Analyzing top-down visual attention in the context of gamma oscillations: a layer- dependent network-of- networks approach.

Top-down visual attention is a fundamental cognitive process that allows individuals to selectively attend to salient visual stimuli in the environment. Recent empirical findings have revealed that gamma oscillations participate in the modulation of visual attention. However, computational studies face challenges when analyzing the attentional process in the context of gamma oscillation due to the unstable nature of gamma oscillations and the complexity induced by the layered fashion in the visual cortex. In this study, we propose a layer-dependent network-of-networks approach to analyze such attention with gamma oscillations. The model is validated by reproducing empirical findings on orientation preference and the enhancement of neuronal response due to top-down attention. We perform parameter plane analysis to classify neuronal responses into several patterns and find that the neuronal response to sensory and attention signals was modulated by the heterogeneity of the neuronal population. Furthermore, we revealed a counter-intuitive scenario that the excitatory populations in layer 2/3 and layer 5 exhibit opposite responses to the attentional input. By modification of the original model, we confirmed layer 6 plays an indispensable role in such cases. Our findings uncover the layer-dependent dynamics in the cortical processing of visual attention and open up new possibilities for further research on layer-dependent properties in the cerebral cortex.

Limiting parameter range for cortical-spherical mapping improves activated domain estimation for attention modulated auditory response.

BACKGROUND: Attention is one of the factors involved in selecting input information for the brain. We applied a method for estimating domains with clear boundaries using magnetoencephalography (the domain estimation method) for auditory-evoked responses (N100m) to evaluate the effects of attention in milliseconds. However, because the surface around the auditory cortex is folded in a complicated manner, it is unknown whether the activity in the auditory cortex can be estimated. NEW METHOD: The parameter range to express current sources was set to include the auditory cortex. Their search region was expressed as a direct product of the parameter ranges used in the adaptive diagonal curves. RESULTS: Without a limitation of the range, activity was estimated in regions other than the auditory cortex in all cases. However, with the limitation of the range, the activity was estimated in the primary or higher auditory cortex. Further analysis of the limitation of the range showed that the domains activated during attention included the regions activated during no attention for the participants whose amplitudes of N100m were higher during attention. COMPARISON WITH EXISTING METHOD: We proposed a method for effectively limiting the search region to evaluate the extent of the activated domain in regions with complex folded structures. CONCLUSION: To evaluate the extent of activated domains in regions with complex folded structures, it is necessary to limit the parameter search range. The area of the activated domains in the auditory cortex may increase by attention on the millisecond timescale.

Development of a Hypersensitivity Evaluation Method for Cultured Sensory Neurons Using Electrical Activity Recording.

Investigation of hypersensitivity caused by peripheral sensitization progression is important for developing novel pain treatments. Existing methods cannot record plastic changes in neuronal activity because they occur over a few days. We aimed to establish an efficient method to evaluate neuronal activity alterations caused by peripheral sensitization on high-density microelectrode arrays (HD-MEAs) which can record neuronal activity for a long time. Rat dorsal root ganglion (DRG) neurons were dissected from rat embryos and cultured on HD-MEAs. DRG neurons were labeled with NeuO, live staining dye. Neurons were detected with the fluorescence signal and electrodes were selected with the fluorescence images. The number of DRG neurons, whose activity were recorded, detected based on fluorescence observation was five times greater than that based on neuronal activity. Analysis of changes in neuronal activity observed in pharmacological stimulation experiments suggested that substance P induced peripheral sensitization and enhanced capsaicin sensitivity. In addition, results of immunofluorescence staining suggested that peripheral sensitization occurred mostly in neurons that co-expressed transient receptor potential vanilloid 1 (TRPV1) and neurokinin 1 receptor (NK1R). In conclusion, we established an efficient method for assessing the effects of peripheral sensitization on DRG neurons cultured on HD-MEAs.

Experimental validation of the free-energy principle with in vitro neural networks.

