bioRxiv Subject Collection: Neuroscience's Journal

Strain concentration drives the anatomical distribution of injury in acute and chronic traumatic brain injury
Brain tissue injury caused by mild traumatic brain injury (mTBI) disproportionately concentrates in the midbrain, cerebellum, mesial temporal lobe, and the interface between cortex and white matter at sulcal depths. The bio-mechanical principles that explain why physical impacts to different parts of the skull translate to common foci of injury concentrated in specific brain structures are unknown. A general and longstanding idea, which has not to date been directly tested in humans, is that different brain regions are differentially susceptible to strain loading. We use Magnetic Resonance Elastography (MRE) in healthy participants to develop whole-brain bio-mechanical vulnerability maps that independently define which regions of the brain exhibit disproportionate strain concentration. We then validate those vulnerability maps in a prospective cohort of mTBI patients, using diffusion MRI data collected at three cross-sectional timepoints after injury: acute, sub-acute, chronic. We show that regions that exhibit high strain, measured with MRE, are also the sites of greatest injury, as measured with diffusion MR in mTBI patients. This was the case in acute, subacute, and chronic subgroups of the mTBI cohort. Follow-on analyses decomposed the biomechanical cause of increased strain by showing it is caused jointly by disproportionately higher levels of energy arriving to high-strain structures, as well as the inability of high-strain structures to effectively disperse that energy. These findings establish a causal mechanism that explains the anatomy of injury in mTBI based on in vivo rheological properties of the human brain.

Distinct release properties of glutamate/GABA co-transmission serve as a frequency-dependent filtering of supramammillary inputs
Glutamate and GABA co-transmitting neurons exist in several brain regions; however, the mechanism by which these two neurotransmitters are co-released from the same synaptic terminals remains unclear. Here, we show that the supramammillary nucleus (SuM) to dentate granule cell synapses, which co-release glutamate and GABA, exhibit differences between glutamate and GABA release properties in paired-pulse ratio, Ca2+-sensitivity, presynaptic receptor modulation, and Ca2+ channel-vesicle coupling configuration. Moreover, uniquantal synaptic responses show independent glutamatergic and GABAergic responses. Morphological analysis reveals that most SuM boutons form distinct glutamatergic and GABAergic synapses in proximity, each characterized by GluN1 and GABAA1 labeling, respectively. Notably, glutamate/GABA co-transmission exhibits distinct short-term plasticities, with frequency-dependent depression of glutamate and frequency-independent stable depression of GABA. Our findings suggest that glutamate and GABA are co-released from different synaptic vesicles within the SuM terminals, and reveal that distinct transmission modes of glutamate/GABA co-release serve as frequency-dependent filters of SuM inputs.

Dynamics of attentional re-orienting in visual working memory following expected and unexpected memory tests
Attentional orienting in world and mind enables prioritization of sensorial and mnemonic information that we anticipate to become relevant, but events may also prompt re-orienting of attention. While attentional re-orienting is well characterized for external attention, whether and how humans re-orient their attention in mind following expected and unexpected working-memory tests remains elusive. Here, we developed a visual working-memory task in which we varied the reliability of retrocues such that ensuing memory tests called upon memory content that was certain, expected, or unexpected to be tested. We leveraged spatial modulations in EEG-alpha activity and eye-movements to track orienting and re-orienting within the spatial layout of visual working memory following central retrocues and memory tests. Both markers reliably tracked orienting of attention following retrocues and scaled with cue reliability. In addition, we unveil a second stage of attentional deployment following memory tests. When tests were expected (but not certain), attentional deployment was not contingent on prior orienting, suggesting an additional verification (double checking) in memory. When memory tests were unexpected, re-focusing of alternative memory content was prolonged. These findings bring attentional re-orienting to the domain of working memory and underscore the relevance of studying attentional dynamics in memory not only following cues, but also following ensuing memory tests that can invoke a revision or verification of our internal focus.

Norepinephrine changes behavioral state via astroglial purinergic signaling
Both neurons and glia communicate via diffusible neuromodulatory substances, but the substrates of computation in such neuromodulatory networks are unclear. During behavioral transitions in the larval zebrafish, the neuromodulator norepinephrine drives fast excitation and delayed inhibition of behavior and circuit activity. We find that the inhibitory arm of this feedforward motif is implemented by astroglial purinergic signaling. Neuromodulator imaging, behavioral pharmacology, and perturbations of neurons and astroglia reveal that norepinephrine triggers astroglial release of adenosine triphosphate, extracellular conversion into adenosine, and behavioral suppression through activation of hindbrain neuronal adenosine receptors. This work, along with a companion piece by Lefton and colleagues demonstrating an analogous pathway mediating the effect of norepinephrine on synaptic connectivity in mice, identifies a computational and behavioral role for an evolutionarily conserved astroglial purinergic signaling axis in norepinephrine-mediated behavioral and brain state transitions.

