bioRxiv Subject Collection: Neuroscience's Journal

Interactions between saccades and smooth pursuit eye movements in marmosets
Animals use a combination of eye-movements to track moving objects in the visual world. The different movement types need to coordinate for successful tracking, requiring interaction between the systems involved. Here, we study such interaction between the saccades and smooth pursuit eye movement system in marmosets. Using single target pursuit, we show that saccades cause an enhancement in pursuit following the saccades. Using two-target task, we show that this enhancement in pursuit is selective towards target motion of the target selected by the saccade, irrespective of any biases in pursuit prior to the saccade. Together, our experiments highlight the similarities in the functioning of saccade and smooth pursuit eye movement systems across primates.

Acquisition phase-specific contribution of climbing fiber transmission to cerebellum-dependent motor memory
Climbing fiber (CF) transmission from the inferior olivary triggers complex spikes (Cs) in Purkinje cells (PCs) driven by a burst of calcium spikes. In the context of motor learning, especially the compensatory optic response, CF transmission serves as instructive signals selectively conveyed to PCs. While the significance of CF input in motor memory formation is widely acknowledged, a comprehensive understanding of its distinct contribution across different temporal windows, spanning from the initial phase of learning to the retrieval period, remains incomplete. Therefore, we aimed to investigate the necessity of CF-induced instructive signals in motor learning by assessing their roles in memory acquisition, consolidation, and retrieval. We employed optogenetics to selectively inhibit CF transmission during targeted time windows. Consequently, the absence of CF-induced instructive signals during motor learning impairs memory acquisition. However, when these signals were suppressed during the consolidation and retrieval period, there was neither a loss of long-term memory nor prevention of memory retrieval. Our results highlight that CF transmission plays a specialized and critical role primarily in memory acquisition, rather than in subsequent processes.

Self-organized emergence of modularity, hierarchy, and mirror reversals from competitive synaptic growth in a developmental model of the visual pathway
A hallmark of the primate visual system is its architectural organization consisting of multiple distinct (modular) areas that connect hierarchically. These areas exhibit specific spatial organization on the cortical sheet, with primary visual cortex at the center and subsequent regions in the hierarchy encircling the earlier one, and detailed topological organization, with retinotopy in each area but striking mirror reversals across area boundaries. The developmental rules that drive the simultaneous formation of these architectural, spatial, and topographic aspects of organization are unknown. Here we demonstrate that a simple synaptic growth rule driven by spontaneous activity and heterosynaptic competition generates a detailed connectome of the visual pathway, with emergence of all three types of organization. We identify a theoretical principle -- local greedy wiring minimization via spontaneous drive (GWM-S) -- implemented by the mechanism, and use this insight to propose biologically distinct growth rules that predict similar endpoints but testably distinguishable developmental trajectories. The same rules predict how input geometry and cortical geometry together drive emergence of hierarchical, convolution-like, spatially and topographically organized sensory processing pathways for different modalities and species, providing a possible explanation for the observed pluripotency of cortical structure formation. We find that the few parameters governing structure emergence in the growth rule constitute simple knobs for rich control, that could (potentially genetically) encode a projection neuron-like connectivity patterns and interneuron-like ones. In all, the presented rules provide a parsimonious mechanistic model for the organization of sensory cortical hierarchies even without detailed genetic cues for features like map reversal, and provide numerous predictions for experiment during normal and perturbed development.

A developmental brain-wide screen identifies retrosplenial cortex as a key player in the emergence of persistent memory
Memories formed early in life are short-lived while those formed later persist. Recent work revealed that infant memories are stored in a latent state. But why they fail to be retrieved is poorly understood. Here we investigated brain-wide circuit mechanisms underlying infantile amnesia in mice. We performed a screen that combined activity-dependent neuronal tagging at different postnatal ages, tissue clearing and light sheet microscopy. We observed striking developmental transitions in the organization of fear memory networks and changes in the activity and functional connectivity of the retrosplenial cortex (RSP) that aligned with the emergence of persistent memory. 7 days after learning, chemogenetic reactivation of tagged RSP ensembles enhanced memory in adults but not in infants. But after 33 days, reactivating infant-tagged RSP ensembles recovered forgotten memories. These studies show that RSP ensembles store latent infant memories, reveal the time course of RSP functional maturation, and suggest that immature RSP functional networks contribute to infantile amnesia.

