bioRxiv Subject Collection: Neuroscience's Journal

Functional consequences of fast-spiking interneurons in striatum
The striatum features a distinct network characterized by a high degree of shared feedforward inhibition (FFI) from a mere 1% of fast-spiking interneurons (FSI). We investigate the potential roles of this extensively shared FFI in striatal function beyond inducing synchrony. Our findings reveal that FSIs increase the across-trial variability of striatal responses to cortical stimuli and, combined with recurrent inhibition, lead to a 'correlation attractor' of striatal activities, i.e., weakly correlated inputs result in more correlated responses and vice versa. Thus, we uncover a mechanism by which input correlation can be bidirectionally modulated, which is possible only because of high sharing of FSI inputs. We posit that the emergence of a correlation attractor leads to non-zero correlation level and variable rate trajectories of striatal responses across trials, hence beneficial for exploration in learning. However, given their role in across-trial variability, we argue that FSIs should be 'disengaged' from the MSNs during performance where stability across trials is required.

A neural model for V1 that incorporates dendritic nonlinearities and back-propagating action potentials
The groundbreaking work of Hubel and Wiesel has been instrumental in shaping our understanding of V1, leading to modeling neural responses as cascades of linear and nonlinear processes in what has come to be known as the ``standard model'' of vision. Under this formulation, however, some dendritic properties cannot be represented in a practical manner, while extensive evidence indicates that dendritic processes are an indispensable element of key neural behaviours. As a result, current V1 models fail to explain neural responses in a number of scenarios. In this work, we propose an implicit model for V1 that considers nonlinear dendritic integration and backpropagation of action potentials from the soma to the dendrites. This is a parsimonious scheme that minimizes an energy, allows for a better conceptual understanding of neural processes, and explains several neurophysiological phenomena that have challenged classical approaches.

Feasibility of laminar functional quantitative susceptibility mapping
Layer fMRI is an increasingly utilized technique that provides insights into the laminar organization of brain activity. However, both blood-oxygen-level-dependent (BOLD) fMRI and vascular space occupancy data (VASO) have certain limitations, such as bias towards larger cortical veins in BOLD fMRI and high specific absorption rate in VASO. This study aims to explore the feasibility of whole-brain laminar functional quantitative susceptibility mapping (fQSM) compared to laminar BOLD fMRI and VASO at ultra-high field. Data were acquired using 3D EPI techniques. Complex data were denoised with NORDIC and susceptibility maps were computed using 3D path-based unwrapping, the variable-kernel sophisticated harmonic artifact reduction as well as the streaking artifact reduction for QSM algorithms. To assess layer-specific activation, twenty layers were segmented in the somatosensory and motor cortices, obtained from a finger tapping paradigm, and further averaged into six anatomical cortical layers. The magnitude of signal change and z-scores were compared across layers for each technique. fQSM showed the largest activation-dependent mean susceptibility decrease in Layers II/III in M1 and Layers I/ II in S1 with up to -1.3 ppb while BOLD fMRI showed the strongest mean signal increase in Layer I. Our data suggest that fQSM demonstrates less bias towards activation in superficial layers compared to BOLD fMRI. Moreover, activation-based susceptibility change was comparable to VASO data. Studying whole-brain, layer-dependent activation with submillimeter fQSM is feasible, and reduces bias towards venous drainage effects on the cortical surface compared to BOLD fMRI, thereby enabling better localization of laminar activation.

Brain-wide microstrokes affect the stability of memory circuits in the hippocampus
Cognitive deficits affect over 70% of stroke survivors, yet the mechanisms by which multiple small ischemic events contribute to cognitive decline remain poorly understood. In this study, we employed chronic two-photon calcium imaging to longitudinally track the fate of individual neurons in the hippocampus of mice navigating a virtual reality environment, both before and after inducing brain-wide microstrokes. Our findings reveal that, under normal conditions, hippocampal neurons exhibit varying degrees of stability in their spatial memory coding. However, microstrokes disrupted this functional network architecture, leading to cognitive impairments. Notably, the preservation of stable coding place cells, along with the stability, precision, and persistence of the hippocampal network, was strongly predictive of cognitive outcomes. Mice with more synchronously active place cells near important locations demonstrated recovery from cognitive impairment. This study uncovers critical cellular responses and network alterations following brain injury, providing a foundation for novel therapeutic strategies preventing cognitive decline.

