Stress in autism (STREAM): A study protocol on the role of circadian activity, sleep quality and sensory reactivity.

Mental health issues are markedly increased in individuals with autism, making it the number one research priority by stakeholders. There is a crucial need to use personalized approaches to understand the underpinnings of mental illness in autism and consequently, to address individual needs. Based on the risk factors identified in typical mental research, we propose the following themes central to mental health issues in autism: sleep difficulties and stress. Indeed, the prevalence of manifold circadian disruptions and sleep difficulties in autism, alongside stress related to sensory overload, forms an integral part of autistic symptomatology. This proof-of-concept study protocol outlines an innovative, individualised approach towards investigating the interrelationships between stress indices, sleep and circadian activation patterns, and sensory sensitivity in autism. Embracing an individualized methodology, we aim to collect 14 days of data per participant from 20 individuals with autism diagnoses and 20 without. Participants' sleep will be monitored using wearable EEG headbands and a sleep diary. Diurnal tracking of heart rate and electrodermal activity through wearables will serve as proxies of stress. Those objective data will be synchronized with subjective experience traces collected throughout the day using the Temporal Experience Tracing (TET) method. TET facilitates the quantification of relevant aspects of individual experience states, such as stress or sensory sensitivities, by providing a continuous multidimensional description of subjective experiences. Capturing the dynamics of subjective experiences phase-locked to neural and physiological proxies both between and within individuals, this approach has the potential to contribute to our understanding of critical issues in autism, including sleep problems, sensory reactivity and stress. The planned strives to provide a pathway towards developing a more nuanced and individualized approach to addressing mental health in autism.

Autistic adults perceive and experience laughter differently to non-autistic adults.

Human interaction is immersed in laughter; though genuine and posed laughter are acoustically distinct, they are both crucial socio-emotional signals. In this novel study, autistic and non-autistic adults explicitly rated the affective properties of genuine and posed laughter. Additionally, we explored whether their self-reported everyday experiences with laughter differ. Both groups could differentiate between these two types of laughter. However, autistic adults rated posed laughter as more authentic and emotionally arousing than non-autistic adults, perceiving it to be similar to genuine laughter. Autistic adults reported laughing less, deriving less enjoyment from laughter, and experiencing difficulty in understanding the social meaning of other people's laughter compared to non-autistic people. Despite these differences, autistic adults reported using laughter socially as often as non-autistic adults, leveraging it to mediate social contexts. Our findings suggest that autistic adults show subtle differences in their perception of laughter, which may be associated with their struggles in comprehending the social meaning of laughter, as well as their diminished frequency and enjoyment of laughter in everyday scenarios. By combining experimental evidence with first-person experiences, this study suggests that autistic adults likely employ different strategies to understand laughter in everyday contexts, potentially leaving them socially vulnerable in communication.

A multimodal interface for speech perception: the role of the left superior temporal sulcus in social cognition and autism.

Multimodal integration is crucial for human interaction, in particular for social communication, which relies on integrating information from various sensory modalities. Recently a third visual pathway specialized in social perception was proposed, which includes the right superior temporal sulcus (STS) playing a key role in processing socially relevant cues and high-level social perception. Importantly, it has also recently been proposed that the left STS contributes to audiovisual integration of speech processing. In this article, we propose that brain areas along the right STS that support multimodal integration for social perception and cognition can be considered homologs to those in the left, language-dominant hemisphere, sustaining multimodal integration of speech and semantic concepts fundamental for social communication. Emphasizing the significance of the left STS in multimodal integration and associated processes such as multimodal attention to socially relevant stimuli, we underscore its potential relevance in comprehending neurodevelopmental conditions characterized by challenges in social communication such as autism spectrum disorder (ASD). Further research into this left lateral processing stream holds the promise of enhancing our understanding of social communication in both typical development and ASD, which may lead to more effective interventions that could improve the quality of life for individuals with atypical neurodevelopment.

Neuroanatomy of autism: what is the role of the cerebellum?