The Subcortical Atlas of the Marmoset (SAM) monkey based on high-resolution MRI and histology
A comprehensive three-dimensional digital brain atlas of cortical and subcortical regions based on MRI and histology has a broad array of applications for anatomical, functional, and clinical studies. We first generated a Subcortical Atlas of the Marmoset, called the SAM, from 251 delineated subcortical regions (e.g., thalamic subregions, etc.) derived from the high-resolution MAP-MRI, T2W, and MTR images ex vivo. We then confirmed the location and borders of these segmented regions in MRI data using matched histological sections with multiple stains obtained from the same specimen. Finally, we estimated and confirmed the atlas-based areal boundaries of subcortical regions by registering this ex vivo atlas template to in vivo T1- or T2W MRI datasets of different age groups (single vs. multisubject population-based marmoset control adults) using a novel pipeline developed within AFNI. Tracing and validating these important deep brain structures in 3D improves neurosurgical planning, anatomical tract tracer injections, navigation of deep brain stimulation probes, fMRI and brain connectivity studies, and our understanding of brain structure-function relationships. This new ex vivo template and atlas are available as volumes in standard NIFTI and GIFTI file formats and are intended for use as a reference standard for marmoset brain research.

Poor decision making and sociability impairment following central serotonin reduction in inducible TPH2-knockdown rats
Serotonin is an essential neuromodulator for mental health and animals socio-cognitive abilities. However, we previously found that a constitutive depletion of central serotonin did not impair rat cognitive abilities in stand-alone tests. Here we investigated how a mild and acute decrease of brain serotonin would affect rats cognitive abilities. Using a novel rat model of inducible serotonin depletion via the genetic knock-down of tryptophan hydroxylase 2 (TPH2), we achieved 20% decrease of serotonin levels in the hypothalamus after three weeks of non-invasive oral doxycycline administration. Decision making in the Rat Gambling Task and the Probability Discounting Task, cognitive flexibility and social recognition memory were tested in low-serotonin (Tph2-kd) and control rats. Our results showed that the Tph2-kd rats were more prone to choose disadvantageously on the long term (poor decision making) and that only the low-serotonin poor decision makers were more sensitive to probabilistic discounting and had poorer social recognition memory than other low-serotonin and control individuals. Flexibility was unaffected by the acute brain serotonin reduction. Poor social recognition memory was the most central characteristic of the behavioral network of low-serotonin poor decision makers, suggesting a key role of social recognition in expression of their profile. The acute decrease of brain serotonin appeared to specifically amplify cognitive impairments of the subgroup of individuals also identified as poor decision makers in the population. This study highlights the great opportunity Tph2-kd rat model offers to study inter-individual susceptibilities to develop cognitive impairment following mild variations of brain serotonin in otherwise healthy individuals. These transgenic and differential approaches together could be critical for the identification of translational markers and vulnerabilities in the development of mental disorders.