The tilt illusion arises from an efficient reallocation of neural coding resources at the contextual boundary
The tilt illusion - a bias in the perceived orientation of a center stimulus induced by an oriented surround - illustrates how context shapes visual perception. While the tilt illusion has been the subject of quantitative study for over 85 years, we still lack a comprehensive account of the phenomenon that connects its neural and behavioral characteristics. Here, we demonstrate that the tilt illusion originates from a dynamic change in neural coding precision induced by the surround context. We simultaneously obtained psychophysical and fMRI responses from human subjects while they viewed gratings in the absence and presence of an oriented surround, and extracted sensory encoding precision from their behavioral and neural data. Both measures show that in the absence of a surround, encoding reflects the natural scene statistics of orientation. However, in the presence of an oriented surround, encoding precision is significantly increased for stimuli similar to the surround orientation. This local change in encoding is sufficient to accurately predict the behavioral characteristics of the tilt illusion using a Bayesian observer model. The effect of surround modulation increases along the ventral stream, and is localized to the portion of the visual cortex with receptive fields at the center-surround boundary. The pattern of change in coding accuracy reflects the surround-conditioned orientation statistics in natural scenes, but cannot be explained by local stimulus configuration. Our results suggest that the tilt illusion naturally emerges from a dynamic coding strategy that efficiently reallocates neural coding resources based on the current stimulus context.

Predictive filtering of sensory response via orbitofrontal top-down input
Habituation is a crucial sensory filtering mechanism whose dysregulation can lead to a continuously intense world in disorders with sensory overload. While habituation is considered to require top-down predictive signaling to suppress irrelevant inputs, the exact brain loci storing the internal predictive model and the circuit mechanisms of sensory filtering remain unclear. We found that daily neural habituation in the primary auditory cortex (A1) was reversed by inactivation of the orbitofrontal cortex (OFC). Top-down projections from the ventrolateral OFC, but not other frontal areas, carried predictive signals that grew with daily sound experience and suppressed A1 via somatostatin-expressing inhibitory neurons. Thus, prediction signals from the OFC cancel out behaviorally irrelevant anticipated stimuli by generating their "negative images" in sensory cortices.

Variations in human trigeminal and facial nerve branches and foramina identified by dissection and microcomputed tomography
The aim of this study was to identify branches of the trigeminal and facial nerves relevant to surgical incisions and injections and the scalp block techniques in the frontotemporal region, and to determine their relationships with superficial vascular structures and bony landmarks. Half-heads from consenting embalmed donors (6 male, 2 female, mean age at death 78.4 years) were used in this study. Detailed dissection was carried out to identify the position of the auriculotemporal nerve (ATN) relative to the superior temporal artery (STA) and the facial nerve (FN) in six subjects (5 male, 1 female). The results provide a minimum safe distance of 5 mm between the STA and the frontotemporal branches of the FN at the level of the low edge of zygoma and 8mm between the low edge of zygoma and the FN trunk, providing a pre-auricular triangle of safety for incisions and injections. Variability between subjects was up to 60%. Microcomputed tomography (microCT) scans were taken from all eight subjects and the three-dimensional reconstructions were used to identify the supraorbital notch (SON), the zygomaticotemporal foramen (ZTF) and the zygomaticofacial foramen (ZFF). The volume and relative locations of these foramina were calculated for 5-8 subjects. The closest distance between ZTF and the FZS ranged from 9 to 21mm (26% variation); 3 subjects had a single ZTF while 5 subjects had two ZTF. The angle at the centre of the orbit between ZFF and the FZS ranged from 156 to 166 degrees (2.5% variation). These findings demonstrate that both traditional cadaveric dissection methods as well as contemporary microCT methods can be used to investigate the relative locations of nerves or their foramina in the human head. The findings provide anatomical considerations for fronto-temporal incisions and local anaesthesia.

Representational shifts from feedforward to feedback rhythms index phenomenological integration in natural vision
How does the brain integrate complex and dynamic visual inputs into phenomenologically seamless percepts? Previous results demonstrate that when visual inputs are organized coherently across space and time, they are more strongly encoded in feedback-related alpha rhythms, and less strongly in feedforward-related gamma rhythms. Here, we tested whether this representational shift from feedforward to feedback rhythms is linked to the phenomenological experience of coherence. In an EEG study, we manipulated the degree of spatiotemporal coherence by presenting two segments from the same video across visual hemifields, either synchronously or asynchronously (with a delay between segments). We asked participants whether they perceived the stimulus as coherent or incoherent. When stimuli were presented at the perceptual threshold (i.e., when the same stimulus was judged as coherent 50% of times), perception co-varied with stimulus coding across alpha and gamma rhythms: When stimuli were perceived as coherent, they were represented in alpha activity; when stimuli were perceived as incoherent, they were represented in gamma activity. Whether the same visual input is perceived as coherent or incoherent thus depends on representational shifts between feedback-related alpha and feedforward-related gamma rhythms.

Sparsity of population activity in the hippocampus is task-invariant across the tri-synaptic circuit and dorsal-ventral axis
Evidence from neurophysiological and genetic studies demonstrates that activity sparsity, the proportion of neurons that are active at a given time in a population, systematically varies across the canonical trisynaptic circuit of the hippocampus. Recent work has also shown that sparsity varies across the hippocampal dorsoventral (long) axis, wherein activity is sparser in ventral than dorsal regions. While the hippocampus has a critical role in long term memory (LTM), whether sparsity across the trisynaptic circuit and hippocampal long axis is task dependent or invariant remains unknown. Importantly, representational sparsity has significant implications for neural computation and theoretical models of learning and memory within and beyond the hippocampus. Here we used functional molecular imaging to quantify sparsity in the rat hippocampus during performance of the Morris water task (MWT) and contextual fear discrimination (CFD); two popular and distinct assays of LTM. We found that activity sparsity is highly reliable across memory tasks, wherein activity increases sequentially across the trisynaptic circuit (DG < CA3 < CA1) and decreases across the long axis (ventral < dorsal). These results have important implications for models of hippocampal function and suggest that activity sparsity is a preserved property in the hippocampal system across cognitive settings.

