The fraction of cortical GABAergic neurons is constant from near the start of cortical neurogenesis to adulthood

Construction of Multicellular Neural Tissue Using Three-Dimensional Printing Technology: Cell Interaction

The study of the human nervous system remains challenging due to its inherent complexity and difficulty in obtaining original samples. Three-dimensional (3D) bioprinting is a rapidly evolving technology in the field of tissue engineering that has made significant contributions to several disciplines, including neuroscience. In order to more accurately reflect the intricate multicellular milieu of the in vivo environment, an increasing number of studies have commenced experimentation with the coprinting of diverse cell types. This article provides an overview of technical details and the application of 3D bioprinting with multiple cell types in the field of neuroscience, focusing on the challenges of coprinting and the research conducted based on multicellular printing. This review discusses cell interactions in coprinting systems, stem cell applications, the construction of brain-like organoids, the establishment of disease models, and the potential for integrating 3D bioprinting with other 3D culture techniques.

Abnormal Local Cortical Functional Connectivity due to Interneuron Dysmaturation after Neonatal Intermittent Hypoxia

Prematurely born infants often experience frequent hypoxic episodes due to immaturity of respiratory control resulting in disturbances of cortical development and long-term cognitive and behavioral abnormalities. We hypothesize that neonatal intermittent hypoxia alters maturation of cortical excitatory and inhibitory circuits that can be detected early with functional MRI. C57BL/6 mouse male and female pups were exposed to an intermittent hypoxia (IH) regimen from P3 to P7, corresponding to preterm humans. Adult mice after neonatal IH exhibited motor hyperactivity and impaired motor learning in complex wheel tests. Patch-clamp and evoked field potential recordings revealed increased glutamatergic synaptic transmission. To investigate the role of GABAergic inhibition on glutamatergic transmission during the developmental, we applied a selective GABAA receptor inhibitor picrotoxin. A decreased synaptic inhibitory drive in the motor cortex was evidenced by miniature IPSC frequency on pyramidal cells, multi-unit activity recording in vivo with picrotoxin injection, and decreased interneuron density. There was also an increased tonic depolarizing effect of picrotoxin after IH on Betz cells' membrane potential on patch-clamp and direct current potential in extracellular recordings. The amplitude of low-frequency fluctuation on resting-state fMRI was larger, with a larger increase in regional homogeneity index after picrotoxin injection in the IH group. The increased glutamatergic transmission, decreased numbers, and activity of inhibitory interneurons after neonatal IH may affect the maturation of connectivity in cortical networks, resulting in long-term cognitive and behavioral changes. Functional MRI reveals increased intrinsic connectivity in the sensorimotor cortex, suggesting neuronal dysfunction in cortical maturation after neonatal IH.

The relationship between cortical synaptic terminal density marker SV2A and glutamate early in the course of schizophrenia: a multimodal PET and MRS imaging study

Loss of glutamatergic terminals is hypothesised to contribute to excitation-inhibition imbalance in schizophrenia, supported by evidence that the normal positive association between glutamate concentrations and synaptic terminal density is not found in patients with chronic schizophrenia. However, it is unknown whether the relationship between synaptic terminal density and glutamate levels is altered early in the course of illness. To address this, we investigated [11C]UCB-J distribution volume ratio (DVR) and glutamatergic markers in healthy volunteers (HV) and in antipsychotic-naïve/free patients with schizophrenia (SCZ) recruited from first-episode psychosis services. Forty volunteers (HV n = 19, SCZ n = 21) underwent [11C]UCB-J positron emission tomography and proton magnetic resonance spectroscopy (1H-MRS) imaging in the anterior cingulate cortex (ACC) and left hippocampus to index [11C]UCB-J DVR and creatine-scaled glutamate (Glu/Cr) and glutamate in combination with glutamine (Glx/Cr). In the HV but not SCZ group, [11C]UCB-J DVR was significantly positively associated with Glu/Cr (Spearman's rho = 0.55, p = 0.02) and Glx/Cr (Spearman's rho = 0.73, p = 0.0004) in the ACC, and with Glu/Cr in the left hippocampus (Spearman's rho = 0.77, p = 0.0001). DVR was significantly lower in the ACC in the SCZ group compared to the HV group (Kolmogorov-Smirnov Z = 1.44, p = 0.03). Together, these findings indicate that the normal relationship between levels of a synaptic terminal density marker and levels of glutamate is disrupted early in the course of schizophrenia. This is consistent with the hypothesis that there is loss of glutamatergic terminals at illness onset.

Spatial profiling of the interplay between cell type- and vision-dependent transcriptomic programs in the visual cortex

How early sensory experience during "critical periods" of postnatal life affects the organization of the mammalian neocortex at the resolution of neuronal cell types is poorly understood. We previously reported that the functional and molecular profiles of layer 2/3 (L2/3) cell types in the primary visual cortex (V1) are vision-dependent [S. Cheng et al., Cell 185, 311-327.e24 (2022)]. Here, we characterize the spatial organization of L2/3 cell types with and without visual experience. Spatial transcriptomic profiling based on 500 genes recapitulates the zonation of L2/3 cell types along the pial-ventricular axis in V1. By applying multitasking theory, we suggest that the spatial zonation of L2/3 cell types is linked to the continuous nature of their gene expression profiles, which can be represented as a 2D manifold bounded by three archetypal cell types. By comparing normally reared and dark reared L2/3 cells, we show that visual deprivation-induced transcriptomic changes comprise two independent gene programs. The first, induced specifically in the visual cortex, includes immediate-early genes and genes associated with metabolic processes. It manifests as a change in cell state that is orthogonal to cell-type-specific gene expression programs. By contrast, the second program impacts L2/3 cell-type identity, regulating a subset of cell-type-specific genes and shifting the distribution of cells within the L2/3 cell-type manifold. Through an integrated analysis of spatial transcriptomics with single-nucleus RNA-seq data, we describe how vision patterns cortical L2/3 cell types during the critical period.

Type-I nNOS neurons orchestrate cortical neural activity and vasomotion

It is unknown how the brain orchestrates coordination of global neural and vascular dynamics. We sought to uncover the role of a sparse but unusual population of genetically-distinct interneurons known as type-I nNOS neurons, using a novel pharmacological strategic to unilaterally ablate these neurons from the somatosensory cortex of mice. Region-specific ablation produced changes in both neural activity and vascular dynamics, decreased power in the delta-band of the local field potential, reduced sustained vascular responses to prolonged sensory stimulation, and abolished the post-stimulus undershoot in cerebral blood volume. Coherence between the left and right somatosensory cortex gamma-band power envelope and blood volume at ultra-low frequencies was decreased, suggesting type-1 nNOS neurons integrate long-range coordination of brain signals. Lastly, we observed decreases in the amplitude of resting-state blood volume oscillations and decreased vasomotion following the ablation of type-I nNOS neurons. This demonstrates that a small population of nNOS-positive neurons are indispensable for regulating both neural and vascular dynamics in the whole brain and implicates disruption of these neurons in diseases ranging from neurodegeneration to sleep disturbances.

Glutamate/GABA/glutamine ratios in intact and ischemia reperfusion challenged rat brain subregions, the effect of ischemic preconditioning

The proper function of the brain is entirely dependent on intact neurotransmission, where glutamate (Glu) and γ-aminobutyric acid (GABA) are the two most present neurotransmitters. Maintenance of these neurotransmitters pools is strictly relying on the de novo synthesis of glutamine in astrocytes. Cerebral ischemic events disrupt the balance in uptake and re-synthesis, altering Glu, GABA, and glutamine (Gln) levels. We focused on the determining of the ratios of glutamate, GABA and glutamine in the brain of rats in the intact state, the early changes and temporal development of changes towards the recovery after disruption of balance by global cerebral ischemia. Animals underwent 15 min of global cerebral ischemia, and changes in Glu/GABA/Gln ratios in the hippocampus, cortex, and cerebellum were assessed at 3 h, 24 h, and 72 h post-reperfusion using high-resolution NMR. Ischemic preconditioning was also used to induce tolerance. In an intact rat brain, glutamate level was about twice that of glutamine in all substructures, about sevenfold compared to GABA in the hippocampus and cortex, and almost eightfold compared to GABA in the cerebellum. There were three to four times as much glutamine compared to GABA. After severe cerebral ischemia, Glu/Gln as well as GABA/Gln ratios extensively dropped in early reperfusion (3 h) and gradually increased in 72 h reperfusion time, however, only the Glu/Gln ratio recovered to the level of controls. Glu/GABA ratio remained in all three reperfusion times over the level of control animals. We observed a decrease in glutathione NMR peak in brain tissue homogenates after ischemia. The obtained data suggest the accelerated accumulation of intraparenchymal glutamate after ischemia, which was even more pronounced in the preconditioned animals three days after an ischemic event. The postischemic GABA level restoration did not achieve the level before ischemia in 72 h reperfusion, which could be one of the limiting factors in the complete postischemic GABA transmission recovery. Presented data may be of advantage not only when comparing glutamate and GABA homeostasis and neurotransmission, but also for glutamine reserve display as neurotransmitter precursor and ammonia transfer buffer in glutamate/GABA/glutamine cycle within the intact brain substructures as well after ischemic insult in rats.

