Neural Circuits Research Articles

Nr4a1 regulates cell-specific transcriptional programs in inhibitory GABAergic interneurons.

The patterns of synaptic connectivity and physiological properties of diverse neuron types are shaped by distinct gene sets. Our study demonstrates that, in the mouse forebrain, the transcriptional profiles of inhibitory GABAergic interneurons are regulated by Nr4a1, an orphan nuclear receptor whose expression is transiently induced by sensory experiences and is required for normal learning. Nr4a1 exerts contrasting effects on the local axonal wiring of parvalbumin- and somatostatin-positive interneurons, which innervate different subcellular domains of their postsynaptic partners. The loss of Nr4a1 activity in these interneurons results in bidirectional, cell-type-specific transcriptional switches across multiple gene families, including those involved in surface adhesion and repulsion. Our findings reveal that combinatorial synaptic organizing codes are surprisingly flexible and highlight a mechanism by which inducible transcription factors can influence neural circuit structure and function.

Neuronal basis and diverse mechanisms of pathogen avoidance in Caenorhabditis elegans.

Pathogen avoidance behaviour has been observed across animal taxa as a vital host-microbe interaction mechanism. The nematode Caenorhabditis elegans has evolved multiple diverse mechanisms for pathogen avoidance under natural selection pressure. We summarise the current knowledge of the stimuli that trigger pathogen avoidance, including alterations in aerotaxis, intestinal bloating, and metabolites. We then survey the neural circuits involved in pathogen avoidance, transgenerational epigenetic inheritance of pathogen avoidance, signalling crosstalk between pathogen avoidance and innate immunity, and C. elegans avoidance of non-Pseudomonas bacteria. In this review, we highlight the latest advances in understanding host-microbe interactions and the gut-brain axis.

Dynamic effective connectivity in the cerebellar dorsal dentate nucleus and the cerebrum, cognitive impairment, and clinical correlates in patients with schizophrenia

BackgroundSchizophrenia (SZ) is characterized by disconnected cerebral networks. Recent studies have shown that functional connectivity between the cerebellar dorsal dentate nucleus (dDN) and cerebrum is correlated with psychotic symptoms, and processing speed in SZ patients. Dynamic effective connectivity (dEC) is a reliable indicator of brain functional status. However, the dEC between the dDN and cerebrum in patients with SZ remains largely unknown. MethodsResting-state functional MRI data, symptom severity, and cognitive performance were collected from 74 SZ patients and 53 healthy controls (HC). Granger causality analysis and sliding time window methods were used to calculate dDN-based dEC maps for all subjects, and k-means clustering was performed to obtain several dEC states. Finally, between-group differences in dynamic effective connectivity variability (dECV) and clinical correlations were obtained using two-sample t-tests and correlation analysis. ResultsWe detected four dEC states from the cerebrum to the right dDN (IN states) and three dEC states from the right dDN to the cerebrum (OUT states), with SZ group having fewer transitions in the OUT states. SZ group had increased dECV from the right dDN to the right middle frontal gyrus (MFG) and left lingual gyrus (LG). Correlations were found between the dECV from the right dDN to the right MFG and symptom severity and between the dECV from the right dDN to the left LG and working memory performance. ConclusionsThis study reveals a dynamic causal relationship between cerebellar dDN and the cerebrum in SZ and provides new evidence for the involvement of cerebellar neural circuits in neurocognitive functions in SZ.

Hormonal and circuit mechanisms controlling female sexual behavior.

Sexual behavior is crucial for reproduction in many animals. In many vertebrates, females exhibit sexual behavior only during a brief period surrounding ovulation. Over the decades, studies have identified the roles of ovarian sex hormones, which peak in levels around the time of ovulation, and the critical brain regions involved in the regulation of female sexual behavior. Modern technical innovations have enabled a deeper understanding of the neural circuit mechanisms controlling this behavior. In this review, I summarize our current knowledge and discuss the neural circuit mechanisms by which female sexual behavior occurs in association with the ovulatory phase of their cycle.

Interoception in Autism: A Narrative Review of Behavioral and Neurobiological Data.

While exteroceptive sensory processing is a hallmark of autism spectrum disorder, how interoceptive processing may impact and contribute to symptomatology remains unclear. In this comprehensive narrative review on interoception in autism, we discuss: 1) difficulties with assessing interoception; 2) potential interoceptive differences; 3) interactions between neural systems for interoception, attention, sensorimotor processing, and cognition; and 4) potential differences in neural circuits involved in interoception. In general, there are mixed findings on potential interoception differences in autism. Nevertheless, some data indicate differences in integration of interoceptive and exteroceptive information may contribute to autism symptomatology. Neurologically, interoceptive processing in autism may be impacted by potential differences in the development, morphometry, and connectivity of key interoceptive hubs (vagal processing, brainstem, thalamus, insula), though much work is needed on this topic.

