(Don't) look where you are going: Evidence for a travel direction signal in humans that is independent of head direction.

We often assume that travel direction is redundant with head direction, but from first principles, these two factors provide differing spatial information. Although head direction has been found to be a fundamental component of human navigation, it is unclear how self-motion signals for travel direction contribute to forming a travel trajectory. Employing a novel motion adaptation paradigm from visual neuroscience designed to preclude a contribution of head direction, we found high-level aftereffects of perceived travel direction, indicating that travel direction is a fundamental component of human navigation. Interestingly, we discovered a higher frequency of reporting perceived travel toward the adapted direction compared to a no-adapt control-an aftereffect that runs contrary to low-level motion aftereffects. This travel aftereffect was maintained after controlling for possible response biases and approaching effects, and it scaled with adaptation duration. These findings demonstrate the first evidence of how a pure travel direction signal might be represented in humans, independent of head direction. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Gated transformations from egocentric to allocentric reference frames involving retrosplenial cortex, entorhinal cortex, and hippocampus.

This paper reviews the recent experimental finding that neurons in behaving rodents show egocentric coding of the environment in a number of structures associated with the hippocampus. Many animals generating behavior on the basis of sensory input must deal with the transformation of coordinates from the egocentric position of sensory input relative to the animal, into an allocentric framework concerning the position of multiple goals and objects relative to each other in the environment. Neurons in retrosplenial cortex show egocentric coding of the position of boundaries in relation to an animal. These neuronal responses are discussed in relation to existing models of the transformation from egocentric to allocentric coordinates using gain fields and a new model proposing transformations of phase coding that differ from current models. The same type of transformations could allow hierarchical representations of complex scenes. The responses in rodents are also discussed in comparison to work on coordinate transformations in humans and non-human primates.

Functional network reconfiguration supporting memory-guided attention.

Studies have identified several brain regions whose activations facilitate attentional deployment via long-term memories. We analyzed task-based functional connectivity at the network and node-specific level to characterize large-scale communication between brain regions underlying long-term memory guided attention. We predicted default mode, cognitive control, and dorsal attention subnetworks would contribute differentially to long-term memory guided attention, such that network-level connectivity would shift based on attentional demands, requiring contribution of memory-specific nodes within default mode and cognitive control subnetworks. We expected that these nodes would increase connectivity with one another and with dorsal attention subnetworks during long-term memory guided attention. Additionally, we hypothesized connectivity between cognitive control and dorsal attention subnetworks facilitating external attentional demands. Our results identified both network-based and node-specific interactions that facilitate different components of LTM-guided attention, suggesting a crucial role across the posterior precuneus and restrosplenial cortex, acting independently from the divisions of default mode and cognitive control subnetworks. We found a gradient of precuneus connectivity, with dorsal precuneus connecting to cognitive control and dorsal attention regions, and ventral precuneus connecting across all subnetworks. Additionally, retrosplenial cortex showed increased connectivity across subnetworks. We suggest that connectivity from dorsal posterior midline regions is critical for the integration of external information with internal memory that facilitates long-term memory guided attention.

Functional reconfiguration of task-active frontoparietal control network facilitates abstract reasoning.

While the brain's functional network architecture is largely conserved between resting and task states, small but significant changes in functional connectivity support complex cognition. In this study, we used a modified Raven's Progressive Matrices Task to examine symbolic and perceptual reasoning in human participants undergoing fMRI scanning. Previously, studies have focused predominantly on discrete symbolic versions of matrix reasoning, even though the first few trials of the Raven's Advanced Progressive Matrices task consist of continuous perceptual stimuli. Our analysis examined the activation patterns and functional reconfiguration of brain networks associated with resting state and both symbolic and perceptual reasoning. We found that frontoparietal networks, including the cognitive control and dorsal attention networks, were significantly activated during abstract reasoning. We determined that these same task-active regions exhibited flexibly-reconfigured functional connectivity when transitioning from resting state to the abstract reasoning task. Conversely, we showed that a stable network core of regions in default and somatomotor networks was maintained across both resting and task states. We propose that these regionally-specific changes in the functional connectivity of frontoparietal networks puts the brain in a "task-ready" state, facilitating efficient task-based activation.

Mechanisms for maintaining information in working memory.

The review by Slotnick is valuable for raising the important question of how much the hippocampal activity induced by novel stimuli is due to mechanisms for encoding into long-term memory, and how much is due to working memory. Slotnick's paper implicitly defines working memory as being equivalent to sustained activation during the late delay period. In this commentary, we suggest that cognitive neuroscientists should consider a broader range of cellular and synaptic mechanisms for maintaining information in working memory.

