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Characterization of brain states is essential for understanding its functioning in the absence of external stimuli. Brain states differ on their balance between excitation and inhibition, and on the diversity of their activity patterns. These can be respectively indexed by 1/f slope and Lempel–Ziv complexity (LZc). However, whether and how these two brain state properties relate remain elusive. Here we analyzed the relation between 1/f slope and LZc with two in-silico approaches and in both rat EEG and monkey ECoG data. We contrasted resting state with propofol anesthesia, which directly modulates the excitation-inhibition balance. We found convergent results among simulated and empirical data, showing a strong, inverse and non trivial monotonic relation between 1/f slope and complexity, consistent at both ECoG and EEG scales. We hypothesize that differentially entropic regimes could underlie the link between the excitation-inhibition balance and the vastness of the repertoire of brain systems.

•Nicotine promotes functional segregation in task, but not in resting-state.•In-task segregation correlates with visual-attentional performance.•A decrease in global coupling and local inhibition reproduces the effects of nicotine.•Modeling suggests mechanisms for the cholinergic influence on connectivity. Integration and segregation are two fundamental principles of brain organization. The brain manages the transitions and balance between different functional segregated or integrated states through neuromodulatory systems. Recently, computational and experimental studies suggest a pro-segregation effect of cholinergic neuromodulation. Here, we studied the effects of the cholinergic system on brain functional connectivity using both empirical fMRI data and computational modeling. First, we analyzed the effects of nicotine on functional connectivity and network topology in healthy subjects during resting-state conditions and during an attentional task. Then, we employed a whole-brain neural mass model interconnected using a human connectome to simulate the effects of nicotine and investigate causal mechanisms for these changes. The drug effect was modeled decreasing both the global coupling and local feedback inhibition parameters, consistent with the known cellular effects of acetylcholine. We found that nicotine incremented functional segregation in both empirical and simulated data, and the effects are context-dependent: observed during the task, but not in the resting state. In-task performance correlates with functional segregation, establishing a link between functional network topology and behavior. Furthermore, we found in the empirical data that the regional density of the nicotinic acetylcholine α4β2 correlates with the decrease in functional nodal strength by nicotine during the task. Our results confirm that cholinergic neuromodulation promotes functional segregation in a context-dependent fashion, and suggest that this segregation is suited for simple visual-attentional tasks.

Brain activity is constrained by local availability of chemical energy, which is generated through compartmentalized metabolic processes. By analyzing data of whole human brain gene expression, we characterize the spatial distribution of seven glucose and monocarboxylate membrane transporters that mediate astrocyte—neuron lactate shuttle transfer of energy. We found that the gene coding for neuronal MCT2 is the only gene enriched in cerebral cortex where its abundance is inversely correlated with cortical thickness. Coexpression network analysis revealed that MCT2 was the only gene participating in an organized gene cluster enriched in K⁺ dynamics. Indeed, the expression of KATP subunits, which mediate lactate increases with spiking activity, is spatially coupled to MCT2 distribution. Notably, MCT2 expression correlated with fluorodeoxyglucose positron emission tomography task-dependent glucose utilization. Finally, the MCT2 messenger RNA gradient closely overlaps with functional MRI brain regions associated with attention, arousal, and stress. Our results highlight neuronal MCT2 lactate transporter as a key component of the cross-talk between astrocytes and neurons and a link between metabolism, cortical structure, and state-dependent brain function.

Perceptual updating has been hypothesised to rely on a network reset modulated by bursts of ascending neuromodulatory neurotransmitters, such as noradrenaline, abruptly altering the brain’s susceptibility to changing sensory activity. To test this hypothesis at a large-scale, we analysed an ambiguous figures task using pupillometry and functional magnetic resonance imaging (fMRI). Behaviourally, qualitative shifts in the perceptual interpretation of an ambiguous image were associated with peaks in pupil diameter, an indirect readout of phasic bursts in neuromodulatory tone. We further hypothesised that stimulus ambiguity drives neuromodulatory tone, leading to heightened neural gain, hastening perceptual switches. To explore this hypothesis computationally, we trained a recurrent neural network (RNN) on an analogous perceptual categorisation task, allowing gain to change dynamically with classification uncertainty. As predicted, higher gain accelerated perceptual switching by transiently destabilising the network’s dynamical regime in periods of maximal uncertainty. We leveraged a low-dimensional readout of the RNN dynamics to develop two novel macroscale predictions: perceptual switches should occur with peaks in low-dimensional brain state velocity and with a flattened egocentric energy landscape. Using fMRI, we confirmed these predictions, highlighting the role of the neuromodulatory system in the large-scale network reconfigurations mediating adaptive perceptual updates.

