Multiple consecutive-biphasic pulse stimulation improves spatially localized firing of retinal ganglion cells in the degenerate retina.

Retinal prostheses have shown some clinical success in restoring vision in patients with retinitis pigmentosa. However, the post-implantation visual acuity does not exceed that of legal blindness. The reason for the poor visual acuity might be that (1) degenerate retinal ganglion cells (RGCs) are less responsive to electrical stimulation than normal RGCs, and (2) electrically-evoked RGC spikes show a more widespread not focal response. The single-biphasic pulse electrical stimulation, commonly used in artificial vision, has limitations in addressing these issues. In this study, we propose the benefit of multiple consecutive-biphasic pulse stimulation. We used C57BL/6J mice and C3H/HeJ (rd1) mice for the normal retina and retinal degeneration model. An 8 × 8 multi-electrode array was used to record electrically-evoked RGC spikes. We compared RGC responses when increasing the amplitude of a single biphasic pulse versus increasing the number of consecutive biphasic pulses at the same stimulus charge. Increasing the amplitude of a single biphasic pulse induced more RGC spike firing while the spatial resolution of RGC populations decreased. For multiple consecutive-biphasic pulse stimulation, RGC firing increased as the number of pulses increased, and the spatial resolution of RGC populations was well preserved even up to 5 pulses. Multiple consecutive-biphasic pulse stimulation using two or three pulses in degenerate retinas induced as much RGC spike firing as in normal retinas. These findings suggest that the newly proposed multiple consecutive-biphasic pulse stimulation can improve the visual acuity in prosthesis-implanted patients.

Toward a Unified Framework for Cognitive Maps.

In this study, we integrated neural encoding and decoding into a unified framework for spatial information processing in the brain. Specifically, the neural representations of self-location in the hippocampus (HPC) and entorhinal cortex (EC) play crucial roles in spatial navigation. Intriguingly, these neural representations in these neighboring brain areas show stark differences. Whereas the place cells in the HPC fire as a unimodal function of spatial location, the grid cells in the EC show periodic tuning curves with different periods for different subpopulations (called modules). By combining an encoding model for this modular neural representation and a realistic decoding model based on belief propagation, we investigated the manner in which self-location is encoded by neurons in the EC and then decoded by downstream neurons in the HPC. Through the results of numerical simulations, we first show the positive synergy effects of the modular structure in the EC. The modular structure introduces more coupling between heterogeneous modules with different periodicities, which provides increased error-correcting capabilities. This is also demonstrated through a comparison of the beliefs produced for decoding two- and four-module codes. Whereas the former resulted in a complete decoding failure, the latter correctly recovered the self-location even from the same inputs. Further analysis of belief propagation during decoding revealed complex dynamics in information updates due to interactions among multiple modules having diverse scales. Therefore, the proposed unified framework allows one to investigate the overall flow of spatial information, closing the loop of encoding and decoding self-location in the brain.

On Decoding Grid Cell Population Codes Using Approximate Belief Propagation.

Neural systems are inherently noisy. One well-studied example of a noise reduction mechanism in the brain is the population code, where representing a variable with multiple neurons allows the encoded variable to be recovered with fewer errors. Studies have assumed ideal observer models for decoding population codes, and the manner in which information in the neural population can be retrieved remains elusive. This letter addresses a mechanism by which realistic neural circuits can recover encoded variables. Specifically, the decoding problem of recovering a spatial location from populations of grid cells is studied using belief propagation. We extend the belief propagation decoding algorithm in two aspects. First, beliefs are approximated rather than being calculated exactly. Second, decoding noises are introduced into the decoding circuits. Numerical simulations demonstrate that beliefs can be effectively approximated by combining polynomial nonlinearities with divisive normalization. This approximate belief propagation algorithm is tolerant to decoding noises. Thus, this letter presents a realistic model for decoding neural population codes and investigates fault-tolerant information retrieval mechanisms in the brain.

On resolving simultaneous congruences using belief propagation.

Graphical models and related algorithmic tools such as belief propagation have proven to be useful tools in (approximately) solving combinatorial optimization problems across many application domains. A particularly combinatorially challenging problem is that of determining solutions to a set of simultaneous congruences. Specifically, a continuous source is encoded into multiple residues with respect to distinct moduli, and the goal is to recover the source efficiently from noisy measurements of these residues. This problem is of interest in multiple disciplines, including neural codes, decentralized compression in sensor networks, and distributed consensus in information and social networks. This letter reformulates the recovery problem as an optimization over binary latent variables. Then we present a belief propagation algorithm, a layered variant of affinity propagation, to solve the problem. The underlying encoding structure of multiple congruences naturally results in a layered graphical model for the problem, over which the algorithms are deployed, resulting in a layered affinity propagation (LAP) solution. First, the convergence of LAP to an approximation of the maximum likelihood (ML) estimate is shown. Second, numerical simulations show that LAP converges within a few iterations and that the mean square error of LAP approaches that of the ML estimation at high signal-to-noise ratios.