Realistic mossy fiber input patterns to unipolar brush cells evoke a continuum of temporal responses comprised of components mediated by different glutamate receptors
Unipolar brush cells (UBCs) are excitatory interneurons in the cerebellar cortex that receive mossy fiber (MF) inputs and excite granule cells. The UBC population responds to brief burst activation of MFs with a continuum of temporal transformations, but it is not known how UBCs transform the diverse range of MF input patterns that occur in vivo. Here we use cell-attached recordings from UBCs in acute cerebellar slices to examine responses to MF firing patterns that are based on in vivo recordings. We find that MFs evoke a continuum of responses in the UBC population, mediated by three different types of glutamate receptors that each convey a specialized component. AMPARs transmit timing information for single stimuli at up to 5 spikes/s, and for very brief bursts. A combination of mGluR2/3s (inhibitory) and mGluR1s (excitatory) mediates a continuum of delayed, and broadened responses to longer bursts, and to sustained high frequency activation. Variability in the mGluR2/3 component controls the time course of the onset of firing, and variability in the mGluR1 component controls the duration of prolonged firing. We conclude that the combination of glutamate receptor types allows each UBC to simultaneously convey different aspects of MF firing. These findings establish that UBCs are highly flexible circuit elements that provide diverse temporal transformations that are well suited to contribute to specialized processing in different regions of the cerebellar cortex.

A dopaminergic basis of behavioral control
Both goal-directed and automatic processes shape human behavior. These processes often conflict, and behavioral control is the decision about which determines behavior. Behavioral control, or deciding how to decide, is critical for adaptive behavior. However, the neural mechanisms underlying behavioral control remain unclear. We performed deep phenotyping of individual dopamine system function by combining PET measures of dopamine physiology, functional MRI, and administration of dopaminergic drugs in a within-subject, double-blind, placebo-controlled design. Subjects performed a rule-based response time task in which we operationalized goal-directed and automatic decision-making as model-based and model-free contributions to behavior, respectively. We found convergent and causal evidence that dopamine D2/3 receptors in the striatum regulate behavioral control by enhancing model-based and blunting model-free influences on behavior. In contrast, we found a double dissociation whereby presynaptic dopamine synthesis capacity in the striatum was linked to acquiring model-based knowledge but not behavioral control. Neuroimaging analysis suggested that striatal D2/3 receptors influence behavioral control by adjusting frontostriatal functional connectivity. This multimodal study establishes a specific role of D2/3 receptors in regulating behavioral control and could contribute to an improved understanding of dysregulated behavioral control in clinical disorders affecting dopamine neurotransmission.

Cortical connectivity supports motoric synchronization to both auditory and visual rhythms in a frontal-temporal network
Synchronizing motoric responses to metrical sensory rhythms is key to social activities, e.g., group singing and dancing. It remains elusive, however, whether there is a common neural network for motoric synchronization to metrical rhythms from different sensory modalities. Here, we separate sensorimotor responses from basic sensory responses by combining a metrical sensorimotor synchronization task with frequency-domain magnetoencephalography (MEG) analysis. A common frontal-temporal network, not including visual cortex, is observed during both visual- and auditory-motor synchronization, and the network remains in congenitally deaf participants during visual-motor synchronization, suggesting the network is formed by intrinsic cortical connections instead of auditory experience. Furthermore, activation of the left and right frontal-temporal areas, as well as the ipsilateral white matter connection, separately predict the precision of auditory and visual synchronization. These results reveal a common but lateralized frontal-temporal network for visual- and auditory-motor synchronization, which is generated based on intrinsic cortical connections.

Neuroimaging model of visceral manipulation in awake rat
Reciprocal neuronal connections exist between the internal organs of the body and the nervous system. These projections to and from the viscera play an essential role in maintaining and finetuning organ responses in order to sustain homeostasis and allostasis. Functional maps of brain regions participating in this bidirectional communication have been previously studied in awake humans and anesthetized rodents. To further refine the mechanistic understanding of visceral influence on brain states, however, new paradigms that allow for more invasive, and ultimately more informative, measurements and perturbations must be explored. Further, such paradigms should prioritize human translatability. In the current paper, we address these issues by demonstrating the feasibility of non-anesthetized animal imaging during visceral manipulation. More specifically, we used a barostat interfaced with an implanted gastric balloon to cyclically induce distension of a non-anesthetized rat's stomach during simultaneous BOLD fMRI. General linear modeling and spatial independent component analysis revealed several regions with BOLD activation temporally coincident with the gastric distension stimulus. The ON-OFF (20 mmHg - 0 mmHg) barostat-balloon pressure cycle resulted in widespread BOLD activation of the inferior colliculus, cerebellum, ventral midbrain, and a variety of hippocampal structures. These results suggest that neuroimaging models of gastric manipulation in the non-anesthetized rat are achievable and provide an avenue for more comprehensive studies involving the integration of other neuroscience techniques like electrophysiology.

