Phototaxis is a satiety-dependent behavioral sequence in Hydra vulgaris.

Understanding how internal states like satiety are connected to animal behavior is a fundamental question in neuroscience. Hydra vulgaris, a freshwater cnidarian with only twelve neuronal cell types, serves as a tractable model system for studying state-dependent behaviors. We find that starved Hydra consistently move towards light, while fed Hydra do not. By modeling this behavior as a set of three sequences of head orientation, jump distance, and jump rate, we demonstrate that the satiety state only affects the rate of the animal jumping to a new position, while the orientation and jump distance are unaffected. These findings yield insights into how internal states in a simple organism, Hydra, affect specific elements of a behavior, and offer general principles for studying the relationship between state-dependent behaviors and their underlying molecular mechanisms.

The use of proxy measurement of internal states in people with intellectual disability: A scoping review.

BACKGROUND: The measurement of internal states of people with an intellectual disability is challenging. Given these difficulties, proxy respondents are sometimes used. However, the literature provides some caution about the validity of the use of proxy respondents. AIMS: This review aims to identify the available evidence regarding the use of proxy respondents in the measurement of internal states of people with intellectual disabilities. METHOD: The Arksey and O'Malley scoping review framework was used for this review, refined with the Joanna Briggs Institute Methodology. RESULTS: Results indicate there are some differences in the findings reported with respect to the efficacy of the use of proxy respondents. These may be due to a number of inconsistencies and weaknesses in examinations of their utility. CONCLUSIONS: If proxy-reports are to be useful in understanding the internal states of people with intellectual disability, researchers need to address the shortcomings revealed by this review.

The Calmodulin-interacting peptide Pcp4a regulates feeding state-dependent behavioral choice in zebrafish.

Animals constantly need to judge the valence of an object in their environment: is it potential food or a threat? The brain makes fundamental decisions on the appropriate behavioral strategy by integrating external information from sensory organs and internal signals related to physiological needs. For example, a hungry animal may take more risks than a satiated one when deciding to approach or avoid an object. Using a proteomic profiling approach, we identified the Calmodulin-interacting peptide Pcp4a as a key regulator of foraging-related decisions. Food intake reduced abundance of protein and mRNA of pcp4a via dopamine D2-like receptor-mediated repression of adenylate cyclase. Accordingly, deleting the pcp4a gene made zebrafish larvae more risk averse in a binary decision assay. Strikingly, neurons in the tectum became less responsive to prey-like visual stimuli in pcp4a mutants, thus biasing the behavior toward avoidance. This study pinpoints a molecular mechanism modulating behavioral choice according to internal state.

Simultaneous, cortex-wide and cellular-resolution neuronal population dynamics reveal an unbounded scaling of dimensionality with neuron number.

The brain's remarkable properties arise from collective activity of millions of neurons. Widespread application of dimensionality reduction to multi-neuron recordings implies that neural dynamics can be approximated by low-dimensional "latent" signals reflecting neural computations. However, what would be the biological utility of such a redundant and metabolically costly encoding scheme and what is the appropriate resolution and scale of neural recording to understand brain function? Imaging the activity of one million neurons at cellular resolution and near-simultaneously across mouse cortex, we demonstrate an unbounded scaling of dimensionality with neuron number. While half of the neural variance lies within sixteen behavior-related dimensions, we find this unbounded scaling of dimensionality to correspond to an ever-increasing number of internal variables without immediate behavioral correlates. The activity patterns underlying these higher dimensions are fine-grained and cortex-wide, highlighting that large-scale recording is required to uncover the full neural substrates of internal and potentially cognitive processes.

Mechanisms for survival: vagal control of goal-directed behavior.

Survival is a fundamental physiological drive, and neural circuits have evolved to prioritize actions that meet the energy demands of the body. This fine-tuning of goal-directed actions based on metabolic states ('allostasis') is deeply rooted in our brain, and hindbrain nuclei orchestrate the vital communication between the brain and body through the vagus nerve. Despite mounting evidence for vagal control of allostatic behavior in animals, its broader function in humans is still contested. Based on stimulation studies, we propose that the vagal afferent pathway supports transitions between survival modes by gating the integration of ascending bodily signals, thereby regulating reward-seeking. By reconceptualizing vagal signals as catalysts for goal-directed behavior, our perspective opens new avenues for theory-driven translational work in mental disorders.

Synaptic plasticity through a naturalistic lens.

