Updating functional brain units: Insights far beyond Luria

This paper reviews Luria's model of the three functional units of the brain. To meet this objective, several issues were reviewed: the theory of functional systems and the contributions of phylogenesis and embryogenesis to the brain's functional organization. This review revealed several facts. In the first place, the relationship/integration of basic homeostatic needs with complex forms of behavior. Secondly, the multi-scale hierarchical and distributed organization of the brain and interactions between cells and systems. Thirdly, the phylogenetic role of exaptation, especially in basal ganglia and cerebellum expansion. Finally, the tripartite embryogenetic organization of the brain: rhinic, limbic/paralimbic, and supralimbic zones. Obviously, these principles of brain organization are in contradiction with attempts to establish separate functional brain units. The proposed new model is made up of two large integrated complexes: a primordial-limbic complex (Luria's Unit I) and a telencephalic-cortical complex (Luria's Units II and III). As a result, five functional units were delineated: Unit I. Primordial or preferential (brainstem), for life-support, behavioral modulation, and waking regulation; Unit II. Limbic and paralimbic systems, for emotions and hedonic evaluation (danger and relevance detection and contribution to reward/motivational processing) and the creation of cognitive maps (contextual memory, navigation, and generativity [imagination]); Unit III. Telencephalic-cortical, for sensorimotor and cognitive processing (gnosis, praxis, language, calculation, etc.), semantic and episodic (contextual) memory processing, and multimodal conscious agency; Unit IV. Basal ganglia systems, for behavior selection and reinforcement (reward-oriented behavior); Unit V. Cerebellar systems, for the prediction/anticipation (orthometric supervision) of the outcome of an action. The proposed brain units are nothing more than abstractions within the brain's simultaneous and distributed physiological processes. As function transcends anatomy, the model necessarily involves transition and overlap between structures. Beyond the classic approaches, this review includes information on recent systemic perspectives on functional brain organization. The limitations of this review are discussed.

Dynamic modulation of mouse thalamocortical visual activity by salient sounds

Visual responses of the primary visual cortex (V1) are altered by sound. Sound-driven behavioral arousal suggests that, in addition to direct inputs from the primary auditory cortex (A1), multiple other sources may shape V1 responses to sound. Here, we show in anesthetized mice that sound (white noise, ≥70dB) drives a biphasic modulation of V1 visually driven gamma-band activity, comprising fast-transient inhibitory and slow, prolonged excitatory (A1-independent) arousal-driven components. An analogous yet quicker modulation of the visual response also occurred earlier in the visual pathway, at the level of the dorsolateral geniculate nucleus (dLGN), where sound transiently inhibited the early phasic visual response and subsequently induced a prolonged increase in tonic spiking activity and gamma rhythmicity. Our results demonstrate that sound-driven modulations of visual activity are not exclusive to V1 and suggest that thalamocortical inputs from the dLGN to V1 contribute to shaping V1 visual response to sound.

Restoring vision in adult amblyopia by enhancing plasticity through deletion of the transcriptional repressor REST

Visual cortical plasticity is high during early life, but gradually decreases with development. This is due to the Otx2-driven maturation of intracortical inhibition that parallels the condensation of extracellular matrix components into perineuronal nets mainly around parvalbumin-positive GABAergic neurons. Repressor Element 1 Silencing Transcription (REST) epigenetically controls the expression of a plethora of neuron-specific genes. We demonstrate that the conditional knockout of REST in the primary visual cortex of adult mice induces a shift of ocular dominance after short-term monocular deprivation and promotes the recovery of vision in long-term deprived animals after reverse suture. These phenomena paralleled a reduction of perineuronal net density and increased expression of REST target genes, but not of the homeoprotein Otx2 in the visual cortex contralateral to the deprived eye. This shows that REST regulates adult visual cortical plasticity and is a potential therapeutic target to restore vision in adult amblyopia by enhancing V1 plasticity.

Brain-wide human oscillatory local field potential activity during visual working memory

Oscillatory activity in the local field potential (LFP) is thought to be a marker of cognitive processes. To understand how it differentiates tasks and brain areas in humans, we recorded LFPs in 15 adults with intracranial depth electrodes, as they performed visual-spatial and shape working memory tasks. Stimulus appearance produced widespread, broad-band activation, including in occipital, parietal, temporal, insular, and prefrontal cortex, and the amygdala and hippocampus. Occipital cortex was characterized by most elevated power in the high-gamma (100-150 Hz) range during the visual stimulus presentation. The most consistent feature of the delay period was a systematic pattern of modulation in the beta frequency (16-40 Hz), which included a decrease in power of variable timing across areas, and rebound during the delay period. These results reveal the widespread nature of oscillatory activity across a broad brain network and region-specific signatures of oscillatory processes associated with visual working memory.

Dorsal motor vagal neurons can elicit bradycardia and reduce anxiety-like behavior

Cardiovagal neurons (CVNs) innervate cardiac ganglia through the vagus nerve to control cardiac function. Although the cardioinhibitory role of CVNs in nucleus ambiguus (CVNNA) is well established, the nature and functionality of CVNs in dorsal motor nucleus of the vagus (CVNDMV) is less clear. We therefore aimed to characterize CVNDMV anatomically, physiologically, and functionally. Optogenetically activating cholinergic DMV neurons resulted in robust bradycardia through peripheral muscarinic (parasympathetic) and nicotinic (ganglionic) acetylcholine receptors, but not beta-1-adrenergic (sympathetic) receptors. Retrograde tracing from the cardiac fat pad labeled CVNNA and CVNDMV through the vagus nerve. Using whole-cell patch-clamp, CVNDMV demonstrated greater hyperexcitability and spontaneous action potential firing ex vivo despite similar resting membrane potentials, compared to CVNNA. Chemogenetically activating DMV also caused significant bradycardia with a correlated reduction in anxiety-like behavior. Thus, DMV contains uniquely hyperexcitable CVNs and is capable of cardioinhibition and robust anxiolysis.

An intra-oral flavor detection task in freely moving mice

Flavor plays a critical role in the pleasure of food. Flavor research has mainly focused on human subjects and revealed that many brain regions are involved in flavor perception. However, animal models for elucidating the mechanisms of neural circuits are lacking. Herein, we demonstrate the use of a novel behavioral task in which mice are capable of flavor detection. When the olfactory pathways of the mice were blocked, they could not perform the task. However, behavioral accuracy was not affected when the gustatory pathway was blocked by benzocaine. These results indicate that the mice performed this detection task mainly based on the olfaction. We conclude that this novel task can contribute to research on the neural mechanisms of flavor perception.

