat striatum

Marko Filipović, Ramon Reig, Ad Aertsen, Gilad Silberberg, Arvind Kumar

P119 Graph properties of the functional connected brain under the influence of Alzheimer’s disease

Claudia Bachmann, Simone Buttler, Heidi Jacobs, Kim Dillen, Gereon R. Fink, Juraj Kukolja, Abigail Morrison

P120 Learning sparse representations in the olfactory bulb

Daniel Kepple, Hamza Giaffar, Dima Rinberg, Steven Shea, Alex Koulakov

P121 Functional classification of homologous basal-ganglia networks

Jyotika Bahuguna,Tom Tetzlaff, Abigail Morrison, Arvind Kumar, Jeanette Hellgren Kotaleski

P122 Short term memory based on multistability

Tim Kunze, Andre Peterson, Thomas Knösche

P123 A physiologically plausible, computationally efficient model and simulation software for mammalian motor units

Minjung Kim, Hojeong Kim

P125 Decoding laser-induced somatosensory information from EEG

Ji Sung Park, Ji Won Yeon, Sung-Phil Kim

P126 Phase synchronization of alpha activity for EEG-based personal authentication

Jae-Hwan Kang, Chungho Lee, Sung-Phil Kim

P129 Investigating phase-lags in sEEG data using spatially distributed time delays in a large-scale brain network model

Andreas Spiegler, Spase Petkoski, Matias J. Palva, Viktor K. Jirsa

P130 Epileptic seizures in the unfolding of a codimension-3 singularity

Maria L. Saggio, Silvan F. Siep, Andreas Spiegler, William C. Stacey, Christophe Bernard, Viktor K. Jirsa

P131 Incremental dimensional exploratory reasoning under multi-dimensional environment

Oh-hyeon Choung, Yong Jeong

P132 A low-cost model of eye movements and memory in personal visual cognition

Yong-il Lee, Jaeseung Jeong

P133 Complex network analysis of structural connectome of autism spectrum disorder patients

Su Hyun Kim, Mir Jeong, Jaeseung Jeong

P134 Cognitive motives and the neural correlates underlying human social information transmission, gossip

Jeungmin Lee, Jaehyung Kwon, Jerald D. Kralik, Jaeseung Jeong

P135 EEG hyperscanning detects neural oscillation for the social interaction during the economic decision-making

Jaehwan Jahng, Dong-Uk Hwang, Jaeseung Jeong

P136 Detecting purchase decision based on hyperfrontality of the EEG

Jae-Hyung Kwon, Sang-Min Park, Jaeseung Jeong

P137 Vulnerability-based critical neurons, synapses, and pathways in the Caenorhabditis elegans connectome

Seongkyun Kim, Hyoungkyu Kim, Jerald D. Kralik, Jaeseung Jeong

P138 Motif analysis reveals functionally asymmetrical neurons in C. elegans

Pyeong Soo Kim, Seongkyun Kim, Hyoungkyu Kim, Jaeseung Jeong

P139 Computational approach to preference-based serial decision dynamics: do temporal discounting and working memory affect it?

Sangsup Yoon, Jaehyung Kwon, Sewoong Lim, Jaeseung Jeong

P141 Social stress induced neural network reconfiguration affects decision making and learning in zebrafish

Choongseok Park, Thomas Miller, Katie Clements, Sungwoo Ahn, Eoon Hye Ji, Fadi A. Issa

P142 Descriptive, generative, and hybrid approaches for neural connectivity inference from neural activity data

JeongHun Baek, Shigeyuki Oba, Junichiro Yoshimoto, Kenji Doya, Shin Ishii

P145 Divergent-convergent synaptic connectivities accelerate coding in multilayered sensory systems

Thiago S. Mosqueiro, Martin F. Strube-Bloss, Brian Smith, Ramon Huerta

P146 Swinging networks

Michal Hadrava, Jaroslav Hlinka

P147 Inferring dynamically relevant motifs from oscillatory stimuli: challenges, pitfalls, and solutions

Hannah Bos, Moritz Helias

P148 Spatiotemporal mapping of brain network dynamics during cognitive tasks using magnetoencephalography and deep learning