Autism (or autism spectrum disorder) was initially defined as a psychiatric disorder, with the likely cause maternal behavior (the very destructive "refrigerator mother" theory). It took several decades for research into brain mechanisms to become established. Both neuropathological and imaging studies found differences in the cerebellum in autism spectrum disorder, the most widely documented being a decreased density of Purkinje cells in the cerebellar cortex. The popular interpretation of these results is that cerebellar neuropathology is a critical cause of autism spectrum disorder. We challenge that view by arguing that if fewer Purkinje cells are critical for autism spectrum disorder, then any condition that causes the loss of Purkinje cells should also cause autism spectrum disorder. We will review data on damage to the cerebellum from cerebellar lesions, tumors, and several syndromes (Joubert syndrome, Fragile X, and tuberous sclerosis). Collectively, these studies raise the question of whether the cerebellum really has a role in autism spectrum disorder. Autism spectrum disorder is now recognized as a genetically caused developmental disorder. A better understanding of the genes that underlie the differences in brain development that result in autism spectrum disorder is likely to show that these genes affect the development of the cerebellum in parallel with the development of the structures that do underlie autism spectrum disorder.

Visual statistical learning in preverbal infants at a higher likelihood of autism and its association with later social communication skills.

Visual statistical Learning (SL) allows infants to extract the statistical relationships embedded in a sequence of elements. SL plays a crucial role in language and communication competencies and has been found to be impacted in Autism Spectrum Disorder (ASD). This study aims to investigate visual SL in infants at higher likelihood of developing ASD (HL-ASD) and its predictive value on autistic-related traits at 24-36 months. At 6 months of age, SL was tested using a visual habituation task in HL-ASD and neurotypical (NT) infants. All infants were habituated to a visual sequence of shapes containing statistically predictable patterns. In the test phase, infants viewed the statistically structured, familiar sequence in alternation with a novel sequence that did not contain any statistical information. HL-ASD infants were then evaluated at 24-36 months to investigate the associations between visual SL and ASD-related traits. Our results showed that NT infants were able to learn the statistical structure embedded in the visual sequences, while HL-ASD infants showed different learning patterns. A regression analysis revealed that SL ability in 6-month-old HL-ASD infants was related to social communication and interaction abilities at 24-36 months of age. These findings indicate that early differences in learning visual statistical patterns might contribute to later social communication skills.

Mapping the differential impact of spontaneous and conversational laughter on brain and mind: an fMRI study in autism.

Spontaneous and conversational laughter are important socio-emotional communicative signals. Neuroimaging findings suggest that non-autistic people engage in mentalizing to understand the meaning behind conversational laughter. Autistic people may thus face specific challenges in processing conversational laughter, due to their mentalizing difficulties. Using fMRI, we explored neural differences during implicit processing of these two types of laughter. Autistic and non-autistic adults passively listened to funny words, followed by spontaneous laughter, conversational laughter, or noise-vocoded vocalizations. Behaviourally, words plus spontaneous laughter were rated as funnier than words plus conversational laughter, and the groups did not differ. However, neuroimaging results showed that non-autistic adults exhibited greater medial prefrontal cortex activation while listening to words plus conversational laughter, than words plus genuine laughter, while autistic adults showed no difference in medial prefrontal cortex activity between these two laughter types. Our findings suggest a crucial role for the medial prefrontal cortex in understanding socio-emotionally ambiguous laughter via mentalizing. Our study also highlights the possibility that autistic people may face challenges in understanding the essence of the laughter we frequently encounter in everyday life, especially in processing conversational laughter that carries complex meaning and social ambiguity, potentially leading to social vulnerability. Therefore, we advocate for clearer communication with autistic people.

Reduced lateralization of multiple functional brain networks in autistic males.

BACKGROUND: Autism spectrum disorder has been linked to a variety of organizational and developmental deviations in the brain. One such organizational difference involves hemispheric lateralization, which may be localized to language-relevant regions of the brain or distributed more broadly. METHODS: In the present study, we estimated brain hemispheric lateralization in autism based on each participant's unique functional neuroanatomy rather than relying on group-averaged data. Additionally, we explored potential relationships between the lateralization of the language network and behavioral phenotypes including verbal ability, language delay, and autism symptom severity. We hypothesized that differences in hemispheric asymmetries in autism would be limited to the language network, with the alternative hypothesis of pervasive differences in lateralization. We tested this and other hypotheses by employing a cross-sectional dataset of 118 individuals (48 autistic, 70 neurotypical). Using resting-state fMRI, we generated individual network parcellations and estimated network asymmetries using a surface area-based approach. A series of multiple regressions were then used to compare network asymmetries for eight significantly lateralized networks between groups. RESULTS: We found significant group differences in lateralization for the left-lateralized Language (d = -0.89), right-lateralized Salience/Ventral Attention-A (d = 0.55), and right-lateralized Control-B (d = 0.51) networks, with the direction of these group differences indicating less asymmetry in autistic males. These differences were robust across different datasets from the same participants. Furthermore, we found that language delay stratified language lateralization, with the greatest group differences in language lateralization occurring between autistic males with language delay and neurotypical individuals. CONCLUSIONS: These findings evidence a complex pattern of functional lateralization differences in autism, extending beyond the Language network to the Salience/Ventral Attention-A and Control-B networks, yet not encompassing all networks, indicating a selective divergence rather than a pervasive one. Moreover, we observed an association between Language network lateralization and language delay in autistic males.