Quantifying Population-level Neural Tuning Functions Using Ricker Wavelets and the Bayesian Bootstrap
Experience changes the tuning of sensory neurons, including neurons in retinotopic visual cortex, as evident from work in humans and non-human animals. In human observers, visuo-cortical re-tuning has been studied during aversive generalization learning paradigms, in which the similarity of generalization stimuli (GSs) with a conditioned threat cue (CS+) is used to quantify tuning functions. This work utilized pre-defined tuning shapes reflecting prototypical generalization (Gaussian) and sharpening (Difference-of-Gaussians) patterns. This approach may constrain the ways in which re-tuning can be characterized, for example if tuning patterns do not match the prototypical functions or represent a mixture of functions. The present study proposes a flexible and data-driven method for precisely quantifying changes in neural tuning based on the Ricker wavelet function and the Bayesian bootstrap. The method is illustrated using data from a study in which university students (n = 31) performed an aversive generalization learning task. Oriented gray-scale gratings served as CS+ and GSs and a white noise served as the unconditioned stimulus (US). Acquisition and extinction of the aversive contingencies were examined, while steady-state visual event potentials (ssVEP) and alpha-band (8-13 Hz) power were measured from scalp EEG. Results showed that the Ricker wavelet model fitted the ssVEP and alpha-band data well. The pattern of re-tuning in ssVEP amplitude across the stimulus gradient resembled a generalization (Gaussian) shape in acquisition and a sharpening (Difference-of-Gaussian) shape in an extinction phase. As expected, the pattern of re-tuning in alpha-power took the form of a generalization shape in both phases. The Ricker-based approach led to greater Bayes factors and more interpretable results compared to prototypical tuning models. The results highlight the promise of the current method for capturing the precise nature of visuo-cortical tuning functions, unconstrained by the exact implementation of prototypical a-priori models.

Top-down and bottom-up interactions rely on nested brain oscillations.
Adaptive visual processing is enabled through the dynamic interplay between top-down and bottom-up (feedback/feedforward) information exchange, presumably propagated through brain oscillations. Here we causally tested for the oscillatory mechanisms governing this interaction in the visual system. Using concurrent TMS-EEG, we emulated top-down signals by a single TMS-pulse over the Frontal Eye Field (right-FEF), while manipulating the strength of sensory input through the presentation of moving concentric gratings (compared to a control-TMS site). FEF-TMS without sensory input led to a top-down controlled occipital phase-realignment, alongside higher fronto-occipital phase-connectivity, in the alpha/beta-band. Sensory input in the absence of FEF-TMS increased occipital gamma activity. Crucially, testing the interaction between top-down and bottom-up processes (FEF-TMS during sensory input) revealed an increased nesting of the bottom-up gamma activity in the alpha/beta-band cycles. This establishes a causal link between phase-to-power coupling and top-down modulation of feedforward signals, providing novel mechanistic insights into how attention interacts with sensory input at the neural level, shaping rhythmic sampling.

Continuous and discrete decoding of overt speech with electroencephalography
Neurological disorders affecting speech production adversely impact quality of life for over 7 million individuals in the US. Traditional speech interfaces like eyetracking devices and P300 spellers are slow and unnatural for these patients. An alternative solution, speech Brain-Computer Interfaces (BCIs), directly decodes speech characteristics, offering a more natural communication mechanism. This research explores the feasibility of decoding speech features using non-invasive EEG. Nine neurologically intact participants were equipped with a 63-channel EEG system with additional sensors to eliminate eye artifacts. Participants read aloud sentences displayed on a screen selected for phonetic similarity to the English language. Deep learning models, including Convolutional Neural Networks and Recurrent Neural Networks with/without attention modules, were optimized with a focus on minimizing trainable parameters and utilizing small input window sizes. These models were employed for discrete and continuous speech decoding tasks, achieving above-chance participant-independent decoding performance for discrete classes and continuous characteristics of the produced audio signal. A frequency sub-band analysis highlighted the significance of certain frequency bands (delta, theta, and gamma) for decoding performance, and a perturbation analysis identified crucial channels. Assessed channel selection methods did not significantly improve performance, but they still outperformed chance levels, suggesting a distributed representation of speech information encoded in the EEG signals. Leave-One-Out training demonstrated the feasibility of utilizing common speech neural correlates, reducing data collection requirements from individual participants.

Selective Functional Connectivity between Ocular Dominance Columns in the Primary Visual Cortex
The primary visual cortex (V1) in humans and many animals is comprised of fine-scale neuronal ensembles that respond preferentially to the stimulation of one eye over the other, also known as the ocular dominance columns (ODCs). Despite its importance in shaping our perception, to date, the nature of the functional interactions between ODCs has remained poorly understood. In this work, we aimed to improve our understanding of the interaction mechanisms between fine-scale neuronal structures distributed within V1. To that end, we applied high-resolution functional MRI to study mechanisms of functional connectivity between ODCs. Using this technique, we quantified the level of functional connectivity between ODCs as a function of the ocular preference of ODCs, showing that alike ODCs are functionally more connected compared to unalike ones. Through these experiments, we aspired to contribute to filling the gap in our knowledge of the functional connectivity of ODCs in humans as compared to animals.