Charles M. Welzig, Zachary J. Harper

P149 Multiscale complexity analysis for the segmentation of MRI images

Won Sup Kim, In-Seob Shin, Hyeon-Man Baek, Seung Kee Han

P150 A neuro-computational model of emotional attention

René Richter, Julien Vitay, Frederick Beuth, Fred H. Hamker

P151 Multi-site delayed feedback stimulation in parkinsonian networks

Kelly Toppin, Yixin Guo

P152 Bistability in Hodgkin–Huxley-type equations

Tatiana Kameneva, Hamish Meffin, Anthony N. Burkitt, David B. Grayden

P153 Phase changes in postsynaptic spiking due to synaptic connectivity and short term plasticity: mathematical analysis of frequency dependency

Mark D. McDonnell, Bruce P. Graham

P154 Quantifying resilience patterns in brain networks: the importance of directionality

Penelope J. Kale, Leonardo L. Gollo

P155 Dynamics of rate-model networks with separate excitatory and inhibitory populations

Merav Stern, L. F. Abbott

P156 A model for multi-stable dynamics in action recognition modulated by integration of silhouette and shading cues

Leonid A. Fedorov, Martin A. Giese

P157 Spiking model for the interaction between action recognition and action execution

Mohammad Hovaidi Ardestani, Martin Giese

P158 Surprise-modulated belief update: how to learn within changing environments?

Mohammad Javad Faraji, Kerstin Preuschoff, Wulfram Gerstner

P159 A fast, stochastic and adaptive model of auditory nerve responses to cochlear implant stimulation

Margriet J. van Gendt, Jeroen J. Briaire, Randy K. Kalkman, Johan H. M. Frijns

P160 Quantitative comparison of graph theoretical measures of simulated and empirical functional brain networks

Won Hee Lee, Sophia Frangou

P161 Determining discriminative properties of fMRI signals in schizophrenia using highly comparative time-series analysis

Ben D. Fulcher, Patricia H. P. Tran, Alex Fornito

P162 Emergence of narrowband LFP oscillations from completely asynchronous activity during seizures and high-frequency oscillations

Stephen V. Gliske, William C. Stacey, Eugene Lim, Katherine A. Holman, Christian G. Fink

P163 Neuronal diversity in structure and function: cross-validation of anatomical and physiological classification of retinal ganglion cells in the mouse

Jinseop S. Kim, Shang Mu, Kevin L. Briggman, H. Sebastian Seung, the EyeWirers

P164 Analysis and modelling of transient firing rate changes in area MT in response to rapid stimulus feature changes

Detlef Wegener, Lisa Bohnenkamp, Udo A. Ernst

P165 Step-wise model fitting accounting for high-resolution spatial measurements: construction of a layer V pyramidal cell model with reduced morphology

Tuomo Mäki-Marttunen, Geir Halnes, Anna Devor, Christoph Metzner, Anders M. Dale, Ole A. Andreassen, Gaute T. Einevoll

P166 Contributions of schizophrenia-associated genes to neuron firing and cardiac pacemaking: a polygenic modeling approach

Tuomo Mäki-Marttunen, Glenn T. Lines, Andy Edwards, Aslak Tveito, Anders M. Dale, Gaute T. Einevoll, Ole A. Andreassen

P167 Local field potentials in a 4 × 4 mm² multi-layered network model

Espen Hagen, Johanna Senk, Sacha J. van Albada, Markus Diesmann

P168 A spiking network model explains multi-scale properties of cortical dynamics

Maximilian Schmidt, Rembrandt Bakker, Kelly Shen, Gleb Bezgin, Claus-Christian Hilgetag, Markus Diesmann, Sacha Jennifer van Albada

P169 Using joint weight-delay spike-timing dependent plasticity to find polychronous neuronal groups

Haoqi Sun, Olga Sourina, Guang-Bin Huang, Felix Klanner, Cornelia Denk

P170 Tensor decomposition reveals RSNs in simulated resting state fMRI

Katharina Glomb, Adrián Ponce-Alvarez, Matthieu Gilson, Petra Ritter, Gustavo Deco

