The research, led by Matthew Leedom and Arun Singh of the University of South Dakota together with colleagues at Oregon Health & Science University and other institutions, analyzed resting-state electroencephalography recordings from 237 participants across three study sites. The cohort included 88 healthy controls and 149 people with Parkinson’s disease, all assessed in their clinically defined ON-medication state while taking their usual dopaminergic medication. Among the patients, 73 experienced freezing of gait and 76 did not, allowing the team to ask a deceptively simple question: do the brains of people with Parkinson’s, and specifically those with freezing, generate neural rhythms differently?

To answer it, the researchers abandoned the traditional approach of measuring average spectral power. Conventional EEG analysis averages oscillatory activity over time, which can obscure the fact that brain rhythms do not behave like continuous signals. Beta activity, the frequency range most closely tied to Parkinson’s motor symptoms, actually arrives in short, intermittent packets known as bursts. By detecting these bursts directly, the team could quantify how often they occurred, how long they lasted, how strong they were, and how much of the recording time the brain spent in a burst state, metrics that capture the temporal architecture of neural synchrony rather than its blunt average.

The technical execution was carefully harmonized. Because the three sites used different EEG systems with different sampling rates, the analysis was restricted to a common set of 11 electrodes spanning frontal, central, parietal, and occipital regions. The primary focus fell on the midline fronto-central Cz electrode, a location relevant to lower limb control and gait. Signals were filtered into four frequency bands, theta from 4 to 8 hertz, alpha from 8 to 13 hertz, low beta from 13 to 20 hertz, and high beta from 20 to 30 hertz, and a burst was defined as any moment when the amplitude envelope of the filtered signal exceeded the 75th percentile threshold for that participant, channel, and band. Rigorous artifact removal, independent component analysis, and false discovery rate correction for multiple comparisons guarded against spurious findings.

The headline result was strikingly frequency-specific. People with Parkinson’s disease showed significantly altered low-beta burst dynamics at the mid-frontal region: their low-beta bursts were more frequent, but shorter in duration, compared with healthy controls. Both effects survived statistical correction, with corrected p-values of 0.004 for burst rate and duration. Crucially, burst amplitude and the total proportion of time spent in a burst did not differ between groups, indicating that the disease changes the temporal organization of beta activity, its rhythm of firing and resting, rather than simply cranking up oscillatory power. Exploratory topographic maps showed that these low-beta abnormalities extended beyond the mid-frontal electrode across several central and posterior channels, consistent with the idea that beta bursts are network-level events involving distributed cortical regions rather than isolated local oscillations.

That pattern contrasts intriguingly with earlier invasive findings. Recordings from the subthalamic nucleus, a deep brain target for stimulation therapy, have typically linked prolonged beta bursts to greater motor impairment, particularly when patients are off medication. The current cortical findings, gathered at rest while patients were medicated, instead suggest a fragmentation of beta activity, more bursts that terminate quickly, possibly reflecting dopaminergic modulation, residual disease-related dysfunction, or compensatory cortical reorganization. The authors are careful to note that without simultaneous cortical-subthalamic recordings or direct ON-OFF medication comparisons, the precise mechanism remains an open question.

When the team turned to freezing of gait, the picture changed. In three-group comparisons across healthy controls, patients without freezing, and patients with freezing, low-beta burst rate and duration differed across groups, but when the analysis was restricted to Parkinson’s patients alone and adjusted for disease duration and motor severity on the MDS-UPDRS scale, no significant differences emerged between those with and without freezing. In other words, the low-beta burst abnormalities appear to mark Parkinson’s disease and general motor-network dysfunction rather than freezing specifically. Some apparent freezing-related differences in the unadjusted data likely reflected the fact that patients with freezing tend to have longer disease duration and more severe motor symptoms.

