Highly Superior Autobiographical Memory (HSAM) is a rare form of enhanced memory in which individuals demonstrate an extraordinary ability to remember details of their personal lives with high levels of accuracy and vividness. Neuroimaging studies have identified brain regions - specifically, midline areas within the default network - associated with remembering events from one's past. Extending this research on the neural underpinnings of autobiographical memory, the present study utilizes graph theory analyses to compare functional brain connectivity in a cohort of HSAM (n = 12) and control participants (n = 29). We perform seed-based analysis in resting-state fMRI data to assess how specific cortical regions within the autobiographical memory network are differentially connected in HSAM individuals. Additionally, we apply a whole-brain connectivity analysis to identify differences in brain hub-network topology associated with enhanced autobiographical memory. Seed-based results show converging patterns of increased connectivity in HSAM across midline areas. Whole-brain analysis also reveals enhanced connectivity across medial prefrontal and posterior cingulate cortex in HSAM individuals. Together, these results extend prior research, highlighting cortical hubs within the default network associated with enhanced autobiographical memory.

As artificial intelligence (AI) advances in the realm of generative art, a critical question emerges: does human creativity matter? That is, do more-creative people produce more-creative AI-assisted artwork? To explore this, we conducted an online, pre-registered study in which we measured individual differences in creativity through two divergent-thinking tasks: The Alternate Uses Task and the Divergent Associations Task. Separately, participants produced creative wordsets for a hypothetical AI-art generator, which we then input into DALL-E to generate images. A group of trained raters independently assessed these images for creativity. Results revealed that both DAT performance and semantic diversity of the wordsets positively associated with the creativity of the AI-assisted images, suggesting that individuals with stronger divergent-thinking skills, and those who generated more-creative wordsets, tended to inspire more-creative AI-assisted artwork. Mediation analyses supported this conclusion by demonstrating a significant pathway between individual creative ability and AI-art creativity, mediated by semantic diversity. However, while our models yielded significant results, the effect sizes were modest, suggesting that the relationship between individual creative ability and AI-assisted creative outputs is relatively small. Taken together, these results suggest that while individual creativity appears to contribute to the quality of AI-assisted artwork, its influence may be relatively limited.

The direct access of olfactory afferents to memory-related cortical systems has inspired theories about the role of the olfactory pathways in the development of cortical neurodegeneration in Alzheimer's disease (AD). In this study, we used baseline olfactory identification measures with longitudinal flortaucipir and PiB PET, diffusion MRI of 89 cognitively normal older adults (73.82 ± 8.44 years; 56% females), and a transcriptomic data atlas to investigate the spatiotemporal spreading and genetic vulnerabilities of AD-related pathology aggregates in the olfactory system. We find that odor identification deficits are predominantly associated with tau accumulation in key areas of the olfactory pathway, with a particularly strong predictive power for longitudinal tau progression. We observe that tau spreads from the medial temporal lobe structures toward the olfactory system, not the reverse. Moreover, we observed a genetic background of odor perception-related genes that might confer vulnerability to tau accumulation along the olfactory system.

As artificial intelligence (AI) continues to evolve, particularly in the context of generative art, a critical question emerges about the future role of human creativity: In the age of generative AI, does individual creative ability still matter? Here, we explored this question via an online, pre-registered study involving 375 participants who completed gold-standard divergent-thinking tasks and generated semantic wordsets for AI-art creation using an AI-art generator. We generated the resultant images from these participant-produced wordsets through DALL-E, and a group of trained raters independently assessed the images for general creativity. Findings revealed widespread positive correlations among the creativity tasks. Specifically, the semantic diversity of wordsets and performance on the gold-standard creativity tasks served as significant positive predictors for the creativity of the AI-generated images, indicating that individuals possessing greater divergent-thinking capabilities, and who generated more-creative word prompts for an art generator, produced more-creative AI-generated artwork. These results suggest that, despite the democratizing effect of AI-art generation, human creativity remains an important component in directing AI-produced creative outcomes like visual art. The implications of these findings are discussed in the context of creative industries and the science of creativity.

