bioRxiv Subject Collection: Neuroscience's Journal

Neural coding in gustatory cortex reflects consumption decisions: Evidence from conditioned taste aversion
Taste-responsive neurons in the gustatory cortex (GC) have been shown to encode multiple properties of stimuli, including whether they are palatable or not. Previous studies have suggested that a form of taste-involved learning, conditioned taste aversion (CTA), may alter the cortical representation of taste stimuli in a number of ways. We used miniscopes to image taste responses from a large population of neurons in the gustatory cortex of mice before and after CTA to NaCl, comparing taste responses in control and conditioned mice. Following conditioning, no significant effects on the number of responsive cells, or the magnitude of response to either NaCl or other taste stimuli were found. However, population-level analyses showed that in mice receiving a CTA, the representation of NaCl diverged from other appetitive stimuli in neural space and moved closer to that of aversive quinine. We also tracked extinction of the CTA in a subset of animals and showed that as NaCl became less aversive, the neural pattern reverted to match the behavior. These data suggest that the predominant function of the taste representation in GC is palatability; the neuronal response pattern to stimuli at the population level reflects the decision of the animal to consume or not consume the stimulus, regardless of quality or chemical identity.

Learning to Choose: Behavioral Dynamics Underlying the Initial Acquisition of Decision Making
Current theories of decision making propose that decisions arise through competition between choice options. Computational models of the decision process estimate how quickly information about choice options is integrated and how much information is needed to trigger a choice. Experiments using this approach typically report data from well-trained participants. As such, we do not know how the decision process evolves as a decision-making task is learned for the first time. To address this gap, we used a behavioral design separating learning the value of choice options from learning to make choices. We trained male rats to respond to single visual stimuli with different reward values. Then, we trained them to make choices between pairs of stimuli. Initially, the rats responded more slowly when presented with choices. However, as they gained experience in making choices, this slowing reduced. Response slowing on choice trials persisted throughout the testing period. We found that it was specifically associated with increased exponential variability when the rats chose the higher value stimulus. Additionally, our analysis using drift diffusion modeling revealed that the rats required less information to make choices over time. Surprisingly, we observed reductions in the decision threshold after just a single session of choice learning. These findings provide new insights into the learning process of decision-making tasks. They suggest that the value of choice options and the ability to make choices are learned separately, and that experience plays a crucial role in improving decision-making performance.

Two-photon imaging of excitatory and inhibitory neural response to infrared neural stimulation
Significance: Pulsed infrared neural stimulation (INS, 1875 nm) is an emerging neurostimulation technology that delivers focal pulsed heat to activate functionally specific mesoscale networks and holds promise for clinical application. However, little is known about its effect on excitatory and inhibitory cell types in cerebral cortex. Aim: Estimates of summed population neuronal response timecourses provide a potential basis for neural and hemodynamic signals described in other studies. Approach: Using two-photon calcium imaging in mouse somatosensory cortex, we have examined the effect of INS pulse train application on hSyn neurons and mDlx neurons tagged with GCaMP6s. Results: We find that, in anesthetized mice, each INS pulse train reliably induces robust response in hSyn neurons exhibiting positive going responses. Surprisingly, mDlx neurons exhibit negative going responses. Quantification using the index of correlation illustrates responses are reproducible, intensity-dependent, and distance-dependent. Also, a contralateral activation is observed when INS application. Conclusions: In sum, the population of neurons stimulated by INS includes both hSyn and mDlx neurons; within a range of stimulation intensities, this leads to overall excitation in the stimulated population, leading to the previously observed activations at distant post-synaptic sites.

Corticothalamic modelling of sleep neurophysiology with applications to mobile EEG
Recent developments in mathematical modelling of EEG data enable estimation and tracking of otherwise-inaccessible neurophysiological parameters over the course of a night's sleep. Likewise, advancements in wearable electronics have enabled easier & more affordable at-home collection of sleep EEG data. The convergence of these two advances, namely neurophysiological modelling for mobile sleep EEG, has the potential to significantly improve sleep assessments in research and the clinic. However, this subject area has received limited attention in existing literature. To address this, we used an established mathematical model of the corticothalamic system to analyze EEG power spectra from 5 datasets, spanning from in-lab, research-grade systems to at-home mobile EEG devices. In the present work, we compare the convergent and divergent features of the data and the estimated physiological model parameters. While data quality and characteristics differ considerably, several key patterns consistent with previous theoretical and empirical work are observed. During the transition from lighter to deeper NREM stages, i) the exponent of the aperiodic (1/f) spectral component is increased, ii) bottom-up thalamocortical drive is reduced, iii) corticocortical connection strengths are increased. This effect, which we observe in healthy individuals across all 5 datasets, is interestingly absent in individuals taking SSRI antidepressants, suggesting possible effects of ascending neuromodulatory systems on corticothalamic oscillations. Our results provide a proof-of-principle for the utility and feasibility of this physiological modelling-based approach to analyzing data from mobile EEG devices, providing a mechanistic measure of brain physiology during sleep at home or in the lab.

Comparison of Alternative pre-mRNA Splicing and Gene Expression Patterns in Midbrain Lineage Cells Carrying Familial Parkinson's Disease Mutations
Parkinson's disease (PD) is a devastating neurodegenerative disorder, with both genetic and environmental causes. Human genetic studies have identified ~20 inherited familial genes that cause monogenic forms of PD. We have investigated the effects of individual familial PD mutations by developing a medium-throughput platform using genome-editing to install individual PD mutations in human pluripotent stem cells (hPSCs) that we subsequently differentiated into midbrain lineage cells including dopaminergic (DA) neurons in cell culture. Both global gene expression and pre-mRNA splicing patterns in midbrain cultures carrying inherited, pathogenic PD mutations in the PRKN and SNCA genes were analyzed. This analysis revealed that PD mutations lead to many more pre-mRNA splicing changes than changes in overall gene RNA expression levels. Importantly, we have also shown that these splicing changes overlap with changes found in PD patient postmortem brain sample RNA-seq datasets. These pre-mRNA splicing changes are in genes related to cytoskeletal and neuronal process formation, as well as splicing factors and spliceosome components. We predict that these mutation-specific pre-mRNA isoforms can be used as biomarkers for PD that are linked to the familial PD mutant genotypes.