Enhanced neural synchronization during social communications between dyads with high autistic traits.

Autism is characterized by atypical social communication styles. To investigate whether individuals with high autistic traits could still have effective social communication among each other, we compared the behavioral patterns and communication quality within 64 dyads of college students paired with both high, both low, and mixed high-low (HL) autistic traits, with their gender matched. Results revealed that the high-high (HH) autistic dyads exhibited atypical behavioral patterns during conversations, including reduced mutual gaze, communicational turns, and emotional sharing compared with the low-low and/or HL autistic dyads. However, the HH autistic dyads displayed enhanced interpersonal neural synchronization during social communications measured by functional near-infrared spectroscopy, suggesting an effective communication style. Besides, they also provided more positive subjective evaluations of the conversations. These findings highlight the potential for alternative pathways to effectively communicate with the autistic community, contribute to a deeper understanding of how high autistic traits influence social communication dynamics among autistic individuals, and provide important insights for the clinical practices for supporting autistic people.

Noninvasive brain stimulation in autism: review and outlook for personalized interventions in adult patients.

Noninvasive brain stimulation (NIBS) has been increasingly investigated during the last decade as a treatment option for persons with autism spectrum disorder (ASD). Yet, previous studies did not reach a consensus on a superior treatment protocol or stimulation target. Persons with ASD often suffer from social isolation and high rates of unemployment, arising from difficulties in social interaction. ASD involves multiple neural systems involved in perception, language, and cognition, and the underlying brain networks of these functional domains have been well documented. Aiming to provide an overview of NIBS effects when targeting these neural systems in late adolescent and adult ASD, we conducted a systematic search of the literature starting at 631 non-duplicate publications, leading to six studies corresponding with inclusion and exclusion criteria. We discuss these studies regarding their treatment rationale and the accordingly chosen methodological setup. The results of these studies vary, while methodological advances may allow to explain some of the variability. Based on these insights, we discuss strategies for future clinical trials to personalize the selection of brain stimulation targets taking into account intersubject variability of brain anatomy as well as function.

Infants' reorienting efficiency depends on parental autistic traits and predicts future socio-communicative behaviors.

Attentional reorienting is dysfunctional not only in children with autism spectrum disorder (ASD), but also in infants who will develop ASD, thus constituting a potential causal factor of future social interaction and communication abilities. Following the research domain criteria framework, we hypothesized that the presence of subclinical autistic traits in parents should lead to atypical infants' attentional reorienting, which in turn should impact on their future socio-communication behavior in toddlerhood. During an attentional cueing task, we measured the saccadic latencies in a large sample (total enrolled n = 89; final sample n = 71) of 8-month-old infants from the general population as a proxy for their stimulus-driven attention. Infants were grouped in a high parental traits (HPT; n = 23) or in a low parental traits (LPT; n = 48) group, according to the degree of autistic traits self-reported by their parents. Infants (n = 33) were then longitudinally followed to test their socio-communicative behaviors at 21 months. Results show a sluggish reorienting system, which was a longitudinal predictor of future socio-communicative skills at 21 months. Our combined transgenerational and longitudinal findings suggest that the early functionality of the stimulus-driven attentional network-redirecting attention from one event to another-could be directly connected to future social and communication development.

Atypical functional connectivity between the amygdala and visual, salience regions in infants with genetic liability for autism.

