Neural Circuits Research Articles

Selective consolidation of learning and memory via recall-gated plasticity.

In a variety of species and behavioral contexts, learning and memory formation recruits two neural systems, with initial plasticity in one system being consolidated into the other over time. Moreover, consolidation is known to be selective; that is, some experiences are more likely to be consolidated into long-term memory than others. Here, we propose and analyze a model that captures common computational principles underlying such phenomena. The key component of this model is a mechanism by which a long-term learning and memory system prioritizes the storage of synaptic changes that are consistent with prior updates to the short-term system. This mechanism, which we refer to as recall-gated consolidation, has the effect of shielding long-term memory from spurious synaptic changes, enabling it to focus on reliable signals in the environment. We describe neural circuit implementations of this model for different types of learning problems, including supervised learning, reinforcement learning, and autoassociative memory storage. These implementations involve synaptic plasticity rules modulated by factors such as prediction accuracy, decision confidence, or familiarity. We then develop an analytical theory of the learning and memory performance of the model, in comparison to alternatives relying only on synapse-local consolidation mechanisms. We find that recall-gated consolidation provides significant advantages, substantially amplifying the signal-to-noise ratio with which memories can be stored in noisy environments. We show that recall-gated consolidation gives rise to a number of phenomena that are present in behavioral learning paradigms, including spaced learning effects, task-dependent rates of consolidation, and differing neural representations in short- and long-term pathways.

Development of neuronal timescales in human cortical organoids and rat hippocampus dissociated cultures.

To support complex cognition, neuronal circuits must integrate information across multiple temporal scales, ranging from milliseconds to decades. Neuronal timescales describe the duration over which activity within a network persists, posing a putative explanatory mechanism for how information might be integrated over multiple temporal scales. Little is known about how timescales develop in human neural circuits or other model systems, limiting insight into how the functional dynamics necessary for cognition emerge. In our work, we show that neuronal timescales develop in a non-linear fashion in both human cortical organoids and dissociated rat hippocampus cultures. We use spectral parameterization of spiking activity to extract an estimate of neuronal timescale that is unbiased by co-evolving oscillations. Cortical organoid timescales begin to increase around month 6 post-differentiation. We complement these findings with an analysis of timescales in rodent hippocampal dissociated cultures over development and see that timescales decrease from in vitro days 13-23 before stabilizing. We speculate that cortical organoid development over the duration studied here reflects an earlier stage of a generalized developmental timeline in contrast to the rodent hippocampal cultures, potentially accounting for differences in timescale developmental trajectories. The fluctuation of timescales might be an important developmental feature that reflects the changing complexity and information capacity in developing neuronal circuits.

Active Neural Interface Circuits and Systems for Selective Control of Peripheral Nerves: A Review.

Interfaces with peripheral nerves have been widely developed to enable bioelectronic control of neural activity. Peripheral nerve neuromodulation shows great potential in addressing motor dysfunctions, neurological disorders, and psychiatric conditions. The integration of high-density neural electrodes with stimulation and recording circuits poses a challenge in the design of neural interfaces. Recent advances in active electrode strategies have achieved improved reliability and performance by implementing in-situ control, stimulation, and recording of neural fibers. This paper presents an overview of state-of-the-art neural interface systems that comprise a range of neural electrodes, neurostimulators, and bio-amplifier circuits, with a special focus on interfaces for the peripheral nerves. A discussion on the efficacy of active electrode systems and recommendations for future directions conclude this paper.

A Systematic Review and Bayesian Meta-Analysis of Acoustic Measures of Prosody in Parkinson's Disease.

Linguistic prosody is affected in Parkinson's disease (PD), which implicates the basal ganglia's role in the production of prosody. However, there is no recent systematic synthesis of the available acoustic evidence of prosodic impairment in PD. This study aimed to identify the acoustic features of linguistic prosody that are consistently affected in PD. The authors systematically reviewed articles that reported acoustic features of prosodic production in PD. Articles focused on fundamental frequency (F0) and its variability, intensity and its variability, speech and articulation rate, and pause duration and ratio. From a total of 648 records identified, 36 met criteria for inclusion and exclusion. For each acoustic measurement and task, data from people with PD (PwPD) were compared with those from controls to extract effect sizes. Pooled effect sizes were estimated using robust Bayesian hierarchical regression models. PD was associated with decreased F0 variability and increased pause duration. There was limited evidence of reduced intensity variability and speech rate in PwPD. No evidence was found to suggest that PD affects articulation rate or pause ratio. The primary acoustic parameters of prosody affected by PD are F0 variability and pause duration. The identification of these acoustic parameters has important clinical implications for the selection of PD management strategies. The association of F0 variability and pause duration with PD suggests that the neural circuits controlling these parameters are at least partly shared and might include the basal ganglia. While the current study focused on the phonetic realization of prosodic cues, future studies should examine whether and how PD affects prosody at higher levels of processing. https://doi.org/10.23641/asha.25892923.