Effects of noncanonical genomic imprinting in monoaminergic pathways on the regulation of social behaviors
Genomic imprinting in the brain is theorized to provide parental control over offspring social behaviors. Noncanonical genomic imprinting is a form of epigenetic regulation in which one of a genes alleles, either that of maternal or paternal inheritance, exhibits a bias towards higher expression of one parental allele compared to the other. This bias can differ depending on tissue type, and the degree of the parental allele expression bias can even vary across anatomical domains within the same tissue. Dopa decarboxylase (Ddc) and tyrosine hydroxylase (Th) are both noncanonically imprinted genes that preferentially express their maternal alleles in the brain and Ddc also has a paternal allele expression bias in the periphery. These two genes encode catecholamine synthesis enzymes for the production of dopamine (DA), norepinephrine (NE), and epinephrine (E), and Ddc is also in the serotonin (5-HT) synthesis pathway. These four neurotransmitters are critical regulators of social behavior and disruptions to them are implicated in human mental illnesses. Here we investigated the functional effects of noncanonical imprinting of Ddc and Th on social behavior in mice. By using reciprocal heterozygous mutant mice, we tested the impacts of Ddc and/or Th maternally and paternally inherited alleles on aggression, social recognition, dominance, and social preference behaviors. We found that Ddc paternal-null alleles affect aggression and social recognition behavior, Th maternal-null alleles affect sociability preferences, and compound inheritance of Th and Ddc maternal-null alleles influence preferences for social novelty. These results are consistent with Th and Ddc maternal allele biased expression in central monoaminergic systems regulating sociability, and Ddc paternal allele biased expression in peripheral monoaminergic systems regulating aggression and social recognition.

Self-organization of modular activity in immature cortical networks
During development, cortical activity is organized into distributed modular patterns that are a precursor of the mature columnar functional architecture. Theoretically, such structured neural activity can emerge dynamically from local synaptic interactions through a recurrent network with effective local excitation with lateral inhibition (LE/LI) connectivity. Utilizing simultaneous widefield calcium imaging and optogenetics in juvenile ferret cortex prior to eye opening, we directly test several critical predictions of an LE/LI mechanism. We show that cortical networks transform uniform stimulations into diverse modular patterns exhibiting a characteristic spatial wavelength. Moreover, patterned optogenetic stimulation matching this wavelength selectively biases evoked activity patterns, while stimulation with varying wavelengths transforms activity towards this characteristic wavelength, revealing a dynamic compromise between input drive and the network's intrinsic tendency to organize activity. Furthermore, the structure of early spontaneous cortical activity - which is reflected in the developing representations of visual orientation - strongly overlaps that of uniform opto-evoked activity, suggesting a common underlying mechanism as a basis for the formation of orderly columnar maps underlying sensory representations in the brain.

α7 nicotinic acetylcholine receptors are necessary for basal forebrain activation to increase expression of the nerve growth factor receptor TrkA
Activation of the basal forebrain leads to increases in the expression of the nerve growth factor receptor, Tropomyosin receptor kinase A (TrkA) and decreases in expression of the beta amyloid cleavage enzyme 1 (BACE1) in the cerebral cortex of both sexes of 5xFAD mice. The studies described in this report were designed to determine if these changes were dependent on acetylcholine receptors. Mice were stimulated unilaterally in the basal forebrain for two weeks. Animals were administered a cholinergic antagonist, or saline, 30 minutes prior to stimulation. Animals administered saline exhibited significant increases in TrkA expression and decreases in BACE1 in the stimulated hemisphere relative to the unstimulated. While both nonselective nicotinic and muscarinic acetylcholine receptor blockade attenuated the BACE1 decline, only the nicotinic receptor antagonism blocked the TrkA increase. Next, we applied selective nicotinic antagonists, and the 7 antagonist blocked the TrkA increases, but the 4{beta}2 antagonist did not. BACE1 declines were not blocked by either intervention. Mice with a loxP conditional knockout of the gene for the 7 nicotinic receptor were also employed in these studies. Animals were either stimulated bilaterally for two weeks, or left unstimulated. With or without stimulation, the expression of TrkA receptors was lower in the cortical region with the 7 nicotinic receptor knockdown. We thus conclude that 7 nicotinic receptor activation is necessary for normal expression of TrkA and increases caused by basal forebrain activation, while BACE1 declines caused by stimulation have dependency on a broader array of receptor subtypes.

Sexual dimorphism in the distribution and density of regulatory interneurons in the striatum
Dysfunction of the cortico-basal circuitry, including its primary input nucleus, the striatum, contributes to neuropsychiatric disorders, including autism and Tourette Syndrome (TS). These conditions show marked sexual dimorphism, occurring more often in males than in females. Regulatory interneurons, including cholinergic interneurons (CINs) and parvalbumin-expressing GABAergic fast spiking interneurons (FSIs), are implicated in human neuropsychiatric disorders such as TS, and ablation of these interneurons produces relevant behavioral pathology in male mice, but not in females. Here we investigate sexual dimorphism in the density and distribution of striatal interneurons, using stereological quantification of CINs, FSIs, and somatostatin-expressing (SOM) GABAergic interneurons in the dorsal and ventral striatum in male and female mice. Males have a higher density of CINs than females, specifically in the dorsal striatum; females have equal distribution between dorsal and ventral striatum. FSIs showed similar effects, with a greater dorsal-ventral density gradient in males than in females. SOM interneurons were denser in the ventral than in the dorsal striatum, with no sexual dimorphism. These sex differences in the density and distribution of FSIs and CINs suggest a potential source of the sexual dimorphism seen in TS and autism spectrum disorder.

Cell-type specific effects of Fusarium mycotoxins on primary neuronal and astroglial cells
Fumonisin B1, deoxynivalenol (DON) and zearalenone (ZEA) are toxic secondary metabolites produced by Fusarium molds. These mycotoxins are common food and feed pollutants and represent a risk for human and animal health. Although the mycotoxins produced by this genus can cross the blood-brain-barrier (BBB) in many species, their effect on neuronal function remains unclear. We investigated cell viability effects of these toxins on specified neural cell types, including mouse primary neuronal, astroglial and mixed cell cultures 24 or 48 hours after mycotoxin administration. Cell viability assay revealed that DON decreased cell viability in a dose-dependent manner, independently from the culture's type. Fumonisin B1 increased cell viability significantly on astroglial and mixed cell cultures in lower doses, while it exerted a highly toxic effect in 50 M. ZEA had significant effects on all culture type in 10 nM by increasing the cell viability. Since ZEA is a mycoestrogen, we analyzed the effects of ZEA on the expression of estrogen receptor isotypes ER and ER{beta} and mitochondrial voltage-dependent anion channel (VDAC1) by qRT-PCR. In neuronal and mixed cultures, ZEA administration decreased ER expression, while in astroglial cultures, it induced the opposite effect. ER{beta} and VDAC1 expression was not altered by ZEA in either culture types. ZEA also affected the firing pattern of neurons by enhancing the burst frequency. Our results demonstrate that Fusarium mycotoxins are acting on a cell specific manner in the brain tissue.