Cortical tracking of speakers' formant changes predicts selective listening
A social scene is particularly informative when people are distinguishable. To understand somebody amid a 'cocktail party' chatter, we automatically index their voice. This ability is underpinned by parallel processing of vocal spectral contours from speech sounds, but it has not yet been established how this occurs in the brain's cortex. We investigate single-trial neural tracking of slow modulations in speech formants using electroencephalography. Participants briefly listened to unfamiliar single speakers, and in addition, they performed a cocktail party comprehension task. Quantified through stimulus reconstruction methods, robust tracking was found in neural responses to slow (delta-theta range) modulations of the fourth and fifth formant band contours equivalent to the 3.5-5 KHz audible range. Instantaneous inter-formant spacing (Delta-F), which also yields indexical information from the vocal tract, was similarly decodable. Moreover, EEG evidence of listeners' spectral tracking abilities predicted their chances of succeeding at selective listening when faced with two-speaker speech mixtures. In summary, the results indicate that the communicating brain can rely on locking of cortical rhythms to major changes led by upper resonances of the vocal tract. Their corresponding articulatory mechanics hence continuously issue a fundamental credential for listeners to target in real time.

Sex and the facilitation of cued fear by prior contextual fear conditioning in rats
Previous studies have shown that the formation of new memories can be influenced by prior experience. This includes work using pavlovian fear conditioning in rodents that have shown that an initial fear conditioning experience can become associated with and facilitate the acquisition of new fear memories, especially when they occur close together in time. However, most of the prior studies used only males as subjects resulting in questions about the generalizability of the findings from this work. Here we tested whether prior contextual fear conditioning would facilitate later learning of cued fear conditioning in both male and female rats, and if there were differences based on the interval between the two conditioning episodes. Our results showed that levels of cued fear were not influenced by prior contextual fear conditioning or by the interval between training, however, females showed lower levels of cued fear. Freezing behavior in the initial training context differed by sex, with females showing lower levels of contextual fear, and by the type of initial training, with rats given delayed shock showing higher levels of fear than rats given immediate shock during contextual fear conditioning. These results indicate that contextual fear conditioning does not prime subsequent cued fear conditioning and that female rats express lower levels of cued and contextual fear conditioning than males.

The Effects of Locus Coeruleus Optogenetic Stimulation on Global Spatiotemporal Patterns in Rats
Whole-brain intrinsic activity as detected by resting-state fMRI can be summarized by three primary spatiotemporal patterns. These patterns have been shown to change with different brain states, especially arousal. The noradrenergic locus coeruleus (LC) is a key node in arousal circuits and has extensive projections throughout the brain, giving it neuromodulatory influence over the coordinated activity of structurally separated regions. In this study, we used optogenetic-fMRI in rats to investigate the impact of LC stimulation on the global signal and three primary spatiotemporal patterns. We report small, spatially specific changes in global signal distribution as a result of tonic LC stimulation, as well as regional changes in spatiotemporal patterns of activity at 5 Hz tonic and 15 Hz phasic stimulation. We also found that LC stimulation had little to no effect on the spatiotemporal patterns detected by complex principal component analysis. These results show that the effects of LC activity on the BOLD signal in rats may be small and regionally concentrated, as opposed to widespread and globally acting.

Multifaceted confidence in exploratory choice
Our choices are typically accompanied by a feeling of confidence - an internal estimate that they are correct. Correctness, however, depends on our goals. For example, exploration-exploitation problems entail a tension between short- and long-term goals: finding out about the value of one option could mean foregoing another option that is apparently more rewarding. Here, we hypothesised that after making an exploratory choice that involves sacrificing an immediate gain, subjects will be confident that they chose a better option for long-term rewards, but not confident that it was a better option for immediate reward. We asked 250 subjects across 2 experiments to perform a varying-horizon two-arm bandits task, in which we asked them to rate their confidence that their choice would lead to more immediate, or more total reward. Confirming previous studies, we found a significant increase in exploration with increasing trial horizon, but, contrary to our predictions, we found no difference between confidence in immediate or total reward. This dissociation is further evidence for a separation in the mechanisms involved in choices and confidence judgements.

Meta-Control Demands Deactivate Cognitive-Control Regions
Control interventions (e.g., attention, inhibition) are well-known to activate frontoparietal regions and increase pupil size. Here, we characterize a different facet of cognitive-control that deactivates these very same regions and decreases pupil size. Control interventions always occur in the context of extended task episodes (e.g., block of trials). Since these extended episodes are controlled and executed as one entity, the various control interventions made across their duration are brought about via common goal-directed programs. These programs are instantiated at the beginning of the episode and are the means of organizing and controlling the numerous control interventions to be made across the task duration. These programs, therefore, are meta-control in function in that they control and organize the control interventions to be made across the task episode. Difficult episodes begin with the instantiation of more complex programs that will go on to bring about a more complex set of control interventions. Across four experiments, we show that while the instantiation of more complex control interventions during difficult task episodes expectedly activated control-related frontoparietal regions and increased pupil size, instantiation of more complex programs at the beginning of these episodes deactivated these very regions and decreased pupil size. Neural and psychophysiological signatures of the meta-control programs are thus categorically different from those of control interventions made through these programs.

