bioRxiv Subject Collection: Neuroscience's Journal

Does global signal regression alter fMRI connectivity patterns related to EEG activity? An EEG-fMRI study in humans
Functional brain connectivity measures extracted from resting-state functional magnetic resonance imaging (fMRI) scans have generated wide interest as potential noninvasive biomarkers. In this context, performing global signal regression (GSR) as a preprocessing step remains controversial. Specifically, while it has been shown that a considerable fraction of global signal variations is associated with physiological and motion sources, GSR may also result in removing neural activity. Here, we address this question by examining the fundamental sources of resting global signal fluctuations using simultaneous electroencephalography (EEG)-fMRI data combined with cardiac and breathing recordings. Our results suggest that systemic physiological fluctuations account for a significantly larger fraction of global signal variability compared to electrophysiological fluctuations. Furthermore, we show that GSR reduces artifactual connectivity due to heart rate and breathing fluctuations, but preserves connectivity patterns associated with electrophysiological activity within the alpha and beta frequency ranges. Overall, these results provide evidence that the neural component of resting-state fMRI-based connectivity is preserved after the global signal is regressed out.

Cerebrospinal fluid proteome profiling using machine learning shows a unique protein signature associated with APOE4 genotype
APOE4 is the biggest genetic risk factor for Alzheimers disease (AD). Proteome-wide changes independent of AD brain pathology and whether these extend to APOE4 carriers irrespective of cognitive status remain unknown. To investigate APOE4-associated proteome changes in people with and without AD. Patient clinical, APOE genotype, and cerebrospinal fluid (CSF) proteome data for 735 participants was sourced from the Alzheimers Disease Neuroimaging Initiative (ADNI) database. Participants with no cognitive impairment, mild cognitive impairment (MCI), and AD were included. Diagnosis was defined using cognitive assessments. Supervised machine learning (classification and regression trees; CART) was used for proteome profiling to identify protein signatures. Enrichment analyses for brain regions and cells and peripheral immune cells were performed using NetworkAnalyst 3.0 and the Human Protein Atlas. CART revealed an APOE4 specific proteome signature consisting of 7 proteins that were independent predictors of APOE4 carriers (sensitivity, specificity, PPV, NPV, and AUC = 1.0) and 50 proteins that interacted together for prediction (sensitivity = 0.99, specificity = 0.74, PPV = 0.86, NPV = 0.98, AUC = 0.92). This signature was found across APOE4 carriers independently of diagnosis and was associated with an increased risk of progression to cognitive impairment over time. Proteins within the signature were enriched in brain regions including the caudate and cortex. Enriched brain cells included endothelial cells, oligodendrocytes, and astrocytes. Enriched peripheral immune cells included T cells, macrophages, and B cells. We identified an APOE4 specific CSF proteome signature of 57 proteins that was independent of cognitive status and was associated with an increased risk of progression to cognitive impairment. It was also associated with a strong immune and inflammatory phenotype across the brain and periphery. Our findings suggest that the APOE4 proteome signature is independent of AD-specific brain pathology and likely underlies APOE4 carriers vulnerability to cognitive decline and AD.

Luminance invariant encoding in primary visual cortex
The retina maintains sensitivity over a large range of luminance intensities by switching between rod and cone photoreceptors. This luminance adaptation has been shown to alter the receptive fields and interneuronal correlations of retinal ganglion cells (RGCs). While these adaptations allow the retina to encode visual information across environmental conditions, they present a challenge to downstream processing areas for which it is important that representations are invariant to light level. We measured the effects of scotopic versus photopic luminance adaptation on thalamic and cortical activity by tracking neuronal populations across light levels. While changes in the output of the retina are evident in the lateral geniculate nucleus (LGN), the representation in primary visual cortex (V1) is largely invariant to the changes in luminance. We show that an invariant V1 code can emerge through the integration of parallel functional pathways at the geniculocortical synapse.