The amygdala undergoes a period of overgrowth in the first year of life, resulting in enlarged volume by 12 months in infants later diagnosed with ASD. The overgrowth of the amygdala may have functional consequences during infancy. We investigated whether amygdala connectivity differs in 12-month-olds at high likelihood (HL) for ASD (defined by having an older sibling with autism), compared to those at low likelihood (LL). We examined seed-based connectivity of left and right amygdalae, hypothesizing that the HL and LL groups would differ in amygdala connectivity, especially with the visual cortex, based on our prior reports demonstrating that components of visual circuitry develop atypically and are linked to genetic liability for autism. We found that HL infants exhibited weaker connectivity between the right amygdala and the left visual cortex, as well as between the left amygdala and the right anterior cingulate, with evidence that these patterns occur in distinct subgroups of the HL sample. Amygdala connectivity strength with the visual cortex was related to motor and communication abilities among HL infants. Findings indicate that aberrant functional connectivity between the amygdala and visual regions is apparent in infants with genetic liability for ASD and may have implications for early differences in adaptive behaviors.

A hybrid CNN-SVM model for enhanced autism diagnosis.

Autism is a representative disorder of pervasive developmental disorder. It exerts influence upon an individual's behavior and performance, potentially co-occurring with other mental illnesses. Consequently, an effective diagnostic approach proves to be invaluable in both therapeutic interventions and the timely provision of medical support. Currently, most scholars' research primarily relies on neuroimaging techniques for auxiliary diagnosis and does not take into account the distinctive features of autism's social impediments. In order to address this deficiency, this paper introduces a novel convolutional neural network-support vector machine model that integrates resting state functional magnetic resonance imaging data with the social responsiveness scale metrics for the diagnostic assessment of autism. We selected 821 subjects containing the social responsiveness scale measure from the publicly available Autism Brain Imaging Data Exchange dataset, including 379 subjects with autism spectrum disorder and 442 typical controls. After preprocessing of fMRI data, we compute the static and dynamic functional connectivity for each subject. Subsequently, convolutional neural networks and attention mechanisms are utilized to extracts their respective features. The extracted features, combined with the social responsiveness scale features, are then employed as novel inputs for the support vector machine to categorize autistic patients and typical controls. The proposed model identifies salient features within the static and dynamic functional connectivity, offering a possible biological foundation for clinical diagnosis. By incorporating the behavioral assessments, the model achieves a remarkable classification accuracy of 94.30%, providing a more reliable support for auxiliary diagnosis.

Differential neural correlates underlying visuospatial versus semantic reasoning in autistic children.

While fronto-posterior underconnectivity has often been reported in autism, it was shown that different contexts may modulate between-group differences in functional connectivity. Here, we assessed how different task paradigms modulate functional connectivity differences in a young autistic sample relative to typically developing children. Twenty-three autistic and 23 typically developing children aged 6 to 15 years underwent functional magnetic resonance imaging (fMRI) scanning while completing a reasoning task with visuospatial versus semantic content. We observed distinct connectivity patterns in autistic versus typical children as a function of task type (visuospatial vs. semantic) and problem complexity (visual matching vs. reasoning), despite similar performance. For semantic reasoning problems, there was no significant between-group differences in connectivity. However, during visuospatial reasoning problems, we observed occipital-occipital, occipital-temporal, and occipital-frontal over-connectivity in autistic children relative to typical children. Also, increasing the complexity of visuospatial problems resulted in increased functional connectivity between occipital, posterior (temporal), and anterior (frontal) brain regions in autistic participants, more so than in typical children. Our results add to several studies now demonstrating that the connectivity alterations in autistic relative to neurotypical individuals are much more complex than previously thought and depend on both task type and task complexity and their respective underlying cognitive processes.

Differences in audiovisual temporal processing in autistic adults are specific to simultaneity judgments.

Research has shown that children on the autism spectrum and adults with high levels of autistic traits are less sensitive to audiovisual asynchrony compared to their neurotypical peers. However, this evidence has been limited to simultaneity judgments (SJ) which require participants to consider the timing of two cues together. Given evidence of partly divergent perceptual and neural mechanisms involved in making temporal order judgments (TOJ) and SJ, and given that SJ require a more global type of processing which may be impaired in autistic individuals, here we ask whether the observed differences in audiovisual temporal processing are task and stimulus specific. We examined the ability to detect audiovisual asynchrony in a group of 26 autistic adult males and a group of age and IQ-matched neurotypical males. Participants were presented with beep-flash, point-light drumming, and face-voice displays with varying degrees of asynchrony and asked to make SJ and TOJ. The results indicated that autistic participants were less able to detect audiovisual asynchrony compared to the control group, but this effect was specific to SJ and more complex social stimuli (e.g., face-voice) with stronger semantic correspondence between the cues, requiring a more global type of processing. This indicates that audiovisual temporal processing is not generally different in autistic individuals and that a similar level of performance could be achieved by using a more local type of processing, thus informing multisensory integration theory as well as multisensory training aimed to aid perceptual abilities in this population.