Human neural dynamics of real-world and imagined navigation
The ability to form episodic memories and later imagine them is integral to the human experience, influencing our recollection of the past and our ability to envision the future. While research on spatial navigation in rodents suggests the involvement of the medial temporal lobe (MTL), especially the hippocampus, in these cognitive functions, it is uncertain if these insights apply to the human MTL, especially regarding imagination and the reliving of events. Importantly, by involving human participants, imaginations can be explicitly instructed and their mental experiences verbally reported. In this study, we investigated the role of hippocampal theta oscillations in both real-world and imagined navigation, leveraging motion capture and intracranial electroencephalographic recordings from individuals with chronically implanted MTL electrodes who could move freely. Our results revealed intermittent theta dynamics, particularly within the hippocampus, which encoded spatial geometry and partitioned navigational routes into linear segments during real-world navigation. During imagined navigation, theta dynamics exhibited similar, repetitive patterns despite the absence of external environmental cues. Furthermore, a computational model, generalizing from real-world to imagined navigation, successfully reconstructed participants' imagined positions using neural data. These findings offer unique insights into the neural mechanisms underlying human navigation and imagination, with implications for understanding episodic memory formation and retrieval in real-world settings.

The fingerprints of pupillary dynamics
The size of the pupils reflects directly the balance of different branches of the autonomic nervous system. This measure is inexpensive, non-invasive, and has provided invaluable insights on a wide range of mental processes, from attention to emotion and executive functions. Two outstanding limitations of current pupillometry research are the lack of consensus in the analytical approaches, which vary wildly across research groups, and the fact that, unlike other neuroimaging techniques, pupillometry lacks the dimensionality to shed light on the different sources of the observed effects. In other words, pupillometry provides an integrated readout of several distinct networks (Strauch et al., 2022), but it is unclear whether each has a specific fingerprint, stemming from its function or physiological substrate. Here we show that phasic changes in pupil size are inherently low-dimensional, with modes that are highly consistent across behavioral tasks of very different nature, suggesting that these changes occur along a pupillary manifold that is highly constrained by the underlying physiological structures. These results provide not only a unified approach to analyze pupillary data, for which we offer a toolbox, but also the opportunity to delve deeper into the sources of the reported changes in pupil size.

The individual determinants of morning dream recall
Evidence suggests that (almost) everyone dreams during their sleep and may actually do so for a large part of the night. Yet, dream recall shows large interindividual variability. Understanding the factors that influence dream recall is crucial for advancing our knowledge regarding dreams' origin, significance, and functions. Here, we tackled this issue by prospectively collecting dream reports along with demographic information and psychometric, cognitive, actigraphic, and electroencephalographic measures in 204 healthy adults (18-70 y, 113 females). We found that attitude towards dreaming, proneness to mind wandering, and sleep patterns are associated with the probability of reporting a dream upon morning awakening. The likelihood of recalling dream content was predicted by age and vulnerability to interference. Moreover, dream recall appeared to be influenced by night-by-night changes in sleep patterns and showed seasonal fluctuations. Our results provide an account for previous observations regarding inter- and intra-individual variability in morning dream recall.

A dorsal versus ventral network for understanding others in the developing brain
Young children strongly depend on others, and learning to understand their mental states (referred to as Theory of Mind, ToM) is a key challenge of early cognitive development. Traditionally, ToM is thought to emerge around the age of 4 years. Yet, in non-verbal tasks, preverbal infants already seem to consider others' mental states when predicting their actions. These early non-verbal capacities, however, seem fragile and distinct from later-developing verbal ToM. So far, little is known about the nature of these early capacities and the neural networks supporting them. To identify these networks, we investigated the maturation of nerve fiber connections associated with children's correct non-verbal action prediction and compared them with connections supporting verbal ToM reasoning in 3- to 4-year-old children, that is, before and after their breakthrough in verbal ToM. This revealed a ventral network for non-verbal action prediction versus a dorsal network for verbal ToM. Non-verbal capacities were associated with maturational indices in ventral fiber tracts connecting regions of the salience network, involved in bottom-up social attention processes. In contrast, verbal ToM performance correlated with maturational indices of the arcuate fascicle and cingulum, which dorsally connect regions of the default network, involved in higher-order social cognitive processes including ToM in adults. As non-verbal tasks were linked to connections of the salience network, young children may make use of salient perceptual social cues to predict others' actions, questioning theories of mature ToM before 4 years.