Control over a mixture of policies determines change of mind topology during continuous choice
Behavior is naturally organized into categorically distinct states with corresponding patterns of neural activity; how does the brain control those states? We propose that states are regulated by specific neural processes that implement meta-control that can blend simpler control processes. To test this hypothesis, we recorded from neurons in the dorsal anterior cingulate cortex (dACC) and dorsal premotor cortex (PMd) while macaques performed a continuous pursuit task with two moving prey that followed evasive strategies. We used a novel control theoretic approach to infer subjects moment-to-moment latent control variables, which in turn dictated their blend of distinct identifiable control processes. We identified low-dimensional subspaces in neuronal responses that reflected the current strategy, the value of the pursued target, and the relative value of the two targets. The top two principal components of activity tracked changes of mind in abstract and change-type-specific formats, respectively. These results indicate that control of behavioral state reflects the interaction of brain processes found in dorsal prefrontal regions that implement a mixture over low-level control policies.

Multisensory integration in Anopheles mosquito swarms: The role of visual and acoustic information in mate tracking and collision avoidance
Malaria mosquitoes mate in swarms. Here, they must rely on multiple sensory cues in shaping their individual responses, such as during mate recognition, swarm maintenance, and collision avoidance. While male mosquitoes are known to use faint female flight tones for recognizing their mates, the role of other sensory modalities remains less explored. By combining free-flight and tethered flight simulator experiments with Anopheles coluzzii, we demonstrate that swarming mosquitoes integrate visual and acoustic information to track conspecifics and avoid collisions. In tethered experiments, acoustic stimuli gated male steering responses to visual objects simulating nearby female mosquitoes, whereas visual cues alone triggered changes in wingbeat amplitude and frequency. Free-flight experiments show that mosquitoes modulate their flight responses to nearby conspecifics similarly to tethered animals, allowing for collision avoidance within swarms. These findings suggest that combined visual and acoustic information contributes to conspecific recognition within swarms, and, for males, permits female tracking while avoiding collisions.

Hypoactivation of ventromedial frontal cortex in major depressive disorder: an MEG study of the Reward Positivity
Background: The Reward Positivity (RewP) is sensitive and specific electrophysiological marker of reward receipt. These characteristics make it a compelling candidate marker of dysfunctional reward processing in major depressive disorder. We previously proposed that the RewP is a nexus of multiple aspects of reward variance, and that a diminished RewP in depression might only reflect a deficit in some of this variance. Specifically, we predicted a diminished ventromedial contribution in depression in the context of maintained reward learning. Methods: Here we collected magnetoencephalographic (MEG) recordings of reward receipt in 43 individuals with major depressive disorder (MDD group) and 38 healthy controls (CTL group). MEG allows effective source estimation due to the absence of volume conduction that compromises electroencephalographic recordings. Results: The MEG RewP analogue was generated by a broad set of cortical areas, yet only right ventromedial and right ventral temporal areas were diminished in MDD. These areas correlated with a principal component of anhedonia derived from multiple questionnaires. Compellingly, BA25 was the frontal region with the largest representation in both of these effects. Conclusions: These findings not only advance our understanding underlying the computation of the RewP, but they also dovetail with convergent findings from other types of functional source imaging in depression, as well as from deep brain stimulation treatments. Together, these discoveries suggest that the RewP may be a valuable marker for objective assessment of reward affect and its disruption in major depression.

No evidence that visual impulses enhance the readout of retrieved long-term memory contents from EEG activity
The application of multivariate pattern analysis (MVPA) to electroencephalography (EEG) data allows neuroscientists to track neural representations at temporally fine-grained scales. This approach has been leveraged to study the locus and evolution of long-term memory contents in the brain, but a limiting factor is that decoding performance remains low. A key reason for this is that processes like encoding and retrieval are intrinsically dynamic across trials and participants, and this runs in tension with MVPA and other techniques that rely on consistently unfolding neural codes to generate predictions about memory contents. The presentation of visually perturbing stimuli may experimentally regularize brain dynamics, making neural codes more stable across measurements to enhance representational readouts. Such enhancements, which have repeatedly been demonstrated in working memory contexts, remain to our knowledge unexplored in long-term memory tasks. In this study, we evaluated whether visual perturbations - or pings - improve our ability to predict the category of retrieved images from EEG activity during cued recall. Overall, our findings suggest that while pings evoked a prominent neural response, they did not reliably produce improvements in MVPA-based classification across several analyses. We discuss possibilities that could explain these results, including the role of experimental and analysis parameter choices and mechanistic differences between working and long-term memory.

