Optical recordings of organellar membrane potentials and the components of membrane conductance in lysosomes.

The eukaryotic cell is highly compartmentalized with organelles. Owing to their function in transporting metabolites, metabolic intermediates and byproducts of metabolic activity, organelles are important players in the orchestration of cellular function. Recent advances in optical methods for interrogating the different aspects of organellar activity promise to revolutionize our ability to dissect cellular processes with unprecedented detail. The transport activity of organelles is usually coupled to the transport of charged species; therefore, it is not only associated with the metabolic landscape but also entangled with membrane potentials. In this context, the targeted expression of fluorescent probes for interrogating organellar membrane potential (Ψorg) emerges as a powerful approach, offering less-invasive conditions and technical simplicity to interrogate cellular signalling and metabolism. Different research groups have made remarkable progress in adapting a variety of optical methods for measuring and monitoring Ψorg. These approaches include using potentiometric dyes, genetically encoded voltage indicators, hybrid fluorescence resonance energy transfer sensors and photoinduced electron transfer systems. These studies have provided consistent values for the resting potential of single-membrane organelles, such as lysosomes, the Golgi and the endoplasmic reticulum. We can foresee the use of dynamic measurements of Ψorg to study fundamental problems in organellar physiology that are linked to serious cellular disorders. Here, we present an overview of the available techniques, a survey of the resting membrane potential of internal membranes and, finally, an open-source mathematical model useful to interpret and interrogate membrane-bound structures of small volume by using the lysosome as an example.

Gaming expertise induces meso­scale brain plasticity and efficiency mechanisms as revealed by whole-brain modeling.

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 meso­scale 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 meso­scale 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 meso­scale 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.

Viscous dynamics associated with hypoexcitation and structural disintegration in neurodegeneration via generative whole-brain modeling.

INTRODUCTION: Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) lack mechanistic biophysical modeling in diverse, underrepresented populations. Electroencephalography (EEG) is a high temporal resolution, cost-effective technique for studying dementia globally, but lacks mechanistic models and produces non-replicable results. METHODS: We developed a generative whole-brain model that combines EEG source-level metaconnectivity, anatomical priors, and a perturbational approach. This model was applied to Global South participants (AD, bvFTD, and healthy controls). RESULTS: Metaconnectivity outperformed pairwise connectivity and revealed more viscous dynamics in patients, with altered metaconnectivity patterns associated with multimodal disease presentation. The biophysical model showed that connectome disintegration and hypoexcitability triggered altered metaconnectivity dynamics and identified critical regions for brain stimulation. We replicated the main results in a second subset of participants for validation with unharmonized, heterogeneous recording settings. DISCUSSION: The results provide a novel agenda for developing mechanistic model-inspired characterization and therapies in clinical, translational, and computational neuroscience settings.

Whole-brain modeling explains the context-dependent effects of cholinergic neuromodulation.

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 α4ß2 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.

Computational modelling in disorders of consciousness: Closing the gap towards personalised models for restoring consciousness.

Disorders of consciousness are complex conditions characterised by persistent loss of responsiveness due to brain injury. They present diagnostic challenges and limited options for treatment, and highlight the urgent need for a more thorough understanding of how human consciousness arises from coordinated neural activity. The increasing availability of multimodal neuroimaging data has given rise to a wide range of clinically- and scientifically-motivated modelling efforts, seeking to improve data-driven stratification of patients, to identify causal mechanisms for patient pathophysiology and loss of consciousness more broadly, and to develop simulations as a means of testing in silico potential treatment avenues to restore consciousness. As a dedicated Working Group of clinicians and neuroscientists of the international Curing Coma Campaign, here we provide our framework and vision to understand the diverse statistical and generative computational modelling approaches that are being employed in this fast-growing field. We identify the gaps that exist between the current state-of-the-art in statistical and biophysical computational modelling in human neuroscience, and the aspirational goal of a mature field of modelling disorders of consciousness; which might drive improved treatments and outcomes in the clinic. Finally, we make several recommendations for how the field as a whole can work together to address these challenges.

High-order functional redundancy in ageing explained via alterations in the connectome in a whole-brain model.

