Biology subjects

Rheims, S.

Publications and source records attributed to Rheims, S..

14 recordsLinked to original sources

bioRxiv2026

CB2 activation during epileptogenesis recruits immunomodulatory monocytes and mitigates cognitive, affective and seizure outcomes

Temporal lobe epilepsy (TLE) is frequently associated with severe cognitive impairment and psychiatric comorbidities that are highly disabling and not targeted by anti-seizure medications, highlighting the need for therapies that target epileptogenesis rather than merely suppress seizures. Despite strong evidence implicating neuroinflammation in this process, anti-inflammatory approaches have not yielded such therapies yet. Infiltrating peripheral monocytes are widely viewed as detrimental amplifiers of post-status epilepticus (SE) inflammation, although emerging data suggest context-dependent protective roles. The cannabinoid receptor type 2 (CB2), highly expressed in myeloid cells, represents a potential immunomodulatory target linking leukocyte recruitment and inflammatory polarization. Using a juvenile rat model of TLE, we characterized hippocampal neuroinflammation and CB2 expression during epileptogenesis and evaluated the effects of transient CB2 activation with the selective agonist GP1a. SE induced a rapid but transient inflammatory response and robust recruitment of peripheral monocytes that persisted as anti-inflammatory monocyte-derived macrophages. CB2 activation did not suppress early cytokine induction but selectively enhanced recruitment of anti-inflammatory monocytes and modestly increased anti-inflammatory signaling. Importantly, transient CB2 stimulation preserved synaptic plasticity, improved cognitive performance, reduced anxiety-like behavior, and delayed seizure onset. These findings identify CB2-dependent modulation of peripheral myeloid cells as a potential disease-modifying axis in TLE.

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bioRxiv2025

Multi-task Intracranial EEG recordings reveal a Comprehensive Role of the Human Dorsal Anterior Insula in High-Level Cognition

The dorsal anterior insula (dAI) is widely recognized as a cornerstone of human cognition. However, its functional characterization remains the subject of considerable debate and competing theories. Embracing a "shift in viewpoint" approach--defining a brain regions function through the observation of the same neural population across diverse experimental contexts--this study used intracranial EEG (iEEG) recordings from a large cohort of patients to investigate the sub-second neural response dynamics of the human dAI across a broad range of cognitive tasks, spanning visual category discrimination, phonological and semantic processing, attentive visual search, and verbal and visuospatial working memory. This within-subject, multi-task iEEG framework offered a robust basis for decoding the structure-function relationship of the dAI and for empirically testing key predictions of prevailing theoretical models concerning its role. Our findings confirmed the dAIs involvement in the Action-Mode Network and shed new light on the large-scale spatiotemporal organization of that network, while providing novel insights into the interplay between cognitive effort and efficiency.

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bioRxiv2025

Choosing the best or avoiding the worst: complementary and opponent value signals in the human brain

Whether the brain encodes the subjective value of pleasant and unpleasant situations via a single integrated circuit or through distinct pathways remains unresolved. It is also unclear how neural value signals guide choices when the context involves choosing the most favorable option or avoiding the most unfavorable one. To address these questions, we recorded intracerebral activity from 27 participants as they first rated pleasant and unpleasant scenarios and then made binary choices across all combinations of item domain (pleasant/unpleasant) and choice frame (choose best/worst). Ventromedial prefrontal cortex (vmPFC) broadband gamma activity (BGA, 50-150 Hz) tracked the value of pleasant items during rating and pre-choice, correlating positively with the most pleasant item irrespective of choice frame. Similarly, anterior insula (aIns) BGA tracked the value of unpleasant items during rating and pre-choice, correlating negatively with the most unpleasant item irrespective of choice frame. The difference in relative value correlations between the vmPFC and aIns was larger for choices involving a conflict between item domain and choice frame, consistent with slower response times and choices less aligned with value differences in these trials. These findings reveal dissociable yet complementary neural systems for pleasant and unpleasant valuation and highlight how such signals may guide flexible decision-making across contexts.

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bioRxiv2025

Brain Infiltrated Monocyte-Macrophages in a rat model of Temporal Lobe Epilepsy: Revisiting the Pro-Inflammatory Paradigm

Neuroinflammation is central to temporal lobe epilepsy, yet the specific role of myeloid cells remains unclear. In status epilepticus (SE) models, circulating monocytes have been reported to infiltrate the brain, though distinguishing them from microglia remains challenging. Using a rat model, we traced infiltrating monocytes post-SE, to investigate their persistence, phenotypic evolution during epileptogenesis and contribution to neuroinflammation. By tracking phagocyted fluorescent nanoparticles and using CD68 immunohistochemistry, we confirmed that monocytes entered the brain in significant numbers 24 hours post-SE, after the inflammatory peak occurred (7h post-SE). Tracked up to 7 weeks, these cells adopted a microglia-like phenotype, contributed to the microglial scar and sustained low-grade inflammation during the chronic phase of epilepsy solely through their presence, as their expression of pro-inflammatory markers resembled that of non-activated microglia. Importantly, monocytes initially and transiently supported an anti-inflammatory response providing a unique opportunity to modulate neuroinflammation and potentially disrupt epilepsy progression, opening new avenues for therapeutic interventions.