Reciprocal inhibition of the thigh muscles in humans: A study using transcutaneous spinal cord stimulation.

Evaluating reciprocal inhibition of the thigh muscles is important to investigate the neural circuits of locomotor behaviors. However, measurements of reciprocal inhibition of thigh muscles using spinal reflex, such as H-reflex, have never been systematically established owing to methodological limitations. The present study aimed to clarify the existence of reciprocal inhibition in the thigh muscles using transcutaneous spinal cord stimulation (tSCS). Twenty able-bodied male individuals were enrolled. We evoked spinal reflex from the biceps femoris muscle (BF) by tSCS on the lumber posterior root. We examined whether the tSCS-evoked BF reflex was reciprocally inhibited by the following conditionings: (1) single-pulse electrical stimulation on the femoral nerve innervating the rectus femoris muscle (RF) at various inter-stimulus intervals in the resting condition; (2) voluntary contraction of the RF; and (3) vibration stimulus on the RF. The BF reflex was significantly inhibited when the conditioning electrical stimulation was delivered at 10 and 20 ms prior to tSCS, during voluntary contraction of the RF, and during vibration on the RF. These data suggested a piece of evidence of the existence of reciprocal inhibition from the RF to the BF muscle in humans and highlighted the utility of methods for evaluating reciprocal inhibition of the thigh muscles using tSCS.

Intergenerational Transmission of Maternal Life Stress and Sleep on Infant Neural Circuits and Behavioral Outcomes

Intergenerational Transmission of Maternal Life Stress and Sleep on Infant Neural Circuits and Behavioral Outcomes

89. Shared Disruptions in Neural Circuits of Eye Gaze Processing in Autism Spectrum Disorder and Schizophrenia

89. Shared Disruptions in Neural Circuits of Eye Gaze Processing in Autism Spectrum Disorder and Schizophrenia

Complementation testing identifies genes mediating effects at quantitative trait loci underlying fear-related behavior

Knowing the genes involved in quantitative traits provides an entry point to understanding the biological bases of behavior, but there are very few examples where the pathway from genetic locus to behavioral change is known. To explore the role of specific genes in fear behavior, we mapped three fear-related traits, tested fourteen genes at six quantitative trait loci (QTLs) by quantitative complementation, and identified six genes. Four genes, Lamp, Ptprd, Nptx2, and Sh3gl, have known roles in synapse function; the fifth, Psip1, was not previously implicated in behavior; and the sixth is a long non-coding RNA, 4933413L06Rik, of unknown function. Variation in transcriptome and epigenetic modalities occurred preferentially in excitatory neurons, suggesting that genetic variation is more permissible in excitatory than inhibitory neuronal circuits. Our results relieve a bottleneck in using genetic mapping of QTLs to uncover biology underlying behavior and prompt a reconsideration of expected relationships between genetic and functional variation.

Microscope-integrated optical coherence tomography for in vivo human brain tumor detection with artificial intelligence.

It has been shown that optical coherence tomography (OCT) can identify brain tumor tissue and potentially be used for intraoperative margin diagnostics. However, there is limited evidence on its use in human in vivo settings, particularly in terms of its applicability and accuracy of residual brain tumor detection (RTD). For this reason, a microscope-integrated OCT system was examined to determine in vivo feasibility of RTD after resection with automated scan analysis. Healthy and diseased brain was 3D scanned at the resection edge in 18 brain tumor patients and investigated for its informative value in regard to intraoperative tissue classification. Biopsies were taken at these locations and labeled by a neuropathologist for further analysis as ground truth. Optical OCT properties were obtained, compared, and used for separation with machine learning. In addition, two artificial intelligence-assisted methods were utilized for scan classification, and all approaches were examined for RTD accuracy and compared to standard techniques. In vivo OCT tissue scanning was feasible and easily integrable into the surgical workflow. Measured backscattered light signal intensity, signal attenuation, and signal homogeneity were significantly distinctive in the comparison of scanned white matter to increasing levels of scanned tumor infiltration (p < 0.001) and achieved high values of accuracy (85%) for the detection of diseased brain in the tumor margin with support vector machine separation. A neuronal network approach achieved 82% accuracy and an autoencoder approach 85% accuracy in the detection of diseased brain in the tumor margin. Differentiating cortical gray matter from tumor tissue was not technically feasible in vivo. In vivo OCT scanning of the human brain has been shown to contain significant value for intraoperative RTD, supporting what has previously been discussed for ex vivo OCT brain tumor scanning, with the perspective of complementing current intraoperative methods for this purpose, especially when deciding to withdraw from further resection toward the end of the surgery.