Estimating forest aboveground biomass in tropical forests with Landsat time-series data and recurrent neural network

ABSTRACT The insensitivity and saturation of sensor signals significantly limit the application of Landsat data on estimating biomass in tropical forests with a high level of biomass. The previous studies with single-date Landsat data have lower accuracies in tropical forests compared to boreal and temperate forests. Landsat time-series data provide a promising opportunity to improve the accuracy by enhancing the relationship between Landsat spectral reflectance and forest aboveground biomass with disturbance and recovery dynamics. Compared to the single-date image, Landsat time-series data can capture abrupt spectral changes (e.g. harvesting and fire) and show the regrowth process in forested pixels. However, very limited studies take advantage of Landsat time-series data to estimate aboveground biomass in tropical forests. Recurrent neural networks (RNNs) are powerful deep learning techniques to capture time dependencies in sequence data. However, the application of RNNs in estimating forest biomass has not been explored yet. Therefore, we integrate the long short-term memory network (LSTM) and the fully connected neuron network (FNN) to establish an RNN-FNN model for estimating forest biomass with Landsat time-series imagery and airborne LiDAR data. We compared the proposed model with the commonly used Random Forest model and linear regression model which are implemented with single-date data. The results show that the RNN-FNN model can deal with Landsat time-series sequence data to enhance the relationship between Landsat spectral reflectance and forest aboveground biomass. The proposed model achieves the R2 of 0.63 and RMSE of 25.5 Mg/ha, which significantly outperformed the Random Forest model and linear regression model with Landsat single-date data. This study demonstrates the value of RNN and Landsat time-series imagery in estimating forest biomass for tropical forests.

Acylhydrazone Derivative A5 Promotes Neurogenesis by Up-Regulating Neurogenesis-Related Genes and Inhibiting Cell-Cycle Progression in Neural Stem/Progenitor Cells

Adult neurogenesis involves the generation of functional neurons from neural progenitor cells, which have the potential to complement and restore damaged neurons and neural circuits. Therefore, the development of drugs that stimulate neurogenesis represents a promising strategy in stem cell therapy and neural regeneration, greatly facilitating the reconstruction of neural circuits in cases of neurodegeneration and brain injury. Our study reveals that compound A5, previously designed and synthesized by our team, exhibits remarkable neuritogenic activities, effectively inducing neurogenesis in neural stem/progenitor cells (NSPCs). Subsequently, transcriptome analysis using high-throughput Illumina RNA-seq technology was performed to further elucidate the underlying molecular mechanisms by which Compound A5 promotes neurogenesis. Notably, comparative transcriptome analysis showed that the up-regulated genes were mainly associated with neurogenesis, and the down-regulated genes were mainly concerned with cell cycle progression. Furthermore, we confirmed that Compound A5 significantly affected the expression of transcription factors related to neurogenesis and cell cycle regulatory proteins. Collectively, these findings identify a new compound with neurogenic activity and may provide insights into drug discovery for neural repair and regeneration.

Biophysical neural adaptation mechanisms enable artificial neural networks to capture dynamic retinal computation

Adaptation is a universal aspect of neural systems that changes circuit computations to match prevailing inputs. These changes facilitate efficient encoding of sensory inputs while avoiding saturation. Conventional artificial neural networks (ANNs) have limited adaptive capabilities, hindering their ability to reliably predict neural output under dynamic input conditions. Can embedding neural adaptive mechanisms in ANNs improve their performance? To answer this question, we develop a new deep learning model of the retina that incorporates the biophysics of photoreceptor adaptation at the front-end of conventional convolutional neural networks (CNNs). These conventional CNNs build on ’Deep Retina,’ a previously developed model of retinal ganglion cell (RGC) activity. CNNs that include this new photoreceptor layer outperform conventional CNN models at predicting male and female primate and rat RGC responses to naturalistic stimuli that include dynamic local intensity changes and large changes in the ambient illumination. These improved predictions result directly from adaptation within the phototransduction cascade. This research underscores the potential of embedding models of neural adaptation in ANNs and using them to determine how neural circuits manage the complexities of encoding natural inputs that are dynamic and span a large range of light levels.