GABA/Glutamate neuron differentiation imbalance and increased AKT/mTOR signalling in CNTNAP2-/-cerebral organoids.
We developed a human cerebral organoid model derived from induced pluripotent stem cells (iPSCs) with targeted genome editing to abolish protein expression of the Contactin Associated Protein-like 2 (CNTNAP2) autism spectrum disorder (ASD) risk gene, mimicking loss-of-function mutations seen in patients. CNTNAP2-/- cerebral organoids displayed accelerated cell cycle, ventricular zone disorganisation and increased cortical folding. Proteomic analysis revealed disruptions in Glutamatergic/GABAergic synaptic pathways and neurodevelopment, highlighting increased protein expression of corticogenesis and neurodevelopment-related genes such as Forkhead box protein G1 (FOXG1) and Paired box 6 (PAX6). Transcriptomic analysis revealed differentially expressed genes (DEG) belonging to inhibitory neuron-related gene networks. Interestingly, there was a weak correlation between the transcriptomic and proteomic data, suggesting nuanced translational control mechanisms. Along these lines we found upregulated Protein Kinase B (Akt)/mechanistic target of rapamycin (mTOR) signalling in CNTNAP2-/- organoids. Spatial transcriptomics analysis of CNTNAP2-/- ventricular-like zones demonstrated pervasive changes in gene expression, particularly in PAX6- cells, implicating upregulation of cell cycle regulation pathways, synaptic and Glutamatergic/GABAergic pathways. We noted a significant overlap of all D30 cerebral organoids 'omics datasets with an idiopathic ASD (macrocephaly) iPSC-derived telencephalic organoids DEG dataset, where FOXG1 was upregulated. Moreover, we detected increased Glutamate decarboxylase 1 (GAD1) and decreased T-Box Brain Transcription Factor 1 (TBR1) expressing cells, suggesting altered GABAergic/Glutamatergic neuron development. These findings potentially highlight a shared mechanism in the early cortical development of various forms of ASD, further elucidate the role of CNTNAP2 in ASD pathophysiology and cortical development and pave the way for targeted therapies using cerebral organoids as preclinical models.

Perpetual step-like restructuring of hippocampal circuit dynamics
Representation of the environment by hippocampal populations is known to drift even within a familiar environment, which could reflect gradual changes in single cell activity or result from averaging across discrete switches of single neurons. Disambiguating these possibilities is crucial, as they each imply distinct mechanisms. Leveraging change point detection and model comparison, we found that CA1 population vectors decorrelated gradually within a session. In contrast, individual neurons exhibited predominantly step-like emergence and disappearance of place fields or sustained change in within-field firing. The changes were not restricted to particular parts of the maze or trials and did not require apparent behavioral changes. The same place fields emerged, disappeared, and reappeared across days, suggesting that the hippocampus reuses pre-existing assemblies, rather than forming new fields de novo. Our results suggest an internally-driven perpetual step-like reorganization of the neuronal assemblies.

Sex differences in the functional network underpinnings of psychotic-like experiences in children
Psychotic-like experiences (PLEs) include a range of sub-threshold symptoms that resemble aspects of psychosis but do not necessarily indicate the presence of psychiatric illness. These experiences are highly prevalent in youth and are associated with developmental disruptions across social, academic, and emotional domains. While not all youth who report PLEs develop psychosis, many develop other psychiatric illnesses during adolescence and adulthood. As such, PLEs are theorized to represent early markers of poor mental health. Here, we characterized the similarities and differences in the neurobiological underpinnings of childhood PLEs across the sexes using a large sample from the ABCD Study (n=5,260), revealing sex-specific associations between functional networks connectivity and PLEs. We find that although the networks associated with PLEs overlap to some extent across the sexes, there are also crucial differences. In females, PLEs are associated with dispersed cortical and non-cortical connections, whereas in males, they are primarily associated with functional connections within limbic, temporal parietal, somato/motor, and visual networks. These results suggest that early transdiagnostic markers of psychopathology may be distinct across the sexes, further emphasizing the need to consider sex in psychiatric research as well as clinical practice.