Aging-associated weakening of the action potential in fast-spiking interneurons in the human neocortex

Aging is associated with the slowdown of neuronal processing and cognitive performance in the brain; however, the exact cellular mechanisms behind this deterioration in humans are poorly elucidated. Recordings in human acute brain slices prepared from tissue resected during brain surgery enable the investigation of neuronal changes with age. Although neocortical fast-spiking cells are widely implicated in neuronal network activities underlying cognitive processes, they are vulnerable to neurodegeneration. Herein, we analyzed the electrical properties of 147 fast-spiking interneurons in neocortex samples resected in brain surgery from 106 patients aged 11–84 years. By studying the electrophysiological features of action potentials and passive membrane properties, we report that action potential overshoot significantly decreases and spike half-width increases with age. Moreover, the action potential maximum-rise speed (but not the repolarization speed or the afterhyperpolarization amplitude) significantly changed with age, suggesting a particular weakening of the sodium channel current generated in the soma. Cell passive membrane properties measured as the input resistance, membrane time constant, and cell capacitance remained unaffected by senescence. Thus, we conclude that the action potential in fast-spiking interneurons shows a significant weakening in the human neocortex with age. This may contribute to the deterioration of cortical functions by aging.

Enhanced adsorption of Bismark Brown R dye by chitosan conjugated magnetic pectin loaded filter mud: A comprehensive study on modeling and mechanisms

Herein, a polymer-based bioadsorbent was prepared by cross-linking chitosan to filter mud and magnetic pectin (Ch-mPC@FM) for the removal of Bismark Brown R dye (BB-R) from wastewater. Morphological characterization analysis indicated that Ch-mPC@FM had a higher surface area and better pore structure than its components. The Artificial Neuron Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) were employed to evaluate the simulation and prediction of the adsorption process based on input variables like temperature, pH, dosage, initial BB-R dye concentration, and contact time. ANFIS and ANN demonstrated significant modeling and predictive accuracy, with R2 > 0.93 and R2 > 0.96, and root mean square error < 0.023 and <0.020, respectively. The Langmuir isotherm and the pseudo-second-order kinetic models provided the best fits to the equilibrium and kinetic data. The thermodynamic assessment showed spontaneous and endothermic adsorption with average entropy and enthalpy changes of 119.32 kJ mol−1 K and 403.47 kJ mol−1, respectively. The study of BB-R dye adsorption on Ch-mPC@FM revealed multiple mechanisms, including electrostatic, complexation, pore filling, cation-π interaction, hydrogen bonding, and π-π interactions. The approximate production cost of US$ 5.809 Kg−1 and excellent adsorption capability render Ch-mPC@FM an inexpensive, pragmatic, and ecologically safe bioadsorbent for BB-R dye removal from wastewater.

Multimodal Technologies for Closed-Loop Neural Modulation and Sensing.

Existing methods for studying neural circuits and treating neurological disorders are typically based on physical and chemical cues to manipulate and record neural activities. These approaches often involve predefined, rigid, and unchangeable signal patterns, which cannot be adjusted in real time according to the patient's condition or neural activities. With the continuous development of neural interfaces, conducting in vivo research on adaptive and modifiable treatments for neurological diseases and neural circuits is now possible. In this review, current and potential integration of various modalities to achieve precise, closed-loop modulation, and sensing in neural systems are summarized. Advanced materials, devices, or systems that generate or detect electrical, magnetic, optical, acoustic, or chemical signals are highlighted and utilized to interact with neural cells, tissues, and networks for closed-loop interrogation. Further, the significance of developing closed-loop techniques for diagnostics and treatment of neurological disorders such as epilepsy, depression, rehabilitation of spinal cord injury patients, and exploration of brain neural circuit functionality is elaborated.

Aberrant cortical activity, functional connectivity, and neural assembly architecture after photothrombotic stroke in mice.