The human brain generates a rich repertoire of spatio-temporal activity patterns, which support a wide variety of motor and cognitive functions. These patterns of activity change with age in a multi-factorial manner. One of these factors is the variations in the brain's connectomics that occurs along the lifespan. However, the precise relationship between high-order functional interactions and connnectomics, as well as their variations with age are largely unknown, in part due to the absence of mechanistic models that can efficiently map brain connnectomics to functional connectivity in aging. To investigate this issue, we have built a neurobiologically-realistic whole-brain computational model using both anatomical and functional MRI data from 161 participants ranging from 10 to 80 years old. We show that the differences in high-order functional interactions between age groups can be largely explained by variations in the connectome. Based on this finding, we propose a simple neurodegeneration model that is representative of normal physiological aging. As such, when applied to connectomes of young participant it reproduces the age-variations that occur in the high-order structure of the functional data. Overall, these results begin to disentangle the mechanisms by which structural changes in the connectome lead to functional differences in the ageing brain. Our model can also serve as a starting point for modeling more complex forms of pathological ageing or cognitive deficits.

Dynamical noise can enhance high-order statistical structure in complex systems.

Recent research has provided a wealth of evidence highlighting the pivotal role of high-order interdependencies in supporting the information-processing capabilities of distributed complex systems. These findings may suggest that high-order interdependencies constitute a powerful resource that is, however, challenging to harness and can be readily disrupted. In this paper, we contest this perspective by demonstrating that high-order interdependencies can not only exhibit robustness to stochastic perturbations, but can in fact be enhanced by them. Using elementary cellular automata as a general testbed, our results unveil the capacity of dynamical noise to enhance the statistical regularities between agents and, intriguingly, even alter the prevailing character of their interdependencies. Furthermore, our results show that these effects are related to the high-order structure of the local rules, which affect the system's susceptibility to noise and characteristic time scales. These results deepen our understanding of how high-order interdependencies may spontaneously emerge within distributed systems interacting with stochastic environments, thus providing an initial step toward elucidating their origin and function in complex systems like the human brain.

Constitutive Phosphorylation as a Key Regulator of TRPM8 Channel Function.

In mammals, environmental cold sensing conducted by peripheral cold thermoreceptor neurons mostly depends on TRPM8, an ion channel that has evolved to become the main molecular cold transducer. This TRP channel is activated by cold, cooling compounds, such as menthol, voltage, and rises in osmolality. TRPM8 function is regulated by kinase activity that phosphorylates the channel under resting conditions. However, which specific residues, how this post-translational modification modulates TRPM8 activity, and its influence on cold sensing are still poorly understood. By mass spectrometry, we identified four serine residues within the N-terminus (S26, S29, S541, and S542) constitutively phosphorylated in the mouse ortholog. TRPM8 function was examined by Ca2+ imaging and patch-clamp recordings, revealing that treatment with staurosporine, a kinase inhibitor, augmented its cold- and menthol-evoked responses. S29A mutation is sufficient to increase TRPM8 activity, suggesting that phosphorylation of this residue is a central molecular determinant of this negative regulation. Biophysical and total internal reflection fluorescence-based analysis revealed a dual mechanism in the potentiated responses of unphosphorylated TRPM8: a shift in the voltage activation curve toward more negative potentials and an increase in the number of active channels at the plasma membrane. Importantly, basal kinase activity negatively modulates TRPM8 function at cold thermoreceptors from male and female mice, an observation accounted for by mathematical modeling. Overall, our findings suggest that cold temperature detection could be rapidly and reversibly fine-tuned by controlling the TRPM8 basal phosphorylation state, a mechanism that acts as a dynamic molecular brake of this thermo-TRP channel function in primary sensory neurons.SIGNIFICANCE STATEMENT Post-translational modifications are one of the main molecular mechanisms involved in adjusting the sensitivity of sensory ion channels to changing environmental conditions. Here we show, for the first time, that constitutive phosphorylation of the well-conserved serine 29 within the N-terminal domain negatively modulates TRPM8 channel activity, reducing its activation by agonists and decreasing the number of active channels at the plasma membrane. Basal phosphorylation of TRPM8 acts as a key regulator of its function as the main cold-transduction channel, significantly contributing to the net response of primary sensory neurons to temperature reductions. This reversible and dynamic modulatory mechanism opens new opportunities to regulate TRPM8 function in pathologic conditions where this thermo-TRP channel plays a critical role.

Selection of stimulus parameters for enhancing slow wave sleep events with a neural-field theory thalamocortical model.

