On the relationship between the “default mode network” and the “social brain”

The default mode network (DMN) of the brain consists of areas that are typically more active during rest than during active task performance. Recently however, this network has been shown to be activated by certain types of tasks. Social cognition, particularly higher-order tasks such as attributing mental states to others, has been suggested to activate a network of areas at least partly overlapping with the DMN. Here, we explore this claim, drawing on evidence from meta-analyses of functional MRI data and recent studies investigating the structural and functional connectivity of the social brain. In addition, we discuss recent evidence for the existence of a DMN in non-human primates. We conclude by discussing some of the implications of these observations

Eight-month-old infants meta-learn by downweighting irrelevant evidence

Infants learn to navigate the complexity of the physical and social world at an outstanding pace, but how they accomplish this learning is still largely unknown. Recent advances in human and artificial intelligence research propose that a key feature to achieving quick and efficient learning is meta-learning, the ability to make use of prior experiences to learn how to learn better in the future. Here we show that 8-month-old infants successfully engage in meta-learning within very short timespans after being exposed to a new learning environment. We developed a Bayesian model that captures how infants attribute informativity to incoming events, and how this process is optimized by the meta-parameters of their hierarchical models over the task structure. We fitted the model with infants’ gaze behavior during a learning task. Our results reveal how infants actively use past experiences to generate new inductive biases that allow future learning to proceed faster

Toddlers strategically adapt their information search

Adaptive information seeking is essential for humans to effectively navigate complex and dynamic environments. Here, we developed a gaze-contingent eye-tracking paradigm to examine the early emergence of adaptive information-seeking. Toddlers (N = 60, 18-36 months) and adults (N = 42) either learnt that an animal was equally likely to be found in any of four available locations, or that it was most likely to be found in one particular location. Afterwards, they were given control of a torchlight, which they could move with their eyes to explore the otherwise pitch-black task environment. Eye-movement data and Markov models show that, from 24 months of age, toddlers become more exploratory than adults, and start adapting their exploratory strategies to the information structure of the task. These results show that toddlers’ search strategies are more sophisticated than previously thought, and identify the unique features that distinguish their information search from adults’

Comparing mouse and human cingulate cortex organization using functional connectivity

The subdivisions of the extended cingulate cortex of the human brain are implicated in a number of high-level behaviors and affected by a range of neuropsychiatric disorders. Its anatomy, function, and response to therapeutics are often studied using non-human animals, including the mouse. However, the similarity of human and mouse frontal cortex, including cingulate areas, is still not fully understood. Some accounts emphasize resemblances between mouse cingulate cortex and human cingulate cortex while others emphasize similarities with human granular prefrontal cortex. We use comparative neuroimaging to study the connectivity of the cingulate cortex in the mouse and human, allowing comparisons between mouse ‘gold standard’ tracer and imaging data, and, in addition, comparison between the mouse and the human using comparable imaging data. We find overall similarities in organization of the cingulate between species, including anterior and midcingulate areas and a retrosplenial area. However, human cingulate contains subareas with a more fine-grained organization than is apparent in the mouse and it has connections to prefrontal areas not present in the mouse. Results such as these help formally address between-species brain organization and aim to improve the translation from preclinical to human results

Autistic traits foster effective curiosity-driven exploration

Curiosity-driven exploration involves actively engaging with the environment to learn from it. Here, we hypothesize that the cognitive mechanisms underlying exploratory behavior may differ across individuals depending on personal characteristics such as autistic traits. In turn, this variability might influence successful exploration. To investigate this, we collected self- and other-reports of autistic traits from university students, and tested them in an exploration task in which participants could learn the hiding patterns of multiple characters. Participants’ prediction errors and learning progress (i.e., the decrease in prediction error) on the task were tracked with a hierarchical delta-rule model. Crucially, participants could freely decide when to disengage from a character and what to explore next. We examined whether autistic traits modulated the relation of prediction errors and learning progress with exploration. We found that participants with lower scores on other-reports of insistence-on-sameness and general autistic traits were less persistent, primarily relying on learning progress during the initial stages of exploration. Conversely, participants with higher scores were more persistent and relied on learning progress in later phases of exploration, resulting in better performance in the task. This research advances our understanding of the interplay between autistic traits and exploration drives, emphasizing the importance of individual traits in learning processes and highlighting the need for personalized learning approaches

