Neuronal Populations Research Articles

Regulation of GABAergic neurotransmission by purinergic receptors in brain physiology and disease.

Purinergic receptors regulate the processing of neural information in the hippocampus and cerebral cortex, structures related to cognitive functions. These receptors are activated when astrocytic and neuronal populations release adenosine triphosphate (ATP) in an autocrine and paracrine manner, following sustained patterns of neuronal activity. The modulation by these receptors of GABAergic transmission has only recently been studied. Through their ramifications, astrocytes and GABAergic interneurons reach large groups of excitatory pyramidal neurons. Their inhibitory effect establishes different synchronization patterns that determine gamma frequency rhythms, which characterize neural activities related to cognitive processes. During early life, GABAergic-mediated synchronization of excitatory signals directs the experience-driven maturation of cognitive development, and dysfunctions concerning this process have been associated with neurological and neuropsychiatric diseases. Purinergic receptors timely modulate GABAergic control over ongoing neural activity and deeply affect neural processing in the hippocampal and neocortical circuitry. Stimulation of A2 receptors increases GABA release from presynaptic terminals, leading to a considerable reduction in neuronal firing of pyramidal neurons. A1 receptors inhibit GABAergic activity but only act in the early postnatal period when GABA produces excitatory signals. P2X and P2Y receptors expressed in pyramidal neurons reduce the inhibitory tone by blocking GABAA receptors. Finally, P2Y receptor activation elicits depolarization of GABAergic neurons and increases GABA release, thus favoring the emergence of gamma oscillations. The present review provides an overall picture of purinergic influence on GABAergic transmission and its consequences on neural processing, extending the discussion to receptor subtypes and their involvement in the onset of brain disorders, including epilepsy and Alzheimer's disease.

Norepinephrine Neurons in the Nucleus of the Solitary Tract Suppress Luteinizing Hormone Secretion in Female Mice.

Stress impairs fertility, at least in part, via inhibition of gonadotropin secretion. Luteinizing hormone (LH) is an important gonadotropin that is released in a pulsatile pattern in males and in females throughout the majority of the ovarian cycle. Several models of stress, including acute metabolic stress, suppress LH pulses via inhibition of neurons in the arcuate nucleus of the hypothalamus that co-express kisspeptin, neurokinin B, and dynorphin (termed KNDy cells) which form the pulse generator. The mechanism for inhibition of KNDy neurons during stress, however, remains a significant outstanding question. Here, we investigated a population of catecholamine neurons in the nucleus of the solitary tract (NTS), marked by expression of the enzyme dopamine beta-hydroxylase (DBH), in female mice. First, we found that a subpopulation of DBH neurons in the NTS are activated (express c-Fos) during metabolic stress. Then, using chemogenetics we determined that activation of these cells is sufficient to suppress LH pulses, augment corticosterone secretion, and induce sickness-like behavior. In subsequent studies, we identified evidence for suppression of KNDy cells (rather than downstream signaling pathways) and determined that the suppression of LH pulses was not dependent on the acute rise in glucocorticoids. Together these data support the hypothesis that DBH cells in the NTS are important for regulation of neuroendocrine and behavioral responses to stress.Significance Statement Stress impairs fertility, at least in part, via inhibition of gonadotropin secretion. The gonadotropin luteinizing hormone (LH) is secreted in a pulsatile pattern in males and females throughout most of the ovarian cycle to support gamete development and sex steroid production in both sexes. Here, we investigated a population of catecholamine neurons in the nucleus of the solitary tract (NTS) for their role in regulation of pulsatile LH secretion. We demonstrate that these neurons are sufficient to suppress pulsatile LH secretion via inhibition of kisspeptin neurons in ovariectomized mice. Moreover, these NTS neurons are also sufficient to augment corticosterone concentrations and induce sickness-like behavior, which raises the possibility that these neurons are important for neuroendocrine and behavioral responses during stress.