Sex-specific maladaptive responses to acute stress upon in utero THC exposure are mediated by dopamine
Cannabis remains by far the most consumed illicit drug in Europe. The availability of more potent cannabis has raised concerns regarding the enhanced health risks associated with its use, particularly among pregnant women. Growing evidence shows that cannabis use during pregnancy increases the risks of child psychopathology. We have previously shown that male rat offspring prenatally exposed to delta9 tetrahydrocannabinol (THC), a rat model of prenatal cannabinoid exposure (PCE), display a hyperdopaminergic phenotype associated with a differential susceptibility to acute THC- and stress-mediated effects on sensorimotor gating functions. Here, we explore the contribution of the hypothalamic-pituitary-adrenal (HPA) axis, key regulator of body adaptive stress responses, to the detrimental effects of acute stress on ventral tegmental area (VTA) dopamine neurons and sensorimotor gating function of PCE rats. We report a sex-dependent compromised balance in mRNA levels of genes encoding mineralocorticoid and glucocorticoid receptors in the VTA, alongside with stress-induced prepulse inhibition (PPI) deficits. Notably, VTA dopamine neuronal activity is required for the manifestation of stress-dependent deterioration of PPI. Finally, pharmacological manipulations targeting glycogen-synthase-kinase-3-beta signaling during postnatal development correct these stress-induced, sex-specific and dopamine-dependent deficits of PPI. Collectively, these results highlight the critical sex-dependent interplay between HPA axis and dopamine system in the regulation of sensorimotor gating functions in rats.

Comparison of Explainable AI Models for MRI-based Alzheimer's Disease Classification
Deep learning models based on convolutional neural networks (CNNs) have been used to classify Alzheimer's disease or infer dementia severity from 3D T1-weighted brain MRI scans. Here, we examine the value of adding occlusion sensitivity analysis (OSA) and gradient-weighted class activation mapping (Grad-CAM) to these models to make the results more interpretable. Much research in this area focuses on specific datasets such as the Alzheimer's Disease Neuroimaging Initiative (ADNI) or National Alzheimer's Coordinating Center (NACC), which assess people of North American, predominantly European ancestry, so we examine how well models trained on these data generalize to a new population dataset from India (NIMHANS cohort). We also evaluate the benefit of using a combined dataset to train the CNN models. Our experiments show feature localization consistent with knowledge of AD from other methods. OSA and Grad-CAM resolve features at different scales to help interpret diagnostic inferences made by CNNs.

Amygdala stimulation transforms short-term memory into remote memory by persistent activation of atypical PKC in the anterior cingulate cortex
Although many studies have addressed the role of the amygdala in modulating long-term memory, it is not known whether weak training plus amygdala stimulation can transform a short-term memory into a remote memory. Object place recognition (OPR) memory after strong training remains hippocampus-dependent through the persistent action of PKM{zeta} for at least 6 days, but it is unknown whether weak training plus amygdala stimulation can transform short-term memory into an even longer memory, and whether such memory is stored through more persistent action of PKM{zeta} in hippocampus. We trained rats to acquire OPR and 15 min or 5 h later induced a brief pattern of electrical stimulation in basolateral amygdala (BLA). Our results reveal that a short-term memory lasting < 4 h can be converted into remote memory lasting at least 3 weeks if the BLA is activated 15 min, but not 5 h after learning. To examine how this remote memory is maintained, we injected ZIP, an inhibitor of atypical PKCs (aPKCs), PKM{zeta} and PKC{iota}/{lambda}, into either hippocampal CA1, dentate gyrus (DG), or anterior cingulate cortex (ACC). Our data reveal amygdala stimulation produces consolidation into remote memory, not by persistent aPKC activation and capture by synaptic tagging processes in the hippocampal formation, but in ACC. Our data establish a powerful modulating role of the BLA in forming remote memory and open a path in the search for neurological restoration of memory, based on enhancing synaptic plasticity in aging or neurodegenerative disorders such as Alzheimer's disease.

