bioRxiv Subject Collection: Neuroscience's Journal

Disruption of Cholinergic Retinal Waves Alters Visual Cortex Development and Function
Retinal waves represent an early form of patterned spontaneous neural activity in the visual system. These waves originate in the retina before eye-opening and propagate throughout the visual system, influencing the assembly and maturation of subcortical visual brain regions. However, because it is technically challenging to ablate retina-derived cortical waves without inducing compensatory activity, the role these waves play in the development of the visual cortex remains unclear. To address this question, we used targeted conditional genetics to disrupt cholinergic retinal waves and their propagation to select regions of primary visual cortex, which largely prevented compensatory patterned activity. We find that loss of cholinergic retinal waves without compensation impaired the molecular and synaptic maturation of excitatory neurons located in the input layers of visual cortex, as well as layer 1 interneurons. These perinatal molecular and synaptic deficits also relate to functional changes observed at later ages. We find that the loss of perinatal cholinergic retinal waves causes abnormal visual cortex retinotopy, mirroring changes in the retinotopic organization of gene expression, and additionally impairs the processing of visual information. We further show that retinal waves are necessary for higher order processing of sensory information by impacting the state-dependent activity of layer 1 interneurons, a neuronal type that shapes neocortical state-modulation, as well as for state-dependent gain modulation of visual responses of excitatory neurons. Together, these results demonstrate that a brief targeted perinatal disruption of patterned spontaneous activity alters early cortical gene expression as well as synaptic and physiological development, and compromises both fundamental and, notably, higher-order functions of visual cortex after eye-opening.

Strength of Activation and Temporal Dynamics of BioLuminescent-Optogenetics in Response to Systemic Injections of the Luciferin
BioLuminescent OptoGenetics (BL-OG) is a chemogenetic method that can evoke optogenetic reactions in the brain non-invasively. In BL-OG, an enzyme that catalyzes a light producing reaction (i.e., a luciferase) is tethered to an optogenetic element that is activated in response to bioluminescent light. Bioluminescence is generated by injecting a chemical substrate (luciferin, e.g., h-Coelenterazine; h-CTZ) that is catalyzed by the luciferase. By directly injecting the luciferin into the brain, we showed that bioluminescent light is proportional to spiking activity, and this relationship scales as a function of luciferin dosage. Here, we build on these previous observations by characterizing the temporal dynamics and dose response curves of BL-OG effects to intravenous (IV) injections of the luciferin. We imaged bioluminescence through a thinned skull of mice running on a wheel, while delivering h-CTZ via the tail vein with different dosage concentrations and injection rates. The data reveal a systematic relationship between strength of bioluminescence and h-CTZ dosage, with higher concentration generating stronger bioluminescence. We also found that bioluminescent activity occurs rapidly (< 60 seconds after IV injection) regardless of concentration dosage. However, as expected, the onset time of bioluminescence is delayed as the injection rate decreases. Notably, the strength and time decay of bioluminescence is invariant to the injection rate of h-CTZ. Taken together, these data show that BL-OG effects are highly consistent across injection parameters of h-CTZ, highlighting the reliability of BL-OG as a non-invasive neuromodulation method.