Empirical applications of the free-energy principle are not straightforward because they entail a commitment to a particular process theory, especially at the cellular and synaptic levels. Using a recently established reverse engineering technique, we confirm the quantitative predictions of the free-energy principle using in vitro networks of rat cortical neurons that perform causal inference. Upon receiving electrical stimuli-generated by mixing two hidden sources-neurons self-organised to selectively encode the two sources. Pharmacological up- and downregulation of network excitability disrupted the ensuing inference, consistent with changes in prior beliefs about hidden sources. As predicted, changes in effective synaptic connectivity reduced variational free energy, where the connection strengths encoded parameters of the generative model. In short, we show that variational free energy minimisation can quantitatively predict the self-organisation of neuronal networks, in terms of their responses and plasticity. These results demonstrate the applicability of the free-energy principle to in vitro neural networks and establish its predictive validity in this setting.

Controlling fluidic oscillator flow dynamics by elastic structure vibration.

In this study, we introduce a design of a feedback-type fluidic oscillator with elastic structures surrounding its feedback channel. By employing phase reduction theory, we extract the phase sensitivity function of the complex fluid-structure coupled system, which represents the system's oscillatory characteristics. We show that the frequency of the oscillating flow inside the fluidic oscillator can be modulated by inducing synchronization with the weak periodic forcing from the elastic structure vibration. This design approach adds controllability to the fluidic oscillator, where conventionally, the intrinsic oscillatory characteristics of such device were highly determined by its geometry. The synchronization-induced control also changes the physical characteristics of the oscillatory fluid flow, which can be beneficial for practical applications, such as promoting better fluid mixing without changing the overall geometry of the device. Furthermore, by analyzing the phase sensitivity function, we demonstrate how the use of phase reduction theory gives good estimation of the synchronization condition with minimal number of experiments, allowing for a more efficient control design process. Finally, we show how an optimal control signal can be designed to reach the fastest time to synchronization.

Macroscopic Gamma Oscillation With Bursting Neuron Model Under Stochastic Fluctuation.

Gamma oscillations are thought to play a role in information processing in the brain. Bursting neurons, which exhibit periodic clusters of spiking activity, are a type of neuron that are thought to contribute largely to gamma oscillations. However, little is known about how the properties of bursting neurons affect the emergence of gamma oscillation, its waveforms, and its synchronized characteristics, especially when subjected to stochastic fluctuations. In this study, we proposed a bursting neuron model that can analyze the bursting ratio and the phase response function. Then we theoretically analyzed the neuronal population dynamics composed of bursting excitatory neurons, mixed with inhibitory neurons. The bifurcation analysis of the equivalent Fokker-Planck equation exhibits three types of gamma oscillations of unimodal firing, bimodal firing in the inhibitory population, and bimodal firing in the excitatory population under different interaction strengths. The analyses of the macroscopic phase response function by the adjoint method of the Fokker-Planck equation revealed that the inhibitory doublet facilitates synchronization of the high-frequency oscillations. When we keep the strength of interactions constant, decreasing the bursting ratio of the individual neurons increases the relative high-gamma component of the populational phase-coupling functions. This also improves the ability of the neuronal population model to synchronize with faster oscillatory input. The analytical frameworks in this study provide insight into nontrivial dynamics of the population of bursting neurons, which further suggest that bursting neurons have an important role in rhythmic activities.

Improving the accuracy of decoding monkey brain-machine interface data by estimating the state of unobserved cell assemblies.

BACKGROUND: The brain-machine interface is a technology that has been used for improving the quality of life of individuals with physical disabilities and also healthy individuals. It is important to improve the methods used for decoding the brain-machine interface data as the accuracy and speed of movements achieved using the existing technology are not comparable to the normal body. COMPARISON WITH THE EXISTING METHOD: Decoding of brain-machine interface data using the proposed method resulted in improved decoding accuracy compared to the existing method. CONCLUSIONS: The results demonstrated the usefulness of cell assembly state estimation method for decoding the brain-machine interface data. NEW METHOD: We incorporated a novel method of estimating cell assembly states using spike trains with the existing decoding method that used only firing rate data. Synaptic connectivity pattern was used as feature values in addition to firing rate. Publicly available monkey brain-machine interface datasets were used in the study. RESULTS: As long as the decoding was successful, the root mean square error of the proposed method was significantly smaller than the existing method. Artificial neural netowork-based decoding method resulted in more stable decoding, and also improved the decoding accuracy due to incorporation of synaptic connectivity pattern.

Coupling of in vitro Neocortical-Hippocampal Coculture Bursts Induces Different Spike Rhythms in Individual Networks.