From the myriad of studies on neuronal plasticity, investigating its underlying molecular mechanisms up to its behavioral relevance, a very complex landscape has emerged. Recent efforts have been achieved toward more naturalistic investigations as an attempt to better capture the synaptic plasticity underpinning of learning and memory, which has been fostered by the development of in vivo electrophysiological and imaging tools. In this review, we examine these naturalistic investigations, by devoting a first part to synaptic plasticity rules issued from naturalistic in vivo-like activity patterns. We next give an overview of the novel tools, which enable an increased spatio-temporal specificity for detecting and manipulating plasticity expressed at individual spines up to neuronal circuit level during behavior. Finally, we put particular emphasis on works considering brain-body communication loops and macroscale contributors to synaptic plasticity, such as body internal states and brain energy metabolism.

The Seeking Proxies for Internal States (SPIS) Model of OCD - A Comprehensive Review of Current Findings and Implications for Future Directions.

The Seeking Proxies for Internal States (SPIS) model of obsessive-compulsive disorder (OCD) explains symptoms of OCD as stemming from attenuated access to internal states, which is compensated for by using proxies, which are indices of these states that are more discernible or less ambiguous. Internal states in the SPIS model are subjective states that are not accessible to others, encompassing physiological states, motivations, preferences, memories, and emotions. Compensatory proxies in OCD include fixed rules and rituals as well as seeking and relying on external information. In the present review, we outline the SPIS model and describe its basic tenets. We then use the SPIS conceptualization to explain two pivotal OCD-related phenomena - obsessive doubt and compulsive rituals. Next, we provide a detailed overview of current empirical evidence supporting the SPIS in several domains, including physiological states, emotions, sense of understanding, decision-making, and sense of agency. We conclude by discussing possible neural correlates of the difficulty in accessing internal states, focusing on the anterior insular cortex (AIC) and highlighting potential clinical implications of the model to the treatment of OCD.

Obsessive-Compulsive Symptoms in Children Are Related to Sensory Sensitivity and to Seeking Proxies for Internal States.

Symptoms of obsessive-compulsive disorder are related to atypical sensory processing, particularly sensory over-responsivity, in both children and adults. In adults, obsessive-compulsive symptoms are also associated with the attenuation of access to the internal state and compensatory reliance on proxies for these states, including fixed rules and rituals. We aimed to examine the associations between sensory over-responsivity, the tendency to seek proxies for internal states, and obsessive-compulsive symptoms in children. Parents of 404 children between 5 and 10 years of age completed online measures of obsessive-compulsive symptoms, seeking proxies for internal states, sensory over-responsivity, and anxiety. Linear regression, dominance analysis, and network analysis were used to explore the unique associations between these variables. The tendency to seek proxies for internal states was more strongly associated with obsessive-compulsive symptoms than with anxiety symptoms and uniquely associated with all major obsessive-compulsive symptom dimensions except obsessing. Both the tendency to seek proxies for internal states and sensory over-responsivity were significantly associated with obsessive-compulsive symptoms, but the association was significantly stronger for the tendency to seek proxies for internal states. While limited by the sole reliance on the parent-report, the present study shows that the tendency to seek proxies for internal states could help clarify the developmental processes involved in the onset of obsessive-compulsive symptoms during childhood and that sensory sensitivity may be important to consider in this process.

Toward an integrative account of internal and external determinants of event segmentation.

Our daily experiences unfold continuously, but we remember them as a series of discrete events through a process called event segmentation. Prominent theories of event segmentation suggest that event boundaries in memory are triggered by significant shifts in the external environment, such as a change in one's physical surroundings. In this review, we argue for a fundamental extension of this research field to also encompass internal state changes as playing a key role in structuring event memory. Accordingly, we propose an expanded taxonomy of event boundary-triggering processes, and review behavioral and neuroscience research on internal state changes in three core domains: affective states, goal states, and motivational states. Finally, we evaluate how well current theoretical frameworks can accommodate the unique and interactive contributions of internal states to event memory. We conclude that a theoretical perspective on event memory that integrates both external environment and internal state changes allows for a more complete understanding of how the brain structures experiences, with important implications for future research in cognitive and clinical neuroscience.

Brain-wide representations of behavior spanning multiple timescales and states in C. elegans.