Cognitive dysfunction in animal models of human lewy-body dementia

Cognitive impairments are a common feature of synucleinopathies such as Parkinson’s Disease Dementia and Dementia with Lewy Bodies. These pathologies are characterized by accumulation of Lewy bodies and Lewy neurites as well as neuronal cell death. Alpha-synuclein is the main proteinaceous component of Lewy bodies and Lewy neurites. To model these pathologies in vivo, toxins that selectively target certain neuronal populations or different means of inducing alpha-synuclein aggregation can be used. Alpha-synuclein accumulation can be induced by genetic manipulation, viral vector overexpression or the use of preformed fibrils of alpha-synuclein. In this review, we summarize the cognitive impairments associated with different models of synucleinopathies and relevance to observations in human diseases.

Imaging of the superficial white matter in health and disease

Abstract The superficial white matter, the layer of white matter immediately deep to the cortical grey matter, is a highly complex, heterogeneous tissue region comprising dense meshes of neural fibres, a robust population of interstitial neurons, and ongoing glial activity and myelination. It originates from the histologically distinct, developmentally vital subplate in the foetal brain, maintains thalamo-cortical connections throughout adult life, and is a necessary passage for all axons passing between the grey and white matter. Despite these features, the superficial white matter is among the most poorly understood regions of the brain, in part due to its complex makeup and the resulting difficulty of its study. In this review, we present our current knowledge of superficial white matter (SWM) anatomy, development, and response to disease. We discuss the unique challenges encountered in the neuroimaging of this region, including the lack of standard definition and the non-specificity of neuroimaging markers amplified by the complexity of the tissue. We discuss recent innovations and offer potential pathways forward.

Neural activity ramps in frontal cortex signal extended motivation during learning

Learning requires the ability to link actions to outcomes. How motivation facilitates learning is not well understood. We designed a behavioral task in which mice self-initiate trials to learn cue-reward contingencies and found that the anterior cingulate region of the prefrontal cortex (ACC) contains motivation-related signals to maximize rewards. In particular, we found that ACC neural activity was consistently tied to trial initiations where mice seek to leave unrewarded cues to reach reward-associated cues. Notably, this neural signal persisted over consecutive unrewarded cues until reward-associated cues were reached, and was required for learning. To determine how ACC inherits this motivational signal we performed projection-specific photometry recordings from several inputs to ACC during learning. In doing so, we identified a ramp in bulk neural activity in orbitofrontal cortex (OFC)-to-ACC projections as mice received unrewarded cues, which continued ramping across consecutive unrewarded cues, and finally peaked upon reaching a reward-associated cue, thus maintaining an extended motivational state. Cellular resolution imaging of OFC confirmed these neural correlates of motivation, and further delineated separate ensembles of neurons that sequentially tiled the ramp. Together, these results identify a mechanism by which OFC maps out task structure to convey an extended motivational state to ACC to facilitate goal-directed learning.

Neural activity ramps in frontal cortex signal extended motivation during learning.

Learning requires the ability to link actions to outcomes. How motivation facilitates learning is not well understood. We designed a behavioral task in which mice self-initiate trials to learn cue-reward contingencies and found that the anterior cingulate region of the prefrontal cortex (ACC) contains motivation-related signals to maximize rewards. In particular, we found that ACC neural activity was consistently tied to trial initiations where mice seek to leave unrewarded cues to reach reward-associated cues. Notably, this neural signal persisted over consecutive unrewarded cues until reward-associated cues were reached, and was required for learning. To determine how ACC inherits this motivational signal we performed projection-specific photometry recordings from several inputs to ACC during learning. In doing so, we identified a ramp in bulk neural activity in orbitofrontal cortex (OFC)-to-ACC projections as mice received unrewarded cues, which continued ramping across consecutive unrewarded cues, and finally peaked upon reaching a reward-associated cue, thus maintaining an extended motivational state. Cellular resolution imaging of OFC confirmed these neural correlates of motivation, and further delineated separate ensembles of neurons that sequentially tiled the ramp. Together, these results identify a mechanism by which OFC maps out task structure to convey an extended motivational state to ACC to facilitate goal-directed learning.

Role of adaptor protein complexes in generating functionally distinct synaptic vesicle pools.