Brain-state alternation is important for long-term memory formation. Each brain state can be identified with a specific process in memory formation, e.g., encoding during wakefulness or consolidation during sleeping. The hippocampal-neocortical dialogue was proposed as a hypothetical framework for systems consolidation, which features different cross-frequency couplings between the hippocampus and distributed neocortical regions in different brain states. Despite evidence supporting this hypothesis, little has been reported about how information is processed with shifts in brain states. To address this gap, we developed an in vitro neocortical-hippocampal coculture model to study how activity coupling can affect connections between coupled networks. Neocortical and hippocampal neurons were cultured in two different compartments connected by a micro-tunnel structure. The network activity of the coculture model was recorded by microelectrode arrays underlying the substrate. Rhythmic bursting was observed in the spontaneous activity and electrical evoked responses. Rhythmic bursting activity in one compartment could couple to that in the other via axons passing through the micro-tunnels. Two types of coupling patterns were observed: slow-burst coupling (neocortex at 0.1-0.5 Hz and hippocampus at 1 Hz) and fast burst coupling (neocortex at 20-40 Hz and hippocampus at 4-10 Hz). The network activity showed greater synchronicity in the slow-burst coupling, as indicated by changes in the burstiness index. Network synchronicity analysis suggests the presence of different information processing states under different burst activity coupling patterns. Our results suggest that the hippocampal-neocortical coculture model possesses multiple modes of burst activity coupling between the cortical and hippocampal parts. With the addition of external stimulation, the neocortical-hippocampal network model we developed can elucidate the influence of state shifts on information processing.

Recording Saltatory Conduction Along Sensory Axons Using a High-Density Microelectrode Array.

Myelinated fibers are specialized neurological structures used for conducting action potentials quickly and reliably, thus assisting neural functions. Although demyelination leads to serious functional impairments, little is known the relationship between myelin structural change and increase in conduction velocity during myelination and demyelination processes. There are no appropriate methods for the long-term evaluation of spatial characteristics of saltatory conduction along myelinated axons. Herein, we aimed to detect saltatory conduction from the peripheral nervous system neurons using a high-density microelectrode array. Rat sensory neurons and intrinsic Schwann cells were cultured. Immunofluorescence and ultrastructure examination showed that the myelinating Schwann cells appeared at 1 month, and compact myelin was formed by 10 weeks in vitro. Activity of rat sensory neurons was evoked with optogenetic stimulation, and axon conduction was detected with high-density microelectrode arrays. Some conductions included high-speed segments with low signal amplitude. The same segment could be detected with electrical recording and immunofluorescent imaging for a myelin-related protein. The spatiotemporal analysis showed that some segments show a velocity of more than 2 m/s and that ends of the segments show a higher electrical sink, suggesting that saltatory conduction occurred in myelinated axons. Moreover, mathematical modeling supported that the recorded signal was in the appropriate range for axon and electrode sizes. Overall, our method could be a feasible tool for evaluating spatial characteristics of axon conduction including saltatory conduction, which is applicable for studying demyelination and remyelination.

Motion-capture technique-based interface screen displaying real-time probe position and angle in kidney ultrasonography.

Professional skill is required to reproduce ultrasound images of the kidney as an optimal cross-section is easily lost with slight deviation in scanning location or angle of the probe. We developed a motion-capture technique-based interface screen that displays the real-time probe position and angle to overlap those provided beforehand. When a professional operator captured the approximate kidney image, our system recorded the relative spatial relationship between the subject and the probe. Next, an amateur operator who had no experience of clinical practice manipulated the probe only with the aid of the interface until the probe position and angle coincided with the professional ones. Eventually, amateur operators could place the probe with a deviation of distance of (x = 2.7 ± 1.2 mm, y = 3.0 ± 1.7 mm, z = 6.6 ± 1.8 mm) and angle of (Rx = 1.5 ± 0.3 degrees, Ry = 2.6 ± 1.1 degrees, Rz = 1.1 ± 0.3 degrees) from the professional goal to produce very similar cross-sectional kidney images (N = 8). Also, motion-capture technique-based evaluation of relative locations of the probe and subject body revealed difficulty in reproducing those without the interface screen navigation. In summary, our motion-capture technique-based ultrasound guide system provides operators with the opportunity to handle the probe just as another operator would beforehand. This could help in medical procedures wherein the same cross-sectional image should be repeatedly obtained. Moreover, it requires no conventional probe training for beginners and could even shift the paradigm for ultrasound probe handling.