The human brain displays a rich repertoire of states that emerge from the microscopic interactions of cortical and subcortical neurons. Difficulties inherent within large-scale simultaneous neuronal recording limit our ability to link biophysical processes at the microscale to emergent macroscopic brain states. Here we introduce a microscale biophysical network model of layer-5 pyramidal neurons that display graded coarse-sampled dynamics matching those observed in macroscale electrophysiological recordings from macaques and humans. We invert our model to identify the neuronal spike and burst dynamics that differentiate unconscious, dreaming, and awake arousal states and provide insights into their functional signatures. We further show that neuromodulatory arousal can mediate different modes of neuronal dynamics around a low-dimensional energy landscape, which in turn changes the response of the model to external stimuli. Our results highlight the promise of multiscale modelling to bridge theories of consciousness across spatiotemporal scales. Here the authors describe a biophysical layer-5 pyramidal neuronal model linking microscale spiking to macroscale complex dynamics, that predicts distinct burst dynamics and information processing across unconscious, dreaming, and awake states.

•Videogames expertise is associated with meso‑scale integration.•Connectivity differences are related to attention, reasoning, and inference.•In-silico stimulation revealed filtering properties of players’ connectomes. Video games are a valuable tool for studying the effects of training and neural plasticity on the brain. However, the underlying mechanisms related to plasticity-associated brain structural changes and their impact on brain dynamics are unknown. Here, we used a semi-empirical whole-brain model to study structural neural plasticity mechanisms linked to video game expertise. We hypothesized that video game expertise is associated with neural plasticity-mediated changes in structural connectivity that manifest at the meso‑scale level, resulting in a more segregated functional network topology. To test this hypothesis, we combined structural connectivity data of StarCraft II video game players (VGPs, n = 31) and non-players (NVGPs, n = 31), with generic fMRI data from the Human Connectome Project and computational models, to generate simulated fMRI recordings. Graph theory analysis on simulated data was performed during both resting-state conditions and external stimulation. VGPs’ simulated functional connectivity was characterized by a meso‑scale integration, with increased local connectivity in frontal, parietal, and occipital brain regions. The same analyses at the level of structural connectivity showed no differences between VGPs and NVGPs. Regions that increased their connectivity strength in VGPs are known to be involved in cognitive processes crucial for task performance such as attention, reasoning, and inference. In-silico stimulation suggested that differences in FC between VGPs and NVGPs emerge in noisy contexts, specifically when the noisy level of stimulation is increased. This indicates that the connectomes of VGPs may facilitate the filtering of noise from stimuli. These structural alterations drive the meso‑scale functional changes observed in individuals with gaming expertise. Overall, our work sheds light on the mechanisms underlying structural neural plasticity triggered by video game experiences.

Tinnitus is the perception of sounds without external stimuli, affecting 10%-15% of the general population and up to 25% of individuals over 70 years of age. While traditionally viewed as an auditory phenomenon, growing evidence highlights the role of the central nervous system in its pathophysiology. One of the proposed mechanisms, the “gating hypothesis” of tinnitus, suggests an alteration in the modulation of sensory activity by the frontostriatal network. Although structural changes in frontal areas support this idea, gray matter differences in subcortical regions—such as the auditory pathway and basal ganglia—remain poorly understood. Here, we examined subcortical structures and auditory function in older adults with mild presbycusis from the ANDES cohort, including 51 tinnitus patients and 40 age-matched controls. We analyzed brain volume via structural magnetic resonance imaging and subcortical auditory functionality via auditory brainstem responses (ABRs). We found non-significant differences in age, hearing loss, cognitive impairment, and ABR amplitudes between the groups. Notably, tinnitus patients presented a significant increase in the volume of basal ganglia structures (striatum and pallidum) but not in auditory areas. These findings reinforce the role of the basal ganglia in age-related tinnitus pathophysiology.