Transcriptomic characterization of 2D and 3D human induced pluripotent stem cell-based in vitro models as New Approach Methodologies for developmental neurotoxicity testing

The safety and developmental neurotoxicity (DNT) potential of chemicals remain critically understudied due to limitations of current in vivo testing guidelines, which are low throughput, resource-intensive, and hindered by species differences that limit their relevance to human health. To address these issues, robust New Approach Methodologies (NAMs) using deeply characterized cell models are essential. This study presents the comprehensive transcriptomic characterization of two advanced human-induced pluripotent stem cell (hiPSC)-derived models: a 2D adherent and a 3D neurosphere model of human neural progenitor cells (hiNPCs) differentiated up to 21 days. Using high-throughput RNA sequencing, we compared gene expression profiles of 2D and 3D models at three developmental stages (3, 14, and 21 days of differentiation). Both models exhibit maturation towards post-mitotic neurons, with the 3D model maturing faster and showing a higher prevalence of GABAergic neurons, while the 2D model is enriched with glutamatergic neurons. Both models demonstrate broad applicability domains, including excitatory and inhibitory neurons, astrocytes, and key endocrine and especially the understudied cholinergic receptors. Comparison with human fetal brain samples confirms their physiological relevance. This study provides novel in-depth applicability insights into the temporal and dimensional aspects of hiPSC-derived neural models for DNT testing. The complementary use of these two models is highlighted: the 2D model excels in synaptogenesis assessment, while the 3D model is particularly suited for neural network formation as observed as well in previous functional studies with these models. This research marks a significant advancement in developing human-relevant, high-throughput DNT assays for regulatory purposes.

Excitatory neuron-prone prion propagation and excitatory neuronal loss in prion-infected mice

The accumulation of a disease-specific isoform of prion protein (PrPSc) and histopathological lesions, such as neuronal loss, are unevenly distributed in the brains of humans and animals affected with prion diseases. This distribution varies depending on the diseases and/or the combinations of prion strain and experimental animal. The brain region-dependent distribution of PrPSc and neuropathological lesions suggests a neuronal cell-type-dependent prion propagation and vulnerability to prion infection. However, the underlying mechanism is largely unknown. In this study, we provided evidence that the prion 22L strain propagates more efficiently in excitatory neurons than inhibitory neurons and that excitatory neurons in the thalamus are vulnerable to prion infection. PrPSc accumulation was less intense in the striatum, where GABAergic inhibitory neurons predominate, compared to the cerebral cortex and thalamus, where glutamatergic excitatory neurons are predominant, in mice intracerebrally or intraperitoneally inoculated with the 22L strain. PrPSc stains were observed along the needle track after stereotaxic injection into the striatum, whereas they were also observed away from the needle track in the thalamus. Consistent with inefficient prion propagation in the striatum, the 22L prion propagated more efficiently in glutamatergic neurons than GABAergic neurons in primary neuronal cultures. RNAscope in situ hybridization revealed a decrease in Vglut1- and Vglut2-expressing neurons in the ventral posterolateral nuclei of the thalamus in 22L strain-infected mice, whereas no decrease in Vgat-expressing neurons was observed in the adjacent reticular nucleus, mainly composed of Vgat-expressing interneurons. The excitatory neuron-prone prion propagation and excitatory neuronal loss in 22L strain-infected mice shed light on the neuropathological mechanism of prion diseases.

Synaptic effects on the intermittent synchronization of gamma rhythms

Synchronization of neural activity in the gamma frequency band is associated with various cognitive phenomena. Abnormalities of gamma synchronization may underlie symptoms of several neurological and psychiatric disorders such as schizophrenia and autism spectrum disorder. Properties of neural oscillations in the gamma band depend critically on the synaptic properties of the underlying circuits. This study explores how synaptic properties in pyramidal-interneuronal circuits affect not only the average synchronization strength but also the fine temporal patterning of neural synchrony. If two signals show only moderate synchrony strength, it may be possible to consider these dynamics as alternating between synchronized and desynchronized states. We use a model of connected circuits that produces pyramidal-interneuronal gamma oscillations to explore the temporal patterning of synchronized and desynchronized intervals. Changes in synaptic strength may alter the temporal patterning of synchronized dynamics (even if the average synchrony strength is not changed). Larger values of local synaptic connections promote longer desynchronization durations, while larger values of long-range synaptic connections promote shorter desynchronization durations. Furthermore, we show that circuits with different temporal patterning of synchronization may have different sensitivity to synaptic input. Thus, the alterations of synaptic strength may mediate physiological properties of neural circuits not only through change in the average synchrony level of gamma oscillations, but also through change in how synchrony is patterned in time over very short time scales.

In vitro electrophysiological drug testing on neuronal networks derived from human induced pluripotent stem cells

BACKGROUND

In vitro models for drug testing constitute a valuable and simplified in-vivo-like assay to better comprehend the biological drugs effect. In particular, the combination of neuronal cultures with Micro-Electrode Arrays (MEAs) constitutes a reliable system to investigate the effect of drugs aimed at manipulating the neural activity and causing controlled changes in the electrophysiology. While chemical modulation in rodents' models has been extensively studied in the literature, electrophysiological variations caused by chemical modulation on neuronal networks derived from human induced pluripotent stem cells (hiPSCs) still lack a thorough characterization.

METHODS

In this work, we created three different configurations of hiPSCs-derived neuronal networks composed of fully glutamatergic neurons (100E), 75% of glutamatergic and 25% of GABAergic neurons (75E25I) and fully GABAergic neurons (100I). We focused on the effects caused by antagonists of three of the most relevant ionotropic receptors of the human brain, i.e., 2-amino-5-phosphonovaleric (APV, NMDA receptors antagonist), 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX, AMPA receptors antagonist), and bicuculline, picrotoxin and pentylenetetrazole (BIC, PTX, and PTZ, respectively, GABAA receptors antagonists).

RESULTS

We found that APV and CNQX completely abolished the network bursting activity and caused major changes in the functional connectivity. On the other hand, the effect of BIC, PTX and PTZ mostly affected configurations in which the inhibitory component was present by increasing the firing and network bursting activity as well as the functional connectivity.

CONCLUSIONS

Our work revealed that hiPSCs-derived neuronal networks are very sensitive to pharmacological manipulation of the excitatory ionotropic glutamatergic and inhibitory ionotropic GABAergic transmission, representing a preliminary and necessary step forward in the field of drug testing that can rely on pathological networks of human origin.

Modeling common and rare genetic risk factors of neuropsychiatric disorders in human induced pluripotent stem cells

Recent genome-wide association studies (GWAS) and whole-exome sequencing of neuropsychiatric disorders, especially schizophrenia, have identified a plethora of common and rare disease risk variants/genes. Translating the mounting human genetic discoveries into novel disease biology and more tailored clinical treatments is tied to our ability to causally connect genetic risk variants to molecular and cellular phenotypes. When combined with the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated (Cas) nuclease-mediated genome editing system, human induced pluripotent stem cell (hiPSC)-derived neural cultures (both 2D and 3D organoids) provide a promising tractable cellular model for bridging the gap between genetic findings and disease biology. In this review, we first conceptualize the advances in understanding the disease polygenicity and convergence from the past decade of iPSC modeling of different types of genetic risk factors of neuropsychiatric disorders. We then discuss the major cell types and cellular phenotypes that are most relevant to neuropsychiatric disorders in iPSC modeling. Finally, we critically review the limitations of iPSC modeling of neuropsychiatric disorders and outline the need for implementing and developing novel methods to scale up the number of iPSC lines and disease risk variants in a systematic manner. Sufficiently scaled-up iPSC modeling and a better functional interpretation of genetic risk variants, in combination with cutting-edge CRISPR/Cas9 gene editing and single-cell multi-omics methods, will enable the field to identify the specific and convergent molecular and cellular phenotypes in precision for neuropsychiatric disorders.

