ABSTRACT
Pain is an immense clinical and societal challenge, and the key to understanding and treating it is variability. Robust interindividual differences are consistently observed in pain sensitivity, susceptibility to developing painful disorders, and response to analgesic manipulations. This review examines the causes of this variability, including both organismic and environmental sources. Chronic pain development is a textbook example of a gene-environment interaction, requiring both chance initiating events (e.g., trauma, infection) and more immutable risk factors. The focus is on genetic factors, since twin studies have determined that a plurality of the variance likely derives from inherited genetic variants, but sex, age, ethnicity, personality variables, and environmental factors are also considered.
Subject(s)
Individuality , Pain , Humans , Pain/geneticsABSTRACT
Complex visual stimuli evoke diverse patterns of gaze, but previous research suggests that their neural representations are shared across brains. Here, we used hyperalignment to compare visual responses between observers viewing identical stimuli. We find that individual eye movements enhance cortical visual responses but also lead to representational divergence. Pairwise differences in the spatial distribution of gaze and in semantic salience predict pairwise representational divergence in V1 and inferior temporal cortex, respectively. This suggests that individual gaze sculpts individual visual worlds.
Subject(s)
Eye Movements , Humans , Male , Female , Adult , Eye Movements/physiology , Photic Stimulation , Fixation, Ocular/physiology , Visual Perception/physiology , Temporal Lobe/physiology , Visual Cortex/physiology , Young AdultABSTRACT
The primary visual cortex (V1) in blindness is engaged in a wide spectrum of tasks and sensory modalities, including audition, touch, language, and memory. This widespread involvement raises questions regarding the constancy of its role and whether it might exhibit flexibility in its function over time, connecting to diverse network functions specific to task demands. This would suggest that reorganized V1 assumes a role like multiple-demand system regions. Alternatively, varying patterns of plasticity in blind V1 may be attributed to individual factors, with different blind individuals recruiting V1 preferentially for different functions. In support of this, we recently showed that V1 functional connectivity (FC) varies greatly across blind individuals. But do these represent stable individual patterns of plasticity, or are they driven more by instantaneous changes, like a multiple-demand system now inhabiting V1? Here, we tested whether individual FC patterns from the V1 of blind individuals are stable over time. We show that over two years, FC from the V1 is unique and highly stable in a small sample of repeatedly sampled congenitally blind individuals. Further, using multivoxel pattern analysis, we demonstrate that the unique reorganization patterns of these individuals allow decoding of participant identity. Together with recent evidence for substantial individual differences in V1 connectivity, this indicates that there may be a consistent role for V1 in blindness, which may differ for each individual. Further, it suggests that the variability in visual reorganization in blindness across individuals could be used to seek stable neuromarkers for sight rehabilitation and assistive approaches.
Subject(s)
Blindness , Neuronal Plasticity , Humans , Blindness/physiopathology , Neuronal Plasticity/physiology , Male , Female , Adult , Middle Aged , Magnetic Resonance Imaging , Primary Visual Cortex/physiology , Longitudinal Studies , Visual Cortex/physiopathology , Visual Cortex/physiology , Visual Cortex/diagnostic imaging , Brain Mapping/methodsABSTRACT
Human cognitive capacities that enable flexible cooperation may have evolved in parallel with the expansion of frontoparietal cortical networks, particularly the default network. Conversely, human antisocial behavior and trait antagonism are broadly associated with reduced activity, impaired connectivity, and altered structure of the default network. Yet, behaviors like interpersonal manipulation and exploitation may require intact or even superior social cognition. Using a reinforcement learning model of decision-making on a modified trust game, we examined how individuals adjusted their cooperation rate based on a counterpart's cooperation and social reputation. We observed that learning signals in the default network updated the predicted utility of cooperation or defection and scaled with reciprocal cooperation. These signals were weaker in callous (vs. compassionate) individuals but stronger in those who were more exploitative (vs. honest and humble). Further, they accounted for associations between exploitativeness, callousness, and reciprocal cooperation. Separately, behavioral sensitivity to prior reputation was reduced in callous but not exploitative individuals and selectively scaled with responses of the medial temporal subsystem of the default network. Overall, callousness was characterized by blunted behavioral and default network sensitivity to cooperation incentives. Exploitativeness predicted heightened sensitivity to others' cooperation but not social reputation. We speculate that both compassion and exploitativeness may reflect cognitive adaptations to social living, enabled by expansion of the default network in anthropogenesis.