Cross-species neuroscience: closing the explanatory gap

Neuroscience has seen substantial development in non-invasive methods available for investigating the living human brain. However, these tools are limited to coarse macroscopic measures of neural activity that aggregate the diverse responses of thousands of cells. To access neural activity at the cellular and circuit level, researchers instead rely on invasive recordings in animals. Recent advances in invasive methods now permit large-scale recording and circuit level manipulations with exquisite spatiotemporal precision. Yet, there has been limited progress in relating these microcircuit measures to complex cognition and behaviour observed in humans. Contemporary neuroscience thus faces an explanatory gap between macroscopic descriptions of the human brain and microscopic descriptions in animal models. To close the explanatory gap, we propose adopting a cross-species approach. Despite dramatic differences in the size of mammalian brains this approach is broadly justified by preserved homology. Here, we outline a three-armed approach for effective cross-species investigation that highlights the need to translate different measures of neural activity into a common space. We discuss how a cross-species approach has the potential to transform basic neuroscience while also benefiting neuropsychiatric drug development where clinical translation has, to date, seen minimal success

Hippocampal connectivity patterns echo macroscale cortical evolution in the primate brain

While the hippocampus is key for human cognitive abilities, it is also a phylogenetically old cortex and paradoxically considered evolutionarily preserved. Here, we introduce a comparative framework to quantify preservation and reconfiguration of hippocampal organisation in primate evolution, by analysing the hippocampus as an unfolded cortical surface that is geometrically matched across species. Our findings revealed an overall conservation of hippocampal macro- and micro-structure, which shows anterior-posterior and, perpendicularly, subfield-related organisational axes in both humans and macaques. However, while functional organisation in both species followed an anterior-posterior axis, we observed a marked reconfiguration in the latter across species, which mirrors a rudimentary integration of the default-mode-network in non-human primates. Here we show that microstructurally preserved regions like the hippocampus may still undergo functional reconfiguration in primate evolution, due to their embedding within heteromodal association networks

An open resource combining multi-contrast MRI and microscopy in the macaque brain

Understanding brain structure and function often requires combining data across different modalities and scales to link microscale cellular structures to macroscale features of whole brain organisation. Here we introduce the BigMac dataset, a resource combining in vivo MRI, extensive postmortem MRI and multi-contrast microscopy for multimodal characterisation of a single whole macaque brain. The data spans modalities (MRI and microscopy), tissue states (in vivo and postmortem), and four orders of spatial magnitude, from microscopy images with micrometre or sub-micrometre resolution, to MRI signals on the order of millimetres. Crucially, the MRI and microscopy images are carefully co-registered together to facilitate quantitative multimodal analyses. Here we detail the acquisition, curation, and first release of the data, that together make BigMac a unique, openly-disseminated resource available to researchers worldwide. Further, we demonstrate example analyses and opportunities afforded by the data, including improvement of connectivity estimates from ultra-high angular resolution diffusion MRI, neuroanatomical insight provided by polarised light imaging and myelin-stained histology, and the joint analysis of MRI and microscopy data for reconstruction of the microscopy-inspired connectome. All data and code are made openly available

Concurrent mapping of brain ontogeny and phylogeny within a common connectivity space

Developmental and evolutionary effects on brain organisation are complex, yet linked, as evidenced by the striking correspondence in cortical expansion changes. However, it is still not possible to study concurrently the ontogeny and phylogeny of cortical areal connections, which is arguably more relevant to brain function than allometric changes. Here, we propose a novel framework that allows the integration of connectivity maps from humans (adults and neonates) and non-human primates (macaques) onto a common space. We use white matter bundles to anchor the definition of the common space and employ the uniqueness of the areal connection patterns to these bundles to probe areal specialisation. This enables us to quantitatively study divergences and similarities in cortical connectivity over both evolutionary and developmental scales. It further allows us to map brain maturation trajectories, including the effect of premature birth, and to translate cortical atlases between diverse brains