•Cardiometabolic status -as measured by the Allostatic load index (ALI)- correlates with neurovascular burden, as well as structural and functional signatures of the aging brain.•Cardiometabolic status links ventricular enlargement but not hippocampal atrophy with neurovascular burden.•EEG spectral exponent flattening and not alpha power— two functional signatures of the aging brain — correlate with cardiometabolic state and neurovascular burden.•Cardiometabolic status fully mediates the relationship between neurovascular burden-related inflammation, as indicated by ventricular enlargement, and flattened EEG spectral exponent.•Our findings suggest that neuroinflammatory pathways explain the link between cardiometabolic health, WMHs, and EEG changes in aging. Aging affects brain structure and function alongside metabolic and vascular processes leading to energetic impairments. While local neurometabolic dysfunction in aging is well-documented, the influence of systemic cardiometabolic and vascular markers on brain structure and function remains less understood. We examine the link between cardiometabolic dysfunction (measured by an allostatic load index) and neurovascular burden (measured by white matter hyperintensities), and their associations with brain changes, including ventricular and hippocampal volume, as well as EEG activity, across the adult lifesplan. Analyzing data from 196 healthy individuals across ages (20–75 years), we found a significant positive correlation between allostatic load index and white-matter hyperintensities, irrespective of age. White matter hyperintensities are also positively linked with ventricular enlargement, but not hippocampal atrophy. The allostatic load index mediated the relationship between white-matter hyperintensities and ventricular volume. Regarding brain function, changes in the spectral aperiodic exponent but not periodic alpha power were linked to white matter hyperintensities and the allostatic load index. The allostatic load index also mediated the relationship between spectral aperiodic exponent and white matter hyperintensities. Thus, findings suggest that the cardiometabolic state, as measured by the allostatic load index, plays a crucial role in brain health in aging, particularly influencing ventricular enlargement and increased aperiodic activity.

The functional evaluation of auditory-nerve activity in spontaneous conditions has remained elusive in humans. In animals, the frequency analysis of the round-window electrical noise recorded by means of electrocochleography yields a frequency peak at around 900 to 1000 Hz, which has been proposed to reflect auditory-nerve spontaneous activity. Here, we studied the spectral components of the electrical noise obtained from cochlear implant electrocochleography in humans. We recruited adult cochlear implant recipients from the Clinical Hospital of the Universidad de Chile, between the years 2021 and 2022. We used the AIM System from Advanced Bionics® to obtain single trial electrocochleography signals from the most apical electrode in cochlear implant users. We performed a protocol to study spontaneous activity and auditory responses to 0.5 and 2 kHz tones. Twenty subjects including 12 females, with a mean age of 57.9 ± 12.6 years (range between 36 and 78 years) were recruited. The electrical noise of the single trial cochlear implant electrocochleography signal yielded a reliable peak at 3.1 kHz in 55% of the cases (11 out of 20 subjects), while an oscillatory pattern that masked the spectrum was observed in seven cases. In the other two cases, the single-trial noise was not classifiable. Auditory stimulation at 0.5 kHz and 2.0 kHz did not change the amplitude of the 3.1 kHz frequency peak. We found two main types of noise patterns in the frequency analysis of the single-trial noise from cochlear implant electrocochleography, including a peak at 3.1 kHz that might reflect auditory-nerve spontaneous activity, while the oscillatory pattern probably corresponds to an artifact.

Sleep onset is characterized by a departure from arousal, and can be separated into well-differentiated stages: NREM (which encompasses three substages: N1, N2 and N3) and REM (Rapid Eye Movement). Awake brain dynamics are maintained by various wake-promoting mechanisms, particularly the neuromodulators Acetylcholine (ACh) and Noradrenaline (NA), whose levels naturally decrease during the transition to sleep. The combined influence of these neurotransmitters on brain connectivity during sleep remains unclear, as previous models have examined them mostly in isolation or only in deep sleep. In this study, we analyze fMRI data obtained from healthy individuals and employ a whole-brain model to investigate how changes in brain neurochemistry during NREM sleep, specifically involving ACh and NA, affect the Functional Connectivity (FC) of the brain. FC analysis reveals distinct connectivity changes: a decrease in Locus Coeruleus (LC) connectivity with the cortex during N2 and N3, and a decrease in Basal Forebrain (BF) connectivity with the cortex during N3. Additionally, compared to Wakefulness (W), there is a transition to a more integrated state in N1 and a more segregated state in N3. Using a Wilson-Cowan whole-brain model, informed by an empirical connectome and a heterogeneous receptivity map of neuromodulators, we explored possible mechanisms underlying these dynamics. We fit the model adjusting the coupling and input-output slope of the whole-brain model to account for ACh and NA, respectively, and show that region-specific neurotransmitter effect is key to explain their effects on FC. This work enhances our understanding of neurotransmitters’ roles in modulating sleep stages and their significant contribution to brain state transitions between different states of consciousness, both in health and disease.