Subject(s)
Cooperative Behavior , Humans , Male , Female , Adult , Motivation/physiology , Decision Making/physiology , Trust/psychology , Young Adult , Nerve Net/physiology , Empathy/physiology , Brain/physiology , Brain/diagnostic imagingABSTRACT
Individuals differ in where they fixate on a face, with some looking closer to the eyes while others prefer the mouth region. These individual biases are highly robust, generalize from the lab to the outside world, and have been associated with social cognition and associated disorders. However, it is unclear, whether these biases are specific to faces or influenced by domain-general mechanisms of vision. Here, we juxtaposed these hypotheses by testing whether individual face fixation biases generalize to inanimate objects. We analyzed >1.8 million fixations toward faces and objects in complex natural scenes from 405 participants tested in multiple labs. Consistent interindividual differences in fixation positions were highly inter-correlated across faces and objects in all samples. Observers who fixated closer to the eye region also fixated higher on inanimate objects and vice versa. Furthermore, the inter-individual spread of fixation positions scaled with target size in precisely the same, non-linear manner for faces and objects. These findings contradict a purely domain-specific account of individual face gaze. Instead, they suggest significant domain-general contributions to the individual way we look at faces, a finding with potential relevance for basic vision, face perception, social cognition, and associated clinical conditions.
Subject(s)
Facial Recognition , Fixation, Ocular , Humans , Individuality , Eye , FaceABSTRACT
Individuals differ in their sensitivity to the adverse consequences of their actions, leading some to persist in maladaptive behaviors. Two pathways have been identified for this insensitivity: a motivational pathway based on excessive reward valuation and a behavioral pathway based on autonomous stimulus-response mechanisms. Here, we identify a third, cognitive pathway based on differences in punishment knowledge and use of that knowledge to suppress behavior. We show that distinct phenotypes of punishment sensitivity emerge from differences in what people learn about their actions. Exposed to identical punishment contingencies, some people (sensitive phenotype) form correct causal beliefs that they use to guide their behavior, successfully obtaining rewards and avoiding punishment, whereas others form incorrect but internally coherent causal beliefs that lead them to earn punishment they do not like. Incorrect causal beliefs were not inherently problematic because we show that many individuals benefit from information about why they are being punished, revaluing their actions and changing their behavior to avoid further punishment (unaware phenotype). However, one condition where incorrect causal beliefs were problematic was when punishment is infrequent. Under this condition, more individuals show punishment insensitivity and detrimental patterns of behavior that resist experience and information-driven updating, even when punishment is severe (compulsive phenotype). For these individuals, rare punishment acted as a "trap," inoculating maladaptive behavioral preferences against cognitive and behavioral updating.
Subject(s)
Punishment , Reward , Punishment/psychology , Learning , Motivation , CognitionABSTRACT
Understanding the psychological processes that drive violent extremism is a pressing global issue. Across six studies, we demonstrate that perceived cultural threats lead to violent extremism because they increase people's need for cognitive closure (NFC). In general population samples (from Denmark, Afghanistan, Pakistan, France, and an international sample) and a sample of former Mujahideen in Afghanistan, single-level and multilevel mediation analyses revealed that NFC mediated the association between perceived cultural threats and violent extremist outcomes. Further, in comparisons between the sample of former Afghan Mujahideen and the general population sample from Afghanistan following the known-group paradigm, the former Mujahideen scored significantly higher on cultural threat, NFC, and violent extremist outcomes. Moreover, the proposed model successfully differentiated former Afghan Mujahideen participants from the general Afghan participants. Next, two preregistered experiments provided causal support for the model. Experimentally manipulating the predictor (cultural threat) in Pakistan led to higher scores on the mediator (NFC) and dependent variables (violent extremist outcomes). Finally, an experiment conducted in France demonstrated the causal effect of the mediator (NFC) on violent extremist outcomes. Two internal meta-analyses using state-of-the-art methods (i.e., meta-analytic structural equation modeling and pooled indirect effects analyses) further demonstrated the robustness of our results across the different extremist outcomes, designs, populations, and settings. Cultural threat perceptions seem to drive violent extremism by eliciting a need for cognitive closure.