Theta oscillations support active exploration in human spatial navigation.

Active navigation seems to yield better spatial knowledge than passive navigation, but it is unclear how active decision-making influences learning and memory. Here, we examined the contributions of theta oscillations to memory-related exploration while testing theories about how they contribute to active learning. Using electroencephalography (EEG), we tested individuals on a maze-learning task in which they made discrete decisions about where to explore at each choice point in the maze. Half the participants were free to make active decisions at each choice point, and the other half passively explored by selecting a marked choice (matched to active exploration) at each intersection. Critically, all decisions were made when stationary, decoupling the active decision-making process from movement and speed factors, which is another prominent potential role for theta oscillations. Participants were then tested on their knowledge of the maze by traveling from object A to object B within the maze. Results show an advantage for active decision-making during learning and indicate that the active group had greater theta power during choice points in exploration, particularly in midfrontal channels. These findings demonstrate that active exploration is associated with theta oscillations during human spatial navigation, and that these oscillations are not exclusively related to movement or speed. Results demonstrating increased theta oscillations in prefrontal regions suggest communication with the hippocampus and integration of new information into memory. We also found evidence for alpha oscillations during active navigation, suggesting a role for attention as well. This study finds support for a general mnemonic role for theta oscillations during navigational learning.

Dynamic Network Analysis Demonstrates the Formation of Stable Functional Networks During Rule Learning.

Variations in the functional connectivity of large-scale cortical brain networks may explain individual differences in learning ability. We used a dynamic network analysis of fMRI data to identify changes in functional brain networks that are associated with context-dependent rule learning. During fMRI scanning, naïve subjects performed a cognitive task designed to test their ability to learn context-dependent rules. Notably, subjects were given minimal instructions about the task prior to scanning. We identified several key network characteristics associated with fast and accurate rule learning. First, consistent with the formation of stable functional networks, a dynamic community detection analysis revealed regionally specific reductions in flexible switching between different functional communities in successful learners. Second, successful rule learners showed decreased centrality of ventral attention regions and increased assortative mixing of cognitive control regions as the rules were learned. Finally, successful subjects showed greater decoupling of default and attention communities throughout the entire task, whereas ventral attention and cognitive control regions became more connected during learning. Overall, the results support a framework by which a stable ventral attention community and more flexible cognitive control community support sustained attention and the formation of rule representations in successful learners.

Evidence for a gradient within the medial temporal lobes for flexible retrieval under hierarchical task rules.

A fundamental question in memory research is how the hippocampus processes contextual cues to retrieve distinct mnemonic associations. Prior research has emphasized the importance of hippocampal-prefrontal interactions for context-dependent memory. Our fMRI study examined the human medial temporal lobes (MTL) and their prefrontal interactions when retrieving memories associated with hierarchically organized task contexts. Participants learned virtual object-location associations governed by subordinate and superordinate task rules, which could be independently cued to change. On each fMRI trial, participants retrieved the correct object for convergent rule and location contextual information. Results demonstrated that hippocampal activity and hippocampal-prefrontal functional interconnectivity distinguished retrieval under different levels of hierarchically organized task rules. In explicit contrast to the hippocampal tail, anterior (body and head) regions were recruited specifically for superordinate changes in the contextual hierarchy. The hippocampal body also differed in its functional connectivity with the prefrontal cortex for superordinate versus subordinate changes. Our findings demonstrate a gradient in MTL for associative retrieval under changing task rules, and advance understanding of hippocampal-prefrontal interactions that support flexible contextual memory.

Cardiorespiratory fitness and mnemonic discrimination across the adult lifespan.

With a rising aging population, it is important to develop behavioral tasks that assess and track cognitive decline, and to identify protective factors that promote healthy brain aging. Mnemonic discrimination tasks that rely on pattern separation mechanisms are a promising metric to detect subtle age-related memory impairments. Behavioral performance on these tasks rely on the integrity of the hippocampus and surrounding circuitry, which are brain regions known to be adversely affected in aging and neurodegenerative disorders. Aerobic exercise, which improves cardiorespiratory fitness (CRF), has been shown to counteract aging-related decreases in structural and functional brain integrity and attenuate decline of cognitive performance. Here, we tested the hypothesis that higher CRF attenuates age-related deficits in mnemonic discrimination in both a nonspatial mnemonic discrimination (Mnemonic Similarity Task) and a virtual navigation task (Route Disambiguation Task). Importantly, we included individuals across the lifespan (aged 18-83 yr), including the middle-age range, to determine mnemonic discrimination performance across adulthood. Participants completed two mnemonic discrimination tasks and a treadmill test to assess CRF. Our results demonstrate robust negative age-related effects on mnemonic discrimination performance across both the nonspatial and spatial domains. Critically, higher CRF mitigated age-related attenuation in spatial contextual discrimination task performance, but did not show an attenuation effect on performance for object-based mnemonic discrimination. These results suggest that performance on spatial mnemonic discrimination may be a useful tool to track vulnerability in older individuals at risk for cognitive decline, and that higher CRF may lead to cognitive preservation across the adult lifespan, particularly for spatial disambiguation of similar contexts.