GABAergic neurons in the dorsal raphe nucleus regulate social hierarchy in mice
Social hierarchy serves as a fundamental organizational mechanism within most animal societies, exerting significant influence on health, survival, and reproductive success in both humans and animals. However, the neural mechanisms by which the brain regulates dominance hierarchies remain inadequately understood. Considering that GABAergic neurons in the dorsal raphe nucleus (DRN) exert substantial inhibitory control over serotonergic firing, which may be implicated in the acquisition of dominance, we hypothesized that DRN GABAergic neurons may play a pivotal role in regulating social hierarchy. To test this hypothesis, we employed a combination of optogenetics, chemogenetics, fiber photometry recordings, and behavioral assays in mice, to elucidate the functional contributions of these neurons. Our results revealed a biphasic activity pattern of DRN GABAergic neurons, characterized by increased firing during retreats and decreased firing during push-initiation in the tube test. Furthermore, the optogenetic and chemogenetic activation of DRN GABAergic neurons led to an increase in the number of retreats and a reduction in social rank, while inhibition of these neurons produced the opposite effects. These findings elucidate the bidirectional regulatory role of DRN GABAergic neurons in social hierarchies.

Unique Transcriptomic Cell Types of the Granular Retrosplenial Cortex are Preserved Across Mice and Rats Despite Dramatic Changes in Key Marker Genes
The granular retrosplenial cortex (RSG) supports key functions ranging from memory consolidation to spatial navigation. The mouse RSG contains several cell types that are remarkably distinct from those found in other cortical regions. This includes the physiologically and transcriptomically unique low rheobase neuron that is the dominant cell-type in RSG layers 2/3 (L2/3 LR), as well as the similarly exclusive pyramidal cells that comprise much of RSG layer 5a (L5a RSG). While the functions of the RSG are extensively studied in both mice and rats, it remains unknown if the transcriptomically unique cell types of the mouse RSG are evolutionarily conserved in rats. Here, we show that mouse and rat RSG not only contain the same cell types, but key subtypes including the L2/3 LR and L5a RSG neurons are amplified in their representations in rats compared to mice. This preservation of cell types in male and female rats happens despite dramatic changes in key cell-type-specific marker genes, with the Scnn1a expression that selectively tags mouse L5a RSG neurons completely absent in rats. Important for Cre-driver line development, we identify alternative, cross-species genes that can be used to selectively target the cell types of the RSG in both mice and rats. Our results show that the unique cell types of the RSG are evolutionarily conserved across millions of years of evolution between mice and rats, but also emphasize stark species-specific differences in marker genes that need to be considered when making cell-type-specific transgenic lines of mice versus rats.

Astrocyte glucocorticoid receptors mediate sex-specific changes in activity following stress
Interactions between orexin neurons and astrocytes in the lateral hypothalamus influence activity levels including circadian and motivated behaviour. These behaviors are disrupted by stress in rodents and form a hallmark of stress-related neuropsychiatric disorders. Here we set out to understand how stress influences activity and the underlying cellular mechanisms. We report that the long-term effects of stress on activity levels correlate with spontaneous firing of orexin neurons with hyperactivity in males and hypoactivity presented by female mice. These neuronal changes were accompanied by extensive astrocyte remodelling. Causal manipulations identified lateral hypothalamic astrocytes as key regulators of activity patterns. In the context of stress, genetic deletion of glucocorticoid receptors in lateral hypothalamic astrocytes rescued the effects of stress on orexin neuron firing, restoring activity to control levels in both males and females. Overall, these data suggest that astrocytic regulation of orexin neuron firing enables the maintenance of activity levels, and their dysfunction drives stress-induced activity dysregulation.

High-resolution in vivo kinematic tracking with injectable fluorescent nanoparticles
Behavioral quantification is a cornerstone of many neuroscience experiments. Recent advances in motion tracking have streamlined the study of behavior in small laboratory animals and enabled precise movement quantification on fast (millisecond) timescales. This includes markerless keypoint trackers, which utilize deep network systems to label positions of interest on the surface of an animal (e.g., paws, snout, tail, etc.). These approaches mark a major technological achievement. However, they have a high error rate relative to motion capture in humans and are yet to be benchmarked against ground truth datasets in mice. Moreover, the extent to which they can be used to track joint or skeletal kinematics remains unclear. As the primary output of the motor system is the activation of muscles that, in turn, exert forces on the skeleton rather than the skin, it is important to establish potential limitations of techniques that rely on surface imaging. This can be accomplished by imaging implanted fiducial markers in freely moving mice. Here, we present a novel tracking method called QD-Pi (Quantum Dot-based Pose estimation in vivo), which employs injectable near-infrared fluorescent nanoparticles (quantum dots, QDs) immobilized on microbeads. We demonstrate that the resulting tags are biocompatible and can be imaged non-invasively using commercially available camera systems when injected into fatty tissue beneath the skin or directly into joints. Using this technique, we accurately capture 3D trajectories of up to ten independent internal positions in freely moving mice over multiple weeks. Finally, we leverage this technique to create a large-scale ground truth dataset for benchmarking and training the next generation of markerless keypoint tracker systems.

