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Sladky, R.

Publications and source records attributed to Sladky, R..

15 recordsLinked to original sources

Alterations in amygdala function explain how aging and loneliness impair trust learning

Functional relationships are essential for healthy aging and they rely on social cognition skills such as establishing and monitoring whom to trust. However, aging and loneliness can negatively affect social brain function, potentially leading to a vicious cycle. Using functional MRI and computational modeling we investigated trust learning in a sample of neurotypical older (64-84 years, n=29f/23m) compared to younger adults (20-33 years, n=31f/31m). Older participants displayed lower initial trust and less trust learning when repeatedly interacting with a trustworthy and an untrustworthy trustee. Their basolateral and central amygdala activation was lower during trust decisions, and this was associated with less optimal trust behavior. Computational modeling also revealed that a crucial learning parameter, trust prediction error precision, was decoupled from basolateral amygdala activation, and this effect was pronounced in lonely older adults. These findings indicate that differences in amygdala function and reward signaling at older age and higher loneliness could drive detrimental effects on trust learning, leading to poorer social cognition and putting individuals sociality and well-being at risk.

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Good dog, bad wolf: Debunking evolutionary preparedness to fear wolves

The return of wolves to historical ranges often causes strong opposition, contrasting with widespread affection for domestic dogs. Evolutionary accounts suggest this discrepancy stems from deeply ingrained affective responses that predispose humans to fear wolves while fostering positive attachment to dogs. Using neuroimaging and self-report data from 42 participants, we investigated how defensive neural circuits linked to implicit threat detection are related to explicit threat evaluations of the two species. During functional MRI, participants viewed images of wolves, dogs, and snakes - the latter chosen for their strong engagement of predisposed threat-related responses - displaying either aggressive or non-aggressive behaviours. As predicted, aggressive displays of all species elicited stronger neural responses in threat-related brain areas. Snakes elicited stronger subcortical threat responses than wolves or dogs, while neural responses to wolves and dogs were largely indistinguishable when comparing aggressive displays. However, explicit threat evaluations strongly differed: wolves were perceived and rated as significantly more threatening than dogs, especially when the species exhibited aggressive displays. Together, these findings challenge accounts that humans are predisposed for negative responses to wolves, suggesting instead that our attitudes towards the species are shaped primarily by deliberate-evaluative processes rather than by implicit-automatic threat responses. This underscores the role of experience, knowledge, stereotypes, and socio-cultural mechanisms in shaping public perceptions of human-wildlife conflicts and conservation efforts. These results provide new insights into the cognitive and affective foundations of human-animal relationships, informing efforts to improve human-wildlife coexistence. Significance statementWhy are wolves feared while dogs are loved? One common explanation is that humans are evolutionarily predisposed to fear wolves as dangerous predators, while dogs, due to domestication, occupy a special niche in human lives. By comparing neural and behavioural responses to wolves, dogs and snakes, we show that wolves do not evoke stronger threat-related brain responses than dogs, despite being judged as the greater threat. However, wolves and dogs alike engage cortical systems associated with perception and evaluation, suggesting that cultural narratives and explicit reasoning, rather than hardwired automatic fear, underlie wolf aversion. These findings challenge evolutionary accounts of fear preparedness and suggest that negative attitudes towards wolves can be addressed through education, communication, and public engagement.

neuroscience↗

SpiDa-MRI, behavioral and (f)MRI data of adults with fear of spiders

Neuroimaging has greatly improved our understanding of phobic mechanisms. To expand on these advancements, we present data on the heterogeneity of neural patterns in spider phobia combined with various psychological dimensions of spider phobia, using spider-relevant stimuli of various intensities. Specifically, we have created a database in which 49 spider-fearful individuals viewed 225 spider-relevant images in the fMRI scanner and performed behavioral avoidance tasks before and after the fMRI scan. For each participant, the database consists of the neuroimaging part, which includes an anatomical scan, 5 passive-viewing and 2 resting-state functional runs in both raw and pre-processed form along with associated quality control reports. Additionally, a behavioral section includes self-report questionnaires and avoidance tasks collected in pre- and post-sessions. The dataset is well suited for investigating neural mechanisms of phobias, brain-behavior correlations, and also contributes to the existing phobic neuroimaging datasets with spider-fearful samples. O_TBL View this table: org.highwire.dtl.DTLVardef@f76a39org.highwire.dtl.DTLVardef@15eeaa2org.highwire.dtl.DTLVardef@7e4f1borg.highwire.dtl.DTLVardef@7b78f1org.highwire.dtl.DTLVardef@413e78_HPS_FORMAT_FIGEXP M_TBL C_TBL