Infraslow dynamic patterns in human cortical networks track a spectrum of external to internal attention
Early efforts to understand the human cerebral cortex focused on localization of function, assigning functional roles to specific brain regions. More recent evidence depicts the cortex as a dynamic system, organized into flexible networks with patterns of spatiotemporal activity corresponding to attentional demands. In functional MRI (fMRI), dynamic analysis of such spatiotemporal patterns is highly promising for providing non-invasive biomarkers of neurodegenerative diseases and neural disorders. However, there is no established neurotypical spectrum to interpret the burgeoning literature of dynamic functional connectivity from fMRI across attentional states. In the present study, we apply dynamic analysis of network-scale spatiotemporal patterns in a range of fMRI datasets across numerous tasks including a left-right moving dot task, visual working memory tasks, congruence tasks, multiple resting state datasets, mindfulness meditators, and subjects watching TV. We find that cortical networks show shifts in dynamic functional connectivity across a spectrum that tracks the level of external to internal attention demanded by these tasks. Dynamics of networks often grouped into a single task positive network show divergent responses along this axis of attention, consistent with evidence that definitions of a single task positive network are misleading. Additionally, somatosensory and visual networks exhibit strong phase shifting along this spectrum of attention. Results were robust on a group and individual level, further establishing network dynamics as a potential individual biomarker. To our knowledge, this represents the first study of its kind to generate a spectrum of dynamic network relationships across such an axis of attention.

How distributed subcortical integration of reward and threat may inform approach-avoidance decisions
Healthy and successful living involves carefully navigating rewarding and threatening situations by balancing approach and avoidance behaviours. Excessive avoidance to evade potential threats often leads to forfeiting potential rewards. However, little is known about how reward and threat information is integrated neurally to inform either approach or avoidance decisions. In this preregistered study, participants (N=31, 17F) made approach-avoidance decisions under varying reward (monetary gains) and threat (electrical stimulations) prospects during functional MRI scanning. In contrast to theorized parallel subcortical processing of reward and threat information before cortical integration, Bayesian Multivariate Multilevel analyses revealed subcortical reward and threat integration prior to indicating approach-avoidance decisions. This integration occurred in the ventral striatum, thalamus, and bed nucleus of the stria terminalis (BNST). When reward was low, avoidance decisions dominated, reflected in stronger reactivity to threat prior to indicating avoidance decisions across these regions. In addition, the amygdala exhibited dual sensitivity to reward and threat. While anticipating the outcome of approach decisions, characterized by elevated risk of electrical stimulation, increased threat-related activity within the salience network (dorsal anterior cingulate cortex, thalamus, periaqueductal gray, BNST) was observed. Conversely, anticipating the outcome of avoidance decisions, marked by reduced reward potential, was associated with suppression of reward-related activity in the ventromedial prefrontal cortex and ventral striatum. These findings shed light on the temporal dynamics of approach-avoidance decision-making. Importantly, they demonstrate the role of subcortical integration of reward and threat information in balancing approach and avoidance, challenging theories positing predominantly separate subcortical processing before cortical integration.

Directed differentiation of functional corticospinal-like neurons from endogenous SOX6+/NG2+ cortical progenitors
Corticospinal neurons (CSN) centrally degenerate in amyotrophic lateral sclerosis (ALS), along with spinal motor neurons, and loss of voluntary motor function in spinal cord injury (SCI) results from damage to CSN axons. For functional regeneration of specifically affected neuronal circuitry in vivo, or for optimally informative disease modeling and/or therapeutic screening in vitro, it is important to reproduce the type or subtype of neurons involved. No such appropriate in vitro models exist with which to investigate CSN selective vulnerability and degeneration in ALS, or to investigate routes to regeneration of CSN circuitry for ALS or SCI, critically limiting the relevance of much research. Here, we identify that the HMG-domain transcription factor Sox6 is expressed by a subset of NG2+ endogenous cortical progenitors in postnatal and adult cortex, and that Sox6 suppresses a latent neurogenic program by repressing inappropriate proneural Neurog2 expression by progenitors. We FACS-purify these genetically accessible progenitors from postnatal mouse cortex and establish a pure culture system to investigate their potential for directed differentiation into CSN. We then employ a multi-component construct with complementary and differentiation-sharpening transcriptional controls (activating Neurog2, Fezf2, while antagonizing Olig2 with VP16:Olig2). We generate corticospinal-like neurons from SOX6+/NG2+ cortical progenitors, and find that these neurons differentiate with remarkable fidelity compared with corticospinal neurons in vivo. They possess appropriate morphological, molecular, transcriptomic, and electrophysiological characteristics, without characteristics of the alternate intracortical or other neuronal subtypes. We identify that these critical specifics of differentiation are not reproduced by commonly employed Neurog2-driven differentiation. Neurons induced by Neurog2 instead exhibit aberrant multi-axon morphology and express molecular hallmarks of alternate cortical projection subtypes, often in mixed form. Together, this developmentally-based directed differentiation from genetically accessible cortical progenitors sets a precedent and foundation for in vitro mechanistic and therapeutic disease modeling, and toward regenerative neuronal repopulation and circuit repair.

