bioRxiv Subject Collection: Neuroscience's Journal

Noise-induced hearing loss enhances Ca2+-dependent spontaneous bursting activity in lateralcochlear efferents
Exposure to loud and/or prolonged noise damages cochlear hair cells and triggers downstream changes in synaptic and electrical activity in multiple brain regions, resulting in hearing loss and altered speech comprehension. It remains unclear however whether or not noise exposure also compromises the cochlear efferent system, a feedback pathway in the brain that fine-tunes hearing sensitivity in the cochlea. We examined the effects of noise-induced hearing loss on the spontaneous action potential (AP) firing pattern in mouse lateral olivocochlear (LOC) neurons. This spontaneous firing exhibits a characteristic burst pattern dependent on Ca2+ channels, and we therefore also examined the effects of noise-induced hearing loss on the function of these and other ion channels. The burst pattern was sustained by an interaction between inactivating Ca2+ currents contributed largely by L-type channels, and steady outward currents mediated by Ba2+-sensitive inwardly-rectifying and two-pore domain K+ channels. One week following exposure to loud broadband noise, hearing thresholds were significantly elevated, and the duration of AP bursts was increased, likely as a result of an enhanced Ca2+ current. Additional effects of noise-induced hearing loss included alteration of Ca2+-dependent inactivation of Ca2+ currents and a small elevation of outward K+ currents. We propose that noise-induced hearing loss enhances efferent activity and may thus amplify the release of neurotransmitters and neuromodulators (i.e., neuropeptides), potentially altering sensory coding within the damaged cochlea.

Significance StatementAlthough the effects of noise-induced hearing loss on the auditory afferent system have been extensively studied, little is known about its impact on the auditory efferent system, which modulates hearing sensitivity via feedback from the brain. Additionally, while Ca2+ channels are related to numerous neurological diseases, their involvement in auditory disorders is underexplored. This study bridges these gaps by examining Ca2+ channel-driven spontaneous burst firing in lateral olivocochlear (LOC) neurons, the most numerous auditory efferent neurons. Noise-induced hearing loss differentially affects Ca2+ channel subtypes by increasing high-voltage activated currents that further prolong burst firing and suggesting altered intracellular Ca2+ signaling. These significant changes in LOC firing behavior may profoundly impact their downstream targets in the cochlea.

Physiologically-relevant light exposure and light behaviour in Switzerland and Malaysia
Light synchronises the internal clock with the external light-dark cycle. Keeping this alignment benefits health and prevents diseases. Quantifying light exposure is, therefore, vital for effective prevention. Since light exposure depends on photoperiod, culture, and behaviour, we investigated objective light exposure and individual light-related behaviour in Switzerland and Malaysia. In this observational field study, participants (N=39) wore a calibrated melanopic light logger at chest level for 30 consecutive days. At baseline and study end, the Pittsburgh Sleep Quality Index was assessed, and every 3 to 4 days, the Light Exposure Behaviour Assessment (LEBA) was filled. Our pre-registered analyses reveal that participants in Switzerland experienced brighter days (+3.16 times the average mEDI) and spent more time (x1.9 times the duration) in daylight levels per hour of daylight, had [~]1.5h later bright light exposure in the afternoon, and stayed over 1h longer in dim light conditions before bedtime. LEBA scores did not differ between Malaysia and Switzerland, and LEBA items were stable over time. LEBA items also correlated with objective light exposure variables in Switzerland but not Malaysia, with a medium effect size (range of absolute r=0.32-0.48). These results highlight cultural and geographical differences in light exposure. We showed that LEBA can be related to actual light exposure and is ecologically informative, but this varies by culture.

The spinal premotor network driving scratching flexor and extensor alternation
Rhythmic motor behaviors are generated by neural networks termed central pattern generators (CPGs). Although locomotor CPGs have been extensively characterized, it remains unknown how the neuronal populations composing them interact to generate adaptive rhythms. We explored the non-linear cooperation dynamics among the three main populations of ipsilaterally projecting spinal CPG neurons - V1, V2a, V2b neurons - in scratch reflex rhythmogenesis. Ablation of all three neuronal subtypes reduced the oscillation frequency. Activation of excitatory V2a neurons enhanced the oscillation frequency, while activating inhibitory V1 neurons caused atonia. These findings required the development of a novel neuromechanical model that consists of flexor and extensor modules coupled via inhibition, in which rhythm in each module is generated by self-bursting excitatory populations and accelerated by intra-module inhibition. Inter-module inhibition coordinates the phases of flexor and extensor activity and slows the oscillations, while facilitation mechanisms in excitatory neurons explain the V2a activation-driven increase in frequency.