Aberrant neuronal connectivity and network activity of neurons derived from patients with idiopathic schizophrenia

Schizophrenia (SCZ) is a psychiatric disorder with a strong genetic determinant. A major hypothesis to explain disease aetiology comprises synaptic dysfunction associated with excitatory-inhibitory imbalance of synaptic transmission, ultimately contributing to impaired network oscillation and cognitive deficits associated with the disease. Here, we studied the morphological and functional properties of a highly defined co-culture of GABAergic and glutamatergic neurons derived from induced pluripotent stem cells (iPSC) from patients with idiopathic SCZ. Our results indicate upregulation of synaptic genes and increased excitatory synapse formation on GABAergic neurons in co-cultures. In parallel, we observed decreased lengths of axon initial segments, concordant with data from postmortem brains from patients with SCZ. In line with increased synapse density, patch-clamp analyses revealed markedly increased spontaneous excitatory postsynaptic currents (EPSC) recorded from GABAergic SCZ neurons. Finally, MEA recordings from neuronal networks indicate increased strength of network activity, potentially in response to altered synaptic transmission and E-I balance in the co-cultures. In conclusion, our results suggest selective deregulation of neuronal activity in SCZ samples, providing evidence for altered synapse formation and synaptic transmission as a potential base for aberrant network synchronization.

Multi-scale spiking network model of human cerebral cortex

Although the structure of cortical networks provides the necessary substrate for their neuronal activity, the structure alone does not suffice to understand the activity. Leveraging the increasing availability of human data, we developed a multi-scale, spiking network model of human cortex to investigate the relationship between structure and dynamics. In this model, each area in one hemisphere of the Desikan-Killiany parcellation is represented by a $1\,\mathrm{mm^{2}}$ column with a layered structure. The model aggregates data across multiple modalities, including electron microscopy, electrophysiology, morphological reconstructions, and diffusion tensor imaging, into a coherent framework. It predicts activity on all scales from the single-neuron spiking activity to the area-level functional connectivity. We compared the model activity with human electrophysiological data and human resting-state functional magnetic resonance imaging (fMRI) data. This comparison reveals that the model can reproduce aspects of both spiking statistics and fMRI correlations if the inter-areal connections are sufficiently strong. Furthermore, we study the propagation of a single-spike perturbation and macroscopic fluctuations through the network. The open-source model serves as an integrative platform for further refinements and future in silico studies of human cortical structure, dynamics, and function.

The emergence of antidepressant drugs targeting GABAA receptors: A concise review

Depression is among the most common psychiatric illnesses, which imposes a major socioeconomic burden on patients, caregivers, and the public health system. Treatment with classical antidepressants (e.g. tricyclic antidepressants and selective serotonine reuptake inhibitors), which primarily affect monoaminergic systems has several limitations, such as delayed onset of action and moderate efficacy in a relatively large proportion of depressed patients. Furthermore, depression is highly heterogeneus, and its different subtypes, including post-partum depression, involve distinct neurobiology, warranting a differential approach to pharmacotherapy. Given these shortcomings, the need for novel antidepressants that are superior in efficacy and faster in onset of action is fully justified. The development and market introduction of rapid-acting antidepressants has accelerated in recent years. Some of these new antidepressants act through the GABAergic system. In this review, we discuss the discovery, efficacy, and limitations of treatment with classic antidepressants. We provide a detailed discussion of GABAergic neurotransmission, with a special focus on GABAA receptors, and possible explanations for the mood-enhancing effects of GABAergic medications (in particular neurosteroids acting at GABAA receptors), and, ultimately, we present the most promising molecules belonging to this family which are currently used in clinical practice or are in late phases of clinical development.

Human Neural Organoid Microphysiological Systems Show the Building Blocks Necessary for Basic Learning and Memory

Brain Microphysiological Systems including neural organoids derived from human induced pluripotent stem cells offer a unique lens to study the intricate workings of the human brain. This paper investigates the foundational elements of learning and memory in neural organoids, also known as Organoid Intelligence by quantifying immediate early gene expression, synaptic plasticity, neuronal network dynamics, and criticality to demonstrate the utility of these organoids in basic science research. Neural organoids showed synapse formation, glutamatergic and GABAergic receptor expression, immediate early gene expression basally and evoked, functional connectivity, criticality, and synaptic plasticity in response to theta-burst stimulation. In addition, pharmacological interventions on GABAergic and glutamatergic receptors, and input specific theta-burst stimulation further shed light on the capacity of neural organoids to mirror synaptic modulation and short-term potentiation, demonstrating their potential as tools for studying neurophysiological and neurological processes and informing therapeutic strategies for diseases.

A neural perspective on the treatment of hypertension: the neurological network excitation and inhibition (E/I) imbalance in hypertension

Despite the increasing number of anti-hypertensive drugs have been developed and used in the clinical setting, persistent deficiencies persist, including issues such as lifelong dosage, combination therapy. Notwithstanding receiving the treatment under enduring these deficiencies, approximately 4 in 5 patients still fail to achieve reliable blood pressure (BP) control. The application of neuromodulation in the context of hypertension presents a pioneering strategy for addressing this condition, con-currently implying a potential central nervous mechanism underlying hypertension onset. We hypothesize that neurological networks, an essential component of maintaining appropriate neurological function, are involved in hypertension. Drawing on both peer-reviewed research and our laboratory investigations, we endeavor to investigate the underlying neural mechanisms involved in hypertension by identifying a close relationship between its onset of hypertension and an excitation and inhibition (E/I) imbalance. In addition to the involvement of excitatory glutamatergic and GABAergic inhibitory system, the pathogenesis of hypertension is also associated with Voltage-gated sodium channels (VGSCs, Nav)-mediated E/I balance. The overloading of glutamate or enhancement of glutamate receptors may be attributed to the E/I imbalance, ultimately triggering hypertension. GABA loss and GABA receptor dysfunction have also proven to be involved. Furthermore, we have identified that abnormalities in sodium channel expression and function alter neural excitability, thereby disturbing E/I balance and potentially serving as a mechanism underlying hypertension. These insights are expected to furnish potential strategies for the advancement of innovative anti-hypertensive therapies and a meaningful reference for the exploration of central nervous system (CNS) targets of anti-hypertensives.

Ultrasound pulse repetition frequency preferentially activates different neuron populations independent of cell type

Objective. Transcranial ultrasound (US) stimulation serves as an external input to a neuron, and thus the evoked response relies on neurons' intrinsic properties. Neural activity is limited to a couple hundred hertz and often exhibits preference to input frequencies. Accordingly, US pulsed at specific physiologic pulse repetition frequencies (PRFs) may selectively engage neurons with the corresponding input frequency preference. However, most US parametric studies examine the effects of supraphysiologic PRFs. It remains unclear whether pulsing US at different physiologic PRFs could activate distinct neurons in the awake mammalian brain.Approach. We recorded cellular calcium responses of individual motor cortex neurons to US pulsed at PRFs of 10, 40, and 140 Hz in awake mice. We compared the evoked responses across these PRFs in the same neurons. To further understand the cell-type dependent effects, we categorized the recorded neurons as parvalbumin positive fast spiking interneurons or putative excitatory neurons and analyzed single-cell mechanosensitive channel expression in mice and humans using the Allen Brain Institute's RNA-sequencing databases.Main results. We discovered that many neurons were preferentially activated by only one PRF and different PRFs selectively engaged distinct neuronal populations. US-evoked cellular calcium responses exhibited the same characteristics as those naturally occurring during spiking, suggesting that US increases intrinsic neuronal activity. Furthermore, evoked responses were similar between fast-spiking inhibitory neurons and putative excitatory neurons. Thus, variation in individual neuron's cellular properties dominates US-evoked response heterogeneity, consistent with our observed cell-type independent expression patterns of mechanosensitive channels across individual neurons in mice and humans. Finally, US transiently increased network synchrony without producing prolonged over-synchronization that could be detrimental to neural circuit functions.Significance. These results highlight the feasibility of activating distinct neuronal subgroups by varying PRF and the potential to improve neuromodulation effects by combining physiologic PRFs.