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bioRxiv2023

Cannabinoid receptor type 2 expression in mouse brain: from mapping to regulation in microglia under inflammatory conditions

Since its detection in the brain, the cannabinoid receptor type 2 (CB2) has been deemed a promising therapeutic target for various neurological and psychiatric disorders. However, precise brain mapping of CB2 expression is currently lacking. Using magnetic cell sorting, calibrated reverse transcription-quantitative PCR, and single-nucleus RNA-seq, we revealed the low level of CB2 expression in all brain regions examined, mainly by a few microglial cells and by neurons in an even lower proportion. Upon lipopolysaccharide stimulation to simulate non-sterile neuroinflammatory conditions, we demonstrated that the inflammatory response was associated with a transient reduction in CB2 mRNA levels in the brain tissue, particularly in microglia. This result, confirmed in the BV2 microglial cells, contrasts with the positive correlation observed between CB2 mRNA levels and the inflammatory response upon stimulation by interferon-gamma, which models sterile inflammatory conditions. Thus, discrete brain CB2 expression may be upregulated or downregulated depending on the inflammatory context.

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bioRxiv2023

Neural interactions in the human frontal cortex dissociate reward and punishment learning

How human prefrontal and insular regions interact while maximizing rewards and minimizing punishments is unknown. Capitalizing on human intracranial recordings, we demonstrate that the functional specificity toward reward or punishment learning is better disentangled by interactions compared to local representations. Prefrontal and insular cortices display non-selective neural populations to rewards and punishments. Non-selective responses, however, give rise to context-specific interareal interactions. We identify a reward subsystem with redundant interactions between the orbitofrontal and ventromedial prefrontal cortices, with a driving role of the latter. In addition, we find a punishment subsystem with redundant interactions between the insular and dorsolateral cortices, with a driving role of the insula. Finally, switching between reward and punishment learning is mediated by synergistic interactions between the two subsystems. These results provide a unifying explanation of distributed cortical representations and interactions supporting reward and punishment learning.

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bioRxiv2021

Intracerebral mechanisms explaining the impact of incidental feedback on mood state and risky choice

Identifying factors whose fluctuations are associated with choice inconsistency is a major issue for rational decision theory. Here, we investigated the neuro-computational mechanisms through which mood fluctuations may bias human choice behavior. Intracerebral EEG data were collected in a large group of participants (n = 30), while they were performing interleaved quiz and choice tasks. Neural baseline activity preceding choice onset was confronted first to mood level, estimated by a computational model integrating the feedbacks received in the quiz task, and then to the weighting of option attributes, in a computational model predicting risk attitude in the choice task. Results showed that 1) elevated broadband gamma activity (BGA) in the ventromedial prefrontal cortex (vmPFC) and dorsal anterior insula (daIns) was respectively signaling periods of high and low mood, 2) increased vmPFC and daIns BGA respectively promoted and tempered risk taking by overweighting gain versus loss prospects. Thus, incidental feedbacks induce brain states that correspond to different moods and bias the comparison of safe and risky options. More generally, these findings might explain why people experiencing positive (or negative) outcome in some part of their life tend to expect success (or failure) in any other.

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bioRxiv2021

Respiratory dysfunctions in two rodent models of chronic epilepsy and acute seizures and their link with brainstem serotonin system

Patients with drug-resistant epilepsy can experience respiratory alterations notably during seizures. The mechanisms underlying this long-term alteration of respiratory function remain unclear. This study aimed at determining in rats whether epilepsy is associated with alterations of both the respiratory function and brainstem serotonin (5-HT) system. Epilepsy was triggered by pilocarpine-induced status epilepticus in rats. 30-50% of epileptic (EPI) rats exhibited sharp decrease of oxygen consumption (SDOC), low metabolic rate of oxygen and slow regular ventilation; these rats were called EPI/SDOC+ rats. These alterations were only detected in rats with chronic epilepsy, independent of behavioral seizures, persisted over the time, and were not associated with death. In these rats, 5-HT fiber density in the nucleus tractus solitarius was below that of control and EPI/SDOC-rats. Both EPI/SDOC+ rats and DBA/2 mice presenting with fatal respiratory arrest following an audiogenic-induced seizure, a model of sudden and expected death in epilepsy, had increased transcript levels of tryptophan hydroxylase 2 (p<0.001 for both strains) and 5-HT presynaptic transporter (rats: p=0.003; mice: p=0.001). Thus, our data support that 5-HT alterations are associated with chronic and acute epilepsy-related respiratory dysfunctions.