May I see what you see? Predicting visual features from neuronal activity

Understanding brain response to audiovisual stimuli is a key challenge in understanding neuronal processes. In this paper, we describe our effort aimed at reconstructing video frames from observed functional MRI images. We also demonstrate that our model can predict visual objects. Our method constructs an autoencoder model for a set of training video segments to code video streams into their corresponding latent representations. Next, we learn a mapping from the observed fMRI response to the corresponding latent video frame representation. Finally, we pass the latent vectors computed using the fMRI response through the decoder to reconstruct the predicted image. We show that the representations of video frames and those constructed from corresponding fMRI images are highly clustered, the latent representations can be used to predict objects in video frames using just the fMRI frames, and fMRI responses can be used to reconstruct the inputs to predict the presence of faces.

Seeing in the dark: High-order visual functions under scotopic conditions

It is unknown how and to what degree people function visually in almost complete darkness, where only rod photoreceptors are active (scotopic conditions). To explore this, we first tested scotopic acuity and crowding. We demonstrated the ∼1° foveal scotoma and found that crowding increases with eccentricity, resulting in optimal scotopic discrimination 2° into the periphery. We then investigated whether these limitations affect high-level foveal tasks. We recorded eye movements while testing reading and upright/inverted face matching under photopic and scotopic conditions. Under scotopic conditions, participants read accurately and showed a face inversion effect. Temporally, fixation durations were longer. Spatially, surprisingly, participants did not avert their gaze 2° into the periphery. Instead, they fixated on similar locations as under photopic conditions, locations that were shown to correlate with global perception. We propose that this result suggests global perception governs under scotopic conditions, and we discuss how receptive-field properties support this conclusion.

DExH-box helicase 9 modulates hippocampal synapses and regulates neuropathic pain

Experimental studies have shown that neuropathic pain impairs hippocampal synaptic plasticity. Here, we sought to determine the underlying mechanisms responsible for synaptic changes in neuropathic painful mouse hippocampal neurons. Beyond demonstrating proof-of-concept for the location of DExH-box helicase 9 (DHX9) in the nucleus, we found that it did exist in the cytoplasm and DHX9 depletion resulted in structural and functional changes at synapses in the hippocampus. A decrease of DHX9 was observed in the hippocampus after peripheral nerve injury; overexpression of DHX9 in the hippocampus significantly alleviated the nociceptive responses and improved anxiety behaviors. Mimicking DHX9 decrease evoked spontaneous pain behavioral symptoms and anxiety emotion in naïve mice. Mechanistically, we found that DHX9 bound to dendrin (Ddn) mRNA, which may have altered the level of synaptic- and dendritic-associated proteins. The data suggest that DHX9 contributes to synapses in hippocampal neurons and may modulate neuropathic pain and its comorbidity aversive emotion.

Understanding divergence: Placing developmental neuroscience in its dynamic context

Neurodevelopment is not merely a process of brain maturation, but an adaptation to constraints unique to each individual and to the environments we co-create. However, our theoretical and methodological toolkits often ignore this reality. There is growing awareness that a shift is needed that allows us to study divergence of brain and behaviour across conventional categorical boundaries. However, we argue that in future our study of divergence must also incorporate the developmental dynamics that capture the emergence of those neurodevelopmental differences. This crucial step will require adjustments in study design and methodology. If our ultimate aim is to incorporate the developmental dynamics that capture how, and ultimately when, divergence takes place then we will need an analytic toolkit equal to these ambitions. We argue that the over reliance on group averages has been a conceptual dead-end with regard to the neurodevelopmental differences. This is in part because any individual differences and developmental dynamics are inevitably lost within the group average. Instead, analytic approaches which are themselves new, or simply newly applied within this context, may allow us to shift our theoretical and methodological frameworks from groups to individuals. Likewise, methods capable of modelling complex dynamic systems may allow us to understand the emergent dynamics only possible at the level of an interacting neural system.

Pretrial predictors of conflict response efficacy in the human prefrontal cortex

The ability to perform motor actions depends, in part, on the brain's initial state. We hypothesized that initial state dependence is a more general principle and applies to cognitive control. To test this idea, we examined human single units recorded from the dorsolateral prefrontal (dlPFC) cortex and dorsal anterior cingulate cortex (dACC) during a task that interleaves motor and perceptual conflict trials, the multisource interference task (MSIT). In both brain regions, variability in pre-trial firing rates predicted subsequent reaction time (RT) on conflict trials. In dlPFC, ensemble firing rate patterns suggested the existence of domain-specific initial states, while in dACC, firing patterns were more consistent with a domain-general initial state. The deployment of shared and independent factors that we observe for conflict resolution may allow for flexible and fast responses mediated by cognitive initial states. These results also support hypotheses that place dACC hierarchically earlier than dlPFC in proactive control.

AKAP150 from nucleus accumbens dopamine D1 and D2 receptor-expressing medium spiny neurons regulates morphine withdrawal

Dopamine D1 receptor-expressing medium spiny neurons (D1R-MSNs) and dopamine D2 receptor-expressing MSNs (D2R-MSNs) in nucleus accumbens (NAc) have been demonstrated to show different effects on reward and memory of abstinence. A-kinase anchoring protein 150 (AKAP150) expression in NAc is significantly upregulated and contributes to the morphine withdrawal behavior. However, the underlying mechanism of AKAP150 under opioid withdrawal remains unclear. In this study, AKAP150 expression in NAc is upregulated in naloxone-precipitated morphine withdrawal model, and knockdown of AKAP150 alleviates morphine withdrawal somatic signs and improves the performance of conditioned place aversion (CPA) test. AKAP150 in NAc D1R-MSNs is related to modulation of the performance of morphine withdrawal CPA test, while AKAP150 in NAc D2R-MSNs is relevant to the severity of somatic responses. Our results suggest that AKAP150 from D1R-MSNs or D2R-MSNs in NAc contributes to the developmental process of morphine withdrawal but plays different roles in aspects of behavior or psychology.

