Individual differences in cognitive style and strategy predict similarities in the patterns of brain activity between individuals

Repetitive Transcranial Magnetic Stimulation (rTMS) Treatment Reduces Variability in Brain Function in Schizophrenia: Data From a Double-Blind, Randomized, Sham-Controlled Trial

BACKGROUND/HYPOTHESIS

There is increasing awareness of interindividual variability in brain function, with potentially major implications for repetitive transcranial magnetic stimulation (rTMS) efficacy. We perform a secondary analysis using data from a double-blind randomized controlled 4-week trial of 20 Hz active versus sham rTMS to dorsolateral prefrontal cortex (DLPFC) during a working memory task in participants with schizophrenia. We hypothesized that rTMS would change local functional activity and variability in the active group compared with sham.

STUDY DESIGN

83 participants were randomized in the original trial, and offered neuroimaging pre- and post-treatment. Of those who successfully completed both scans (n = 57), rigorous quality control left n = 42 (active/sham: n = 19/23), who were included in this analysis. Working memory-evoked activity during an N-Back (3-Back vs 1-Back) task was contrasted. Changes in local brain activity were examined from an 8 mm ROI around the rTMS coordinates. Individual variability was examined as the mean correlational distance (MCD) in brain activity pattern from each participant to others within the same group.

RESULTS

We observed an increase in task-evoked left DLPFC activity in the active group compared with sham (F1,36 = 5.83, False Discovery Rate (FDR))-corrected P = .04). Although whole-brain activation patterns were similar in both groups, active rTMS reduced the MCD in activation pattern compared with sham (F1,36 = 32.57, P < .0001). Reduction in MCD was associated with improvements in attention performance (F1,16 = 14.82, P = .0014, uncorrected).

CONCLUSIONS

Active rTMS to DLPFC reduces individual variability of brain function in people with schizophrenia. Given that individual variability is typically higher in schizophrenia patients compared with controls, such reduction may "normalize" brain function during higher-order cognitive processing.

Individual differences in spatial working memory strategies differentially reflected in the engagement of control and default brain networks

Spatial locations can be encoded and maintained in working memory using different representations and strategies. Fine-grained representations provide detailed stimulus information, but are cognitively demanding and prone to inexactness. The uncertainty in fine-grained representations can be compensated by the use of coarse, but robust categorical representations. In this study, we employed an individual differences approach to identify brain activity correlates of the use of fine-grained and categorical representations in spatial working memory. We combined data from six functional magnetic resonance imaging studies, resulting in a sample of $155$ ($77$ women, $25 \pm 5$ years) healthy participants performing a spatial working memory task. Our results showed that individual differences in the use of spatial representations in working memory were associated with distinct patterns of brain activity. Higher precision of fine-grained representations was related to greater engagement of attentional and control brain systems throughout the task trial, and the stronger deactivation of the default network at the time of stimulus encoding. In contrast, the use of categorical representations was associated with lower default network activity during encoding and higher frontoparietal network activation during maintenance. These results may indicate a greater need for attentional resources and protection against interference for fine-grained compared with categorical representations.

Disentangling the Individual-Shared and Individual-Specific Subspace of Altered Brain Functional Connectivity in Autism Spectrum Disorder

BACKGROUND

Despite considerable effort toward understanding the neural basis of autism spectrum disorder (ASD) using case-control analyses of resting-state functional magnetic resonance imaging data, findings are often not reproducible, largely due to biological and clinical heterogeneity among individuals with ASD. Thus, exploring the individual-shared and individual-specific altered functional connectivity (AFC) in ASD is important to understand this complex, heterogeneous disorder.

METHODS

We considered 254 individuals with ASD and 295 typically developing individuals from the Autism Brain Imaging Data Exchange to explore the individual-shared and individual-specific subspaces of AFC. First, we computed AFC matrices of individuals with ASD compared with typically developing individuals. Then, common orthogonal basis extraction was used to project AFC of ASD onto 2 subspaces: an individual-shared subspace, which represents altered connectivity patterns shared across ASD, and an individual-specific subspace, which represents the remaining individual characteristics after eliminating the individual-shared altered connectivity patterns.

RESULTS

Analysis yielded 3 common components spanning the individual-shared subspace. Common components were associated with differences of functional connectivity at the group level. AFC in the individual-specific subspace improved the prediction of clinical symptoms. The default mode network-related and cingulo-opercular network-related magnitudes of AFC in the individual-specific subspace were significantly correlated with symptom severity in social communication deficits and restricted, repetitive behaviors in ASD.

CONCLUSIONS

Our study decomposed AFC of ASD into individual-shared and individual-specific subspaces, highlighting the importance of capturing and capitalizing on individual-specific brain connectivity features for dissecting heterogeneity. Our analysis framework provides a blueprint for parsing heterogeneity in other prevalent neurodevelopmental conditions.

What is it like to do a visuo-spatial working memory task: A qualitative phenomenological study of the visual span task

Working memory is typically measured with specifically designed psychological tasks. When evaluating the validity of working memory tasks, we commonly focus on the reliability of the outcome measurements. Only rarely do we focus on how participants experience these tasks. Accounting for lived experience of working memory task may help us better understand variability in working memory performance and conscious experience in general. We replicated recently established protocols for the phenomenological investigation of working memory using the visual span task. We collected subjective reports from eighteen healthy participants (10 women) aged 21 to 35 years. We observed that working memory can be phenomenologically characterized at three different time scales: background feelings, strategies, and tactics. On the level of tactics, we identified transmodality (i.e., how one modality of lived experience can be transformed into another one) as the central phenomenological dynamic at play during working memory task performance.

Quantifying the contribution of subject and group factors in brain activation

Research in neuroscience often assumes universal neural mechanisms, but increasing evidence points toward sizeable individual differences in brain activations. What remains unclear is the extent of the idiosyncrasy and whether different types of analyses are associated with different levels of idiosyncrasy. Here we develop a new method for addressing these questions. The method consists of computing the within-subject reliability and subject-to-group similarity of brain activations and submitting these values to a computational model that quantifies the relative strength of group- and subject-level factors. We apply this method to a perceptual decision-making task (n = 50) and find that activations related to task, reaction time, and confidence are influenced equally strongly by group- and subject-level factors. Both group- and subject-level factors are dwarfed by a noise factor, though higher levels of smoothing increases their contributions relative to noise. Overall, our method allows for the quantification of group- and subject-level factors of brain activations and thus provides a more detailed understanding of the idiosyncrasy levels in brain activations.