Creative tempo: Spatiotemporal dynamics of the default mode network in improvisational musicians
The intrinsic dynamics of human brain activity display a recurring pattern of anti-correlated activity between the default mode network (DMN), associated with internal processing and mentation, and task positive regions, associated with externally directed attention. In human functional magnetic resonance imaging (fMRI) data, this anti-correlated pattern is detectable on the infraslow timescale (<0.1 Hz) as a quasi-periodic pattern (QPP). While the DMN is implicated in creativity and musicality in traditional time-averaged functional connectivity studies, no one has yet explored how creative training may alter dynamic spatiotemporal patterns involving the DMN such as QPPs. In the present study, we compare the outputs of two QPP detection approaches, sliding window algorithm and complex principal components analysis (cPCA). We apply both methods to an existing dataset of musicians captured with resting state fMRI, grouped as either classical, improvisational, or minimally trained non-musicians. The original time-averaged functional connectivity (FC) analysis of this dataset used improvisation as a proxy for creative thinking and found that the DMN and visual networks (VIS) display higher connectivity in improvisational musicians. We expand upon the original study of this dataset and find that QPP analysis detects convergent results at the group level with both methods. In improvisational musicians, dynamic functional correlation in the group-averaged QPP was found to be increased between the DMN-VIS and DMN-FPN for both the QPP algorithm and complex principal components analysis (cPCA) methods. Additionally, we found an unexpected increase in FC in the group-averaged QPP between the dorsal attention network and amygdala in improvisational musicians; this result was not reported in the original seed-based study of this dataset. The current study represents a novel application of two dynamic FC detection methods with results that replicate and expand upon previous seed-based FC findings. The results show the robustness of both the QPP phenomenon and its detection methods. This study also demonstrates the value of dynamic FC methods in reproducing seed-based findings and their promise in detecting group-wise or individual differences that may be missed by traditional seed-based resting state fMRI studies.

Virus-like particle (VLP)-based vaccine targeting tau phosphorylated at Ser396/Ser404 (PHF1) site outperforms phosphorylated S199/S202 (AT8) site in reducing tau pathology and restoring cognitive deficits in the rTg4510 mouse model of tauopathy.
Tauopathies, including Alzheimers disease (AD) and Frontotemporal Dementia (FTD), are histopathologically defined by the aggregation of hyperphosphorylated pathological tau (pTau) as neurofibrillary tangles in the brain. Site-specific phosphorylation of tau occurs early in the disease process and correlates with progressive cognitive decline, thus serving as targetable pathological epitopes for immunotherapeutic development. Previously, we developed a vaccine (Q{beta}-pT181) displaying phosphorylated Thr181 tau peptides on the surface of a Q{beta} bacteriophage virus-like particle (VLP) that induced robust antibody responses, cleared pathological tau, and rescued memory deficits in a transgenic mouse model of tauopathy. Here, we report the characterization and comparison of two additional Q{beta} VLP-based vaccines targeting the dual phosphorylation sites Ser199/Ser202 (Q{beta}-AT8) and Ser396/Ser404 (Q{beta}-PHF1). Both Q{beta}-AT8 and Q{beta}-PHF1 vaccines elicited high-titer antibody responses against their pTau epitopes. However, only Q{beta}-PHF1 rescued cognitive deficits, reduced soluble and insoluble pathological tau, and reactive microgliosis in a 4-month rTg4510 model of FTD. Both sera from Q{beta}-AT8 and Q{beta}-PHF1 vaccinated mice were specifically reactive to tau pathology in human AD post-mortem brain sections. These studies further support the use of VLP-based immunotherapies to target pTau in AD and related tauopathies and provide potential insight into the clinical efficacy of various pTau epitopes in the development of immunotherapeutics.

Translational control of microglial inflammatory and neurodegenerative responses
In Alzheimer's Disease (AD), activation of the mechanistic target of rapamycin (mTOR) pathway is essential for microglia neuroprotective roles, but it is unclear which mTOR effectors promote these neuroprotective functions. The mTOR complex 1 (mTORC1) inactivates the translation suppressors eukaryotic translation Initiation Factor 4E (eIF4E)-Binding Proteins (4E-BP) to promote mRNA translation. We show that 4E-BP1 inactivation is impaired in microglia under AD-relevant conditions. Depleting 4E-BPs in microglia increases mitochondrial metabolism, suppresses the pro-inflammatory profile, and mitigates amyloid-induced apoptosis. Furthermore, in the cerebrospinal fluid of patients with amyloid pathology, there was a positive association between microglia activation and neurodegeneration, which increases along 4E-BP1 levels. Thus, we propose the engagement mTORC1-4E-BP1 axis as a neuroprotective mechanism and a therapeutic target or biomarker for microglia modulation in AD.