Direct retino-iridal projections and intrinsic iris contraction mediate the pupillary light reflex in early vertebrates
The pupillary light reflex (PLR) adapts the amount of light reaching the retina, protecting it and improving image formation. Two PLR mechanisms have been described in vertebrates. First, the pretectum receives retinal inputs and projects to the Edinger-Westphal nucleus (EWN), which targets the ciliary ganglion through the oculomotor nerve (nIII). Postganglionic fibers enter the eye-globe, travelling to the iris sphincter muscle. Additionally, some vertebrates exhibit an iris-intrinsic PLR mechanism mediated by sphincter muscle cells that express melanopsin inducing muscle contraction. Given the high degree of conservation of the lamprey visual system, we investigated the mechanisms underlying the PLR to shed light onto their evolutionary origins. Recently, a PLR mediated by melanopsin was demonstrated in lampreys, suggested to be brain mediated. Remarkably, we found that PLR is instead mediated by direct retino-iridal cholinergic projections, a mechanism not demonstrated before, although suggested to be present in mice. This retina-mediated PLR acts synergistically with the iris-intrinsic mechanism mediated by melanopsin, which has contribution of gap junctions, as in other vertebrates. In contrast, we show that lampreys lack the brain-mediated PLR. Our results suggest that two eye-intrinsic PLR mechanisms were present in early vertebrate evolution, whereas the brain-mediated PLR has a more recent origin.

Functional Specialization and Distributed Processing across Marmoset Lateral Prefrontal Subregions
A prominent aspect of the organization of primate lateral prefrontal cortex (lPFC) is its division into a number of cytoarchitecturally distinct subregions. Investigations in macaque lPFC using neurophysiological approaches have provided much insight into the functions associated with these subregions; however, our understanding is based largely on a patchwork of findings from many studies and across many animals, rarely covering the entire lPFC in individual subjects. Here, we leveraged the small size and lissencephalic cortex of the common marmoset (Callithrix jacchus) to characterize the responses of large numbers of single lPFC neurons to a diverse collection of test stimuli recorded across sets of lPFC subregions using high-density microelectrode arrays. Untethered extracellular electrophysiological recordings were obtained from two adult marmosets with 4 x 4 mm 96-channel Utah arrays implanted in lPFC, covering areas 8aD, 8aV, 9, 10, 46D, 46V and 47. We employed a test battery comprised of a variety of visual stimuli including faces and body parts, auditory stimuli including marmoset calls, and a spatial working memory task. Task-modulated units and units responsive to different stimulus modalities were distributed throughout the lPFC. Visual, auditory and call-selective units were distributed across all lPFC subregions. Neurons with contralateral visual receptive fields were found in 8aV and 8aD. Neurons responsive to faces and saccade-related units were found in 8aV, 8aD, 10, 46V and 47. These findings demonstrate that responses to some stimuli are relatively restricted within specific lPFC subregions, while others are more distributed throughout the marmoset lPFC.

Neuronal lysosome transfer to oligodendrocyte precursor cells: a novel mechanism of neuron-glia communication and its role in neurodegenerative disease
Oligodendrocyte precursor cells (OPCs) shape brain function through intricate regulatory mechanisms. Here, we observed that OPC processes establish connections with neuronal somata, with smaller lysosomes positioned near these contact sites. Tracking lysosomes demonstrated neuronal lysosomes were attracted to and released at these contact points, eventually becoming incorporated into OPC processes, suggesting a selective, OPC-evoked release of lysosomes from neuronal soma and their ingestion by OPCs, highlighting a unique lysosome-mediated communication between neurons and OPCs. Diminished branching of OPC processes resulted in fewer neuron-OPC contacts, fostering larger lysosome accumulation in neurons, altered neuronal activity and escalated prevalence of senescent neurons during aging. A similar reduction in OPC branching and neuronal lysosome accumulation was evident in an early-stage Alzheimer's disease mouse model. Together, these findings underscore the pivotal role of OPC processes in modulating neuronal activity through direct somatic contact and lysosome ingestion, presenting a prospective therapeutic avenue for addressing neurodegenerative diseases.

Time Cells in the Retrosplenial Cortex.
The retrosplenial cortex (RSC) is a key component of the brain's memory systems, with anatomical connections to the hippocampus, anterior thalamus, and entorhinal cortex. This circuit has been implicated in episodic memory and many of these structures have been shown to encode temporal information, which is critical for episodic memory. For example, hippocampal time cells reliably fire during specific segments of time during a delay period. Although RSC lesions are known to disrupt temporal memory, time cells have not been observed there. In the present study, we examined the firing patterns of RSC neurons during the intertrial delay period of two behavioral tasks, a blocked alternation task and a cued T-maze task. For the blocked alternation task, rats were required to approach the east or west arm of a plus maze for reward during different blocks of trials. Because the reward locations were not cued, the rat had to remember the goal location for each trial. In the cued T-maze task, the reward location was explicitly cued with a light and the rats simply had to approach the light for reward, so there was no requirement to hold a memory during the intertrial delay. Time cells were prevalent in the blocked alternation task, and most time cells clearly differentiated the east and west trials. We also found that RSC neurons could exhibit off-response time fields, periods of reliably inhibited firing. Time cells were also observed in the cued T-maze, but they were less prevalent and they did not differentiate left and right trials as well as in the blocked alternation task, suggesting that RSC time cells are sensitive to the memory demands of the task. These results suggest that temporal coding is a prominent feature of RSC firing patterns, consistent with an RSC role in episodic memory.

Prediction of brain age in individuals with and at risk for alcohol use disorder using brain morphological features
Brain age measures predicted from structural and functional brain features are increasingly being used to understand brain integrity, disorders, and health. While there is a vast literature showing aberrations in both structural and functional brain measures in individuals with and at risk for alcohol use disorder (AUD), few studies have investigated brain age in these groups. The current study examines brain age measures predicted using brain morphological features, such as cortical thickness and brain volume, in individuals with a lifetime diagnosis of AUD as well as in those at higher risk to develop AUD from families with multiple members affected with AUD (i.e., higher family history density (FHD) scores). The AUD dataset included a group of 30 adult males (mean age = 41.25 years) with a lifetime diagnosis of AUD and currently abstinent and a group of 30 male controls (mean age = 27.24 years) without any history of AUD. A second dataset of young adults who were categorized based on their FHD scores comprised a group of 40 individuals (20 males) with high FHD of AUD (mean age = 25.33 years) and a group of 31 individuals (18 males) with low FHD (mean age = 25.47 years). Brain age was predicted using 187 brain morphological features of cortical thickness and brain volume in an XGBoost regression model; a bias-correction procedure was applied to the predicted brain age. Results showed that both AUD and high FHD individuals showed an increase of 1.70 and 0.09 years (1.08 months), respectively, in their brain age relative to their chronological age, suggesting accelerated brain aging in AUD and risk for AUD. Increased brain age was associated with poor performance on neurocognitive tests of executive functioning in both AUD and high FHD individuals, indicating that brain age can also serve as a proxy for cognitive functioning and brain health. These findings on brain aging in these groups may have important implications for the prevention and treatment of AUD and ensuing cognitive decline.