Single-cell sequencing reveals psilocybin induces sustained cell-type specific plasticity in mouse medial prefrontal cortex
The ever-increasing burden of psychiatric disorders and limitations of current treatments have fueled enormous interest in the therapeutic potential of psychedelics. Yet how psychedelics, such as psilocybin, produce lasting therapeutic effects is unclear. Using scRNA-sequencing we identify a type of deep layer near projecting neuron that is most robustly regulated in the medial prefrontal cortex of female mice 24h after psilocybin. We show that this cell-type specificity does not align with 5-HT2A receptor expression but is consistent with the integrated signaling via cell-type specific 5-HT receptor co-expression patterns. Cell-cell communication reveals that psilocybin also broadly suppresses GABAergic inhibition. Ultimately, psilocybin induces plasticity-related genes in subsets of excitatory neurons suggesting that psilocybin induces sustained increases in neuroplasticity in the mouse mPFC. Our findings point to L5/6NP neurons as a key mediator of psilocybin neuroplastic effects.

Coordination of distinct sources of excitatory inputs enhances motion selectivity in the mouse visual thalamus
Multiple sources innervate the visual thalamus to influence image-forming vision prior to the cortex, yet it remains unclear how non-retinal and retinal input coordinate to shape thalamic visual selectivity. Using dual-color two-photon calcium imaging in the thalamus of awake mice, we observed similar coarse-scale retinotopic organization between axons of superior colliculus neurons and retinal ganglion cells, both providing strong converging excitatory input to thalamic neurons. At a fine scale of ~10 m, collicular boutons often shared visual feature preferences with nearby retinal boutons. Inhibiting collicular input significantly suppressed visual responses in thalamic neurons and specifically reduced motion selectivity in neurons preferring nasal-to-temporal motion. The reduction in motion selectivity could be the result of silencing sharply tuned direction-selective colliculogeniculate input. These findings suggest that the thalamus is not merely a relay but selectively integrates inputs from multiple regions to build stimulus selectivity and shape the information transmitted to the cortex.

Higher-order EEG microstate syntax and surrogate testing
Higher-order syntax properties of EEG microstate sequences offer insight into the transition dynamics of functional brain networks. We here define higher-order syntax as microstate sequence properties that are not explained by the first-order transition matrix, and we postulate three requirements that surrogate data should fulfill to provide a null hypothesis for higher-order syntax tests. We then compare two general approaches to surrogate data generation that have been used in microstate research, (a) surrogates from a first-order Markov chain model, and, (b) surrogates obtained from sequence shuffling. There are two different ways of representing microstate sequences, and syntax analyses can be applied to both, continuous microstate sequences, where each time sample is assigned the nearest microstate cluster, or to jump sequences which record only non-identical transitions by removing adjacent duplicates. We show that jump sequences have at least first-order syntax properties, whereas continuous sequences allow for zero-order and first-order surrogates. Markov chain generated surrogates fulfill the three requirements, i.e. they preserve the microstate distribution and transition matrix, and have no higher-order properties. Jump sequence shuffling, on the other hand, yields first-order surrogates whose first-order parameters are markedly different from the original sequence. Using a large open-access resting-state EEG dataset we show that jump sequence shuffling almost certainly produces microstate word probabilities that are significantly different from first-order expected word frequencies, erroneously indicating higher-order syntax properties. Markov chain surrogates reproduce the expected word probabilities of first-order sequences and correctly reject higher-order syntax properties in these cases. We conclude that jump sequence shuffling does not produce adequate surrogates for higher-order syntax investigations. The proposed Markov chain generative method for surrogate data synthesis is computationally efficient and allows the generation of surrogate sequences of arbitrary length, whereas shuffling can lead to sequences that are shorter than the original sequence and have variable length. Sample code in Python and MATLAB is provided.