Structure-function coupling and decoupling during movie-watching and resting-state: Novel insights bridging EEG and structural imaging
The intricate structural and functional architecture of the brain enables a wide range of cognitive processes ranging from perception and action to higher-order abstract thinking. Despite important progress, the relationship between the brains structural and functional properties is not yet fully established. In particular, the way the brains anatomy shapes its electrophysiological dynamics remains elusive. The electroencephalography (EEG) activity recorded during naturalistic tasks is thought to exhibit patterns of coupling with the underlying brain structure that vary as a function of behavior. Yet these patterns have not yet been sufficiently quantified. We address this gap by jointly examining individual Diffusion-Weighted Imaging (DWI) scans and continuous EEG recorded during video-watching and resting state, using a Graph Signal Processing (GSP) framework. By decomposing the structural graph into Eigenmodes and expressing the EEG activity as an extension of anatomy, GSP provides a way to quantify the structure-function coupling. Our findings indicate that the EEG activity in the sensorimotor cortex is strongly coupled with brain structure, while the activity in higher-order systems is less constrained by anatomy, i.e., shows more flexibility. In addition, we found that watching videos was associated with stronger structure-function coupling in the sensorimotor cortex, as compared to resting-state data. Together, this un-precedented characterization of the link between structure and function using continuous EEG during naturalistic behavior underscores the role of anatomy in shaping ongoing cognitive processes. Taken together, by combining the temporal and spectral resolution of EEG and the methodological advantages of GSP, our work sheds new light onto the anatomo-functional organization of the brain.

Gossamer: Scaling Image Processing and Reconstruction to Whole Brains
Neuronal reconstruction--a process that transforms image volumes into 3D geometries and skeletons of cells--bottlenecks the study of brain function, connectomics and pathology. Unlike artistic domains with similar challenges (e.g., hair modeling), scientists need exact and complete segmentations to study subtle topological differences. Existing methods are disk-bound, dense-access, coupled, single-threaded, algorithmically unscalable and require manual cropping of small windows and proofreading of skeletons due to low topological accuracy. Designing a data-intensive parallel solution suited to a neurons' shape, topology and far-ranging connectivity is particularly challenging due to I/O and load-balance, yet by abstracting vision tasks such as segmentation and skeletonization into strategically ordered specializations of search, we progressively lower memory by 4 orders of magnitude. This enables 1 mouse brain to be fully processed in-memory on a single server, at 67X the scale with 870X less memory while having 78% higher automated yield than the highest performing alternative methods.

Selective modification of ascending spinal outputs in acute and neuropathic pain states
Pain hypersensitivity arises from the plasticity of peripheral and spinal somatosensory neurons, which modifies nociceptive input to the brain and alters pain perception. We utilized chronic calcium imaging of spinal dorsal horn neurons to determine how the representation of somatosensory stimuli in the anterolateral tract, the principal pathway transmitting nociceptive signals to the brain, changes between distinct pain states. In healthy conditions, we identify stable, narrowly tuned outputs selective for cooling or warming, and a neuronal ensemble activated by intense/noxious thermal and mechanical stimuli. Induction of an acute peripheral sensitization with capsaicin selectively and transiently retunes nociceptive output neurons to encode low-intensity stimuli. In contrast, peripheral nerve injury-induced neuropathic pain results in a persistent suppression of innocuous spinal outputs coupled with activation of a normally silent population of high-threshold neurons. These results demonstrate the differential modulation of specific spinal outputs to the brain during nociceptive and neuropathic pain states.