Motor Control of Distinct Layer 6 Corticothalamic Feedback Circuits
Layer 6 corticothalamic (L6 CT) neurons provide massive input to the thalamus, and these feedback connections enable the cortex to influence its own sensory input by modulating thalamic excitability. However, the functional role(s) feedback serves during sensory processing is unclear. One hypothesis is that CT feedback is under the control of extra-sensory signals originating from higher-order cortical areas, yet we know nothing about the mechanisms of such control. It is also unclear whether such regulation is specific to CT neurons with distinct thalamic connectivity. Using mice (either sex) combined with in vitro electrophysiology techniques, optogenetics, and retrograde labeling, we describe studies of vibrissal primary motor cortex (vM1) influences on different CT neurons in the vibrissal primary somatosensory cortex (vS1) with distinct intrathalamic axonal projections. We found that vM1 inputs are highly selective, evoking stronger postsynaptic responses in Dual ventral posterior medial nucleus (VPm) and posterior medial nucleus (POm) projecting CT neurons located in lower L6a than VPm-only projecting CT cells in upper L6a. A targeted analysis of the specific cells and synapses involved revealed that the greater responsiveness of Dual CT neurons was due to their distinctive intrinsic membrane properties and synaptic mechanisms. These data demonstrate that vS1 has at least two discrete L6 CT subcircuits distinguished by their thalamic projection patterns, intrinsic physiology, and functional connectivity with vM1. Our results also provide insights into how a distinct CT subcircuit may serve specialized roles specific to contextual modulation of tactile-related sensory signals in the somatosensory thalamus during active vibrissa movements.

Distributed and integrated representations of tools in human parietal and anterior temporal regions revealed by fMRI-RSA
Classical models of tool knowledge and use are centred on dorsal and ventral parietal pathways. Theories of semantic cognition implicate a 'hub-and-spoke' network, centred on the anterior temporal lobe (ATL), that underpins all concepts including tools. Despite their prominence, the two theoretical frameworks have never been brought together and the large discrepancy in the functional neuroanatomy addressed. We undertook a multiple-regression Representational Similarity Analysis (RSA) of task fMRI data with four (motor action, broad function, mechanical function, object structure) feature-based models. The motor action model correlated with the activation patterns in bilateral superior parietal lobules (SPL), while the models of broad function and mechanical effect aligned with the activation patterns in bilateral ATLs. The object-structure model correlated with activation patterns in bilateral middle occipital gyri. The results also showed that the ventral ATL activation patterns corresponded simultaneously with all RDM models except object structure. Furthermore, a standard univariate analysis using tool-familiarity ratings for parametric modulation revealed that the classical tool-network regions (frontal, inferior parietal, and posterior middle temporal cortices) were increasingly active as the tool familiarity reduced. These results demonstrate that parietal and ATL regions are both crucial, and motivate a major extension and revision of the neuroanatomical framework for tool use.