Changes in an animal's behavior and internal state are accompanied by widespread changes in activity across its brain. However, how neurons across the brain encode behavior and how this is impacted by state is poorly understood. We recorded brain-wide activity and the diverse motor programs of freely moving C. elegans and built probabilistic models that explain how each neuron encodes quantitative behavioral features. By determining the identities of the recorded neurons, we created an atlas of how the defined neuron classes in the C. elegans connectome encode behavior. Many neuron classes have conjunctive representations of multiple behaviors. Moreover, although many neurons encode current motor actions, others integrate recent actions. Changes in behavioral state are accompanied by widespread changes in how neurons encode behavior, and we identify these flexible nodes in the connectome. Our results provide a global map of how the cell types across an animal's brain encode its behavior.

From perception to behavior: The neural circuits underlying prey hunting in larval zebrafish.

A key challenge for neural systems is to extract relevant information from the environment and make appropriate behavioral responses. The larval zebrafish offers an exciting opportunity for studying these sensing processes and sensory-motor transformations. Prey hunting is an instinctual behavior of zebrafish that requires the brain to extract and combine different attributes of the sensory input and form appropriate motor outputs. Due to its small size and transparency the larval zebrafish brain allows optical recording of whole-brain activity to reveal the neural mechanisms involved in prey hunting and capture. In this review we discuss how the larval zebrafish brain processes visual information to identify and locate prey, the neural circuits governing the generation of motor commands in response to prey, how hunting behavior can be modulated by internal states and experience, and some outstanding questions for the field.

Adaption and validation of the Perceived Control of Internal States Scale (PCOISS) in Chinese adults: a cross-sectional study.

BACKGROUND: Perceived control of internal states is important for disease prevention, stress buffering and life adaptability. However, there is no psychometric scale to measure control beliefs over internal states in China. This study aimed to adapt and validate the Perceived Control of Internal States Scale (PCOISS) in a large sample of Chinese adults. METHODS: Data was collected through a big project, in which a cross-sectional online survey was conducted nationwide in China using a powerful Chinese online survey platform named WenJuanXing ( https://www.wjx.cn/ ). We translated the PCOISS into Chinese (C-PCOISS) with the forward-backward translation procedure. For the first time of the survey, a sample of 2709 participants (Sample 1) was valid for final analysis. Sample 1 was split into two datasets for principal component analysis (PCA) (nA = 1355) and confirmatory factor analyses (CFA) (nB = 1354) to determine potential factor structure. The scale's validity (i.e., discriminant validity, convergent validity, criterion validity) and internal consistency reliability were evaluated. Among the 1354 respondents (nB), 761 (nC = 761) participated in the follow-up second wave of the survey to assess a cross-sectional test-retest reliability. RESULTS: The C-PCOISS retained 14 items. PCA yielded a three-factor model which was supported with the best fit indices in CFA. The C-PCOISS had satisfactory internal consistency with Cronbach's alpha coefficients of 0.86, 0.78 and 0.72 for three subscales, respectively. The scale also showed adequate test-retest reliability (Pearson correlations coefficient of 0.64, 0.62 and 0.54 with p < 0.001 for three subscales, respectively). Three factors of the C-PCOISS were positively associated with positive affect, and negatively associated with negative affect, depression, compulsion-anxiety and perceived stress. CONCLUSIONS: The C-PCOISS is reliable and valid for measuring control beliefs over internal states in Chinese adults.

Flexibility of neural circuits regulating mating behaviors in mice and flies.

Mating is essential for the reproduction of animal species. As mating behaviors are high-risk and energy-consuming processes, it is critical for animals to make adaptive mating decisions. This includes not only finding a suitable mate, but also adapting mating behaviors to the animal's needs and environmental conditions. Internal needs include physical states (e.g., hunger) and emotional states (e.g., fear), while external conditions include both social cues (e.g., the existence of predators or rivals) and non-social factors (e.g., food availability). With recent advances in behavioral neuroscience, we are now beginning to understand the neural basis of mating behaviors, particularly in genetic model organisms such as mice and flies. However, how internal and external factors are integrated by the nervous system to enable adaptive mating-related decision-making in a state- and context-dependent manner is less well understood. In this article, we review recent knowledge regarding the neural basis of flexible mating behaviors from studies of flies and mice. By contrasting the knowledge derived from these two evolutionarily distant model organisms, we discuss potential conserved and divergent neural mechanisms involved in the control of flexible mating behaviors in invertebrate and vertebrate brains.

The emergence and influence of internal states.