Subject(s)
Terrorism , Violence , Humans , Violence/psychology , Terrorism/psychology , Aggression , Afghanistan , CognitionABSTRACT
Individual differences in using multiple languages are thought to differentially affect brain structure and function. The present study assessed the neuroanatomical predictions of an emerging theory, the Unifying the Bilingual Experience Trajectories framework, which provides the most comprehensive set of predictions of how individual differences in bilingual experiences lead to specific neural and cognitive adaptations. A total of 140 young adults with variable language experiences were scanned using magnetic resonance imaging and completed demographic questionnaires. Brain structure measures implicated in predictions of the Unifying the Bilingual Experience Trajectories model were extracted and regressed against the model's experiential factors. Consistent with the model's predictions, greater intensity and diversity of bilingual language use resulted in changes in gray matter volume in cortical regions involved in executive control (including inferior frontal gyrus, middle temporal gyrus, angular gyrus, and medial frontal gyrus), indicating adaptations toward handling increased executive control demands. Conversely, duration of bilingual engagement resulted in changes within white matter microstructure (bilateral superior longitudinal fasciculus) and increases in subcortical gray matter (left caudate), indicative of adaptations toward increased efficiency of control. Overall, this research enhances our understanding of how bilingual experiences influence brain structure and provides the first direct empirical evidence for the predictions made by the Unifying the Bilingual Experience Trajectories framework.
Subject(s)
Multilingualism , Young Adult , Humans , Brain/diagnostic imaging , Language , Executive Function , Brain Mapping , Magnetic Resonance ImagingABSTRACT
Statistical learning (SL) is the ability to detect and learn regularities from input and is foundational to language acquisition. Despite the dominant role of SL as a theoretical construct for language development, there is a lack of direct evidence supporting the shared neural substrates underlying language processing and SL. It is also not clear whether the similarities, if any, are related to linguistic processing, or statistical regularities in general. The current study tests whether the brain regions involved in natural language processing are similarly recruited during auditory, linguistic SL. Twenty-two adults performed an auditory linguistic SL task, an auditory nonlinguistic SL task, and a passive story listening task as their neural activation was monitored. Within the language network, the left posterior temporal gyrus showed sensitivity to embedded speech regularities during auditory, linguistic SL, but not auditory, nonlinguistic SL. Using a multivoxel pattern similarity analysis, we uncovered similarities between the neural representation of auditory, linguistic SL, and language processing within the left posterior temporal gyrus. No other brain regions showed similarities between linguistic SL and language comprehension, suggesting that a shared neurocomputational process for auditory SL and natural language processing within the left posterior temporal gyrus is specific to linguistic stimuli.