Quantitative Analysis of Roles of Direct and Indirect Pathways for Action Selection in The Basal Ganglia
The basal ganglia (BG) show diverse functions for motor and cognition. Here, we are concerned about action selection performed by the BG. Particularly, we make quantitative analysis of roles of direct pathway (DP) and indirect pathway (IP) for action selection in a spiking neural network with 3 competing channels. For such quantitative work, in each channel, we get the competition degree Cd, given by the ratio of strength of DP (SDP) to strength of IP (SIP) (i.e., Cd = SDP / SIP). Then, desired action is selected in the channel with the largest Cd. Desired action selection is made mainly due to strong focused inhibitory projection to the output nucleus, SNr (substantia nigra pars reticulata) via the "Go" DP in the corresponding channel. Unlike the case of DP, there are two types of IPs; intra-channel IP and inter-channel IP, due to widespread diffusive excitation from the STN (subthalamic nucleus). The intra-channel "No-Go" IP plays a role of brake to suppress the desired action selection. On the other hand, the inter-channel IP to the SNr in the neighboring channels suppresses competing actions, leading to spotlight the desired action selection. In this way, role of the inter-channel IP is opposite to that of the intra-channel IP. But, to the best of our knowledge, no quantitative analysis for such roles of the DP and the two IPs was made. Here, by direct calculations of the DP and the intra- and the inter-channel IP presynaptic currents into the SNr in each channel, we get the competition degree of each channel to determine a desired action, and then roles of the DP and the intra- and inter-channel IPs are quantitatively made clear.

How many colours can you see? Real environmental lighting increases discriminability of surface colours
Color supports object identification. However, two objects that differ in color under one light can appear indiscriminable under a second light. This phenomenon, known as illuminant metamerism, underlies the difficulty faced by consumers of selecting matching fabric or paint colors in a store only to find that they appear not to match under home lighting. The frequency of illuminant metamerism has been evaluated only under single, uniform illuminants. However, in real world conditions, the spectral content of light falling on an object varies with direction (Morimoto et al. 2019), meaning that a surface will sample different spectra depending on its angle within the environment. Here we used computer-graphics techniques to simulate a pair of planar surfaces placed under newly measured hyperspectral illumination maps that quantify the directional variability of real-world lighting environments. We counted the instances of illuminant metamerism that can be solved simply by viewing surfaces tilted to a different direction. Results show that most instances of illuminant metamerism can in theory be resolved for both trichromatic and dichromatic observers. Color deficient observers benefit more than trichromats implying that the directional variability allows the recovery of the missing dimension in their colour vision systems. This study adds a new perspective to the classic trichromatic theory of human vision and emphasizes the importance of carefully considering the environments in which biological vision operates in daily life. It is striking that the physical directional variability available in natural lighting environments substantially mitigates the biological limitations of trichromacy or dichromacy.

JNK and PI3K signaling pathways mediate synapse formation and network spontaneous activities in primary neurons
BackgroundCellular signals orchestrating synapse formation and neuronal network function remain poorly understood. To explore the critical signaling pathways in neurons and their influence on network development, pharmacological assays were employed to inhibit multiple signaling pathways in cultured neurons.

MethodsImmunofluorescence and western blotting are applied to identify the expression of synapse-related proteins within neurons. micro-electrode arrays (MEAs) are employed to study the developmental characteristics of neuronal networks. RNA sequencing is utilized to determine the gene expression profiles pertaining to multiple signaling pathways.

ResultsCanonical c-jun N-terminal kinases (JNK) pathway is necessary for pre- and post-synaptic specializations, while phosphatidylinositide3-kinases (PI3K) is a key to postsynaptic specialization and affects the puncta sizes of presynaptic marker. Unexpectedly, pharmacological inhibition of JNK pathway significantly suppressed the mean firing rate (MFR), network burst frequency (NBF) and regularity of network firing after 4 weeks, but did not alter the synchrony of the network. During network development, PI3K pathway regulates the longer burst duration and lower network synchrony. Gene sets associated with neurodevelopmental processes and myelination was disturbed during restraining these signal pathways. Furthermore, inhibition of the PI3K signaling pathway obviously transformed voltage-gated ion channel activity, synaptic transmission and synaptic plasticity of neurons.

ConclusionThis study reveals that JNK and PI3K signaling pathways play different roles during synapse formation, and these signaling pathways have a lasting impact on the development of neuronal networks. Thus, this study provides further insights into the intracellular signaling pathways associated with synapse formation in the development of neuronal networks.