FUS-dependent microRNA deregulations identify TRIB2 as a druggable target for ALS motor neurons

MicroRNAs (miRNAs) modulate mRNA expression, and their deregulation contributes to various diseases including amyotrophic lateral sclerosis (ALS). As fused in sarcoma (FUS) is a causal gene for ALS and regulates biogenesis of miRNAs, we systematically analyzed the miRNA repertoires in spinal cords and hippocampi from ALS-FUS mice to understand how FUS-dependent miRNA deregulation contributes to ALS. miRNA profiling identified differentially expressed miRNAs between different central nervous system (CNS) regions as well as disease states. Among the up-regulated miRNAs, miR-1197 targets the pro-survival pseudokinase Trib2. A reduced TRIB2 expression was observed in iPSC-derived motor neurons from ALS patients. Pharmacological stabilization of TRIB2 protein with a clinically approved cancer drug rescues the survival of iPSC-derived human motor neurons, including those from a sporadic ALS patient. Collectively, our data indicate that miRNA profiling can be used to probe the molecular mechanisms underlying selective vulnerability, and TRIB2 is a potential therapeutic target for ALS.

Mitochondrial network adaptations of microglia reveal sex-specific stress response after injury and UCP2 knockout

Mitochondrial networks remodel their connectivity, content, and subcellular localization to support optimized energy production in conditions of increased environmental or cellular stress. Microglia rely on mitochondria to respond to these stressors, however our knowledge about mitochondrial networks and their adaptations in microglia in vivo is limited. Here, we generate a mouse model that selectively labels mitochondria in microglia. We identify that mitochondrial networks are more fragmented with increased content and perinuclear localization in vitro vs. in vivo. Mitochondrial networks adapt similarly in microglia closest to the injury site after optic nerve crush. Preventing microglial UCP2 increase after injury by selective knockout induces cellular stress. This results in mitochondrial hyperfusion in male microglia, a phenotype absent in females due to circulating estrogens. Our results establish the foundation for mitochondrial network analysis of microglia in vivo, emphasizing the importance of mitochondrial-based sex effects of microglia in other pathologies.

Dissociable contributions of the medial parietal cortex to recognition memory

Human neuroimaging studies of episodic memory retrieval routinely observe the engagement of specific cortical regions beyond the medial temporal lobe. Of these, medial parietal cortex (MPC) is of particular interest given its ubiquitous, and yet distinct, functional characteristics during different types of retrieval tasks. Specifically, while recognition memory and autobiographical recall tasks are both used to probe episodic retrieval, these paradigms consistently drive distinct patterns of response within MPC. This dissociation adds to growing evidence suggesting a common principle of functional organization across memory related brain structures, specifically regarding the control or content demands of memory-based decisions. To carefully examine this putative organization, we used a high-resolution fMRI dataset collected at ultra-high field (7T) while subjects performed thousands of recognition-memory trials to identify MPC regions responsive to recognition-decisions or semantic content of stimuli within and across individuals. We observed interleaving, though distinct, functional subregions of MPC where responses were sensitive to either recognition decisions or the semantic representation of stimuli, but rarely both. In addition, this functional dissociation within MPC was further accentuated by distinct profiles of connectivity bias with the hippocampus during task and rest. Finally, we show that recent observations of person and place selectivity within MPC reflect category specific responses from within identified semantic regions that are sensitive to mnemonic demands. Together, these data better account for how distinct patterns of MPC responses can occur as a result of task demands during episodic retrieval and may reflect a common principle of organization throughout hippocampal-neocortical memory systems.

Large-scale survey of excitatory synapses reveals sublamina-specific and asymmetric synapse disassembly in a neurodegenerative circuit

In the nervous system, parallel circuits are organized in part by the lamina-specific compartmentalization of synaptic connections. In sensory systems such as mammalian retina, degenerating third-order neurons remodel their local presynaptic connectivity with second-order neurons. To determine whether there are sublamina-specific perturbations after injury of adult retinal ganglion cells, we comprehensively analyzed excitatory synapses across the inner plexiform layer (IPL) where bipolar cells connect to ganglion cells. Here, we show that pre- and postsynaptic component loss occurs throughout the IPL in a sublamina-dependent fashion after transient intraocular pressure elevation. Partnered synaptic components are lost as neurodegeneration progresses, while unpartnered synaptic components remain stable. Furthermore, presynaptic components are either lost first or simultaneously with the postsynaptic component. Our results demonstrate that this degenerating neural circuit exhibits differential vulnerability of excitatory synapses depending on IPL depth, highlighting the ordered disassembly of synapses that is specific to laminar compartments of the retina.

Ventral pallidal glutamatergic neurons regulate wakefulness and emotion through separated projections

Insomnia is often comorbid with depression, but the underlying neuronal circuit mechanism remains elusive. Recently, we reported that GABAergic ventral pallidum (VP) neurons control wakefulness associated with motivation. However, whether and how other subtypes of VP neurons regulate arousal and emotion are largely unknown. Here, we report glutamatergic VP (VPVglut2) neurons control wakefulness and depressive-like behaviors. Physiologically, the calcium activity of VPVglut2 neurons was increased during both NREM sleep-to-wake transitions and depressive/anxiety-like behaviors in mice. Functionally, activation of VPVglut2 neurons was sufficient to increase wakefulness and induce anxiety/depressive-like behaviors, whereas inhibition attenuated both. Dissection of the circuit revealed that separated projections of VPVglut2 neurons to the lateral hypothalamus and lateral habenula promote arousal and depressive-like behaviors, respectively. Our results demonstrate a subtype of VP neurons is responsible for wakefulness and emotion through separated projections, and may provide new lines for the intervention of insomnia and depression in patients.

Pathway and directional specificity of Hebbian plasticity in the cortical visual motion processing network

Cortico-cortical paired associative stimulation (ccPAS), which repeatedly pairs single-pulse transcranial magnetic stimulation (TMS) over two distant brain regions, is thought to modulate synaptic plasticity. We explored its spatial selectivity (pathway and direction specificity) and its nature (oscillatory signature and perceptual consequences) when applied along the ascending (Forward) and descending (Backward) motion discrimination pathway. We found unspecific connectivity increases in bottom-up inputs in the low gamma band, probably reflecting visual task exposure. A clear distinction in information transfer occurred in the re-entrant alpha signals, which were only modulated by Backward-ccPAS, and predictive of visual improvements in healthy participants. These results suggest a causal involvement of the re-entrant MT-to-V1 low-frequency inputs in motion discrimination and integration in healthy participants. Modulating re-entrant input activity could provide single-subject prediction scenarios for visual recovery. Visual recovery might indeed partly rely on these residual inputs projecting to spared V1 neurons.