Activation of 5-HT7 receptors in the mouse dentate gyrus selectively enhances GABAergic inhibition of hilar mossy cells without affecting plasticity at the perforant path synapse
Background: The study examined the effects of 5-HT7 receptor activation on GABAergic transmission within the dentate gyrus and plasticity at the glutamatergic perforant path input. Methods: Immunofluorescence imaging was performed using transverse hippocampal slices from transgenic mice expressing GFP under the Htr7 promoter. This was followed by whole-cell patch clamp electrophysiological recordings of spontaneous inhibitory postsynaptic currents recorded from dentate granule cells and hilar mossy cells -- two glutamatergic neuron types present in the dentate gyrus. Extracellular recordings of field excitatory postsynaptic potentials were then performed to assess whether 5-HT7 receptor activation influenced theta burst stimulation-evoked plasticity of the perforant path synaptic input. Results: It was found that parvalbumin and somatostatin interneurons in the dentate gyrus expressed GFP. Activation of 5-HT7 receptors increased GABAergic transmission targeting mossy cells but not granule cells. However, there was no effect of 5-HT7 receptor activation on perforant path plasticity either with intact or blocked GABAA receptor signaling. Conclusion: The presence of 5-HT7 receptors in a subset of parvalbumin and somatostatin interneurons in the mouse dentate gyrus could mean that they are involved in the inhibitory control of dentate gyrus activity, although the effect seems to be confined to mossy cells and did not translate to changes in perforant path plasticity. Further experiments are needed to fully elucidate the functional role of these receptors in the dentate gyrus.

Overabundant endocannabinoids in neurons are detrimental to cognitive function
2-Arachidonoylglycerol (2-AG) is the most prevalent endocannabinoid involved in maintaining brain homeostasis. Previous studies have demonstrated that inactivating monoacylglycerol lipase (MAGL), the primary enzyme responsible for degrading 2-AG in the brain, alleviates neuropathology and prevents synaptic and cognitive decline in animal models of neurodegenerative diseases. However, we show that selectively inhibiting 2-AG metabolism in neurons impairs cognitive function in mice. This cognitive impairment appears to result from decreased expression of synaptic proteins and synapse numbers, impaired long-term synaptic plasticity and cortical circuit functional connectivity, and diminished neurogenesis. Interestingly, the synaptic and cognitive deficits induced by neuronal MAGL inactivation can be counterbalanced by inhibiting astrocytic 2-AG metabolism. Transcriptomic analyses reveal that inhibiting neuronal 2-AG degradation leads to widespread changes in expression of genes associated with synaptic function. These findings suggest that crosstalk in 2-AG signaling between astrocytes and neurons is crucial for maintaining synaptic and cognitive functions and that excessive 2-AG in neurons alone is detrimental to cognitive function.

Alzheimer's pathology disrupts flexible place cell coding and hippocampal-prefrontal neural dynamics during risky foraging decisions in mice
This study investigates the neural activity patterns associated with impaired decision-making in Alzheimer's disease (AD) by examining the effects of amyloid pathology on prefrontal-hippocampal circuit dynamics in 5XFAD mice, a model system known for its pronounced early amyloid pathology. Using ecologically relevant ''approach food-avoid predator'' paradigms, we revealed that 5XFAD mice display impaired decision strategies in risky foraging tasks, characterized by rigid hippocampal place fields and diminished sharp-wave ripple (SWR) frequencies, accompanied by disrupted prefrontal-hippocampal connectivity. These neural deficits align with behavioral inflexibility in dynamic threat scenarios. Our findings indicate that disrupted SWR dynamics and corticolimbic connectivity contribute to decision-making deficits in AD, emphasizing the potential of targeting these specific neural mechanisms to ameliorate cognitive impairments. This research contributes significantly to our understanding of AD's impact on cognition, providing insights that could lead to more targeted therapeutic strategies.

Limbic System White Matter in Children and Adolescents with ADHD: A Longitudinal Diffusion MRI Analysis
Attention-deficit/hyperactivity disorder (ADHD) is increasingly recognized as a disorder linked to atypical white matter development across large-scale brain networks. However, current research predominantly focuses on cortical networks, leaving the developmental trajectories of many subcortical networks, including the limbic system, largely unexplored. The limbic system is crucial for emotion and cognition, making it a key area of interest in ADHD research. This study employed multi-shell high angular resolution diffusion magnetic resonance imaging to map the development of limbic system white matter in individuals with ADHD (n = 72) and controls (n = 97) across three time points between ages 9 and 14. Diffusion kurtosis imaging and graph theory metrics were used to characterize limbic system white matter, alongside assessments of emotional regulation and ADHD symptom severity. Compared to controls, individuals with ADHD exhibited significantly lower microstructural organization, particularly in kurtosis anisotropy, within the bilateral cingulum bundle from childhood to adolescence. Brain-behavior analyses further revealed that higher ADHD symptom severity was associated with a lower number of limbic system white matter connections, notably decreased routing efficiency and network density. These findings offer novel insights into the role of disrupted limbic system white matter in ADHD pathophysiology, broadening our understanding of the disorder's neural mechanisms and opening promising avenues for future exploration of subcortical brain networks.

