Traditional neuropathic pain models such as chronic constriction injury (CCI) induce permanent peripheral nerve damage and cannot mimic persistent pain after resolved transient nerve compression. We established an acute constriction injury (ACI) model on male C57BL/6 J mice with 2-h sciatic nerve constriction followed by complete ligature removal, and performed a 250-day multimodal longitudinal comparison of Control, CCI and ACI mice using behavioral pain assays, somatosensory evoked potentials (SEPs), sciatic function index (SFI), nerve histology, muscle atrophy measurement, open field test, and serial 9.4 T pain-evoked BOLD-fMRI. ACI and CCI mice developed comparable long-lasting ipsilateral and delayed contralateral mechanical allodynia and thermal hyperalgesia over the 250-day observation period. Nonetheless, ACI mice achieved robust peripheral nerve structural and functional recovery without muscle atrophy, whereas CCI mice suffered irreversible peripheral nerve lesions. Serial fMRI revealed distinct brain activation trajectories: ACI mice exhibited spatially restricted response reductions relative to Controls and widespread suppression relative to CCI mice at day 3, isolated hypothalamic activation at day 12, and widespread bilateral activation of brainstem descending modulatory networks at day 250; in contrast, CCI mice showed cerebellar and somatosensory cortical activation at early/mid time points and significant deactivation of striatal-limbic circuits at late chronic stages. Anxiety-like behaviors were detected in both CCI and ACI mice at 12 day post-surgery but only in ACI mice at 7 months post-injury. These data support the pain centralization hypothesis: Brief peripheral nerve insult triggers self-maintained central sensitization that sustains chronic pain after peripheral anatomical and functional recovery. The ACI model may facilitate translational research on central-targeted therapeutics for compression-induced persistent neuropathic pain.
Zebrafish (Danio rerio) are a widely used animal model to study a variety of neuropsychiatric disorders, including drug addiction. Existing paradigms to examine alcohol addiction use repeated daily or continuous ethanol exposures over multiple days. The present study evaluated a condensed repeated dosing paradigm, involving three 1-h ethanol doses (0.8%) per day over 5 days. To examine ethanol withdrawal, locomotor and anxiety-like behavior was assessed at 2, 4, and 8 days following the dosing schedule, using the open field test. There was a significant increase in immobility and angular velocity with ethanol regardless of withdrawal duration. At 8 days of withdrawal, ethanol-treated fish spent significantly less time highly mobile compared to controls. Likewise, there was a change in zone preference at 8 days of withdrawal, with ethanol-treated fish spending significantly more time in the transition zone and less time in the thigmotaxis zone compared to controls. No other significant zone preferences or sex differences were found. These findings suggest that the condensed repeated dosing paradigm produces a measurable behavioral withdrawal phenotype. This dosing schedule is an effective and efficient approach for high-throughput drug addiction research in adult zebrafish and may be useful for evaluating many pharmacological treatments.
Introduction:Understanding the neural mechanisms underlying general anesthesia remains a significant challenge in neuroscience and clinical practice. Traditional software-based simulations of large-scale brain networks are often constrained by high computational costs and fail to achieve real-time performance. Methods:In this paper, we propose a high-performance hardware implementation of large-scale neuromorphic system to investigate anesthetic-induced neural dynamics. The system successfully models a cortical network comprising 10,000 spiking neurons (8,000 excitatory and 2,000 inhibitory) utilizing the biologically plausible Izhikevich neuron model. Deployed on a field-programmable gate array (FPGA), the proposed architecture exploits high parallelism to achieve real-time simulation speeds. By adjusting synaptic weights and network parameters to mimic the pharmacological eects of anesthetic agents, our system can continuously monitor and evaluate state transitions in neural synchronization and firing patterns. Results:The results demonstrate that the hardware-accelerated neuromorphic approach provides an efficient, scalable, and real-time platform for investigating large-scale neural dynamics. Discussion:Pending future validation against empirical clinical EEG data, this foundational framework paves the way for advanced brain-machine interfaces and closed-loop anesthetic delivery systems.
IntroductionDistributed electroencephalography (EEG) brain-computer interface (BCI) systems increasingly transmit neural data and control messages between a head-worn device, a nearby hub, and cloud-assisted services. These links require integrity, authenticity, replay protection, and low latency, while migration to post-quantum cryptography can increase session-establishment cost.MethodsWe present PQ-NeuroLink, a latency-aware post-quantum-ready communication framework that separates authenticated session establishment from the symmetric streaming fast path. The design supports classical X25519, post-quantum ML-KEM-768, and hybrid ML-KEM-768 plus X25519 key establishment, with pinned ML-DSA public keys for endpoint identity binding. The prototype was evaluated using EEG-derived traffic from public datasets over BLE-like and Wi-Fi-like link profiles, 1-hop and 2-hop topologies, symmetric key-update and public-key refresh events, active tampering scenarios, and MCU-informed resource and processing-energy projections.ResultsIdentity pinning and transcript binding prevented successful modeled session-splicing attempts. Post-quantum and hybrid modes primarily increased handshake bytes rather than steady-state streaming latency. In the most constrained BLE 1-hop summary condition, the hybrid M3 mode increased p95 latency by 0.45 ms relative to the unsecured M0 baseline while maintaining 99.0% packet delivery.DiscussionPost-quantum-ready authenticated session establishment can be integrated into distributed EEG communication prototypes when public-key operations are kept off the per-frame path. PQ-NeuroLink provides a reproducible communication-layer basis for secure next-generation BCI deployment studies requiring low-latency operation and long-horizon post-quantum protection.
Consciousness remains incompletely explained at the anatomical, biophysical, and functional levels. Although existing theories characterize key functional correlates of conscious experience-including global broadcasting, information integration, attentional selection, working-memory-based awareness, and electromagnetic field dynamics-none has yet identified a specific cellular mechanism embedded within a defined long-range cortical pathway that could support the transmission of integrated sensory, interoceptive, emotional, and cognitive information toward anterior access and control systems. Here, the "Raslan Circuit" is defined as a candidate solution centered on the fronto-insular cortex (FI), the anterior cingulate cortex (ACC), and their von Economo neurons (VENs). Anatomically, VENs form a selectively localized population in FI and ACC, two regions already implicated in salience processing, interoception, emotional evaluation, and conscious awareness. Biophysically, within the Raslan Circuit hypothesis, VENs are proposed to act not merely as histological markers of higher cognition but as elongated, polarity-organizing neuronal elements with biological dipole antenna properties, supporting field-sensitive coupling and potentially resonance-based communication between FI and ACC. Functionally, FI is proposed to act as a deep multimodal collecting and organizing station, while ACC serves as a receiving and redistributive hub that links the transmitted signal to working memory, awareness, emotional valuation, and action selection. Together, this FI-ACC-VEN axis is advanced as a previously unrecognized communication infrastructure that could complement-rather than replace-Global Workspace Theory, Integrated Information Theory, embedded-processes and awareness-buffer models of working memory, salience-network accounts, and electromagnetic field theories of consciousness. The dimensional properties of VENs suggest a theoretically motivated, though speculative, prediction of resonance in the terahertz range, providing a falsifiable spectral hypothesis. More generally, the Raslan Circuit is grounded in four interlocking components: an anatomical foundation in VEN-rich FI and ACC, a biophysical rationale based on field-sensitive coupling, an explicit integration with existing functional theories of consciousness, and a set of testable predictions spanning connectivity, cellular and field measurements, clinical syndromes, and computational modeling.