P171 Getting in the groove: testing a new model-based method for comparing task-evoked vs resting-state activity in fMRI data on music listening

Matthieu Gilson, Maria AG Witek, Eric F. Clarke, Mads Hansen, Mikkel Wallentin, Gustavo Deco, Morten L. Kringelbach^, Peter Vuust

P172 STochastic engine for pathway simulation (STEPS) on massively parallel processors

Guido Klingbeil, Erik De Schutter

P173 Toolkit support for complex parallel spatial stochastic reaction–diffusion simulation in STEPS

Weiliang Chen, Erik De Schutter

P174 Modeling the generation and propagation of Purkinje cell dendritic spikes caused by parallel fiber synaptic input

Yunliang Zang, Erik De Schutter

P175 Dendritic morphology determines how dendrites are organized into functional subunits

Sungho Hong, Akira Takashima, Erik De Schutter

P176 A model of Ca²⁺/calmodulin-dependent protein kinase II activity in long term depression at Purkinje cells

Criseida Zamora, Andrew R. Gallimore, Erik De Schutter

P177 Reward-modulated learning of population-encoded vectors for insect-like navigation in embodied agents

Dennis Goldschmidt, Poramate Manoonpong, Sakyasingha Dasgupta

P178 Data-driven neural models part II: connectivity patterns of human seizures

Philippa J. Karoly, Dean R. Freestone, Daniel Soundry, Levin Kuhlmann, Liam Paninski, Mark Cook

P179 Data-driven neural models part I: state and parameter estimation

Dean R. Freestone, Philippa J. Karoly, Daniel Soundry, Levin Kuhlmann, Mark Cook

P180 Spectral and spatial information processing in human auditory streaming

Jaejin Lee, Yonatan I. Fishman, Yale E. Cohen

P181 A tuning curve for the global effects of local perturbations in neural activity: Mapping the systems-level susceptibility of the brain

Leonardo L. Gollo, James A. Roberts, Luca Cocchi

P182 Diverse homeostatic responses to visual deprivation mediated by neural ensembles

Yann Sweeney, Claudia Clopath

P183 Opto-EEG: a novel method for investigating functional connectome in mouse brain based on optogenetics and high density electroencephalography

Soohyun Lee, Woo-Sung Jung, Jee Hyun Choi

P184 Biphasic responses of frontal gamma network to repetitive sleep deprivation during REM sleep

Bowon Kim, Youngsoo Kim, Eunjin Hwang, Jee Hyun Choi

P185 Brain-state correlate and cortical connectivity for frontal gamma oscillations in top-down fashion assessed by auditory steady-state response

Younginha Jung, Eunjin Hwang, Yoon-Kyu Song, Jee Hyun Choi

P186 Neural field model of localized orientation selective activation in V1

James Rankin, Frédéric Chavane

P187 An oscillatory network model of Head direction and Grid cells using locomotor inputs

Karthik Soman, Vignesh Muralidharan, V. Srinivasa Chakravarthy

P188 A computational model of hippocampus inspired by the functional architecture of basal ganglia

Karthik Soman, Vignesh Muralidharan, V. Srinivasa Chakravarthy

P189 A computational architecture to model the microanatomy of the striatum and its functional properties

Sabyasachi Shivkumar, Vignesh Muralidharan, V. Srinivasa Chakravarthy

P190 A scalable cortico-basal ganglia model to understand the neural dynamics of targeted reaching

Vignesh Muralidharan, Alekhya Mandali, B. Pragathi Priyadharsini, Hima Mehta, V. Srinivasa Chakravarthy

P191 Emergence of radial orientation selectivity from synaptic plasticity

Catherine E. Davey, David B. Grayden, Anthony N. Burkitt

P192 How do hidden units shape effective connections between neurons?