Mnemicity: A Cognitive Gadget?

Episodic representations can be entertained either as "remembered" or "imagined"-as outcomes of experience or as simulations of such experience. Here, we argue that this feature is the product of a dedicated cognitive function: the metacognitive capacity to determine the mnemicity of mental event simulations. We argue that mnemicity attribution should be distinguished from other metacognitive operations (such as reality monitoring) and propose that this attribution is a "cognitive gadget"-a distinctively human ability made possible by cultural learning. Cultural learning is a type of social learning in which traits are inherited through social interaction. In the case of mnemicity, one culturally learns to discriminate metacognitive "feelings of remembering" from other perceptual, emotional, action-related, and metacognitive feelings; to interpret feelings of remembering as indicators of memory rather than imagination; and to broadcast the interpreted feelings in culture- and context-specific ways, such as "I was there" or "I witnessed it myself." We review evidence from the literature on memory development and scaffolding, metacognitive learning and teaching, as well as cross-cultural psychology in support of this view before pointing out various open questions about the nature and development of mnemicity highlighted by our account.

The Diversity of Strategies Used in Working Memory for Colors, Orientations, and Positions: A Quantitative Approach to a First-Person Inquiry

The study of individual experience during the performance of a psychological task using a phenomenological approach is a relatively new area of research. The aim of this paper was to combine first- and third-person approaches to investigate whether the strategies individuals use during a working memory task are associated with specific task conditions, whether the strategies combine to form stable patterns, and whether the use of specific strategies is related to task accuracy. Thirty-one participants took part in an experiment in which they were instructed to remember colors, orientations, or positions of stimuli presented in a change detection task. After every 7th-15th trial, participants took part in an in-depth phenomenological interview in which they described their experiences during the trial that immediately preceded the interview. Qualitative analysis revealed a set of 18 strategies that participants used while performing the task, which we divided into active and passive strategies of encoding, maintenance, and retrieval. Quantitative analysis revealed that while many strategies were used in all task conditions, some strategies and their combinations may be better suited to the specific task demands, while others are more general in nature. The results also suggest a distinction between strategies for encoding object identity and spatial features. Finally, our results did not provide robust evidence for a relationship between specific strategies and task accuracy.

Greater individual variability in functional brain activity during working memory performance in Schizophrenia Spectrum Disorders (SSD)

Heterogeneity has been a persistent challenge in understanding Schizophrenia Spectrum Disorders (SSD). Traditional case-control comparisons often show variable results, and may not map well onto individuals. To better understand heterogeneity and group differences in SSD compared to typically developing controls (TDC), we examined variability in functional brain activity during a working memory (WM) task with known deficits in SSD. Neuroimaging and behavioural data were extracted from two datasets collectively providing 34 TDC and 56 individuals with SSD (n = 90). Functional activity in response to an N-Back WM task (3-Back vs 1-Back) was examined between and within groups. Individual variability was calculated via the correlational distance of fMRI activity maps between participants; mean correlational distance from one participant to all others was defined as a 'variability score'. Greater individual variability in functional activity was found in SSD compared to TDC (p = 0.00090). At the group level, a case-control comparison suggested SSD had reduced activity in task positive and task negative networks. However, when SSD were divided into high and low variability subgroups, the low variability groups showed no differences relative to TDC while the high variability group showed little activity at the group level. Our results imply prior case-control differences may be driven by a subgroup of SSD who do not show specific impairments but instead show more 'idiosyncratic' activity patterns. In SSD but not TDC, variability was also related to cognitive performance and age. This novel approach focusing on individual variability has important implications for understanding the neurobiology of SSD.

Relationship of neurite architecture to brain activity during task-based fMRI

Functional MRI (fMRI) has been widely used to examine changes in neuronal activity during cognitive tasks. Commonly used measures of gray matter macrostructure (e.g., cortical thickness, surface area, volume) do not consistently appear to serve as structural correlates of brain function. In contrast, gray matter microstructure, measured using neurite orientation dispersion and density imaging (NODDI), enables the estimation of indices of neurite density (neurite density index; NDI) and organization (orientation dispersion index; ODI) in gray matter. Our study explored the relationship among neurite architecture, BOLD (blood-oxygen-level-dependent) fMRI, and cognition, using a large sample (n = 750) of young adults of the human connectome project (HCP) and two tasks that index more cortical (working memory) and more subcortical (emotion processing) targeting of brain functions. Using NODDI, fMRI, structural MRI and task performance data, hierarchical regression analyses revealed that higher working memory- and emotion processing-evoked BOLD activity was related to lower ODI in the right DLPFC, and lower ODI and NDI values in the right and left amygdala, respectively. Common measures of brain macrostructure (i.e., DLPFC thickness/surface area and amygdala volume) did not explain any additional variance (beyond neurite architecture) in BOLD activity. A moderating effect of neurite architecture on the relationship between emotion processing task-evoked BOLD response and performance was observed. Our findings provide evidence that neuro-/social-affective cognition-related BOLD activity is partially driven by the local neurite organization and density with direct impact on emotion processing. In vivo gray matter microstructure represents a new target of investigation providing strong potential for clinical translation.

Individual differences in frontoparietal plasticity in humans

Neuroplasticity, defined as the brain's potential to change in response to its environment, has been extensively studied at the cellular and molecular levels. Work in animal models suggests that stimulation to the ventral tegmental area (VTA) enhances plasticity, and that myelination constrains plasticity. Little is known, however, about whether proxy measures of these properties in the human brain are associated with learning. Here, we investigated the plasticity of the frontoparietal system by asking whether VTA resting-state functional connectivity and myelin map values (T1w/T2w ratios) predicted learning after short-term training on the adaptive n-back (n = 46, ages 18-25). We found that stronger baseline connectivity between VTA and lateral prefrontal cortex predicted greater improvements in accuracy. Lower myelin map values predicted improvements in response times, but not accuracy. Our findings suggest that proxy markers of neural plasticity can predict learning in humans.