TRIM46 is not required for axon specification or axon initial segment formation in vivo
Vertebrate nervous systems use the axon initial segment (AIS) to initiate action potentials and maintain neuronal polarity. The microtubule-associated protein tripartite motif containing 46 (TRIM46) was reported to regulate axon specification, AIS assembly, and neuronal polarity through the bundling of microtubules in the proximal axon. However, these claims are based on TRIM46 knockdown in cultured neurons. To investigate TRIM46 function in vivo, we examined TRIM46 knockout mice. Contrary to previous reports, we find that TRIM46 is dispensable for AIS formation and maintenance, and axon specification. TRIM46 knockout mice are viable, have normal behavior, and have normal brain structure. Thus, TRIM46 is not required for AIS formation, axon specification, or nervous system function. We also show TRIM46 enrichment in the first ~100 m of axon occurs independently of ankyrinG (AnkG), although AnkG is required to restrict TRIM46 only to the AIS. Our results suggest an unidentified protein may compensate for loss of TRIM46 in vivo and highlight the need for further investigation of the mechanisms by which the AIS and microtubules interact to shape neuronal structure and function.

Functional Activity, Functional Connectivity and Complex Network Biomarkers of Progressive Hyposmia Parkinson's Disease with No Cognitive Impairment: Evidences from Resting-state fMRI Study
Background: Olfactory dysfunction stands as one of the most prevalent non-motor symptoms in the initial stage of Parkinson's disease (PD). Nevertheless, the intricate mechanisms underlying olfactory deficits in Parkinson's disease still remain elusive. Methods: This study collected rs-fMRI data from 30 PD patients (15 with severe hyposmia (PD-SH) and 15 with no/mild hyposmia (PD-N/MH)) and 15 healthy controls (HC). To investigate functional segregation, the amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) were utilized. Functional connectivity (FC) analysis was performed to explore the functional integration across diverse brain regions. Additionally, the graph theory-based network analysis was employed to assess functional networks in PD patients. Furthermore, Pearson correlation analysis was conducted to delve deeper into the relationship between the severity of olfactory dysfunction and various functional metrics. Results: Firstly, PD patients showed significantly higher ALFF values in the superior temporal gyrus compared to HC, especially in the PD-SH group versus PD-N/MH. Meanwhile, ALFF values in this region negatively correlated with olfactory testing scores. Secondly, PD patients had higher ReHo in middle temporal gyrus and superior frontal gyrus than HC, especially PD-SH. Meanwhile, olfactory scores negatively correlated with these ReHo values. Thirdly, we observed a negative correlation between superior cerebellar-insula connectivity and olfactory scores, suggesting a neural circuit link to olfactory dysfunction. Lastly, the PD patients' brain networks consistently showed small-world attributes, with the PD-N/MH group having significantly higher nodal betweenness in the superior cerebellum than the PD-SH group. There's also a positive link between superior cerebellum's betweenness and olfactory scores. Additionally, there is a notable difference in the node degree of the superior temporal gyrus when comparing the PD-SH group to the PD-N/MH group. Conclusion: Using fMRI, our study analyzed brain function in PD-SH, PD-N/MH, and HC groups, revealing impaired segregation and integration in PD-SH and PD-N/MH. We hypothesize that changes in temporal, frontal, occipital, and cerebellar activities, along with aberrant cerebellum-insula connectivity and node degree and betweenness disparities, may be linked to olfactory dysfunction in PD patients.

Automated inference of disease mechanisms in patient-hiPSC-derived neuronal networks
Human induced pluripotent stem cells (hiPSCs)-derived neurons offer a valuable platform for studying neurological disorders in a patient-specific manner. These neurons can be rapidly differentiated into excitatory neuronal networks, whose activity is measurable using multi-electrode arrays (MEAs). Neuronal networks derived from patients exhibit distinct characteristics, reflecting underlying pathological molecular mechanisms. However, elucidating these mechanisms traditionally requires extensive and hypothesis-driven additional experiments. Computational models can link observable network activity to underlying molecular mechanisms by identifying biophysical model parameters that simulate the activity, but this identification process is challenging. Here, we address this challenge by using simulation-based inference (SBI), a machine-learning approach, to automatically identify the full range of model parameters able to explain the patient-derived MEA activity. Our study demonstrates that SBI can accurately identify ground-truth parameters in simulated data, and successfully estimate the parameters that replicate the network activity of healthy hiPSC-derived neuronal networks. Furthermore, we show that SBI can pinpoint molecular mechanisms affected by pharmacological agents and identify key disease mechanisms in neuronal networks derived from patients. These findings underscore the potential of SBI to automate and enhance the identification of disease mechanisms from MEA measurements, offering a robust and scalable method for advancing research with hiPSC-derived neuronal networks.

Mapping Large-scale Spatiotemporal Dynamics of Synaptic Plasticity and LTP for Memory Encoding in the Hippocampal Network
Understanding memory formation requires elucidating the intricate dynamics of neuronal networks in the hippocampus, where information is encoded and processed through specific activity patterns and synaptic plasticity. Here, we introduce "EVOX," an advanced network electrophysiology platform equipped with high-density microelectrode arrays to capture critical network-level synaptic dynamics integral to learning and memory. This platform surpasses traditional methods by enabling label-free, high-order mapping of neural interactions, providing unprecedented insights into network Long-Term Potentiation (LTP) and evoked synaptic transmission within the hippocampal network. Utilizing EVOX, we demonstrate that high-frequency stimulation induces network-wide LTP, revealing enhanced synaptic efficacy in previously inactive cell assemblies in hippocampal layers. Our platform enables the real-time observation of network synaptic transmission, capturing the intricate patterns of connectivity and plasticity that underpin memory encoding. Advanced computational techniques further elucidate the mesoscale transmembrane generators and the dynamic processes that govern network-level memory encoding mechanisms. These findings uncover the complex dynamics that underlie learning and memory, showcasing EVOX's potential to explore synaptic and cellular phenomena in aging circuits. EVOX not only advances our understanding of hippocampal memory mechanisms but also serves as a powerful tool to investigate the broader scope of neural plasticity and network interactions in healthy and diseased states.