On the Dynamics of Inferential Behavior while Reading Expository and Narrative Texts.

Inference plays a key role in reading comprehension. This study examines changes in inferential behavior while reading different genres. The inferential behavior of 28 students with reading disabilities (RDs) and 44 students without RDs was quantified while they read expository and narrative texts. First, the average rates of inference attempts and correct inferences were measured during reading. Then, the same rates were measured separately during early and late reading to see if there was a change in inferential behavior. The results show that the change in inferential behavior depends on the genre. While reading the expository text, both groups showed no significant change in their inference making. In contrast, while reading the narrative text, both groups showed higher rates of inference attempts, and only the students without RD showed a significant increase in correct inferences. The implications of these findings for the design of more engaging and effective reading programs are discussed.

High amplitude pulses on the same charge condition efficiently elicit bipolar cell-mediated retinal ganglion cell responses in the degenerate retina.

Retinal pigmentosa (RP) patients lose vision due to the loss of photoreceptors. Retinal prostheses bypass the dead photoreceptors by electrically stimulating surviving retinal neurons, such as bipolar cells or retinal ganglion cells (RGCs). In previous studies, stimulus charge has been mainly optimized to maximize the RGC response to electrical stimulation. This study aimed to investigate the effect of amplitude and duration even under the same charge condition on eliciting RGC spikes in the wild-type and degenerate retinas. Wild-type (WT) Sprague-Dawley rats were used as the normal retinal model, and Pde6b knockout rats were used as a retinal degeneration (RD) model. Electrically-evoked RGC spikes were recorded from isolated rat retinas using an 8 × 8 multielectrode array. The same charge was maintained (10 or 20 nC), and electrical stimulation was applied to WT and RD retinas, adjusting the amplitude and duration of the 1st phase of biphasic pulses. In the pulse modulation of the 1st phase, high amplitude (short duration) pulses induced more RGC spikes than low amplitude (long duration) pulses. Both WT and RD retinas showed a significant reduction in the number of RGC spikes upon stimulation with lower amplitude (longer duration) pulses. In clinical trials where stimulus charges are delivered to the degenerate retina of blind patients, high amplitude (short duration) pulses would help elicit more RGC spikes.

The Variation of Electrical Pulse Duration Elicits Reliable Network-Mediated Responses of Retinal Ganglion Cells in Normal, Not in Degenerate Primate Retinas.

This study aims to investigate the efficacy of electrical stimulation by comparing network-mediated RGC responses in normal and degenerate retinas using a N-methyl-N-nitrosourea (MNU)-induced non-human primate (NHPs) retinitis pigmentosa (RP) model. Adult cynomolgus monkeys were used for normal and outer retinal degeneration (RD) induced by MNU. The network-mediated RGC responses were recorded from the peripheral retina mounted on an 8 × 8 multielectrode array (MEA). The amplitude and duration of biphasic current pulses were modulated from 1 to 50 µA and 500 to 4000 µs, respectively. The threshold charge density for eliciting a network-mediated RGC response was higher in the RD monkeys than in the normal monkeys (1.47 ± 0.13 mC/cm2 vs. 1.06 ± 0.09 mC/cm2, p < 0.05) at a 500 µs pulse duration. The monkeys required a higher charge density than rodents among the RD models (monkeys; 1.47 ± 0.13 mC/cm2, mouse; 1.04 ± 0.09 mC/cm2, and rat; 1.16 ± 0.16 mC/cm2, p < 0.01). Increasing the pulse amplitude and pulse duration elicited more RGC spikes in the normal primate retinas. However, only pulse amplitude variation elicited more RGC spikes in degenerate primate retinas. Therefore, the pulse strategy for primate RD retinas should be optimized, eventually contributing to retinal prosthetics. Given that RD NHP RGCs are not sensitive to pulse duration, using shorter pulses may potentially be a more charge-effective approach for retinal prosthetics.

Correlated Activity in the Degenerate Retina Inhibits Focal Response to Electrical Stimulation.

