Perceptual events derive their significance to an animal from their meaning about the world, that is from the information they carry about their causes. The brain should thus be able to efficiently infer the causes underlying our sensory events. Here we use multisensory cue combination to study causal inference in perception. We formulate an ideal-observer model that infers whether two sensory cues originate from the same location and that also estimates their location(s). This model accurately predicts the nonlinear integration of cues by human subjects in two auditory-visual localization tasks. The results show that indeed humans can efficiently infer the causal structure as well as the location of causes. By combining insights from the study of causal inference with the ideal-observer approach to sensory cue combination, we show that the capacity to infer causal structure is not limited to conscious, high-level cognition; it is also performed continually and effortlessly in perception. <<<

The role of the heart in the experience of time has been long theorized but empirical evidence is scarce. Here, we examined the interaction between fine-grained cardiac dynamics and the momentary experience of subsecond intervals. Participants performed a temporal bisection task for brief tones (80-188 ms) synchronized with the heart. We developed a cardiac Drift-Diffusion Model (cDDM) that embedded contemporaneous heart rate dynamics into the temporal decision model. Results revealed the existence of temporal wrinkles-dilation or contraction of short intervals-in synchrony with cardiac dynamics. A lower prestimulus heart rate was associated with an initial bias in encoding the millisecond-level stimulus duration as longer, consistent with facilitation of sensory intake. Concurrently, a higher prestimulus heart rate aided more consistent and faster temporal judgments through more efficient evidence accumulation. Additionally, a higher speed of poststimulus cardiac deceleration, a bodily marker of attention, was associated with a greater accumulation of sensory temporal evidence in the cDDM. These findings suggest a unique role of cardiac dynamics in the momentary experience of time. Our cDDM framework opens a new methodological avenue for investigating the role of the heart in time perception and perceptual judgment. <<<

The medial (MEC) and lateral entorhinal cortex (LEC), widely studied in rodents, are well defined and characterized. In humans, however, the exact locations of their homologues remain uncertain. Previous functional magnetic resonance imaging (fMRI) studies have subdivided the human EC into posteromedial (pmEC) and anterolateral (alEC) parts, but uncertainty remains about the choice of imaging modality and seed regions, in particular in light of a substantial revision of the classical model of EC connectivity based on novel insights from rodent anatomy. Here, we used structural, not functional imaging, namely diffusion tensor imaging (DTI) and probabilistic tractography to segment the human EC based on differential connectivity to other brain regions known to project selectively to MEC or LEC. We defined MEC as more strongly connected with presubiculum and retrosplenial cortex (RSC), and LEC as more strongly connected with distal CA1 and proximal subiculum (dCA1pSub) and lateral orbitofrontal cortex (OFC). Although our DTI segmentation had a larger medial-lateral component than in the previous fMRI studies, our results show that the human MEC and LEC homologues have a border oriented both towards the posterior-anterior and medial-lateral axes, supporting the differentiation between pmEC and alEC. <<<

The default mode network (DMN) involves interacting cortical areas, including the posterior cingulate cortex (PCC) and the retrosplenial cortex (RSC), and subcortical areas, including the medial temporal lobe (MTL). The degree of functional connectivity (FC) within the DMN, particularly between MTL and medial-parietal subsystems, relates to episodic memory (EM) processes. However, past resting-state studies investigating the link between posterior DMN-MTL FC and EM performance yielded inconsistent results, possibly reflecting heterogeneity in the degree of connectivity between MTL and specific cortical DMN regions. Animal work suggests that RSC has structural connections to both cortical DMN regions and MTL, and may thus serve as an intermediate layer that facilitates information transfer between cortical and subcortical DMNs. We studied 180 healthy old adults (aged 64-68 years), who underwent comprehensive assessment of EM, along with resting-state fMRI. We found greater FC between MTL and RSC than between MTL and the other cortical DMN regions (e.g., PCC), with the only significant association with EM observed for MTL-RSC FC. Mediational analysis showed that MTL-cortical DMN connectivity increased with RSC as a mediator. Further analysis using a graph-theoretical approach on DMN nodes revealed the highest betweenness centrality for RSC, confirming that a high proportion of short paths among DMN regions pass through RSC. Importantly, the degree of RSC mediation was associated with EM performance, suggesting that individuals with greater mediation have an EM advantage. These findings suggest that RSC forms a critical gateway between MTL and cortical DMN to support EM in older adults. <<<

Katharine C Simon, Gregory D Clemenson, Jing Zhang, Negin Sattari, Alessandra E Shuster, Brandon Clayton, Elisabet Alzueta, Teji Dulai, Massimiliano de Zambotti, Craig Stark, Fiona C Baker, Sara C Mednick <<<