Animal behavior is shaped by a variety of "internal states"-partially hidden variables that profoundly shape perception, cognition, and action. The neural basis of internal states, such as fear, arousal, hunger, motivation, aggression, and many others, is a prominent focus of research efforts across animal phyla. Internal states can be inferred from changes in behavior, physiology, and neural dynamics and are characterized by properties such as pleiotropy, persistence, scalability, generalizability, and valence. To date, it remains unclear how internal states and their properties are generated by nervous systems. Here, we review recent progress, which has been driven by advances in behavioral quantification, cellular manipulations, and neural population recordings. We synthesize research implicating defined subsets of state-inducing cell types, widespread changes in neural activity, and neuromodulation in the formation and updating of internal states. In addition to highlighting the significance of these findings, our review advocates for new approaches to clarify the underpinnings of internal brain states across the animal kingdom.

Using Smartphone Sensor Paradata and Personalized Machine Learning Models to Infer Participants' Well-being: Ecological Momentary Assessment.

BACKGROUND: Sensors embedded in smartphones allow for the passive momentary quantification of people's states in the context of their daily lives in real time. Such data could be useful for alleviating the burden of ecological momentary assessments and increasing utility in clinical assessments. Despite existing research on using passive sensor data to assess participants' moment-to-moment states and activity levels, only limited research has investigated temporally linking sensor assessment and self-reported assessment to further integrate the 2 methodologies. OBJECTIVE: We investigated whether sparse movement-related sensor data can be used to train machine learning models that are able to infer states of individuals' work-related rumination, fatigue, mood, arousal, life engagement, and sleep quality. Sensor data were only collected while the participants filled out the questionnaires on their smartphones. METHODS: We trained personalized machine learning models on data from employees (N=158) who participated in a 3-week ecological momentary assessment study. RESULTS: The results suggested that passive smartphone sensor data paired with personalized machine learning models can be used to infer individuals' self-reported states at later measurement occasions. The mean R2 was approximately 0.31 (SD 0.29), and more than half of the participants (119/158, 75.3%) had an R2 of ≥0.18. Accuracy was only slightly attenuated compared with earlier studies and ranged from 38.41% to 51.38%. CONCLUSIONS: Personalized machine learning models and temporally linked passive sensing data have the capability to infer a sizable proportion of variance in individuals' daily self-reported states. Further research is needed to investigate factors that affect the accuracy and reliability of the inference.

Emotion Recognizing by a Robotic Solution Initiative (EMOTIVE Project).

BACKGROUND: Emotion recognition skills are predicted to be fundamental features in social robots. Since facial detection and recognition algorithms are compute-intensive operations, it needs to identify methods that can parallelize the algorithmic operations for large-scale information exchange in real time. The study aims were to identify if traditional machine learning algorithms could be used to assess every user emotions separately, to relate emotion recognizing in two robotic modalities: static or motion robot, and to evaluate the acceptability and usability of assistive robot from an end-user point of view. METHODS: Twenty-seven hospital employees (M = 12; F = 15) were recruited to perform the experiment showing 60 positive, negative, or neutral images selected in the International Affective Picture System (IAPS) database. The experiment was performed with the Pepper robot. Concerning experimental phase with Pepper in active mode, a concordant mimicry was programmed based on types of images (positive, negative, and neutral). During the experimentation, the images were shown by a tablet on robot chest and a web interface lasting 7 s for each slide. For each image, the participants were asked to perform a subjective assessment of the perceived emotional experience using the Self-Assessment Manikin (SAM). After participants used robotic solution, Almere model questionnaire (AMQ) and system usability scale (SUS) were administered to assess acceptability, usability, and functionality of robotic solution. Analysis wasperformed on video recordings. The evaluation of three types of attitude (positive, negative, andneutral) wasperformed through two classification algorithms of machine learning: k-nearest neighbors (KNN) and random forest (RF). RESULTS: According to the analysis of emotions performed on the recorded videos, RF algorithm performance wasbetter in terms of accuracy (mean ± sd = 0.98 ± 0.01) and execution time (mean ± sd = 5.73 ± 0.86 s) than KNN algorithm. By RF algorithm, all neutral, positive and negative attitudes had an equal and high precision (mean = 0.98) and F-measure (mean = 0.98). Most of the participants confirmed a high level of usability and acceptability of the robotic solution. CONCLUSIONS: RF algorithm performance was better in terms of accuracy and execution time than KNN algorithm. The robot was not a disturbing factor in the arousal of emotions.

Attenuated Access to Emotions in Obsessive-Compulsive Disorder.