Retinal prostheses have shown some clinical success in patients with retinitis pigmentosa and age-related macular degeneration. However, even after the implantation of a retinal prosthesis, the patient's visual acuity is at best less than 20/420. Reduced visual acuity may be explained by a decrease in the signal-to-noise ratio due to the spontaneous hyperactivity of retinal ganglion cells (RGCs) found in degenerate retinas. Unfortunately, abnormal retinal rewiring, commonly observed in degenerate retinas, has rarely been considered for the development of retinal prostheses. The purpose of this study was to investigate the aberrant retinal network response to electrical stimulation in terms of the spatial distribution of the electrically evoked RGC population. An 8 × 8 multielectrode array was used to measure the spiking activity of the RGC population. RGC spikes were recorded in wild-type [C57BL/6J; P56 (postnatal day 56)], rd1 (P56), rd10 (P14 and P56) mice, and macaque [wild-type and drug-induced retinal degeneration (RD) model] retinas. First, we performed a spike correlation analysis between RGCs to determine RGC connectivity. No correlation was observed between RGCs in the control group, including wild-type mice, rd10 P14 mice, and wild-type macaque retinas. In contrast, for the RD group, including rd1, rd10 P56, and RD macaque retinas, RGCs, up to approximately 400-600 µm apart, were significantly correlated. Moreover, to investigate the RGC population response to electrical stimulation, the number of electrically evoked RGC spikes was measured as a function of the distance between the stimulation and recording electrodes. With an increase in the interelectrode distance, the number of electrically evoked RGC spikes decreased exponentially in the control group. In contrast, electrically evoked RGC spikes were observed throughout the retina in the RD group, regardless of the inter-electrode distance. Taken together, in the degenerate retina, a more strongly coupled retinal network resulted in the widespread distribution of electrically evoked RGC spikes. This finding could explain the low-resolution vision in prosthesis-implanted patients.

Stage-Dependent Changes of Visual Function and Electrical Response of the Retina in the rd10 Mouse Model.

One of the critical prerequisites for the successful development of retinal prostheses is understanding the physiological features of retinal ganglion cells (RGCs) in the different stages of retinal degeneration (RD). This study used our custom-made rd10 mice, C57BL/6-Pde6bem1(R560C)Dkl /Korl mutated on the Pde6b gene in C57BL/6J mouse with the CRISPR/Cas9-based gene-editing method. We selected the postnatal day (P) 45, P70, P140, and P238 as representative ages for RD stages. The optomotor response measured the visual acuity across degeneration stages. At P45, the rd10 mice exhibited lower visual acuity than wild-type (WT) mice. At P140 and older, no optomotor response was observed. We classified RGC responses to the flashed light into ON, OFF, and ON/OFF RGCs via in vitro multichannel recording. With degeneration, the number of RGCs responding to the light stimulation decreased in all three types of RGCs. The OFF response disappeared faster than the ON response with older postnatal ages. We elicited RGC spikes with electrical stimulation and analyzed the network-mediated RGC response in the rd10 mice. Across all postnatal ages, the spikes of rd10 RGCs were less elicited by pulse amplitude modulation than in WT RGCs. The ratio of RGCs showing multiple peaks of spike burst increased in older ages. The electrically evoked RGC spikes by the pulse amplitude modulation differ across postnatal ages. Therefore, degeneration stage-dependent stimulation strategies should be considered for developing retinal prosthesis and successful vision restoration.

Foldable Perovskite Solar Cells Using Carbon Nanotube-Embedded Ultrathin Polyimide Conductor.

Recently, foldable electronics technology has become the focus of both academic and industrial research. The foldable device technology is distinct from flexible technology, as foldable devices have to withstand severe mechanical stresses such as those caused by an extremely small bending radius of 0.5 mm. To realize foldable devices, transparent conductors must exhibit outstanding mechanical resilience, for which they must be micrometer-thin, and the conducting material must be embedded into a substrate. Here, single-walled carbon nanotubes (CNTs)-polyimide (PI) composite film with a thickness of 7 µm is synthesized and used as a foldable transparent conductor in perovskite solar cells (PSCs). During the high-temperature curing of the CNTs-embedded PI conductor, the CNTs are stably and strongly p-doped using MoO x , resulting in enhanced conductivity and hole transportability. The ultrathin foldable transparent conductor exhibits a sheet resistance of 82 Ω sq.-1 and transmittance of 80% at 700 nm, with a maximum-power-point-tracking-output of 15.2% when made into a foldable solar cell. The foldable solar cells can withstand more than 10 000 folding cycles with a folding radius of 0.5 mm. Such mechanically resilient PSCs are unprecedented; further, they exhibit the best performance among the carbon-nanotube-transparent-electrode-based flexible solar cells.

Spike-triggered Clustering for Retinal Ganglion Cell Classification.