Ensemble priming via competitive inhibition: local mechanisms of sensory context storage and deviance detection in the neocortical column
The process by which neocortical neurons and circuits amplify their response to an unexpected change in stimulus, often referred to as deviance detection (DD), has long been thought to be the product of specialized cell types and/or routing between mesoscopic brain areas. Here, we explore a different theory, whereby DD emerges from local network-level interactions within a neocortical column. We propose that deviance-driven neural dynamics can emerge through interactions between ensembles of neurons that have a fundamental inhibitory motif: competitive inhibition between reciprocally connected ensembles under modulation from feed-forward selective (dis)inhibition. Using this framework, we were able to simulate a variety of phenomena pertaining to the experimentally observed shifts in neural tuning across neurons, time, and stimulus history. Anchoring our approach in a variety of experimentally observed phenomena, we used computation modeling in two types of neural networks of vastly different levels of biophysical detail to test hypotheses on emergent dynamics and explore the robustness of underlying connectivity parameters. With a number of corollary predictions that can be tested in future in vivo studies, we show that ensemble priming via competitive inhibition under modulation from selective (dis)inhibition acts as a local mechanism for sensory context storage and that DD does not require specialized input from other brain areas--a novel theoretical paradigm that resolves previously confounding aspects of sensory encoding and predictive processing in the neocortex.

Learning-induced plasticity decreases cortical engram cell dendritic excitability during memory recall
The ability to associate stimuli to create a memory is one of the most fundamental functions of the brain. Research from the past decade has revealed that memory is encoded in sparse neuronal networks active during learning called engram cells. Although the cortex is recognized as playing an important role in memory, the biophysical properties of cortical engram cells are largely unknown. To address this, we tagged engram cells in the auditory cortex during tone fear conditioning and compared their dendritic and somatic properties with neighbouring non-engram cells. Using two-photon calcium imaging, we show that tuft dendrites of engram cells had dampened, but synchronous, activity during recall. Ex vivo patch-clamp recordings illustrated that engram cells were preferentially connected with neighbouring engram cells and had decreased excitability due to a transient increase in Ih current. Together, these findings reveal Ih-driven intrinsic plasticity which leads to specific information processing in engram cells.

Distinct roles of cortical layer 5 subtypes in associative learning
Adaptive behavior is critically dependent on associative learning, where environmental cues are linked with subsequent positive or negative outcomes. In mammals, primary neocortical sensory areas serve as pivotal nodes in this process, processing stimuli and distributing information to cortical and subcortical networks. Layer 5 (L5) of the cortex comprises two types of pyramidal projection neurons--intratelencephalic (IT) and extratelencephalic (ET) neurons--each with distinct downstream targets. Despite the crucial function of L5 as a main output node of the cortex, the specific contributions of these L5 neuronal subtypes to associative learning remain poorly understood. In the present study, by leveraging transgenic mouse lines, we distinguished IT and ET neurons in the primary somatosensory cortex and examined their roles in a whisker-based frequency-discrimination learning task. Longitudinal two-photon calcium imaging revealed distinct response characteristics between IT and ET neurons throughout learning. Interestingly, the activity of IT neurons hardly changed over the five days of learning, while the activity of ET neurons developed robustly. Furthermore, IT neurons appeared to show stimuli encoding from the beginning, whereas the ET neurons became increasingly responsive to stimuli associated with reward. Chemogenetic silencing of either IT or ET neurons both impaired learning, but in strikingly distinct ways, each associated with a different phase of learning. By modeling the response characteristics of IT and ET neurons using a reinforcement learning framework, we show that IT neurons primarily encode sensory stimuli, and their representations are critical for forming stimulus-reward associations. ET neurons instead represent the value of the stimulus, used for refining behavior. Thus, our results delineate the distinct roles of L5 IT and ET neurons, underscoring their integral and complementary contributions to associative learning.