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Amygdala habituation during exposure is associated with failure to reduce phobic symptoms

Exposure therapy is an established treatment for anxiety disorders but the mechanisms underpinning its effectiveness remain unclear. Two theories offer contrasting perspectives: the traditional habituation model posits that a form of stimulus desensitization is required during exposure, while the inhibitory learning model emphasizes the formation of new non-fearful associations. Crucially, while the former may manifest as amygdala habituation, the latter may not. To distinguish between the two models, this study uses functional magnetic resonance imaging to examine the amygdala responses of spider-fearful participants during fear exposure. We hypothesized that intervention success might align with stable or even increased amygdala activation - an indicator of active engagement and re-learning as proposed by the inhibitory learning model. Conversely, decreasing amygdala activity might not be a sign of reduced fear memory as proposed by the habituation model, but could signal mental detachment, leading to suboptimal treatment outcomes. Our results corroborated our hypotheses: individuals with escalating amygdala responses during exposure exhibited better clinical progress, while those showing amygdala habituation benefited less. Our results strengthen the case for the inhibitory learning model and highlight that therapy may not aim to diminish fear per se but rather to engage patients in active processing and association formation.

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Functional mapping of the somatosensory cortex using noninvasive fMRI and touch in awake dogs

Dogs are increasingly used as a model for neuroscience due to their ability to undergo functional MRI fully awake and unrestrained, after extensive behavioral training. Still, we know rather little about dogs basic functional neuroanatomy, including how basic perceptual and motor functions are localized in their brains. This is a major shortcoming in interpreting activations obtained in dog fMRI. The aim of this preregistered study was to localize areas associated with somatosensory processing. To this end, we touched N = 22 dogs undergoing fMRI scanning on their left and right flanks using a wooden rod. We identified activation in anatomically defined primary and secondary somatosensory areas (SI and SII), lateralized to the contralateral hemisphere depending on the side of touch, as well as activations, beyond an anatomical mask of SI and SII, in the cingulate cortex, right cerebellum and vermis, and the Sylvian gyri. These activations may partly relate to motor control (cerebellum, cingulate), but also potentially to higher-order cognitive processing of somatosensory stimuli (rostral Sylvian gyri), and the affective aspects of the stimulation (cingulate). We also found evidence for individual side biases in a vast majority of dogs in our sample, pointing at functional lateralization of somatosensory processing. These findings not only provide further evidence that fMRI is suited to localize neuro-cognitive processing in dogs in vivo, but also expand our understanding of touch processing in mammals, beyond classically defined primary and secondary somatosensory cortices. Significance StatementTo understand brain function and evolution, it is necessary to look beyond the human lineage. This study provides insights into the engagement of brain areas related to somatosensation using whole-brain non-invasive neuroimaging of trained, non-sedated, and unrestrained pet dogs. It showcases again the usefulness of non-invasive methods, in particular fMRI, for investigating brain function and advances the mapping of brain functions in dogs; using this non-invasive approach without sedation, we are able to identify previously unknown potential higher-order processing areas and offer a quantification of touch processing lateralization.

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Pre- and post-task resting-state differs in clinical populations

Resting-state functional connectivity has generated great hopes as a potential brain biomarker for improving prevention, diagnosis, and treatment in psychiatry. This neuroimaging protocol can routinely be performed by patients and does not depend on the specificities of a task. Thus, it seems ideal for big data approaches that require aggregating data across multiple studies and sites. However, technical variability, diverging data analysis approaches, and differences in data acquisition protocols might introduce heterogeneity to the aggregated data. Besides these technical aspects, the psychological state of participants might also contribute to heterogeneity. In healthy participants, studies have shown that behavioral tasks can influence resting-state measures, but such effects have not yet been reported in clinical populations. Here, we fill this knowledge gap by comparing resting-state functional connectivity before and after clinically relevant tasks in two clinical conditions, namely substance use disorders and phobias. The tasks consisted of viewing craving-inducing and spider anxiety provoking pictures that are frequently used in cue-reactivity studies and exposure therapy. We found distinct pre- vs. post-task resting-state connectivity differences in each group, as well as decreased thalamo-cortical and increased intra-thalamic connectivity which might be associated with decreased vigilance in both groups. Notably, the pre- vs. post-task thalamus-amygdala connectivity change within a patient cohort seems more pronounced than the difference of that connection between the smoker vs. phobia clinical trait. Our results confirm that resting-state measures can be strongly influenced by changes in psychological states that need to be taken into account when pooling resting-state scans for clinical biomarker detection. This demands that resting-state datasets should include a complete description of the experimental design, especially when a task preceded data collection.