Molecular Signatures of Normal Pressure Hydrocephalus: A Large-scale Proteomic Analysis of Cerebrospinal Fluid
Given the persistent challenge of differentiating idiopathic Normal Pressure Hydrocephalus (iNPH) from similar clinical entities, we conducted an in-depth proteomic study of cerebrospinal fluid (CSF) in 28 shunt-responsive iNPH patients, 38 Mild Cognitive Impairment (MCI) due to Alzheimers disease, and 49 healthy controls. Utilizing the Olink Explore 3072 panel, we identified distinct proteomic profiles in iNPH that highlight significant downregulation of synaptic markers and cell-cell adhesion proteins. Alongside vimentin and inflammatory markers upregulation, these results suggest ependymal layer and transependymal flow dysfunction. Moreover, downregulation of multiple proteins associated with congenital hydrocephalus (e.g., L1CAM, PCDH9, ISLR2, ADAMTSL2, and B4GAT1) points to a possible shared molecular foundation between congenital hydrocephalus and iNPH. Through orthogonal partial least squares discriminant analysis (OPLS-DA), a panel comprising 13 proteins has been identified as potential diagnostic biomarkers of iNPH, pending external validation. These findings offer novel insights into the pathophysiology of iNPH, with implications for improved diagnosis.

The TD drive - A parametric, open-source implant for multi-area electrophysiological recordings in behaving and sleeping rats
Intricate interactions between multiple brain areas underlie most functions attributed to the brain. The process of learning, as well as formation and consolidation of memories are two examples that rely heavily on functional connectivity across the brain. In addition, investigating hemispheric similarities and/or differences goes hand in hand with these multi-area interactions. Electrophysiological studies trying to further elucidate these complex processes thus depend on recording brain activity at multiple locations simultaneously and often in a bilateral fashion. Presented here is a 3D-printable implant for rats, named TD drive, capable of symmetric, bilateral wire electrode recordings, currently in up to ten distributed brain areas simultaneously. The open-source design was created employing parametric design principles, allowing prospective users to easily adapt the drive design to their needs by simply adjusting high-level parameters, such as anterior-posterior and medio-lateral coordinates of the recording electrode locations. The implant design was validated in n = 20 Lister Hooded rats that performed different tasks. The implant was compatible with tethered sleep recordings and open field recordings (Object Exploration) as well as wireless recording in a large maze (HexMaze 9x5 m) using two different commercial recording systems and headstages. In sum, presented here is the adaptable design and assembly of a new electrophysiological implant facilitating fast preparation and implantation.

Distinct neural bases of subcomponents of the attentional blink
The attentional blink reflects a ubiquitous bottleneck with selecting and processing the second of two targets that occur in close temporal proximity. An extensive literature has examined the attention blink as a unitary phenomenon, As a result, which specific component of attention - perceptual sensitivity or choice bias - is compromised during the attentional blink, and their respective neural bases, remains unknown. Here, we address this question with a multialternative task and novel signal detection model, which decouples sensitivity from bias effects. We find that the attentional blink impairs specifically one component of attention - sensitivity - while leaving the other component - bias - unaffected. Distinct neural markers of the attentional blink mapped on to distinct subcomponents of the sensitivity deficits. Parieto-occipital N2p and P3 potential amplitudes characterized target detection deficits whereas long-range high-beta band (20-30 Hz) coherence between frontoparietal electrodes signalled target discrimination deficits. We synthesized these results with representational geometry analysis. The analysis revealed that detection and discrimination deficits were encoded along separable neural dimensions, whose configural distances robustly correlated with the neural markers of each. Overall, these findings shed new light on subcomponents of the attentional blink, and reveal dissociable neural bases underlying its detection and discrimination bottlenecks.

Indirect Haptic Disturbances Enhance Motor Variability, with Divergent Effects on Skill Transfer
Research on motor learning has found evidence that learning rate is positively correlated with the learner's motor variability. However, it is still unclear how to robotically promote that variability without compromising the learner's sense of agency and motivation, which are crucial for motor learning. We propose a novel method to enhance motor variability during learning of a dynamic task by applying pseudorandom perturbing forces to the internal degree of freedom of the dynamic system rather than directly applying the forces to the learner's limb. Twenty healthy participants practiced swinging a virtual pendulum to hit oncoming targets, either with the novel method or without disturbances, to evaluate the effect of the method on motor learning, skill transfer, motivation, and agency. We evaluated skill transfer using two tasks, changing either the target locations or the task dynamics by shortening the pendulum rod. The indirect haptic disturbance method successfully increased participants' motor variability during training compared to training without disturbance. Although we did not observe group-level differences in learning, we observed divergent effects on skill generalization. The indirect haptic disturbances seemed to promote skill transfer to the altered task dynamics but limited transfer in the task with altered target positions. Motivation was not affected by the haptic disturbances, but future work is needed to determine if indirect haptic noise negatively impacts sense of agency. Increasing motor variability by indirect haptic disturbance is promising for enhancing skill transfer in tasks that incorporate complex dynamics. However, more research is needed to make indirect haptic disturbance a valuable tool for real-life motor learning situations.

Increasing the vitamin C transporter SVCT2 in microglia improves synaptic plasticity and restrains memory impairments in Alzheimer's disease models
Alzheimer's Disease (AD) is characterized by progressive cognitive decline and synaptic dysfunction, often associated with amyloid-beta accumulation and microglial alterations. Here, we investigate the role of the Sodium-dependent Vitamin C Transporter 2 (SVCT2) in microglia to modulate AD-like pathology in mice. Using a combination of RNA sequencing, advanced quantitative proteomics, electrophysiology, behavioral tests, high-throughput imaging, and microglial viral gene delivery, we explore the interplay between SVCT2 expression in microglia, amyloid-beta load, synaptic proteome changes, and synaptic plasticity. Our results demonstrate that SVCT2 expression in microglia decreases with age in the 5xFAD mice, correlating with memory deficits and alterations in synaptic mitochondrial proteome. Importantly, overexpression of SVCT2 in microglia leads to enhanced clearance of amyloid plaques and reconfiguration of the mitochondrial proteome landscape in the synapses, improving synaptic long-term plasticity (LTP) and memory performance. Our findings underscore the SVCT2 overexpression in microglia as a potent strategy to simultaneously decrease amyloid pathology and enhance synaptic function and memory performance, offering new avenues for therapeutic interventions in AD.