Spatiotemporal transcriptomic maps of mouse intracerebral hemorrhage at single-cell resolution
Intracerebral hemorrhage (ICH) is a severe and widespread disease that results in high mortality and morbidity. Despite significant advances made in clinical and preclinical research, the prognosis of ICH remains poor due to an incomplete understanding of the complex pathological responses. To address this challenge, we generated single-cell resolution spatiotemporal transcriptomic maps of mouse brain 1, 3, 7, 14, and 28 days after ICH. Our analysis revealed the cellular constituents and their dynamic responses following ICH. We found changes in gene expression that are indicative of active phagocytosis and lipid processing in the lesion core and identified genes associated with brain repair at the lesion border. Persistent lipid accumulation culminated in the phenotypic transition of macrophages into foam cells. Furthermore, our results demonstrate that ICH could stimulate neural stem cells in the subventricular zone, thereby enhancing neurogenesis in this niche. This study provides a spatiotemporal molecular atlas of mouse ICH that advances the understanding of both local and global responses of brain cells to ICH and offers a valuable resource that can aid the development of novel therapies for this devastating condition.

Contribute to balance, wire in accordance: Emergence of backpropagation from a simple, bio-plausible neuroplasticity rule
Over the past several decades, backpropagation (BP) has played a critical role in the advancement of machine learning and remains a core method in numerous computational applications. It is also utilized extensively in comparative studies of biological and artificial neural network representations. Despite its widespread use, the implementation of BP in the brain remains elusive, and its biological plausibility is often questioned due to inherent issues such as the need for symmetry of weights between forward and backward connections, and the requirement of distinct forward and backward phases of computation. Here, we introduce a novel neuroplasticity rule that offers a potential mechanism for implementing BP in the brain. Similar in general form to the classical Hebbian rule, this rule is based on the core principles of maintaining the balance of excitatory and inhibitory inputs as well as on retrograde signaling, and operates over three progressively slower timescales: neural firing, retrograde signaling, and neural plasticity. We hypothesize that each neuron possesses an internal state, termed credit, in addition to its firing rate. After achieving equilibrium in firing rates, neurons receive credits based on their contribution to the E-I balance of postsynaptic neurons through retrograde signaling. As the network's credit distribution stabilizes, connections from those presynaptic neurons are strengthened that significantly contribute to the balance of postsynaptic neurons. We demonstrate mathematically that our learning rule precisely replicates BP in layered neural networks without any approximations. Simulations on artificial neural networks reveal that this rule induces varying community structures in networks, depending on the learning rate. This simple theoretical framework presents a biologically plausible implementation of BP, with testable assumptions and predictions that may be evaluated through biological experiments.

Potential Benefits of Ketone Therapy as a Novel Immunometabolic Treatment for Schizophrenia
Rationale: Current treatment options for patients with schizophrenia-spectrum disorders (SSD) remain unsatisfactory, leaving patients with persistent negative and cognitive symptoms and metabolic side effects. Therapeutic ketosis was recently hypothesized to target the bio-energetic pathophysiology of SSD. However, neuro-inflammation plays an important role in the pathobiology of SSD as well. Ideally, novel treatments would target both the bio-energetic, and the inflammatory aspects of SSD. In this study, we aimed to investigate the effects of ketone bodies on neuro-inflammation in an acute inflammation mouse model. Methods: 8-week-old male C57BL/6 N mice (n=11) were treated with either ketone ester (KE) or vehicle for 3 days. On day 3, a single intraperitoneal injection of lipopolysaccharide (LPS) or phosphate buffered saline (PBS) was administered. Mice were euthanized 24 h after LPS/PBS injection. Whole brain gene expression analysis using RT-PCR was done for Tnf-a, Il-6 and Il-1b. Results: LPS caused a potent transcriptional upregulation of Tnf-a, Il-6 and Il-1b in the vehicle-treated mouse brain compared to PBS-injected controls. KE strongly and significantly attenuated the increased transcription of pro-inflammatory cytokines (Tnf-a, Il-6 and Il-1b) in the brain upon LPS injection compared to vehicle. Conclusions: KE potently dampened neuro-inflammation in this acute inflammation mouse model. Ketone therapy holds great promise as a treatment for SSD patients by simultaneously targeting two main pathophysiological disease pathways. We encourage more research into the immunometabolic potential of therapeutic ketosis in SSD.

