neural circuits

The ventral subiculum (vSUB), the major output structure of the hippocampal formation, regulates motivation, stress integration, and anxiety-like behaviors that rely on heightened arousal. However, the roles and underlying neural circuits of the vSUB in wakefulness are poorly known. Using in vivo fiber photometry and multichannel electrophysiological recordings in mice, we found that the vSUB glutamatergic neurons exhibited high activities during wakefulness. Moreover, activation of vSUB glutamatergic neurons caused an increase in wakefulness and anxiety-like behaviors and induced a rapid transition from sleep to wakefulness...

The activity of neurons in sensory areas sometimes covaries with upcoming choices in decision-making tasks. However, the prevalence, causal origin, and functional role of choice-related activity remain controversial. Understanding the circuit-logic of decision signals in sensory areas will require understanding their laminar specificity, but simultaneous recordings of neural activity across the cortical layers in forced-choice discrimination tasks have not yet been performed. Here, we describe neural activity from such recordings in the auditory cortex of mice during a frequency discrimination task with delayed report, which, as we show, requires the auditory cortex...

We used diverse methods to characterize the role of avian lateral spiriform nucleus (SpL) in basal ganglia motor function. Connectivity analysis showed that SpL receives input from globus pallidus (GP), and the intrapeduncular nucleus (INP) located ventromedial to GP, whose neurons express numerous striatal markers. SpL-projecting GP neurons were large and aspiny, while SpL-projecting INP neurons were medium sized and spiny. Connectivity analysis further showed that SpL receives inputs from subthalamic nucleus (STN) and substantia nigra pars reticulata (SNr), and that the SNr also receives inputs from GP, INP, and STN...

The remaining useful life (RUL) prediction of RF circuits is an important tool for circuit reliability. Data-driven-based approaches do not require knowledge of the failure mechanism and reduce the dependence on knowledge of complex circuits, and thus can effectively realize RUL prediction. This manuscript proposes a novel RUL prediction method based on a gated recurrent unit-convolutional neural network (GRU-CNN). Firstly, the data are normalized to improve the efficiency of the algorithm; secondly, the degradation of the circuit is evaluated using the hybrid health score based on the Euclidean and Manhattan distances; then, the life cycle of the RF circuits is segmented based on the hybrid health scores; and finally, an RUL prediction is carried out for the circuits at each stage using the GRU-CNN model...

This paper addresses the issue of LED short-circuit fault detection in signaling and lighting systems in the automotive industry. The conventional diagnostic method commonly implemented in newer vehicles relies on measuring the voltage drop across different LED branches and comparing it with threshold values indicating faults caused by open circuits or LED short circuits. With this algorithm, detecting cases of a few LEDs short-circuited within a branch, particularly a single malfunctioning LED, is particularly challenging...

Intelligent compaction (IC) has emerged as a breakthrough technology that utilizes advanced sensing, data transmission, and control systems to optimize asphalt pavement compaction quality and efficiency. However, accurate assessment of compaction status remains challenging under real construction conditions. This paper reviewed recent progress and applications of smart sensors and machine learning (ML) to address existing limitations in IC. The principles and components of various advanced sensors deployed in IC systems were introduced, including SmartRock, fiber Bragg grating, and integrated circuit piezoelectric acceleration sensors...

Methamphetamine, a commonly abused drug, is known for its high relapse rate. The persistence of addictive memories associated with methamphetamine poses a significant challenge in preventing relapse. Memory retrieval and subsequent reconsolidation provide an opportunity to disrupt addictive memories. However, the key node in the brain network involved in methamphetamine-associated memory retrieval has not been clearly defined. In this study, using the conditioned place preference in male mice, whole brain c-FOS mapping and functional connectivity analysis, together with chemogenetic manipulations of neural circuits, we identified the medial prefrontal cortex (mPFC) as a critical hub that integrates inputs from the retrosplenial cortex and the ventral tegmental area to support both the expression and reconsolidation of methamphetamine-associated memory during its retrieval...

BACKGROUND: Schizophrenia (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. METHODS: Resting-state functional MRI data, symptom severity, and cognitive performance were collected from 74 SZ patients and 53 healthy controls (HC)...

Inhibitory neurons embedded within mammalian neural circuits shape breathing, walking, and other rhythmic motor behaviors. At the core of the neural circuit controlling breathing is the preBötzinger Complex (preBötC), where GABAergic (GAD1/2+ ) and glycinergic (GlyT2+ ) neurons are functionally and anatomically intercalated among glutamatergic Dbx1-derived (Dbx1+ ) neurons that generate rhythmic inspiratory drive. The roles of these preBötC inhibitory neurons in breathing remain unclear. We first characterized the spatial distribution of molecularly-defined preBötC inhibitory subpopulations in male and female neonatal double reporter mice expressing either tdTomato or EGFP in GlyT2+ , GAD1+ , or GAD2+ neurons...

The development of the vertebrate spinal cord involves the formation of the neural tube and the generation of multiple distinct cell types. The process starts during gastrulation, combining axial elongation with specification of neural cells and the formation of the neuroepithelium. Tissue movements produce the neural tube which is then exposed to signals that provide patterning information to neural progenitors. The intracellular response to these signals, via a gene regulatory network, governs the spatial and temporal differentiation of progenitors into specific cell types, facilitating the assembly of functional neuronal circuits...