Slow-wave sleep cortical brain activity, conformed by slow-oscillations and sleep spindles, plays a key role in memory consolidation. The increase of the power of the slow-wave events, obtained by auditory sensory stimulation, positively correlates with memory consolidation performance. However, little is known about the experimental protocol maximizing this effect, which could be induced by the power of slow-oscillation, the number of sleep spindles, or the timing of both events' co-occurrence. Using a mean-field model of thalamocortical activity, we studied the effect of several stimulation protocols, varying the pulse shape, duration, amplitude, and frequency, as well as a target-phase using a closed-loop approach. We evaluated the effect of these parameters on slow-oscillations (SO) and sleep-spindles (SP), considering: (i) the power at the frequency bands of interest, (ii) the number of SO and SP, (iii) co-occurrences between SO and SP, and (iv) synchronization of SP with the up-peak of the SO. The first three targets are maximized using a decreasing ramp pulse with a pulse duration of 50 ms. Also, we observed a reduction in the number of SO when increasing the stimulus energy by rising its amplitude. To assess the target-phase parameter, we applied closed-loop stimulation at 0°, 45°, and 90° of the phase of the narrow-band filtered ongoing activity, at 0.85 Hz as central frequency. The 0° stimulation produces better results in the power and number of SO and SP than the rhythmic or random stimulation. On the other hand, stimulating at 45° or 90° change the timing distribution of spindles centers but with fewer co-occurrences than rhythmic and 0° phase. Finally, we propose the application of closed-loop stimulation at the rising zero-cross point using pulses with a decreasing ramp shape and 50 ms of duration for future experimental work.

Cholinergic neuromodulation of inhibitory interneurons facilitates functional integration in whole-brain models.

Segregation and integration are two fundamental principles of brain structural and functional organization. Neuroimaging studies have shown that the brain transits between different functionally segregated and integrated states, and neuromodulatory systems have been proposed as key to facilitate these transitions. Although whole-brain computational models have reproduced this neuromodulatory effect, the role of local inhibitory circuits and their cholinergic modulation has not been studied. In this article, we consider a Jansen & Rit whole-brain model in a network interconnected using a human connectome, and study the influence of the cholinergic and noradrenergic neuromodulatory systems on the segregation/integration balance. In our model, we introduce a local inhibitory feedback as a plausible biophysical mechanism that enables the integration of whole-brain activity, and that interacts with the other neuromodulatory influences to facilitate the transition between different functional segregation/integration regimes in the brain.

Extracting temporal relationships between weakly coupled peptidergic and motoneuronal signaling: Application to Drosophila ecdysis behavior.

Neuromodulators, such as neuropeptides, can regulate and reconfigure neural circuits to alter their output, affecting in this way animal physiology and behavior. The interplay between the activity of neuronal circuits, their modulation by neuropeptides, and the resulting behavior, is still poorly understood. Here, we present a quantitative framework to study the relationships between the temporal pattern of activity of peptidergic neurons and of motoneurons during Drosophila ecdysis behavior, a highly stereotyped motor sequence that is critical for insect growth. We analyzed, in the time and frequency domains, simultaneous intracellular calcium recordings of peptidergic CCAP (crustacean cardioactive peptide) neurons and motoneurons obtained from isolated central nervous systems throughout fictive ecdysis behavior induced ex vivo by Ecdysis triggering hormone. We found that the activity of both neuronal populations is tightly coupled in a cross-frequency manner, suggesting that CCAP neurons modulate the frequency of motoneuron firing. To explore this idea further, we used a probabilistic logistic model to show that calcium dynamics in CCAP neurons can predict the oscillation of motoneurons, both in a simple model and in a conductance-based model capable of simulating many features of the observed neural dynamics. Finally, we developed an algorithm to quantify the motor behavior observed in videos of pupal ecdysis, and compared their features to the patterns of neuronal calcium activity recorded ex vivo. We found that the motor activity of the intact animal is more regular than the motoneuronal activity recorded from ex vivo preparations during fictive ecdysis behavior; the analysis of the patterns of movement also allowed us to identify a new post-ecdysis phase.

Cortical ignition dynamics is tightly linked to the core organisation of the human connectome.