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bioRxiv2021

Low grade inflammation in the epileptic hippocampus contrasts with explosive inflammation occurring in the acute phase following status epilepticus in rats: translation to patients with epilepsy

There is still a lack of robust data, acquired identically and reliably from tissues either surgically resected from patients with mesial temporal lobe epilepsy (mTLE) or collected in animal models, to answer the question of whether the degree of inflammation of the hippocampus differs between mTLE patients, and between epilepsy and epileptogenesis. Here, using highly calibrated RTqPCR, we show that neuroinflammatory marker expression was highly variable in the hippocampus and the amygdala of mTLE patients. This variability was not associated with gender, age, duration of epilepsy, seizure frequency, and anti-seizure drug treatments. In addition, it did not correlate between the two structures and was reduced when the inflammatory status was averaged between the two structures. We also show that brain tissue not frozen within minutes after resection had significantly decreased housekeeping gene transcript levels, precluding the possibility of using post-mortem tissues to assess physiological baseline transcript levels in the hippocampus. We thus used rat models of mTLE, induced by status epilepticus (SE), that have the advantage of providing access to physiological baseline values. They indisputably indicated that inflammation measured during the chronic phase of epilepsy was much lower than the explosive inflammation occurring after SE, and was only detected when epilepsy was associated with massive neurodegeneration and gliosis. Comparison between the inter-individual variability measured in patients and that established in all epileptic and control rats suggests that some mTLE patients may have very low inflammation in the hippocampus, close to control values. However, the observation of elevated inflammation in the amygdala of some patients indicates that inflammation should be studied not only at the epileptic hippocampus, but also in the associated brain structures in order to have a more integrated view of the degree of inflammation present in brain networks involved in mesial temporal lobe epilepsy.

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bioRxiv2020

THE DUAL-TASK COST IS DUE TO NEURAL INTERFERENCES DISRUPTING THE OPTIMAL SPATIO-TEMPORAL DYNAMICS OF THE COMPETING TASKS

Dual-tasking is extremely prominent nowadays, despite ample evidence that it comes with a performance cost: the Dual-Task (DT) cost. Neuroimaging studies have established that tasks are more likely to interfere if they rely on common brain regions, but the precise neural origin of the DT cost has proven elusive so far, mostly because fMRI does not record neural activity directly and cannot reveal the key effect of timing, and how the spatio-temporal neural dynamics of the tasks coincide. Recently, DT electrophysiological studies in monkeys have recorded neural populations shared by the two tasks with millisecond precision to provide a much finer understanding of the origin of the DT cost. We used a similar approach in humans, with intracranial EEG, to assess the neural origin of the DT cost in a particularly challenging naturalistic paradigm which required accurate motor responses to frequent visual stimuli (task T1) and the retrieval of information from long-term memory (task T2), as when answering passengers questions while driving. We found that T2 elicited neuroelectric interferences in the gamma-band (>40 Hz), in key regions of the T1 network including the Multiple Demand Network. They reproduced the effect of disruptive electrocortical stimulations to create a situation of dynamical incompatibility, which might explain the DT cost. Yet, participants were able to flexibly adapt their strategy to minimize interference, and most surprisingly, reduce the reliance of T1 on key regions of the executive control network - the anterior insula and the dorsal anterior cingulate cortex - with no performance decrement. HIGHLIGHTS- First direct evidence in humans of neural interferences between two tasks. - First explanation of the Dual-Task cost at the neural level in humans. - First Dual-Tasking study with intracranial EEG in naturalistic conditions.

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bioRxiv2020

Opponent intracerebral signals for reward and punishment prediction errors in humans

Whether maximizing rewards and minimizing punishments rely on distinct brain systems remains debated, inconsistent results coming from human neuroimaging and animal electrophysiology studies. Bridging the gap across species and techniques, we recorded intracerebral activity from twenty patients with epilepsy while they performed an instrumental learning task. We found that both reward and punishment prediction errors (PE), estimated from computational modeling of choice behavior, correlated positively with broadband gamma activity (BGA) in several brain regions. In all cases, BGA increased with both outcome (reward or punishment versus nothing) and surprise (how unexpected the outcome is). However, some regions (such as the ventromedial prefrontal and lateral orbitofrontal cortex) were more sensitive to reward PE, whereas others (such as the anterior insula and dorsolateral prefrontal cortex) were more sensitive to punishment PE. Thus, opponent systems in the human brain might mediate the repetition of rewarded choices and the avoidance of punished choices.