Subject(s)
Learning , Speech Perception , Adult , Humans , Language , Linguistics , Language Development , Brain , Speech Perception/physiology , Brain Mapping , Magnetic Resonance ImagingABSTRACT
Exacerbated negativity bias, including in responses to ambiguity, represents a common phenotype of internalizing disorders. Individuals differ in their propensity toward positive or negative appraisals of ambiguity. This variability constitutes one's valence bias, a stable construct linked to mental health. Evidence suggests an initial negativity in response to ambiguity that updates via regulatory processes to support a more positive bias. Previous work implicates the amygdala and prefrontal cortex, and regions of the cingulo-opercular system, in this regulatory process. Nonetheless, the neurodevelopmental origins of valence bias remain unclear. The current study tests whether intrinsic brain organization predicts valence bias among 119 children and adolescents (6 to 17 years). Using whole-brain resting-state functional connectivity, a machine-learning model predicted valence bias (r = 0.20, P = 0.03), as did a model restricted to amygdala and cingulo-opercular system features (r = 0.19, P = 0.04). Disrupting connectivity revealed additional intra-system (e.g. fronto-parietal) and inter-system (e.g. amygdala to cingulo-opercular) connectivity important for prediction. The results highlight top-down control systems and bottom-up perceptual processes that influence valence bias in development. Thus, intrinsic brain organization informs the neurodevelopmental origins of valence bias, and directs future work aimed at explicating related internalizing symptomology.
Subject(s)
Brain , Prefrontal Cortex , Child , Adolescent , Humans , Brain/diagnostic imaging , Brain/physiology , Prefrontal Cortex/physiology , Amygdala/diagnostic imaging , Amygdala/physiology , Brain Mapping , Magnetic Resonance ImagingABSTRACT
The speed-accuracy trade-off (SAT), whereby faster decisions increase the likelihood of an error, reflects a cognitive strategy humans must engage in during the performance of almost all daily tasks. To date, computational modeling has implicated the latent decision variable of response caution (thresholds), the amount of evidence required for a decision to be made, in the SAT. Previous imaging has associated frontal regions, notably the left prefrontal cortex and the presupplementary motor area (pre-SMA), with the setting of such caution levels. In addition, causal brain stimulation studies, using transcranial direct current stimulation (tDCS), have indicated that while both of these regions are involved in the SAT, their role appears to be dissociable. tDCS efficacy to impact decision-making processes has previously been linked with neurochemical concentrations and cortical thickness of stimulated regions. However, to date, it is unknown whether these neurophysiological measures predict individual differences in the SAT, and brain stimulation effects on the SAT. Using ultra-high field (7T) imaging, here we report that instruction-based adjustments in caution are associated with both neurochemical excitability (the balance between GABA+ and glutamate) and cortical thickness across a range of frontal regions in both sexes. In addition, cortical thickness, but not neurochemical concentrations, was associated with the efficacy of left prefrontal and superior medial frontal cortex (SMFC) stimulation to modulate performance. Overall, our findings elucidate key neurophysiological predictors, frontal neural excitation, of individual differences in latent psychological processes and the efficacy of stimulation to modulate these.SIGNIFICANCE STATEMENT The speed-accuracy trade-off (SAT), faster decisions increase the likelihood of an error, reflects a cognitive strategy humans must engage in during most daily tasks. The SAT is often investigated by explicitly instructing participants to prioritize speed or accuracy when responding to stimuli. Using ultra-high field (7T) magnetic resonance imaging (MRI), we found that individual differences in the extent to which participants adjust their decision strategies with instruction related to neurochemical excitability (ratio of GABA+ to glutamate) and cortical thickness in the frontal cortex. Moreover, brain stimulation to the left prefrontal cortex and the superior medial frontal cortex (SMFC) modulated performance, with the efficacy specifically related to cortical thickness. This work sheds new light on the neurophysiological basis of decision strategies and brain stimulation.