Aperiodic and Hurst EEG exponents across early human brain development: A systematic review

In electroencephalographic (EEG) data, power-frequency slope exponents (1/f_β) can provide non-invasive markers of in vivo neural activity excitation-inhibition (E:I) balance. E:I balance may be altered in neurodevelopmental conditions; hence, understanding how 1/fβ evolves across infancy/childhood has implications for developing early assessments/interventions. This systematic review (PROSPERO-ID: CRD42023363294) explored the early maturation (0-26 yrs) of resting-state EEG 1/f measures (aperiodic [AE], power law [PLE] and Hurst [HE] exponents), including studies containing ≥1 1/f measures and ≥10 typically developing participants. Five databases (including Embase and Scopus) were searched during March 2023. Forty-two studies were identified (Nparticipants=3478). Risk of bias was assessed using the Quality Assessment with Diverse Studies tool. Narrative synthesis of HE data suggests non-stationary EEG activity occurs throughout development. Age-related trends were complex, with rapid decreases in AEs during infancy and heterogenous changes thereafter. Regionally, AE maxima shifted developmentally, potentially reflecting spatial trends in maturing brain connectivity. This work highlights the importance of further characterising the development of 1/f measures to better understand how E:I balance shapes brain and cognitive development.

Recent advances and current challenges of new approach methodologies in developmental and adult neurotoxicity testing

Adult neurotoxicity (ANT) and developmental neurotoxicity (DNT) assessments aim to understand the adverse effects and underlying mechanisms of toxicants on the human nervous system. In recent years, there has been an increasing focus on the so-called new approach methodologies (NAMs). The Organization for Economic Co-operation and Development (OECD), together with European and American regulatory agencies, promote the use of validated alternative test systems, but to date, guidelines for regulatory DNT and ANT assessment rely primarily on classical animal testing. Alternative methods include both non-animal approaches and test systems on non-vertebrates (e.g., nematodes) or non-mammals (e.g., fish). Therefore, this review summarizes the recent advances of NAMs focusing on ANT and DNT and highlights the potential and current critical issues for the full implementation of these methods in the future. The status of the DNT in vitro battery (DNT IVB) is also reviewed as a first step of NAMs for the assessment of neurotoxicity in the regulatory context. Critical issues such as (i) the need for test batteries and method integration (from in silico and in vitro to in vivo alternatives, e.g., zebrafish, C. elegans) requiring interdisciplinarity to manage complexity, (ii) interlaboratory transferability, and (iii) the urgent need for method validation are discussed.

Native-state proteomics of Parvalbumin interneurons identifies unique molecular signatures and vulnerabilities to early Alzheimer's pathology

Dysfunction in fast-spiking parvalbumin interneurons (PV-INs) may represent an early pathophysiological perturbation in Alzheimer's Disease (AD). Defining early proteomic alterations in PV-INs can provide key biological and translationally-relevant insights. We used cell-type-specific in-vivo biotinylation of proteins (CIBOP) coupled with mass spectrometry to obtain native-state PV-IN proteomes. PV-IN proteomic signatures include high metabolic and translational activity, with over-representation of AD-risk and cognitive resilience-related proteins. In bulk proteomes, PV-IN proteins were associated with cognitive decline in humans, and with progressive neuropathology in humans and the 5xFAD mouse model of Aβ pathology. PV-IN CIBOP in early stages of Aβ pathology revealed signatures of increased mitochondria and metabolism, synaptic and cytoskeletal disruption and decreased mTOR signaling, not apparent in whole-brain proteomes. Furthermore, we demonstrated pre-synaptic defects in PV-to-excitatory neurotransmission, validating our proteomic findings. Overall, in this study we present native-state proteomes of PV-INs, revealing molecular insights into their unique roles in cognitive resiliency and AD pathogenesis.

Aperiodic EEG and 7T MRSI evidence for maturation of E/I balance supporting the development of working memory through adolescence

Adolescence has been hypothesized to be a critical period for the development of human association cortex and higher-order cognition. A defining feature of critical period development is a shift in the excitation: inhibition (E/I) balance of neural circuitry, however how changes in E/I may enhance cortical circuit function to support maturational improvements in cognitive capacities is not known. Harnessing ultra-high field 7 T MR spectroscopy and EEG in a large, longitudinal cohort of youth (N = 164, ages 10-32 years old, 347 neuroimaging sessions), we delineate biologically specific associations between age-related changes in excitatory glutamate and inhibitory GABA neurotransmitters and EEG-derived measures of aperiodic neural activity reflective of E/I balance in prefrontal association cortex. Specifically, we find that developmental increases in E/I balance reflected in glutamate:GABA balance are linked to changes in E/I balance assessed by the suppression of prefrontal aperiodic activity, which in turn facilitates robust improvements in working memory. These findings indicate a role for E/I-engendered changes in prefrontal signaling mechanisms in the maturation of cognitive maintenance. More broadly, this multi-modal imaging study provides evidence that human association cortex undergoes physiological changes consistent with critical period plasticity during adolescence.

Ultrasound pulse repetition frequency preferentially activates different neuron populations independent of cell type

Transcranial ultrasound activates mechanosensitive cellular signaling and modulates neural dynamics. Given that intrinsic neuronal activity is limited to a couple hundred hertz and often exhibits frequency preference, we examined whether pulsing ultrasound at physiologic pulse repetition frequencies (PRFs) could selectively influence neuronal activity in the mammalian brain. We performed calcium imaging of individual motor cortex neurons, while delivering 0.35 MHz ultrasound at PRFs of 10, 40, and 140 Hz in awake mice. We found that most neurons were preferentially activated by only one of the three PRFs, highlighting unique cellular effects of physiologic PRFs. Further, ultrasound evoked responses were similar between excitatory neurons and parvalbumin positive interneurons regardless of PRFs, indicating that individual cell sensitivity dominates ultrasound-evoked effects, consistent with the heterogeneous mechanosensitive channel expression we found across single neurons in mice and humans. These results highlight the feasibility of tuning ultrasound neuromodulation effects through varying PRFs.

Defined co-cultures of glutamatergic and GABAergic neurons with a mutation in DISC1 reveal aberrant phenotypes in GABAergic neurons

BACKGROUND

Mutations in the gene DISC1 are associated with increased risk for schizophrenia, bipolar disorder and major depression. The study of mutated DISC1 represents a well-known and comprehensively characterized approach to understand neuropsychiatric disease mechanisms. However, previous studies have mainly used animal models or rather heterogeneous populations of iPSC-derived neurons, generated by undirected differentiation, to study the effects of DISC1 disruption. Since major hypotheses to explain neurodevelopmental, psychiatric disorders rely on altered neuronal connectivity observed in patients, an ideal iPSC-based model requires accurate representation of the structure and complexity of neuronal circuitries. In this study, we made use of an isogenic cell line with a mutation in DISC1 to study neuronal synaptic phenotypes in a culture system comprising a defined ratio of NGN2 and ASCL1/DLX2 (AD2)-transduced neurons, enriched for glutamatergic and GABAergic neurons, respectively, to mimic properties of the cortical microcircuitry.

RESULTS

In heterozygous DISC1 mutant neurons, we replicated the expected phenotypes including altered neural progenitor proliferation as well as neurite outgrowth, deregulated DISC1-associated signaling pathways, and reduced synaptic densities in cultures composed of glutamatergic neurons. Cultures comprising a defined ratio of NGN2 and AD2 neurons then revealed considerably increased GABAergic synapse densities, which have not been observed in any iPSC-derived model so far. Increased inhibitory synapse densities could be associated with an increased efficiency of GABAergic differentiation, which we observed in AD2-transduced cultures of mutant neurons. Additionally, we found increased neuronal activity in GABAergic neurons through calcium imaging while the activity pattern of glutamatergic neurons remained unchanged.

CONCLUSIONS

In conclusion, our results demonstrate phenotypic differences in a co-culture comprising a defined ratio of DISC1 mutant NGN2 and AD2 neurons, as compared to culture models comprising only one neuronal cell type. Altered synapse numbers and neuronal activity imply that DISC1 impacts the excitatory/inhibitory balance in NGN2/AD2 co-cultures, mainly through increased GABAergic input.