What Individuals Experience During Visuo-Spatial Working Memory Task Performance: An Exploratory Phenomenological Study

In experimental cognitive psychology, objects of inquiry are typically operationalized with psychological tasks. When interpreting results from such tasks, we focus primarily on behavioral measures such as reaction times and accuracy rather than experiences - i.e., phenomenology - associated with the task, and posit that the tasks elicit the desired cognitive phenomenon. Evaluating whether the tasks indeed elicit the desired phenomenon can be facilitated by understanding the experience during task performance. In this paper we explore the breadth of experiences that are elicited by and accompany task performance using in-depth phenomenological and qualitative methodology to gather subjective reports during the performance of a visuo-spatial change detection task. Thirty-one participants (18 females) were asked to remember either colors, orientations or positions of the presented stimuli and recall them after a short delay. Qualitative reports revealed rich experiential landscapes associated with the task-performance, suggesting a distinction between two broad classes of experience: phenomena at the front of consciousness and background feelings. The former includes cognitive strategies and aspects of metacognition, whereas the latter include more difficult-to-detect aspects of experience that comprise the overall sense of experience (e.g., bodily feelings, emotional atmosphere, mood). We focus primarily on the background feelings, since strategies of task-performance to a large extent map onto previously identified cognitive processes and discuss the methodological implications of our findings.

Subjective difficulty in a verbal recognition-based memory task: Exploring brain-behaviour relationships at the individual level in healthy young adults

The vast majority of fMRI studies of task-related brain activity utilize common levels of task demands and analyses that rely on the central tendencies of the data. This approach does not take into account perceived difficulty nor regional variations in brain activity between people. The results are findings of brain-behavior relationships that weaken as sample sizes increase. Participants of the current study included twenty-six healthy young adults evenly split between the sexes. The current work utilizes five parametrically modulated levels of memory load centered around each individual's predetermined working memory cognitive capacity. Principal components analyses (PCA) identified the group-level central tendency of the data. After removing the group effect from the data, PCA identified individual-level patterns of brain activity across the five levels of task demands. Expression of the group effect significantly differed between the sexes across all load levels. Expression of the individual level patterns demonstrated a significant load by sex interaction. Furthermore, expressions of the individual maps make better predictors of response time behavior than group-derived maps. We demonstrated that utilization of an individual's unique pattern of brain activity in response to increasing a task's perceived difficulty is a better predictor of brain-behavior relationships than study designs and analyses focused on identification of group effects. Furthermore, these methods facilitate exploration into how individual differences in patterns of brain activity relate to individual differences in behavior and cognition.

Individual differences in skill acquisition and transfer assessed by dual task training performance and brain activity

Assessment of expertise development during training program primarily consists of evaluating interactions between task characteristics, performance, and mental load. Such a traditional assessment framework may lack consideration of individual characteristics when evaluating training on complex tasks, such as driving and piloting, where operators are typically required to execute multiple tasks simultaneously. Studies have already identified individual characteristics arising from intrinsic, context, strategy, personality, and preference as common predictors of performance and mental load. Therefore, this study aims to investigate the effect of individual difference in skill acquisition and transfer using an ecologically valid dual task, behavioral, and brain activity measures. Specifically, we implemented a search and surveillance task (scanning and identifying targets) using a high-fidelity training simulator for the unmanned aircraft sensor operator, acquired behavioral measures (scan, not scan, over scan, and adaptive target find scores) using simulator-based analysis module, and measured brain activity changes (oxyhemoglobin and deoxyhemoglobin) from the prefrontal cortex (PFC) using a portable functional near-infrared spectroscopy (fNIRS) sensor array. The experimental protocol recruited 13 novice participants and had them undergo three easy and two hard sessions to investigate skill acquisition and transfer, respectively. Our results from skill acquisition sessions indicated that performance on both tasks did not change when individual differences were not accounted for. However inclusion of individual differences indicated that some individuals improved only their scan performance (Attention-focused group), while others improved only their target find performance (Accuracy-focused group). Brain activity changes during skill acquisition sessions showed that mental load decreased in the right anterior medial PFC (RAMPFC) in both groups regardless of individual differences. However, mental load increased in the left anterior medial PFC (LAMPFC) of Attention-focused group and decreased in the Accuracy-focused group only when individual differences were included. Transfer results showed no changes in performance regardless of grouping based on individual differences; however, mental load increased in RAMPFC of Attention-focused group and left dorsolateral PFC (LDLPFC) of Accuracy-focused group. Efficiency and involvement results suggest that the Attention-focused group prioritized the scan task, while the Accuracy-focused group prioritized the target find task. In conclusion, training on multitasks results in individual differences. These differences may potentially be due to individual preference. Future studies should incorporate individual differences while assessing skill acquisition and transfer during multitask training.

Inter-Individual Differences in Cognitive Tasks: Focusing on the Shaping of Decision-Making Strategies

In this paper, we review recent (published and novel) data showing inter-individual variation in decision-making strategies established by mice in a gambling task (MGT for Mouse Gambling Task). It may look intriguing, at first, that congenic animals develop divergent behaviors. However, using large groups of mice, we show that individualities emerge in the MGT, with about 30% of healthy mice displaying risk-averse choices while about 20-25% of mice make risk-prone choices. These strategies are accompanied by different brain network mobilization and individual levels of regional -prefrontal and striatal- monoamines. We further illustrate three ecological ways that influence drastically cognitive strategies in healthy adult mice: sleep deprivation, sucrose or artificial sweetener exposure, and regular exposure to stimulating environments. Questioning how to unmask individual strategies, what are their neural/neurochemical bases and whether we can shape or reshape them with different environmental manipulations is of great value, first to understand how the brain may build flexible decisions, and second to study behavioral plasticity, in healthy adult, as well as in developing brains. The latter may open new avenues for the identification of vulnerability traits to adverse events, before the emergence of mental pathologies.

Gene expression associated with human brain activations in facial expression recognition

Previous studies identified some genetic loci of emotion, but few focused on human emotion-related gene expression. In this study, the facial expression recognition (FER) task-based high-resolution fMRI data of 203 subjects in the Human Connectome Project (HCP) and expression data of the six healthy human postmortem brain tissues in the Allen Human Brain Atlas (AHBA) were used to conduct a transcriptome-neuroimaging spatial association analysis. Finally, 371 genes were identified to be significantly associated with FER-related brain activations. Enrichment analyses revealed that FER-related genes were mainly expressed in the brain, especially neurons, and might be related to cell junction organization, synaptic functions, and nervous system development regulation, indicating that FER was a complex polygenetic biological process involving multiple pathways. Moreover, these genes exhibited higher enrichment for psychiatric diseases with heavy emotion impairments. This study provided new insight into understanding the FER-related biological mechanisms and might be helpful to explore treatment methods for emotion-related psychiatric disorders.