Unique cortical and subcortical activation patterns for different conspecific calls in marmosets
The common marmoset (Callithrix jacchus) is known for its highly vocal nature, displaying a diverse range of different calls. Functional imaging in marmosets has shown that the processing of conspecific calls activates a brain network that includes fronto-temporal cortical and subcortical areas. It is currently unknown whether different call types activate the same or different networks. Here we show unique activation patterns for different calls. Nine adult marmosets were exposed to four common vocalizations (phee, chatter, trill, and twitter), and their brain responses were recorded using event-related fMRI at 9.4T. We found robust activations in the auditory cortices, encompassing core, belt, and parabelt regions, and in subcortical areas like the inferior colliculus, medial geniculate nucleus, and amygdala in response to these conspecific calls. Different neural activation patterns were observed among the vocalizations, suggesting vocalization-specific neural processing. Phee and twitter calls, often used over long distances, activated similar neural circuits, whereas trill and chatter, associated with closer social interactions, demonstrated a closer resemblance in their activation patterns. Our findings also indicate the involvement of the cerebellum and medial prefrontal cortex (mPFC) in distinguishing particular vocalizations from others.

Significance StatementThis study investigates the neural processing of vocal communications in the common marmoset (Callithrix jacchus), a species with a diverse vocal repertoire. Utilizing event-related fMRI at 9.4T, we demonstrate that different marmoset calls (phee, chatter, trill, and twitter) elicit distinct activation patterns in the brain, challenging the notion of a uniform neural network for all vocalizations. Each call type distinctly engages various regions within the auditory cortices and subcortical areas, reflecting the complexity and context-specific nature of primate communication. These findings offer insights into the evolutionary mechanisms of primate vocal perception and provide a foundation for understanding the origins of human speech and language processing.

Modeling CSF circulation and the glymphatic system during infusion using subject specific intracranial pressures and brain geometries
Background: Infusion testing is an established method for assessing CSF resistance in patients with idiopathic normal pressure hydrocephalus (iNPH). To what extent the increased resistance is related to the glymphatic system is an open question. Here we introduce a computational model that includes the glymphatic system and enables us to determine the importance of 1) brain geometry, 2) intracranial pressure and 3) physiological parameters on the outcome of and response to an infusion test. Methods: We implemented a seven-compartment multiple network porous medium model with subject specific geometries from MR images. The model consists of the arterial, capillary and venous blood vessels, their corresponding perivascular spaces, and the extracellular space (ECS). Both subject specific brain geometries and subject specific infusion tests were used in the modeling of both healthy adults and iNPH patients. Furthermore, we performed a systematic study of the effect of variations in model parameters. Results: Both the iNPH group and the control group reached a similar steady state solution when subject specific geometries under identical boundary conditions was used in simulation. The difference in terms of average fluid pressure and velocity between the iNPH and control groups, was found to be less than 6 % during all stages of infusion in all compartments. With subject specific boundary conditions, the largest computed difference was a 75 % greater fluid speed in the arterial perivascular space (PVS) in the iNPH group compared to the control group. Changes to material parameters changed fluid speeds by several orders of magnitude in some scenarios. A considerable amount of the CSF pass through the glymphatic pathway in our models during infusion, i.e., 28% and 38% in the healthy and iNPH patients, respectively.

Beyond cortical geometry: brain dynamics shaped by long-range connections
A fundamental topological principle is that the container always shapes the content. In neuroscience, this translates into how the brain anatomy shapes brain dynamics. From neuroanatomy, the topology of the mammalian brain can be approximated by local connectivity, accurately described by an exponential distance rule (EDR). The compact, folded geometry of the cortex is shaped by this local connectivity and the geometric harmonic modes can reconstruct much of the functional dynamics. However, this ignores the fundamental role of the rare long-range cortical connections, crucial for improving information processing in the mammalian brain, but not captured by local cortical folding and geometry. Here we show the superiority of harmonics mode combining rare long-range with EDR (EDR+LR) in capturing functional dynamics (specifically long-range functional connectivity and task-evoked brain activity) compared to geometry and EDR representations. Importantly, the orchestration of dynamics is carried out by a more efficient manifold made up of a low number of fundamental EDR+LR modes. Our results show the importance of long-range connectivity for capturing the complexity of functional brain activity through a low-dimensional manifold shaped by fundamental EDR+LR modes.