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bioRxiv2018

BLAST : a short computerized test to measure the ability to stay on task. Normative behavioral data and detailed cortical dynamics.

1.This article provides an exhaustive description of a new short computerized test to assess on a second-to-second basis the ability of individuals to << stay on task >>, that is, to apply selectively and repeatedly task-relevant cognitive processes. The task (Bron/Lyon Attention Stability Test, or BLAST) lasts around one minute, and measures repeatedly the time to find a target letter in a two-by-two letter array, with an update of all letters every new trial across thirty trials. Several innovative psychometric measures of attention stability are proposed based on the instantaneous fluctuations of reaction times throughout the task, and normative data stratified over a wide range of age are provided by a large (>6000) dataset of participants aged 8 to 70. We also detail the large-scale brain dynamics supporting the task from an in-depth study of 32 participants with direct electrophysiological cortical recordings (intracranial EEG) to prove that BLAST involves critically large-scale executive attention networks, with a marked activation of the dorsal attention network and a deactivation of the default-mode network. Accordingly, we show that BLAST performance correlates with scores established by ADHD-questionnaires.

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bioRxiv2018

Identifying task-relevant spectral signatures of perceptual categorization in the human cortex

Human brain has developed mechanisms to efficiently decode sensory information according to perceptual categories of high prevalence in the environment, such as faces, symbols, objects. Neural activity produced within localized brain networks has been associated with the process that integrates both sensory bottom-up and cognitive top-down information processing. Yet, how specifically the different types and components of neural responses reflect the local networks selectivity for categorical information processing is still unknown. By mimicking the decoding of the sensory information with machine learning we can obtain accurate artificial decoding models. Having the artificial system functionally on par with the biological one we can analyze the mechanics of the artificial system to gain insights into the inner workings of its biological counterpart. In this work we train a Random Forest classification model to decode eight perceptual categories from visual stimuli given a broad spectrum of human intracranial signals (4 - 150 Hz) obtained during a visual perception task, and analyze which of the spectral features the algorithm deemed relevant to the perceptual decoding. We show that network selectivity for a single or multiple categories in sensory and non-sensory cortices is related to specific patterns of power increases and decreases in both low (4 - 50 Hz) and high (50 - 150 Hz) frequency bands. We demonstrate that the locations and patterns of activity that are identified by the algorithm not only coincide with the known spectro-spatial signatures, but extend our knowledge by uncovering additional spectral signatures describing neural mechanisms of visual category perception in human brain.\n\nSignificance statementPrevious works have shown where and when perceptual category information can be decoded from the human brain, our study adds to that line of research by allowing to identify spectrotemporal patterns that contribute to category decoding without the need to formulate a priori hypothesis on which spectral components and at which times are worth investigating. Application of this method to an extensive dataset of human intracerebral recordings delineates the locations that are predictive of several perceptual categories from the locations that are have narrow specialization, identifies spectral signatures characteristic of each of 8 perceptual categories and allows to observe global and category-specific patterns of neural activity pertinent to functional perceptual categorization.

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bioRxiv2017

Frequency-Resolved Correlates Of Visual Object Recognition In Human Brain Revealed By Deep Convolutional Neural Networks

Previous work demonstrated a direct correspondence between the hierarchy of the human visual areas and layers of deep convolutional neural networks (DCNN) trained on visual object recognition. We used DCNNs to investigate which frequency bands correlate with feature transformations of increasing complexity along the ventral visual pathway. By capitalizing on intracranial depth recordings from 100 patients and 11293 electrodes we assessed the alignment between the DCNN and signals at different frequency bands in different time windows. We found that gamma activity, especially in the low gamma-band (30 - 70 Hz), matched the increasing complexity of visual feature representations in the DCNN. These findings show that the activity of the DCNN captures the essential characteristics of biological object recognition not only in space and time, but also in the frequency domain. These results also demonstrate the potential that modern artificial intelligence algorithms have in advancing our understanding of the brain.\n\nSignificance StatementRecent advances in the field of artificial intelligence have revealed principles about neural processing, in particular about vision. Previous works have demonstrated a direct correspondence between the hierarchy of human visual areas and layers of deep convolutional neural networks (DCNNs), suggesting that DCNN is a good model of visual object recognition in primate brain. Studying intracranial depth recordings allowed us to extend previous works by assessing when and at which frequency bands the activity of the visual system corresponds to the DCNN. Our key finding is that signals in gamma frequencies along the ventral visual pathway are aligned with the layers of DCNN. Gamma frequencies play a major role in transforming visual input to coherent object representations.

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