Different macaque brain network remodeling after spinal cord injury and NT3 treatment

Graph theory-based analysis describes the brain as a complex network. Only a few studies have examined modular composition and functional connectivity (FC) between modules in patients with spinal cord injury (SCI). Little is known about the longitudinal changes in hubs and topological properties at the modular level after SCI and treatment. We analyzed differences in FC and nodal metrics reflecting modular interaction to investigate brain reorganization after SCI-induced compensation and neurotrophin-3 (NT3)-chitosan-induced regeneration. Mean inter-modular FC and participation coefficient of areas related to motor coordination were significantly higher in the treatment animals than in the SCI-only ones at the late stage. The magnocellular part of the red nucleus may reflect the best difference in brain reorganization after SCI and therapy. Treatment can enhance information flows between regions and promote the integration of motor functions to return to normal. These findings may reveal the information processing of disrupted network modules.

Dynamic segregation and integration of brain functional networks associated with emotional arousal

The organization of brain functional networks dynamically changes with emotional stimuli, but its relationship to emotional behaviors is still unclear. In the DEAP dataset, we used the nested-spectral partition approach to identify the hierarchical segregation and integration of functional networks and investigated the dynamic transitions between connectivity states under different arousal conditions. The frontal and right posterior parietal regions were dominant for network integration whereas the bilateral temporal, left posterior parietal, and occipital regions were responsible for segregation and functional flexibility. High emotional arousal behavior was associated with stronger network integration and more stable state transitions. Crucially, the connectivity states of frontal, central, and right parietal regions were closely related to arousal ratings in individuals. Besides, we predicted the individual emotional performance based on functional connectivity activities. Our results demonstrate that brain connectivity states are closely associated with emotional behaviors and could be reliable and robust indicators for emotional arousal.

Exploration behavior after reversals is predicted by STN-GPe synaptic plasticity in a basal ganglia model

Humans can quickly adapt their behavior to changes in the environment. Classical reversal learning tasks mainly measure how well participants can disengage from a previously successful behavior but not how alternative responses are explored. Here, we propose a novel 5-choice reversal learning task with alternating position-reward contingencies to study exploration behavior after a reversal. We compare human exploratory saccade behavior with a prediction obtained from a neuro-computational model of the basal ganglia. A new synaptic plasticity rule for learning the connectivity between the subthalamic nucleus (STN) and external globus pallidus (GPe) results in exploration biases to previously rewarded positions. The model simulations and human data both show that during experimental experience exploration becomes limited to only those positions that have been rewarded in the past. Our study demonstrates how quite complex behavior may result from a simple sub-circuit within the basal ganglia pathways.

Hierarchical overlapping modular structure in the human cerebral cortex improves individual identification

The idea that brain networks have a hierarchical modular organization is pervasive. Increasing evidence suggests that brain modules overlap. However, little is known about the hierarchical overlapping modular structure in the brain. In this study, we developed a framework to uncover brain hierarchical overlapping modular structures based on a nested-spectral partition algorithm and an edge-centric network model. Overlap degree between brain modules is symmetrical across hemispheres, with highest overlap observed in the control and salience/ventral attention networks. Furthermore, brain edges are clustered into two groups: intrasystem and intersystem edges, to form hierarchical overlapping modules. At different levels, modules are self-similar in the degree of overlap. Additionally, the brain's hierarchical structure contains more individual identifiable information than a single-level structure, particularly in the control and salience/ventral attention networks. Our results offer pathways for future studies aimed at relating the organization of hierarchical overlapping modules to brain cognitive behavior and disorders.

A whole new world: embracing the systems-level to understand the indirect impact of pathology in neurodegenerative disorders

The direct link between neuropathology and the symptoms that emerge from damage to the brain is often difficult to discern. In this perspective, we argue that a satisfying account of neurodegenerative symptoms most naturally emerges from the consideration of the brain from the systems-level. Specifically, we will highlight the role of the neuromodulatory arousal system, which is uniquely positioned to coordinate the brain's ability to flexibly integrate the otherwise segregated structures required to support higher cognitive functions. Importantly, the neuromodulatory arousal system is highly heterogeneous, encompassing structures that are common sites of neurodegeneration across Alzheimer's and Parkinson's disease. We will review studies that implicate the dysfunctional interactions amongst distributed brain regions as a side-effect of pathological involvement of the neuromodulatory arousal system in these neurodegenerative disorders. From this perspective, we will argue that future work in clinical neuroscience should attempt to consider the inherent complexity in the brain and employ analytic techniques that do not solely focus on regional functional impairments, but rather captures the brain as an inherently dynamic, distributed, multi-scale system. Through this lens, we hope that we will devise new and improved diagnostic markers and interventional approaches to aid in the treatment of neurodegenerative disorders.

Efficient inference of synaptic plasticity rule with Gaussian process regression

Finding the form of synaptic plasticity is critical to understanding its functions underlying learning and memory. We investigated an efficient method to infer synaptic plasticity rules in various experimental settings. We considered biologically plausible models fitting a wide range of in-vitro studies and examined the recovery of their firing-rate dependence from sparse and noisy data. Among the methods assuming low-rankness or smoothness of plasticity rules, Gaussian process regression (GPR), a nonparametric Bayesian approach, performs the best. Under the conditions measuring changes in synaptic weights directly or measuring changes in neural activities as indirect observables of synaptic plasticity, which leads to different inference problems, GPR performs well. Also, GPR could simultaneously recover multiple plasticity rules and robustly perform under various plasticity rules and noise levels. Such flexibility and efficiency, particularly at the low sampling regime, make GPR suitable for recent experimental developments and inferring a broader class of plasticity models.

GABAergic neurons in the dorsomedial hypothalamus regulate states of consciousness in sevoflurane anesthesia

The neural inhibitory gamma-aminobutyric acid (GABA) system in the regulation of anesthetic consciousness is heterogeneous, and the medial hypothalamus (MH), consisting of ventromedial hypothalamus (VMH) and dorsomedial hypothalamus (DMH), plays an important role in sleep and circadian rhythm. However, the role of MH GABAergic neurons (MH^GABA) in anesthesia remains unclear. In this study, we used righting reflex, electroencephalogram (EEG), and arousal behavioral score to evaluate the sevoflurane anesthesia. Activation of MH^GABA or DMH^GABA neurons prolonged the anesthesia induction time, shortened the anesthesia emergence time, and induced EEG arousal and body movement during anesthesia; meanwhile, VMH^GABA neurons activated only induced EEG changes during 1.5% sevoflurane anesthesia. Furthermore, inhibition of DMH^GABA neurons significantly deepened sevoflurane anesthesia. Therefore, DMH^GABA neurons exert a strong emergence-promoting effect on induction, maintenance, and arousal during sevoflurane general anesthesia, which helps to reveal the mechanism of anesthesia.