A neural circuit model for a contextual association task inspired by recommender systems.

Behavioral data shows that humans and animals have the capacity to learn rules of associations applied to specific examples, and generalize these rules to a broad variety of contexts. This article focuses on neural circuit mechanisms to perform a context-dependent association task that requires linking sensory stimuli to behavioral responses and generalizing to multiple other symmetrical contexts. The model uses neural gating units that regulate the pattern of physiological connectivity within the circuit. These neural gating units can be used in a learning framework that performs low-rank matrix factorization analogous to recommender systems, allowing generalization with high accuracy to a wide range of additional symmetrical contexts. The neural gating units are trained with a biologically inspired framework involving traces of Hebbian modification that are updated based on the correct behavioral output of the network. This modeling demonstrates potential neural mechanisms for learning context-dependent association rules and for the change in selectivity of neurophysiological responses in the hippocampus. The proposed computational model is evaluated using simulations of the learning process and the application of the model to new stimuli. Further, human subject behavioral experiments were performed and the results validate the key observation of a low-rank synaptic matrix structure linking stimuli to responses.

Improving fitness increases dentate gyrus/CA3 volume in the hippocampal head and enhances memory in young adults.

Converging evidence suggests a relationship between aerobic exercise and hippocampal neuroplasticity that interactively impacts hippocampally dependent memory. The majority of human studies have focused on the potential for exercise to reduce brain atrophy and attenuate cognitive decline in older adults, whereas animal studies often center on exercise-induced neurogenesis and hippocampal plasticity in the dentate gyrus (DG) of young adult animals. In the present study, initially sedentary young adults (18-35 years) participated in a moderate-intensity randomized controlled exercise intervention trial (ClinicalTrials.gov; NCT02057354) for a duration of 12 weeks. The aims of the study were to investigate the relationship between change in cardiorespiratory fitness (CRF) as determined by estimated V˙O2MAX , hippocampally dependent mnemonic discrimination, and change in hippocampal subfield volume. Results show that improving CRF after exercise training is associated with an increased volume in the left DG/CA3 subregion in young adults. Consistent with previous studies that found exercise-induced increases in anterior hippocampus in older adults, this result was specific to the hippocampal head, or most anterior portion, of the subregion. Our results also demonstrate a positive relationship between change in CRF and change in corrected accuracy for trials requiring the highest level of discrimination on a putative behavioral pattern separation task. This relationship was observed in individuals who were initially lower-fit, suggesting that individuals who show greater improvement in their CRF may receive greater cognitive benefit. This work extends animal models by providing evidence for exercise-induced neuroplasticity specific to the neurogenic zone of the human hippocampus.

Resting State Connectivity Between Medial Temporal Lobe Regions and Intrinsic Cortical Networks Predicts Performance in a Path Integration Task.

Humans differ in their individual navigational performance, in part because successful navigation relies on several diverse abilities. One such navigational capability is path integration, the updating of position and orientation during movement, typically in a sparse, landmark-free environment. This study examined the relationship between path integration abilities and functional connectivity to several canonical intrinsic brain networks. Intrinsic networks within the brain reflect past inputs and communication as well as structural architecture. Individual differences in intrinsic connectivity have been observed for common networks, suggesting that these networks can inform our understanding of individual spatial abilities. Here, we examined individual differences in intrinsic connectivity using resting state magnetic resonance imaging (rsMRI). We tested path integration ability using a loop closure task, in which participants viewed a single video of movement in a circle trajectory in a sparse environment, and then indicated whether the video ended in the same location in which it started. To examine intrinsic brain networks, participants underwent a resting state scan. We found that better performance in the loop task was associated with increased connectivity during rest between the central executive network (CEN) and posterior hippocampus, parahippocampal cortex (PHC) and entorhinal cortex. We also found that connectivity between PHC and the default mode network (DMN) during rest was associated with better loop closure performance. The results indicate that interactions between medial temporal lobe (MTL) regions and intrinsic networks that involve prefrontal cortex (PFC) are important for path integration and navigation.

Introduction to the special issue on the cognitive functions of the retrosplenial cortex.