A novel mouse home cage lickometer system reveals sex- and housing-based influences on alcohol drinking
Alcohol use disorder (AUD) is a significant global health issue. Despite historically higher rates among men, AUD prevalence and negative alcohol-related outcomes in women are rising. Loneliness in humans has been associated with increased alcohol use, and traditional rodent drinking models involve single housing, presenting challenges for studying social enrichment. We developed LIQ PARTI (Lick Instance Quantifier with Poly-Animal RFID Tracking Integration), an open-source tool to examine home cage continuous access two-bottle choice drinking behavior in a group-housed setting, investigating the influence of sex and social isolation on ethanol consumption and bout microstructure in C57Bl/6J mice. LIQ PARTI, based on our previously developed single-housed LIQ HD system, accurately tracks drinking behavior using capacitive-based sensors and RFID technology. Group-housed female mice exhibited higher ethanol preference than males, while males displayed a unique undulating pattern of ethanol preference linked to cage changes, suggesting a potential stress-related response. Chronic ethanol intake distinctly altered bout microstructure between male and female mice, highlighting sex and social environmental influences on drinking behavior. Social isolation with the LIQ HD system amplified fluid intake and ethanol preference in both sexes, accompanied by sex- and fluid-dependent changes in bout microstructure. However, these effects largely reversed upon resocialization, indicating the plasticity of these behaviors in response to social context. Utilizing a novel group-housed home cage lickometer device, our findings illustrate the critical interplay of sex and housing conditions in voluntary alcohol drinking behaviors in C57Bl/6J mice, facilitating nuanced insights into the potential contributions to AUD etiology.

A new GRAB sensor reveals differences in the dynamics and molecular regulation between neuropeptide and neurotransmitter release
The co-existence and co-transmission of neuropeptides and small molecule neurotransmitters in the same neuron is a fundamental aspect of almost all neurons across various species. However, the differences regarding their in vivo spatiotemporal dynamics and underlying molecular regulation remain poorly understood. Here, we developed a GPCR-activation-based (GRAB) sensor for detecting short neuropeptide F (sNPF) with high sensitivity and spatiotemporal resolution. Furthermore, we explore the differences of in vivo dynamics and molecular regulation between sNPF and acetylcholine (ACh) from the same neurons. Interestingly, the release of sNPF and ACh shows different spatiotemporal dynamics. Notably, we found that distinct synaptotagmins (Syt) are involved in these two processes, as Syt7 and Sytalpha for sNPF release, while Syt1 for ACh release. Thus, this new GRAB sensor provides a powerful tool for studying neuropeptide release and providing new insights into the distinct release dynamics and molecular regulation between neuropeptides and small molecule neurotransmitters.

Regulation of dopamine release by tonic activity patterns in the striatal brain slice
Voluntary movement, motivation, and reinforcement learning depend on the activity of ventral midbrain neurons that extend axons to release dopamine (DA) in the striatum. These neurons exhibit two patterns of action potential activity: a low-frequency tonic activity that is intrinsically generated, and superimposed high-frequency phasic bursts that are driven by synaptic inputs. Ex vivo acute striatal brain preparations are widely employed to study the regulation of evoked DA release but exhibit very different DA release kinetics than in vivo recordings. To investigate the relationship between phasic and tonic neuronal activity, we stimulated the slice in patterns intended to mimic tonic activity, which were interrupted by a series of burst stimuli. Conditioning the striatal slice with low-frequency activity altered DA release triggered by high-frequency bursts, and produced kinetic parameters that resemble those in vivo. In the absence of applied tonic activity, nicotinic acetylcholine receptor and D2 dopamine receptor antagonists had no significant effect on neurotransmitter release driven by repeated burst activity in the striatal brain slice. In contrast, in tonically stimulated slices, D2 receptor blockade decreased the amount of DA released during a single burst and facilitated DA release in subsequent bursts. This experimental system provides a means to reconcile the difference in the kinetics of DA release ex vivo and in vivo and provides a novel approach to more accurately emulate pre- and post-synaptic mechanisms that control axonal DA release in the acute striatal brain slice.

SH3BP2 regulates the organization of the neuromuscular synapses through protein-driven phase separation
The molecular mechanisms underlying the development and maintenance of the neuromuscular junction are poorly understood, even though the malfunction of these specialized synapses is associated with severe genetic and autoimmune disorders. The identity of factors controlling the maintenance mechanisms of postsynaptic acetylcholine receptors (AChR) in high-density has been elusive and is of great interest to the pharma industry, searching for possible new targets for disease interventions. Here, we report the identification of a scaffold protein SH3BP2, which exhibits polyvalent interaction with the dystrophin-glycoprotein complex (DGC) and AChR pentamers, promoting AChR clustering through phase separation. Muscle-specific SH3BP2 deletion in mice leads to impaired organization of the neuromuscular synapses, defects in synaptic transmission, and reduced muscle strength. Our studies identified a novel regulator of the postsynaptic machinery involved in clustering AChR and linking it to the DGC.