Sleep facilitates hippocampal-dependent memories, supporting the acquisition and maintenance of internal representation of spatial relations within an environment. In humans, however, findings have been mixed regarding sleep's contribution to spatial memory and navigation, which may be due to task designs or outcome measurements. We developed the Minecraft Memory and Navigation (MMN) task for the purpose of disentangling how spatial memory accuracy and navigation change over time, and to study sleep's independent contributions to each. In the MMN task, participants learned the locations of objects through free exploration of an open field computerized environment. At test, they were teleported to random positions around the environment and required to navigate to the remembered location of each object. In study 1, we developed and validated four unique MMN environments with the goal of equating baseline learning and immediate test performance. A total of 86 participants were administered the training phases and immediate test. Participants' baseline performance was equivalent across all four environments, supporting the use of the MMN task. In study 2, 29 participants were trained, tested immediately, and again 12 h later after a period of sleep or wake. We found that the metric accuracy of object locations, i.e., spatial memory, was maintained over a night of sleep, while after wake, metric accuracy declined. In contrast, spatial navigation improved over both sleep and wake delays. Our findings support the role of sleep in retaining the precise spatial relationships within a cognitive map; however, they do not support a specific role of sleep in navigation. <<<

Face processing supports our ability to recognize friend from foe, form tribes and understand the emotional implications of changes in facial musculature. This skill relies on a distributed network of brain regions, but how these regions interact is poorly understood. Here we integrate anatomical and functional connectivity measurements with behavioural assays to create a global model of the face connectome. We dissect key features, such as the network topology and fibre composition. We propose a neurocognitive model with three core streams; face processing along these streams occurs in a parallel and reciprocal manner. Although long-range fibre paths are important, the face network is dominated by short-range fibres. Finally, we provide evidence that the well-known right lateralization of face processing arises from imbalanced intra- and interhemispheric connections. In summary, the face network relies on dynamic communication across highly structured fibre tracts, enabling coherent face processing that underpins behaviour and cognition. <<<

Triangle completion is a task widely used to study human path integration, an important navigation method relying on idiothetic cues. Systematic biases (compression patterns in the inbound responses) have been well documented in human triangle completion. However, the sources of systematic biases remain controversial. We used cross-validation modeling to compare three plausible theoretical models that assume that systematic errors occur in the encoding outbound path solely (encoding-error model), executing the inbound responses solely (execution-error model), and both (bi-component model), respectively. The data for cross-validation modeling are from a previous study (Qi et al., 2021), in which participants learned three objects’ locations (one at the path origin, that is, home) very well before walking each outbound path and then pointed to the objects’ original locations after walking the outbound path. The modeling algorithm used one inbound response (i.e., response to the home) or multiple inbound responses (i.e., responses to two non-home locations and the home) for each outbound path. The algorithm of using multiple inbound responses demonstrated that the bi-component model outperformed the other models in accounting for the systematic errors. This finding suggests that both encoding the outbound path and executing the inbound responses contribute to the systematic biases in human path integration. In addition, the results showed that the algorithm using only the home response could not distinguish among these three models, suggesting that the typical triangle-completion task with only the home response for each outbound path cannot determine the sources of the systematic biases. <<<

Despite over a century of research on intelligence, the cognitive processes underlying intelligent behavior are still unclear. In this review, we summarize empirical results investigating the contribution of cognitive processes associated with working memory capacity, processing speed, and executive processes to intelligence differences. Specifically, we (a) evaluate how cognitive processes associated with the three different cognitive domains have been measured, and (b) how these processes are related to individual differences in intelligence. Consistently, this review illustrates that isolating single cognitive processes using average performance in cognitive tasks is hardly possible. Instead, formal models that implement theories of cognitive processes underlying performance in different cognitive tasks may provide more adequate indicators of single cognitive processes. Therefore, we outlined which models for working memory capacity, processing speed, and executive processes may provide more specific insights into cognitive processes associated with individual differences in intelligence. Finally, we discuss implications of a process-oriented intelligence research using cognitive measurement models for psychometric theories of intelligence and argue that a model-based approach might overcome validity problems of traditional intelligence theories. <<<

The ability to anticipate and flexibly plan for the future is critical for achieving goal-directed outcomes. Extant data suggest that neural and cognitive stress mechanisms may disrupt memory retrieval and restrict prospective planning, with deleterious impacts on behavior. Here, we examined whether and how acute psychological stress influences goal-directed navigational planning and efficient, flexible behavior. Our methods combined fMRI, neuroendocrinology, and machine learning with a virtual navigation planning task. Human participants were trained to navigate familiar paths in virtual environments and then (concurrent with fMRI) performed a planning and navigation task that could be most efficiently solved by taking novel shortcut paths. Strikingly, relative to non-stressed control participants, participants who performed the planning task under experimentally induced acute psychological stress demonstrated (1) disrupted neural activity critical for mnemonic retrieval and mental simulation and (2) reduced traversal of shortcuts and greater reliance on familiar paths. These neural and behavioral changes under psychological stress were tied to evidence for disrupted neural replay of memory for future locations in the spatial environment, providing mechanistic insight into why and how stress can alter planning and foster inefficient behavior. <<<

Our representation of the physical world requires judgments of magnitudes, such as loudness, distance, or time. Interestingly, magnitude estimates are often not veridical but subject to characteristic biases. These biases are strikingly similar across different sensory modalities, suggesting common processing mechanisms that are shared by different sensory systems. However, the search for universal neurobiological principles of magnitude judgments requires guidance by formal theories. Here, we discuss a unifying Bayesian framework for understanding biases in magnitude estimation. This Bayesian perspective enables a re-interpretation of a range of established psychophysical findings, reconciles seemingly incompatible classical views on magnitude estimation, and can guide future investigations of magnitude estimation and its neurobiological mechanisms in health and in psychiatric diseases, such as schizophrenia. <<<