Reorganization of the Neurobiology of Language After Sentence Overlearning

It is assumed that there are a static set of "language regions" in the brain. Yet, language comprehension engages regions well beyond these, and patients regularly produce familiar "formulaic" expressions when language regions are severely damaged. These suggest that the neurobiology of language is not fixed but varies with experiences, like the extent of word sequence learning. We hypothesized that perceiving overlearned sentences is supported by speech production and not putative language regions. Participants underwent 2 sessions of behavioral testing and functional magnetic resonance imaging (fMRI). During the intervening 15 days, they repeated 2 sentences 30 times each, twice a day. In both fMRI sessions, they "passively" listened to those sentences, novel sentences, and produced sentences. Behaviorally, evidence for overlearning included a 2.1-s decrease in reaction times to predict the final word in overlearned sentences. This corresponded to the recruitment of sensorimotor regions involved in sentence production, inactivation of temporal and inferior frontal regions involved in novel sentence listening, and a 45% change in global network organization. Thus, there was a profound whole-brain reorganization following sentence overlearning, out of "language" and into sensorimotor regions. The latter are generally preserved in aphasia and Alzheimer's disease, perhaps explaining residual abilities with formulaic expressions in both.

Moving beyond the mean: Subgroups and dimensions of brain activity and cognitive performance across domains

Human neuroimaging during cognitive tasks has provided unique and important insights into the neurobiology of cognition. However, the vast majority of research relies on group aggregate or average statistical maps of activity, which do not fully capture the rich intersubject variability in brain function. In order to fully understand the neurobiology of cognitive processes, it is necessary to explore the range of variability in activation patterns across individuals. To better characterize individual variability, hierarchical clustering was performed separately on six fMRI tasks in 822 participants from the Human Connectome Project. Across all tasks, clusters ranged from a predominantly 'deactivating' pattern towards a more 'activating' pattern of brain activity, with significant differences in out-of-scanner cognitive test scores between clusters. Cluster stability was assessed via a resampling approach; a cluster probability matrix was generated, as the probability of any pair of participants clustering together when both were present in a random subsample. Rather than forming distinct clusters, participants fell along a spectrum or into pseudo-clusters without clear boundaries. A principal components analysis of the cluster probability matrix revealed three components explaining over 90% of the variance in clustering. Plotting participants in this lower-dimensional 'similarity space' revealed manifolds of variations along an S 'snake' shaped spectrum or a folded circle or 'tortilla' shape. The 'snake' shape was present in tasks where individual variability related to activity along covarying networks, while the 'tortilla' shape represented multiple networks which varied independently.

Individualizing Representational Similarity Analysis

Representational similarity analysis (RSA) is a popular multivariate analysis technique in cognitive neuroscience that uses functional neuroimaging to investigate the informational content encoded in brain activity. As RSA is increasingly being used to investigate more clinically-geared questions, the focus of such translational studies turns toward the importance of individual differences and their optimization within the experimental design. In this perspective, we focus on two design aspects: applying individual vs. averaged behavioral dissimilarity matrices to multiple participants' neuroimaging data and ensuring the congruency between tasks when measuring behavioral and neural representational spaces. Incorporating these methods permits the detection of individual differences in representational spaces and yields a better-defined transfer of information from representational spaces onto multivoxel patterns. Such design adaptations are prerequisites for optimal translation of RSA to the field of precision psychiatry.

Subject-specific segregation of functional territories based on deep phenotyping

Functional magnetic resonance imaging (fMRI) has opened the possibility to investigate how brain activity is modulated by behavior. Most studies so far are bound to one single task, in which functional responses to a handful of contrasts are analyzed and reported as a group average brain map. Contrariwise, recent data-collection efforts have started to target a systematic spatial representation of multiple mental functions. In this paper, we leverage the Individual Brain Charting (IBC) dataset-a high-resolution task-fMRI dataset acquired in a fixed environment-in order to study the feasibility of individual mapping. First, we verify that the IBC brain maps reproduce those obtained from previous, large-scale datasets using the same tasks. Second, we confirm that the elementary spatial components, inferred across all tasks, are consistently mapped within and, to a lesser extent, across participants. Third, we demonstrate the relevance of the topographic information of the individual contrast maps, showing that contrasts from one task can be predicted by contrasts from other tasks. At last, we showcase the benefit of contrast accumulation for the fine functional characterization of brain regions within a prespecified network. To this end, we analyze the cognitive profile of functional territories pertaining to the language network and prove that these profiles generalize across participants.

Individual Differences in the Neural Localization of Relational Networks of Semantic Concepts

Semantic concepts relate to each other to varying degrees to form a network of zero-order relations, and these zero-order relations serve as input into networks of general relation types as well as higher order relations. Previous work has studied the neural mapping of semantic concepts across domains, although much work remains to be done to understand how the localization and structure of those architectures differ depending on various individual differences in attentional bias toward different content presentation formats. Using an item-wise model of semantic distance of zero-order relations (Word2vec) between stimuli (presented both in word and picture forms), we used representational similarity analysis to identify individual differences in the neural localization of semantic concepts and how those localization differences can be predicted by individual variance in the degree to which individuals attend to word information instead of pictures. Importantly, there were no reliable representations of this zero-order semantic relational network when looking at the full group, and it was only through considering individual differences that a stable localization difference became evident. These results indicate that individual differences in the degree to which a person habitually attends to word information instead of picture information substantially affects the neural localization of zero-order semantic representations.

Individual Differences in Brain Responses: New Opportunities for Tailoring Health Communication Campaigns

Prevention neuroscience investigates the brain basis of attitude and behavior change. Over the years, an increasingly structurally and functionally resolved "persuasion network" has emerged. However, current studies have only identified a small handful of neural structures that are commonly recruited during persuasive message processing, and the extent to which these (and other) structures are sensitive to numerous individual difference factors remains largely unknown. In this project we apply a multi-dimensional similarity-based individual differences analysis to explore which individual factors-including characteristics of messages and target audiences-drive patterns of brain activity to be more or less similar across individuals encountering the same anti-drug public service announcements (PSAs). We demonstrate that several ensembles of brain regions show response patterns that are driven by a variety of unique factors. These results are discussed in terms of their implications for neural models of persuasion, prevention neuroscience and message tailoring, and methodological implications for future research.