Despite substantial progress in mapping the trajectory of network plasticity resulting from focal ischemic stroke, the extent and nature of changes in neuronal excitability and activity within the peri-infarct cortex of mice remains poorly defined. Most of the available data have been acquired from anesthetized animals, acute tissue slices, or infer changes in excitability from immunoassays on extracted tissue, and thus may not reflect cortical activity dynamics in the intact cortex of an awake animal. Here, in vivo two-photon calcium imaging in awake, behaving mice was used to longitudinally track cortical activity, network functional connectivity, and neural assembly architecture for 2 months following photothrombotic stroke targeting the forelimb somatosensory cortex. Sensorimotor recovery was tracked over the weeks following stroke, allowing us to relate network changes to behavior. Our data revealed spatially restricted but long-lasting alterations in somatosensory neural network function and connectivity. Specifically, we demonstrate significant and long-lasting disruptions in neural assembly architecture concurrent with a deficit in functional connectivity between individual neurons. Reductions in neuronal spiking in peri-infarct cortex were transient but predictive of impairment in skilled locomotion measured in the tapered beam task. Notably, altered neural networks were highly localized, with assembly architecture and neural connectivity relatively unaltered a short distance from the peri-infarct cortex, even in regions within 'remapped' forelimb functional representations identified using mesoscale imaging with anaesthetized preparations 8 weeks after stroke. Thus, using longitudinal two-photon microscopy in awake animals, these data show a complex spatiotemporal relationship between peri-infarct neuronal network function and behavioral recovery. Moreover, the data highlight an apparent disconnect between dramatic functional remapping identified using strong sensory stimulation in anaesthetized mice compared to more subtle and spatially restricted changes in individual neuron and local network function in awake mice during stroke recovery.

Aberrant cortical activity, functional connectivity, and neural assembly architecture after photothrombotic stroke in mice

Despite substantial progress in mapping the trajectory of network plasticity resulting from focal ischemic stroke, the extent and nature of changes in neuronal excitability and activity within the peri-infarct cortex of mice remains poorly defined. Most of the available data have been acquired from anesthetized animals, acute tissue slices, or infer changes in excitability from immunoassays on extracted tissue, and thus may not reflect cortical activity dynamics in the intact cortex of an awake animal. Here, in vivo two-photon calcium imaging in awake, behaving mice was used to longitudinally track cortical activity, network functional connectivity, and neural assembly architecture for 2 months following photothrombotic stroke targeting the forelimb somatosensory cortex. Sensorimotor recovery was tracked over the weeks following stroke, allowing us to relate network changes to behavior. Our data revealed spatially restricted but long-lasting alterations in somatosensory neural network function and connectivity. Specifically, we demonstrate significant and long-lasting disruptions in neural assembly architecture concurrent with a deficit in functional connectivity between individual neurons. Reductions in neuronal spiking in peri-infarct cortex were transient but predictive of impairment in skilled locomotion measured in the tapered beam task. Notably, altered neural networks were highly localized, with assembly architecture and neural connectivity relatively unaltered a short distance from the peri-infarct cortex, even in regions within ‘remapped’ forelimb functional representations identified using mesoscale imaging with anaesthetized preparations 8 weeks after stroke. Thus, using longitudinal two-photon microscopy in awake animals, these data show a complex spatiotemporal relationship between peri-infarct neuronal network function and behavioral recovery. Moreover, the data highlight an apparent disconnect between dramatic functional remapping identified using strong sensory stimulation in anaesthetized mice compared to more subtle and spatially restricted changes in individual neuron and local network function in awake mice during stroke recovery.

The limits of knowledge

The definition of knowledge encompasses various meanings, from the process by which we have the perception of the outside world, through the stimuli that we receive from this, when that perception becomes part of our system of awareness and experience. When awareness of ourselves and the outside world is acquired and recorded, we can define it as learning. In the broader, philosophical sense, knowledge consists in learning and retaining in the mind a notion, an information. In use, however, it has a more concrete semantic value, and can indicate the various degrees of knowledge, from the initial perception of the existence of a thing to the full cognition of its being, its modes and qualities. Whatever the subject, cell, organism, neuronal network, and so on, the process always takes place by the use of specific receptor systems, adapted to the reception of different stimuli from the environment. Because they are calibrated only on the stimuli they receive, the receptor systems have limited sensitivity. This limitation is extended to all living beings, who therefore have partial and incomplete knowledge of the world. In this work we are going to examine these limitations and invite scholars to become aware of them.