The capability of cortical regions to flexibly sustain an "ignited" state of activity has been discussed in relation to conscious perception or hierarchical information processing. Here, we investigate how the intrinsic propensity of different regions to get ignited is determined by the specific topological organisation of the structural connectome. More specifically, we simulated the resting-state dynamics of mean-field whole-brain models and assessed how dynamic multistability and ignition differ between a reference model embedding a realistic human connectome, and alternative models based on a variety of randomised connectome ensembles. We found that the strength of global excitation needed to first trigger ignition in a subset of regions is substantially smaller for the model embedding the empirical human connectome. Furthermore, when increasing the strength of excitation, the propagation of ignition outside of this initial core-which is able to self-sustain its high activity-is way more gradual than for any of the randomised connectomes, allowing for graded control of the number of ignited regions. We explain both these assets in terms of the exceptional weighted core-shell organisation of the empirical connectome, speculating that this topology of human structural connectivity may be attuned to support enhanced ignition dynamics.

Role of TRPM8 Channels in Altered Cold Sensitivity of Corneal Primary Sensory Neurons Induced by Axonal Damage.

The cornea is extensively innervated by trigeminal ganglion cold thermoreceptor neurons expressing TRPM8 (transient receptor potential cation channel subfamily M member 8). These neurons respond to cooling, hyperosmolarity and wetness of the corneal surface. Surgical injury of corneal nerve fibers alters tear production and often causes dry eye sensation. The contribution of TRPM8-expressing corneal cold-sensitive neurons (CCSNs) to these symptoms is unclear. Using extracellular recording of CCSNs nerve terminals combined with in vivo confocal tracking of reinnervation, Ca2+ imaging and patch-clamp recordings of fluorescent retrogradely labeled corneal neurons in culture, we analyzed the functional modifications of CCSNs induced by peripheral axonal damage in male mice. After injury, the percentage of CCSNs, the cold- and menthol-evoked intracellular [Ca2+] rises and the TRPM8 current density in CCSNs were larger than in sham animals, with no differences in the brake K+ current IKD Active and passive membrane properties of CCSNs from both groups were alike and corresponded mainly to those of canonical low- and high-threshold cold thermoreceptor neurons. Ongoing firing activity and menthol sensitivity were higher in CCSN terminals of injured mice, an observation accounted for by mathematical modeling. These functional changes developed in parallel with a partial reinnervation of the cornea by TRPM8(+) fibers and with an increase in basal tearing in injured animals compared with sham mice. Our results unveil key TRPM8-dependent functional changes in CCSNs in response to injury, suggesting that increased tearing rate and ocular dryness sensation derived from deep surgical ablation of corneal nerves are due to enhanced functional expression of TRPM8 channels in these injured trigeminal primary sensory neurons.SIGNIFICANCE STATEMENT We unveil a key role of TRPM8 channels in the sensory and autonomic disturbances associated with surgical damage of eye surface nerves. We studied the damage-induced functional alterations of corneal cold-sensitive neurons using confocal tracking of reinnervation, extracellular corneal nerve terminal recordings, tearing measurements in vivo, Ca2+ imaging and patch-clamp recordings of cultured corneal neurons, and mathematical modeling. Corneal nerve ablation upregulates TRPM8 mainly in canonical cold thermoreceptors, enhancing their cold and menthol sensitivity, inducing a rise in the ongoing firing activity of TRPM8(+) nerve endings and an increase in basal tearing. Our results suggest that unpleasant dryness sensations, together with augmented tearing rate after corneal nerve injury, are largely due to upregulation of TRPM8 in cold thermoreceptor neurons.

Negative Modulation of TRPM8 Channel Function by Protein Kinase C in Trigeminal Cold Thermoreceptor Neurons.

TRPM8 is the main molecular entity responsible for cold sensing. This polymodal ion channel is activated by cold, cooling compounds such as menthol, voltage, and rises in osmolality. In corneal cold thermoreceptor neurons (CTNs), TRPM8 expression determines not only their sensitivity to cold, but also their role as neural detectors of ocular surface wetness. Several reports suggest that Protein Kinase C (PKC) activation impacts on TRPM8 function; however, the molecular bases of this functional modulation are still poorly understood. We explored PKC-dependent regulation of TRPM8 using Phorbol 12-Myristate 13-Acetate to activate this kinase. Consistently, recombinant TRPM8 channels, cultured trigeminal neurons, and free nerve endings of corneal CTNs revealed a robust reduction of TRPM8-dependent responses under PKC activation. In corneal CTNs, PKC activation decreased ongoing activity, a key parameter in the role of TRPM8-expressing neurons as humidity detectors, and also the maximal cold-evoked response, which were validated by mathematical modeling. Biophysical analysis indicated that PKC-dependent downregulation of TRPM8 is mainly due to a decreased maximal conductance value, and complementary noise analysis revealed a reduced number of functional channels at the cell surface, providing important clues to understanding the molecular mechanisms of how PKC activity modulates TRPM8 channels in CTNs.