Cortical state contributions to response variability in the early visual cortex: A system identification approach
Neurons in the early visual cortex respond selectively to multiple features of visual stimuli, but they respond differently to repeated presentation of the same visual stimulus. Such trial-to-trial response variabilities are often treated as noise and addressed by simple trial-averaging to obtain the stimulus-driven response, though this approach is insufficient to fully remove the response variability. More importantly, there is evidence that response variability may primarily be caused by non-sensory factors, particularly by variations in cortical state. Here we recorded and analyzed neuronal spiking activity in response to natural images from areas 17 and 18 of cats, along with local population neuronal signals; local field potential (LFP) and multi-unit activity (MUA). We used a variability ratio (VR) measure to quantify the variability of neural responses across trials and two cortical state indicative measures; global fluctuation index (GFI) calculated using MUA and synchrony index (SI) calculated using LFP signals. We propose a compact convolutional neural network model with two parallel pathways, to capture the stimulus-driven activity and the cortical state-driven response variabilities. The stimulus-driven pathway contains a spatiotemporal filter, a parametric rectifier and a Gaussian map and the cortical state-driven pathway contains temporal filters for MUA and LFP. The model parameters are fit to best predict the spiking activity of each neuron. Single neurons showed highly varying degrees of trial-to-trial response variability, even when recorded simultaneously. The fitted model performed with a significantly higher accuracy in predicting neural responses compared to a basic model with a stimulus-driven pathway alone. The neurons with higher response variability benefited more from the cortical state-driven pathway compared to less variable neurons. These results provide insights to understanding the possibility of trial-to-trial response variabilities emerging as an effect of cortical state dynamics.

Interaction between facial expression and color in modulating EPR P3
The relationships between facial expression and color affect human cognition functions such as perception and memory. However, whether these relationships influence attention remains unclear. Additionally, whether facial expressions affect selective attention is unknown; for example, reddish angry faces increase negative social evaluation or emotion intensity, but it is unclear whether selective attention is similarly enhanced. To investigate these questions, we examined whether event-related potentials for faces vary depending on facial expression and color by recording electroencephalography (EEG) data. We conducted an oddball task using stimuli that combined facial expressions (angry, neutral) and facial colors (original, red, green). The participants counted the number of times a rarely appearing target face stimulus appeared among the standard face stimuli. The results indicated that the difference in P3 amplitudes for the target and standard faces depended on the combinations of facial expressions and facial colors; the P3 amplitudes for red angry faces were greater than those for red neutral faces. Additionally, there was no significant main effect or interaction effect of facial expression or facial color on P1 amplitudes for the target, and there were significant main effects of facial expression only on the N170 amplitude. These findings suggest that the intensity of a human's selective attention to facial expressions varies according to the higher-order semantic processing of the relationship between emotion and color rather than simple facial expression or facial color effects individually. Our results support the idea that red color increases the human response to anger from an EEG perspective.

Sex-Specific Complement and Cytokine Imbalances in Drug-Resistant Epilepsy: Biomarkers of Immune Vulnerability
Objective: Drug-resistant epilepsy (DRE) poses significant challenges in treatment and management. While seizure-related alterations in peripheral immune players are increasingly recognized, the involvement of the complement system, central to immune function, remains insufficiently explored in DRE. This study aimed to investigate the levels of complement system components and their association with cytokine profiles in patients with DRE. Methods: We analyzed serum samples from DRE patients (n = 46) and age- and sex-matched healthy controls (n = 45). Complement components and cytokines were quantified using Multi- and Single-plex ELISA. Statistical analyses examined relationships between complement molecules, cytokines, and clinical outcomes including epilepsy duration, Full-Scale Intelligence Quotient (FSIQ) scores, and age. Results: We found common alterations in all DRE cases, including significant complement deficiencies (C1q, Factor H, C4, C4b, C3, and C3b/iC3b) and detectable bFGF levels. DRE females showed significantly lower levels of TNF- and IL-8 compared to healthy females. In DRE males, we observed a trend towards elevated CCL2 and CCL5 levels compared to healthy males. These findings suggest potential sex-dimorphism in immune profiles. Our analysis also indicated associations between specific complement and inflammatory markers (C2, IL-8, and IL-9) and Full-Scale Intelligence Quotient (FSIQ) scores in DRE patients. Interpretation: Our study reveals sex-specific peripheral complement deficiencies and cytokine dysregulation in DRE patients, indicating an underlying immune system vulnerability. These findings provide new insights into DRE mechanisms, potentially guiding future research on complement and cytokine signaling towards personalized treatments for DRE patients.