Decision making under uncertainty in a quasi realistic binary decision task - An fMRI study

Approaching real life decision making through Quasi Realistic Decision Making may increase the ecological validity of decision making experiments. This could help narrow the gap between laboratory settings and observations in real world contexts and thus allow for generalization of laboratory results to everyday life. A binary decision task with quasi realistic context and stimuli was created to investigate neural processing of certain and uncertain decision making, using functional Magnetic Resonance Imaging. On the basis of behavioral data (consistency of decisions in identical contexts), trials with uncertain and certain decision making were identified. This allowed for comparing uncertain and certain conditions, and contrasting each condition with a low level baseline (i.e., between trial fixation dot). A Conjunction analysis between contrasts of uncertainty versus baseline and certainty versus baseline indicated a large overlap of neural network recruitment distributed in bilateral middle frontal, medial frontal, inferior parietal, occipito-temporal, and medio-temporal areas, and the cingulate cortex. While basic neural processing principles in uncertain and certain contexts were comparable, the direct contrast revealed activation foci in middle cingulate and in frontal and parietal areas. The quasi realistic approach revealed a common network for decision making which is modulated by uncertainty.

Mental state space visualization for interactive modeling of personalized BCI control strategies

OBJECTIVE

Numerous studies in the area of BCI are focused on the search for a better experimental paradigm-a set of mental actions that a user can evoke consistently and a machine can discriminate reliably. Examples of such mental activities are motor imagery, mental computations, etc. We propose a technique that instead allows the user to try different mental actions in the search for the ones that will work best.

APPROACH

The system is based on a modification of the self-organizing map (SOM) algorithm and enables interactive communication between the user and the learning system through a visualization of user's mental state space. During the interaction with the system the user converges on the paradigm that is most efficient and intuitive for that particular user.

MAIN RESULTS

Results of the two experiments, one allowing muscular activity, another permitting mental activity only, demonstrate soundness of the proposed method and offer preliminary validation of the performance improvement over the traditional closed-loop feedback approach.

SIGNIFICANCE

The proposed method allows a user to visually explore their mental state space in real time, opening new opportunities for scientific inquiry. The application of this method to the area of brain-computer interfaces enables more efficient search for the mental states that will allow a user to reliably control a BCI system.

Trait-like variants in human functional brain networks

Resting-state functional magnetic resonance imaging (fMRI) has provided converging descriptions of group-level functional brain organization. Recent work has revealed that functional networks identified in individuals contain local features that differ from the group-level description. We define these features as network variants. Building on these studies, we ask whether distributions of network variants reflect stable, trait-like differences in brain organization. Across several datasets of highly-sampled individuals we show that 1) variants are highly stable within individuals, 2) variants are found in characteristic locations and associate with characteristic functional networks across large groups, 3) task-evoked signals in variants demonstrate a link to functional variation, and 4) individuals cluster into subgroups on the basis of variant characteristics that are related to differences in behavior. These results suggest that distributions of network variants may reflect stable, trait-like, functionally relevant individual differences in functional brain organization.

Brainglance: Visualizing Group Level MRI Data at One Glance

The vast majority of studies using functional magnetic resonance imaging (fMRI) are analyzed on the group level. Standard group-level analyses, however, come with severe drawbacks: First, they assume functional homogeneity within the group, building on the idea that we use our brains in similar ways. Second, group-level analyses require spatial warping and substantial smoothing to accommodate for anatomical variability across subjects. Such procedures massively distort the underlying fMRI data, which hampers the spatial specificity. Taken together, group statistics capture the effective overlap, rendering the modeling of individual deviations impossible – a major source of false positivity and negativity. The alternative analysis approach is to leave the data in the native subject space, but this makes comparison across individuals difficult. Here, we propose a new framework for visualizing group-level information, better preserving the information of individual subjects. Our proposal is to limit the use of invasive data procedures such as spatial smoothing and warping and rather extract regional information from the individuals. This information is then visualized for all subjects and brain areas at one glance – hence we term the method brainglance. Additionally, our method incorporates a means for clustering individuals to further identify common traits. We showcase our method on two publicly available data sets and discuss our findings.

Sensorimotor, language, and working memory representation within the human cerebellum

The cerebellum is involved in a wide range of behaviours. A key organisational principle from animal studies is that somatotopically corresponding sensory input and motor output reside in the same cerebellar cortical areas. However, compelling evidence for a similar arrangement in humans and whether it extends to cognitive functions is lacking. To address this, we applied cerebellar optimised whole‐brain functional MRI in 20 healthy subjects. To assess spatial overlap within the sensorimotor and cognitive domains, we recorded activity to a sensory stimulus (vibrotactile) and a motor task; the Sternberg verbal working memory (VWM) task; and a verb generation paradigm. Consistent with animal data, sensory and motor activity overlapped with a somatotopic arrangement in ipsilateral areas of the anterior and posterior cerebellum. During the maintenance phase of the Sternberg task, a positive linear relationship between VWM load and activity was observed in right Lobule VI, extending into Crus I bilaterally. Articulatory movement gave rise to bilateral activity in medial Lobule VI. A conjunction of two independent language tasks localised activity during verb generation in right Lobule VI‐Crus I, which overlapped with activity during VWM. These results demonstrate spatial compartmentalisation of sensorimotor and cognitive function in the human cerebellum, with each area involved in more than one aspect of a given behaviour, consistent with an integrative function. Sensorimotor localisation was uniform across individuals, but the representation of cognitive tasks was more variable, highlighting the importance of individual scans for mapping higher order functions within the cerebellum.

Separable and Replicable Neural Strategies During Social Brain Function in People With and Without Severe Mental Illness

OBJECTIVE

Case-control study design and disease heterogeneity may impede biomarker discovery in brain disorders, including serious mental illnesses. To identify biologically and/or behaviorally driven as opposed to diagnostically driven subgroups of individuals, the authors used hierarchical clustering to identify individuals with similar patterns of brain activity during a facial imitate/observe functional MRI task.