Graded spikes differentially signal neurotransmitter input in cerebrospinal fluid contacting neurons of the mouse spinal cord

The action potential and its all-or-none nature is fundamental to neural communication. Canonically, the action potential is initiated once voltage-activated Na⁺ channels are activated, and their rapid kinetics of activation and inactivation give rise to the action potential's all-or-none nature. Here we demonstrate that cerebrospinal fluid contacting neurons (CSFcNs) surrounding the central canal of the mouse spinal cord employ a different strategy. Rather than using voltage-activated Na⁺ channels to generate binary spikes, CSFcNs use two different types of voltage-activated Ca²⁺ channel, enabling spikes of different amplitude. T-type Ca²⁺ channels generate small amplitude spikes, whereas larger amplitude spikes require high voltage-activated Cd²⁺-sensitive Ca²⁺ channels. We demonstrate that these different amplitude spikes can signal input from different transmitter systems; purinergic inputs evoke smaller T-type dependent spikes whereas cholinergic inputs evoke larger spikes that do not rely on T-type channels. Different synaptic inputs to CSFcNs can therefore be signaled by the spike amplitude.

Modulation of social investigation by anterior hypothalamic nucleus rhythmic neural activity

Social interactions involve both approach and avoidance toward specific individuals. Currently, the brain regions subserving these behaviors are not fully recognized. The anterior hypothalamic nucleus (AHN) is a poorly defined brain area, and recent studies have yielded contradicting conclusions regarding its behavioral role. Here we explored the role of AHN neuronal activity in regulating approach and avoidance actions during social interactions. Using electrophysiological recordings from behaving mice, we revealed that theta rhythmicity in the AHN is enhanced during affiliative interactions, but decreases during aversive ones. Moreover, the spiking activity of AHN neurons increased during the investigation of social stimuli, as compared to objects, and was modulated by theta rhythmicity. Finally, AHN optogenetic stimulation during social interactions augmented the approach toward stimuli associated with the stimulation. These results suggest the role for AHN neural activity in regulating approach behavior during social interactions, and for theta rhythmicity in mediating the valence of social stimuli.

Modeling foot sole cutaneous afferents: FootSim

While walking and maintaining balance, humans rely on cutaneous feedback from the foot sole. Electrophysiological recordings reveal how this tactile feedback is represented in neural afferent populations, but obtaining them is difficult and limited to stationary conditions. We developed the FootSim model, a realistic replication of mechanoreceptor activation in the lower limb. The model simulates neural spiking responses to arbitrary mechanical stimuli from the combined population of all four types of mechanoreceptors innervating the foot sole. It considers specific mechanics of the foot sole skin tissue, and model internal parameters are fitted using human microneurography recording dataset. FootSim can be exploited for neuroscientific insights, to understand the overall afferent activation in dynamic conditions, and for overcoming the limitation of currently available recording techniques. Furthermore, neuroengineers can use the model as a robust in silico tool for neuroprosthetic applications and for designing biomimetic stimulation patterns starting from the simulated afferent neural responses.

Aberrant cortical projections to amygdala GABAergic neurons contribute to developmental circuit dysfunction following early life stress

Early life stress (ELS) results in enduring dysfunction of the corticolimbic circuitry, underlying emotional and social behavior. However, the neurobiological mechanisms involved remain elusive. Here, we have combined viral tracing and electrophysiological techniques to study the effects of maternal separation (MS) on frontolimbic connectivity and function in young (P14-21) rats. We report that aberrant prefrontal inputs to basolateral amygdala (BLA) GABAergic interneurons transiently increase the strength of feed-forward inhibition in the BLA, which raises LTP induction threshold in MS treated male rats. The enhanced GABAergic activity after MS exposure associates with lower functional synchronization within prefrontal-amygdala networks in vivo. Intriguingly, no differences in these parameters were detected in females, which were also resistant to MS dependent changes in anxiety-like behaviors. Impaired plasticity and synchronization during the sensitive period of circuit refinement may contribute to long-lasting functional changes in the prefrontal-amygdaloid circuitry that predispose to neuropsychiatric conditions later on in life.

First few seconds for flow: A comprehensive proposal of the neurobiology and neurodynamics of state onset

Flow is a cognitive state that manifests when there is complete attentional absorption while performing a task. Flow occurs when certain internal as well as external conditions are present, including intense concentration, a sense of control, feedback, and a balance between the challenge of the task and the relevant skillset. Phenomenologically, flow is accompanied by a loss of self-consciousness, seamless integration of action and awareness, and acute changes in time perception. Research has begun to uncover some of the neurophysiological correlates of flow, as well as some of the state's neuromodulatory processes. We comprehensively review this work and consider the neurodynamics of the onset of the state, considering large-scale brain networks, as well as dopaminergic, noradrenergic, and endocannabinoid systems. To accomplish this, we outline an evidence-based hypothetical situation, and consider the flow state in a broader context including other profound alterations in consciousness, such as the psychedelic state and the state of traumatic stress that can induce PTSD. We present a broad theoretical framework which may motivate future testable hypotheses.

Plasticity after cognitive training reflected in prefrontal local field potentials

Learning to perform a new cognitive task induces plasticity of the prefrontal cortex generally involving activation of more neurons and increases in firing rate; however, its effects on single neurons are diverse and complex. We sought to understand how training affects global measures of neural activity by recording and analyzing local field potentials (LFPs) in monkeys before and after they learned to perform working memory tasks. LFP power after training was characterized by a reduction in power in 20-40 Hz during the stimulus presentations and delay periods of the task. Both evoked power, synchronized to task events, and induced power exhibited this decrease after training. The effect was consistent across tasks requiring memory of spatial location and stimulus shape. Error trials were characterized by a lack of LFP power ramping around the fixation onset. Our results reveal signatures of cortical plasticity in LFPs associated with learning to perform cognitive tasks.