Off-Equilibrium Fluctuation-Dissipation Theorem Paves the Way in Alzheimer's Disease Research
INTRODUCTION: Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline. Although traditional methods have provided insights into brain dynamics in AD, they have limitations in capturing non-equilibrium dynamics across disease stages. Recent studies suggest that dynamic functional connectivity in resting-state networks (RSNs) may serve as a biomarker for AD, but the role of deviations from dynamical equilibrium remains underexplored. OBJECTIVE: This study applies the off-equilibrium fluctuation-dissipation theorem (FDT) [Monti2024] to analyze brain dynamics in AD, aiming to compare deviations from equilibrium in healthy controls, patients with mild cognitive impairment (MCI), and those with AD. The goal is to identify potential biomarkers for early AD detection and understand disease progression's mechanisms. METHODS: We employed a model-free approach based on FDT to analyze functional magnetic resonance imaging (fMRI) data, including healthy controls, MCI patients, and AD patients. Deviations from equilibrium in resting-state brain activity were quantified using fMRI scans. In addition, we performed model-based simulations incorporating Amyloid-Beta (ABeta), tau burdens, and Generative Effective Connectivity (GEC) for each subject. RESULTS: Our findings show that deviations from equilibrium increase during the MCI stage, indicating hyperexcitability, followed by a significant decline in later stages of AD, reflecting neuronal damage. Model-based simulations incorporating ABeta and tau burdens closely replicated these dynamics, especially in AD patients, highlighting their role in disease progression. Healthy controls exhibited lower deviations, while AD patients showed the most significant disruptions in brain dynamics. DISCUSSION: The study demonstrates that the off-equilibrium FDT framework can accurately characterize brain dynamics in AD, providing a potential biomarker for early detection. The increase in non-equilibrium deviations during the MCI stage followed by their decline in AD offers a mechanistic explanation for disease progression. Future research should explore how combining this framework with other dynamic brain measures could further refine diagnostic tools and therapeutic strategies for AD and other neurodegenerative diseases.

Neurophysiological signatures of default mode network dysfunction and cognitive decline in Alzheimer disease.
Neural hyper-excitability and network dysfunction are neurophysiological hallmarks of Alzheimer disease (AD) in animal studies, but their presence and clinical relevance in humans remain poorly understood. We introduce a novel perturbation-based approach combining transcranial magnetic stimulation and electroencephalography (TMS-EEG), alongside resting-state EEG (rsEEG), to investigate neurophysiological basis of default mode network (DMN) dysfunction in early AD. While rsEEG revealed global neural slowing and disrupted synchrony, these measures reflected widespread changes in brain neurophysiology without network-specific insights. In contrast, TMS-EEG identified network-specific local hyper-excitability in the parietal DMN and disrupted connectivity with frontal DMN regions, which uniquely predicted distinct cognitive impairments and mediated the link between structural brain integrity and cognition. Our findings provide mechanistic insights into how network-specific neurophysiological disruptions contribute to AD-related cognitive dysfunction. Perturbation-based assessments hold promise as novel markers of early detection, disease progression, and target engagement for disease-modifying therapies aiming to restore abnormal neurophysiology in AD.

Precision-dependent modulation of social attention
Social attention, guided by cues like gaze direction, is crucial for effective social interactions. However, how dynamic environmental context modulates this process remains unclear. Integrating a hierarchical Bayesian model with fMRI, this study investigated how individuals adjusted attention based on the predictions about cue validity (CV). Thirty-three participants performed a modified Posner location-cueing task with varying CV. Behaviorally, individuals' allocation of social attention was finely tuned to the precision (inverse variance) of CV predictions, with the predictions being updated by precision-weighted prediction errors (PEs) about the occurrence of target locations. Neuroimaging results revealed that the interaction between allocation of social attention and CV influenced activity in regions involved in spatial attention and/or social perception, such as the temporoparietal junction (TPJ), frontal eye field (FEF), superior temporal sulcus (STS), and inferior parietal sulcus (IPS). Precision-weighted PEs about target locations specifically modulated activity in the TPJ, STS, and primary visual cortex (V1), underscoring their roles in refining attentional predictions. Dynamic causal modeling (DCM) further demonstrated that enhanced absolute precision-weighted PEs about target locations strengthened the effective connectivity from V1 and STS to TPJ, emphasizing their roles in conveying residual error signals from low-level sensory areas to high-level critical attention areas. These findings elucidated how the precision of contextual predictions dynamically modulated social attention, offering insights into the computational and neurocognitive mechanisms of context-dependent social attention.

Towards Longitudinal Characterization of Multiple Sclerosis Atrophy Employing SynthSeg Framework and Normative Modeling
Multiple Sclerosis (MS) is a complex neurodegenerative disease characterized by heterogeneous progression patterns. Traditional clinical measures like the Expanded Disability Status Scale (EDSS) inadequately capture the full spectrum of disease progression, highlighting the need for advanced Disease Progression Modeling (DPM) approaches.This study harnesses cutting-edge neuroimaging and deep learning techniques to investigate deviations in subcortical volumes in MS patients. We analyze T1-weighted and Fluid-attenuated inversion recovery (FLAIR) Magnetic Resonance Imaging (MRI) data using advanced DL segmentation models, SynthSeg+ and SynthSeg-WMH, which address the challenges of conventional methods in the presence of white matter lesions. By comparing subcortical volumes of 326 MS patients to a normative model from 37,407 healthy individuals, we identify significant deviations that enhance our understanding of MS progression. This study highlights the potential of integrating DL with normative modeling to refine MS progression characterization, automate informative MRI contrasts, and contribute to data-driven DPM in neurodegenerative diseases.