METHODS

Participants in the Social Processes Initiative in Neurobiology of the Schizophrenia(s) study (N=179; 109 with a schizophrenia spectrum disorder and 70 healthy control participants) underwent MRI scanning at three sites. Hierarchical clustering was used to identify new data-driven groups of participants; differences on social and neurocognitive tests completed outside the scanner were compared among the new groups.

RESULTS

Three clusters with distinct patterns of neural activity were found. Cluster membership was not related to diagnosis or scan site. The largest cluster consisted of "typical activators," with activity in the canonical "simulation" circuit. The other clusters represented a "hyperactivating" group and a "deactivating" group. Between-participants Euclidean distances were smaller within clusters than within site or diagnostics groups. The deactivating group had the highest social cognitive and neurocognitive test scores. The hierarchical clustering analysis was repeated on a replication sample (N=108; 32 schizophrenia spectrum disorder, 37 euthymic bipolar disorder, and 39 healthy control participants), which exhibited the same three cluster patterns.

CONCLUSIONS

The study findings demonstrate replicable differing patterns of neural activity among individuals during a socio-emotional task, independent of DSM diagnosis or scan site. The findings may provide objective neuroimaging endpoints (biomarkers) for subgroups of individuals in target engagement research aimed at enhancing cognitive performance independent of diagnostic category.

Redefining Visual Working Memory: A Cognitive-Strategy, Brain-Region Approach

The ability to remember and manipulate visual information is pervasive and is associated with many cognitive abilities. Yet despite the importance of visual working memory (VWM), there is little consensus among researchers in the field as to which neural areas are necessary and sufficient and which models best describe its capacity. Here, we propose that an assumption that all people remember visual information in the same way has led to much contention and inconsistencies in the field. By accepting that there are multiple cognitive strategies and methods to perform a VWM task, we introduce an individual “precision” approach to the study of memory. We propose that VWM should be redefined, not by the type of stimuli used (e.g., visual) but rather by the specific mental processes (e.g., visual imagery, semantic, propositional, spatial) and the corresponding brain regions used to complete the mnemonic task. We further provide a short how-to guide for measuring different mnemonic strategies used for working memory.

The situation or the person? Individual and task-evoked differences in BOLD activity

Investigations of between-person variability are enjoying a recent resurgence in functional magnetic resonance imaging (fMRI) research. Several recent studies have found persistent between-person differences in blood-oxygenated-level dependent (BOLD) activation patterns and resting-state functional connectivity. Conflicting findings have been reported regarding the extent to which (a) between-person or (b) within-person cognitive state differences explain differences in BOLD activation patterns. These discrepancies may arise due to statistical analysis choices, parcellation resolution, and limited sampling of task-fMRI datasets. We attempt to address these issues in a large-scale analysis of several task-fMRI paradigms. Using a novel application of multivariate distance matrix regression, we examine between-person and task-condition variability estimates across varying levels of "resolution", from a coarse region-of-interest level to the vertex-level, and across different distance metrics. These analyses revealed that under most circumstances, differences in task conditions explained a greater amount of variance in activation map differences than between-person differences. However, this finding was reversed when comparing activation maps at a "high-resolution" vertex level. More generally, we observed that when moving from "low" to "high" resolutions, the variance explained by between-person differences increased while variance explained by task conditions decreased. We further analyzed the relationships among subject-level activation maps across all task-conditions using an unsupervised clustering approach and identified a superordinate task structure. This structure went beyond conventional task labels and highlighted those experimental manipulations across task conditions that produce contrasting versus similar whole-brain activation patterns. Overall, these analyses suggest that the question of the subject- versus task-effects on BOLD activation patterns is nontrivial, and depends on the comparison "resolution," choice of distance metric, and the coding of task-conditions.

The evolution of cognitive models: From neuropsychology to neuroimaging and back

This paper provides a historical and future perspective on how neuropsychology and neuroimaging can be used to develop cognitive models of human brain functions. Section 1 focuses on the emergence of cognitive modelling from neuropsychology, why lesion location was considered to be unimportant and the challenges faced when mapping symptoms to impaired cognitive processes. Section 2 describes how established cognitive models based on behavioural data alone cannot explain the complex patterns of distributed brain activity that are observed in functional neuroimaging studies. This has led to proposals for new cognitive processes, new cognitive strategies and new functional ontologies for cognition. Section 3 considers how the integration of data from lesion, behavioural and functional neuroimaging studies of large cohorts of brain damaged patients can be used to determine whether inter-patient variability in behaviour is due to differences in the premorbid function of each brain region, lesion site or cognitive strategy. This combination of neuroimaging and neuropsychology is providing a deeper understanding of how cognitive functions can be lost and re-learnt after brain damage - an understanding that will transform our ability to generate and validate cognitive models that are both physiologically plausible and clinically useful.

Verbal and visual cognition: Individual differences in the lab, in the brain, and in the classroom

In many ways, individuals vary in their thought processes, and in their cognitive strengths and weaknesses. Among the findings revealed by individual differences research, one major dividing line highlighted recurrently by decades of experimental studies is that between linguistically-mediated cognitive operations (verbal cognition), versus cognition, which primarily operates on visual - or visuospatial - representations (visual cognition). In this article, we review findings from three research areas-cognitive abilities, working memory, and task strategies-focusing on individual differences in verbal and visual cognition. In each area we highlight behavioral, neuroimaging, and classroom-based findings, bridging the perspectives of these different methodologies.

Small sample sizes reduce the replicability of task-based fMRI studies

Despite a growing body of research suggesting that task-based functional magnetic resonance imaging (fMRI) studies often suffer from a lack of statistical power due to too-small samples, the proliferation of such underpowered studies continues unabated. Using large independent samples across eleven tasks, we demonstrate the impact of sample size on replicability, assessed at different levels of analysis relevant to fMRI researchers. We find that the degree of replicability for typical sample sizes is modest and that sample sizes much larger than typical (e.g., N = 100) produce results that fall well short of perfectly replicable. Thus, our results join the existing line of work advocating for larger sample sizes. Moreover, because we test sample sizes over a fairly large range and use intuitive metrics of replicability, our hope is that our results are more understandable and convincing to researchers who may have found previous results advocating for larger samples inaccessible.