The synaptic vesicle (SV) cycle ensures the release of neurotransmitters and the replenishment of SVs to sustain neuronal activity. Multiple endocytosis and sorting pathways contribute to the recapture of the SV membrane and proteins after fusion. Adaptor protein (AP) complexes are among the critical components of the SV retrieval machinery. The canonical clathrin adaptor AP2 ensures the replenishment of most SVs across many neuronal populations. An alternative AP1/AP3-dependent process mediates the formation of a subset of SVs that differ from AP2 vesicles in molecular composition and respond preferentially during higher frequency firing. Furthermore, recent studies show that vesicular transporters for different neurotransmitters depend to a different extent on the AP3 pathway and this affects the release properties of the respective neurotransmitters. This review focuses on the current understanding of the AP-dependent molecular and functional diversity among SVs. We also discuss the contribution of these pathways to the regulation of neurotransmitter release across neuronal populations.

Nested compressed co-representations of multiple sequential experiences during sleep.

Animals encounter and remember multiple experiences daily. During sleep, hippocampal neuronal ensembles replay past experiences and preplay future ones. Although most previous studies investigated p/replay of a single experience, it remains unclear how the hippocampus represents many experiences without major interference during sleep. By monitoring hippocampal neuronal ensembles as rats encountered 15 distinct linear track experiences, we uncovered principles for efficient multi-experience compressed p/replay representation. First, we found a serial position effect whereby the earliest and the most recent experiences had the strongest representations. Second, distinct experiences were co-represented in a multiplexed, flickering manner during nested p/replay events, which greatly enhanced the network's representational capacity. Third, spatially contiguous and disjunct track pairs were bound together into contiguous conjunctive representations during sleep. Finally, sequences spanning day-long multi-track experiences were p/replayed at hyper-compressed ratios during sleep. These coding schemes efficiently parallelize, bind and compress multiple sequential representations with reduced interference and enhanced capacity during sleep.

SomaSeg: A robust neuron identification framework for two-photon imaging video.

Accurate neuron identification is fundamental to the analysis of neuronal population dynamics and signal extraction in fluorescence videos. However, several factors such as severe imaging noise, out-of-focus neuropil contamination, and adjacent neuron overlap would impair the performance of neuron identification algorithms and lead to errors in neuron shape and calcium activity extraction, or ultimately compromise the reliability of analysis conclusions. Herein, to address these challenges, we developed a novel cascade framework - SomaSeg that combines Duffing denoising, neuropil contamination defogging and stacked instance differentiating. Compared with the state-of-the-art neuron identification methods, both simulation and actual experimental results demonstrate that SomaSeg framework is robust to noise, insensitive to out-of-focus contamination and effective in dealing with overlapping neurons in actual complex imaging scenarios, providing a widely applicable framework for two-photon video processing.

Brainstem neuronal responses to transcutaneous auricular and cervical vagus nerve stimulation in rats.

Transcutaneous auricular vagus nerve stimulation (taVNS) targets subcutaneous axons in the auricular branch of the vagus nerve at the outer ear. Its non-invasive nature makes it a potential treatment for various disorders. taVNS induces neuromodulatory effects within the nucleus of the solitary tract (NTS), and due to its widespread connectivity, the NTS acts as a gateway to elicit neuromodulation in both higher-order brain regions and other brainstem nuclei (e.g. spinal trigeminal nucleus; Sp5). Our objective was to examine stimulation parameters on single-neuron electrophysiological responses in α-chloralose-anaesthetized Sprague-Dawley rats within NTS and Sp5. taVNS was also compared to traditional cervical VNS (cVNS) on single neuronal activation. Specifically, electrophysiological extracellular recordings were evaluated for a range of frequency and intensity parameters (20-250Hz, 0.5-1.0mA). Neurons were classified as positive, negative or non-responders based on increased activity, decreased activity or no response during stimulation, respectively. Frequency-dependent analysis showed that 20 and 100Hz generated the highest proportion of positive responders in NTS and Sp5 with 1.0mA intensities eliciting the greatest magnitude of response. Comparisons between taVNS and cVNS revealed similar parameter-specific activation for caudal NTS neuronal populations; however, individual neurons showed different activation profiles. The latter suggests that cVNS and taVNS send afferent input to NTS via different neuronal pathways. This study demonstrates differential parameter-specific taVNS responses and begins an investigation of the mechanisms responsible for taVNS modulation. Understanding the neuronal pathways responsible for eliciting neuromodulatory effects will enable more tailored taVNS treatments in various clinical disorders. KEY POINTS: Transcutaneous auricular vagus nerve stimulation (taVNS) offers a non-invasive alternative to invasive cervical vagus nerve stimulation (cVNS) by activating vagal afferents in the ear to induce neuromodulation. Our study evaluated taVNS effects on neuronal firing patterns in the nucleus of the solitary tract (NTS) and spinal trigeminal nucleus (Sp5) and found that 20 and 100Hz notably increased neuronal activity during stimulation in both nuclei. Increasing taVNS intensity not only increased the number of neurons responding in Sp5 but also increased the magnitude of response, suggesting a heightened sensitivity to taVNS compared to NTS. Comparisons between cVNS and taVNS revealed similar overall activation but different responses on individual neurons, indicating distinct neural pathways. These results show parameter-specific and nuclei-specific responses to taVNS and confirm that taVNS can elicit responses comparable to cVNS at the neuronal level, but it does so through different neuronal pathways.