Identification of Novel Biomarkers for Alzheimer's Disease and Related Dementias Using Unbiased Plasma Proteomics
Alzheimer's disease (AD) and related dementias (ADRD) is a complex disease with multiple pathophysiological drivers that determine clinical symptomology and disease progression. These diseases develop insidiously over time, through many pathways and disease mechanisms and continue to have a huge societal impact for affected individuals and their families. While emerging blood-based biomarkers, such as plasma p-tau181 and p-tau217, accurately detect Alzheimer neuropthology and are associated with faster cognitive decline, the full extension of plasma proteomic changes in ADRD remains unknown. Earlier detection and better classification of the different subtypes may provide opportunities for earlier, more targeted interventions, and perhaps a higher likelihood of successful therapeutic development. In this study, we aim to leverage unbiased mass spectrometry proteomics to identify novel, blood-based biomarkers associated with cognitive decline. 1,786 plasma samples from 1,005 patients were collected over 12 years from partcipants in the Massachusetts Alzheimer's Disease Research Center Longitudinal Cohort Study. Patient metadata includes demographics, final diagnoses, and clinical dementia rating (CDR) scores taken concurrently. The Proteograph Product Suite (Seer, Inc.) and liquid-chromatography mass-spectrometry (LC-MS) analysis were used to process the plasma samples in this cohort and generate unbiased proteomics data. Data-independent acquisition (DIA) mass spectrometry results yielded 36,259 peptides and 4,007 protein groups. Linear mixed effects models revealed 138 differentially abundant proteins between AD and healthy controls. Machine learning classification models for AD diagnosis identified potential candidate biomarkers including MBP, BGLAP, and APoD. Cox regression models were created to determine the association of proteins with disease progression and suggest CLNS1A, CRISPLD2, and GOLPH3 as targets of further investigation as potential biomarkers. The Proteograph workflow provided deep, unbiased coverage of the plasma proteome at a speed that enabled a cohort study of almost 1,800 samples, which is the largest, deep, unbiased proteomics study of ADRD conducted to date.

Behaviour-based movement cut-off points in 3-year old children comparing wrist- with hip-worn actigraphs MW8 and GT3X
Introduction: Behaviour-based physical intensities have not undergone rigorous calibration in long-term recordings of 3-year-old childrens sleep/activity patterns. This study aimed at (i) calibrating activity counts of motor behaviour measured simultaneously with MotionWatch 8 (MW8) and ActiGraph (GT3X) in 3-year-old children, (ii) documenting movement intensities in 30s-epochs at wrist/hip positions, and (iii) evaluating the accuracy of cut-off agreements between different behavioural activities. Methods: Thirty 3-year-old children of the NorthPop cohort performed six directed behavioural activities individually, each for 8-10 minutes while wearing two pairs of devices at hip and wrist position. Directly observed naturally-occurring behaviours included: watching cartoons, recumbent story listening, sit and handcraft, floor play with toys, engaging in a walk and a sprinting game. Receiver-Operating-Curve classification was applied to determine activity count thresholds and to assign context-guided, physical activity composite classes. Results: Activity counts of MW8 and GT3X pairs of wrist-worn (r = 0.94) and hip-worn (r = 0.79) devices correlated significantly (p < 0.001). Activity counts at hip position were significantly lower compared to those at the wrist position (p < 0.001), irrespective of device type. Sprinting, floorball/walk and floorplay assigned as "Physically Mobile" classes achieved outstanding accuracy (AUC >0.9) and two sedentary and a motionless activities assigned into "Physically Stationary" classes achieved excellent accuracy (AUC >0.8). Conclusion: This study provides useful cut-offs for physical activity levels of preschool children using two different devices. Contextual information of behaviour is advantageous over intensity classifications only, because interventions reallocate time among behaviours, which allows to establish dose-response relationships between behavioural changes and health outcomes. Our comparative calibration is one step forward to inform behaviour-based public health guidelines for 3-year-old children.

