Brain States Research Articles

Dopaminergic modulation and dosage effects on brain state dynamics and working memory component processes in Parkinson’s disease

Parkinson’s disease (PD) is primarily diagnosed through its characteristic motor deficits, yet it also encompasses progressive cognitive impairments that profoundly affect quality of life. While dopaminergic medications are routinely prescribed to manage motor symptoms in PD, their influence extends to cognitive functions as well. Here we investigate how dopaminergic medication influences aberrant brain circuit dynamics associated with encoding, maintenance and retrieval working memory (WM) task-phases processes. PD participants, both on and off dopaminergic medication, and healthy controls, performed a Sternberg WM task during fMRI scanning. We employ a Bayesian state-space computational model to delineate brain state dynamics related to different task phases. Importantly, a within-subject design allows us to examine individual differences in the effects of dopaminergic medication on brain circuit dynamics and task performance. We find that dopaminergic medication alters connectivity within prefrontal-basal ganglia-thalamic circuits, with changes correlating with enhanced task performance. Dopaminergic medication also restores engagement of task-phase-specific brain states, enhancing task performance. Critically, we identify an “inverted-U-shaped” relationship between medication dosage, brain state dynamics, and task performance. Our study provides valuable insights into the dynamic neural mechanisms underlying individual differences in dopamine treatment response in PD, paving the way for more personalized therapeutic strategies.

Transient destabilization of whole brain dynamics induced by N,N-Dimethyltryptamine (DMT)

The transition towards the brain state induced by psychedelic drugs is frequently neglected in favor of a static description of their acute effects. We use a time-dependent whole-brain model to reproduce large-scale brain dynamics measured with fMRI from 15 volunteers under 20 mg intravenous N,N-Dimethyltryptamine (DMT), a short-acting psychedelic. To capture its transient effects, we parametrize the proximity to a global bifurcation using a pharmacokinetic equation. Simulated perturbations reveal a transient of heightened reactivity concentrated in fronto-parietal regions and visual cortices, correlated with serotonin 5HT2a receptor density, the primary target of psychedelics. These advances suggest a mechanism to explain key features of the psychedelic state and also predicts that the temporal evolution of these features aligns with pharmacokinetics. Our results contribute to understanding how psychedelics introduce a transient where minimal perturbations can achieve a maximal effect, shedding light on how short psychedelic episodes may extend an overarching influence over time.

Dynamic Functional Connectivity Markers in Anorexia Nervosa and Their Association With Clinical Symptoms: A Cross‐Sectional Study

ABSTRACTThe human brain possesses a unique ability to switch between patterns of functional connectivity, known as brain states, which are crucial for regulating biological, cognitive, and emotional processes. These states are linked to numerous neurological and neuropsychiatric conditions, however, their relationship to clinical symptoms of anorexia nervosa (AN) is not well understood. In this exploratory study, we aimed to identify whole‐brain dynamic functional alterations in AN and their association with AN symptoms. To this end, we recruited 19 women diagnosed with AN and 22 healthy controls (HCs) who underwent resting‐state functional magnetic resonance imaging. By implementing a sliding‐window approach, we found that AN patients had limited flexibility to transit between different brain configurations compared to HCs. Moreover, AN patients spent a significant amount of time in a functional configuration characterised by strong coupling between the ventral attentional network and the somatomotor network. Changes in these networks play a crucial role in body image disturbances, interoceptive awareness, and body image‐body schema interaction. Interestingly, the time spent in this specific brain state showed a negative relationship with body mass index, along with a positive correlation with eating disorder indices. Our study highlights the potential of dynamic functional connectivity as a prognostic and therapeutic means to spotlight maladaptive functional brain configurations in AN.

ThermoMaze behavioral paradigm for assessing immobility-related brain events in rodents.