Instead, the strongest signal tied to freezing came from an entirely different frequency band. Theta burst amplitude at the mid-frontal electrode correlated positively with freezing severity, measured with site-standardized questionnaire scores. Both the median theta burst amplitude and the 90th percentile amplitude, capturing the strongest theta events, showed significant correlations with severity, with Spearman’s rho of 0.22 and corrected p-values of 0.032 and 0.028 respectively. No beta-band metric survived correction in these severity analyses. This dissociation is physiologically compelling: theta activity in mid-frontal cortex has long been linked to cognitive control and conflict monitoring, and freezing episodes are most likely to occur in situations demanding heightened executive control, such as turning, navigating doorways, or dual-tasking. Elevated theta burst amplitude could reflect greater recruitment of cognitive control networks as a compensatory response to failing automatic motor control, or alternatively a maladaptive state of network instability and excessive conflict monitoring. Because the data were cross-sectional and collected at rest, the study cannot definitively distinguish between these interpretations.

The findings carry practical implications. Burst-based EEG metrics may serve as complementary biomarkers that capture aspects of Parkinson’s pathophysiology invisible to conventional spectral analysis. A low-beta burst timing signature could help characterize motor-network dysfunction, while theta burst amplitude might offer a continuous, quantitative index of the cognitive-motor burden underlying freezing severity, potentially useful for tracking disease progression or evaluating therapies. Notably, the continuous severity measure proved more sensitive than the categorical freezing-versus-non-freezing classification, hinting that neural dysfunction accumulates along a spectrum rather than switching on at a diagnostic threshold.

The study also has honest limitations. Harmonizing to 11 channels limited spatial resolution and ruled out source localization, resting-state recordings may miss the dynamic processes that unfold during actual walking and freezing episodes, and the timing of patients’ last medication dose was not uniformly standardized across sites, leaving open whether medication itself shaped the burst patterns. FOG severity was measured with different questionnaires at different sites, requiring within-site normalization, and the operational definition of bursts via an amplitude threshold, while consistent with prior work, should not be taken to represent discrete biological events in every instance. Still, the scale of the cohort, the multi-site harmonization, and the clean frequency-specific dissociation make this one of the most systematic examinations of cortical burst dynamics in Parkinson’s disease to date. The next step, the authors suggest, is to combine standardized medication manipulations, higher-density recordings, and tasks that provoke freezing in the laboratory, bringing science closer to the moment when the brain’s rhythm of rhythm itself explains why feet freeze.

Subject of Research: Frequency-specific EEG burst dynamics in Parkinson's disease and freezing of gait

Article Title: Frequency-Specific EEG burst dynamics in Parkinson’s Disease and freezing of gait

Article References: Frequency-Specific EEG burst dynamics in Parkinson’s Disease and freezing of gait. (n.d.). https://doi.org/10.1007/s00415-026-14149-6

Image Credits: AI Generated

DOI: 10.1007/s00415-026-14149-6

Keywords: Parkinson's disease, freezing of gait, EEG, beta bursts, theta oscillations, neural oscillations, basal ganglia, motor networks, cognitive control, biomarkers, neurophysiology, Journal of Neurology

The work synthesizes decades of behavioral experiments, neurobiological findings, and clinical observations into a single integrated framework. Its central claim is that timing deficits in schizophrenia are not scattered, unrelated impairments. Instead, the authors contend, they reflect systematic alterations in the neural systems that build and use internal clocks, and these alterations ripple outward into language processing, motor coordination, social functioning, and even the structure of hallucinations and delusions.

Behavioral studies have documented timing abnormalities in schizophrenia across an astonishing range of time scales. At the millisecond level, patients show difficulties in tasks such as simultaneity judgment, temporal order judgment, and rapid speech perception—abilities that healthy brains perform effortlessly and continuously. When researchers ask participants to estimate durations of a few seconds, a range known as interval timing, patients tend to both overproduce and underestimate intervals with markedly greater variability than controls. Crucially, the deficit pattern is not simply a matter of slowed responses or poor attention; the characteristic signatures of timing distortion appear even when overall performance accuracy is taken into account.