Subject(s)
Motor Cortex , Transcranial Direct Current Stimulation , Male , Female , Humans , Individuality , Motor Cortex/physiology , Glutamic Acid , gamma-Aminobutyric AcidABSTRACT
Diversity in brain health is influenced by individual differences in demographics and cognition. However, most studies on brain health and diseases have typically controlled for these factors rather than explored their potential to predict brain signals. Here, we assessed the role of individual differences in demographics (age, sex, and education; n = 1298) and cognition (n = 725) as predictors of different metrics usually used in case-control studies. These included power spectrum and aperiodic (1/f slope, knee, offset) metrics, as well as complexity (fractal dimension estimation, permutation entropy, Wiener entropy, spectral structure variability) and connectivity (graph-theoretic mutual information, conditional mutual information, organizational information) from the source space resting-state EEG activity in a diverse sample from the global south and north populations. Brain-phenotype models were computed using EEG metrics reflecting local activity (power spectrum and aperiodic components) and brain dynamics and interactions (complexity and graph-theoretic measures). Electrophysiological brain dynamics were modulated by individual differences despite the varied methods of data acquisition and assessments across multiple centers, indicating that results were unlikely to be accounted for by methodological discrepancies. Variations in brain signals were mainly influenced by age and cognition, while education and sex exhibited less importance. Power spectrum activity and graph-theoretic measures were the most sensitive in capturing individual differences. Older age, poorer cognition, and being male were associated with reduced alpha power, whereas older age and less education were associated with reduced network integration and segregation. Findings suggest that basic individual differences impact core metrics of brain function that are used in standard case-control studies. Considering individual variability and diversity in global settings would contribute to a more tailored understanding of brain function.
Subject(s)
Brain , Cognition , Electroencephalography , Humans , Male , Female , Adult , Cognition/physiology , Middle Aged , Brain/physiology , Aged , Young Adult , Individuality , Adolescent , Age Factors , Aging/physiologyABSTRACT
The knowledge that brain functional connectomes are unique and reliable has enabled behaviourally relevant inferences at a subject level. However, whether such "fingerprints" persist under altered states of consciousness is unknown. Ayahuasca is a potent serotonergic psychedelic which produces a widespread dysregulation of functional connectivity. Used communally in religious ceremonies, its shared use may highlight relevant novel interactions between mental state and functional connectome (FC) idiosyncrasy. Using 7T fMRI, we assessed resting-state static and dynamic FCs for 21 Santo Daime members after collective ayahuasca intake in an acute, within-subject study. Here, connectome fingerprinting revealed FCs showed reduced idiosyncrasy, accompanied by a spatiotemporal reallocation of keypoint edges. Importantly, we show that interindividual differences in higher-order FC motifs are relevant to experiential phenotypes, given that they can predict perceptual drug effects. Collectively, our findings offer an example of how individualised connectivity markers can be used to trace a subject's FC across altered states of consciousness.
Subject(s)
Banisteriopsis , Connectome , Humans , Brain/physiology , Consciousness , Magnetic Resonance ImagingABSTRACT
Recent work demonstrating low test-retest reliability of neural activation during fMRI tasks raises questions about the utility of task-based fMRI for the study of individual variation in brain function. Two possible sources of the instability in task-based BOLD signal over time are noise or measurement error in the instrument, and meaningful variation across time within-individuals in the construct itself-brain activation elicited during fMRI tasks. Examining the contribution of these two sources of test-retest unreliability in task-evoked brain activity has far-reaching implications for cognitive neuroscience. If test-retest reliability largely reflects measurement error, it suggests that task-based fMRI has little utility in the study of either inter- or intra-individual differences. On the other hand, if task-evoked BOLD signal varies meaningfully over time, it would suggest that this tool may yet be well suited to studying intraindividual variation. We parse these sources of variance in BOLD signal in response to emotional cues over time and within-individuals in a longitudinal sample with 10 monthly fMRI scans. Test-retest reliability was low, reflecting a lack of stability in between-person differences across scans. In contrast, within-person, within-session internal consistency of the BOLD signal was higher, and within-person fluctuations across sessions explained almost half the variance in voxel-level neural responses. Additionally, monthly fluctuations in neural response to emotional cues were associated with intraindividual variation in mood, sleep, and exposure to stressors. Rather than reflecting trait-like differences across people, neural responses to emotional cues may be more reflective of intraindividual variation over time. These patterns suggest that task-based fMRI may be able to contribute to the study of individual variation in brain function if more attention is given to within-individual variation approaches, psychometrics-beginning with improving reliability beyond the modest estimates observed here, and the validity of task fMRI beyond the suggestive associations reported here.
