On the nature and use of models in network neuroscience.

Network theory provides an intuitively appealing framework for studying relationships among interconnected brain mechanisms and their relevance to behaviour. As the space of its applications grows, so does the diversity of meanings of the term network model. This diversity can cause confusion, complicate efforts to assess model validity and efficacy, and hamper interdisciplinary collaboration. In this Review, we examine the field of network neuroscience, focusing on organizing principles that can help overcome these challenges. First, we describe the fundamental goals in constructing network models. Second, we review the most common forms of network models, which can be described parsimoniously along the following three primary dimensions: from data representations to first-principles theory; from biophysical realism to functional phenomenology; and from elementary descriptions to coarse-grained approximations. Third, we draw on biology, philosophy and other disciplines to establish validation principles for these models. We close with a discussion of opportunities to bridge model types and point to exciting frontiers for future pursuits.

Within-person variability in curiosity during daily life and associations with well-being.

OBJECTIVE: Curiosity promotes engagement in novel situations and the accruement of resources that promote well-being. An open question is the extent to which curiosity lability, the degree to which curiosity fluctuates over short timescales, impacts well-being. METHOD: We use data from a 21-day daily diary as well as trait measures in 167 participants (mean age = 25.37 years, SD = 7.34) to test (a) the importance of curiosity lability for depression, flourishing, and life satisfaction, (b) day-to-day associations among curiosity and happiness, depressed mood, anxiety, and physical activity, and (c) the role of day's mood as a mediator between physical activity and curiosity. RESULTS: We observe positive associations among curiosity lability and depression, as well as negative associations among curiosity lability and both life satisfaction and flourishing. Curiosity is higher on days of greater happiness and physical activity, and lower on days of greater depressed mood. We find evidence consistent with day's depressed mood and happiness being mediators between physical activity and curiosity. CONCLUSIONS: Greater consistency in curiosity is associated with well-being. We identify several potential sources of augmentation and blunting of curiosity in daily life and provide support for purported mechanisms linking physical activity to curiosity via mood.

Expanding Diversity, Equity, and Inclusion to Disability: Opportunities for Biological Psychiatry.

Given its subject matter, biological psychiatry is uniquely poised to lead STEM (science, technology, engineering, and mathematics) DEI (diversity, equity, and inclusion) initiatives related to disability. Drawing on literatures in science, philosophy, psychiatry, and disability studies, we outline how that leadership might be undertaken. We first review existing opportunities for the advancement of DEI in biological psychiatry around axes of gender and race. We then explore the expansion of biological psychiatry's DEI efforts to disability, especially along the lines of representation and access, community accountability, first-person testimony, and revised theoretical frameworks for pathology. We close with concrete recommendations for scholarship and practice going forward. By tackling head-on the challenge of disability inclusion, biological psychiatry has the opportunity to be a force of transformation in the biological sciences and beyond.

Citation bias, diversity, and ethics.

How often a researcher is cited usually plays a decisive role in that person's career advancement, because academic institutions often use citation metrics, either explicitly or implicitly, to estimate research impact and productivity. Research has shown, however, that citation patterns and practices are affected by various biases, including the prestige of the authors being cited and their gender, race, and nationality, whether self-attested or perceived. Some commentators have proposed that researchers can address biases related to social identity or position by including a Citation Diversity Statement in a manuscript submitted for publication. A Citation Diversity Statement is a paragraph placed before the reference section of a manuscript in which the authors address the diversity and equitability of their references in terms of gender, race, ethnicity, or other factors and affirm a commitment to promoting equity and diversity in sources and references. The present commentary considers arguments in favor of Citation Diversity Statements, and some practical and ethical issues that these statements raise.

Hunters, busybodies and the knowledge network building associated with deprivation curiosity.

The open-ended and internally driven nature of curiosity makes characterizing the information seeking that accompanies it a daunting endeavour. We use a historico-philosophical taxonomy of information seeking coupled with a knowledge network building framework to capture styles of information-seeking in 149 participants as they explore Wikipedia for over 5 hours spanning 21 days. We create knowledge networks in which nodes represent distinct concepts and edges represent the similarity between concepts. We quantify the tightness of knowledge networks using graph theoretical indices and use a generative model of network growth to explore mechanisms underlying information-seeking. Deprivation curiosity (the tendency to seek information that eliminates knowledge gaps) is associated with the creation of relatively tight networks and a relatively greater tendency to return to previously visited concepts. With this framework in hand, future research can readily quantify the information seeking associated with curiosity.

Network architectures supporting learnability.