Low intensity repetitive transcranial magnetic stimulation enhances remyelination by newborn and surviving oligodendrocytes in the cuprizone model of toxic demyelination
In people with multiple sclerosis (MS), newborn and surviving oligodendrocytes (OLs) can contribute to remyelination, however, current therapies are unable to enhance or sustain endogenous repair. Low intensity repetitive transcranial magnetic stimulation (LI-rTMS), delivered as an intermittent theta burst stimulation (iTBS), increases the survival and maturation of newborn OLs in the healthy adult mouse cortex, but it is unclear whether LI-rTMS can promote remyelination. To examine this possibility, we fluorescently labelled oligodendrocyte progenitor cells (OPCs; Pdgfr-CreER transgenic mice) or mature OLs (Plp-CreER transgenic mice) in the adult mouse brain and traced the fate of each cell population over time. Multiple consecutive daily sessions of iTBS (600 pulses; 120 mT), delivered during cuprizone (CPZ) feeding, did not alter new or pre-existing OL survival but increased the number of myelin internodes elaborated by new OLs in the primary motor cortex (M1). This resulted in each new M1 OL producing ~471 micrometres more myelin. When LI-rTMS was delivered after CPZ withdrawal (during remyelination), it significantly increased the length of the internodes elaborated by new M1 and callosal OLs and increased the number of surviving OLs that contributed to remyelination in the corpus callosum (CC). As LI-rTMS can non-invasively promote remyelination by modifying the behaviour of new and surviving OLs, it may be suitable as an adjunct intervention to enhance remyelination in people with MS.

PKHD1L1 is required for stereocilia bundle maintenance, prolonged hearing function and enhanced resilience to noise exposure.
Sensory hair cells of the cochlea are essential for hearing, relying on the mechanosensitive stereocilia bundle at their apical pole for their function. Polycystic Kidney and Hepatic Disease 1-Like 1 (PKHD1L1) is a stereocilia protein required for normal hearing in mice, and for the formation of the transient stereocilia surface coat, expressed during early postnatal development. While the function of the stereocilia coat remains unclear, growing evidence supports PKHD1L1 as a human deafness gene. In this study we carry out in depth characterization of PKHD1L1 expression in mice during development and adulthood, analyze hair-cell bundle morphology and hearing function in aging PKHD1L1-defficient mouse lines, and assess their susceptibility to noise damage. Our findings reveal that PKHD1L1-deficient mice display no disruption to bundle cohesion or tectorial membrane attachment-crown formation during development. However, starting from 6 weeks of age, PKHD1L1-defficient mice display missing stereocilia and disruptions to bundle coherence. Both conditional and constitutive PKHD1L1 knock-out mice develop high-frequency hearing loss progressing to lower frequencies with age. Furthermore, PKHD1L1-deficient mice are susceptible to permanent hearing loss following low-level acoustic overexposure, which typically induces only temporary shifts in hearing thresholds. These results suggest a role for PKHD1L1 in establishing robust sensory hair bundles during development, necessary for maintaining bundle cohesion and function in response to acoustic trauma and aging.

Explainable Deep Learning Framework: Decoding Brain Task and Prediction of Individual Performance in False-Belief Task at Early Childhood Stage
Decoding of brain tasks aims to identify individuals' brain states and brain fingerprints to predict behavior. Deep learning provides an important platform for analyzing brain signals at different developmental stages to understand brain dynamics. Due to their internal architecture and feature extraction techniques, existing machine learning and deep-learning approaches for fMRI-based brain decoding must improve classification performance and explainability. The existing approaches also focus on something other than the behavioral traits that can tell about individuals' variability in behavioral traits. In the current study, we hypothesized that even at the early childhood stage (as early as 3 years), connectivity between brain regions could decode brain tasks and predict behavioural performance in false-belief tasks. To this end, we proposed an explainable deep learning framework to decode brain states (Theory of Mind and Pain states) and predict individual performance on ToM-related false-belief tasks in a developmental dataset. We proposed an explainable spatiotemporal connectivity-based Graph Convolutional Neural Network (Ex-stGCNN) model for decoding brain tasks. Here, we consider a dataset (age range: 3-12 yrs and adults, samples: 155 ) in which participants were watching a short, soundless animated movie, "Partly Cloudy," that activated Theory-of-Mind (ToM) and pain networks. After scanning, the participants underwent a ToM-related false-belief task, leading to categorization into the pass, fail, and inconsistent groups based on performance. We trained our proposed model using Static Functional Connectivity (SFC) and Inter-Subject Functional Correlations (ISFC) matrices separately. We observed that the stimulus-driven feature set (ISFC) could capture ToM and Pain brain states more accurately with an average accuracy of 94%, whereas it achieved 85% accuracy using SFC matrices. We also validated our results using five-fold cross-validation and achieved an average accuracy of 92%. Besides this study, we applied the SHAP approach to identify neurobiological brain fingerprints that contributed the most to predictions. We hypothesized that ToM network brain connectivity could predict individual performance on false-belief tasks. We proposed an Explainable Convolutional Variational Auto-Encoder model using functional connectivity (FC) to predict individual performance on false-belief tasks and achieved 90% accuracy.

Brain orchestra under spontaneous conditions: Identifying communication modules from the functional architecture of area V1
We used two-photon imaging to record from granular and supragranular layers in mouse primary visual cortex (V1) under spontaneous conditions and applied an extension of the spike time tiling coefficient (STTC; introduced by Cutts and Eglen) to map functional connectivity architecture within and across layers. We made several observations: Approximately, 19-34% of neuronal pairs within 300um of each other exhibit statistically significant functional connections, compared to ~10% at distances of 1mm or more. As expected, neuronal pairs with similar tuning functions exhibit a significant, though relatively small, increase in the fraction of functional inter-neuronal correlations. In contrast, internal state as reflected by pupillary diameter or aggregate neuronal activity appears to play a much stronger role in determining inter-neuronal correlation distributions and topography. Overall, inter-neuronal correlations appear to be slightly more prominent in layer 4. The first-order functionally connected neighbors of neurons determine the hub structure of the V1 microcircuit. Layer 4 exhibits a nearly flat degree of connectivity distribution, extending to higher values than seen in supragranular layers, whose distribution drops exponentially. In all layers, functional connectivity architecture exhibits small-world characteristics and network robustness. The probability of firing of layer 2/3 pyramidal neurons can be predicted as a function of the aggregate activity in their first-order functionally connected partners within layer 4, which represent their putative input group. The functional form of this prediction conforms well to a ReLU function, reaching up to firing probability one in some neurons. Interestingly, the properties of layer 2/3 pyramidal neurons differ based on the size of their Layer 4 functional connectivity group. Specifically, layer 2/3 neurons with small Layer-4 degrees of connectivity appear to be more sensitive to the firing of their Layer 4 functional connectivity partners, suggesting they may be more effective at transmitting synchronous activity downstream from layer 4. They also appear to fire largely independently from each other, compared to neurons with high layer-4 degrees of connectivity, and are less modulated by changes in pupil size and aggregate population dynamics. Information transmission is best viewed as occurring from neuronal ensembles in layer 4 to neuronal ensembles in layer 2/3. Under spontaneous conditions, we were able to identify such candidate neuronal ensembles, which exhibit high sensitivity, precision, and specificity for L4 to L2/3 information transmission. In sum, functional connectivity analysis under spontaneous activity conditions reveals a modular neuronal ensemble architecture within and across granular and supragranular layers of mouse primary visual cortex. Furthermore, modules with different degrees of connectivity appear to obey different rules of engagement and communication across the V1 columnar circuit.