How do we assess the quality of an idea? Current theories suggest that episodic memory contributes to creative ideation, implicating memory retrieval and mental simulation in the generation of creative ideas; however, the role of memory in creative evaluation has not been systematically examined. Across two independent online samples (Study 1 n = 50, Study 2 n = 626), we explore how episodic retrieval supports the evaluation of two distinct aspects of creativity: novelty and effectiveness. In both studies, participants were presented with a series of creative ideas - responses on the alternate uses task - and were asked to independently rate them for novelty/effectiveness. Following each rating, participants were prompted to reflect on their process and type a brief description about how they made their evaluation. We apply computational linguistic analysis to quantify the prevalence of episodic/perceptual details (sights, sounds, etc.) in each evaluation, along with past-focused and future-focused words. Consistent with prior work, we observe a negative correlation (r=-.39) between novelty and effectiveness ratings. Ordinal logistic regression models indicate that perceptual detail and temporal orientation of evaluations are predictive of novelty and effectiveness ratings. We show that people refer more to the past when evaluating familiar, effective ideas; conversely, people refer more to the future when evaluating highly novel, less effective ideas. Overall, these results are consistent with the hypothesis that episodic retrieval supports the evaluation of creative ideas.

Recent developments in computerized scoring via semantic distance have provided automated assessments of verbal creativity. Here, we extend past work, applying computational linguistic approaches to characterize salient features of creative text. We hypothesize that, in addition to semantic diversity, the degree to which a story includes perceptual details, thus transporting the reader to another time and place, would be predictive of creativity. Additionally, we explore the use of generative language models to supplement human data collection and examine the extent to which machine-generated stories can mimic human creativity. We collect 600 short stories from human participants and GPT-3, subsequently randomized and assessed on their creative quality. Results indicate that the presence of perceptual details, in conjunction with semantic diversity, is highly predictive of creativity. These results were replicated in an independent sample of stories (n = 120) generated by GPT-4. We do not observe a significant difference between human and AI-generated stories in terms of creativity ratings, and we also observe positive correlations between human and AI assessments of creativity. Implications and future directions are discussed.

Objectives: How does creative expression change across the life span? Although creativity is generally preserved well into adulthood, certain cognitive functions, such as episodic detail and ideational fluency, have been shown to decline with age. The present study employs computational linguistic analyses to investigate the salient features of creative writing in older adults. Methods: We collected short stories from a sample of 50 older adults (age 65 <=) which were subsequently rated for creativity by an independent set of participants. Mixed-effects linear regression models were used to describe semantic diversity and perceptual details as predictors of creativity. Semantic diversity reflects the extent to which a narrative connects divergent ideas and is closely associated with creativity. Perceptual details, characterized by sensorial descriptions, have been previously associated with creative writing and may serve to transport readers to alternative times and places. Additionally, we compare these measures to a previously collected sample of stories from younger adults. Results: Results indicate that the presence of perceptual details and semantic diversity were significant positive predictors of creativity (p < .05). Moreover, we find that stories written by older adults contain fewer perceptual details compared with stories written by younger adults. Discussion: These results advance our understanding of age-related changes in creativity and highlight the potential role of episodic simulation in writing creative short stories.

The neuroscience of creativity seeks to disentangle the complex brain processes that underpin the generation of novel ideas. Neuroimaging studies of functional connectivity, particularly functional magnetic resonance imaging (fMRI), have revealed individual differences in brain network organization associated with creative ability; however, much of the extant research is limited to laboratory-based divergent thinking measures. To overcome these limitations, we compare functional brain connectivity in a cohort of creative experts (n = 27) and controls (n = 26) and examine links with creative behavior. First, we replicate prior findings showing reduced connectivity in visual cortex related to higher creative performance. Second, we examine whether this result is driven by integrated or segregated connectivity. Third, we examine associations between functional connectivity and vivid distal simulation separately in creative experts and controls. In accordance with past work, our results show reduced connectivity to the primary visual cortex in creative experts at rest. Additionally, we observe a negative association between distal simulation vividness and connectivity to the lateral visual cortex in creative experts. Taken together, these results highlight connectivity profiles of highly creative people and suggest that creative thinking may be related to, though not fully redundant with, the ability to vividly imagine the future.