MEF2C Hypofunction in GABAergic Cells Alters Sociability and Prefrontal Cortex Inhibitory Synaptic Transmission in a Sex-Dependent Manner

Background

Heterozygous mutations or deletions of MEF2C cause a neurodevelopmental disorder termed MEF2C haploinsufficiency syndrome (MCHS), characterized by autism spectrum disorder and neurological symptoms. In mice, global Mef2c heterozygosity has produced multiple MCHS-like phenotypes. MEF2C is highly expressed in multiple cell types of the developing brain, including GABAergic (gamma-aminobutyric acidergic) inhibitory neurons, but the influence of MEF2C hypofunction in GABAergic neurons on MCHS-like phenotypes remains unclear.

Methods

We employed GABAergic cell type-specific manipulations to study mouse Mef2c heterozygosity in a battery of MCHS-like behaviors. We also performed electroencephalography, single-cell transcriptomics, and patch-clamp electrophysiology and optogenetics to assess the impact of Mef2c haploinsufficiency on gene expression and prefrontal cortex microcircuits.

Results

Mef2c heterozygosity in developing GABAergic cells produced female-specific deficits in social preference and altered approach-avoidance behavior. In female, but not male, mice, we observed that Mef2c heterozygosity in developing GABAergic cells produced 1) differentially expressed genes in multiple cell types, including parvalbumin-expressing GABAergic neurons, 2) baseline and social-related frontocortical network activity alterations, and 3) reductions in parvalbumin cell intrinsic excitability and inhibitory synaptic transmission onto deep-layer pyramidal neurons.

Conclusions

MEF2C hypofunction in female, but not male, developing GABAergic cells is important for typical sociability and approach-avoidance behaviors and normal parvalbumin inhibitory neuron function in the prefrontal cortex of mice. While there is no apparent sex bias in autism spectrum disorder symptoms of MCHS, our findings suggest that GABAergic cell-specific dysfunction in females with MCHS may contribute disproportionately to sociability symptoms.

An Agent-Based Model to Reproduce the Boolean Logic Behaviour of Neuronal Self-Organised Communities through Pulse Delay Modulation and Generation of Logic Gates

The human brain is arguably the most complex "machine" to ever exist. Its detailed functioning is yet to be fully understood, let alone modelled. Neurological processes have logical signal-processing and biophysical aspects, and both affect the brain's structure, functioning and adaptation. Mathematical approaches based on both information and graph theory have been extensively used in an attempt to approximate its biological functioning, along with Artificial Intelligence frameworks inspired by its logical functioning. In this article, an approach to model some aspects of the brain learning and signal processing is presented, mimicking the metastability and backpropagation found in the real brain while also accounting for neuroplasticity. Several simulations are carried out with this model to demonstrate how dynamic neuroplasticity, neural inhibition and neuron migration can reshape the brain's logical connectivity to synchronise signal processing and obtain certain target latencies. This work showcases the importance of dynamic logical and biophysical remodelling in brain plasticity. Combining mathematical (agents, graph theory, topology and backpropagation) and biomedical ingredients (metastability, neuroplasticity and migration), these preliminary results prove complex brain phenomena can be reproduced-under pertinent simplifications-via affordable computations, which can be construed as a starting point for more ambitiously accurate simulations.

Electrical and chemical modulation of homogeneous and heterogeneous human-iPSCs-derived neuronal networks on high density arrays

The delicate "Excitatory/Inhibitory balance" between neurons holds significance in neurodegenerative and neurodevelopmental diseases. With the ultimate goal of creating a faithful in vitro model of the human brain, in this study, we investigated the critical factor of heterogeneity, focusing on the interplay between excitatory glutamatergic (E) and inhibitory GABAergic (I) neurons in neural networks. We used high-density Micro-Electrode Arrays (MEA) with 2304 recording electrodes to investigate two neuronal culture configurations: 100% glutamatergic (100E) and 75% glutamatergic / 25% GABAergic (75E25I) neurons. This allowed us to comprehensively characterize the spontaneous electrophysiological activity exhibited by mature cultures at 56 Days in vitro, a time point in which the GABA shift has already occurred. We explored the impact of heterogeneity also through electrical stimulation, revealing that the 100E configuration responded reliably, while the 75E25I required more parameter tuning for improved responses. Chemical stimulation with BIC showed an increase in terms of firing and bursting activity only in the 75E25I condition, while APV and CNQX induced significant alterations on both dynamics and functional connectivity. Our findings advance understanding of diverse neuron interactions and their role in network activity, offering insights for potential therapeutic interventions in neurological conditions. Overall, this work contributes to the development of a valuable human-based in vitro system for studying physiological and pathological conditions, emphasizing the pivotal role of neuron diversity in neural network dynamics.

Quantifying the proportion of different cell types in the human cortex using DNA methylation profiles

BACKGROUND

Due to interindividual variation in the cellular composition of the human cortex, it is essential that covariates that capture these differences are included in epigenome-wide association studies using bulk tissue. As experimentally derived cell counts are often unavailable, computational solutions have been adopted to estimate the proportion of different cell types using DNA methylation data. Here, we validate and profile the use of an expanded reference DNA methylation dataset incorporating two neuronal and three glial cell subtypes for quantifying the cellular composition of the human cortex.

RESULTS

We tested eight reference panels containing different combinations of neuronal- and glial cell types and characterised their performance in deconvoluting cell proportions from computationally reconstructed or empirically derived human cortex DNA methylation data. Our analyses demonstrate that while these novel brain deconvolution models produce accurate estimates of cellular proportions from profiles generated on postnatal human cortex samples, they are not appropriate for the use in prenatal cortex or cerebellum tissue samples. Applying our models to an extensive collection of empirical datasets, we show that glial cells are twice as abundant as neuronal cells in the human cortex and identify significant associations between increased Alzheimer's disease neuropathology and the proportion of specific cell types including a decrease in NeuNNeg/SOX10Neg nuclei and an increase of NeuNNeg/SOX10Pos nuclei.

CONCLUSIONS

Our novel deconvolution models produce accurate estimates for cell proportions in the human cortex. These models are available as a resource to the community enabling the control of cellular heterogeneity in epigenetic studies of brain disorders performed on bulk cortex tissue.

Investigating the reliability of the evoked response in human iPSCs-derived neuronal networks coupled to micro-electrode arrays

In vitro models of neuronal networks have emerged as a potent instrument for gaining deeper insights into the intricate mechanisms governing the human brain. Notably, the integration of human-induced pluripotent stem cells (hiPSCs) with micro-electrode arrays offers a means to replicate and dissect both the structural and functional elements of the human brain within a controlled in vitro environment. Given that neuronal communication relies on the emission of electrical (and chemical) stimuli, the employment of electrical stimulation stands as a mean to comprehensively interrogate neuronal assemblies, to better understand their inherent electrophysiological dynamics. However, the establishment of standardized stimulation protocols for cultures derived from hiPSCs is still lacking, thereby hindering the precise delineation of efficacious parameters to elicit responses. To fill this gap, the primary objective of this study resides in delineating effective parameters for the electrical stimulation of hiPSCs-derived neuronal networks, encompassing the determination of voltage amplitude and stimulation frequency able to evoke reliable and stable responses. This study represents a stepping-stone in the exploration of efficacious stimulation parameters, thus broadening the electrophysiological activity profiling of neural networks sourced from human-induced pluripotent stem cells.

Acetylcholine facilitates localized synaptic potentiation and location specific feature binding

Forebrain acetylcholine (ACh) signaling has been shown to drive attention and learning. Recent experimental evidence of spatially and temporally constrained cholinergic signaling has sparked interest to investigate how it facilitates stimulus-induced learning. We use biophysical excitatory-inhibitory (E-I) multi-module neural network models to show that external stimuli and ACh signaling can mediate spatially constrained synaptic potentiation patterns. The effects of ACh on neural excitability are simulated by varying the conductance of a muscarinic receptor-regulated hyperpolarizing slow K+ current (m-current). Each network module consists of an E-I network with local excitatory connectivity and global inhibitory connectivity. The modules are interconnected with plastic excitatory synaptic connections, that change via a spike-timing-dependent plasticity (STDP) rule. Our results indicate that spatially constrained ACh release influences the information flow represented by network dynamics resulting in selective reorganization of inter-module interactions. Moreover the information flow depends on the level of synchrony in the network. For highly synchronous networks, the more excitable module leads firing in the less excitable one resulting in strengthening of the outgoing connections from the former and weakening of its incoming synapses. For networks with more noisy firing patterns, activity in high ACh regions is prone to induce feedback firing of synchronous volleys and thus strengthening of the incoming synapses to the more excitable region and weakening of outgoing synapses. Overall, these results suggest that spatially and directionally specific plasticity patterns, as are presumed necessary for feature binding, can be mediated by spatially constrained ACh release.