Electrophysiological responses to appetitive and consummatory behavior in the rostral nucleus tractus solitarius in awake, unrestrained rats

IntroductionAs the intermediate nucleus in the brainstem receiving information from the tongue and transmitting information upstream, the rostral portion of the nucleus tractus solitarius (rNTS) is most often described as a “taste relay”. Although recent evidence implicates the caudal NTS in a broad neural circuit involved in regulating ingestion, there is little information about how cells in the rNTS respond when an animal is eating solid food.MethodsSingle cells in the rNTS were recorded in awake, unrestrained rats as they explored and ate solid foods (Eating paradigm) chosen to correspond to the basic taste qualities: milk chocolate for sweet, salted peanuts for salty, Granny Smith apples for sour and broccoli for bitter. A subset of cells was also recorded as the animal licked exemplars of the five basic taste qualities: sucrose, NaCl, citric acid, quinine and MSG (Lick paradigm).ResultsMost cells were excited by exploration of a food-filled well, sometimes responding prior to contact with the food. In contrast, cells that were excited by food well exploration became significantly less active while the animal was eating the food. Most cells were broadly tuned across foods, and those cells that were recorded in both the Lick and Eating paradigms showed little correspondence in their tuning across paradigms.DiscussionThe preponderance of robust responses to the appetitive versus the consummatory phase of ingestion suggests that multimodal convergence onto cells in the rNTS may be used in decision making about ingestion.

Fluoxetine Rescues Excessive Myelin Formation and Psychological Behaviors in a Murine PTSD Model.

Posttraumatic stress disorder (PTSD) is a complex mental disorder notable for traumatic experience memory. Although current first-line treatments are linked with clinically important symptom reduction, a large proportion of patients retained to experience considerable residual symptoms, indicating pathogenic mechanism should be illustrated further. Recent studies reported that newly formed myelin could shape neural circuit function and be implicated in fear memory preservation. However, its role in PTSD remains to be elucidated. In this study, we adopted a restraint stress-induced PTSD mouse model and found that PTSD-related neuropsychiatric symptoms were accompanied by increased myelination in the posterior parietal cortex and hippocampus. Fluoxetine, but not risperidone or sertraline, has a more profound rescue effect on neuropsychological behaviors and myelin abnormalities. Further mechanistic experiments revealed that fluoxetine could directly interfere with oligodendroglial differentiation by upregulating Wnt signaling. Our data demonstrated the correlation between PTSD and abnormal myelination, suggesting that the oligodendroglial lineage could be a target for PTSD treatment.

Conversion Factor Estimation of Stacked Eucalypt Timber Using Supervised Image Classification with Artificial Neural Networks

Stacked timber is quantified in-store units and then adjusted with a conversion factor for volume estimation in cubic meters, which is important for the wood trade in South America. However, measuring large quantities accurately can be challenging. Digital image processing and artificial intelligence advancements offer promising solutions, making research in this area increasingly attractive. This study aims to estimate conversion factors of stacked Eucalyptus grandis timber using supervised image classification with Artificial Neuronal Network (ANN). Measured data and photographs from an experiment involving thirty stacks of timber were used to achieve this. The conversion factor was determined using photographic methods that involved the applications of equidistant points and ANN and subsequently validated with values observed through the manual method. The ANN method produced more accurate conversion factor estimates than the equidistant points method. Approximately 97% of the ANN estimates were within the ±1% error class, even when using low-resolution digital photographs.

Modeling Normal and Abnormal Circuit Development with Recurrent Neural Networks.

Neural development must construct neural circuits that can perform the computations necessary for survival. However, many theoretical models of development do not explicitly address the computational goals of the resulting networks, or computations that evolve in time. Recurrent neural networks (RNNs) have recently come to prominence as both models of neural circuit computation and building blocks of powerful artificial intelligence systems. Here, we review progress in using RNNs for understanding how developmental processes lead to effective computations, and how abnormal development disrupts these computations.

Astrocytes facilitate gabazine-evoked electrophysiological hyperactivity and distinct biochemical responses in mature neuronal cultures.