Inhibitory Plasticity Enhances Sequence Storage Capacity and Retrieval Robustness
The generation of motor behaviors and the performance of complex cognitive tasks rely on sequential activity in specific brain structures. The mechanisms of learning and retrieval of these temporal patterns of activity are still poorly understood. Emerging evidence has highlighted the importance of inhibition to learning and memory. However, the specific functions of inhibitory plasticity in the learning and retrieval of sequential activity have been studied very little, apart from its role in maintaining excitation-inhibition (E-I) balance. Using simulations and dynamical mean-field theory of balanced E-I networks, we found that sequences can be stored and retrieved using plasticity in both E-to-I and I-to-E pathways, in the absence of recurrent excitatory plasticity. Networks with both E-to-I and I-to-E plasticity are shown to exhibit higher optimal capacity than models in which plasticity is restricted to recurrent excitation. We further show that inhibitory plasticity enhances robustness to external noise and initial cue perturbation. Thus, our work suggests new computational roles for inhibitory plasticity in improving capacity and robustness of sequence learning.

Hippocampal sharp wave ripples and coincident cortical ripples orchestrate human semantic networks
Episodic memory function is predicated upon the precise coordination between the hippocampus and widespread cortical regions. However, our understanding of the neural mechanisms involved in this process is incomplete. We utilize human intracranial recordings during a list learning task and demonstrate hippocampal sharp-wave ripple (SWR)-locked reactivation of specific semantic processing regions during free recall. This cortical activation consists of both broadband high frequency (non-oscillatory) and cortical ripple (oscillatory) activity. SWRs and cortical ripples in a major semantic hub, the anterior temporal lobe, co-occur and increase in rate prior to recall. Coincident hippocampal-cortical ripples are associated with a greater increase in cortical reactivation, show specificity in location based on recall content, and are preceded by cortical theta oscillations. These findings may represent a reactivation of hippocampus and cortical semantic regions orchestrated by an interplay between hippocampal SWRs, cortical ripples, and theta oscillations.

Chronic hyperactivation of midbrain dopamine neurons causes preferential dopamine neuron degeneration
Parkinson's disease (PD) is characterized by the death of substantia nigra (SNc) dopamine (DA) neurons, but the pathophysiological mechanisms that precede and drive their death remain unknown. The activity of DA neurons is likely altered in PD, but we understand little about if or how chronic changes in activity may contribute to degeneration. To address this question, we developed a chemogenetic (DREADD) mouse model to chronically increase DA neuron activity, and confirmed this increase using ex vivo electrophysiology. Chronic hyperactivation of DA neurons resulted in prolonged increases in locomotor activity during the light cycle and decreases during the dark cycle, consistent with chronic changes in DA release and circadian disturbances. We also observed early, preferential degeneration of SNc projections, recapitulating the PD hallmarks of selective vulnerability of SNc axons and the comparative resilience of ventral tegmental area axons. This was followed by eventual loss of midbrain DA neurons. Continuous DREADD activation resulted in a sustained increase in baseline calcium levels, supporting an important role for increased calcium in the neurodegeneration process. Finally, spatial transcriptomics from DREADD mice examining midbrain DA neurons and striatal targets, and cross-validation with human patient samples, provided insights into potential mechanisms of hyperactivity-induced toxicity and PD. Our results thus reveal the preferential vulnerability of SNc DA neurons to increased neural activity, and support a potential role for increased neural activity in driving degeneration in PD.