Activation of locus coeruleus noradrenergic neuronsrapidly drives homeostatic sleep pressure
Homeostatic sleep regulation is essential for optimizing the amount and timing of sleep, but the underlying mechanism remains unclear. Optogenetic activation of locus coeruleus noradrenergic neurons immediately increased sleep propensity following transient wakefulness. Fiber photometry showed that repeated optogenetic or sensory stimulation caused rapid declines of locus coeruleus calcium activity and noradrenaline release. This suggests that functional fatigue of noradrenergic neurons, which reduces their wake-promoting capacity, contributes to sleep pressure.

Network Analysis of the Cerebrospinal Fluid Proteome Reveals Shared and Unique Differences Between Sporadic and Familial Forms of Amyotrophic Lateral Sclerosis
Background: Amyotrophic Lateral Sclerosis (ALS), a neurodegenerative disease involving loss of motor neurons, typically results in death within 3-5 years of disease onset. Although roughly 10 % of cases can be linked to a specific inherited mutation (e.g., C9orf72 hexanucleotide repeat expansion or SOD1 mutation), the cause of the majority of cases is unknown. Consequently, there is a critical need for biomarkers that reflect disease onset and progression across ALS subgroups. Methods: We employed tandem mass tag mass spectrometry (TMT-MS) based proteomics on cerebrospinal fluid (CSF) to identify and quantify 2105 proteins from ALS patients with sporadic disease (n=35), C9orf72 ALS (n=10), and SOD1 ALS (n=6), as well as age-matched healthy controls (n=44) and asymptomatic C9orf72 carriers (n=6). We used differential protein abundance and network analyses to determine how protein profiles vary across disease types in ALS CSF. Results: Integrated differential and co-expression network analysis identified proteomic differences between ALS and control, and differentially abundant proteins between sporadic, C9orf72 and SOD1 ALS. Groups of proteins also differentiated asymptomatic C9orf72 mutation carriers from those with C9orf72 ALS, marking a pre-symptomatic proteomic signature of C9orf72 ALS. Similarly, additional proteins differentiated asymptomatic from controls. Leveraging additional publicly available ALS and AD proteomic datasets, we validated our ALS CSF network and identified ALS-specific proteins within Module 5 (M5)-Extracellular matrix (e.g., IGF2, RARRES2, LGALS3, GALNT15, and LYZ) and shared biomarkers across neurodegenerative diseases linked to Module 10 (M10)-Ubiquitination/Gluconeogenesis (e.g., NEFL, NEFM, CHIT1, and CHI3L1). Conclusions: This study represents a comprehensive analysis of the CSF proteome across sporadic and genetic causes of ALS that resolves differences among these disease subgroups and points to varying pathogenic pathways that result in disease.

Secondary microglia formation center in the human fetal brain
Yolk sac-derived microglia migrate and populate the brain during development, constituting 10-15% of the total brain cells. The human brain is the largest and most complex brain with the highest cognitive capacity among all species. Therefore, the limitations of rodent brain studies in interpreting the human brain are evident. By co immunostaining microglia in 50 um fetal brain sections from 7.5 to 16 gestational weeks (gw) and combining high-resolution scanning, we identified a highly proliferative microglia aggregate (0.108-2.129 mm2) that expanded in Down's Syndrome fetal brain (4.168 mm2) and was located near the ganglion eminence, in which Ki67+ microglia accounted for 23.4% of total microglia compared to 6.3% in other brain regions. The microglia in the aggregates lack phagocytic bulbs, membrane ruffles, and long/branching processes compared to microglia in other brain regions. Introducing human microglia into cortical organoids, but not macrophages, replicated proliferative microglial aggregates on the brain organoid surface and sufficiently penetrated deeper regions of the cortical organoids. Penetrating microglia display phagocytic capacity, enhance immunity, and accelerate the maturation of brain organoids. The large proliferative microglial aggregate may be a unique secondary microglial formation center in the human fetal brain to compensate for the enormous microglial demands during brain expansion.

miR-155-5p/miR-674-3p presence in peripheral blood leukocytes and relative proportion of white blood cell types as biomarkers of asymptomatic and symptomatic phases of temporal lobe epilepsy
Epilepsy frequently develops as a result of brain insult, for example, brain injury or stroke. Currently, there are no tools allowing us to predict which trauma patients will eventually develop epilepsy. There is evidence that microRNAs levels are altered in the blood, making them attractive candidates for peripheral biomarkers of epilepsy. We analyzed white blood cell subpopulations containing miR-155-5p and miR-674-3p, in control and stimulated animals and in control and symptomatic or asymptomatic animals in the amygdala stimulation model. The first proposed early biomarker of epilepsy is the relative proportion of CD45RA+ B cells containing miR-155-5p and/or miR-674-3p. Others are increased number of CD45RA+ B cells containing either miR-155-5p or miR-155-5p and miR-674-3p together or decreased number of CD161+ NK cells not containing miR-155-5p nor miR-674-3p. Additionally, we found that the decreased number of CD4+ T cells can be used as a potential biomarker for identifying epileptic animals with symptomatic epilepsy.

Quadriceps-hamstrings muscle co-activation during the swing phase of walking is modulated by task constraints in healthy adults
Background: Muscle co-activation, the simultaneous activation of muscle groups, is a common strategy to stabilize walking. However, co-activation can also be the consequence of underlying neurological impairments. This complicates differentiation between functional and pathological co-activation during walking. To better understand and discern functional co-activation during walking, this study investigated the difference between quadriceps-hamstrings co-activation during the swing phase of walking and isolated leg-swinging in healthy adults. Methods: Twelve healthy young adults performed walking and isolated leg-swinging at slow (0.6 m/s) and comfortable speed. Electromyography signals from m. vastus lateralis, m. rectus femoris, m. biceps femoris, and m. semitendinosus were recorded. Co-activation index (CI) was calculated using Pearson correlation coefficient and area under the curve (AUC) and averaged to one quadriceps-hamstrings CI per metric. Results: The results showed a higher Pearson-CI during walking compared to isolated leg-swinging, specifically during mid- and terminal-swing at both speeds. AUC-CI, but not Pearson-CI was significantly different between the two speeds. Conclusion: Quadriceps-hamstrings co-activation towards the end of the swing phase during walking reflects preparation for heel-strike, which is not present in isolated leg-swinging. Therefore, an isolated leg-swinging task could serve as a feasible method to distinguish pathological from functional muscle co-activation during walking.