Interindividual variation in human cortical cell type abundance and expression

Single-cell transcriptomic studies have identified a conserved set of neocortical cell types from small postmortem cohorts. We extended these efforts by assessing cell type variation across 75 adult individuals undergoing epilepsy and tumor surgeries. Nearly all nuclei map to one of 125 robust cell types identified in the middle temporal gyrus. However, we found interindividual variance in abundances and gene expression signatures, particularly in deep-layer glutamatergic neurons and microglia. A minority of donor variance is explainable by age, sex, ancestry, disease state, and cell state. Genomic variation was associated with expression of 150 to 250 genes for most cell types. This characterization of cellular variation provides a baseline for cell typing in health and disease.

Compressive sensing of functional connectivity maps from patterned optogenetic stimulation of neuronal ensembles

Mapping functional connectivity between neurons is an essential step toward probing the neural computations mediating behavior. Accurately determining synaptic connectivity maps in populations of neurons is challenging in terms of yield, accuracy, and experimental time. Here, we developed a compressive sensing approach to reconstruct synaptic connectivity maps based on random two-photon cell-targeted optogenetic stimulation and membrane voltage readout of many putative postsynaptic neurons. Using a biophysical network model of interconnected populations of excitatory and inhibitory neurons, we characterized mapping recall and precision as a function of network observability, sparsity, number of neurons stimulated, off-target stimulation, synaptic reliability, propagation latency, and network topology. We found that mapping can be achieved with far fewer measurements than the standard pairwise sequential approach, with network sparsity and synaptic reliability serving as primary determinants of the performance. Our results suggest a rapid and efficient method to reconstruct functional connectivity of sparsely connected neuronal networks.

Deepening the role of excitation/inhibition balance in human iPSCs-derived neuronal networks coupled to MEAs during long-term development

Objective.The purpose of this study is to investigate whether and how the balance between excitation and inhibition ('E/I balance') influences the spontaneous development of human-derived neuronal networksin vitro. To achieve that goal, we performed a long-term (98 d) characterization of both homogeneous (only excitatory or inhibitory neurons) and heterogeneous (mixed neuronal types) cultures with controlled E/I ratios (i.e. E:I 0:100, 25:75, 50:50, 75:25, 100:0) by recording their electrophysiological activity using micro-electrode arrays.Approach.Excitatory and inhibitory neurons were derived from human induced pluripotent stem cells (hiPSCs). We realized five different configurations by systematically varying the glutamatergic and GABAergic percentages.Main results.We successfully built both homogeneous and heterogeneous neuronal cultures from hiPSCs finely controlling the E/I ratios; we were able to maintain them for up to 3 months. Homogeneity differentially impacted purely inhibitory (no bursts) and purely excitatory (few bursts) networks, deviating from the typical traits of heterogeneous cultures (burst dominated). Increased inhibition in heterogeneous cultures strongly affected the duration and organization of bursting and network bursting activity. Spike-based functional connectivity and image-based deep learning analysis further confirmed all the above.Significance.Healthy neuronal activity is controlled by a well-defined E/I balance whose alteration could lead to the onset of neurodevelopmental disorders like schizophrenia or epilepsy. Most of the commonly usedin vitromodels are animal-derived or too simplified and thus far from thein vivohuman condition. In this work, by performing a long-term study of hiPSCs-derived neuronal networks obtained from healthy human subjects, we demonstrated the feasibility of a robustin vitromodel which can be further exploited for investigating pathological conditions where the E/I balance is impaired.

Modular architecture facilitates noise-driven control of synchrony in neuronal networks

High-level information processing in the mammalian cortex requires both segregated processing in specialized circuits and integration across multiple circuits. One possible way to implement these seemingly opposing demands is by flexibly switching between states with different levels of synchrony. However, the mechanisms behind the control of complex synchronization patterns in neuronal networks remain elusive. Here, we use precision neuroengineering to manipulate and stimulate networks of cortical neurons in vitro, in combination with an in silico model of spiking neurons and a mesoscopic model of stochastically coupled modules to show that (i) a modular architecture enhances the sensitivity of the network to noise delivered as external asynchronous stimulation and that (ii) the persistent depletion of synaptic resources in stimulated neurons is the underlying mechanism for this effect. Together, our results demonstrate that the inherent dynamical state in structured networks of excitable units is determined by both its modular architecture and the properties of the external inputs.

From Youthful Vigor to Aging Decline: Unravelling the Intrinsic and Extrinsic Determinants of Hippocampal Neural Stem Cell Aging

Since Joseph Altman published his pioneering work demonstrating neurogenesis in the hippocampus of adult rats, the number of publications in this field increased exponentially. Today, we know that the adult hippocampus harbors a pool of adult neural stem cells (NSCs) that are the source of life-long neurogenesis and plasticity. The functions of these NSCs are regulated by extrinsic cues arising from neighboring cells and the systemic environment. However, this tight regulation is subject to imbalance with age, resulting in a decline in adult NSCs and neurogenesis, which contributes to the progressive deterioration of hippocampus-related cognitive functions. Despite extensive investigation, the mechanisms underlying this age-related decline in neurogenesis are only incompletely understood, but appear to include an increase in NSC quiescence, changes in differentiation patterns, and NSC exhaustion. In this review, we summarize recent work that has improved our knowledge of hippocampal NSC aging, focusing on NSC-intrinsic mechanisms as well as cellular and molecular changes in the niche and systemic environment that might be involved in the age-related decline in NSC functions. Additionally, we identify future directions that may advance our understanding of NSC aging and the concomitant loss of hippocampal neurogenesis and plasticity.

Organelle mapping in dendrites of human iPSC-derived neurons reveals dynamic functional dendritic Golgi structures

Secretory pathways within dendrites of neurons have been proposed for local transport of newly synthesized proteins. However, little is known about the dynamics of the local secretory system and whether the organelles are transient or stable structures. Here, we quantify the spatial and dynamic behavior of dendritic Golgi and endosomes during differentiation of human neurons generated from induced pluripotent stem cells (iPSCs). In early neuronal development, before and during migration, the entire Golgi apparatus transiently translocates from the soma into dendrites. In mature neurons, dynamic Golgi elements, containing cis and trans cisternae, are transported from the soma along dendrites, in an actin-dependent process. Dendritic Golgi outposts are dynamic and display bidirectional movement. Similar structures were observed in cerebral organoids. Using the retention using selective hooks (RUSH) system, Golgi resident proteins are transported efficiently into Golgi outposts from the endoplasmic reticulum. This study reveals dynamic, functional Golgi structures in dendrites and a spatial map for investigating dendrite trafficking in human neurons.

Role of GABAergic system in the comorbidity of pain and depression

Patients with chronic pain often suffer with depressive symptoms, and these two conditions can be aggravated by each other over time, leading to an increase in symptom intensity and duration. The comorbidity of pain and depression poses a significant challenge to human health and quality of life, as it is often difficult to diagnose early and treat effectively. Therefore, exploring the molecular mechanisms underlying the comorbidity of chronic pain and depression is crucial to identifying new therapeutic targets for treatment. However, understanding the pathogenesis of comorbidity requires examining interactions among multiple factors, which calls for an integrative perspective. While several studies have explored the role of the GABAergic system in pain and depression, fewer have examined its interactions with other systems involved in their comorbidity. Here, we review the evidence that the role of GABAergic system in the comorbidity of chronic pain and depression, as well as the interactions between the GABAergic system and other secondary systems involved in pain and depression comorbidity, providing a comprehensive understanding of their intricate interplay.

Native-state proteomics of Parvalbumin interneurons identifies novel molecular signatures and metabolic vulnerabilities to early Alzheimer's disease pathology

One of the earliest pathophysiological perturbations in Alzheimer's Disease (AD) may arise from dysfunction of fast-spiking parvalbumin (PV) interneurons (PV-INs). Defining early protein-level (proteomic) alterations in PV-INs can provide key biological and translationally relevant insights. Here, we use cell-type-specific in vivo biotinylation of proteins (CIBOP) coupled with mass spectrometry to obtain native-state proteomes of PV interneurons. PV-INs exhibited proteomic signatures of high metabolic, mitochondrial, and translational activity, with over-representation of causally linked AD genetic risk factors. Analyses of bulk brain proteomes indicated strong correlations between PV-IN proteins with cognitive decline in humans, and with progressive neuropathology in humans and mouse models of Aβ pathology. Furthermore, PV-IN-specific proteomes revealed unique signatures of increased mitochondrial and metabolic proteins, but decreased synaptic and mTOR signaling proteins in response to early Aβ pathology. PV-specific changes were not apparent in whole-brain proteomes. These findings showcase the first native state PV-IN proteomes in mammalian brain, revealing a molecular basis for their unique vulnerabilities in AD.