One of the most consistent findings across studies is increased variability. People with schizophrenia do not merely misjudge durations in a fixed direction; their estimates fluctuate far more from trial to trial. Researchers interpret this as evidence that the internal clock itself is noisy—that the neural pacemaker or accumulator processes presumed to underlie duration judgments are less stable in the psychotic brain. Computational models of interval timing, including pacemaker-accumulator and striatal beat frequency models, have been used to formalize this idea, and fitting these models to patient data suggests alterations in clock speed and in the precision with which durations are held in working memory.

On the neurobiological side, the review draws together evidence from neuroimaging, electrophysiology, pharmacology, and animal work. A recurring theme is the central role of the basal ganglia, and particularly the striatum, which many theories identify as the hub of the internal clock. Dopamine, the neurotransmitter most closely associated with schizophrenia since the discovery of antipsychotic drugs, modulates striatal timing functions; the speed of the internal pacemaker is thought to scale with dopaminergic activity. This convergence is striking because dopamine dysregulation remains one of the most robust biological findings in the illness, offering a mechanistic bridge between a well-established neurochemistry and a measurable perceptual deficit.

But the framework is not purely dopaminergic. Timing in the range relevant to perception and action depends on distributed networks that include the cerebellum, which refines sub-second timing essential for coordinated movement and smooth speech; the prefrontal and parietal cortices, which sustain attention to duration and maintain temporal information in memory; and the supplementary motor area, which links timing to prediction and action preparation. Neuroimaging studies in schizophrenia have reported altered activation and connectivity across precisely these regions during timing tasks, suggesting that the temporal disturbances observed behaviorally arise from dysfunction in a large-scale timing network rather than a single faulty structure.

Electrophysiological research adds another layer. Oscillatory brain activity in the theta and gamma bands has been implicated in segmenting the continuous stream of experience into discrete temporal chunks. In schizophrenia, abnormalities in neural oscillations—particularly reduced gamma-band power and disrupted phase synchronization—are among the best-re replicated findings in the field. The review argues that these oscillatory disturbances provide a plausible neural substrate for the perceptual fragmentation often described by patients, in which sounds, images, and events lose their natural temporal binding and arrive as disconnected fragments.

The clinical implications of this perspective are considerable. Timing abilities correlate with measures of everyday functioning in schizophrenia, including language comprehension, social communication, and motor skills. Speech perception, for example, depends on resolving acoustic differences of only a few tens of milliseconds; when this resolution is degraded, patients may struggle to follow fast conversations, misinterpret prosody, and withdraw from social interaction. Similarly, the temporal coordination of gestures, eye contact, and turn-taking that structures human dialogue relies on implicit timing capacities that appear to be compromised in the disorder. Disturbed timing may therefore contribute to the social-cognitive deficits that strongly predict real-world disability, even when positive symptoms are well controlled by medication.

The framework also extends to the phenomenology of psychosis itself. Some theorists have proposed that hallucinations and delusions can be understood, in part, as failures of temporal prediction—the brain’s normally seamless anticipation of the next moment in a sensory stream breaks down, and self-generated inner speech may be misattributed to external sources when the predictive timing that usually marks it as self-produced falters. Patients’ own accounts frequently describe a world in which events feel abrupt, unsynchronized, or frozen, and the review treats these first-person reports as data consistent with the laboratory findings rather than as epiphenomena.

Methodologically, the authors emphasize the value of integration. Behavioral paradigms that isolate specific timing processes, combined with computational modeling, pharmacological challenge studies, and multimodal imaging, can begin to disentangle which components of the timing system—clock speed, memory for duration, decision thresholds, attention to time—are affected in individual patients. This matters because timing measures are cheap, rapid, and reliable compared with many other neurocognitive assessments, raising the possibility that standardized timing batteries could eventually serve as translational biomarkers, linking animal models of dopamine dysfunction to human symptoms and to the effects of novel interventions.