Brain states fluctuate between exploratory and consummatory phases of behavior. These state changes affect both internal computation and the organism's responses to sensory inputs. Understanding neuronal mechanisms supporting exploratory and consummatory states and their switching requires experimental control of behavioral shifts and collecting sufficient amounts of brain data. To achieve this goal, we developed the ThermoMaze, which exploits the animal's natural warmth-seeking homeostatic behavior. By decreasing the floor temperature and selectively heating unmarked areas, we observed that mice avoided the aversive state by exploring the maze and finding the warm spot. In its design, the ThermoMaze is analogous to the widely used water maze but without the inconvenience of a wet environment and, therefore, allows the collection of physiological data in many trials. We combined the ThermoMaze with electrophysiology recording, and report that spiking activity of hippocampal CA1 neurons during sharp-wave ripple events encode the position of mice. Thus, place-specific firing is not confined to locomotion and associated theta oscillations but persist during waking immobility and sleep at the same location. The ThermoMaze will allow for detailed studies of brain correlates of immobility, preparatory-consummatory transitions, and open new options for studying behavior-mediated temperature homeostasis.

Restoring the Redox and Norepinephrine Homeostasis in Mouse Brains Promotes an Antidepressant Response.

Effective diagnosis and treatment of major depressive disorder remains a major challenge because diagnostic criteria overlap with other conditions and 50% of patients are resistant to conventional treatments. Emerging evidence has indicated that oxidative stress and reduced norepinephrine are key pathological features of depression. Herein, we constructed a smart organic small-molecule fluorescence-based therapeutic system (Cou-NE-H2O2) for the diagnosis and treatment of depression targeted at restoring redox homeostasis and efficiently upregulating norepinephrine in the brain. Utilizing Cou-NE-H2O2, we could evaluate the depressive phenotype via the fluorescence monitoring of the redox state in mouse brains. By reducing hydrogen peroxide and continuously increasing norepinephrine, Cou-NE-H2O2 elicited a synergistic antidepressant action. Furthermore, we identified that Cou-NE-H2O2 can promote the expression of genes such as Grin2a, Drd1, and Fxyd2 related to the cyclic adenosine monophosphate signaling pathway, upregulate glutathione and cysteine to alleviate oxidative stress, and boost neuronal activity by enhancing dopaminergic synapses, ultimately achieving an effective antidepressant response. Taken together, this work provides a new strategy for the evaluation of depression and appropriate treatments and identifies the mechanisms underlying antioxidant and norepinephrine disorders in the brain as potential targets for the development of novel diagnostics and treatments for depression.

Enhanced EEG Forecasting: A Probabilistic Deep Learning Approach.

Forecasting electroencephalography (EEG) signals, that is, estimating future values of the time series based on the past ones, is essential in many real-time EEG-based applications, such as brain-computer interfaces and closed-loop brain stimulation. As these applications are becoming more and more common, the importance of a good prediction model has increased. Previously, the autoregressive model (AR) has been employed for this task; however, its prediction accuracy tends to fade quickly as multiple steps are predicted. We aim to improve on this by applying probabilistic deep learning to make robust longer-range forecasts. For this, we applied the probabilistic deep neural network model WaveNet to forecast resting-state EEG in theta- (4-7.5 Hz) and alpha-frequency (8-13 Hz) bands and compared it to the AR model. WaveNet reliably predicted EEG signals in both theta and alpha frequencies 150 ms ahead, with mean absolute errors of 1.0 $\pm$ 1.1 $\mu$V (theta) and 0.9 $\pm$ 1.1 $\mu$V (alpha), and outperformed the AR model in estimating the signal amplitude and phase. Furthermore, we found that the probabilistic approach offers a way of forecasting even more accurately while effectively discarding uncertain predictions. We demonstrate for the first time that probabilistic deep learning can be used to forecast resting-state EEG time series. In the future, the developed model can enhance the real-time estimation of brain states in brain-computer interfaces and brain stimulation protocols. It may also be useful for answering neuroscientific questions and for diagnostic purposes.

Dynamic cycles between brain states during creative storytelling.

Dynamic cycles between brain states during creative storytelling.

Neural impact of anti-G suits on pilots: Analyzing microstates and functional connectivity.

Neural impact of anti-G suits on pilots: Analyzing microstates and functional connectivity.

Objective outcome prediction in depression through functional MRI brain network dynamics.

Objective outcome prediction in depression through functional MRI brain network dynamics.

Self-Organizing Dynamic Research Based on Phase Coherence Graph Autoencoders: Analysis of Brain Metastable States Across the Lifespan.