Tonotopic organization of auditory cortex in awake marmosets revealed by multi-modal wide-field optical imaging
Tonotopic organization of the auditory cortex has been extensively studied in many mammalian species using various methodologies and physiological preparations. Tonotopy mapping in primates, however, is more limited due to constraints such as cortical folding, use of anesthetized subjects, and mapping methodology. Here we applied a combination of through-skull and through-window intrinsic optical signal imaging, wide-field calcium imaging, and neural probe recording techniques in awake marmosets (Callithrix jacchus), a New World monkey with most of its auditory cortex located on a flat brain surface. Coarse tonotopic gradients, including a recently described rostral-temporal (RT) to parabelt gradient, were revealed by the through-skull imaging of intrinsic optical signals and were subsequently validated by single-unit recording. Furthermore, these tonotopic gradients were observed with more details through chronically implanted cranial windows with additional verifications on the experimental design. Moreover, the tonotopy mapped by the intrinsic-signal imaging methods was verified by wide-field calcium imaging in an AAV-GCaMP labeled subject. After these validations and with the further effort to expand the field of view more anteroventrally in both windowed and through-skull subjects, an additional putative tonotopic gradient was observed more rostrally to the area RT, which has not been previously described by the standard model of tonotopic organization of the primate auditory cortex. Together, these results provide the most comprehensive data of tonotopy mapping in awake primate species with unprecedented coverage and details in the rostral proportion and supports a caudorostrally arranged mesoscale organization of at least three repeats of functional gradients in the primate auditory cortex, similar to the ventral stream of primate visual cortex.

Resource: A Curated Database of Brain-Related Functional Gene Sets (Brain.GMT)
Transcriptional profiling has become a common tool for investigating the nervous system. During analysis, differential expression results are often compared to functional ontology databases, which contain curated gene sets representing well-studied pathways. This dependence can cause neuroscience studies to be interpreted in terms of functional pathways documented in better studied tissues (e.g., liver) and topics (e.g., cancer), and systematically emphasizes well-studied genes, leaving other findings in the obscurity of the brain "ignorome". To address this issue, we compiled a curated database of 918 gene sets related to nervous system function, tissue, and cell types ("Brain.GMT") that can be used within common analysis pipelines (GSEA, limma, edgeR) to interpret results from three species (rat, mouse, human). Brain.GMT includes brain-related gene sets curated from the Molecular Signatures Database (MSigDB) and extracted from public databases (GeneWeaver, Gemma, DropViz, BrainInABlender, HippoSeq) and published studies containing differential expression results. Although Brain.GMT is still undergoing development and currently only represents a fraction of available brain gene sets, "brain ignorome" genes are already better represented than in traditional Gene Ontology databases. Moreover, Brain.GMT substantially improves the quantity and quality of gene sets identified as enriched with differential expression in neuroscience studies, enhancing interpretation.

Cross-subject brain entropy mapping
We present a method to map the regional similarity between resting state fMRI activities of different individuals. The similarity was measured using cross-entropy. Group level patterns were displayed based on the Human Connectome Project Youth data. While we only showed the cross-subject brain entropy (BEN) mapping results in this manuscript, the same concept can be directly extended to map the cross-sessional BEN and the cross-regional cross-subject or subject-session BEN.

Task-specific topology of brain networks supporting working memory and inhibition
Network neuroscience investigates the brains connectome, revealing that cognitive functions are underpinned by dynamic neural networks. This study investigates how distinct cognitive abilities--working memory and inhibition--are supported by unique brain network configurations, which are constructed by estimating whole-brain networks through mutual information. The study involved 195 participants who completed the Sternberg Item Recognition and Flanker tasks while undergoing EEG recording. A mixed-effects linear model analyzed the influence of network metrics on cognitive performance, considering individual differences and task-specific dynamics. Results indicate that working memory and inhibition are associated with different network attributes, with working memory relying on distributed networks and inhibition on more segregated ones. Our analysis suggests that both strong and weak connections contribute to cognitive processes, as weak connections could potentially lead to a more stable and support networks of memory and inhibition. The findings indirectly support the Network Neuroscience Theory of Intelligence, suggesting different functional topology of networks inherent to various cognitive functions. Nevertheless, we propose that understanding individual variations in cognitive abilities requires recognizing both shared and unique processes within the brains network dynamics.