The review is candid about limitations. Much of the existing literature involves small samples, medication effects are difficult to fully control, and timing tasks can be sensitive to motivation and generalized cognitive impairment. Heterogeneity across patients is substantial, and the field lacks longitudinal studies tracking whether timing deficits precede illness onset, track symptom fluctuation, or respond to treatment. The authors call for large-scale, multi-site studies that combine timing assessments with genetics, neurochemistry, and naturalistic measures of daily functioning to test whether disturbed time processing truly qualifies as a translational marker of the illness.

Even so, the synthesis marks a shift in perspective. What was once treated as an isolated experimental phenomenon—patients pressing buttons slightly off-beat—now appears as a window onto the architecture of psychosis itself. If the brain’s timing systems help bind perception, action, and self-experience into a coherent flow, then their disruption may sit closer to the heart of schizophrenia than anyone assumed. Understanding how the psychotic brain loses its grip on time, the authors suggest, may ultimately illuminate not only the disorder but the fundamental mechanisms by which any human brain constructs the seamless present we all take for granted.

Subject of Research: Time processing disturbances and their behavioral, neurobiological, and clinical significance in schizophrenia

Article Title: Time processing in schizophrenia: integrating behavioral, neurobiological, and clinical data

Article References: Ashoori, A., Buch, A. M., Eagleman, D. M., & Jarskog, L. F. (2026). Time processing in schizophrenia: integrating behavioral, neurobiological, and clinical data. Translational Psychiatry. https://doi.org/10.1038/s41398-026-04322-w

Image Credits: AI Generated

DOI: 10.1038/s41398-026-04322-w

Keywords: schizophrenia, time perception, interval timing, basal ganglia, dopamine, translational psychiatry, neural oscillations, cerebellum, cognitive neuroscience, psychosis, internal clock, temporal processing

The subthalamic nucleus, a small lens-shaped structure deep in the brain, sits at a critical junction in the basal ganglia circuitry that governs movement. In Parkinson’s disease, as dopamine-producing neurons in the substantia nigra degenerate, this circuitry falls into disarray. One of the most robust electrophysiological signatures of the disease is an exaggeration of beta-band oscillations, rhythmic fluctuations in the roughly 13 to 30 hertz range, in the subthalamic nucleus. These oscillations have been correlated with the cardinal motor symptoms of Parkinson’s, including bradykinesia, rigidity, and tremor, and their suppression through deep brain stimulation is associated with therapeutic benefit. This has made beta activity a cornerstone biomarker, both for understanding the disease and for engineering next-generation adaptive stimulation devices that deliver therapy only when the pathological signal is detected.

Yet the meaning of the local field potential remains one of the enduring puzzles of systems neuroscience. The LFP is thought to arise primarily from summed synaptic currents flowing across populations of neurons, filtered by the passive electrical properties of the surrounding tissue. Spikes, by contrast, are the discrete action potentials emitted by individual cells, and they contribute comparatively little to the field potential. When researchers observe beta oscillations in the LFP, they infer that the synaptic inputs to subthalamic neurons are oscillating, and they often further assume that the neurons’ output spikes must therefore be modulated in phase with that rhythm. The new findings complicate that second inference. Burst discharges from subthalamic neurons, the study reports, can be found both in phase and in antiphase with the simultaneously recorded beta LFP, and neither relationship dominates in a stable, predictable way.

This inconsistency matters because the phase of a spike relative to an oscillation is not an incidental detail. In the theoretical framework of neural coding, the timing of action potentials relative to population rhythms carries information and shapes downstream communication. Two neurons that receive the same oscillating input but burst on opposite phases of it are, in a functional sense, responding oppositely: one fires when the population signal peaks, the other when it troughs. If the spiking output of the subthalamic nucleus is split between in-phase and antiphase bursting, then a single LFP beta measurement cannot reliably indicate whether the neurons it governs are firing together or in opposition. The aggregate signal may look identical in both situations while the underlying cellular behavior differs fundamentally.