Self-Organizing Dynamic Research Based on Phase Coherence Graph Autoencoders: Analysis of Brain Metastable States Across the Lifespan.

Trajectories of intrinsic connectivity one year post pediatric mild traumatic brain injury: Neural injury superimposed on neurodevelopment.

Trajectories of intrinsic connectivity one year post pediatric mild traumatic brain injury: Neural injury superimposed on neurodevelopment.

Environmental context influences visual processing in thalamus.

Environmental context influences visual processing in thalamus.

“Oxyplastogen”: Investigating biological mechanisms and potential applications for hyperbaric Induced neuroplasticity, a narrative review

Neuroplasticity, also known as neural plasticity or brain plasticity, is the brain’s ability to reorganize, restructure, adapt and create new connections in response to stimuli from the environment. This plays a large role in the treatment, rehabilitation and management of brain pathologies, injuries and diseases as well as creating an optimized brain state for learning and skill acquisition. Hyperbaric oxygen therapy (HBOT) is a treatment where the patient is placed into a chamber that is pressurized to a pressure greater than 1 atmosphere of absolute pressure (ATA) whilst breathing air or pure oxygen. This leads to large amounts of oxygen dissolving in the plasma creating a substantial increase in cellular oxygen. This review searched the online databases such as MEDLINE, PubMed and the Cochrane library for studies reporting HBOT having a neuroplastic effect and the pathologies/injuries it was used for. Analysis of these studies suggest how HBOT can create a favorable environment for neuroplasticity to take place, the biological mechanisms on how this is achieved, the literature on the potential applications to brain/nervous system disorders and the literature around dosages and protocols. This review will inform future research looking at further understanding the neuroplasticity biological processes and optimizing the dose and protocol of HBOT to achieve optimum neuroplasticity for specific conditions as well as looking at therapeutic synergy with other modalities such as psychological therapies. To the authors knowledge this is the first review to exclusively look at HBOT and neuroplasticity which will help guide further research on the subject.

Antidepressant efficacy of administering repetitive transcranial magnetic stimulation (rTMS) with psychological and other non-pharmacological methods: a scoping review and meta-analysis.

To optimize the antidepressant efficacy of repetitive transcranial magnetic stimulation (rTMS), it is important to examine the impact of brain state during therapeutic rTMS. Evidence suggests that brain state can modulate the brain's response to stimulation, potentially diminishing antidepressant efficacy if left uncontrolled or enhancing it with inexpensive psychological or other non-pharmacological methods. Thus, we conducted a PRISMA-ScR-based scoping review to pool studies administering rTMS with psychological and other non-pharmacological methods. PubMed and Web of Science databases were searched from inception to 10 July 2024. Inclusion criteria: neuropsychiatric patients underwent rTMS; studies assessed depressive symptom severity; non-pharmacological tasks or interventions were administered during rTMS, or did not include a wash-out period. Of 8,442 studies, 20 combined rTMS with aerobic exercise, bright light therapy, cognitive training or reactivation, psychotherapy, sleep deprivation, or a psychophysical task. Meta-analyses using random effects models were conducted based on change scores on standardized scales. The effect size was large and therapeutic for uncontrolled pretest-posttest comparisons (17 studies, Hedges' g=-1.91, (standard error) SE=0.45, 95% (confidence interval) CI=-2.80 to -1.03, p<0.01); medium when studies compared active combinations with sham rTMS plus active non-pharmacological methods (8 studies, g=-0.55, SE=0.14, 95% CI=-0.82 to -0.28, p<0.01); and non-significant when active combinations were compared with active rTMS plus sham psychological methods (4 studies, p=0.96). Attempts to administer rTMS with non-pharmacological methods show promise but have not yet outperformed rTMS alone.

Post-mortem interval leads to loss of disease-specific signatures in brain tissue.