Gamma-aminobutyric acid (GABA) is the principal inhibitory neurotransmitter in the adult brain that binds to GABA receptors and hyperpolarizes the postsynaptic neuron. Gabazine acts as a competitive antagonist to type A GABA receptors (GABAAR), thereby causing diminished neuronal hyperpolarization and GABAAR-mediated inhibition. However, the biochemical effects and the potential regulatory role of astrocytes in this process remain poorly understood. To address this, we investigated the neuronal responses of gabazine in rat cortical cultures containing varying ratios of neurons and astrocytes. Electrophysiological characterization was performed utilizing microelectrode arrays (MEAs) with topologically controlled microcircuit cultures that enabled control of neuronal network growth. Biochemical analysis of the cultures was performed using traditional dissociated cultures on coverslips. Our study indicates that, upon gabazine stimulation, astrocyte-rich neuronal cultures exhibit elevated electrophysiological activity and tyrosine phosphorylation of tropomyosin receptor kinase B (TrkB; receptor for brain-derived neurotrophic factor), along with distinct cytokine secretion profiles. Notably, neurons lacking proper astrocytic support were found to experience synapse loss and decreased mitogen-activated protein kinase (MAPK) phosphorylation. Furthermore, astrocytes contributed to neuronal viability, morphology, vascular endothelial growth factor (VEGF) secretion, and overall neuronal network functionality, highlighting the multifunctional role of astrocytes.

SUMOylation of nuclear receptor Nor1/NR4A3 coordinates microtubule cytoskeletal dynamics and stability in neuronal cells

BackgroundNor1/NR4A3 is a member of the NR4A subfamily of nuclear receptors that play essential roles in regulating gene expression related to development, cell homeostasis and neurological functions. However, Nor1 is still considered an orphan receptor, as its natural ligand remains unclear for mediating transcriptional activation. Yet other activation signals may modulate Nor1 activity, although their precise role in the development and maintenance of the nervous system remains elusive.MethodsWe used transcriptional reporter assays, gene expression profiling, protein turnover measurement, and cell growth assays to assess the functional relevance of Nor1 and SUMO-defective variants in neuronal cells. SUMO1 and SUMO2 conjugation to Nor1 were assessed by immunoprecipitation. Tubulin stability was determined by acetylation and polymerization assays, and live-cell fluorescent microscopy.ResultsHere, we demonstrate that Nor1 undergoes SUMO1 conjugation at Lys-89 within a canonical ψKxE SUMOylation motif, contributing to the complex pattern of Nor1 SUMOylation, which also includes Lys-137. Disruption of Lys-89, thereby preventing SUMO1 conjugation, led to reduced Nor1 transcriptional competence and protein stability, as well as the downregulation of genes involved in cell growth and metabolism, such as ENO3, EN1, and CFLAR, and in microtubule cytoskeleton dynamics, including MAP2 and MAPT, which resulted in reduced survival of neuronal cells. Interestingly, Lys-89 SUMOylation was potentiated in response to nocodazole, a microtubule depolymerizing drug, although this was insufficient to rescue cells from microtubule disruption despite enhanced Nor1 gene expression. Instead, Lys-89 deSUMOylation reduced the expression of microtubule-severing genes like KATNA1, SPAST, and FIGN, and enhanced α-tubulin cellular levels, acetylation, and microfilament organization, promoting microtubule stability and resistance to nocodazole. These effects contrasted with Lys-137 SUMOylation, suggesting distinct regulatory mechanisms based on specific Nor1 input SUMOylation signals.ConclusionsOur study provides novel insights into Nor1 transcriptional signaling competence and identifies a hierarchical mechanism whereby selective Nor1 SUMOylation may govern neuronal cytoskeleton network dynamics and resistance against microtubule disturbances, a condition strongly associated with neurodegenerative diseases.

Astrocytic Neuroligin-3 influences gene expression and social behavior, but is dispensable for synapse number.

Neuroligin-3 (Nlgn3) is an autism-associated cell-adhesion molecule that interacts with neurexins and is robustly expressed in both neurons and astrocytes. Neuronal Nlgn3 is an essential regulator of synaptic transmission but the function of astrocytic Nlgn3 is largely unknown. Given the high penetrance of Nlgn3 mutations in autism and the emerging role of astrocytes in neuropsychiatric disorders, we here asked whether astrocytic Nlgn3 might shape neural circuit properties in the cerebellum similar to neuronal Nlgn3. Imaging of tagged Nlgn3 protein produced by CRISPR/Cas9-mediated genome editing showed that Nlgn3 is enriched in the cell body but not the fine processes of cerebellar astrocytes (Bergmann glia). Astrocyte-specific knockout of Nlgn3 did not detectably alter the number of synapses, synaptic transmission, or astrocyte morphology in mouse cerebellum. However, spatial transcriptomic analyses revealed a significant shift in gene expression among multiple cerebellar cell types after the deletion of astrocytic Nlgn3. Hence, in contrast to neuronal Nlgn3, astrocytic Nlgn3 in the cerebellum is not involved in shaping synapses but may modulate gene expression in specific brain areas.