Single-nucleus chromatin accessibility and RNA sequencing reveal impaired brain development in prenatally e-cigarette exposed neonatal rats

Although emerging evidence reveals that vaping alters the function of the central nervous system, the effects of maternal vaping on offspring brain development remain elusive. Using a well-established in utero exposure model, we performed single-nucleus ATAC-seq (snATAC-seq) and RNA sequencing (snRNA-seq) on prenatally e-cigarette-exposed rat brains. We found that maternal vaping distorted neuronal lineage differentiation in the neonatal brain by promoting excitatory neurons and inhibiting lateral ganglionic eminence-derived inhibitory neuronal differentiation. Moreover, maternal vaping disrupted calcium homeostasis, induced microglia cell death, and elevated susceptibility to cerebral ischemic injury in the developing brain of offspring. Our results suggest that the aberrant calcium signaling, diminished microglial population, and impaired microglia-neuron interaction may all contribute to the underlying mechanisms by which prenatal e-cigarette exposure impairs neonatal rat brain development. Our findings raise the concern that maternal vaping may cause adverse long-term brain damage to the offspring.

Model scenarios for cell cycle re-entry in Alzheimer's disease

Alzheimer's disease (AD) is the most prevalent neurodegenerative disease. Aberrant production and aggregation of amyloid beta (Aβ) peptide into plaques is a frequent feature of AD, but therapeutic approaches targeting Aβ accumulation fail to inhibit disease progression. The approved cholinesterase inhibitor drugs are symptomatic treatments. During human brain development, the progenitor cells differentiate into neurons and switch to a postmitotic state. However, cell cycle re-entry often precedes loss of neurons. We developed mathematical models of multiple routes leading to cell cycle re-entry in neurons that incorporate the crosstalk between cell cycle, neuronal, and apoptotic signaling mechanisms. We show that the integration of multiple feedback loops influences disease severity making the switch to pathological state irreversible. We observe that the transcriptional changes associated with this transition are also characteristics of the AD brain. We propose that targeting multiple arms of the feedback loop may bring about disease-modifying effects in AD.

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Developed mathematical models of cell cycle re-entry in Alzheimer's disease (AD)

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Integration of multiple feedback loops drives irreversible transition to AD

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Predicted transcriptional dysregulation is validated using AD gene expression data

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Inhibition of self-amplifying feedback loops brings about disease-modifying effects

Decoding defensive systems

Our understanding of the neuronal circuits and mechanisms of defensive systems has been primarily dominated by studies focusing on the contribution of individual cells in the processing of threat-predictive cues, defensive responses, the extinction of such responses and the contextual modulation of threat-related behavior. These studies have been key in establishing threat-related circuits and mechanisms. Yet, they fall short in answering long-standing questions related to the integrative processing of distinct threatening cues, behavioral states induced by threat-related events, or the bridging from sensory processing of threat-related cues to specific defensive responses. Recent conceptual and technical developments has allowed the monitoring of large populations of neurons, which in addition to advanced analytic tools, have improved our understanding of how collective neuronal activity supports threat-related behaviors. In this review, we discuss the current knowledge of neuronal population codes within threat-related networks, in the context of aversive motivated behavior and the study of defensive systems.

A network model of glymphatic flow under different experimentally-motivated parametric scenarios

Flow of cerebrospinal fluid (CSF) through perivascular spaces (PVSs) in the brain delivers nutrients, clears metabolic waste, and causes edema formation. Brain-wide imaging cannot resolve PVSs, and high-resolution methods cannot access deep tissue. However, theoretical models provide valuable insight. We model the CSF pathway as a network of hydraulic resistances, using published parameter values. A few parameters (permeability of PVSs and the parenchyma, and dimensions of PVSs and astrocyte endfoot gaps) have wide uncertainties, so we focus on the limits of their ranges by analyzing different parametric scenarios. We identify low-resistance PVSs and high-resistance parenchyma as the only scenario that satisfies three essential criteria: that the flow be driven by a small pressure drop, exhibit good CSF perfusion throughout the cortex, and exhibit a substantial increase in flow during sleep. Our results point to the most important parameters, such as astrocyte endfoot gap dimensions, to be measured in future experiments.

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We model the CSF pathway as a network of hydraulic resistances

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Predictions are bracketed by analyzing parametric scenarios for unknown parameters

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Low-resistance PVSs and high-resistance parenchyma produce realistic flows

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Astrocyte endfoot gap size is among the important parameters to be measured

A neural circuit perspective on brain aromatase

This review explores the role of aromatase in the brain as illuminated by a set of conserved network-level connections identified in several vertebrate taxa. Aromatase-expressing neurons are neurochemically heterogeneous but the brain regions in which they are found are highly-conserved across the vertebrate lineage. During development, aromatase neurons have a prominent role in sexual differentiation of the brain and resultant sex differences in behavior and human brain diseases. Drawing on literature primarily from birds and rodents, we delineate brain regions that express aromatase and that are strongly interconnected, and suggest that, in many species, aromatase expression essentially defines the Social Behavior Network. Moreover, in several cases the inputs to and outputs from this core Social Behavior Network also express aromatase. Recent advances in molecular and genetic tools for neuroscience now enable in-depth and taxonomically diverse studies of the function of aromatase at the neural circuit level.

Concurrent frontal and parietal network TMS for modulating attention

Transcranial magnetic stimulation (TMS) has been applied to frontal eye field (FEF) and intraparietal sulcus (IPS) in isolation, to study their role in attention. However, these nodes closely interact in a "dorsal attention network". Here, we compared effects of inhibitory TMS applied to individually fMRI-localized FEF or IPS (single-node TMS), to effects of simultaneously inhibiting both regions ("network TMS"), and sham. We assessed attention performance using the lateralized attention network test, which captures multiple facets of attention: spatial orienting, alerting, and executive control. TMS showed no effects on alerting and executive control. For spatial orienting, only network TMS showed a reduction of the orienting effect in the right hemifield compared to the left hemifield, irrespective of the order of TMS application (IPS→FEF or FEF→IPS). Network TMS might prevent compensatory mechanisms within a brain network, which is promising for both research and clinical applications to achieve superior neuromodulation effects.

Self-motion illusions from distorted optic flow in multifocal glasses

Progressive addition lenses (PALs) are ophthalmic lenses to correct presbyopia by providing improvements of near and far vision in different areas of the lens, but distorting the periphery of the wearer's field of view. Distortion-related difficulties reported by PAL wearers include unnatural self-motion perception. Visual self-motion perception is guided by optic flow, the pattern of retinal motion produced by self-motion. We tested the influence of PAL distortions on optic flow-based heading estimation using a model of heading perception and a virtual reality-based psychophysical experiment. The model predicted changes of heading estimation along a vertical axis, depending on visual field size and gaze direction. Consistent with this prediction, participants experienced upwards deviations of self-motion when gaze through the periphery of the lens was simulated, but not for gaze through the center. We conclude that PALs may lead to illusions of self-motion which could be remedied by a careful gaze strategy.