Resting State connectivity patterns associated with trait anxiety in adolescence
Anxiety symptoms can vary across different life stages, with a higher frequency during adolescence and early adulthood, increasing the risk of developing future anxiety disorders. To date, neuroscientific research on anxiety has primarily focused on adulthood, thus limiting our understanding of how anxiety may characterize earlier stages of life, and employing mostly univariate approaches, thus discounting large-scale alterations of the brain. One intriguing hypothesis is that adolescents with trait anxiety may display similar abnormalities shown by adults in brain regions ascribed to the Default Mode Network (DMN) associated with self-referential thinking, awareness, and rumination-related processes. The present study aims to expand our previous knowledge on this topic using a large sample of young individuals to uncover the resting-state connectivity patterns associated with trait anxiety in a network approach. To test our hypotheses, we analyzed the rs-fMRI images of 1263 adolescents (mean age 20.55 years) as well as their scores on anxiety trait. A significant association between trait anxiety and resting-state functional connectivity in two networks was found, with some regions overlapping with the Default Mode Network. The first network included regions such as the cingulate gyrus and the middle temporal gyri known to be involved in self-referential processing and emotional perception and control, both altered in anxiety disorders. The second network included the precuneus, possibly related to rumination that characterizes anxiety. Of note, the higher the trait anxiety, the lower the connectivity within both networks, suggesting abnormal self-referential processing, awareness, and emotion regulation abilities in adolescents with high anxiety trait. These findings provided a better understanding of the association between trait anxiety and brain rs-functional connectivity, and may pave the way for the development of potential biomarkers in adolescents with anxiety.

Activity dependent Clustering of Neuronal L-Type Calcium Channels by CaMKII
Neuronal excitation-transcription (E-T) coupling pathways can be initiated by local increases of Ca2+ concentrations within a nanodomain close to the L-type voltage-gated Ca2+ channel (LTCC). However, molecular mechanisms controlling LTCC organization within the plasma membrane that help creation these localized signaling domains remain poorly characterized. Here, we report that neuronal depolarization increases CaV1.3 LTCC clustering in cultured hippocampal neurons. Our previous work showed that binding of the activated catalytic domain of Ca2+/calmodulin-dependent protein kinase II (CaMKII) to an RKR motif in the N-terminal cytoplasmic domain of CaV1.3 is required for LTCC-mediated E-T coupling. We tested whether multimeric CaMKII holoenzymes can bind simultaneously to co-expressed CaV1.3 1 subunits with two different epitope tags. Co-immunoprecipitation assays from HEK293T cell lysates revealed that CaMKII assembles multimeric CaV1.3 LTCC complexes in a Ca2+/calmodulin-dependent manner. CaMKII-dependent assembly of multi-CaV1.3 complexes is further facilitated by co-expression of the CaMKII-binding LTCC {beta}2a subunit, relative to the {beta}3 subunit, which cannot bind directly to CaMKII. Moreover, clustering of surface localized CaV1.3 1 subunits in intact HEK293 cells was increased by pharmacological LTCC activation, but only in the presence of co-expressed wild-type CaMKII. Moreover, depolarization-induced clustering of surface-expressed CaV1.3 LTCCs in cultured hippocampal neurons was disrupted by suppressing the expression of CaMKII and CaMKII{beta} using shRNAs. The CaMKII-binding RKR motif is conserved in the N-terminal domain of CaV1.2 1 subunits and we found that activated CaMKII promoted the assembly of CaV1.2 homomeric complexes, as well as CaV1.3-CaV1.2 heteromeric complexes in vitro. Furthermore, neuronal depolarization enhanced the clustering of surface-expressed CaV1.2 LTCCs, and enhanced the colocalization of endogenous CaV1.2 LTCCs with surface-expressed CaV1.3, by CaMKII-dependent mechanisms. This work indicates that CaMKII activation-dependent LTCC clustering in the plasma membrane following neuronal depolarization may be essential for the initiation of a specific long-range signal to activate gene expression.