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Validation of a new coil array tailored for dog functional magnetic resonance imaging (fMRI) studies

Comparative neuroimaging allows for the identification of similarities and differences between species. It provides an important and promising avenue, to answer questions about the evolutionary origins of the brains organization, in terms of both structure and function. Dog fMRI has recently become one particularly promising and increasingly used approach to study brain function and coevolution. In dog neuroimaging, image acquisition has so far been mostly performed with coils originally developed for use in human MRI. Since such coils have been tailored to human anatomy, their sensitivity and data quality is likely not optimal for dog MRI. Therefore, we developed a multi-channel receive coil (K9 coil) tailored for high-resolution functional imaging in canines, optimized for dog cranial anatomy. In this paper we report structural (n = 9) as well as functional imaging data (resting-state, n = 6; simple visual paradigm, n = 9) collected with the K9 coil in comparison to reference data collected with a human knee coil. Our results show that the K9 coil significantly outperforms the human knee coil, improving the signal-to-noise ratio across the imaging modalities. We noted increases of roughly 45% signal-to-noise in the structural and functional domain. In terms of translation to functional fMRI data collected in a visual flickering checkerboard paradigm, group-level analyses show that the K9 coil performs better than the knee coil as well. These findings demonstrate how hardware improvements may be instrumental in driving data quality, and thus, quality of imaging results, for dog-human comparative neuroimaging. Significance StatementComparative neuroimaging is a powerful avenue to discover evolutionary mechanisms at the brain level. However, data quality is a major constraint in non-human functional magnetic resonance imaging. We describe a novel canine head coil for magnetic resonance imaging, designed specifically for dog cranial anatomy. Data quality performance and improvements over previously used human knee coils are described quantitatively. In brief, the canine coil improved signal quality substantially across both structural and functional imaging domains, with strongest improvements noted on the cortical surface.

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Effective connectivity reveals distinctive patterns in response to others' genuine affective experience of disgust as compared to pain

Empathy is significantly influenced by the identification of others emotions. In a recent study, we have found increased activation in the anterior insular cortex (aIns) that could be attributed to affect sharing rather than perceptual saliency, when seeing another person genuinely experiencing pain as opposed to merely acting to be in pain. In that prior study, effective connectivity between aIns and the right supramarginal gyrus (rSMG) was revealed to track what another person really feels. In the present study, we used a similar paradigm to investigate the corresponding neural signatures in the domain of empathy for disgust - with participants seeing others genuinely sniffing unpleasant odors as compared to pretending to smell something disgusting. Consistent with the previous findings on pain, we found stronger activations in aIns associated with affect sharing for genuine disgust compared with pretended disgust. However, instead of rSMG we found engagement of the olfactory cortex. Using dynamic causal modeling (DCM), we estimated the neural dynamics of aIns and the olfactory cortex between the genuine and pretended conditions. This revealed an increased excitatory modulatory effect for genuine disgust compared to pretended disgust. For genuine disgust only, brain-to-behavior regression analyses highlighted a link between the observed modulatory effect and the perspective-taking empathic trait. Altogether, the current findings complement and expand our previous work, by showing that perceptual saliency alone does not explain responses in the insular cortex. Moreover, it reveals that different brain networks are implicated in a modality-specific way when sharing the affective experiences associated with pain vs. disgust.