Creative ideas are thought to result from flexible recombination of concepts from memory. A growing number of behavioural and neuroscientific studies provide evidence of a link between episodic memory and divergent thinking; however, little is known about the potential contributions of autobiographical memory to creative ideation. To provide a novel perspective on this issue, we assessed measures of divergent and convergent creative thinking in a cohort (n = 14) of rare individuals showing Highly Superior Autobiographical Memory (HSAM). The HSAM cohort completed memory tasks in addition to a battery of creativity measures, including the Alternative Uses Task, Consequences Task and Remote Associates Task. We performed statistical analyses to establish whether there were any significant differences between HSAM and controls (n = 28) across these measures. Although HSAM participants were superior in the recall of autobiographical events compared to controls, we observed no overall difference between the groups in relation to the creativity measures. These findings suggest that the constructive episodic processes relevant to creative thinking are not enhanced in individuals with HSAM, perhaps because they are compulsively and narrowly focused on consolidation and retrieval of autobiographical events.

How does imagining future events-whether positive or negative-influence our choices in the present? Prior work has shown the simulation of hypothetical future events, dubbed episodic future thinking, can alter the propensity to engage in delay discounting (the tendency to devalue future rewards) and does so in a valence-specific manner. Some research shows that positive episodic future thinking reduces delay discounting, whereas negative future thinking augments it. However, more recent research indicates that both positive and negative episodic future thinking reduce delay discounting, suggesting an effect of episodic future thinking that is independent of valence. In this study, we sought to replicate and extend these latter findings. Here, participants (N = 604; N = 572 after exclusions) completed an online study. In the baseline task, participants completed a delay discounting task. In the experimental task, they engaged in episodic future thinking before completing a second delay discounting task. Participants were randomly assigned to engage in either positive, neutral, or negative episodic future thinking. In accordance with Bulley et al., we found that episodic future thinking, regardless of valence, reduced delay discounting. Although episodic future thinking shifted decision-making in all conditions, the effect was stronger when participants engaged in positive episodic future thinking, even after accounting for personal relevance and vividness of imagined events. These findings suggest that episodic future thinking may promote future-oriented choices by contextualising the future, and this effect is further strengthened when the future is tied to positive emotion.

A key hallmark of Alzheimer's disease (AD) pathology is the intracellular accumulation of tau protein in the form of neurofibrillary tangles across large-scale networks of the human brain cortex. Currently, it is still unclear how tau accumulates within specific cortical systems and whether in situ genetic traits play a role in this circuit-based propagation progression. In this study, using two independent cohorts of cognitively normal older participants, we reveal the brain network foundation of tau spreading and its association with using high-resolution transcriptomic genetic data. We observed that specific connectomic and genetic gradients exist along the tau spreading network. In particular, we identified 577 genes whose expression is associated with the spatial spreading of tau. Within this set of genes, APOE and glutamatergic synaptic genes, such as SLC1A2, play a central role. Thus, our study characterizes neurogenetic topological vulnerabilities in distinctive brain circuits of tau spreading and suggests that drug development strategies targeting the gradient expression of this set of genes should be explored to help reduce or prevent pathological tau accumulation.

Small vessel disease (SVD) is a disorder that causes vascular lesions in the entire parenchyma of the human brain. At present, it is not well understood how primary and secondary damage interact to give rise to the complex scenario of white matter (WM) and grey matter (GM) lesions. Using novel cross-sectional and longitudinal connectomic approaches, we unveil the bidirectional nature of GM and WM changes, that is, primary cortical neurodegeneration that leads to secondary alterations in vascular border zones, and WM lesions that lead to secondary neurodegeneration in cortical projecting areas. We found this GM-WM interaction to be essential for executive cognitive performance. Moreover, we also observed that the interlocked degeneration of GM and WM over time associates with prototypical expression levels of genes potentially linked to SVD. Among these connectomic-genetic intersections, we found that the Androgen Receptor (AR) gene, is a particularly central candidate gene that might confer key vulnerability for brain lesion development in SVD. In conclusion, this study advances in the understanding of the bidirectional relationships between GM and WM lesions, primary and secondary vascular neurodegeneration, and sheds light on the genetic signatures of SVD.