Braden A. W. Brinkman, Tyler Kekona, Fred Rieke, Eric Shea-Brown, Michael Buice

P193 Characterization of neural firing in the presence of astrocyte-synapse signaling

Maurizio De Pittà, Hugues Berry, Nicolas Brunel

P194 Metastability of spatiotemporal patterns in a large-scale network model of brain dynamics

James A. Roberts, Leonardo L. Gollo, Michael Breakspear

P195 Comparison of three methods to quantify detection and discrimination capacity estimated from neural population recordings

Gary Marsat, Jordan Drew, Phillip D. Chapman, Kevin C. Daly, Samual P. Bradley

P196 Quantifying the constraints for independent evoked and spontaneous NMDA receptor mediated synaptic transmission at individual synapses

Sat Byul Seo, Jianzhong Su, Ege T. Kavalali, Justin Blackwell

P199 Gamma oscillation via adaptive exponential integrate-and-fire neurons

LieJune Shiau, Laure Buhry, Kanishka Basnayake

P200 Visual face representations during memory retrieval compared to perception

Sue-Hyun Lee, Brandon A. Levy, Chris I. Baker

P201 Top-down modulation of sequential activity within packets modeled using avalanche dynamics

Timothée Leleu, Kazuyuki Aihara

Q28 An auto-encoder network realizes sparse features under the influence of desynchronized vascular dynamics

Ryan T. Philips, Karishma Chhabria, V. Srinivasa Chakravarthy

Computational modeling of epileptiform activities in medial temporal lobe epilepsy combined with in vitro experiments

In this paper, we propose a comprehensive computational model that is able to reproduce three epileptiform activities. The model targets a hippocampal formation that is known to be an important lesion in medial temporal lobe epilepsy. It consists of four sub-networks consisting of excitatory and inhibitory neurons and well-known signal pathways, with consideration of propagation delay. The three epileptiform activities involve fast and slow interictal discharge and ictal discharge, and those activities can be induced in vitro by application of 4-Aminopyridine in entorhinal cortex combined hippocampal slices. We model the three epileptiform activities upon previously reported biological mechanisms and verify the simulation results by comparing them with in vitro experimental data obtained using a microelectrode array. We use the results of Granger causality analysis of recorded data to set input gains of signal pathways in the model, so that the compatibility between the computational and experimental models can be improved. The proposed model can be expanded to evaluate the suppression effect of epileptiform activities due to new treatment methods.

Synergistic combination of near-infrared irradiation and targeted gold nanoheaters for enhanced photothermal neural stimulation

Despite a potential of infrared neural stimulation (INS) for modulating neural activities, INS suffers from limited light confinement and bulk tissue heating. Here, a novel methodology for an advanced optical stimulation is proposed by combining near-infrared (NIR) stimulation with gold nanorods (GNRs) targeted to neuronal cell membrane. We confirmed experimentally that in vitro and in vivo neural activation is associated with a local heat generation based on NIR stimulation and GNRs. Compared with the case of NIR stimulation without an aid of GNRs, combination with cell-targeted GNRs allows photothermal stimulation with faster neural response, lower delivered energy, higher stimulation efficiency and stronger behavior change. Since the suggested method can reduce a requisite radiant exposure level and alleviate a concern of tissue damage, it is expected to open up new possibilities for applications to optical neuromodulations for diverse excitable tissues and treatments of neurological disorders.

Enhanced infrared neural stimulation using localized surface plasmon resonance of gold nanorods

An advanced optical activation of neural tissues is demonstrated using pulsed infrared light and plasmonic gold nanorods. Photothermal effect localized in plasma membrane triggers action potentials of in vivo neural tissues. Compared with conventional infrared stimulation, the suggested method can increase a neural responsivity and lower a threshold stimulation level significantly, thereby reducing a requisite radiant exposure and the concern of tissue damage.

Multi-color fluorescence imaging based on plasmonic wavelength selection and double illumination by white light

We demonstrate the proof-of-concept for developing a multi-color fluorescence imaging system based on plasmonic wavelength selection and double illumination by white light source. This technique is associated with fluorescence excitation by transmitted light via a diffraction of propagating surface plasmons. Since double illumination through both sides of isosceles triangle prism in the Kretschmann configuration enables multiple transmission beams of different wavelengths to interact with the specimen, our approach can be an alternative to conventional fluorescence detection owing to alignment stability and functional expandability. After fabricating a plasmonic wavelength splitter and integrating it with microscopic imaging system, we successfully confirm the performance by visualizing in vitro neuron cells labeled with green and red fluorescence dyes. The suggested method has a potential that it could be combined with plasmonic biosensor scheme to realize a multi-functional platform which allows imaging and sensing of biological samples at the same time.