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Multifocal lenses impair vision of spectacle wearers with gaze-dependent distortions

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A model of heading perception from distorted optic flow suggest a misperception

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Heading perception was tested with a virtual reality-based simulation of distortions

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Distortions lead to gaze direction-dependent illusions in perceived vertical heading

The emergence of molecular systems neuroscience

Systems neuroscience is focused on how ensemble properties in the brain, such as the activity of neuronal circuits, gives rise to internal brain states and behavior. Many of the studies in this field have traditionally involved electrophysiological recordings and computational approaches that attempt to decode how the brain transforms inputs into functional outputs. More recently, systems neuroscience has received an infusion of approaches and techniques that allow the manipulation (e.g., optogenetics, chemogenetics) and imaging (e.g., two-photon imaging, head mounted fluorescent microscopes) of neurons, neurocircuits, their inputs and outputs. Here, we will review novel approaches that allow the manipulation and imaging of specific molecular mechanisms in specific cells (not just neurons), cell ensembles and brain regions. These molecular approaches, with the specificity and temporal resolution appropriate for systems studies, promise to infuse the field with novel ideas, emphases and directions, and are motivating the emergence of a molecularly oriented systems neuroscience, a new discipline that studies how the spatial and temporal patterns of molecular systems modulate circuits and brain networks, and consequently shape the properties of brain states and behavior.

Functional ultrasound imaging: A useful tool for functional connectomics?

Functional ultrasound (fUS) is a hemodynamic-based functional neuroimaging technique, primarily used in animal models, that combines a high spatiotemporal resolution, a large field of view, and compatibility with behavior. These assets make fUS especially suited to interrogating brain activity at the systems level. In this review, we describe the technical capabilities offered by fUS and discuss how this technique can contribute to the field of functional connectomics. First, fUS can be used to study intrinsic functional connectivity, namely patterns of correlated activity between brain regions. In this area, fUS has made the most impact by following connectivity changes in disease models, across behavioral states, or dynamically. Second, fUS can also be used to map brain-wide pathways associated with an external event. For example, fUS has helped obtain finer descriptions of several sensory systems, and uncover new pathways implicated in specific behaviors. Additionally, combining fUS with direct circuit manipulations such as optogenetics is an attractive way to map the brain-wide connections of defined neuronal populations. Finally, technological improvements and the application of new analytical tools promise to boost fUS capabilities. As brain coverage and the range of behavioral contexts that can be addressed with fUS keep on increasing, we believe that fUS-guided connectomics will only expand in the future. In this regard, we consider the incorporation of fUS into multimodal studies combining diverse techniques and behavioral tasks to be the most promising research avenue.

Neuronal population models reveal specific linear conductance controllers sufficient to rescue preclinical disease phenotypes

Preclinical drug candidates are screened for their ability to ameliorate in vitro neuronal electrophysiology, and go/no-go decisions progress drugs to clinical trials based on population means across cells and animals. However, these measures do not mitigate clinical endpoint risk. Population-based modeling captures variability across multiple electrophysiological measures from healthy, disease, and drug phenotypes. We pursued optimizing therapeutic targets by identifying coherent sets of ion channel target modulations for recovering heterogeneous wild-type (WT) population excitability profiles from a heterogeneous Huntington's disease (HD) population. Our approach combines mechanistic simulations with population modeling of striatal neurons using evolutionary optimization algorithms to design 'virtual drugs'. We introduce efficacy metrics to score populations and rank virtual drug candidates. We found virtual drugs using heuristic approaches that performed better than single target modulators and standard classification methods. We compare a real drug to virtual candidates and demonstrate a novel in silico triaging method.

An integrated multi-omic analysis of iPSC-derived motor neurons from C9ORF72 ALS patients

Neurodegenerative diseases are challenging for systems biology because of the lack of reliable animal models or patient samples at early disease stages. Induced pluripotent stem cells (iPSCs) could address these challenges. We investigated DNA, RNA, epigenetics, and proteins in iPSC-derived motor neurons from patients with ALS carrying hexanucleotide expansions in C9ORF72. Using integrative computational methods combining all omics datasets, we identified novel and known dysregulated pathways. We used a C9ORF72 Drosophila model to distinguish pathways contributing to disease phenotypes from compensatory ones and confirmed alterations in some pathways in postmortem spinal cord tissue of patients with ALS. A different differentiation protocol was used to derive a separate set of C9ORF72 and control motor neurons. Many individual -omics differed by protocol, but some core dysregulated pathways were consistent. This strategy of analyzing patient-specific neurons provides disease-related outcomes with small numbers of heterogeneous lines and reduces variation from single-omics to elucidate network-based signatures.

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Multi-omic analysis of differentiated C9ORF72 iPSC-derived motor neurons

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Network-based integrative computational analysis

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Pathogenic versus compensatory pathways elucidated using C9ORF72 Drosophila model

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Pathways confirmed with alternative differentiation protocol and postmortem data

Bridging large-scale cortical networks: Integrative and function-specific hubs in the thalamus

The thalamus is critical for the brain's integrative hub functions; however, the localization and characterization of the different thalamic hubs remain unclear. Using a voxel-level network measure called functional connectivity overlap ratio (FCOR), we examined the thalamus' association with large-scale resting-state networks (RSNs) to elucidate its connector hub roles. Connections to the core-neurocognitive networks were localized in the anterior and medial parts, such as the anteroventral and mediodorsal nuclei areas. Regions functionally connected to the sensorimotor network were distinctively located around the lateral pulvinar nucleus but to a limited extent. Prominent connector hubs include the anteroventral, ventral lateral, and mediodorsal nuclei with functional connections to multiple RSNs. These findings suggest that the thalamus, with extensive connections to most of the RSNs, is well placed as a critical integrative functional hub and could play an important role for functional integration facilitating brain functions associated with primary processing and higher cognition.