Studies suggest that internally oriented cognitive processes are central to creativity. Here, we distinguish between intentional and unintentional forms of mind wandering and explore their behavioral and neural correlates. We used a sample of 155 healthy adults from the mind-brain-body dataset, all of whom completed resting-state fMRI scans and trait-level measures of mind wandering. We analyzed intentional and unintentional mind wandering tendencies using self-report measures. Next, we explored the relationship between mind wandering tendencies and creativity, as measured by a divergent thinking task. Finally, we describe patterns of resting-state network connectivity associated with mind wandering, using graph theory analysis. At the behavioral level, results showed a significant positive association between creativity and both intentional and unintentional mind wandering. Neuroimaging analysis revealed higher weighted degree connectivity associated with both forms of mind wandering, implicating core regions of the default network and the left temporal pole. We observed topological connectivity differences within the default network: intentional mind wandering was associated with degree connectivity in posterior regions, whereas unintentional mind wandering showed greater involvement of prefrontal areas. Overall, the findings highlight patterns of resting-state network connectivity associated with intentional and unintentional mind wandering, and provide novel evidence of a link between mind wandering and creativity.

Amyloid‐beta (Aβ) plaques and tau neurofibrillary tangles are pathological hallmarks of Alzheimer's disease (AD); their contribution to neurodegeneration and clinical manifestations are critical in understanding preclinical AD. At present, the mechanisms related to Aβ and tau pathogenesis leading to cognitive decline in older adults remain largely unknown. Here, we examined graph theory‐based positron emission tomography (PET) analytical approaches, within and between tau and Aβ PET modalities, and tested the effects on cognitive changes in cognitively normal older adults (CN). Particularly, we focused on the network interdigitations of Aβ and tau deposits, along with cognitive test scores in CN at both baseline and 2‐year follow‐up (FU). We found highly significant Aβ‐tau network integrations in AD vulnerable areas, as well as significant associations between those Aβ‐tau interdigitations and general cognitive impairment in CN at baseline and FU. Our findings suggest a distinctive contribution of interlinking network relationships between Aβ and tau deposits in heteromodal areas of the human brain. They support a network‐based interaction between Aβ and tau accumulations as a key factor for cognitive deterioration in CN prior to dementia.

Recent studies of creative cognition have revealed interactions between functional brain networks involved in the generation of novel ideas; however, the neural basis of creativity is highly complex and presents a great challenge in the field of cognitive neuroscience, partly because of ambiguity around how to assess creativity. We applied a novel computational method of verbal creativity assessment-semantic distance-and performed weighted degree functional connectivity analyses to explore how individual differences in assembly of resting-state networks are associated with this objective creativity assessment. To measure creative performance, a sample of healthy adults (n = 175) completed a battery of divergent thinking (DT) tasks, in which they were asked to think of unusual uses for everyday objects. Computational semantic models were applied to calculate the semantic distance between objects and responses to obtain an objective measure of DT performance. All participants underwent resting-state imaging, from which we computed voxel-wise connectivity matrices between all gray matter voxels. A linear regression analysis was applied between DT and weighted degree of the connectivity matrices. Our analysis revealed a significant connectivity decrease in the visual-temporal and parietal regions, in relation to increased levels of DT. Link-level analyses showed higher local connectivity within visual regions was associated with lower DT, whereas projections from the precuneus to the right inferior occipital and temporal cortex were positively associated with DT. Our results demonstrate differential patterns of resting-state connectivity associated with individual creative thinking ability, extending past work using a new application to automatically assess creativity via semantic distance.