Human learners acquire complex interconnected networks of relational knowledge. The capacity for such learning naturally depends on two factors: the architecture (or informational structure) of the knowledge network itself and the architecture of the computational unit-the brain-that encodes and processes the information. That is, learning is reliant on integrated network architectures at two levels: the epistemic and the computational, or the conceptual and the neural. Motivated by a wish to understand conventional human knowledge, here, we discuss emerging work assessing network constraints on the learnability of relational knowledge, and theories from statistical physics that instantiate the principles of thermodynamics and information theory to offer an explanatory model for such constraints. We then highlight similarities between those constraints on the learnability of relational networks, at one level, and the physical constraints on the development of interconnected patterns in neural systems, at another level, both leading to hierarchically modular networks. To support our discussion of these similarities, we employ an operational distinction between the modeller (e.g. the human brain), the model (e.g. a single human's knowledge) and the modelled (e.g. the information present in our experiences). We then turn to a philosophical discussion of whether and how we can extend our observations to a claim regarding explanation and mechanism for knowledge acquisition. What relation between hierarchical networks, at the conceptual and neural levels, best facilitate learning? Are the architectures of optimally learnable networks a topological reflection of the architectures of comparably developed neural networks? Finally, we contribute to a unified approach to hierarchies and levels in biological networks by proposing several epistemological norms for analysing the computational brain and social epistemes, and for developing pedagogical principles conducive to curious thought. This article is part of the theme issue 'Unifying the essential concepts of biological networks: biological insights and philosophical foundations'.

(In)citing Action to Realize an Equitable Future.

Reference lists of neuroscience articles show marked gender imbalances. To mitigate this disparity, we discuss relevant ethical considerations and offer practical recommendations to scientists of all ages. We envision an equitable future by all scientists for all scientists.

The Citation Diversity Statement: A Practice of Transparency, A Way of Life.

Appending a Citation Diversity Statement to a paper is a simple and effective way to increase awareness about citation bias and help mitigate it. Here, we describe why reducing citation bias is important and how to include a Citation Diversity Statement in your next publication.

The growth and form of knowledge networks by kinesthetic curiosity.

Throughout life, we might seek a calling, companions, skills, entertainment, truth, self-knowledge, beauty, and edification. The practice of curiosity can be viewed as an extended and open-ended search for valuable information with hidden identity and location in a complex space of interconnected information. Despite its importance, curiosity has been challenging to computationally model because the practice of curiosity often flourishes without specific goals, external reward, or immediate feedback. Here, we show how network science, statistical physics, and philosophy can be integrated into an approach that coheres with and expands the psychological taxonomies of specific-diversive and perceptual-epistemic curiosity. Using this interdisciplinary approach, we distill functional modes of curious information seeking as searching movements in information space. The kinesthetic model of curiosity offers a vibrant counterpart to the deliberative predictions of model-based reinforcement learning. In doing so, this model unearths new computational opportunities for identifying what makes curiosity curious.

The extent and drivers of gender imbalance in neuroscience reference lists.

Similarly to many scientific disciplines, neuroscience has increasingly attempted to confront pervasive gender imbalances. Although publishing and conference participation are often highlighted, recent research has called attention to the prevalence of gender imbalance in citations. Because of the downstream effects of citations on visibility and career advancement, understanding the role of gender in citation practices is vital for addressing scientific inequity. Here, we investigate whether gendered patterns are present in neuroscience citations. Using data from five top neuroscience journals, we find that reference lists tend to include more papers with men as first and last author than would be expected if gender were unrelated to referencing. Importantly, we show that this imbalance is driven largely by the citation practices of men and is increasing over time as the field diversifies. We assess and discuss possible mechanisms and consider how researchers might approach these issues in their own work.

Seizing an opportunity.

As the techniques available to neuroscientists to probe the inner workings of the brain become more powerful, the volume of data generated increases exponentially and the tools used to analyze these data become ever more sophisticated. Alongside this feverish press into the future comes a growing interest in the use of new data technologies to study old literary and philosophical texts. And as researchers develop new methods to unearth patterns hidden within complex data, it is natural to think of these old texts as simply more data reflecting the intricacies of the human mind, waiting to succumb to the powerful, objective, and reliable perception of machines. Here we argue that historical texts are more than prone booty to be exploited: rather, they offer researchers in neuroscience, philosophy, and literature the opportunity to work together, to learn from and enrich each other's methodologies. Using the study of human curiosity as an illustration, we describe our vision for a collaborative approach to exploring the mysteries of the mind and human behavior.

On Curiosity: A Fundamental Aspect of Personality, a Practice of Network Growth.

Human personality is reflected in patterns-or networks-of behavior, either in thought or action. Curiosity is an oft-treasured component of one's personality, commonly associated with information-seeking proclivities with distinct neurophysiological correlates. The markers of curiosity can differ substantially across people, suggesting the possibility that personality also determines the architectural style of one's curiosity. Yet progress in defining those styles, and marking their neurophysiological basis, has been hampered by fairly fundamental difficulties in defining curiosity itself. Here, we offer and exercise a definition of the practice of curiosity as knowledge network building, one particular pattern of thought behavior. To unpack this definition and motivate its utility, we begin with a short primer on network science and describe how the mathematical object of a network can be used to map items and relations that are characteristic of bodies of knowledge. Next, we turn to a discussion of how networks grow, how their growth can be modeled, and how the practice of curiosity can be formalized as a process of network growth. We pay particular attention to how individuals may differ in how they build their knowledge networks, and discuss how the sort, manner, and action of building can be modulated by experience. We discuss how this definition of the practice of curiosity motivates new experiments and theory development at the interdisciplinary intersection of network science, personality neuroscience, education, and curiosity studies. We close with a note on the potential of network science to inform studies of other domains of personality, and the patterns of thought- or action-behavior characteristic thereof.