Unlocking information alignment between interacting brains with EEG hyperscanning
Social interactions shape our perception of the world as the people we interact with, and groups we belong to, influence how we interpret incoming information. Alignment between interacting individuals sensory and cognitive processes plays a critical role in facilitating cooperation and communication in everyday joint activities. However, despite recent advances in hyperscanning techniques to measure the brain activity of multiple people simultaneously, the neural processes underlying this alignment remain unknown. Here, we leveraged Representational Similarity Analysis (RSA) with electroencephalography (EEG) hyperscanning data to measure neural representations and uncover the emergence of information alignment between interacting individuals brains during joint visual categorisation. We recorded EEG from 24 pairs of participants sitting back-to-back while they performed a 4-way categorisation task based on rules they first agreed upon together. The results revealed significant interbrain information alignment as early as 45 ms after stimulus presentation, lasting over hundreds of milliseconds. Importantly, early alignment between brains arose between 45 and 180 ms regardless of whether participants performed the task together or were randomly matched up a posteriori to form pseudo pairs, whereas alignment after 200 ms was only present for real pairs who previously formed the categories together. This result distinguishes alignment that was socially induced by pre-agreed and shared interpretation of the stimuli from alignment that was purely evoked by shared sensory responses due to participants seeing the same visual input. In addition, our results showed that socially induced alignment was an active and dynamic process, which strengthened over time with practice and reinforcement of shared agreements, but appeared to remain largely task specific with no transfer during passive viewing of the same stimuli. Together, these findings highlight distinct sensory evoked and socially induced processes underpinning human perception and interbrain information alignment during social interactions that can be effectively captured and disentangled with Interbrain RSA.

Temporal recurrence as a general mechanism toexplain neural responses in the auditory system
Computational models of neural processing in the auditory cortex usually ignore that neurons have an internal memory: they characterize their responses from simple convolutions with a finite temporal window of arbitrary duration. To circumvent this limitation, we propose here a new, simple and fully recurrent neural network (RNN) architecture incorporating cutting-edge computational blocks from the deep learning community and constituting the first attempt to model auditory responses with deep RNNs. We evaluated the ability of this approach to fit neural responses from 8 publicly available datasets, spanning 3 animal species and 6 auditory brain areas, representing the largest compilation of this kind. Our recurrent models significantly outperform previous methods and a new Transformerbased architecture of our design on this task, suggesting that temporal recurrence is the key to explain auditory responses. Finally, we developed a novel interpretation technique to reverse-engineer any pretrained model, regardless of their stateful or stateless nature. Largely inspired by works from explainable artificial intelligence (xAI), our method suggests that auditory neurons have much longer memory (several seconds) than indicated by current STRF techniques. Together, these results highly motivate the use of deep RNNs within computational models of sensory neurons, as protean building blocks capable of assuming any function.

Two independent translocation modes drive neural stem cell dissemination into the human fetal cortex
The strong size increase of the human neocortex is supported both by the amplification and the basal translocation of a neural stem cell population, the basal radial glial cells (or bRG cells). Using live imaging of second trimester human fetal tissue and cortical organoids, we identify two independent translocation modes for bRG cell colonization of the human neocortex. On top of an actomyosin-dependent movement called mitotic somal translocation (MST), we identify a microtubule-dependent motion occurring during interphase, that we call interphasic somal translocation (IST). We show that IST is driven by the LINC complex, through the nuclear envelope recruitment of the dynein motor and of its activator LIS1. Consequently, IST severely altered in LIS1 patient-derived cortical organoids. We also demonstrate that MST occurs during prometaphase and is a mitotic spindle translocation event. MST is controlled by the mitotic cell rounding molecular pathway, via Moesin and Vimentin, driving translocation. We report that 85% of bRG cell translocation is due to IST, for a total movement of 0,67 mm per month of human fetal gestation. Our work identifies how bRG cells colonize the human fetal cortex, and further shows that IST and MST are conserved in bRG-related migrating glioblastoma cells.