The implications ripple outward into several active areas of research and clinical development. Adaptive deep brain stimulation, one of the most promising advances in the field, uses real-time measurement of beta-band LFP to trigger or modulate stimulation. Devices currently in clinical trials, and early sensing-capable implants already in patients, treat elevated beta power as a proxy for the pathological state of the circuit. If beta power does not map consistently onto the bursting behavior of subthalamic neurons, then the biomarker may sometimes capture a circuit state that differs from the cellular dynamics the stimulation is intended to disrupt. This does not invalidate the approach, since beta suppression demonstrably correlates with symptom relief, but it does suggest that the chain of inference from LFP measurement to neuronal mechanism is weaker than often assumed.

The findings also speak to long-standing debates about the origins of pathological beta oscillations in Parkinson’s disease. Competing models assign different weights to the subthalamic nucleus itself, to its reciprocal connections with the external segment of the globus pallidus, and to cortical input delivered through the hyperdirect pathway. If subthalamic neurons burst in antiphase with the local field oscillation in a substantial fraction of cases, then the relationship between synaptic drive and spiking output in the nucleus is more heterogeneous than many models allow. Inhibitory input from the globus pallidus, which arrives as rhythmic bursts in parkinsonian conditions, could plausibly produce bursts of spikes in subthalamic neurons that occur during phases of suppressed synaptic depolarization in the surrounding population, contributing a sign-inverted component to the spike-LFP relationship. The new results are consistent with such heterogeneity in the sources and signs of rhythmic drive.

Methodologically, the study underscores the importance of examining spike-field relationships at the level of individual units rather than relying on population averages. When spikes from many neurons are pooled, in-phase and antiphase bursting can partially cancel, yielding a weak or ambiguous phase locking statistic that might be dismissed as noise. The more informative observation is that both relationships coexist, often within the same recording session, which means the averaging itself obscures the underlying structure. This echoes a broader lesson in electrophysiology: aggregate signals such as the LFP, electrocorticogram, and scalp EEG are powerful and clinically practical, but their interpretation requires careful attention to the geometry of the sources and the diversity of the cellular responses they summarize.

For patients and clinicians, the immediate practical consequences are limited but worth stating precisely. The therapeutic effectiveness of deep brain stimulation does not depend on the spike-field relationship being in phase; high-frequency stimulation suppresses symptoms regardless, presumably by driving the circuit into a more regular, information-rich regime that disrupts pathological patterning. The concern is prospective: as the field moves toward closed-loop therapies that decode brain state from field potentials, and toward brain-computer interfaces that treat oscillatory phase as a control signal, the assumption that phase reflects cellular firing must be tested rather than assumed. The new results provide a concrete, clinically relevant example where that assumption fails, at least intermittently, in a structure that is the single most common target of functional neurosurgery.

The research also raises questions that future work will need to address. Whether the inconsistent phase relationships reflect differences among neuron types within the subthalamic nucleus, shifts across behavioral states such as rest and movement, fluctuations in the balance of excitatory and inhibitory drive over time, or artifacts of how recording contacts sample spatially extended oscillatory sources remains to be determined. Longitudinal recordings from implanted patients, combined with computational models of the basal ganglia network, offer a path toward resolving which cellular configurations generate which field signatures. Such work could ultimately refine the biomarkers used in adaptive stimulation, allowing devices to distinguish circuit states that currently look identical in the LFP.

In the broader arc of neuroscience, the study is a reminder that the brain’s rhythms are not monolithic expressions of collective firing but composites whose relationship to cellular activity is contingent and, in the parkinsonian subthalamic nucleus, demonstrably inconsistent. The beta oscillation will remain a valuable clinical signal, and the correlation between its power and Parkinsonian symptoms is not in dispute. What the new findings erode is the simpler narrative in which the rhythm and the spikes move as one. In the subthalamic nucleus, neurons can march with the beta wave or against it, and the field potential alone cannot tell an observer which. For a field betting increasingly on oscillations as the language of pathological brain circuits, that ambiguity is a finding worth taking seriously.