Author summaryThis study analyzes how working memory and inhibition correspond to distinct neural network patterns by constructing whole-brain networks via mutual information from EEG data of 195 subjects performing cognitive tasks. Findings reveal working memory is supported by distributed connections while inhibition depends on segregated ones. The research underscores the importance of both strong and weak neural connections in cognitive function and supports the notion that cognitive functions emerge from the brain network of distinct topology. Moreover, it highlights the need to account for individual and task-specific variations to fully grasp the diverse network dynamics influencing cognitive abilities.

H-current modulation of cortical Up and Down states
Understanding the link between cellular processes and brain function remains a key challenge in neuroscience. One crucial aspect is the interplay between specific ion channels and network dynamics. This work reveals a role for h-current, a hyperpolarization-activated cationic current, in shaping cortical slow oscillations. Cortical slow oscillations exhibit rhythmic periods of activity (Up states) alternating with silent periods (Down states). By progressively reducing h-current in both cortical slices and in a computational model, we observed Up states transformed into prolonged plateaus of sustained firing, while Down states were also significantly extended. This transformation led to a five-fold reduction in oscillation frequency. In a biophysical recurrent network model, we identified the cellular mechanisms: an increased input resistance and membrane time constant, increasing neuronal responsiveness to even weak inputs. HCN channels, the molecular basis of h-current, are known neuromodulatory targets, suggesting potential pathways for dynamic control of brain rhythms.

Early hippocampal high-amplitude rhythmic spikes predict post-traumatic epilepsy in mice
Oscillations, a highly conserved brain function across mammalian species, are pivotal in brain physiology and pathology. Traumatic brain injury (TBI) often leads to subacute and chronic brain oscillatory alterations associated with complications like post-traumatic epilepsy (PTE) in patients and animal models. Our recent work longitudinally recorded local field potential from the contralateral hippocampus of 12 strains of recombinant inbred Collaborative Cross (CC) mice alongside classical laboratory inbred C57BL/6J mice after lateral fluid percussion injury. In this study, we profiled the acute (<12 hr post-injury) and subacute (12-48 hr post-injury) hippocampal oscillatory responses to TBI and evaluated their predictive value for PTE. We found dynamic high-amplitude rhythmic spikes with elevated power density and reduced entropy that prevailed during the acute phase in CC031 mice who later developed PTE. This characteristic early brain oscillatory alteration is absent in CC031 sham controls or other CC and reference C57BL/6J strains that did not develop PTE after TBI. Our work provides quantitative measures linking early brain oscillation to PTE at a population level in mice under controlled experimental conditions. These findings will offer insights into circuit mechanisms and potential targets for neuromodulatory intervention.

Multimodal assessment of acute stress dynamics using an Aversive Video Paradigm (AVP)
This study explored the efficacy of inducing stress through aversive video clips and investigated its impact on psychological processes, brain, and vegetative physiology. It had a randomized, single-blinded, crossover design, where participants were exposed in separate sessions to aversive or neutral video clips. Subjective feelings of stress were assessed via questionnaires. Electroencephalography (EEG) with 62 electrodes was recorded continuously. EEG power and connectivity changes based on coherence were analyzed. Heart rate (HR) and heart rate variability (HRV) data were obtained during the whole experiment, and saliva was collected for cortisol and cytokine analysis at different time intervals. Subjective data showed increased anxiety and negative affect induced by the aversive video clips, accompanied by elevated salivary cortisol levels after exposure to the stressful clips, and decreased heart rate variability. Cytokine levels however increased over time in both control and stress conditions, which argues against a stress-specific alteration of cytokines in this specific stress protocol. EEG alterations during stress induction suggest a disruption of top-down control and increased bottom-up processing. These results show that aversive video clips are suited to induce psychological stress in an experimental setting reliably, and are associated with stress-specific emotional, and physiological changes.