The suprapyramidal and infrapyramidal blades of the dentate gyrus exhibit different GluN subunit content and dissimilar frequency-dependent synaptic plasticity in vivo
The entorhinal cortex sends afferent information to the hippocampus by means of the perforant path(PP), whereby the medial PP (MPP) is believed to convey information about spatial context and the lateral PP (LPP) may convey information about item identity. This information is encoded by means of synaptic plasticity. The PP input to the dentate gyrus(DG) terminates in the suprapyramidal (upper/inner) and infrapyramidal (lower/outer) blades. To what extent frequency-dependent synaptic plasticity in these blades differs is unclear. Here, we compared MPP-DG responses in the supra- (sDG) and infrapyramidal blades (iDG) of freely behaving adult rats and found that synaptic plasticity in the sDG is broadly frequency-dependent whereby long-term depression (LTD, >24h) is induced with stimulation at 1Hz, short-term depression (<2h) is triggered by 5 or 10Hz and long-term potentiation (LTP) of increasing magnitudes is induced by 200 and 400 Hz stimulation, respectively. By contrast, although the iDG expresses STD following 5 or 10Hz stimulation, LTD induced by 1Hz is weaker, LTP is not induced by 200Hz and LTP induced by 400Hz stimulation is significantly smaller in magnitude and is less persistent (<4h) compared to LTP in sDG. Furthermore, the stimulus-response relationship of the iDG is suppressed compared to sDG. Patch clamp recordings, in vitro, revealed reduced firing frequencies in response to high currents, and different action potential thresholds in iDG compared to sDG. Assessment of the expression of GluN subunits revealed significantly lower expression levels of GluN1, GluN2A and GluN2B in iDG compared to sDG. Taken together, these data indicate that synaptic plasticity in the infrapyramidal blade of the dentate gyrus is weaker, less persistent and less responsive to afferent frequencies than synaptic plasticity in sDG. Effects may be mediated by weaker NMDA receptor expression in iDG. These characteristics may explain reported differences in experience-dependent information processing in sDG versus iDG.

The cervical and meningeal lymphatic network as a pathway for retrograde nanoparticle transport to the brain
The meningeal lymphatic vessels have been described as a pathway that transports cerebrospinal fluid and interstitial fluid in a unidirectional manner towards the deep cervical lymph nodes. However, these vessels exhibit anatomical and molecular characteristics typical of initial lymphatic vessels, with the absence of surrounding smooth muscle and few or absent valves. Given its structure, this network could theoretically allow for bidirectional motion. Nevertheless, it has not been assessed as a potential route for nanoparticles to travel from peripheral tissues to the brain. Here we show that extracellular vesicles derived from the B16F10 melanoma cell line, along with superparamagnetic iron oxide nanoparticles, gold nanorods, and Chinese ink nanoparticles can reach the meningeal lymphatic vessels and the brain of C57BL/6 mice after administration within deep cervical lymph nodes in vivo, exclusively through lymphatic structures. Since the functional anatomy of dural lymphatics has been found to be conserved between mice and humans, we expect that our results will encourage further research into the retrograde motion of nanoparticles towards the brain for pharmacological purposes in nanomedicine, as well as to better understand the fluid dynamics in different physiological or neuropathological conditions.

The role of conscious attention in statistical learning: evidence from patients with impaired consciousness
The debate over whether conscious attention is necessary for statistical learning has produced mixed and conflicting results. Testing individuals with impaired consciousness may provide some insight, but very few studies have been conducted due to the difficulties associated with testing such patients. In this study, we examined the ability of patients with varying levels of consciousness disorders (DOC), including coma, unresponsive wakefulness syndrome, minimally conscious patients, and emergence from minimally conscious state patients, to extract statistical regularities from an artificial language composed of four randomly concatenated pseudowords. We used a methodology based on frequency tagging in EEG, which was developed in our previous studies on speech segmentation in sleeping neonates. Our study had two main objectives: firstly, to assess the automaticity of the segmentation process and explore correlations between the level of covert consciousness and the abilities to extract statistical regularities, second, to explore a potential new diagnostic indicator to aid in patient management by examining the correlation between successful statistical learning markers and consciousness level. We observed that segmentation abilities were preserved in some minimally conscious patients, suggesting that statistical learning is an inherently automatic low-level process. Due to significant inter-individual variability, word segmentation may not be a sufficiently robust candidate for clinical use, unlike temporal accuracy of auditory syllable responses, which correlates strongly with coma severity. Therefore, we propose that frequency tagging of an auditory stimulus train, a simple and robust measure, should be further investigated as a possible metric candidate for DOC diagnosis.