Predicting Grapevine Physiological Parameters Using Hyperspectral Remote Sensing Integrated with Hybrid Convolutional Neural Network and Ensemble Stacked Regression

Predicting Grapevine Physiological Parameters Using Hyperspectral Remote Sensing Integrated with Hybrid Convolutional Neural Network and Ensemble Stacked Regression

Amygdala and cortex relationships during learning of a sensory discrimination task.

During learning of a sensory discrimination task, cortical and sub-cortical regions display complex spatiotemporal dynamics. During learning, both amygdala and cortex link stimulus information to its appropriate association, for example a reward. In addition, both structures are also related to non-sensory parameters such as body movements and licking during the reward period. However, the emergence of cortico-amygdala relationships during learning is largely unknown. To study this, we combined wide-field cortical imaging with fiber photometry to simultaneously record cortico-amygdala population dynamics as male mice learn a whisker-dependent go/no-go task. We were able to simultaneously record neuronal populations from the posterior cortex and either the basolateral amygdala (BLA) or central medial amygdala (CEM). Prior to learning, somatosensory and associative cortex responded during sensation, while amygdala areas did not show significant responses. As mice became experts, amygdala responses emerged early during the sensation period, increasing in CEM, while decreasing in BLA. Interestingly, amygdala and cortical responses were associated with task-related body movement, displaying significant responses ∼200 ms before movement initiation which led to licking for the reward. A correlation analysis between cortex and amygdala revealed negative and positive correlation with BLA and CEM respectively, only in the expert case. These results imply that learning induces an involvement of cortex and amygdala which may aid to link sensory stimuli with appropriate associations.Significance Statement Levitan and Gilad study neuronal dynamics in cortex and amygdala as mice learn a sensory discrimination task. They find that amygdala areas display opposing responses only after the mice learn the task. In contrast cortical areas display responses both before and after learning. These results imply that learning induces an involvement of amygdala and cortical areas in order to optimally link sensory stimuli with appropriate associations.

Enterovirus-A71 Preferentially Infects and Replicates in Human Motor Neurons, Inducing Neurodegeneration by Ferroptosis

Enterovirus A71 (EV-A71) causes Hand, Foot, and Mouth Disease and has been clinically associated with neurological complications. However, there is a lack of relevant models to elucidate the neuropathology of EV-A71 and its mechanism, as the current models mainly utilize animal models or immortalized cell lines. In this study, we established a human motor neuron model for EV-A71 infection. Single cell transcriptomics of a mixed neuronal population reveal higher viral RNA load in motor neurons, suggesting higher infectivity and replication of EV-A71 in motor neurons. The elevated RNA load in motor neurons correlates with the downregulation of ferritin-encoding genes. Subsequent analysis confirms that neurons infected with EV-A71 undergo ferroptosis, as evidenced by increased levels of labile Fe2+ and peroxidated lipids. Notably, the Fe2+ chelator Deferoxamine improves mitochondrial function and promotes survival of motor neurons by 40% after EV-A71 infection. These findings deepen understanding of the molecular pathogenesis of EV-A71 infection, providing insights which suggest that improving mitochondrial respiration and inhibition of ferroptosis can mitigate the impact of EV-A71 infection in the central nervous system.