Observing Cell Assemblies From Spike Train Recordings Based on the Biological Basis of Synaptic Connectivity.

Cell assemblies are difficult to observe because they consist of many neurons. We aimed to observe cell assemblies based on biological statistics, such as synaptic connectivity. We developed an estimation method to estimate the activity and synaptic connectivity of cell assemblies from spike trains using mathematical models of individual neurons and cell assemblies. Synaptic transmissions were averaged to generate postsynaptic currents with the same timing and waveform but different amplitudes, as the number of presynaptic neurons was large. We estimated the average synaptic transmission and synaptic connectivity from active cell assemblies based on the stochastic prediction of membrane potentials and verified the estimation ability of the average synaptic transmission and synaptic connectivity using the proposed method on simulated neural activity. Different cell assembly activities evoked by electrical stimuli were correctly sorted into various clusters in experiments using rat cortical neurons cultured on microelectrode arrays. We observed multiple cell assemblies from the spontaneous activity of rat cortical networks on microelectrode arrays, based on the synaptic connectivity patterns estimated by the proposed method. The proposed method was superior to the conventional method for detecting the activity of multiple cell assemblies. Using the proposed method, it is possible to observe multiple cell assemblies based on the biological basis of synaptic connectivity. In summary, we report a novel method to observe cell assemblies from spike train recordings based on the biological basis of synaptic connectivity, rather than merely relying on a statistical method.

Change in network dynamics over time by administering Notch response inhibitor DAPT to hippocampal culture.

Although previous researches have investigated the relationship between learning and memory function in the hippocampus and continuously produced newborn neurons, the detailed role of newly generated neurons remains unclear. Here, we investigated the correlation between immature neurons and the electrical activity of the hippocampus at the network level in vitro. We showed that administrating the Notch response inhibitor DAPT to the hippocampal network enhances the neuronal differentiation of newborn cells and decreases the ratio of immature neurons in hippocampal culture. Unlike the hippocampal network without DAPT, the network with DAPT decreased the burst duration and the coefficient of variation of interburst intervals over culturing time and showed a higher synchronization level of the network over time. Moreover, the number of neurons playing a receiver or sender neuron was lower in the network with DAPT than without DAPT. Our results indicate that immature neurons may contribute to assigning neurons specific nodes as the receiver of the sender and to the diversity of the network activity while altering connections among neurons in the network.Clinical Relevance- Our research demonstrated the effect of DAPT on the ratio of immature neurons. Furthermore, our study showed the role of immature neurons in the hippocampus at the network level.

Relationship Between Subjective Ratings of Answers and Behavioral and Autonomic Nervous Activities During Creative Problem-Solving via Online Conversation.

Creative problem solving has been important for the advent of new technologies. In this study, we hypothesized that subjective ratings of answers should be useful for evaluating the answer quality in creative problem solving. To test this hypothesis and extract objective indicators of the subjective ratings of answers, we evaluated the relationship between subjective ratings of task performance and behavioral and autonomic nervous activities during a creative problem-solving task performed via online conversation. The task involved an answerer and a supporter, and in the experiment, each pair performed 10 trials. The trials were categorized as highly or lowly rated according to the answerer's confidence in the answer. The task performance and behavioral and autonomic nervous activities were then compared between these categories of trials. Behavioral activity was evaluated via movements and speech activities, while for autonomic nervous activity, sympathetic nervous activity (SNA) was evaluated via skin conductance. The task performance was significantly better in the highly rated trials, whereas there were no significant differences in the behavioral activities between the highly and lowly rated trials. Moreover, in the highly rated trials, the skin conductance of the answerer was significantly high, whereas that of the supporter was significantly low. The results support the hypothesis and suggest that contrasting differences in SNA between an answerer and a supporter are indicators of the subjective ratings of answers in creative problem solving.

Initiation and termination of reentry-like activity in rat cardiomyocytes cultured in a microelectrode array.