Interpreting and Utilising Intersubject Variability in Brain Function

We consider between-subject variance in brain function as data rather than noise. We describe variability as a natural output of a noisy plastic system (the brain) where each subject embodies a particular parameterisation of that system. In this context, variability becomes an opportunity to: (i) better characterise typical versus atypical brain functions; (ii) reveal the different cognitive strategies and processing networks that can sustain similar tasks; and (iii) predict recovery capacity after brain damage by taking into account both damaged and spared processing pathways. This has many ramifications for understanding individual learning preferences and explaining the wide differences in human abilities and disabilities. Understanding variability boosts the translational potential of neuroimaging findings, in particular in clinical and educational neuroscience.

Age-Related Changes in Field Dependence-Independence and Implications for Geriatric Rehabilitation: A Review

Human aging is a dynamic life-long process and an inevitable experience. As the average age of the world's population rises, demands for effective geriatric rehabilitation dramatically increase. An important consideration for enhancing geriatric behavioral interventions is to better understand aging characteristics in perceptual, cognitive, and motor performances. A general shift in cognitive style from field independence to field dependence has been consistently observed during human aging, as older adults show a greater tendency to rely on environmental information, presumably reflecting a neuro-compensatory mechanism of reducing top-down control and relying instead on bottom-up processing. These changes in cognitive style can impact motor skill learning and relearning and, consequently, affect geriatric rehabilitation and behavioral treatments. In this article, we review research related to the cognitive style of field dependence and independence, and its dynamic associations with aging. We also identify implications of cognitive style for geriatric rehabilitation and explore future research.

The neuroscience of cognitive-motivational styles: Sign- and goal-trackers as animal models

Cognitive-motivational styles describe predominant patterns of processing or biases that broadly influence human cognition and performance. Here we focus on the impact of cognitive-motivational styles on the response to cues predicting the availability of food or addictive drugs. An individual may preferably conduct an analysis of the motivational significance of reward cues, with the result that such cues per se are perceived as rewarding and worth approaching and working for. Alternatively, a propensity for a "cold" analysis of the behavioral utility of a reward cue may yield search behavior for food or drugs but not involve cue approach. Animal models for studying the neuronal mechanisms mediating such styles have originated from research concerning behavioral indices that predict differential vulnerability to addiction-like behaviors. Rats classified as sign- or goal-trackers (STs, GTs) were found to have opposed attentional biases (bottom-up or cue-driven attention vs. top-down or goal-driven attentional control) that are mediated primarily via relatively unresponsive versus elevated levels of cholinergic neuromodulation in the cortex. The capacity for cholinergic neuromodulation in STs is limited by a neuronal choline transporter (CHT) that fails to support increases in cholinergic activity. Moreover, in contrast to STs, the frontal dopamine system in GTs does not respond to the presence of drug cues and, thus, biases against cue-oriented behavior. The opponent cognitive-motivational styles that are indexed by sign- and goal-tracking bestow different cognitive-behavioral vulnerabilities that may contribute to the manifestation of a wide range of neuropsychiatric disorders. (PsycINFO Database Record

Sex and Ability Differences in Neural Strategy for Piaget’s Water Level Test

To explore brain activation differences between the sexes and between high and low performers on spatial perception performance, 43 college students (20 males and 23 females) performed the Piaget’s Water Level Test (WLT) while their electroencephalogram signals were recorded. A 2 (Sex) × 2 (Group: high performing vs. low performing) × 2 (Hemisphere: left vs. right) × 3 (Region: frontal, parietal, and temporal) mixed analysis of variance on beta power data showed that females more significantly activated the left hemisphere when performing the WLT, suggesting their application of an analytic strategy. In contrast, males showed a bilateral activation pattern, suggesting their use of an analytic- or holistic-combined strategy. Moreover, superior performance on the WLT was associated with enhanced temporal lobe functioning, suggesting that a superior analytic skill is key to successful performance on the WLT. There is likely modulating impact of both cognitive style and specific task properties on spatial perception strategy preferences.

A novel method linking neural connectivity to behavioral fluctuations: Behavior-regressed connectivity

BACKGROUND

During an experimental session, behavioral performance fluctuates, yet most neuroimaging analyses of functional connectivity derive a single connectivity pattern. These conventional connectivity approaches assume that since the underlying behavior of the task remains constant, the connectivity pattern is also constant.

NEW METHOD

We introduce a novel method, behavior-regressed connectivity (BRC), to directly examine behavioral fluctuations within an experimental session and capture their relationship to changes in functional connectivity. This method employs the weighted phase lag index (WPLI) applied to a window of trials with a weighting function. Using two datasets, the BRC results are compared to conventional connectivity results during two time windows: the one second before stimulus onset to identify predictive relationships, and the one second after onset to capture task-dependent relationships.

RESULTS

In both tasks, we replicate the expected results for the conventional connectivity analysis, and extend our understanding of the brain-behavior relationship using the BRC analysis, demonstrating subject-specific BRC maps that correspond to both positive and negative relationships with behavior. Comparison with Existing Method(s): Conventional connectivity analyses assume a consistent relationship between behaviors and functional connectivity, but the BRC method examines performance variability within an experimental session to understand dynamic connectivity and transient behavior.

CONCLUSION

The BRC approach examines connectivity as it covaries with behavior to complement the knowledge of underlying neural activity derived from conventional connectivity analyses. Within this framework, BRC may be implemented for the purpose of understanding performance variability both within and between participants.

Disentangling subgroups of participants recruiting shared as well as different brain regions for the execution of the verb generation task: A data-driven fMRI study

The spatial pattern of task-related brain activity in fMRI studies might be expected to change according to several variables such as handedness and age. However this spatial heterogeneity might also be due to other unmodeled sources of inter-subject variability. Since group-level results reflect patterns of task-evoked brain activity common to most of the subjects in the sample, they could conceal the presence of subgroups recruiting other brain regions beyond the common pattern. To deal with these issues, data-driven methods can be used to detect the presence of sources of inter-subject variability that might be hard to identify and therefore model a priori. Here we assess the potential of Independent Component Analysis (ICA) to detect the presence of unexpected subgroups of participants. To this end, we acquired task-evoked fMRI data on 45 healthy adults using the verb generation (VGEN) task, in which participants are visually presented with the noun of an object of everyday use, and asked to covertly generate a verb describing the corresponding action. As expected, the task elicited activity in a temporo-parieto-frontal network typically found in previous VGEN experiments. We then quantified the contribution of every subject to nine task-related spatio-temporal processes identified by ICA. A cluster analysis of this quantity yielded three subgroups of participants. Differences between the three identified subgroups were distributed in left and right prefrontal, posterior parietal and extrastriate occipital regions. These results could not be explained by differences in sex, age or handedness across the participants. Furthermore, some regions where a significant difference was found between subgroups were not present in the group-level pattern of task-related activity. We discuss the potential application of this approach for characterizing brain activity in different subgroups of patients with neuropsychiatric or neurological conditions.