FORECASTING THE CONSUMPTION OF ELECTRICAL ENERGY ON THE CEB ELECTRICAL NETWORK IN LOME IN TOGO BY APPROACHES: SIMPLE LINEAR REGRESSION, RECURRENT NEURAL NETWORKS AND GENETIC ALGORITHMS

Forecasting the electrical power to be consumed requires planning production on several levels. In this work we used data from the Electric Community of Benin. Temperature, relative humidity, wind speed, normal direct irradiance, precipitation and diffuse radiation are the meteorological variables that made it possible to analyze the forecasts. The objective is to do learning with genetic algorithms, LSTM recurrent neural networks and simple linear regression after a characterization and a correlation study and then to submit the results to performance evaluation criteria. The results of the characterization made it possible to understand that certain variables are significant and influence the consumption of electrical energy. The study of the correlation gives 94% between direct normal irradiance and diffuse irradiance. Both give with the temperature 67% for one and 68% for the other. Regarding modeling, the results are bad with genetic algorithms if we take into account the correlation coefficient (R² = 28.84%), good with simple linear regression (R² = 69.08%) and very interesting for networks of recurrent neurons where we find: MAE = 0.11 MSE = 0.02 MAPE = 18.50% RMSE = 13.09% RRMSE = 18.25% and R² = 96.11%. Given these results, we deduce that short- and long-term memory recurrent neural networks (LSTM) are very well suited to predicting the electrical power consumed on the CEB electrical network.

Optimizing Hyperparameters for Enhanced Performance in Convolutional Neural Networks: A Study Using NASNetMobile and DenseNet201 Models

Convolutional neural networks, inspired by the workings of biological neural networks, have proven highly successful in tasks like image data recognition, classification, and feature extraction. Yet, designing and implementing these networks pose certain challenges. One such challenge involves optimizing hyperparameters tailored to the specific model, dataset, and hardware. This study delved into how various hyperparameters impact the classification performance of convolutional neural network models. The investigation focused on parameters like the number of epochs, neurons, batch size, activation functions, optimization algorithms, and learning rate. Using the Keras library, experiments were conducted using NASNetMobile and DenseNet201 models—highlighted for their superior performance on the dataset. After running 65 different training sessions, accuracy rates saw a notable increase of 6.5% for NASNetMobile and 11.55% for DenseNet201 compared to their initial values.

Sensory Stimulation-dependent Npas4 Expression in the Olfactory Bulb during Early Postnatal Development.

The development of the olfactory system is influenced by sensory inputs, and it maintains neuronal generation and plasticity throughout the lifespan. The olfactory bulb contains a higher proportion of interneurons than other brain regions, particularly during the early postnatal period of neurogenesis. Although the relationship between sensory stimulation and olfactory bulb development during the postnatal period has been well studied, the molecular mechanisms have yet to be identified. In this study, we used western blotting and immunohistochemistry to analyze the expression of the transcription factor Npas4, a neuron-specific immediate-early gene that acts as a developmental regulator in many brain regions. We found that Npas4 is highly expressed in olfactory bulb interneurons during the early postnatal stages and gradually decreases toward the late postnatal stages. Npas4 expression was observed in all olfactory bulb layers, including the rostral migratory stream, where newborn neurons are generated and migrate to the olfactory bulb. Under sensory deprivation, the olfactory bulb size and the number of olfactory bulb interneurons were reduced. Furthermore, Npas4 expression and the expression of putative Npas4 downstream molecules were decreased. Collectively, these findings indicate that Npas4 expression induced by sensory input plays a role in the formation of neural circuits with excitatory mitral/tufted cells by regulating the survival of olfactory bulb interneurons during the early stages of postnatal development.

Stress during pubertal development affects female sociosexual behavior in mice

Puberty is a crucial phase for the development of female sexual behavior. Growing evidence suggests that stress during this period may interfere with the development of sexual behavior. However, the neural circuits involved in this alteration remain elusive. Here, we demonstrated in mice that pubertal stress permanently disrupted sexual performance without affecting sexual preference. This was associated with a reduced expression and activation of neuronal nitric oxide synthase (nNOS) in the ventrolateral part of the ventromedial hypothalamus (VMHvl). Fiber photometry revealed that VMHvl nNOS neurons are strongly responsive to male olfactory cues with this activation being substantially reduced in pubertally stressed females. Finally, treatment with a NO donor partially restored sexual performance in pubertally stressed females. This study provides insights into the involvement of VMHvl nNOS in the processing of olfactory cues important for the expression of female sexual behavior. In addition, exposure to stress during puberty disrupts the integration of male olfactory cues leading to reduced sexual behavior.