Cardiac reentry is a lethal arrhythmia associated with cardiac diseases. Although arrhythmias are reported to be due to localized propagation abnormalities, little is known about the mechanisms underlying the initiation and termination of reentry. This is primarily because of a lack of an appropriate experimental system in which activity pattern switches between reentry and normal beating can be investigated. In this study, we aimed to develop a culture system for measuring the spatial dynamics of reentry-like activity during its onset and termination. Rat cardiomyocytes were seeded in microelectrode arrays and purified with a glucose-free culture medium to generate a culture with a heterogeneous cell density. Reentry-like activity was recorded in purified cardiomyocytes, but not in the controls. Reentry-like activity occurred by a unidirectional conduction block after shortening of the inter-beat interval. Furthermore, reentry-like activity was terminated after propagation with a conduction delay of less than 300 ms, irrespective of whether the propagation pattern changed or not. These results indicate that a simple purification process is sufficient to induce reentry-like activity. In the future, a more detailed evaluation of spatial dynamics will contribute to the development of effective treatment methods.

Modulation of dynamics in a pre-existing hippocampal network by neural stem cells on a microelectrode array.

Objective.Neural stem cells (NSCs) are continuously produced throughout life in the hippocampus, which is a vital structure for learning and memory. NSCs in the brain incorporate into the functional hippocampal circuits and contribute to processing information. However, little is known about the mechanisms of NSCs' activity in a pre-existing neuronal network. Here, we investigate the role of NSCs in the neuronal activity of a pre-existing hippocampalin vitronetwork grown on microelectrode arrays.Approach.We assessed the change in internal dynamics of the network by additional NSCs based on spontaneous activity. We also evaluated the networks' ability to discriminate between different input patterns by measuring evoked activity in response to external inputs.Main results.Analysis of spontaneous activity revealed that additional NSCs prolonged network bursts with longer intervals, generated a lower number of initiating patterns, and decreased synchronization among neurons. Moreover, the network with NSCs showed higher synchronicity in close connections among neurons responding to external inputs and a larger difference in spike counts and cross-correlations during evoked response between two different inputs. Taken together, our results suggested that NSCs alter the internal dynamics of the pre-existing hippocampal network and produce more specific responses to external inputs, thus enhancing the ability of the network to differentiate two different inputs.Significance.We demonstrated that NSCs improve the ability to distinguish external inputs by modulating the internal dynamics of a pre-existing network in a hippocampal culture. Our results provide novel insights into the relationship between NSCs and learning and memory.

Distinct effects of heterogeneity and noise on gamma oscillation in a model of neuronal network with different reversal potential.

Gamma oscillation is crucial in brain functions such as attentional selection, and is inextricably linked to both heterogeneity and noise (or so-called stochastic fluctuation) in neuronal networks. However, under coexistence of these factors, it has not been clarified how the synaptic reversal potential modulates the entraining of gamma oscillation. Here we show distinct effects of heterogeneity and noise in a population of modified theta neurons randomly coupled via GABAergic synapses. By introducing the Fokker-Planck equation and circular cumulants, we derive a set of two-cumulant macroscopic equations. In bifurcation analyses, we find a stabilizing effect of heterogeneity and a nontrivial effect of noise that results in promoting, diminishing, and shifting the oscillatory region, and is largely dependent on the reversal potential of GABAergic synapses. These findings are verified by numerical simulations of a finite-size neuronal network. Our results reveal that slight changes in reversal potential and magnitude of stochastic fluctuations can lead to immediate control of gamma oscillation, which would results in complex spatio-temporal dynamics for attentional selection and recognition.

Microfabricated Device to Record Axonal Conduction Under Pharmacological Treatment for Functional Evaluation of Axon Ion Channel.

OBJECTIVE: Neuronal networks are fundamental structures for information processing in the central nervous system. This processing function is severely impaired by abnormal axonal conduction from changes in functional ion channel expression. The evaluation of axonal conduction properties can be effective in the early diagnosis of information-processing abnormalities. However, little is known about functional ion channel expression in axons owing to lack of an appropriate method. In this study, we developed a device to measure changes in axonal conduction properties by selective pharmacological stimulation for the functional evaluation of Na channels expressed in axons. METHODS: Axons of rat cortical neurons were guided across a pair of electrodes through microtunnel structures by employing surface patterning. RESULTS: The developed device detected more than 50 axons while recording for 10 min. The conduction delay along the axons decreased by 22.5% with neuron maturation. Tetrodotoxin and lidocaine (Na channel blockers) increased the conduction delay in a concentration-dependent manner depending on their working concentrations, indicating the effectiveness of the device. Finally, selective Na channel blockers for various Na channel subtypes were used. Phrixotoxin, a Nav1.2 blocker, markedly increased the conduction delay, suggesting that Nav1.2 is functionally expressed in the unmyelinated axons of the cerebral cortex. CONCLUSION: These results show that our device is feasible for the high-throughput functional evaluation of Na channel subtypes in axons. SIGNIFICANCE: The results obtained can contribute to the understanding of the pathogenic mechanisms of neurological diseases that involve changes in the functional expression states of ion channels in axons.