Role of the Excitability Brake Potassium Current IKD in Cold Allodynia Induced by Chronic Peripheral Nerve Injury.

Cold allodynia is a common symptom of neuropathic and inflammatory pain following peripheral nerve injury. The mechanisms underlying this disabling sensory alteration are not entirely understood. In primary somatosensory neurons, cold sensitivity is mainly determined by a functional counterbalance between cold-activated TRPM8 channels and Shaker-like Kv1.1-1.2 channels underlying the excitability brake current IKD Here we studied the role of IKD in damage-triggered painful hypersensitivity to innocuous cold. We found that cold allodynia induced by chronic constriction injury (CCI) of the sciatic nerve in mice, was related to both an increase in the proportion of cold-sensitive neurons (CSNs) in DRGs contributing to the sciatic nerve, and a decrease in their cold temperature threshold. IKD density was reduced in high-threshold CSNs from CCI mice compared with sham animals, with no differences in cold-induced TRPM8-dependent current density. The electrophysiological properties and neurochemical profile of CSNs revealed an increase of nociceptive-like phenotype among neurons from CCI animals compared with sham mice. These results were validated using a mathematical model of CSNs, including IKD and TRPM8, showing that a reduction in IKD current density shifts the thermal threshold to higher temperatures and that the reduction of this current induces cold sensitivity in former cold-insensitive neurons expressing low levels of TRPM8-like current. Together, our results suggest that cold allodynia is largely due to a functional downregulation of IKD in both high-threshold CSNs and in a subpopulation of polymodal nociceptors expressing TRPM8, providing a general molecular and neural mechanism for this sensory alteration.SIGNIFICANCE STATEMENT This paper unveils the critical role of the brake potassium current IKD in damage-triggered cold allodynia. Using a well-known form of nerve injury and combining behavioral analysis, calcium imaging, patch clamping, and pharmacological tools, validated by mathematical modeling, we determined that the functional expression of IKD is reduced in sensory neurons in response to peripheral nerve damage. This downregulation not only enhances cold sensitivity of high-threshold cold thermoreceptors signaling cold discomfort, but it also transforms a subpopulation of polymodal nociceptors signaling pain into neurons activated by mild temperature drops. Our results suggest that cold allodynia is linked to a reduction of IKD in both high-threshold cold thermoreceptors and nociceptors expressing TRPM8, providing a general model for this form of cold-induced pain.

An integrate-and-fire model to generate spike trains with long-range dependence.

Long-range dependence (LRD) has been observed in a variety of phenomena in nature, and for several years also in the spiking activity of neurons. Often, this is interpreted as originating from a non-Markovian system. Here we show that a purely Markovian integrate-and-fire (IF) model, with a noisy slow adaptation term, can generate interspike intervals (ISIs) that appear as having LRD. However a proper analysis shows that this is not the case asymptotically. For comparison, we also consider a new model of individual IF neuron with fractional (non-Markovian) noise. The correlations of its spike trains are studied and proven to have LRD, unlike classical IF models. On the other hand, to correctly measure long-range dependence, it is usually necessary to know if the data are stationary. Thus, a methodology to evaluate stationarity of the ISIs is presented and applied to the various IF models. We explain that Markovian IF models may seem to have LRD because of non-stationarities.

Chaos versus noise as drivers of multistability in neural networks.