Potassium homeostasis during disease progression of Alzheimers Disease
Alzheimers disease (AD) is an age-dependent neurodegenerative disorder characterized by neuronal loss leading to dementia and ultimately death. Whilst the loss of neurons is central to the disease, it is becoming clear that glia, specifically astrocytes, contribute to the onset and progression of neurodegeneration. Astrocytic role in retaining ion homeostasis in the extracellular milieu is fundamental for multiple brain functions, including synaptic plasticity and neuronal excitability, which are compromised during AD and affect neuronal signalling. In this study, we have measured the astrocytic K+ clearance rate in the hippocampus and somatosensory cortex of a mouse model for AD during disease progression. Our results establish that astrocytic [K+]o clearance in the hippocampus is reduced in symptomatic 5xFAD mice, and this decrease is region-specific. The decrease in the [K+]o clearance rate correlated with a significant reduction in the expression and conductivity of Kir4.1 channels and a decline in the number of primary connected astrocytes. Moreover, astrocytes in the hippocampus of symptomatic 5xFAD mice demonstrated increased reactivity which was accompanied by an increased excitability and altered spiking profile of nearby neurons. These findings indicate that the supportive function astrocytes typically provide to nearby neurons is diminished during disease progression, which affects the neuronal circuit signalling in this area and provides a potential explanation for the increased vulnerability of neurons in AD.

Representation of grasping type and force in the primate motor cortex
The primary motor cortex (M1) is strongly engaged by movement planning and movement execution. However, the role of M1 activity in voluntary grasping is still not completely understood. Here we analyze recordings of M1 neurons during the execution of a delayed reach-to-grasp task, where monkeys had to actively grasp an object with either a side or a precision grip, and then pull it with a low or high amount of force. Single cell and neural populations analyses showed that grip type was robustly and specifically encoded by a large population of neurons, while force level was weakly encoded within mixed-selective neurons that also provided grip type information. Notably, the grip type was stably decoded from motor cortical populations during the preparation and execution epochs of the task. Our results are consistent with the idea that planning and performing specific grasping movements are high-level skills that strongly engage M1 neurons, while the execution of grasping-pulling force might be prominently encoded at lower stages of the motor system.

NMDA receptor activation drives early synapse formation in vivo
The rules governing neural circuit formation in mammalian central nervous systems are poorly understood. NMDA receptors are involved in synaptic plasticity mechanisms in mature neurons, but their contribution to circuit formation and dendritic maturation remains controversial. Using pharmacological and genetic interventions to disrupt NMDA receptor signaling in hippocampal CA1 pyramidal neurons in vitro and in vivo, we identify an early critical window for a synapse-specific function in wiring Schaffer collateral connections and dendritic arborization. Through in vivo imaging, we show that NMDA receptors are frequently activated during early development and elicit minute-long calcium transients, which immediately precede the emergence of filopodia. These results demonstrate that NMDA receptors drive synapto- and dendritogenesis during development, challenging the view that these processes are primarily mediated by molecular cues.

Decreased cellular excitability of pyramidal tract neurons in primary motor cortex leads to paradoxically increased network activity in simulated parkinsonian motor cortex
Decreased excitability of pyramidal tract neurons in layer 5B (PT5B) of primary motor cortex (M1) has recently been shown in a dopamine-depleted mouse model of parkinsonism. We hypothesized that decreased PT5B neuron excitability would substantially disrupt oscillatory and non-oscillatory firing patterns of neurons in layer 5 (L5) of primary motor cortex (M1). To test this hypothesis, we performed computer simulations using a previously validated computer model of mouse M1. Inclusion of the experimentally identified parkinsonism-associated decrease of PT5B excitability into our computational model produced a paradoxical increase in rest-state PT5B firing rate, as well as an increase in beta-band oscillatory power in local field potential (LFP). In the movement-state, PT5B population firing and LFP showed reduced beta and increased high-beta, low-gamma activity of 20-35 Hz in the parkinsonian, but not in control condition. The appearance of beta-band oscillations in parkinsonism would be expected to disrupt normal M1 motor output and contribute to motor activity deficits seen in patients with Parkinson's disease (PD).

Altered striosome-matrix distribution and activity of striatal cholinergic interneurons in a model of autism-linked repetitive behaviors
Repetitive behaviors are cardinal features of many brain disorders, including autism spectrum disorder (ASD). We previously associated dysfunction of striatal cholinergic interneurons (SCINs) with repetitive behaviors in a mouse model based on conditional deletion of the ASD-related gene Tshz3 in cholinergic neurons (Chat-cKO). Here, we provide evidence linking SCIN abnormalities to the unique organization of the striatum into striosome and matrix compartments, whose imbalances are implicated in several pathological conditions. Chat-cKO mice exhibit altered relationship between the embryonic birthdate of SCINs and their adult striosome-matrix distribution, leading to an increased proportion of striosomal SCINs. In addition, the ratio of striosomal SCINs with slow-irregular vs. sustained-regular firing is increased, which translates into decreased activity, further stressing the striosome-matrix imbalance. These findings provide novel insights onto the pathogenesis of ASD-related stereotyped behaviors by pointing to abnormal developmental compartmentalization and activity of SCINs as a substrate.