Touch and slippage detection in robotic hands with spiking neural networks

Significant research efforts have focused on advancing upper limb prostheses, addressing issues such as dexterity, embodiment, weight, and resistance. These key features require enhancements to mitigate prosthesis abandonment. Sensory feedback is a vital feature for improving the dexterity and embodiment of prostheses for patients. Current techniques utilize electronic signals for feedback to control systems and to partially restore tactile sensations to amputees. However, it has already been demonstrated that, in order to elicit responses from biological neurons signals must be converted into neuromorphic tactile information. Most of those demonstrations relied on algorithmic implementations of mechanoreceptor and neuron models running on classic processor cores. However, integrating real-time encoding and control strategies into such architectures is challenging due to computational complexity and high power usage. A prospective solution is to increasingly incorporate neuromorphic technologies for prosthesis sensing and control. In this work, we demonstrate the feasibility of using spiking neural networks for performing two key functions in controlling upper limb prosthesis: touch and slippage detection. We found that a simple two-layered architecture with a few tens of neurons is sufficient to identify slip and touch with nearly 100% accuracy. The first layer consists of a heterogeneous population of neurons with their parameters adjusted to model slowly and fast-adapting type 1 mechanoreceptors. An output layer classifies touch or slip events. Furthermore, simulations showed that implementing the network in ultra-low-power neuromorphic hardware, such as Loihi, has the potential to reduce power consumption by up to 162 times, with respect to a von Neumann processor.

Electrophysiological activity pattern of mouse hippocampal CA1 and dentate gyrus under isoflurane anesthesia

General anesthesia can impact a patient’s memory and cognition by influencing hippocampal function. The CA1 and dentate gyrus (DG), serving as the primary efferent and gateway of the hippocampal trisynaptic circuit facilitating cognitive learning and memory functions, exhibit significant differences in cellular composition, molecular makeup, and responses to various stimuli. However, the effects of isoflurane-induced general anesthesia on CA1 and DG neuronal activity in mice are not well understood. In this study, utilizing electrophysiological recordings, we examined neuronal population dynamics and single-unit activity (SUA) of CA1 and DG in freely behaving mice during natural sleep and general anesthesia. Our findings reveal that isoflurane anesthesia shifts local field potential (LFP) to delta frequency and reduces the firing rate of SUA in both CA1 and DG, compared to wakefulness. Additionally, the firing rates of DG neurons are significantly lower than CA1 neurons during isoflurane anesthesia, and the recovery of theta power is slower in DG than in CA1 during the transition from anesthesia to wakefulness, indicating a stronger and more prolonged impact of isoflurane anesthesia on DG. This work presents a suitable approach for studying brain activities during general anesthesia and provides evidence for distinct effects of isoflurane anesthesia on hippocampal subregions.

Noise Enhances Excitability of a Neuronal Population with Heterogeneous Excitatory Neurons

AbstractCortical excitability is sensitive to noise perturbations despite homeostatic regulation. However, modeling the effect of noise in a heterogeneous neuronal population is a mathematical challenge. Using a mean‐field model of a randomly connected excitatory population, we investigated how noise affects excitability at the resting state. Stable equilibrium analysis revealed that increasing noise intensity enhances excitability, indexed by synaptic conductance. Further, this enhancement disappeared when excitability is sufficiently high due to strong mean input current, but not influenced by the connection probability of the population. Finally, the mechanism of noise‐induced enhancement was explained by eigenvalues moving toward the imaginary axis. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Optimal gamma-band entrainment of visual cortex.