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In amygdala we trust: different contributions of the basolateral and central amygdala in learning whom to trust

Human societies are built on cooperation and mutual trust, but not everybody is trustworthy. Research on rodents suggests an essential role of the basolateral amygdala (BLA) in learning from social experiences (Hernandez-Lallement J et al., 2016), which was also confirmed in human subjects with selective bilateral BLA damage as they failed to adapt their trust behavior towards trustworthy vs. untrustworthy interaction partners (Rosenberger LA et al., 2019). However, neuroimaging in neurotypical populations did not consistently report involvement of the amygdala in trust behavior. This might be explained by the difficulty of differentiating between amygdalas structurally and functionally different subnuclei, i.e., the BLA and central amygdala (CeA), which have even antagonistic features particularly in trust behavior (van Honk J et al., 2013). Here, we used fMRI of the amygdala subnuclei of neurotypical adults (n=31f/31m) engaging in the repeated trust game. Our data show that both the BLA and the CeA play a role and indeed differentially: While the BLA was most active when obtaining feedback on whether invested trust had been reciprocated or not, the CeA was most active when subjects were preparing their next trust decision. In the latter phase, improved learning was associated with higher activation differences in response to untrustworthy vs. trustworthy trustees, in both BLA and CeA. Our data not only translate to rodent models and support our earlier findings in BLA-damaged subjects, but also show the specific contributions of other brain structures in the amygdala-centered network in learning whom to trust, and better not to trust. SIGNIFICANCE STATEMENTIn this fMRI study, the central amygdala was found active during trust behavior planning, while the basolateral amygdala was active during outcome evaluation. When planning trust behavior, central and basolateral amygdala activation differences between the players was related to whether participants learned to differentiate the players trustworthiness. Nucleus accumbens tracked whether trust was reciprocated but was not related to learning. This suggests learning whom to trust is not related to reward processing in the nucleus accumbens but rather to engagement of the basolateral amygdala. This study overcomes major empirical gaps between animal models and human neuroimaging and shows how different amygdala subnuclei and connected areas orchestrate learning to form different subjective trustworthiness beliefs about others and guide trust choice behavior.

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Neural dynamics between anterior insular cortex and right supramarginal gyrus dissociate genuine affect sharing from automatic responses to pretended pain

Empathy for pain engages both shared affective responses and self-other distinction. In this study, we addressed the highly debated question of whether neural responses previously linked to affect sharing could result from the perception of salient affective displays. Moreover, we investigated how affect sharing and self-other distinction interact to determine our response to a pain that is either perceived as genuine or pretended (while in fact both were acted for reasons of experimental control). We found stronger activations in regions associated with affect sharing (anterior insula, aIns, and anterior mid-cingulate cortex, aMCC) as well as with affective self-other distinction (right supramarginal gyrus, rSMG), in participants watching video clips of genuine vs. pretended facial expressions of pain. Using dynamic causal modeling (DCM), we then assessed the neural dynamics between the right aIns and rSMG in these two conditions. This revealed a reduced inhibitory effect on the aIns to rSMG connection for genuine compared to pretended pain. For genuine pain only, brain-to-behavior regression analyses highlighted a linkage between this inhibitory effect on the one hand, and pain ratings as well as empathic traits on the other. These findings imply that if the pain of others is genuine and thus calls for an appropriate empathic response, neural responses in the aIns indeed seem related to affect sharing and self-other distinction is engaged to avoid empathic over-arousal. In contrast, if others merely pretend to be in pain, the perceptual salience of their painful expression results in neural responses that are down-regulated to avoid inappropriate affect sharing and social support.

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Determinants of Real-Time fMRI Neurofeedback Performance and Improvement: a Machine Learning Mega-Analysis

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments. With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in Open Science and data sharing.

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Tailored haemodynamic response function increases detection power of fMRI in awake dogs (Canis familiaris)