Concerted neuron-astrocyte gene expression declines in aging and schizophrenia
Human brains vary across people and over time; such variation is not yet understood in cellular terms. Here we describe a striking relationship between peoples cortical neurons and cortical astrocytes. We used single-nucleus RNA-seq to analyze the prefrontal cortex of 191 human donors ages 22-97 years, including healthy individuals and persons with schizophrenia. Latent-factor analysis of these data revealed that in persons whose cortical neurons more strongly expressed genes for synaptic components, cortical astrocytes more strongly expressed distinct genes with synaptic functions and genes for synthesizing cholesterol, an astrocyte-supplied component of synaptic membranes. We call this relationship the Synaptic Neuron- and-Astrocyte Program (SNAP). In schizophrenia and aging - two conditions that involve declines in cognitive flexibility and plasticity 1,2 - cells had divested from SNAP: astrocytes, glutamatergic (excitatory) neurons, and GABAergic (inhibitory) neurons all reduced SNAP expression to corresponding degrees. The distinct astrocytic and neuronal components of SNAP both involved genes in which genetic risk factors for schizophrenia were strongly concentrated. SNAP, which varies quantitatively even among healthy persons of similar age, may underlie many aspects of normal human interindividual differences and be an important point of convergence for multiple kinds of pathophysiology.

Neural precursor cells rescue symptoms of Rett syndrome by activation of the Interferon γ pathway
The beneficial effects of Neural Precursor Cell (NPC) transplantation in several neurological disorders are well established and they are generally mediated by the secretion of immunomodulatory and neurotrophic molecules. We therefore investigated whether Rett syndrome (RTT), that represents the first cause of severe intellectual disability in girls, might benefit from an NPC-based therapy.

Using in vitro co-cultures, we demonstrate that, by sensing the pathological context, NPC-secreted factors induce the recovery of morphological and synaptic defects typical of Mecp2 deficient neurons. In vivo, we prove that intracerebral transplantation of NPCs in RTT mice significantly ameliorates neurological functions. To uncover the molecular mechanisms underpinning the mediated benefic effects, we analysed the transcriptional profile of the cerebellum of transplanted animals, disclosing the possible involvement of the Interferon {gamma} (IFN{gamma}) pathway. Accordingly, we report the capacity of IFN{gamma} to rescue synaptic defects, as well as motor and cognitive alterations in Mecp2 deficient models, thereby suggesting this molecular pathway as a potential therapeutic target for RTT.

EEG responses to rapidly unfolding stochastic sounds reflect precision tracking
The brain is increasingly viewed as a statistical learning machine, where our sensations and decisions arise from the intricate interplay between bottom-up sensory signals and constantly changing expectations regarding the surrounding world. Which statistics does the brain track while monitoring the rapid progression of sensory information?

Here, by combining EEG (three experiments N[≥]22 each) and computational modelling, we examined how the brain processes rapid and stochastic sound sequences that simulate key aspects of dynamic sensory environments. Passively listening participants were exposed to structured tone-pip arrangements that contained transitions between a range of stochastic patterns. Predictions were guided by a Bayesian predictive inference model. We demonstrate that listeners automatically track the statistics of unfolding sounds, even when these are irrelevant to behaviour. Transitions between sequence patterns drove an increase of the sustained EEG response. This was observed to a range of distributional statistics, and even in situations where behavioural detection of these transitions was at floor. These observations suggest that the modulation of the EEG sustained response reflects a universal process of belief updating within the brain. By establishing a connection between the outputs of the computational model and the observed brain responses, we demonstrate that the dynamics of these transition-related responses align with the tracking of precision - the confidence or reliability assigned to a predicted sensory signal - shedding light on the intricate interplay between the brains statistical tracking mechanisms and its response dynamics.