Changes in intra- and interlimb reflexes from forelimb cutaneous afferents after staggered thoracic lateral hemisections during locomotion in cats
In quadrupeds, such as cats, cutaneous afferents from the forepaw dorsum signal external perturbations and send signals to spinal circuits to coordinate the activity in muscles of all four limbs. How these cutaneous reflex pathways from forelimb afferents are reorganized after an incomplete spinal cord injury is not clear. Using a staggered thoracic lateral hemisections paradigm, we investigated changes in intralimb and interlimb reflex pathways by electrically stimulating the left and right superficial radial nerves in seven adult cats and recording reflex responses in five forelimb and ten hindlimb muscles. After the first (right T5-T6) and second (left T10-T11) hemisections, forelimb-hindlimb coordination was altered and weakened. After the second hemisection, cats required balance assistance to perform quadrupedal locomotion. Short-, mid- and long-latency homonymous and crossed reflex responses in forelimb muscles and their phase modulation remained largely unaffected after staggered hemisections. The occurrence of homolateral and diagonal mid- and long-latency responses in hindlimb muscles evoked with left and right superficial radial nerve stimulation was significantly reduced at the first time point after the first hemisection, but partially recovered at the second time point with left superficial radial nerve stimulation. These responses were lost or reduced after the second hemisection. When present, all reflex responses, including homolateral and diagonal, maintained their phase-dependent modulation. Therefore, our results show a considerable loss in cutaneous reflex transmission from cervical to lumbar levels after incomplete spinal cord injury, albeit with preservation of phase modulation, likely affecting functional responses to external perturbations.

Sequential and dynamic coding of water-sucrose categorization in rat gustatory cortices
The gustatory system underlies our conscious perception of sweetness and allows us to distinguish a sweet solution from plain water. However, the neural mechanisms in gustatory cortices that enable rats to differentiate sweetness from water remain elusive. In this study, we designed a novel sucrose categorization task in which rats classified water from a gradient of sucrose solutions. We found that in the anterior Insular Cortex (aIC) and the Orbitofrontal Cortex (OFC), neural activity prioritized encoding the categorization of water versus sucrose rather than the specific concentrations within the sucrose solutions. aIC neurons more rapidly encoded sucrose/water distinction, followed by the OFC. In contrast, the OFC encoded choice information slightly earlier than aIC, but both gustatory cortices maintained a comparable encoding of the rats choices in parallel. The encoding of sensory and categorical decisions was dynamic and sequentially encoded, forming a sequence of encoding neurons spanning the entire length of a task trial. Our results demonstrate that sucrose categorization relies on dynamic encoding sequences in the neuronal activity of aIC and the OFC rather than static, long-lasting (sustained) neural representations. Single-cell, population decoding, and principal component analyses confirmed our results. This aligns with the concept of a dynamic code, where the brain updates its representation of sucrose categorization as new information becomes available. Additionally, aIC and the OFC rapidly encoded reward outcomes. Our data supports the view that gustatory cortices use sequential and dynamic coding to compute sensorimotor transformations from taste detection to encoding categorical taste decisions and reward outcomes.

Activity-driven trafficking of endogenous synaptic proteins through proximity labeling
To enable transmission of information in the brain, synaptic vesicles fuse to presynaptic membranes, liberating their content and exposing transiently a myriad of vesicular transmembrane proteins. However, versatile methods for quantifying the synaptic translocation of endogenous proteins during neuronal activity remain unavailable, as the fast dynamics of synaptic vesicle cycling difficult specific isolation trafficking proteins during such a transient surface exposure. Here we developed a novel approach using synaptic cleft proximity labeling to capture and quantify activity-driven trafficking of endogenous synaptic proteins at the synapse. We show that accelerating cleft biotinylation times to match the fast dynamics of vesicle exocytosis allows capturing endogenous proteins transiently exposed at the synaptic surface during neural activity, enabling for the first time the study of the translocation of nearly every endogenous synaptic protein. As proof-of-concept, we further applied this technology to obtain direct evidence of the surface translocation of non-canonical trafficking proteins, such as ATG9A and NPTX1, which had been proposed to traffic during activity but for which direct proof had not yet been shown. The technological advancement presented here will facilitate future studies dissecting the molecular identity of proteins exocytosed at the synapse during activity, helping to define the molecular machinery that sustains neurotransmission in the mammalian brain.