Individual Differences in Dynamic Functional Brain Connectivity across the Human Lifespan

Individual differences in brain functional networks may be related to complex personal identifiers, including health, age, and ability. Dynamic network theory has been used to identify properties of dynamic brain function from fMRI data, but the majority of analyses and findings remain at the level of the group. Here, we apply hypergraph analysis, a method from dynamic network theory, to quantify individual differences in brain functional dynamics. Using a summary metric derived from the hypergraph formalism-hypergraph cardinality-we investigate individual variations in two separate, complementary data sets. The first data set ("multi-task") consists of 77 individuals engaging in four consecutive cognitive tasks. We observe that hypergraph cardinality exhibits variation across individuals while remaining consistent within individuals between tasks; moreover, the analysis of one of the memory tasks revealed a marginally significant correspondence between hypergraph cardinality and age. This finding motivated a similar analysis of the second data set ("age-memory"), in which 95 individuals, aged 18-75, performed a memory task with a similar structure to the multi-task memory task. With the increased age range in the age-memory data set, the correlation between hypergraph cardinality and age correspondence becomes significant. We discuss these results in the context of the well-known finding linking age with network structure, and suggest that hypergraph analysis should serve as a useful tool in furthering our understanding of the dynamic network structure of the brain.

Ten problems and solutions when predicting individual outcome from lesion site after stroke

In this paper, we consider solutions to ten of the challenges faced when trying to predict an individual's functional outcome after stroke on the basis of lesion site. A primary goal is to find lesion-outcome associations that are consistently observed in large populations of stroke patients because consistent associations maximise confidence in future individualised predictions. To understand and control multiple sources of inter-patient variability, we need to systematically investigate each contributing factor and how each factor depends on other factors. This requires very large cohorts of patients, who differ from one another in typical and measurable ways, including lesion site, lesion size, functional outcome and time post stroke (weeks to decades). These multivariate investigations are complex, particularly when the contributions of different variables interact with one another. Machine learning algorithms can help to identify the most influential variables and indicate dependencies between different factors. Multivariate lesion analyses are needed to understand how the effect of damage to one brain region depends on damage or preservation in other brain regions. Such data-led investigations can reveal predictive relationships between lesion site and outcome. However, to understand and improve the predictions we need explanatory models of the neural networks and degenerate pathways that support functions of interest. This will entail integrating the results of lesion analyses with those from functional imaging (fMRI, MEG), transcranial magnetic stimulation (TMS) and diffusor tensor imaging (DTI) studies of healthy participants and patients.

Different Dimensions of Cognitive Style in Typical and Atypical Cognition: New Evidence and a New Measurement Tool

We developed the Sussex Cognitive Styles Questionnaire (SCSQ) to investigate visual and verbal processing preferences and incorporate global/local processing orientations and systemising into a single, comprehensive measure. In Study 1 (N = 1542), factor analysis revealed six reliable subscales to the final 60 item questionnaire: Imagery Ability (relating to the use of visual mental imagery in everyday life); Technical/Spatial (relating to spatial mental imagery, and numerical and technical cognition); Language & Word Forms; Need for Organisation; Global Bias; and Systemising Tendency. Thus, we replicate previous findings that visual and verbal styles are separable, and that types of imagery can be subdivided. We extend previous research by showing that spatial imagery clusters with other abstract cognitive skills, and demonstrate that global/local bias can be separated from systemising. Study 2 validated the Technical/Spatial and Language & Word Forms factors by showing that they affect performance on memory tasks. In Study 3, we validated Imagery Ability, Technical/Spatial, Language & Word Forms, Global Bias, and Systemising Tendency by issuing the SCSQ to a sample of synaesthetes (N = 121) who report atypical cognitive profiles on these subscales. Thus, the SCSQ consolidates research from traditionally disparate areas of cognitive science into a comprehensive cognitive style measure, which can be used in the general population, and special populations.

Visualising inter-subject variability in fMRI using threshold-weighted overlap maps

Functional neuroimaging studies are revealing the neural systems sustaining many sensory, motor and cognitive abilities. A proper understanding of these systems requires an appreciation of the degree to which they vary across subjects. Some sources of inter-subject variability might be easy to measure (demographics, behavioural scores, or experimental factors), while others are more difficult (cognitive strategies, learning effects, and other hidden sources). Here, we introduce a simple way of visualising whole-brain consistency and variability in brain responses across subjects using threshold-weighted voxel-based overlap maps. The output quantifies the proportion of subjects activating a particular voxel or region over a wide range of statistical thresholds. The sensitivity of our approach was assessed in 30 healthy adults performing a matching task with their dominant hand. We show how overlap maps revealed many effects that were only present in a subsample of our group; we discuss how overlap maps can provide information that may be missed or misrepresented by standard group analysis, and how this information can help users to understand their data. In particular, we emphasize that functional overlap maps can be particularly useful when it comes to explaining typical (or atypical) compensatory mechanisms used by patients following brain damage.

Intrinsic medial temporal lobe connectivity relates to individual differences in episodic autobiographical remembering

People vary in how they remember the past: some recall richly detailed episodes; others more readily access the semantic features of events. The neural correlates of such trait-like differences in episodic and semantic remembering are unknown. We found that self-reported individual differences in how one recalls the past were related to predictable intrinsic connectivity patterns of the medial temporal lobe (MTL) memory system. A pattern of MTL connectivity to posterior brain regions supporting visual-perceptual processing (occipital/parietal cortices) was related to the endorsement of episodic memory-based remembering (recalling spatiotemporal event information), whereas MTL connectivity to inferior and middle prefrontal cortical regions was related to the endorsement of semantic memory-based remembering (recalling facts). These findings suggest that the tendency to engage in episodic autobiographical remembering is associated with accessing and constructing detailed images of a past event in memory, while the tendency to engage in semantic autobiographical remembering is associated with organizing and integrating higher-order conceptual information. More broadly, these findings suggest that differences in how people naturally use memory are instantiated though distinct patterns of MTL functional connectivity.