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Multiple large-scale cortical networks converged in the thalamus

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Neurocognitive associated hub existed in the anterior and medial region

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Control-processing hub localized in the intermediate thalamus

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Sensorimotor network was located around the lateral pulvinar nucleus

A single cell transcriptomics map of paracrine networks in the intrinsic cardiac nervous system

We developed a spatially-tracked single neuron transcriptomics map of an intrinsic cardiac ganglion, the right atrial ganglionic plexus (RAGP) that is a critical mediator of sinoatrial node (SAN) activity. This 3D representation of RAGP used neuronal tracing to extensively map the spatial distribution of the subset of neurons that project to the SAN. RNA-seq of laser capture microdissected neurons revealed a distinct composition of RAGP neurons compared to the central nervous system and a surprising finding that cholinergic and catecholaminergic markers are coexpressed, suggesting multipotential phenotypes that can drive neuroplasticity within RAGP. High-throughput qPCR of hundreds of laser capture microdissected single neurons confirmed these findings and revealed a high dimensionality of neuromodulatory factors that contribute to dynamic control of the heart. Neuropeptide-receptor coexpression analysis revealed a combinatorial paracrine neuromodulatory network within RAGP informing follow-on studies on the vagal control of RAGP to regulate cardiac function in health and disease.

3D single cell scale anatomical map of sex-dependent variability of the rat intrinsic cardiac nervous system

We developed and analyzed a single cell scale anatomical map of the rat intrinsic cardiac nervous system (ICNS) across four male and three female hearts. We find the ICNS has a reliable structural organizational plan across individuals that provide the foundation for further analyses of the ICNS in cardiac function and disease. The distribution of the ICNS was evaluated by 3D visualization and data-driven clustering. The pattern, distribution, and clustering of ICNS neurons across all male and female rat hearts is highly conserved, demonstrating a coherent organizational plan where distinct clusters of neurons are consistently localized. Female hearts had fewer neurons, lower packing density, and slightly reduced distribution, but with identical localization. We registered the anatomical data from each heart to a geometric scaffold, normalizing their 3D coordinates for standardization of common anatomical planes and providing a path where multiple experimental results and data types can be integrated and compared.

Intergenerational transmission of the patterns of functional and structural brain networks

There is clear evidence of intergenerational transmission of life values, cognitive traits, psychiatric disorders, and even aspects of daily decision making. To investigate biological substrates of this phenomenon, the brain has received increasing attention as a measurable biomarker and potential target for intervention. However, no previous study has quantitatively and comprehensively investigated the effects of intergenerational transmission on functional and structural brain networks. Here, by employing an unusually large cohort dataset (N = 84 parent-child dyads; 45 sons, 39 daughters, 81 mothers, and 3 fathers), we show that patterns of functional and structural brain networks are preserved over a generation. We also demonstrate that several demographic factors and behavioral/physiological phenotypes have a relationship with brain similarity. Collectively, our results provide a comprehensive picture of neurobiological substrates of intergenerational transmission and demonstrate the usability of our dataset for investigating the neurobiological substrates of intergenerational transmission.

Neural mechanisms underlying the role of fructose in overfeeding

Fructose consumption has been linked with metabolic syndrome and obesity. Fructose-based sweeteners like high fructose corn syrup taste sweeter, improve food palatability, and are increasingly prevalent in our diet. The increase in fructose consumption precedes the rise in obesity and is a contributing driver to the obesity epidemic worldwide. The role of dietary fructose in obesity can be multifactorial by promoting visceral adiposity, hypertension, and insulin resistance. Interestingly, one emergent finding from human and animal studies is that dietary fructose promotes overfeeding. As the brain is a critical regulator of food intake, we reviewed the evidence that fructose can act in the brain and elucidated the major brain systems underlying fructose-induced overfeeding. We found that fructose acts on multiple interdependent brain systems to increase orexigenic drive and the incentive salience of food while decreasing the latency between food bouts and reducing cognitive control to disinhibit feeding. We concluded that the collective actions of fructose may promote feeding behavior by producing a hunger-like state in the brain.

Relationships between lognormal distributions of neural properties, activity, criticality, and connectivity

Relationships between convergence of inputs onto neurons, divergence of outputs from them, synaptic strengths, nonlinear firing response properties, and randomness of axonal ranges are systematically explored by interrelating means and variances of synaptic strengths, firing rates, and soma voltages. When self-consistency is imposed, it is found that broad distributions of synaptic strength are a necessary concomitant of the known massive convergence of inputs to individual neurons, and observed widths of lognormal distributions of synaptic strength and firing rate are explained provided the brain is in a near-critical state, consistent with independent observations. The strongest individual synapses are shown to have an effect on soma voltage comparable to the effect of all others combined, which supports suggestions that they may have a key role in neural communication. Remarkably, inclusion of moderate randomness in characteristic axonal ranges is shown to account for the observed [Formula: see text]-fold variability in two-point connectivity at a given separation and [Formula: see text]-fold overall when the known mean exponential fall-off is included, consistent with observed near-lognormal distributions. Inferred axonal deviations from straight-line paths are also consistent with independent estimates.

Risk factors of pain, physical function, and health-related quality of life in elderly people with knee osteoarthritis: A cross-sectional study

Data on the precise mechanisms of the complex interactions of factors related to clinical impact of knee osteoarthritis (KOA) in the elderly population remain limited. To find predictors that explain pain intensity, physical function, and quality of life in elderly KOA subjects, we performed a cross-sectional analysis of the baseline data from a randomized trial. The trial included 104 subjects (aged ≥60) with KOA pain and dysfunctional endogenous pain-inhibitory system activity assessed by conditioned pain modulation (CPM). Three multiple linear regression models were performed to understand the independent predictors of Brief Pain Inventory (BPI), WOMAC function subscale (WOMACFunc), and SF-12 physical subscale (SF12-PCS). Model 1 showed that BPI pain score was predicted by low CPM response, high von-Frey light touch threshold, worse radiological severity as indexed by Kellgren-Lawrence grade (KL), high von-Frey punctate pain intensity and high levels of anxiety (adjusted R2 = 27.1%, F (6,95) = 7.27, P < 0.0001). In model 2, von-Frey light touch threshold, KL, depressive symptoms indexed by Beck Depression Inventory (BDI), level of sleepiness and pain pressure threshold were risk factors for SF12-PCS (adjusted R2 = 31.9%, F (5,96) = 10.5, P < 0.0001). Finally, model 3 showed that WOMACFunc was predicted by BDI, KL and BPI (adjusted R2 = 41%, F (3,98) = 24.42, P < 0.0001). Our data provides an interesting framework to understand the predictors of KOA pain in the elderly and highlights how its related outcomes are affected by disease-specific factors, somatosensory dysfunction and emotional factors.