Human brain banks are essential for studying a wide variety of neurological and neurodegenerative diseases, yet the variability in post-mortem interval (PMI)-the time from death to tissue preservation-poses significant challenges due to rapid cellular decomposition, protein alterations, and RNA degradation. Furthermore, the post-mortem transcriptomic alterations occurring within distinct cell types are poorly understood. In this study, we analyzed the effect of a 3-hour post-mortem interval on single-nucleus RNA signatures in the brains of wild-type (WT) and PS19 mice, a common model of tauopathy. We observed that basic quality control metrics (such as the number of genes and reads per cell), total nuclei counts, and RNA integrity number (RINe) remained consistent across all samples, regardless of PMI or genotype. However, a 3-hour PMI diminished the number of genes differentially expressed between PS19 and WT mice, suggesting an impact of delayed processing on the detection of disease-specific transcriptomic signatures. When directly comparing 3-hour PMI versus freshly harvested 0-hour mouse brains, we identified genes upregulated in neurons and interneurons involved in DNA repair, immune response, and stress pathways. Furthermore, genes that were altered in non-neuronal cell types at 3-hours versus 0-hour PMI were associated with cell-cell adhesion processes. These findings highlight the effects of PMI on single-nucleus transcriptional changes that may dampen the true changes in cellular states in banked brain tissues.Significance Statement This study investigates how post-mortem interval (PMI)-the time between death and tissue preservation-affects gene expression in brain cell types using single-nucleus RNA sequencing. By comparing brain samples collected immediately and 3 hours post-mortem in mice, we found that PMI can obscure disease-related gene expression changes, especially in neurons. These findings underscore the importance of accounting for PMI in studies of neurodegenerative disease using human brain banks.

A hypothalamic circuit underlying the dynamic control of social homeostasis.

Social grouping increases survival in many species, including humans1,2. By contrast, social isolation generates an aversive state ('loneliness') that motivates social seeking and heightens social interaction upon reunion3-5. The observed rebound in social interaction triggered by isolation suggests a homeostatic process underlying the control of social need, similar to physiological drives such as hunger, thirst or sleep3,6. In this study, we assessed social responses in several mouse strains, among which FVB/NJ mice emerged as highly, and C57BL/6J mice as moderately, sensitive to social isolation. Using both strains, we uncovered two previously uncharacterized neuronal populations in the hypothalamic preoptic nucleus that are activated during either social isolation or social rebound and orchestrate the behaviour display of social need and social satiety, respectively. We identified direct connectivity between these two populations and with brain areas associated with social behaviour, emotional state, reward and physiological needs and showed that mice require touch to assess the presence of others and fulfil their social need. These data show a brain-wide neural system underlying social homeostasis and provide significant mechanistic insights into the nature and function of circuits controlling instinctive social need and for the understanding of healthy and diseased brain states associated with social context.

Brain-wide impacts of sedation on spontaneous activity and auditory processing in larval zebrafish.

Despite their widespread use, we have limited knowledge of the mechanisms by which sedatives mediate their effects on brain-wide networks. This is, in part, due to the technical challenge of observing activity across large populations of neurons in normal and sedated brains. In this study, we examined the effects of the sedative dexmedetomidine, and its antagonist atipamezole, on spontaneous brain dynamics and auditory processing in zebrafish larvae, a stage when sex differentiation has not yet occurred. Our brain-wide, cellular-resolution calcium imaging reveals the brain regions involved in these network-scale dynamics and the individual neurons that are affected within those regions. Further analysis reveals a variety of dynamic changes in the brain at baseline, including marked reductions in spontaneous activity, correlation, and variance. The reductions in activity and variance represent a "quieter" brain state during sedation, an effect inducing highly correlated evoked activity in the auditory system to stand out more than it does in un-sedated brains. We also observe a reduction in the persistence of auditory information across the brain during sedation, suggesting that the removal of spontaneous activity leaves the core auditory pathway free of impingement from other non-auditory information. Finally, we describe a less dynamic brain-wide network during sedation, with a higher energy barrier and a lower probability of brain state transitions during sedation. In total, our brain-wide, cellular-resolution analysis shows that sedation leads to quieter, more stable, and less dynamic brain, and that against this background, responses across the auditory processing pathway become sharper and more prominent.Significance Statement Animals' brain states constantly fluctuate in response to their environment and context, leading to changes in perception and behavioral choices. Alterations in perception, sensorimotor gating, and behavioral selection are hallmarks of numerous neuropsychiatric disorders, but the circuit- and network-level underpinnings of these alterations are poorly understood.Pharmacological sedation alters perception and responsiveness and provides a controlled and repeatable manipulation for studying brain states and their underlying circuitry. Here, we show that sedation of larval zebrafish with dexmedetomidine reduces brain-wide spontaneous activity and locomotion but leaves portions of brain-wide auditory processing and behavior intact. We describe and computationally model changes at the levels of individual neurons, local circuits, and brain-wide networks that lead to altered brain states and sensory processing during sedation.