Measuring instability in chronic human intracortical neural recordings towards stable, long-term brain-computer interfaces
Intracortical brain-computer interfaces (iBCIs) enable people with tetraplegia to gain intuitive cursor control from movement intentions. To translate to practical use, iBCIs should provide reliable performance for extended periods of time. However, performance begins to degrade as the relationship between kinematic intention and recorded neural activity shifts compared to when the decoder was initially trained. In addition to developing decoders to better handle long-term instability, identifying when to recalibrate will also optimize performance. We propose a method to measure instability in neural data without needing to label user intentions. Longitudinal data were analyzed from two BrainGate2 participants with tetraplegia as they used fixed decoders to control a computer cursor spanning 142 days and 28 days, respectively. We demonstrate a measure of instability that correlates with changes in closed-loop cursor performance solely based on the recorded neural activity (Pearson r = 0.93 and 0.72, respectively). This result suggests a strategy to infer online iBCI performance from neural data alone and to determine when recalibration should take place for practical long-term use.

Specifying the orthographic prediction error for a better understanding of efficient visual word recognition in humans and machines
Recent evidence suggests that readers optimize low-level visual information following the principles of predictive coding. Based on a transparent neurocognitive model, we postulated that readers optimize their percept by removing redundant visual signals, which allows them to focus on the informative aspects of the sensory input, i.e., the orthographic prediction error (oPE). Here, we test alternative oPE implementations by assuming all-or-nothing signaling units based on multiple thresholds and compare them to the original oPE implementation. For model evaluation, we implemented the comparison based on behavioral and electrophysiological data (EEG at 230, 430 ms). We found the highest model fit for the oPE with a 50% threshold integrating multiple prediction units for behavior and the late EEG component. The early EEG component was still explained best by the original hypothesis. In the final evaluation, we used image representations of both oPE implementations as input to a deep-neuronal network model (DNN). We compared the lexical decision performance of the DNN in two tasks (words vs. consonant strings; words vs. pseudowords) to the performance after training with unaltered word images and found better DNN performance when trained with the 50% oPE representations in both tasks. Thus, the new formulation is adequate for late but not early neuronal signals and lexical decision behavior in humans and machines. The change from early to late neuronal processing likely reflects a transformation in the representational structure over time that relates to accessing the meaning of words.

Machine learning-based spike sorting reveals how subneuronal concentrations of monomeric Tau cause a loss in excitatory postsynaptic currents in hippocampal neurons
Extracellular recordings of neuronal activity constitute a powerful tool for investigating the intricate dynamics of neural networks and the activity of individual neurons. Microelectrode arrays (MEAs) allow for recordings with a high electrode count, ranging from 10s to 1000s, generating extensive datasets of neuronal information. Furthermore, MEAs capture extracellular field potentials from cultured cells, resulting in highly complex neuronal signals that necessitate precise spike sorting for meaningful data extraction. Nevertheless, conventional spike sorting methods face limitations in recognising diverse spike shapes, thereby constraining the full utilisation of the rich dataset acquired from MEA recordings. To overcome these limitations, we have developed a machine learning algorithm, named PseudoSort, which employs advanced self-supervised learning techniques, a distinctive density-based pseudo-labelling strategy, and an iterative fine-tuning process to enhance spike sorting accuracy. Through extensive benchmarking on large-scale simulated datasets, we demonstrate the superior performance of PseudoSort compared to recently developed machine learning-based (ML) spike sorting algorithms. We showcase the practical application of PseudoSort by utilising MEA recordings from hippocampal neurons exposed to subneuronal concentrations of monomeric Tau, a protein associated with Alzheimer's disease (AD). Our results, validated against patch clamp experiments, unveil that monomeric Tau at subneuronal concentrations induces stimulation-dependent disruptions in both local and global activity of hippocampal neurons. Remarkably, patch clamp electrophysiology highlights the effect of combined Tau and neuronal stimulation treatment on excitatory postsynaptic currents, whereas PseudoSort excels in identifying neuronal clusters that exhibit diminished firing capacity following Tau treatment alone, i.e., in the absence of stimulation. This comprehensive approach validates the prowess of PseudoSort and unravels the intricate effects of Tau on neuronal activity, particularly in the context of AD.

Prostaglandin D2 synthase controls Schwann cells metabolism
We previously reported that in the absence of Prostaglandin D2 synthase (LPGDS) peripheral nerves are hypomyelinated in development and that with aging they present aberrant myelin sheaths. We now demonstrate that glial LPGDS is part of a coordinated program that preserves myelin integrity. In vivo and in vitro lipidomic, metabolomic and transcriptomic analyses confirmed that myelin lipids composition, Schwann cells energetic metabolism and key enzymes controlling these processes are altered in the absence of LPGDS. Moreover, Schwann cells undergo a metabolic rewiring and turn to acetate as the main energetic source. Further, they produce ketone bodies to ensure glial cell and neuronal survival, describing the first physiological pathway implicated in preserving PNS myelin. All these changes correlate with morphological myelin alterations. We posit that myelin lipids serve as a reservoir to provide ketone bodies, which together with acetate represent the adaptive substrates Schwann cells can rely on to sustain the axoglial unit and preserve PNS integrity.

Delineating Transdiagnostic Subtypes in Neurodevelopmental Disorders via Contrastive Graph Machine Learning of Brain Connectivity Patterns
Neurodevelopmental disorders, such as Attention Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD), are characterized by comorbidity and heterogeneity. Identifying distinct subtypes within these disorders can illuminate the underlying neurobiological and clinical characteristics, paving the way for more tailored treatments. We adopted a novel transdiagnostic approach across ADHD and ASD, using cutting-edge contrastive graph machine learning to determine subtypes based on brain network connectivity as revealed by resting-state functional magnetic resonance imaging. Our approach identified two generalizable subtypes characterized by robust and distinct functional connectivity patterns, prominently within the frontoparietal control network and the somatomotor network. These subtypes exhibited pronounced differences in major cognitive and behavioural measures. We further demonstrated the generalizability of these subtypes using data collected from independent study sites. Our data-driven approach provides a novel solution for parsing biological heterogeneity in neurodevelopmental disorders.

Social transmission of inflammation in mice
The ability to detect and respond to sickness in others promotes survival. Here we show that mouse dams respond to immune challenged pups by mirroring their inflammatory response. Thus, dams with pups subjected to immune challenge displayed a marked induction of inflammatory mediators in both the brain and the periphery, accompanied by an increase in maternal behaviors and corticosterone levels. This social transmission of inflammation did not require physical contact, and it contributed to the stress hormone response in the dams. In adult dyads, interaction with an immune challenged cagemate did not elicit robust inflammatory signaling but induced an increased responsiveness to a subsequent immune challenge. The identification of social transmission of inflammation, or inflammatory responsiveness, may open new avenues for research on social behavior, just like the description of similar phenomena such as observational fear and transmitted pain have done.