Functional Scaffolding for Brain Implants: Engineered Neuronal Network by Microfabrication and iPSC Technology.

Neuroengineering methods can be effectively used in the design of new approaches to treat central nervous system and brain injury caused by neurotrauma, ischemia, or neurodegenerative disorders. During the last decade, significant results were achieved in the field of implant (scaffold) development using various biocompatible and biodegradable materials carrying neuronal cells for implantation into the injury site of the brain to repair its function. Neurons derived from animal or human induced pluripotent stem (iPS) cells are expected to be an ideal cell source, and induction methods for specific cell types have been actively studied to improve efficacy and specificity. A critical goal of neuro-regeneration is structural and functional restoration of the injury site. The target treatment area has heterogeneous and complex network topology with various types of cells that need to be restored with similar neuronal network structure to recover correct functionality. However, current scaffold-based technology for brain implants operates with homogeneous neuronal cell distribution, which limits recovery in the damaged area of the brain and prevents a return to fully functional biological tissue. In this study, we present a neuroengineering concept for designing a neural circuit with a pre-defined unidirectional network architecture that provides a balance of excitation/inhibition in the scaffold to form tissue similar to that in the injured area using various types of iPS cells. Such tissue will mimic the surrounding niche in the injured site and will morphologically and topologically integrate into the brain, recovering lost function.

Long-Term Developmental Process of the Human Cortex Revealed In Vitro by Axon-Targeted Recording Using a Microtunnel-Augmented Microelectrode Array.

OBJECTIVE: We aimed to develop a method for evaluating developmental changes in the synchronized activity of human induced pluripotent stem cell (hiPSC)-derived neurons without extrinsic signals from feeder astrocytes. METHODS: Microelectrode arrays (MEAs) and microtunnels were fabricated with photolithography and soft lithography. hiPSCs were induced to differentiate into cortical neurons, and seeded to conventional and microtunnel MEAs. Spontaneous activity was recorded every ten days, and spiking and bursting activities were elucidated. RESULTS: First, hiPSC-derived neurons were cultured on conventional MEAs. They formed aggregates and subsequently detached from the culture substrate. Hence, no MEAs showed spontaneous synchronized activity beyond 300 days post-induction. Next, we applied a microtunnel structure designed to keep the axons on the array. Synchronized activity was then recorded from all microtunnel MEAs by 450 days post-induction. The proportion of electrodes showing neural activity was greater than that in conventional MEAs. The activity pattern reached a steady state after approximately 330 days, which may be the maturation time of the human neuronal network. CONCLUSION: The use of a microtunnel MEA enables the monitoring of the long-term development of human neuronal networks of cell populations that are relatively natural given their lack of astrocyte feeders. SIGNIFICANCE: We report a more accurate method for culturing cortical neurons differentiated from hiPSCs, validating their use in elucidating cortical development and pathogenic mechanisms in humans.

Microdevice for Evaluating Ion Channel Expression by Axon-Targeted Recording to Cultured Neurons.

Recording axonal conduction will be a strong tool to continuously evaluate Na channel expression of cultured neurons. However, little is known about the relationship between ion channel expression and axonal conduction velocity. In this study, we aim to develop a method to evaluate the relationship. A microdevice was developed with photo- and soft-lithography. Cortical neurons were cultured, and activity propagating along axons was recorded. After spike sorting, mixed signal from multiple axons were sorted into clusters of individual axons. Axons were treated with non-selective and subtype specific Na channel blockers, and changes in conduction delay were evaluated. TTX and lidocaine increased conduction delay with a different manner, suggesting that the different affinity and binding kinetics can be detected with the device. Moreover, although Nav 1.2 blocker increased the conduction delay and eventually clocked the conduction at around IC50, the other blockers did not. This result suggests that Nav 1.2 is dominant for the conduction along unmyelinated cortical axons. Overall, our device should be a feasible tool for elucidating Na channel properties by axon-targeted recording.