The relationship between human brain connectomics and genetic evolutionary traits remains elusive due to the inherent challenges in combining complex associations within cerebral tissue. In this study, insights are provided about the relationship between connectomics, gene expression and divergent evolutionary pathways from non-human primates to humans. Using in vivo human brain resting-state data, we detected two co-existing idiosyncratic functional systems: the segregation network, in charge of module specialization, and the integration network, responsible for information flow. Their topology was approximated to whole-brain genetic expression (Allen Human Brain Atlas) and the co-localization patterns yielded that neuron communication functionalities—linked to Neuron Projection —were overrepresented cell traits. Homologue-orthologue comparisons using dN/dS-ratios bridged the gap between neurogenetic outcomes and biological data, summarizing the known evolutionary divergent pathways within the Homo Sapiens lineage. Evidence suggests that a crosstalk between functional specialization and information flow reflects putative biological qualities of brain architecture, such as neurite cellular functions like axonal or dendrite processes, hypothesized to have been selectively conserved in the species through positive selection. These findings expand our understanding of human brain function and unveil aspects of our cognitive trajectory in relation to our simian ancestors previously left unexplored.

The ability to produce novel ideas is central to societal progress and innovation; however, little is known about the biological basis of creativity. Here, we investigate the organization of brain networks that support creativity by combining functional neuroimaging data with gene expression information. Given the multifaceted nature of creative thinking, we hypothesized that distributed connectivity would not only be related to individual differences in creative ability, but also delineate the cortical distributions of genes involved in synaptic plasticity. We defined neuroimaging phenotypes using a graph theory approach that detects local and distributed network circuits, then characterized the spatial associations between functional connectivity and cortical gene expression distributions. Our findings reveal strong spatial correlations between connectivity maps and sets of genes devoted to synaptic assembly and signaling. This connectomic-transcriptome approach thus identifies gene expression profiles associated with high creative ability, linking cognitive flexibility to neural plasticity in the human brain.

Fractal dimension (FD) has become a very useful tool in neuroscience with a wide range of applications in characterizing several neurodegenerative diseases. The most commonly used method for computing the FD of brain tissues is box-counting. This technique performs very well on 2D images and 3D volumes; however, it presents several drawbacks when processing cortical surfaces in 3D. In this study, we present a MATLAB program for computing the FD of 3D surfaces based on spherical harmonics. We developed a novel MATLAB program, called UJA-SHFD, based on a spherical harmonics FD algorithm which overcomes the limitations of the classical box-counting algorithm when processing 3D surfaces. Moreover, spherical-harmonic-based FD (SHFD) enables the processing of both global (providing a single FD value for the entire surface) and local level assessments in each cortical surface vertex. UJA-SHFD has been specifically designed and tested for processing cortical surfaces obtained from the FreeSurfer software suite. Nevertheless, the program can also process any kind of surface in the Wavefront OBJ format. UJA-SHFD can be used both through a graphical user interface and at the command line. The present study demonstrates the usefulness of UJA-SHFD through its application to a neuroimaging study looking at the progression of brain atrophy in Alzheimer's disease. UJA-SHFD is a novel MATLAB program with the goal of developing neuroimaging analyses of FD computation for the investigation of brain morphological changes in neurodegenerative and neuropsychiatric disorders. The MATLAB source code of UJA-SHFD is freely available. Program summary Program title: UJA-SHFD CPC Library link to program files: http://doi.org/10.17632/wzzv2wc7fd.1 Licensing provisions: GNU General Public License version 3 Programming language: MATLAB, C++ Nature of problem: To compute the fractal dimension of 3D surfaces avoiding the common problems of software based on the box-counting algorithm. Solution method: Spherical harmonics are used to obtain a set of reconstructed surfaces approximating the shape of the original surface. The areas of the reconstructed surfaces are used to obtain the global fractal dimension of the original surface. The areas of the triangles associated to each vertex of the reconstructed surfaces are used to obtain local fractal dimension maps. (C) 2020 Elsevier B.V. All rights reserved.