Alpha-synuclein regulates the repair of genomic DNA double-strand breaks in a DNA-PKcs-dependent manner
-synuclein (Syn) is a presynaptic and nuclear protein that aggregates in important neurodegenerative diseases such as Parkinson's Disease (PD), Parkinson's Disease Dementia (PDD) and Lewy Body Dementia (LBD). Our past work suggests that nuclear Syn may regulate forms of DNA double-strand break (DSB) repair in HAP1 cells after DNA damage induction with the chemotherapeutic agent bleomycin1. Here, we report that genetic deletion of Syn specifically impairs the non-homologous end-joining (NHEJ) pathway of DSB repair using an extrachromosomal plasmid-based repair assay in HAP1 cells. Importantly, induction of a single DSB at a precise genomic location using a CRISPR/Cas9 lentiviral approach also showed the importance of Syn in regulating NHEJ in HAP1 cells and primary mouse cortical neuron cultures. This modulation of DSB repair is dependent on the activity of the DNA damage response signaling kinase DNA-PKcs, since the effect of Syn loss-of-function is reversed by DNA-PKcs inhibition. Using in vivo multiphoton imaging in mouse cortex after induction of Syn pathology, we find an increase in longitudinal cell survival of inclusion-bearing neurons after Polo-like kinase (PLK) inhibition, which is associated with an increase in the amount of aggregated Syn within inclusions. Together, these findings suggest that Syn plays an important physiologic role in regulating DSB repair in both a transformed cell line and in primary cortical neurons. Loss of this nuclear function may contribute to the neuronal genomic instability detected in PD, PDD and DLB and points to DNA-PKcs and PLK as potential therapeutic targets.

Synfire Chain Dynamics Unravelling Theta-nested Gamma Oscillations for Balancing Prediction and Dodge in Navigation
Theta-nested gamma oscillations, widely observed in experiments, play a crucial role in navigation, yet their functional roles and the origin of the positive correlation between theta frequency and motion velocity remain unclear. We propose that the object's survival relies on both prediction and dodge - predicting future events and staying alert to unpredictable ones, the latter of which has seldom been considered in goal-navigation tasks. By building a biologically plausible spiking neuronal network model and reproducing experimental results, we leverage synfire chain properties - length and separation - to elucidate the functional roles of theta-nested gamma oscillations: theta oscillations for self-location awareness, gamma oscillations for predictive capabilities and their coupling for enhancing functionality. The positive correlation between theta frequency and motion velocity is demonstrated to optimally balance representing predictable events for planning and staying alert to unexpected events. Our study offers a new avenue for unravelling the neural mechanisms of navigation.

Remembrance with gazes passed: Eye movements precede continuous recall of episodic details of real-life events
Autobiographical memory entails reconstructing the visual features of past events. Eye movements are associated with vivid autobiographical recollection, but this research has yet to capitalize on the high temporal resolution of eye-tracking data. We aligned eye movement data with participants' simultaneous free recall of a verified real-life event, allowing us to assess the temporal correspondence of saccades to production of episodic and non-episodic narrative content at the millisecond level. Eye movements reliably predicted subsequent episodic - but not non-episodic - details by 250-1100 ms, suggesting that they facilitate episodic recollection by reinstating spatiotemporal context during vivid recollection. Assessing the relationship of oculomotor responses to naturalistic memory informs theory as well as diagnosis and treatment of conditions involving pathological recollection, such as Alzheimer's disease and post-traumatic stress disorder (PTSD).

Frequency-tagging of spatial attention using periliminal flickers
Steady-State Visually Evoked Potentials (SSVEP) manifest as a sustained rhythmic activity that can be observed in surface electroencephalography (EEG) in response to periodic visual stimuli, commonly referred to as flickers. SSVEPs are widely used in fundamental cognitive neuroscience paradigms and Brain-Computer Interfaces (BCI) due to their robust and rapid onset. However, they have drawbacks related to the intrusive saliency of flickering visual stimuli, which may induce eye strain, cognitive fatigue, and biases in visual exploration. Previous findings highlighted the potential of altering features of flicker stimuli to improve user experience. In this study, we propose to reduce the amplitude modulation depth of flickering stimuli down to the individuals' perceptual visibility threshold (periliminal) and below (subliminal). The stimulus amplitude modulation depth represents the contrast difference between the two alternating states of a flicker. A simple visual attention task where participants responded to the presentation of spatially-cued target stimuli (left and right) was used to assess the validity of such periliminal and subliminal frequency-tagging probes to capture spatial attention. The left and right sides of the screen, where target stimuli were presented, were covered by large flickers (13 and 15 Hz respectively). The amplitude modulation depth of these flickers was manipulated across three conditions: control, periliminal, and subliminal. The latter two levels of flickers amplitude modulation depth were defined through a perceptual visibility threshold protocol on a single-subject basis. Subjective feedback indicated that the use of periliminal and subliminal flickers substantially improved user experience. The present study demonstrates that periliminal and subliminal flickers evoked SSVEP responses that can be used to derive spatial attention in frequency-tagging paradigms. The single-trial classification of attended space (left versus right) based on SSVEP response reached an average accuracy of 81.1% for the periliminal and 58% for the subliminal conditions. These findings reveal the promises held by the application of inconspicuous flickers to both cognitive neuroscience research and BCI development.

Assessing the Effects of Various Physiological Signal Modalities on Predicting Different Human Cognitive States
Robust estimation of systemic human cognitive states is critical for a variety of applications, from simply detecting inefficiencies in task assignments, to the adaptation of artificial agents behaviors to improve team performance in mixed-initiative human-machine teams. This study showed that human eye gaze, in particular, the percentage change in pupil size (PCPS), is the most reliable biomarker for assessing three human cognitive states including workload, sense of urgency, and mind wandering compared to electroencephalogram (EEG), functional near-infrared spectroscopy (fNIRS), respiration, and skin conductance. We used comprehensive multi-modal driving dataset to examine the accuracy of signals to assess these cognitive states. We performed comprehensive statistical tests to validate the performance of several physiological signals to determine human cognitive states and demonstrated that PCPS shows noticeably superior performance. We also characterized the link between workload and sense of urgency with eye gaze and observed that consecutive occurrences of higher sense of urgency were prone to increase overall workload. Finally, we trained five machine learning (ML) models and showed that four of them had similar accuracy in cognitive state classification (with one, random forest, showing inferior performance). The results provided evidence that the PCPS is a reliable physiological marker for cognitive state estimation.

Prioritizing replay when future goals are unknown
Although hippocampal place cells replay nonlocal trajectories, the computational function of these events remains controversial. One hypothesis, formalized in a prominent reinforcement learning account, holds that replay plans routes to current goals. However, recent puzzling data appear to contradict this perspective by showing that replayed destinations lag current goals. These results may support an alternative hypothesis that replay updates route information to build a "cognitive map." Yet no similar theory exists to formalize this view, and it is unclear how such a map is represented or what role replay plays in computing it. We address these gaps by introducing a theory of replay that learns a map of routes to candidate goals, before reward is available or when its location may change. Our work extends the planning account to capture a general map-building function for replay, reconciling it with data, and revealing an unexpected relationship between the seemingly distinct hypotheses.