Human hippocampal ripples predict the alignment of experience to a grid-like schema
Humans create internal cognitive maps that allow us to make inferences beyond direct experience. These maps often rely on hexagonal grid-cell-like neural codes, serving as a schema for two-dimensional (2D) spaces. Yet it remains unclear how new experiences become aligned with this schema, especially in non-spatial contexts. Here, we show that hippocampal ripples - brief bursts of neuronal activity during rest - predict the emergence of grid-like codes in a novel 2D inference task. We recorded intracranial neuronal activity in 42 epilepsy patients as they learned rank relationships among feature objects (for example, objects differing in "magic" or "speed"). After learning, these objects were combined to form "compounds" occupying a 2D conceptual space defined by two feature dimensions. During learning, hippocampal ripple activity increased during pauses between trials, suggesting that ripples integrated newly acquired information offline. Subsequently, ripple activity during post-learning rest predicted the later emergence of grid-like codes in the entorhinal cortex (EC) and medial prefrontal cortex (mPFC), a core region of the default mode network (DMN), when participants inferred unseen relationships among the compounds. Critically, coordination during rest between hippocampal ripples and DMN activity in the mPFC predicted participants ability to infer complex relationships beyond direct memory retrieval. These findings provide the first direct evidence that hippocampal ripples, working with the DMN, align new experiences with a grid-like schema offline, transforming discrete learning events into structured knowledge that supports flexible and adaptive reasoning in human cognition.

Physiological and molecular impairment of PV circuit homeostasis in mouse models of autism
Circuit dysfunction in autism may involve a failure of homeostatic plasticity. To test this, we studied parvalbumin (PV) interneurons which exhibit rapid homeostatic plasticity of intrinsic excitability following whisker deprivation in mouse somatosensory cortex. Brief deprivation reduces PV excitability by increasing Kv1 current to increase PV spike threshold. We found that PV homeostatic plasticity is disrupted in Tsc2+/- and Fmr1-/- models of autism. In wildtype mice, deprivation elevates the transcription factor ER81 which drives Kcna1 transcription, increasing Kv1.1 protein in the axon initial segment and soma. These molecular signatures of homeostasis were absent in Tsc2+/- and Fmr1-/-. Whisker enrichment increased PV excitability, but not in Tsc2+/-, indicating that homeostasis is lost bidirectionally. Deprivation reduced feedforward L4-L2/3 inhibition in wildtype but not Tsc2+/- mice. Thus, two autism models show a convergent loss of PV circuit homeostasis at physiological and molecular levels, potentially contributing to sensory processing impairments.

Hippocampal-cortical connectivity relates to inter-individual differences and training gains in distinguishing similar memories
Mnemonic discrimination (MD) is the ability to distinguish current experiences from similar memories. Research on the brain correlates of MD has focused on how regional neural responses are linked to MD. Here we go beyond this approach to investigate inter-regional functional connectivity patterns related to MD, its inter-individual variability and training-related improvement. Based on prior work we focused on medial temporal lobe (MTL), prefrontal cortex (PFC) and visual regions. We used fMRI to determine how functional connectivity patterns between these regions are related to MD before and after 2-weeks of web-based cognitive training. We found that hippocampal-PFC connectivity was negatively associated with interindividual variability in MD performance across two different tasks. Hippocampal-PFC connectivity decrease was also linked to interindividual variability in post-training MD improvement. Additionally, training led to increased connectivity from the lateral occipital cortex to the occipital pole area. Our results point to a hippocampal-PFC connectivity pattern which is a reliable, task-invariant, marker of MD performance. This pattern is further related to MD training gains providing causal evidence for its relevance in distinguishing similar memories. Overall, we show that hippocampal-PFC connectivity constitutes a neural resource for MD that enables training-related improvements and could be targeted in future research to enhance cognition.

Spherical code of retinal orientation-selectivity enables decoding in ensembled and retinotopic operation
Selectivity to orientations of edges is seen at the earliest stages of visual processing, in retinal orientation-selective ganglion cells (OSGCs), thought to prefer vertical or horizontal orientation. However, as stationary edges are projected on the hemispherical retina as lines of longitude or latitude, how edge orientation is encoded, and decoded by the brain, is unknown. Here, by mapping the OS of thousands of OSGCs at known retinal locations in mice, we identified three OSGC types whose preferences match two longitudinal fields, and a fourth type matching two latitudinal fields, the members of each field-pair being non-orthogonal. A geometric decoder revealed that two OS sensors yield optimal orientation decoding when approaching the deviation from orthogonality we observed for OSGC field-pairs. Retinotopically-organized decoding generated type-specific variation in decoding efficiency across the visual field. OS tuning was greater in the dorsal retina, possibly reflecting an evolutionary adaptation to an environmental gradient of edges.