Genetically Defined Subtypes of Somatostatin-Containing Cortical Interneurons

Inhibitory interneurons play a crucial role in proper development and function of the mammalian cerebral cortex. Of the different inhibitory subclasses, dendritic-targeting, somatostatin-containing (SOM) interneurons may be the most diverse. Earlier studies used transgenic mouse lines to identify and characterize subtypes of SOM interneurons by morphological, electrophysiological and neurochemical properties. More recently, large-scale studies classified SOM interneurons into 13 morpho-electro-transcriptomic (MET) types. It remains unclear, however, how these various classification schemes relate to each other, and experimental access to MET types has been limited by the scarcity of type-specific mouse driver lines. To begin to address these issues we crossed Flp and Cre driver mouse lines and a dual-color combinatorial reporter, allowing experimental access to genetically defined SOM subsets. Brains from adult mice of both sexes were retrogradely dye-labeled from the pial surface to identify layer 1-projecting neurons, and immunostained against several marker proteins, allowing correlation of genetic label, axonal target and marker protein expression in the same neurons. Using whole-cell recordings ex-vivo, we compared electrophysiological properties between intersectional and transgenic SOM subsets. We identified two layer 1-targeting intersectional subsets with non-overlapping marker protein expression and electrophysiological properties which, together with a previously characterized layer 4-targeting subtype, account for about half of all layer 5 SOM cells and >40% of all SOM cells, and appear to map onto 5 of the 13 MET types. Genetic access to these subtypes will allow researchers to determine their synaptic inputs and outputs and uncover their roles in cortical computations and animal behavior.

SIGNIFICANCE STATEMENT

Inhibitory neurons are critically important for proper development and function of the cerebral cortex. Although a minority population, they are highly diverse, which poses a major challenge to investigating their contributions to cortical computations and animal and human behavior. As a step towards understanding this diversity we crossed genetically modified mouse lines to allow detailed examination of genetically-defined groups of the most diverse inhibitory subtype, somatostatin-containing interneurons. We identified and characterized three somatostatin subtypes in the deep cortical layers with distinct combinations of anatomical, neurochemical and electrophysiological properties. Future studies could now use these genetic tools to examine how these different subtypes are integrated into the cortical circuit and what roles they play during sensory, cognitive or motor behavior.

Electrophysiological Activity of Primary Cortical Neuron-Glia Mixed Cultures

Neuroinflammation plays a central role in many neurological disorders, ranging from traumatic brain injuries to neurodegeneration. Electrophysiological activity is an essential measure of neuronal function, which is influenced by neuroinflammation. In order to study neuroinflammation and its electrophysiological fingerprints, there is a need for in vitro models that accurately capture the in vivo phenomena. In this study, we employed a new tri-culture of primary rat neurons, astrocytes, and microglia in combination with extracellular electrophysiological recording techniques using multiple electrode arrays (MEAs) to determine the effect of microglia on neural function and the response to neuroinflammatory stimuli. Specifically, we established the tri-culture and its corresponding neuron-astrocyte co-culture (lacking microglia) counterpart on custom MEAs and monitored their electrophysiological activity for 21 days to assess culture maturation and network formation. As a complementary assessment, we quantified synaptic puncta and averaged spike waveforms to determine the difference in excitatory to inhibitory neuron ratio (E/I ratio) of the neurons. The results demonstrate that the microglia in the tri-culture do not disrupt neural network formation and stability and may be a better representation of the in vivo rat cortex due to its more similar E/I ratio as compared to more traditional isolated neuron and neuron-astrocyte co-cultures. In addition, only the tri-culture displayed a significant decrease in both the number of active channels and spike frequency following pro-inflammatory lipopolysaccharide exposure, highlighting the critical role of microglia in capturing electrophysiological manifestations of a representative neuroinflammatory insult. We expect the demonstrated technology to assist in studying various brain disease mechanisms.

Flexibility of in vitro cortical circuits influences resilience from microtrauma

Background

Small clusters comprising hundreds to thousands of neurons are an important level of brain architecture that correlates single neuronal properties to fulfill brain function, but the specific mechanisms through which this scaling occurs are not well understood. In this study, we developed an in vitro experimental platform of small neuronal circuits (islands) to probe the importance of structural properties for their development, physiology, and response to microtrauma.

Methods

Primary cortical neurons were plated on a substrate patterned to promote attachment in clusters of hundreds of cells (islands), transduced with GCaMP6f, allowed to mature until 10-13 days in vitro (DIV), and monitored with Ca²⁺ as a non-invasive proxy for electrical activity. We adjusted two structural factors-island size and cellular density-to evaluate their role in guiding spontaneous activity and network formation in neuronal islands.

Results

We found cellular density, but not island size, regulates of circuit activity and network function in this system. Low cellular density islands can achieve many states of activity, while high cellular density biases islands towards a limited regime characterized by low rates of activity and high synchronization, a property we summarized as "flexibility." The injury severity required for an island to lose activity in 50% of its population was significantly higher in low-density, high flexibility islands.

Conclusion

Together, these studies demonstrate flexible living cortical circuits are more resilient to microtrauma, providing the first evidence that initial circuit state may be a key factor to consider when evaluating the consequences of trauma to the cortex.

Age, Education Years, and Biochemical Factors Are Associated with Selective Neuronal Changes in the Elderly Hippocampus

Brain aging involves regional alterations of specific cellular subpopulations in the human hippocampus: a network hub for memory consolidation. The present study investigates whether age, sex, education years, and the concentration of neuropathological and inflammatory proteins influence neuronal-type marker expression in the elderly hippocampus. We analyzed the digital images (1 µm/pixel) of postmortem hippocampal sections from 19 non-demented individuals (from 78 to 99 years). This material was obtained from the "Aging Dementia and TBI Study" open database. Brain samples were processed through in situ hybridization (ISH) for the immunodetection of VGLUT1 (glutamatergic transporter) and GAT1 (GABAergic transporter) and mRNAs and Luminex protein quantifications. After image acquisition, we delineated the dentate gyrus, CA 3/2, and CA1 hippocampal subdivisions. Then, we estimated the area fraction in which the ISH markers were expressed. Increased VGLUT1 was observed in multiple hippocampal subfields at late ages. This glutamatergic marker is positively correlated with beta-amyloid and tau proteins and negatively correlated with interleukin-7 levels. Additionally, education years are positively correlated with GAT1 in the hippocampus of elderly women. This GABAergic marker expression is associated with interferon-gamma and brain-derived neurotrophic factor levels. These associations can help to explain how hippocampal sub-regions and neurotransmitter systems undergo distinct physiological changes during normal aging.

Functional network properties derived from wide-field calcium imaging differ with wakefulness and across cell type

To improve 'bench-to-bedside' translation, it is integral that knowledge flows bidirectionally-from animal models to humans, and vice versa. This requires common analytical frameworks, as well as open software and data sharing practices. We share a new pipeline (and test dataset) for the preprocessing of wide-field optical fluorescence imaging data-an emerging mode applicable in animal models-as well as results from a functional connectivity and graph theory analysis inspired by recent work in the human neuroimaging field. The approach is demonstrated using a dataset comprised of two test-cases: (1) data from animals imaged during awake and anesthetized conditions with excitatory neurons labeled, and (2) data from awake animals with different genetically encoded fluorescent labels that target either excitatory neurons or inhibitory interneuron subtypes. Both seed-based connectivity and graph theory measures (global efficiency, transitivity, modularity, and characteristic path-length) are shown to be useful in quantifying differences between wakefulness states and cell populations. Wakefulness state and cell type show widespread effects on canonical network connectivity with variable frequency band dependence. Differences between excitatory neurons and inhibitory interneurons are observed, with somatostatin expressing inhibitory interneurons emerging as notably dissimilar from parvalbumin and vasoactive polypeptide expressing cells. In sum, we demonstrate that our pipeline can be used to examine brain state and cell-type differences in mesoscale imaging data, aiding translational neuroscience efforts. In line with open science practices, we freely release the pipeline and data to encourage other efforts in the community.