Enhancing early autism diagnosis through machine learning: Exploring raw motion data for classification.

In recent years, research has been demonstrating that movement analysis, utilizing machine learning methods, can be a promising aid for clinicians in supporting autism diagnostic process. Within this field of research, we aim to explore new models and delve into the detailed observation of certain features that previous literature has identified as prominent in the classification process. Our study employs a game-based tablet application to collect motor data. We use artificial neural networks to analyze raw trajectories in a "drag and drop" task. We compare a two-features model (utilizing only raw coordinates) with a four-features model (including velocities and accelerations). The aim is to assess the effectiveness of raw data analysis and determine the impact of acceleration on autism classification. Our results revealed that both models demonstrate promising accuracy in classifying motor trajectories. The four-features model consistently outperforms the two-features model, as evidenced by accuracy values (0.90 vs. 0.76). However, our findings support the potential of raw data analysis in objectively assessing motor behaviors related to autism. While the four-features model excels, the two-features model still achieves reasonable accuracy. Addressing limitations related to sample size and noise is essential for future research. Our study emphasizes the importance of integrating intelligent solutions to enhance and assist autism traditional diagnostic process and intervention, paving the way for more effective tools in assessing motor skills.

Female-specific dysfunction of sensory neocortical circuits in a mouse model of autism mediated by mGluR5 and estrogen receptor α.

Little is known of the brain mechanisms that mediate sex-specific autism symptoms. Here, we demonstrate that deletion of the autism spectrum disorder (ASD)-risk gene, Pten, in neocortical pyramidal neurons (NSEPten knockout [KO]) results in robust cortical circuit hyperexcitability selectively in female mice observed as prolonged spontaneous persistent activity states. Circuit hyperexcitability in females is mediated by metabotropic glutamate receptor 5 (mGluR5) and estrogen receptor α (ERα) signaling to mitogen-activated protein kinases (Erk1/2) and de novo protein synthesis. Pten KO layer 5 neurons have a female-specific increase in mGluR5 and mGluR5-dependent protein synthesis. Furthermore, mGluR5-ERα complexes are generally elevated in female cortices, and genetic reduction of ERα rescues enhanced circuit excitability, protein synthesis, and neuron size selectively in NSEPten KO females. Female NSEPten KO mice display deficits in sensory processing and social behaviors as well as mGluR5-dependent seizures. These results reveal mechanisms by which sex and a high-confidence ASD-risk gene interact to affect brain function and behavior.

Disrupted cognitive and affective empathy network interactions in autistic children viewing social animation.

Empathy can be divided into two core components, cognitive empathy (CE) and affective empathy (AE), mediated by distinct neural networks. Deficient empathy is a central feature of autism spectrum conditions (ASCs), but it is unclear if this deficit results from disruption solely within empathy networks or from disrupted functional integration between CE and AE networks. To address this issue, we measured functional connectivity (FC) patterns both within and between empathy networks in autistic children (4-8 years, n = 31) and matched typically developing (TD) children (n = 26) using near-infrared spectroscopy during the presentation of an animated story evoking CE and AE. Empathy and social communication ability were also assessed using the Empathy Quotient/Systemizing Quotient (EQ/SQ) and Social Responsiveness Scale, respectively. The results showed that the FC in the AE network of autistic children did not differ from the TD group across conditions; however, the ASC group showed weaker FC in the CE network under the CE condition and weaker FC between networks when processing AE information, the latter of which was negatively correlated with EQ scores in ASC. The empathy defect in ASC may involve abnormal integration of CE and AE network activities under AE conditions.

GABA and Glx predict EEG responses of visual sensitivity in autism.