Subject of Research: The relationship between subthalamic local field potential beta oscillations and neuronal burst firing in Parkinson's disease.

Article Title: Inconsistent subthalamic local field potential beta activity amid in- and antiphasic neuronal bursts

Article References: Inconsistent subthalamic local field potential beta activity amid in- and antiphasic neuronal bursts. (n.d.). https://doi.org/10.1038/s41531-026-01531-4

Image Credits: AI Generated

DOI: 10.1038/s41531-026-01531-4

Keywords: Parkinson's disease, subthalamic nucleus, local field potentials, beta oscillations, neuronal bursting, deep brain stimulation, basal ganglia, electrophysiology, neural coding, phase-amplitude coupling, brain-computer interfaces, movement disorders

The team turned to a well-established animal model in which mice are treated with β,β′-iminodipropionitrile, commonly abbreviated IDPN. This compound, when administered systemically, reliably produces stereotyped, repetitive movements in rodents that closely mirror the phenomenology of human tics. Researchers have used the IDPN model for decades to probe the basal ganglia circuits and neurotransmitter systems implicated in movement disorders, but the contribution of histaminergic signaling and neuroinflammation to the phenotype had not been fully characterized. The new work set out to fill that gap by measuring histamine dynamics, receptor expression, and microglial activation in the brains of IDPN-treated animals.

The first key finding concerned the hypothalamus, the brain region that contains the majority of the brain’s histamine-producing neurons. When the researchers quantified histamine levels and H1 receptor expression in this region, they found that both were significantly reduced in IDPN-treated mice compared with controls. This depletion of the central histaminergic tone is notable because histamine released from the tuberomammillary nucleus of the hypothalamus projects widely across the brain, influencing arousal, motor control, and immune signaling. A deficit in this system, the authors suggest, could plausibly disturb the circuit balance that governs the initiation and suppression of movements, creating conditions favorable to the emergence of tic-like stereotypies.

To test whether the loss of H1 receptor signaling is not merely a correlate but a potential driver of the behavior, the investigators administered diphenhydramine, a classic first-generation antihistamine that readily crosses the blood-brain barrier and blocks the H1 receptor. When wild-type mice, animals with no prior IDPN exposure, received intraperitoneal injections of diphenhydramine, they began to display tic-like stereotyped behaviors of their own. This pharmacological mimicry is a striking result: simply silencing H1 receptor signaling in otherwise healthy brains was sufficient to elicit a behavioral phenotype resembling that produced by IDPN. The observation aligns with clinical reports that have associated exposure to H1 receptor antagonists with increased risk and severity of tic disorders in children, lending translational weight to the animal data.

The second half of the study shifted focus to the striatum, a key component of the basal ganglia motor circuitry and a region long implicated in tic pathophysiology. In the IDPN-treated mice, the researchers observed increased immunoreactivity for Iba-1, a calcium-binding protein expressed specifically in microglia and macrophages that serves as a standard marker of microglial activation. Elevated Iba-1 staining indicates that the resident immune cells of the striatum had shifted into a reactive state, a phenomenon often associated with neuroinflammatory processes. Because microglia are the central phagocytic and immune-surveying cells of the central nervous system, their reactivity can influence synaptic pruning, neuronal excitability, and circuit function, all of which are plausible mechanistic links to abnormal movement patterns.

Having established that microglial reactivity accompanies the tic-like phenotype, the team then asked whether boosting histamine signaling in the striatum could reverse it. They performed intrastriatal injections of histamine directly into the brains of IDPN-treated mice. The result was twofold: the animals showed a reduction in their stereotyped behaviors, and the heightened Iba-1 immunoreactivity in the striatum was attenuated. In other words, replenishing histamine locally appeared to calm both the behavior and the immune activation simultaneously. This parallel effect strengthens the hypothesis that the behavioral and neuroimmune changes are mechanistically connected rather than independent byproducts of the IDPN treatment.