Microglia contribute to the postnatal development of cortical somatostatin-positive inhibitory cells and to whisker-evoked cortical activity

Microglia play a key role in shaping the formation and refinement of the excitatory network of the brain. However, less is known about whether and how they organize the development of distinct inhibitory networks. We find that microglia are essential for the proper development of somatostatin-positive (SST⁺) cell synapses during the second postnatal week. We further identify a pair of molecules that act antagonistically to one another in the organization of SST⁺ cell axonal elaboration. Whereas CX3CL1 acts to suppress axonal growth and complexity, CXCL12 promotes it. Assessing the functional importance of microglia in the development of cortical activity, we find that a whisker stimulation paradigm that drives SST⁺ cell activation leads to reduced cortical spiking in brains depleted of microglia. Collectively, our data demonstrate an important role of microglia in regulating the development of SST⁺ cell output early in life.

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Microglia depletion leads to an increase of SST⁺ cell synapses during development

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Microglia control SST⁺ cell axonal development through CX3CL1 and CXCL12

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Microglia depletion reduces sensory-driven cortical activation early postnatally

Percolation may explain efficiency, robustness, and economy of the brain

The brain consists of billions of neurons connected by ultra-dense synapses, showing remarkable efficiency, robust flexibility, and economy in information processing. It is generally believed that these advantageous properties are rooted in brain connectivity; however, direct evidence remains absent owing to technical limitations or theoretical vacancy. This research explores the origins of these properties in the largest yet brain connectome of the fruit fly. We reveal that functional connectivity formation in the brain can be explained by a percolation process controlled by synaptic excitation-inhibition (E/I) balance. By increasing the E/I balance gradually, we discover the emergence of these properties as byproducts of percolation transition when the E/I balance arrives at 3:7. As the E/I balance keeps increase, an optimal E/I balance 1:1 is unveiled to ensure these three properties simultaneously, consistent with previous in vitro experimental predictions. Once the E/I balance reaches over 3:2, an intrinsic limitation of these properties determined by static (anatomical) brain connectivity can be observed. Our work demonstrates that percolation, a universal characterization of critical phenomena and phase transitions, may serve as a window toward understanding the emergence of various brain properties.

From Analog to Digital Computing: Is Homo sapiens’ Brain on Its Way to Become a Turing Machine?

The abstract basis of modern computation is the formal description of a finite state machine, the Universal Turing Machine, based on manipulation of integers and logic symbols. In this contribution to the discourse on the computer-brain analogy, we discuss the extent to which analog computing, as performed by the mammalian brain, is like and unlike the digital computing of Universal Turing Machines. We begin with ordinary reality being a permanent dialog between continuous and discontinuous worlds. So it is with computing, which can be analog or digital, and is often mixed. The theory behind computers is essentially digital, but efficient simulations of phenomena can be performed by analog devices; indeed, any physical calculation requires implementation in the physical world and is therefore analog to some extent, despite being based on abstract logic and arithmetic. The mammalian brain, comprised of neuronal networks, functions as an analog device and has given rise to artificial neural networks that are implemented as digital algorithms but function as analog models would. Analog constructs compute with the implementation of a variety of feedback and feedforward loops. In contrast, digital algorithms allow the implementation of recursive processes that enable them to generate unparalleled emergent properties. We briefly illustrate how the cortical organization of neurons can integrate signals and make predictions analogically. While we conclude that brains are not digital computers, we speculate on the recent implementation of human writing in the brain as a possible digital path that slowly evolves the brain into a genuine (slow) Turing machine.

Principles of GABAergic signaling in developing cortical network dynamics

GABAergic signaling provides inhibitory stabilization and spatiotemporally coordinates the firing of recurrently connected excitatory neurons in mature cortical circuits. Inhibition thus enables self-generated neuronal activity patterns that underlie various aspects of sensation and cognition. In this review, we aim to provide a conceptual framework describing how and when GABA-releasing interneurons acquire their network functions during development. Focusing on the developing visual neocortex and hippocampus in mice and rats in vivo, we hypothesize that at the onset of patterned activity, glutamatergic neurons are stable by themselves and inhibitory stabilization is not yet functional. We review important milestones in the development of GABAergic signaling and illustrate how the cell-type-specific strengthening of synaptic inhibition toward eye opening shapes cortical network dynamics and allows the developing cortex to progressively disengage from extra-cortical synaptic drive. We translate this framework to human cortical development and discuss clinical implications for the treatment of neonatal seizures.

Gabaergic Interneurons in Early Brain Development: Conducting and Orchestrated by Cortical Network Activity

Throughout early phases of brain development, the two main neural signaling mechanisms—excitation and inhibition—are dynamically sculpted in the neocortex to establish primary functions. Despite its relatively late formation and persistent developmental changes, the GABAergic system promotes the ordered shaping of neuronal circuits at the structural and functional levels. Within this frame, interneurons participate first in spontaneous and later in sensory-evoked activity patterns that precede cortical functions of the mature brain. Upon their subcortical generation, interneurons in the embryonic brain must first orderly migrate to and settle in respective target layers before they can actively engage in cortical network activity. During this process, changes at the molecular and synaptic level of interneurons allow not only their coordinated formation but also the pruning of connections as well as excitatory and inhibitory synapses. At the postsynaptic site, the shift of GABAergic signaling from an excitatory towards an inhibitory response is required to enable synchronization within cortical networks. Concomitantly, the progressive specification of different interneuron subtypes endows the neocortex with distinct local cortical circuits and region-specific modulation of neuronal firing. Finally, the apoptotic process further refines neuronal populations by constantly maintaining a controlled ratio of inhibitory and excitatory neurons. Interestingly, many of these fundamental and complex processes are influenced—if not directly controlled—by electrical activity. Interneurons on the subcellular, cellular, and network level are affected by high frequency patterns, such as spindle burst and gamma oscillations in rodents and delta brushes in humans. Conversely, the maturation of interneuron structure and function on each of these scales feeds back and contributes to the generation of cortical activity patterns that are essential for the proper peri- and postnatal development. Overall, a more precise description of the conducting role of interneurons in terms of how they contribute to specific activity patterns—as well as how specific activity patterns impinge on their maturation as orchestra members—will lead to a better understanding of the physiological and pathophysiological development and function of the nervous system.

Neuro-Scientific Analysis of Weights in Neural Networks

Deep learning is a popular topic among machine learning researchers nowadays, with great strides being made in recent years to develop robust artificial neural networks for faster convergence to a reasonable accuracy. Network architecture and hyperparameters of the model are fundamental aspects of model convergence. One such important parameter is the initial values of weights, also known as weight initialization. In this paper, we perform two research tasks concerned with the weights of neural networks. First, we develop three novel weight initialization algorithms inspired by the neuroscientific construction of the mammalian brains and then test them on benchmark datasets against other algorithms to compare and assess their performance. We call these algorithms the lognormal weight initialization, modified lognormal weight initialization, and skewed weight initialization. We observe from our results that these initialization algorithms provide state-of-the-art results on all of the benchmark datasets. Second, we analyze the influence of training an artificial neural network on its weight distribution by measuring the correlation between the quantitative metrics of skewness and kurtosis against the model accuracy using linear regression for different weight initializations. Results indicate a positive correlation between network accuracy and skewness of the weight distribution but no affirmative relation between accuracy and kurtosis. This analysis provides further insight into understanding the inner mechanism of neural network training using the shape of weight distribution. Overall, the works in this paper are the first of their kind in incorporating neuroscientific knowledge into the domain of artificial neural network weights.

Identification of neural oscillations and epileptiform changes in human brain organoids

Brain organoids represent a powerful tool for studying human neurological diseases, particularly those that affect brain growth and structure. However, many diseases manifest with clear evidence of physiological and network abnormality in the absence of anatomical changes, raising the question of whether organoids possess sufficient neural network complexity to model these conditions. Here, we explore the network-level functions of brain organoids using calcium sensor imaging and extracellular recording approaches that together reveal the existence of complex network dynamics reminiscent of intact brain preparations. We demonstrate highly abnormal and epileptiform-like activity in organoids derived from induced pluripotent stem cells from individuals with Rett syndrome, accompanied by transcriptomic differences revealed by single-cell analyses. We also rescue key physiological activities with an unconventional neuroregulatory drug, pifithrin-α. Together, these findings provide an essential foundation for the utilization of brain organoids to study intact and disordered human brain network formation and illustrate their utility in therapeutic discovery.