Functional magnetic resonance imaging (fMRI) of awake and unrestrained dogs (Canis familiaris) has been established as a novel opportunity for comparative neuroimaging, promising important insights into the evolutionary roots of human brain function and cognition. However, data processing and analysis pipelines are often derivatives of methodological standards developed for human neuroimaging, which may be problematic due to profound neurophysiological and anatomical differences between humans and dogs. Here, we explore whether dog fMRI studies would benefit from a tailored dog haemodynamic response function (HRF). In two independent experiments, dogs were presented with different visual stimuli. BOLD signal changes in the visual cortex during these experiments were used for (a) the identification and estimation of a tailored dog HRF, and (b) the independent validation of the resulting dog HRF estimate. Time course analyses revealed that the BOLD signal in the primary visual cortex peaks significantly earlier in dogs compared to humans, while being comparable in shape. Deriving a tailored dog HRF significantly improved the model fit in both experiments, compared to the canonical HRF used in human fMRI. Using the dog HRF yielded significantly increased activation during visual stimulation, extending from the occipital lobe, to the caudal parietal cortex, the bilateral temporal cortex, and into bilateral hippocampal and thalamic regions. In sum, our findings provide robust evidence for an earlier onset of the dog HRF in a visual stimulation paradigm, and suggest that using such an HRF will be important to increase fMRI detection power in canine neuroimaging. By providing the parameters of the tailored dog HRF and related code, we encourage and enable other researchers to validate whether our findings generalize to other sensory modalities and experimental paradigms. HighlightsO_LIDog fMRI typically uses human HRF, but underlying neurophysiology might differ C_LIO_LIV1 BOLD signal peaked earlier in dogs than predicted by the human HRF C_LIO_LITailored dog HRF improved model fit when tested with independent data C_LIO_LIWhole-brain comparisons confirmed increased detection power for tailored dog HRF C_LIO_LIDog fMRI will benefit from increased detection power of tailored HRF C_LI

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Can we predict real-time fMRI neurofeedback learning success from pre-training brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large interindividual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pre-training functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pre-training activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.

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Individual differences in the mechanistic control of the dopaminergic midbrain

The dopaminergic midbrain is associated with brain functions, such as reinforcement learning, motivation and decision-making that are often disturbed in neuropsychiatric disease. Previous research has shown that activity in the dopaminergic midbrain can be endogenously modulated via neurofeedback, suggesting potential for non-pharmacological interventions. However, the robustness of endogenous modulation, a requirement for clinical translation, is unclear. Here, we examined how self-modulation capability relates to regulation transfer. Moreover, to elucidate potential mechanisms underlying successful self-regulation, we studied individual prediction error coding, and, during an independent monetary incentive delay (MID) task, individual reward sensitivity. Fifty-nine participants underwent neurofeedback training either in a veridical or inverted feedback group. Successful self-regulation was associated with post-training activity within the cognitive control network and accompanied by decreasing prefrontal prediction error signals and increased prefrontal reward sensitivity in the MID task. The correlative link of dopaminergic self-regulation with individual differences in prefrontal prediction error and reward sensitivity suggests that reinforcement learning contributes to successful self-regulation. Our findings therefore provide new insights in the control of dopaminergic midbrain activity and pave the way to improve neurofeedback training in neuropsychiatric patients.

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Self-regulation of the Dopaminergic Reward Circuit in Cocaine Users with Mental Imagery and Neurofeedback

Background: Enhanced drug-related reward sensitivity accompanied by impaired sensitivity to non-drug related rewards in the mesolimbic dopamine system are thought to underlie the broad motivational deficits and dysfunctional decision-making frequently observed in cocaine use disorder (CUD). Effective approaches to modify this imbalance and reinstate non-drug reward responsiveness are urgently needed. Here we examine whether cocaine users (CU) can use mental imagery of non-drug rewards to self-regulate the ventral tegmental area and substantia nigra (VTA/SN). We expected that compulsive and obsessive thoughts about cocaine consumption would hamper the ability to self-regulate the VTA/SN. Finally, we tested if self-regulation of the VTA/SN can be improved with real-time fMRI (rtfMRI) neurofeedback (NFB).\n\nMethods: Twenty-two CU and 28 healthy controls (HC) were asked to voluntarily up-regulate VTA/SN activity with rewarding non-drug imagery alone, or combined with rtfMRI NFB of VTA/SN activity. Obsessive-compulsive drug use was measured with the Obsessive Compulsive Cocaine Use Scale (OCCUS).\n\nResults: CU were able to induce activity in the dopaminergic midbrain and other reward regions with reward imagery. The ability to self-regulate the VTA/SN was reduced in those with more severe obsessive-compulsive drug use. NFB enhanced the effect of non-drug imagery.\n\nConclusion: CU can voluntary activate their reward system through non-drug related imagery and improve this ability with rtfMRI NFB. Combining reward imagery and rtFMRI NFB has great potential for modifying the maladapted reward sensitivity and reinstating non-drug reward responsiveness. This motivates further work to examine the therapeutic potential of cognitive neurostimulation in CUD.

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