Subject(s)
Brain Mapping , Magnetic Resonance Imaging , Humans , Reproducibility of Results , Brain/diagnostic imaging , Brain/physiology , Emotions/physiologyABSTRACT
Women's psychological and behavioral responses to hormonal contraceptive (HC) treatment can be highly variable. One of the great challenges to researchers seeking to improve the experiences of women who use HCs is to identify the sources of this variability to minimize unpleasant psychobehavioral side-effects. In the following, we provide recommendations for programs of research aimed at identifying sources of heterogeneity in women's experiences with HC. First, we review research demonstrating person- and prescription- based heterogeneity in women's psychobehavioral responses to HCs. Next, we identify several promising person- and prescription- based sources of this heterogeneity that warrant future research. We close with a discussion of research approaches that are particularly well-suited to address the research questions raised in article. Together, this review provides researchers with several promising research pathways to help support the development of a precision medicine approach to HC treatment.
Subject(s)
Contraception , Hormonal Contraception , Humans , Female , Contraception/psychology , Precision MedicineABSTRACT
Recent magnetoencephalography (MEG) studies have reported that functional connectivity (FC) and power spectra can be used as neural fingerprints in differentiating individuals. Such studies have mainly used correlations between measurement sessions to distinguish individuals from each other. However, it has remained unclear whether such correlations might reflect a more generalizable principle of individually distinctive brain patterns. Here, we evaluated a machine-learning based approach, termed latent-noise Bayesian reduced rank regression (BRRR) as a means of modelling individual differences in the resting-state MEG data of the Human Connectome Project (HCP), using FC and power spectra as neural features. First, we verified that BRRR could model and reproduce the differences between metrics that correlation-based fingerprinting yields. We trained BRRR models to distinguish individuals based on data from one measurement and used the models to identify subsequent measurement sessions of those same individuals. The best performing BRRR models, using only 20 spatiospectral components, were able to identify subjects across measurement sessions with over 90% accuracy, approaching the highest correlation-based accuracies. Using cross-validation, we then determined whether that BRRR model could generalize to unseen subjects, successfully classifying the measurement sessions of novel individuals with over 80% accuracy. The results demonstrate that individual neurofunctional differences can be reliably extracted from MEG data with a low-dimensional predictive model and that the model is able to classify novel subjects.
Subject(s)
Bayes Theorem , Brain , Connectome , Magnetoencephalography , Humans , Magnetoencephalography/methods , Connectome/methods , Brain/physiology , Machine Learning , Male , Female , Adult , Models, NeurologicalABSTRACT
Mismatch negativity (MMN) and P3b are well known for their clinical utility. There exists no gold standard, however, for acquiring them as EEG markers of consciousness in clinical settings. This may explain why the within-individual sensitivity of MMN/P3b paradigms is often quite poor and why seemingly identical EEG markers can behave differently across Disorders of consciousness (DoC) studies. Here, we compare two traditional paradigms for MMN or P3b assessment with the recently more popular local-global paradigm that promises to assess MMN and P3b orthogonally within one oddball sequence. All three paradigms were administered to healthy participants (N = 15) with concurrent EEG. A clear MMN and local effect were found for 15/15 participants. The P3b and global effect were found for 14/15 and 13/15 participants, respectively. There were no systematic differences between the global effect and P3b. Indeed, P3b amplitude was highly correlated across paradigms. The local effect differed clearly from the MMN, however. It occurred earlier than MMN and was followed by a much more prominent P3a. The peak latencies and amplitudes were also not correlated across paradigms. Caution should therefore be exercised when comparing the local effect and MMN across studies. We conclude that the within-individual MMN sensitivity is adequate for both the local-global and a dedicated MMN paradigm. The within-individual sensitivity of P3b was lower than expected for both the local-global and a dedicated P3b paradigm, which may explain the often-low sensitivity of P3b paradigms in patients with DoC.