The mechanisms underlying atypical sensory processing in autism remain to be elucidated, but research points toward a role of the glutamatergic/GABAergic balance. To investigate the potential relationships between visual sensitivity and its molecular correlates in autism, we combined data from electroencephalography (EEG) and magnetic resonance spectroscopy (MRS) studies. Twenty autistic adults and sixteen neurotypical adults (NT) participated in both an EEG study assessing visual sensitivity (Sapey-Triomphe et al., Autism Research, 2023) and in an MRS study measuring Glx and GABA+ concentrations in the occipital cortex (Sapey-Triomphe et al., Molecular Autism, 2021). These studies revealed no group differences in neural detection thresholds or in Glx/GABA levels in the occipital cortex. Neural detection thresholds for contrast and spatial frequency (SF) were determined using fast periodic visual stimulations and neural frequency tagging. In the present study, Glx/GABA+ concentrations in the occipital cortex and neural detection thresholds did not differ between groups. Interestingly, lower Glx/GABA+ ratios were associated with lower contrast detection thresholds and higher SF detection thresholds. These correlations were also significant within the neurotypical and autistic groups. This report suggests that the Glx/GABA balance regulates visual detection thresholds across individuals. In both autistic and NTs, lower Glx/GABA ratios in the occipital cortex allow for better detection of visual inputs at the neural level. This study sheds light on the neurochemical underpinnings of visual sensitivity in autism and warrants further investigation.

Autistic and nonautistic adolescents do not differ in adaptation to gaze direction.

Predictive processing accounts of autism posit that autistic individuals' perception is less biased by expectations than nonautistic individuals', perhaps through stronger precision-weighting of prediction errors. Since precision-weighting is fundamental to all information processing, under this theory, the differences between autistic and nonautistic individuals should be domain-general and observable in both behavior and brain responses. This study used EEG, behavioral responses, and eye-tracking co-registration during gaze-direction adaptation, to investigate whether increased precision-weighting of prediction errors is evident through smaller adaptation after-effects in autistic adolescents compared with nonautistic peers. Multilevel modeling showed that autistic and nonautistic adolescents' responses were consistent with behavioral adaptation, with Bayesian statistics providing extremely strong evidence for the absence of a group difference. Cluster-based permutation testing of ERP responses did not show the expected adaptation after-effect but did show habituation to repeated stimulus presentation, and no group difference was detected, a result not consistent with the theoretical account. Combined with the few other available studies, the current findings raise challenges for the theory, suggesting no fundamental difference in precision-weighting of prediction errors in autism.

Processing of visual social-communication cues during a social-perception of action task in autistic and non-autistic observers.

Social perception and communication differ between those with and without autism, even when verbal fluency and intellectual ability are equated. Previous work found that observers responded more quickly to an actor's points if the actor had chosen by themselves where to point instead of being directed where to point. Notably, this 'choice-advantage' effect decreased across non-autistic participants as the number of autistic-like traits and tendencies increased (Pesquita et al., 2016). Here, we build on that work using the same task to study individuals over a broader range of the spectrum, from autistic to non-autistic, measuring both response initiation and mouse movement times, and considering the response to each actor separately. Autistic and non-autistic observers viewed videos of three different actors pointing to one of two locations, without knowing that the actors were sometimes freely choosing to point to one target and other times being directed where to point. All observers exhibited a choice-advantage overall, meaning they responded more rapidly when actors were freely choosing versus when they were directed, indicating a sensitivity to the actors' postural cues and movements. Our fine-grained analyses found a more robust choice-advantage to some actors than others, with autistic observers showing a choice-advantage only in response to one of the actors, suggesting that both actor and observer characteristics influence the overall effect. We briefly explore existing actor characteristics that may have contributed to this effect, finding that both duration of exposure to pre-movement cues and kinematic cues of the actors likely influence the choice advantage to different degrees across the groups. Altogether, the evidence suggested that both autistic and non-autistic individuals could detect the choice-advantage signal, but that for autistic observers the choice-advantage was actor specific. Notably, we found that the influence of the signal, when present, was detected early for all actors by the non-autistic observers, but detected later and only for one actor by the autistic observers. Altogether, we have more accurately characterized the ability of social-perception in autistic individuals as intact, but highlighted that detection of signal is likely delayed/distributed compared to non-autistic observers and that it is important to investigate actor characteristics that may influence detection and use of their social-perception signals.