The multistable behavior of neural networks is actively being studied as a landmark of ongoing cerebral activity, reported in both functional Magnetic Resonance Imaging (fMRI) and electro- or magnetoencephalography recordings. This consists of a continuous jumping between different partially synchronized states in the absence of external stimuli. It is thought to be an important mechanism for dealing with sensory novelty and to allow for efficient coding of information in an ever-changing surrounding environment. Many advances have been made to understand how network topology, connection delays, and noise can contribute to building this dynamic. Little or no attention, however, has been paid to the difference between local chaotic and stochastic influences on the switching between different network states. Using a conductance-based neural model that can have chaotic dynamics, we showed that a network can show multistable dynamics in a certain range of global connectivity strength and under deterministic conditions. In the present work, we characterize the multistable dynamics when the networks are, in addition to chaotic, subject to ion channel stochasticity in the form of multiplicative (channel) or additive (current) noise. We calculate the Functional Connectivity Dynamics matrix by comparing the Functional Connectivity (FC) matrices that describe the pair-wise phase synchronization in a moving window fashion and performing clustering of FCs. Moderate noise can enhance the multistable behavior that is evoked by chaos, resulting in more heterogeneous synchronization patterns, while more intense noise abolishes multistability. In networks composed of nonchaotic nodes, some noise can induce multistability in an otherwise synchronized, nonchaotic network. Finally, we found the same results regardless of the multiplicative or additive nature of noise.

IKD Current in Cold Transduction and Damage-Triggered Cold Hypersensitivity.

In primary sensory neurons of the spinal and trigeminal somatosensory system, cold-sensitivity is strongly dependent on the functional balance between TRPM8 channels, the main molecular entity responsible for the cold-activated excitatory current, and Shaker-like Kv1.1-1.2 potassium channels, the molecular counterpart underlying the excitability brake current IKD. This slow-inactivating outward K+ current reduces the excitability of cold thermoreceptor neurons increasing their thermal threshold, and prevents unspecific activation by cold of neurons of other somatosensory modalities. Here we examine the main biophysical properties of this current in primary sensory neurons, its central role in cold thermotransduction, and its contribution to alterations in cold sensitivity triggered by peripheral nerve damage.

Modeling neural activity with cumulative damage distributions.

Neurons transmit information as action potentials or spikes. Due to the inherent randomness of the inter-spike intervals (ISIs), probabilistic models are often used for their description. Cumulative damage (CD) distributions are a family of probabilistic models that has been widely considered for describing time-related cumulative processes. This family allows us to consider certain deterministic principles for modeling ISIs from a probabilistic viewpoint and to link its parameters to values with biological interpretation. The CD family includes the Birnbaum-Saunders and inverse Gaussian distributions, which possess distinctive properties and theoretical arguments useful for ISI description. We expand the use of CD distributions to the modeling of neural spiking behavior, mainly by testing the suitability of the Birnbaum-Saunders distribution, which has not been studied in the setting of neural activity. We validate this expansion with original experimental and simulated electrophysiological data.

Elevating understanding: Linking high-altitude hypoxia to brain aging through EEG functional connectivity and spectral analyses.

High-altitude hypoxia triggers brain function changes reminiscent of those in healthy aging and Alzheimer's disease, compromising cognition and executive functions. Our study sought to validate high-altitude hypoxia as a model for assessing brain activity disruptions akin to aging. We collected EEG data from 16 healthy volunteers during acute high-altitude hypoxia (at 4,000 masl) and at sea level, focusing on relative changes in power and aperiodic slope of the EEG spectrum due to hypoxia. Additionally, we examined functional connectivity using wPLI, and functional segregation and integration using graph theory tools. High altitude led to slower brain oscillations, that is, increased δ and reduced α power, and flattened the 1/f aperiodic slope, indicating higher electrophysiological noise, akin to healthy aging. Notably, functional integration strengthened in the θ band, exhibiting unique topographical patterns at the subnetwork level, including increased frontocentral and reduced occipitoparietal integration. Moreover, we discovered significant correlations between subjects' age, 1/f slope, θ band integration, and observed robust effects of hypoxia after adjusting for age. Our findings shed light on how reduced oxygen levels at high altitudes influence brain activity patterns resembling those in neurodegenerative disorders and aging, making high-altitude hypoxia a promising model for comprehending the brain in health and disease.

Exposure to high-altitude hypoxia, with reduced oxygen levels, can replicate brain function changes akin to aging and Alzheimer's disease. In our work, we propose high-altitude hypoxia as a possible reversible model of human brain aging. We gathered EEG data at high altitude and sea level, investigating the impact of hypoxia on brainwave patterns and connectivity. Our findings revealed that high-altitude exposure led to slower and noisier brain oscillations and produced altered brain connectivity, resembling some remarkable changes seen in the aging process. Intriguingly, these changes were linked to age, even when hypoxia's effects were considered. Our research unveils how high-altitude conditions emulate brain patterns associated with aging and neurodegenerative conditions, providing valuable insights into the understanding of both normal and impaired brain function.