Subject(s)
Consciousness , Humans , Healthy VolunteersABSTRACT
AbstractSampling, investing time or energy to learn about the environment, allows organisms to track changes in resource distribution and quality. The use of sampling is predicted to change as a function of energy expenditure, food availability, and starvation risk, all of which can vary both within and among individuals. We studied sampling behavior in a field study with black-capped chickadees (Poecile atricapillus) and show that individuals adjust their use of sampling as a function of ambient temperature (a proxy for energy expenditure), the presence of an alternative food source (yes or no, a proxy for risk of energy shortfall), and their interaction, as predicted by models of optimal sampling. We also observed repeatable differences in sampling. Some individuals consistently sampled more, and individuals that sampled more overall also had a higher annual survival. These results are consistent with among-individual differences in resource acquisition (e.g., food caches or dominance-related differences in priority access to feeders), shaping among-individual differences in both sampling and survival, with greater resource acquisition leading to both higher sampling and higher survival. Although this explanation requires explicit testing, it is in line with several recent studies suggesting that variation in resource acquisition is a key mechanism underlying animal personality.
Subject(s)
Songbirds , Humans , Animals , LearningABSTRACT
Naturalistic paradigms, such as watching movies during functional magnetic resonance imaging, are thought to prompt the emotional and cognitive processes typically elicited in real life situations. Therefore, naturalistic viewing (NV) holds great potential for studying individual differences. Previous studies have primarily focused on using shorter movie clips, geared toward eliciting specific and often isolated emotions, while the potential behind using full narratives depicted in commercial movies as a proxy for real-life experiences has barely been explored. Here, we offer preliminary evidence that a full narrative movie (FNM), that is, a movie covering a complete narrative arc, can capture complex socio-affective dynamics and their links to individual differences. Using the studyforrest dataset, we investigated inter- and intra-subject similarity in network functional connectivity (NFC) of 14 meta-analytically defined networks across a full narrative, audio-visual movie split into eight consecutive movie segments. We characterized the movie segments by valence and arousal portrayed within the sequences, before utilizing a linear mixed model to analyze which factors explain inter- and intra-subject similarity. Our results show that the model best explaining inter-subject similarity comprised network, movie segment, valence and a movie segment by valence interaction. Intra-subject similarity was influenced significantly by the same factors and an additional three-way interaction between movie segment, valence and arousal. Overall, inter- and intra-subject similarity in NFC were sensitive to the ongoing narrative and emotions in the movie. We conclude that FNMs offer complex content and dynamics that might be particularly valuable for studying individual differences. Further characterization of movie features, such as the overarching narratives, that enhance individual differences is needed for advancing the potential of NV research.
Subject(s)
Connectome , Magnetic Resonance Imaging , Motion Pictures , Nerve Net , Humans , Adult , Connectome/methods , Nerve Net/physiology , Nerve Net/diagnostic imaging , Emotions/physiology , Individuality , Female , Male , Narration , Young Adult , Arousal/physiologyABSTRACT
It has been suggested that visual images are memorized across brief periods of time by vividly imagining them as if they were still there. In line with this, the contents of both working memory and visual imagery are known to be encoded already in early visual cortex. If these signals in early visual areas were indeed to reflect a combined imagery and memory code, one would predict them to be weaker for individuals with reduced visual imagery vividness. Here, we systematically investigated this question in two groups of participants. Strong and weak imagers were asked to remember images across brief delay periods. We were able to reliably reconstruct the memorized stimuli from early visual cortex during the delay. Importantly, in contrast to the prediction, the quality of reconstruction was equally accurate for both strong and weak imagers. The decodable information also closely reflected behavioral precision in both groups, suggesting it could contribute to behavioral performance, even in the extreme case of completely aphantasic individuals. Our data thus suggest that working memory signals in early visual cortex can be present even in the (near) absence of phenomenal imagery.