Visual entrainment is a powerful and widely used research tool to study visual information processing in the brain. While many entrainment studies have focused on frequencies around 14-16 Hz, there is renewed interest in understanding visual entrainment at higher frequencies (e.g., gamma-band entrainment). Notably, recent groundbreaking studies have demonstrated that gamma-band visual entrainment at 40 Hz may have therapeutic effects in the context of Alzheimer's disease (AD) by stimulating specific neural ensembles, which utilize GABAergic signaling. Despite such promising findings, few studies have investigated the optimal parameters for gamma-band visual entrainment. Herein, we examined whether visual stimulation at 32, 40, or 48 Hz produces optimal visual entrainment responses using high-density magnetoencephalography (MEG). Our results indicated strong entrainment responses localizing to the primary visual cortex in each condition. Entrainment responses were stronger for 32 and 40 Hz relative to 48 Hz, indicating more robust synchronization of neural ensembles at these lower gamma-band frequencies. In addition, 32 and 40 Hz entrainment responses showed typical patterns of habituation across trials, but this effect was absent for 48 Hz. Finally, connectivity between visual cortex and parietal and prefrontal cortices tended to be strongest for 40 relative to 32 and 48 Hz entrainment. These results suggest that neural ensembles in the visual cortex may resonate at around 32 and 40 Hz and thus entrain more readily to photic stimulation at these frequencies. Emerging AD therapies, which have focused on 40 Hz entrainment to date, may be more effective at lower relative to higher gamma frequencies, although additional work in clinical populations is needed to confirm these findings. PRACTITIONER POINTS: Gamma-band visual entrainment has emerged as a therapeutic approach for eliminating amyloid in Alzheimer's disease, but its optimal parameters are unknown. We found stronger entrainment at 32 and 40 Hz compared to 48 Hz, suggesting neural ensembles prefer to resonate around these relatively lower gamma-band frequencies. These findings may inform the development and refinement of innovative AD therapies and the study of GABAergic visual cortical functions.

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.

Lineage-tracing reveals an expanded population of NPY neurons in the inferior colliculus.

Growing evidence suggests that neuropeptide signaling shapes auditory computations. We previously showed that neuropeptide Y (NPY) is expressed in the inferior colliculus (IC) by a population of GABAergic stellate neurons and that NPY regulates the strength of local excitatory circuits in the IC. NPY neurons were initially characterized using the NPY-hrGFP mouse, in which humanized renilla Green Fluorescent Protein (hrGFP) expression indicates NPY expression at the time of assay, i.e., an expression-tracking approach. However, studies in other brain regions have shown that NPY expression can vary based on several factors, suggesting that the NPY-hrGFP mouse might miss NPY neurons not expressing NPY on the experiment date. Here, we hypothesized that neurons with the ability to express NPY represent a larger population of IC GABAergic neurons than previously reported. To test this hypothesis, we used a lineage-tracing approach to irreversibly tag neurons that expressed NPY at any point prior to the experiment date. We then compared the physiological and anatomical features of neurons labeled with this lineage-tracing approach to our prior data set, revealing a larger population of NPY neurons than previously found. In addition, we used optogenetics to test the local connectivity of NPY neurons and found that NPY neurons routinely provide inhibitory synaptic input to other neurons in the ipsilateral IC. Together, our data expand the definition of NPY neurons in the IC, suggest that NPY expression might be dynamically regulated in the IC, and provide functional evidence that NPY neurons form local inhibitory circuits in the IC.

Integrative Analysis of Long Isoform Sequencing and Functional Data Identifies Distinct Cortical Layer Neuronal Subtypes Derived from Human iPSCs.

Generation of human induced pluripotent stem cells (iPSCs) through reprogramming was a transformational change in the field of regenerative medicine that led to new possibilities for drug discovery and cell replacement therapy. Several protocols have been established to differentiate hiPSCs into neuronal lineages. However, low differentiation efficiency is one of the major drawbacks of these approaches. Here, we compared the efficiency of two methods of neuronal differentiation from iPSCs cultured in two different culture media, StemFlex Medium (SFM) and Essential 8 Medium (E8M). The results indicated that iPSCs cultured in E8M efficiently generated different types of neurons in a shorter time and without the growth of undifferentiated non-neuronal cells in the culture as compared to those generated from iPSCs in SFM. Furthermore, these neurons were validated as functional units immunocytochemically by confirming the expression of mature neuronal markers (i.e., NeuN, Beta tubulin, and Synapsin I), and whole-cell patch-clamp recordings. Long-read single-cell RNA sequencing confirms the presence of upper and deep layer cortical layer excitatory and inhibitory neuronal subtypes in addition to small populations of GABAergic neurons in day 30 neuronal cultures. Pathway analysis indicated that our protocol triggers the signaling transcriptional networks important for the process of neuronal differentiation in vivo.