Detection of memory engrams in mammalian neuronal circuits.

It has long been assumed that activity patterns persist in neuronal circuits after they are first experienced, as part of the process of information processing and storage by the brain. However, these "reverberations" of current activity have not been directly observed on a single neuron level in a mammalian system. Here we demonstrate that specific induced activity patterns are retained in mature cultured hippocampal neuronal networks. Neurons within the network are induced to fire at a single frequency or in a more complex pattern containing two distinct frequencies. After the stimulation was stopped, the subsequent neuronal activity of hundreds of neurons in the network was monitored. In the case of single-frequency stimulation, it was observed that many of the neurons continue to fire at the same frequency that they were stimulated to fire at. Using a Recurrent Neural Network (RNN) trained to detect specific, more complex patterns, we found that the multiple-frequency stimulation patterns were also retained within the neuronal network. Moreover, it appears that the component frequencies of the more complex patterns are stored in different populations of neurons and neuron subtypes.Significance Statement The existence of memory engrams, or reverberations of recently experienced activity patterns, has long been supposed but never directly demonstrated in mammalian neuronal networks. Through the use of highly accessible cultured neuronal networks grown on silicon wafers, stimulated to fire in user-defined patterns using photoconductive stimulation, we have demonstrated their existence and established a paradigm for the analysis of the microcircuitry involved.

The Clinical Impact of Real-Time fMRI Neurofeedback on Emotion Regulation: A Systematic Review

Emotion dysregulation has long been considered a key symptom in multiple psychiatric disorders. Difficulties in emotion regulation have been associated with neural dysregulation in fronto-limbic circuits. Real-time fMRI-based neurofeedback (rt-fMRI-NFB) has become increasingly popular as a potential treatment for emotional dysregulation in psychiatric disorders, as it is able to directly target the impaired neural circuits. However, the clinical impact of these rt-fMRI-NFB protocols in psychiatric populations is still largely unknown. Here we provide a comprehensive overview of primary studies from 2010 to 2023 that used rt-fMRI-NFB to target emotion regulation. We assessed 41 out of 4001 original studies for methodological quality and risk of bias and synthesised concerning the frequency of significant rt-fMRI-NFB-related effects on the neural and behaviour level. Successful modulation of brain activity was reported in between 25 and 50 percent of study samples, while neural effects in clinical samples were more diverse than in healthy samples. Interestingly, the frequency of rt-fMRI-NFB-related behavioural improvement was over 75 percent in clinical samples, while healthy samples showed behavioural improvements between 0 and 25 percent. Concerning clinical subsamples, rt-fMRI-NFB-related behavioural improvement was observed in up to 100 percent of major depressive disorder (MDD) and post-traumatic stress disorder (PTSD) samples. Substance use samples showed behavioural benefits ranging between 50 and 75 percent. Neural effects appeared to be less frequent than behavioural improvements: most neural outcomes ranged between 25 and 50 percent for MDD and substance use and between 0 and 25 percent for PTSD. Using multiple individualised regions of interest (ROIs) for rt-fMRI-NFB training resulted in more frequent behavioural benefits than rt-fMRI-NFB solely based on the amygdala or the prefrontal cortex. While a significant improvement in behavioural outcomes was reported in most clinical studies, the study protocols were heterogeneous, which limits the current evaluation of rt-fMRI-NFB as a putative treatment for emotional dysregulation.

Sex differences in neural projections of fear memory processing in mice and humans.