Crucially, the protective effect of histamine was not absolute. When the mice were pretreated with diphenhydramine before receiving the intrastriatal histamine, both the behavioral improvement and the reduction in microglial reactivity were blunted. This antagonist-attenuation experiment provides the strongest causal inference available within the study’s design: the benefits of histamine appear to depend on intact H1 receptor signaling, since blocking the receptor abolished the effect. Taken together, the data sketch a coherent pathway in which histamine acts through H1 receptors to restrain microglial reactivity in the striatum, and disruption of this signaling, whether by IDPN-induced depletion or by pharmacological antagonism, promotes tic-like stereotypies.

The authors are careful to frame their conclusions with appropriate scientific caution. Because the study relied on a pharmacological antagonist approach rather than genetic manipulation of the H1 receptor, and because it did not include microglia-specific interventions such as conditional knockout or depletion strategies, the findings should be interpreted as hypothesis-generating rather than definitive proof of mechanism. Diphenhydramine has pharmacological actions beyond H1 receptor blockade, including anticholinergic effects, and systemic administration cannot exclude contributions from peripheral immune signaling. Nonetheless, the convergence of multiple lines of evidence, reduced hypothalamic histamine and H1R in the model, induction of tic-like behavior by antagonist in wild-type animals, and rescue of both behavior and microglial activation by striatal histamine that is reversed by antagonist pretreatment, forms a compelling pattern.

The clinical implications are intriguing but require careful handling. Antihistamines are among the most widely used medications in pediatric populations, found in allergy remedies, cold preparations, and sleep aids. If H1 receptor blockade indeed exacerbates tic vulnerability, as both this animal work and prior clinical associations suggest, it may prompt clinicians to weigh tic risk more deliberately when prescribing brain-penetrant first-generation antihistamines to children, particularly those with a family history or early signs of tic disorders. Conversely, strategies that enhance central histaminergic tone or support H1 receptor signaling could represent a novel therapeutic direction, though any such approach would need to navigate histamine’s broad involvement in sleep, appetite, cognition, and other physiological functions.

Beyond tics, the study contributes to a rapidly growing appreciation of neuroimmunology in developmental neuropsychiatric conditions. Microglial reactivity has been implicated in conditions ranging from autism spectrum disorder to obsessive-compulsive disorder, conditions that share phenomenological and neurobiological overlap with tic disorders. The idea that a classical neurotransmitter system like histamine can serve as a modulatory bridge between neuronal circuits and glial immune responses opens a conceptual avenue that extends well beyond a single disease. The work was supported by the Joint Funds for the Innovation of Science and Technology of Fujian Province and the Fujian Provincial Natural Science Foundation of China, and all animal experiments were approved by the Experimental Animal Ethics Committee of Fujian Medical University. As the field moves forward, genetic models and microglia-specific tools will be essential to confirm whether the histamine-H1R-microglia axis can be safely and effectively targeted to help patients whose lives are disrupted by persistent tics.

Subject of Research: Histamine-H1 receptor regulation of microglial reactivity in an IDPN-induced mouse model of tic-like behaviors

Article Title: Histamine and H1R regulate microglia in an IDPN-Induced Mouse Model of Tic-like behaviors

Article References: Lin, D., Tang, Y., Li, Q., Lu, Y., Xie, J., & Liu, X. (2026). Histamine and H1R regulate microglia in an IDPN-Induced Mouse Model of Tic-like behaviors. BMC Neuroscience. https://doi.org/10.1186/s12868-026-01039-w

Image Credits: AI Generated

DOI: 10.1186/s12868-026-01039-w

Keywords: tic disorder, histamine, H1 receptor, microglia, IDPN, diphenhydramine, neuroinflammation, striatum, basal ganglia, hypothalamus, neuroimmunology, movement disorders