The property of mixed selectivity has been discussed at a computational level and offers a strategy to maximize computational power by adding versatility to the functional role of each neuron. Here, we offer a biologically grounded implementational-level mechanistic explanation for mixed selectivity in neural circuits. We define pure, linear, and nonlinear mixed selectivity and discuss how these response properties can be obtained in simple neural circuits. Neurons that respond to multiple, statistically independent variables display mixed selectivity...

Implantable electrode arrays are powerful tools for directly interrogating neural circuitry in the brain, but implementing this technology in the spinal cord in behaving animals has been challenging due to the spinal cord's significant motion with respect to the vertebral column during behavior. Consequently, the individual and ensemble activity of spinal neurons processing motor commands remains poorly understood. Here, we demonstrate that custom ultraflexible 1-μm-thick polyimide nanoelectronic threads can conduct laminar recordings of many neuronal units within the lumbar spinal cord of unrestrained, freely moving mice...

Next generation of wireless brain-computer-interface (BCI) devices require dedicated neural signal processors (NSPs) to extract key neurological information while operating within given power consumption and transmission bandwidth limits. Spike detection and clustering are important signal processing steps in neurological research and clinical applications. Computational-friendly spike detection and feature extraction algorithms are first systematically evaluated in this work. The nonlinear energy operator (NEO) and the first-and-second-derivative (FSDE) together with the 'perturbed' K-mean clustering achieve the highest accuracy performance...

Zebrafish are a powerful system to study brain development and to dissect the activity of complex circuits. One advantage is that they display complex behaviors, including prey capture, learning, responses to photic and acoustic stimuli, and social interaction (Dreosti et al., Front Neural Circuits 9:39, 2015; Bruckner et al., PLoS Biol 20:e3001838, 2022; Zoodsma et al., Mol Autism 13:38, 2022) that can be probed to assess brain function. Many of these behaviors are easily assayed at early larval stages, offering a noninvasive and high-throughput readout of nervous system function...

Synapses play a pivotal role in forming neural circuits, with critical implications for brain functions such as learning, memory, and emotions. Several advances in synaptic research have demonstrated the diversity of synaptic structure and function, which can form thousands of connections depending on the neuronal cell types. Moreover, synapses not only interconnect neurons but also establish connections with glial cells such as astrocytes, which play a key role in the architecture and function of neuronal circuits in the brain...

BACKGROUND: Fear responses significantly affect daily life and shape our approach to uncertainty. However, the potential resurgence of fear in unfamiliar situations poses a significant challenge to exposure-based therapies for maladaptive fear responses. Nonetheless, how novel contextual stimuli are associated with the relapse of extinguished fear remains unknown. METHODS: Using a context-dependent fear renewal model, the functional circuits and underlying mechanisms of the posterior parietal cortex (PPC) and anterior cingulate cortex (ACC) were investigated using optogenetic, histological, in vivo, and ex vivo electrophysiological and pharmacological techniques...

SIGNIFICANCE: Pain comprises a complex interaction between motor action and somatosensation that is dependent on dynamic interactions between the brain and spinal cord. This makes understanding pain particularly challenging as it involves rich interactions between many circuits (e.g., neural and vascular) and signaling cascades throughout the body. As such, experimentation on a single region may lead to an incomplete and potentially incorrect understanding of crucial underlying mechanisms...

Background The subgenual cingulate cortex (SGC) has been identified as a key structure within multiple neural circuits whose dysfunction is implicated in the neurobiology of depression. Deep brain stimulation in the SGC is thought to reduce and normalize local metabolism, causing normalization of circuit behavior and an improvement in depressive symptoms. We hypothesized that nonablative stereotactic radiosurgery (SRS) to the SGC would reduce local metabolism and reduce the severity of depression in patients with treatment-resistant bipolar depression...

Mounting evidence from animal models and human studies indicates that psychostimulants can significantly affect social behaviors. This is not surprising considering that the neural circuits underlying the regulation and expression of social behaviors are highly overlapped with those targeted by psychostimulants, which in most cases have strong rewarding and, consequently, addictive properties. In the present work, we provide an overview regarding the effects of illicit and prescription psychostimulants, such as cocaine, amphetamine-type stimulants, methylphenidate or modafinil, upon social behaviors such as social play, maternal behavior, aggression, pair bonding and social cognition and how psychostimulants in both animals and humans alter them...

Deep brain stimulation (DBS) is a powerful tool for the treatment of circuitopathy-related neurological and psychiatric diseases and disorders such as Parkinson's disease and obsessive-compulsive disorder, as well as a critical research tool for perturbing neural circuits and exploring neuroprostheses. Electrically mediated DBS, however, is limited by the spread of stimulus currents into tissue unrelated to disease course and treatment, potentially causing undesirable patient side effects. In this work, we utilize infrared neural stimulation (INS), an optical neuromodulation technique that uses near to midinfrared light to drive graded excitatory and inhibitory responses in nerves and neurons, to facilitate an optical and spatially constrained DBS paradigm...