In-vivo Optical Measurement of Neural Activity in the Brain

The optical neural recording techniques are promising tools in recent years. Compared to the traditional electrophysiological recording, the optical means offer several advantages including no inclusion of electrical noise, simultaneous imaging of a large number of neurons, or selective recording from genetically-targeted neurons. Overall the optical neural recording technique comprises the intrinsic and the extrinsic optical recordings. The methods for intrinsic neural recording employ the change of optical properties in brains such as blood flow/oxygenation, cellular volume change, or refractive index change without addition of external indicators. Those properties can be detected using various optical techniques including laser Doppler flowmetry (LDF), near-infrared (NIR) spectrometer, functional optical coherence tomography (fOCT), and surface plasmon resonance (SPR). The extrinsic monitoring techniques use fluorescence signals reflecting neuronal activity via chemical or genetic modification of the neuronal cells. Two most popular activity-dependent fluorescent probes, calcium indicators and voltage-sensitive fluorescent proteins will be examined in this review. The principles, the instrumentations and in vivo applications of those optical signal measurements are described.

A flexible depth probe using liquid crystal polymer

We proposed a method of making a flexible depth-type neural probe using liquid crystal polymer. Conventional depth neural probes made of metal or silicon have the limitations of a single recording site per shank or the brittleness of the silicon substrate. To avoid these drawbacks, polymer-based depth neural probes have been developed with biocompatible polymers such as polyimides or parylenes. However, those have suffered from the difficulty of inserting the probes into brain tissues due to their high flexibility, requiring mechanical reinforcements. Herein, we report the first attempt to use a flexible material, liquid crystal polymer (LCP), as a substrate for a depth-type neural probe. The LCP-based probe offers a controllable stiffness vs. flexibility and compatibility with thin-film processes in addition to its inherent characteristics such as high reliability and biocompatibility. In the present study, an LCP neural probe was fabricated to have enough stiffness to penetrate the dura mater of rodent brains without a guide tool or additional reinforcement structures. A simultaneous multichannel neural recording was successfully achieved from the somatosensory motor cortex of the rodents. Immunohistochemistry showed that the electrodes could be inserted into the desired regions in the brain.

In vivo optical neural recording using fiber-based surface plasmon resonance

We propose an intrinsic optical method for in vivo neural recording using optic fiber-based surface plasmon resonance (SPR) phenomena. The fiber-based SPR method is electrical artifact free, labeling free, and feasible for a portable system compared with conventional in vivo neural recording systems. We simultaneously detected SPR signals and electrical neural activity from the rat somatosensory cortex evoked by electrical stimulation on the forepaw. Pharmacological analysis using a voltage-gated sodium channel blocker confirmed the neural origins of the optical signals. This fiber-based SPR system promises the enhanced ability to record in vivo neural activity for the investigation of neurons and their networks.

A 1μm diameter tip fiber-based surface plasmon resonance system for single unit optical neural recording

A gold-deposited optical fiber sensor system based on surface plasmon resonance (SPR) was developed for optical measurement of neuronal activity. To enhance the sensitivity of localized SPR and to make a precise and safe contact with the cellular membrane, we designed a tapered optical probe of 1 μm diameter at the tip of the fiber. By wet etching and gold evaporating processes, pencil-shaped optical probes were successfully fabricated. The SPR system with the sharp optical probe was integrated with a conventional patch clamping system to realize a simultaneous optical and electrical recording on a single neuron. Although the shape of optical signal is not clear due to tiny change of intrinsic optical properties on the neuron, optical and electrical signals were simultaneously changed by capsaicin stimulation. Furthermore, our designed fiber probe can be applicable to localized optical stimulation as well as in vivo optical neuroprosthetic devices.