Altered Visuomotor Network Dynamics Associated with Freezing of Gait in Parkinson's Disease.

Freezing of gait (FOG) is a common gait disorder that often accompanies Parkinson's disease (PD). The current understanding of brain functional organization in FOG was built on the assumption that the functional connectivity (FC) of networks is static, but FC changes dynamically over time. We aimed to characterize the dynamic functional connectivity (DFC) in patients with FOG based on high temporal-resolution functional MRI (fMRI). Eighty-seven PD patients, including 29 with FOG and 58 without FOG, and 32 healthy controls underwent resting-state fMRI. Spatial independent component analysis and a sliding-window approach were used to estimate DFC. Four patterns of structured FC 'states' were identified: a frequent and sparsely connected network (State I), a less frequent but highly synchronized network (State IV), and two states with opposite connecting directions between the visual network and the sensorimotor network (positively connected in State II, negatively connected in State III). Compared with the non-FOG group, patients with FOG spent significantly less time in State II and more time in State III. The longer dwell time in State III was correlated with more severe FOG symptoms. The fractional window of State III tended to correlate to visual-spatial and executive dysfunction in FOG. Moreover, fewer transitions between brain states and lower variability in local efficiency were observed in FOG, suggesting a relatively 'rigid' brain. This study highlights how visuomotor network dynamics are related to the presence and severity of FOG in PD patients, which provides new insights into understanding the pathophysiological mechanisms that underly FOG. © 2025 International Parkinson and Movement Disorder Society.

Lag synchronization in an unidirectional ring of memristive neurons

Abstract In recent years, the study of neuronal models has provided significant insights into brain dynamics and neurological disorders. Map-based neuronal models, such as the Rulkov map, have gained considerable popularity due to their computational efficiency and ability to replicate complex neuronal dynamics. We thus here study the collective dynamics of an unidirectional ring network composed of three memristive Rulkov maps, with particular emphasis on synchronization patterns and their dependence on coupling types. By employing electrical and memristive/field couplings, we analyze the emergence of complete synchronization, lag synchronization, and phase synchronization under varying coupling strengths. Our findings highlight how diffusive-based synaptic pathways modulate synchronization and collective behavior in the network. The presented results also offer new perspectives on the role of coupling functions in shaping neuronal synchronization, and they reveal their deeper implications for understanding pathological brain states and for designing neuromorphic systems.

Dynamic brain states underlying advanced concentrative absorption meditation: A 7-T fMRI-intensive case study

ABSTRACT Advanced meditation consists of states and stages of practice that unfold with mastery and time. Dynamic functional connectivity (DFC) analysis of fMRI could identify brain states underlying advanced meditation. We conducted an intensive DFC case study of a meditator who completed 27 runs of jhāna advanced absorptive concentration meditation (ACAM-J), concurrently with 7-T fMRI and phenomenological reporting. We identified three brain states that marked differences between ACAM-J and nonmeditative control conditions. These states were characterized as a DMN-anticorrelated brain state, a hyperconnected brain state, and a sparsely connected brain state. Our analyses indicate higher prevalence of the DMN-anticorrelated brain state during ACAM-J than control states, and the prevalence increased significantly with deeper ACAM-J states. The hyperconnected brain state was also more common during ACAM-J and was characterized by elevated thalamocortical connectivity and somatomotor network connectivity. The hyperconnected brain state significantly decreased over the course of ACAM-J, associating with self-reports of wider attention and diminished physical sensations. This brain state may be related to sensory awareness. Advanced meditators have developed well-honed abilities to move in and out of different altered states of consciousness, and this study provides initial evidence that functional neuroimaging can objectively track their dynamics.