It remains unexplored in the field of fear memory whether functional neuronal connectivity between two brain areas is necessary for one sex but not the other. Here, we show that chemogenetic silencing of centromedial (CeM)-Tac2 fibers in the lateral posterior BNST (BNSTpl) decreased fear memory consolidation in male mice but not females. Optogenetic excitation of CeM-Tac2 fibers in the BNSTpl exhibited enhanced inhibitory postsynaptic currents in males compared to females. In vivo calcium imaging analysis revealed a sex-dimorphic fear memory engram in the BNSTpl. Furthermore, in humans, the single-nucleotide polymorphism (SNP) in the Tac2 receptor (rs2765) (TAC3R) decreased CeM-BNST connectivity in a fear task, impaired fear memory consolidation, and increased the expression of the TAC3R mRNA in AA-carrier men but not in women. These sex differences in critical neuronal circuits underlying fear memory formation may be relevant to human neuropsychiatric disorders with fear memory alterations such as posttraumatic stress disorder.

The astrocyte α1A-adrenoreceptor is a key component of the neuromodulatory system in mouse visual cortex.

Noradrenaline (norepinephrine) is known to modulate many physiological functions and behaviors. In this study, we tested to what extent astrocytes, a type of glial cell, participate in noradrenergic signaling in mouse primary visual cortex (V1). Astrocytes are essential partners of neurons in the central nervous system. They are central to brain homeostasis, but also dynamically regulate neuronal activity, notably by relaying and regulating neuromodulator signaling. Indeed, astrocytes express receptors for multiple neuromodulators, including noradrenaline, but the extent to which astrocytes are involved in noradrenergic signaling remains unclear. To test whether astrocytes are involved in noradrenergic neuromodulation in mice, we employed both short hairpin RNA mediated knockdown as well as pharmacological manipulation of the major noradrenaline receptor in astrocytes, the α1A-adrenoreceptor. Using acute brain slices, we found that the astrocytic α1A-adrenoreceptor subtype contributes to the generation of large intracellular Ca2+ signals in visual cortex astrocytes, which are generally thought to underlie astrocyte function. To test if reduced α1A-adrenoreceptor signaling in astrocytes affected the function of neuronal circuits in V1, we used both patch-clamp and field potential recordings. These revealed that noradrenergic signaling through the astrocyte α1A-adrenoreceptor is important to not only modulate synaptic activity but also to regulate plasticity in V1, through the potentiation of synaptic responses in circuits involved in visual information processing.

Sex differences in neural projections of fear memory processing in mice and humans.

It remains unexplored in the field of fear memory whether functional neuronal connectivity between two brain areas is necessary for one sex but not the other. Here, we show that chemogenetic silencing of centromedial (CeM)-Tac2 fibers in the lateral posterior BNST (BNSTpl) decreased fear memory consolidation in male mice but not females. Optogenetic excitation of CeM-Tac2 fibers in the BNSTpl exhibited enhanced inhibitory postsynaptic currents in males compared to females. In vivo calcium imaging analysis revealed a sex-dimorphic fear memory engram in the BNSTpl. Furthermore, in humans, the single-nucleotide polymorphism (SNP) in the Tac2 receptor (rs2765) (TAC3R) decreased CeM-BNST connectivity in a fear task, impaired fear memory consolidation, and increased the expression of the TAC3R mRNA in AA-carrier men but not in women. These sex differences in critical neuronal circuits underlying fear memory formation may be relevant to human neuropsychiatric disorders with fear memory alterations such as posttraumatic stress disorder.

Amniotic Membrane-Derived Multichannel Hydrogels for Neural Tissue Repair.

In the pursuit of advancing neural tissue regeneration, biomaterial scaffolds have emerged as promising candidates, offering potential solutions for nerve disruptions. Among these scaffolds, multichannel hydrogels, characterized by meticulously designed micrometer-scale channels, stand out as instrumental tools for guiding axonal growth and facilitating cellular interactions. This study explores the innovative application of human amniotic membranes modified with methacryloyl domains (AMMA) in neural stem cell (NSC) culture. AMMA hydrogels, possessing a tailored softness resembling the physiological environment, are prepared in the format of multichannel scaffolds to simulate native-like microarchitecture of nerve tracts. Preliminary experiments on AMMA hydrogel films showcase their potential for neural applications, demonstrating robust adhesion, proliferation, and differentiation of NSCs without the need for additional coatings. Transitioning into the 3D realm, the multichannel architecture fosters intricate neuronal networks guiding neurite extension longitudinally. Furthermore, the presence of synaptic vesicles within the cellular arrays suggests the establishment of functional synaptic connections, underscoring the physiological relevance of the developed neuronal networks. This work contributes to the ongoing efforts to find ethical, clinically translatable, and functionally relevant approaches for regenerative neuroscience.