Vibrodissociation of neurons from rodent brain slices to study synaptic transmission and image presynaptic terminals

Mechanical dissociation of neurons from the central nervous system has the advantage that presynaptic boutons remain attached to the isolated neuron of interest. This allows for examination of synaptic transmission under conditions where the extracellular and postsynaptic intracellular environments can be well controlled. A vibration-based technique without the use of proteases, known as vibrodissociation, is the most popular technique for mechanical isolation. A micropipette, with the tip fire-polished to the shape of a small ball, is placed into a brain slice made from a P1-P21 rodent. The micropipette is vibrated parallel to the slice surface and lowered through the slice thickness resulting in the liberation of isolated neurons. The isolated neurons are ready for study within a few minutes of vibrodissociation. This technique has advantages over the use of primary neuronal cultures, brain slices and enzymatically isolated neurons including: rapid production of viable, relatively mature neurons suitable for electrophysiological and imaging studies; superior control of the extracellular environment free from the influence of neighboring cells; suitability for well-controlled pharmacological experiments using rapid drug application and total cell superfusion; and improved space-clamp in whole-cell recordings relative to neurons in slice or cell culture preparations. This preparation can be used to examine synaptic physiology, pharmacology, modulation and plasticity. Real-time imaging of both pre- and postsynaptic elements in the living cells and boutons is also possible using vibrodissociated neurons. Characterization of the molecular constituents of pre- and postsynaptic elements can also be achieved with immunological and imaging-based approaches.

Optical monitoring of neural networks evoked by focal electrical stimulation on microelectrode arrays using FM dyes

Patch-clamping or microelectrode arrays (MEA) are conventional methods to monitor the electrical activity in biological neural networks in vitro. Despite the effectiveness of these techniques, there are disadvantages including the limited number of electrodes and the predetermined location of electrodes in MEAs. In particular, these drawbacks raise a difficulty in monitoring a number of neurons outnumbering the electrodes. Here, we propose an optical technique to determine the effective range of focal electrical stimulation using FM dyes in neural networks grown on planar-type MEAs. After 3 weeks in culture, electrical stimulation was delivered to neural networks via an underlying electrode in the presence of FM dyes. The stimulation induced the internalization of the dye into the neurons around the stimulating electrodes. Fluorescent images of dye distribution successfully showed the effects of focal stimulation. A range of stimulus amplitudes and frequencies were examined to collect fluorescence images. FM-dye uptake after electrical stimulation resulted in the labeling of cells up to approximately 300 microm away from the stimulating electrode. Fluorescence intensity increased proportionally to stimulation amplitude. Tetrodotoxin was shown to inhibit the labeling of neurons except those located immediately adjacent (within 40 microm) from the stimulating electrode. In the presence of AMPA and NMDA receptors antagonists, the FM-dye labeling appeared within 80 microm from the electrode, indicating directly evoked neural networks via blocking of glutamatergic synaptic transmission. These results showed that FM dyes can be a useful tool for monitoring activity-dependent synaptic events and determining the effect of focal stimulation in cultured neural networks.

Docosahexaenoic acid promotes hippocampal neuronal development and synaptic function

Docosahexaenoic acid (DHA, 22:6n-3), the major polyunsaturated fatty acid accumulated in the brain during development, has been implicated in learning and memory, but underlying cellular mechanisms are not clearly understood. Here, we demonstrate that DHA significantly affects hippocampal neuronal development and synaptic function in developing hippocampi. In embryonic neuronal cultures, DHA supplementation uniquely promoted neurite growth, synapsin puncta formation and synaptic protein expression, particularly synapsins and glutamate receptors. In DHA-supplemented neurons, spontaneous synaptic activity was significantly increased, mostly because of enhanced glutamatergic synaptic activity. Conversely, hippocampal neurons from DHA-depleted fetuses showed inhibited neurite growth and synaptogenesis. Furthermore, n-3 fatty acid deprivation during development resulted in marked decreases of synapsins and glutamate receptor subunits in the hippocampi of 18-day-old pups with concomitant impairment of long-term potentiation, a cellular mechanism underlying learning and memory. While levels of synapsins and NMDA receptor subunit NR2A were decreased in most hippocampal regions, NR2A expression was particularly reduced in CA3, suggesting possible role of DHA in CA3-NMDA receptor-dependent learning and memory processes. The DHA-induced neurite growth, synaptogenesis, synapsin, and glutamate receptor expression, and glutamatergic synaptic function may represent important cellular aspects supporting the hippocampus-related cognitive function improved by DHA.