Retinal ganglion cells (RGCs), the retina's output neurons, encode visual information through spiking. The RGC receptive field (RF) represents the basic unit of visual information processing in the retina. RFs are commonly estimated using the spike-triggered average (STA), which is the average of the stimulus patterns to which a given RGC is sensitive. Whereas STA, based on the concept of the average, is simple and intuitive, it leaves more complex structures in the RFs undetected. Alternatively, spike-triggered covariance (STC) analysis provides information on second-order RF statistics. However, STC is computationally cumbersome and difficult to interpret. Thus, the objective of this study was to propose and validate a new computational method, called spike-triggered clustering (STCL), specific for multimodal RFs. Specifically, RFs were fit with a Gaussian mixture model, which provides the means and covariances of multiple RF clusters. The proposed method recovered bipolar stimulus patterns in the RFs of ON-OFF cells, while the STA identified only ON and OFF RGCs, and the remaining RGCs were labeled as unknown types. In contrast, our new STCL analysis distinguished ON-OFF RGCs from the ON, OFF, and unknown RGC types classified by STA. Thus, the proposed method enables us to include ON-OFF RGCs prior to retinal information analysis.

New Features of Receptive Fields in Mouse Retina through Spike-triggered Covariance.

Retinal ganglion cells (RGCs) encode various spatiotemporal features of visual information into spiking patterns. The receptive field (RF) of each RGC is usually calculated by spike-triggered average (STA), which is fast and easy to understand, but limited to simple and unimodal RFs. As an alternative, spike-triggered covariance (STC) has been proposed to characterize more complex patterns in RFs. This study compares STA and STC for the characterization of RFs and demonstrates that STC has an advantage over STA for identifying novel spatiotemporal features of RFs in mouse RGCs. We first classified mouse RGCs into ON, OFF, and ON/OFF cells according to their response to full-field light stimulus, and then investigated the spatiotemporal patterns of RFs with random checkerboard stimulation, using both STA and STC analysis. We propose five sub-types (T1-T5) in the STC of mouse RGCs together with their physiological implications. In particular, the relatively slow biphasic pattern (T1) could be related to excitatory inputs from bipolar cells. The transient biphasic pattern (T2) allows one to characterize complex patterns in RFs of ON/OFF cells. The other patterns (T3-T5), which are contrasting, alternating, and monophasic patterns, could be related to inhibitory inputs from amacrine cells. Thus, combining STA and STC and considering the proposed sub-types unveil novel characteristics of RFs in the mouse retina and offer a more holistic understanding of the neural coding mechanisms of mouse RGCs.

Synchrony of Spontaneous Burst Firing between Retinal Ganglion Cells Across Species.

Neurons communicate with other neurons in response to environmental changes. Their goal is to transmit information to their targets reliably. A burst, which consists of multiple spikes within a short time interval, plays an essential role in enhancing the reliability of information transmission through synapses. In the visual system, retinal ganglion cells (RGCs), the output neurons of the retina, show bursting activity and transmit retinal information to the lateral geniculate neuron of the thalamus. In this study, to extend our interest to the population level, the burstings of multiple RGCs were simultaneously recorded using a multi-channel recording system. As the first step in network analysis, we focused on investigating the pairwise burst correlation between two RGCs. Furthermore, to assess if the population bursting is preserved across species, we compared the synchronized bursting of RGCs between marmoset monkey (callithrix jacchus), one species of the new world monkeys and mouse (C57BL/6J strain). First, monkey RGCs showed a larger number of spikes within a burst, while the inter-spike interval, burst duration, and inter-burst interval were smaller compared with mouse RGCs. Monkey RGCs showed a strong burst synchronization between RGCs, whereas mouse RGCs showed no correlated burst firing. Monkey RGC pairs showed significantly higher burst synchrony and mutual information than mouse RGC pairs did. Comprehensively, through this study, we emphasize that two species have a different bursting activity of RGCs and different burst synchronization suggesting two species have distinctive retinal processing.

On predicting epileptic seizures from intracranial electroencephalography.

This study investigates the sensitivity and specificity of predicting epileptic seizures from intracranial electroencephalography (iEEG). A monitoring system is studied to generate an alarm upon detecting a precursor of an epileptic seizure. The iEEG traces of ten patients suffering from medically intractable epilepsy were used to build a prediction model. From the iEEG recording of each patient, power spectral densities were calculated and classified using support vector machines. The prediction results varied across patients. For seven patients, seizures were predicted with 100% sensitivity without any false alarms. One patient showed good sensitivity but lower specificity, and the other two patients showed lower sensitivity and specificity. Predictive analytics based on the spectral feature of iEEG performs well for some patients but not all. This result highlights the need for patient-specific prediction models and algorithms.