The Seeking Proxies for Internal States (SPIS) model of obsessive-compulsive disorder (OCD) posits that OCD is associated with attenuated access to internal states. Here we explored the implications of this model in the realm of emotions. Participants with OCD, anxiety disorders, and nonclinical control participants completed the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT), assessing two domains of emotional intelligence: Experiential emotional intelligence (EI), reflecting the ability to perceive and feel emotions accurately, and Strategic EI, reflecting the ability to understand and manage emotions correctly. As only Experiential EI requires accurate perception of one's emotions for adequate performance, we predicted an interaction between group and EI area. Specifically, we predicted that compared to both anxiety disorders and healthy control participants, OCD participants would show a larger deficit in Experiential area of the MSCEIT relative to the Strategic area. Results were fully in line with this prediction. Moreover, supporting the specificity of the hypothesized deficit to OCD, participants with anxiety disorders did not differ from nonclinical control participants in their performance, and findings were not attributable to anxiety or depression levels. These results replicate and extend previous findings obtained with analogue samples and suggest that OCD is associated with attenuated access to emotional states, which may be partially compensated for by reliance on semantic knowledge of emotion.

Development and validation of the Interoceptive States Static Images (ISSI) database.

Internal bodily signals provide an essential function for human survival. Accurate recognition of such signals in the self, known as interoception, supports the maintenance of homeostasis, and is closely related to emotional processing, learning and decision-making, and mental health. While numerous studies have investigated interoception in the self, the recognition of these states in others has not been examined despite its crucial importance for successful social relationships. This paper presents the development and validation of the Interoceptive States Static Images (ISSI), introducing a validated database of 423 visual stimuli for the study of non-affective internal state recognition in others, freely available to other researchers. Actors were photographed expressing various exemplars of both interoceptive states and control actions. The images went through a two-stage validation procedure, the first involving free-labelling and the second using multiple choice labelling and quality rating scales. Five scores were calculated for each stimulus, providing information about the quality and specificity of the depiction, as well as the extent to which labels matched the intended state/action. Results demonstrated that control action stimuli were more recognisable than internal state stimuli. Inter-category variability was found for the internal states, with some states being more recognisable than others. Recommendations for the utilisation of ISSI stimuli are discussed. The stimulus set is freely available to researchers, alongside data concerning recognisability.

Metaphorical expressions originating from human senses: Psycholinguistic and affective norms for German metaphors for internal state terms (MIST database).

Internal states, e.g., emotions, cognitive states, or desires, are often verbalized by figurative means, in particular by embodied metaphors involving human senses, such as touch, taste, and smell. The present paper presents a database for German metaphorical expressions conveying internal states with human senses as their source domains. 168 metaphorical expressions from the source domains of vision, hearing, smell, taste, touch, and temperature combined with literal equivalents were collected and rated by 643 adults. The agreement between the metaphor and an equivalent literal expression, as well as emotional valence, arousal, and familiarity values were assessed using a 7-point Likert scale. Between the metaphorical expressions and their equivalents, familiarity, but not valence or arousal differed significantly while agreement ratings indicated high similarity in meaning. The novel database offers carefully controlled stimuli that can be used in both empirical metaphor research and research on internal state language. Using part of the stimuli in a sentence completion experiment revealed a significant preference for literal over metaphorical expressions that cannot be attributed to higher familiarity levels.

Seeking proxies for internal states (SPIS): Towards a novel model of obsessive-compulsive disorder.

The Seeking Proxies for Internal States (SPIS) model of obsessive-compulsive disorder (OCD) proposes an account of OCD symptoms in terms of two core components: attenuation of access to internal states and seeking proxies for internal states. Specifically, the SPIS model posits that OCD is associated with difficulty in accessing various internal states, including feelings, preferences, memories, and even physiological states. This difficulty drives obsessive-compulsive individuals seek and rely on compensatory proxies, or substitutes, for their internal states. These proxies are perceived by the individual with OCD to be more easily discernible or less ambiguous compared to the internal states for which they substitute, and can take the form of fixed rules, rituals, or reliance on external sources of information. In the present article we first provide a detailed explanation of the SPIS model, and then review empirical studies that examined the model in a variety of domains, including bodily states, emotions, and decision-making. Next, we elaborate on the SPIS model's novel account of compulsive rituals, obsessions and doubt and relate them to extant theoretical accounts of OCD. To conclude, we highlight open questions that can guide future research and discuss the model's clinical implications.