Cell-based olfactory biosensor using microfabricated planar electrode

The initial event in olfactory perception is the binding of odorant molecules to specific receptor proteins in the human nose. The interaction between odorant and receptor initiates olfactory signal transduction that leads to a cation influx and change in the membrane potential of the olfactory sensory neuron. In this study, a microfabricated planar electrode was used to measure the generated membrane potential in a heterologous olfactory system. Human embryonic kidney (HEK)-293 cells expressing the olfactory receptor I7 were transfected with the gustatory cyclic nucleotide gated (CNG) channel to amplify the membrane potential. A microfabricated planar electrode was used to measure the electrical responses of odorant-receptor binding. Stimulation of the olfactory receptor with its specific odorant caused an intracellular Ca(2+) influx, which was quantitatively measured using a planar electrode. The extracellular field potential generated by the Ca(2+) influx through the CNGgust channel of the cells was approximately 10 mV. This cell-based olfactory biosensor, which uses a microfabricated planar electrode for detection, would be useful for screening specific ligands for binding to orphan olfactory receptors.

Activity-dependent neuronal cell migration induced by electrical stimulation

Recently, we found that electrical stimulation can induce neuronal migration in neural networks cultured for more than 3 weeks on microelectrode arrays. Immunocytochemistry data showed that the aggregation of neurons was related to the emergence of astrocytes in culture. In this study, when neurons were cocultured with astrocytes, electrical stimulation could induce the migration of neuronal cell bodies after only 1 week in culture, while the same stimulation paradigm caused neural necrosis in neuron-only cultures. In addition, the stimulation-induced migration was inhibited by blocking action potentials in neural networks using the voltage-gated sodium channel blocker, tetrodotoxin. Immunocytochemistry was performed to monitor precisely the neuronal migration and count the number of neurons. These results indicate that neuronal migration of cell bodies is dependent on neuronal activity evoked by electrical stimulation and can be enhanced by coculturing with astrocytes. We believe this method can be employed as a means for modifying neural networks and improving the interface between electrodes and neurons.

Modulation of cultured neural networks using neurotrophin release from hydrogel-coated microelectrode arrays

Polyacrylamide and poly(ethylene glycol) diacrylate hydrogels were synthesized and characterized for use as drug release and substrates for neuron cell culture. Protein release kinetics was determined by incorporating bovine serum albumin (BSA) into hydrogels during polymerization. To determine if hydrogel incorporation and release affect bioactivity, alkaline phosphatase was incorporated into hydrogels and a released enzyme activity determined using the fluorescence-based ELF-97 assay. Hydrogels were then used to deliver a brain-derived neurotrophic factor (BDNF) from hydrogels polymerized over planar microelectrode arrays (MEAs). Primary hippocampal neurons were cultured on both control and neurotrophin-containing hydrogel-coated MEAs. The effect of released BDNF on neurite length and process arborization was investigated using automated image analysis. An increased spontaneous activity as a response to the released BDNF was recorded from the neurons cultured on the top of hydrogel layers. These results demonstrate that proteins of biological interest can be incorporated into hydrogels to modulate development and function of cultured neural networks. These results also set the stage for development of hydrogel-coated neural prosthetic devices for local delivery of various biologically active molecules.

Reduction of polarization-induced performance degradation in WDM PON utilizing MQW-SLD-based broadband source

We report on the reduction of polarization-induced performance degradation in WDM PON utilizing MQW-SLD-based ASE source for injection locking to FPLD. The results show that, to suppress the polarization-induced Q penalty sufficiently less than 0.5 dB, the MQW-SLD output should be depolarized within the locking range of the wavelength-locked FPLD.