SqueakOut: Autoencoder-based segmentation of mouse ultrasonic vocalizations
Mice emit ultrasonic vocalizations (USVs) that are important for social communication. Despite great advancements in tools to detect USVs from audio files in recent years, highly accurate segmentation of USVs from spectrograms (i.e., removing noise) remains a significant challenge. Here, we present a new dataset of 12,954 annotated spectrograms explicitly labeled for mouse USV segmentation. Leveraging this dataset, we developed SqueakOut, a lightweight (4.6M parameters) fully convolutional autoencoder that achieves high accuracy in supervised segmentation of USVs from spectrograms, with a Dice score of 90.22. SqueakOut combines a MobileNetV2 backbone with skip connections and transposed convolutions to precisely segment USVs. Using stochastic data augmentation techniques and a hybrid loss function, SqueakOut learns robust segmentation across varying recording conditions. We evaluate SqueakOut's performance, demonstrating substantial improvements over existing methods like VocalMat (63.82 Dice score). The accurate USV segmentations enabled by SqueakOut will facilitate novel methods for vocalization classification and more accurate analysis of mouse communication. To promote further research, we release the annotated 12,954 spectrogram USV segmentation dataset and the SqueakOut implementation publicly.

Probing sensitivity to statistical structure in rapid sound sequences using deviant detection tasks
Statistical structures and our ability to exploit them are a ubiquitous component of daily life. Yet, we still do not fully understand how we track these sophisticated statistics and the role they play in sensory processing. Predictive coding frameworks hypothesise that for stimuli that can be accurately anticipated based on prior experience, we rely more strongly on our internal model of the sensory world and are more "surprised" when that expectation is unmet. The current study used this phenomenon to probe listeners' sensitivity to probabilistic structures generated using rapid 50 milli-second tone-pip sequences that precluded conscious prediction of upcoming stimuli. Over three experiments we measured listeners' sensitivity and response time to deviants of a frequency outside the expected range. Predictable sequences were generated using either a triplet-based or community structure and deviance detection contrasted against the same set of tones but in a random, unpredictable order. All experiments found structured sequences enhanced deviant detection relative to random sequences. Additionally, Experiment 2 used three different instantiations of the community structure to demonstrate that the level of uncertainty in the structured sequences modulated deviant saliency. Finally, Experiment 3 placed the deviant within an established community or immediately after a transition between communities, where the perceptual boundary should generate momentary uncertainty. However, this manipulation did not impact performance. Together these results demonstrate that probabilistic contexts generated from statistical structures modulate the processing of an ongoing auditory signal, leading to an improved ability to detect unexpected deviant stimuli, consistent with the predictive coding framework.

Spinal cord injury: What are the lesion effects on transplanted cells in an autograft model?
Spinal cord injury (SCI) is a serious pathology of the central nervous system that result in loss of motor, sensory and autonomic functions below the level of the lesion and for which, unfortunately, there is currently no cure. In addition to the loss of function, SCI induces a systemic inflammation that is not confined to the spinal cord and whose effects are increasingly well characterized. In particular, SCI causes cerebral inflammation, which is responsible for the impairment of hippocampal and bulbar neurogenesis. Many therapies have been tested as potential treatments for SCI. In animal models, cell therapies have shown interesting effects such as medullary scar reduction, anti-inflammatory properties, axonal regrowth or neuronal survival, allowing better functional recovery. However, in human studies, their therapeutic capacities are less significant. Beyond obvious differences in pathophysiology and cell culture procedures, a key paradigm of cell transplantation differs between humans and animals. In animal models, transplanted cells are systematically taken from healthy animals, whereas in humans the immune incompatibility leads to the realization of autologous transplantation. Therefore, we were interested in the lesion effects on the neuro-repairing potential of olfactory ensheathing cells (OECs) harvested from olfactory bulbs. Using functional sensory-motor studies, histological and gene expression analyses, we were able to demonstrate for the first time that the lesion negatively affects the therapeutic properties of cells used to treat SCI. These innovative results shed new light on the future use of cell transplantation in autologous transplantation after SCI.