This special issue on the cognitive functions of the retrosplenial cortex highlights progress that has been made in recent years in understanding the anatomy and function of the retrosplenial cortex in both animals and humans. The articles in this issue of Behavioral Neuroscience use a number of different approaches that together provide an up-to-date account of recent progress in understanding how the retrosplenial cortex contributes to cognition, with an emphasis on its functional role in spatial navigation and learning and memory. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Converging meta-analytic and connectomic evidence for functional subregions within the human retrosplenial region.

Interest in the retrosplenial cortex (RSC) has surged in recent years, as this region has been implicated in a range of cognitive processes. Previously reported anatomical and functional definitions of the human RSC encompass a larger area than expected from underlying cytoarchitectonic profiles. Here, we used a large-scale, unbiased, and data-driven approach combining functional MRI meta-analysis and resting-state functional connectivity (rsFC) methods to test the nature of this heterogeneity. The automated toolset Neurosynth was used to conduct meta-analyses in order to (a) identify heterogeneous areas in the retrosplenial region (RS region) associated with one or more cognitive domains, and (b) contrast the activation profiles related to these domains. These analyses yielded several functional subregions across the RS region, highlighting differences between anterior RS regions associated with episodic memory and posterior RS regions in the parietal-occipital sulcus associated with scenes and navigation. These regions were subsequently used as seeds to conduct whole brain rsFC analyses using data from the Human Connectome Project. In support of the meta-analysis findings, rsFC revealed divergent connectivity profiles, with anterior regions demonstrating connectivity to the default mode network (DMN) and posterior regions demonstrating connectivity to visual regions. Anterior RS regions and the parietal-occipital sulcus connected to different subnetworks of the DMN. This convergent evidence supports the conclusion that the broad cortical RS region incorporating both anatomical and functional RSC consists of functionally heterogeneous subregions. This study combines two large databases to provide a novel methodological blueprint for understanding brain function in the RS region and beyond. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Predictability matters: role of the hippocampus and prefrontal cortex in disambiguation of overlapping sequences.

Previous research has demonstrated that areas in the medial temporal lobe and prefrontal cortex (PFC) show increased activation during retrieval of overlapping sequences. In this study, we designed a task in which degree of overlap varied between conditions in order to parse out the contributions of hippocampal and prefrontal subregions as overlap between associations increased. In the task, participants learned sequential associations consisting of a picture frame, a face within the picture frame, and an outdoor scene. The control condition consisted of a single frame-face-scene sequence. In the low overlap condition, each frame was paired with two faces and two scenes. In the high overlap condition, each frame was paired with four faces and four scenes. In all conditions the correct scene was chosen among four possible scenes and was dependent on the frame and face that preceded the choice point. One day after training, participants were tested on the retrieval of learned sequences during fMRI scanning. Results showed that the middle and posterior hippocampus (HC) was active at times when participants acquired information that increased predictability of the correct response in the overlapping sequences. Activation of dorsolateral PFC occurred at time points when the participant was able to ascertain which set of sequences the correct response belonged to. The ventrolateral PFC was active when inhibition was required, either of irrelevant stimuli or incorrect responses. These results indicate that areas of lateral PFC work in concert with the HC to disambiguate between overlapping sequences and that sequence predictability is key to when specific brain regions become active.

Structural Differences in Hippocampal and Entorhinal Gray Matter Volume Support Individual Differences in First Person Navigational Ability.

The ability to update position and orientation to reach a goal is crucial to spatial navigation and individuals vary considerably in this ability. The current structural MRI study used voxel-based morphometry (VBM) analysis to relate individual differences in human brain morphology to performance in an active navigation task that relied on updating position and orientation in a landmark-free environment. Goal-directed navigation took place from either a first person perspective, similar to a person walking through the landmark-free environment, or Survey perspective, a bird's eye view. Critically, the first person perspective required a transformation of spatial information from an allocentric into an egocentric reference frame for goal-directed navigation. Significant structural volume correlations in the hippocampus, entorhinal cortex, and thalamus were related to first person navigational accuracy. Our results support the theory that hippocampus, entorhinal cortex, and thalamus are key structures for updating position and orientation during ground-level navigation. Furthermore, the results suggest that morphological differences in these regions underlie individual navigational abilities, providing an important link between animal models of navigation and the variability in human navigation.

A network model of behavioural performance in a rule learning task.

Humans demonstrate differences in performance on cognitive rule learning tasks which could involve differences in properties of neural circuits. An example model is presented to show how gating of the spread of neural activity could underlie rule learning and the generalization of rules to previously unseen stimuli. This model uses the activity of gating units to regulate the pattern of connectivity between neurons responding to sensory input and subsequent gating units or output units. This model allows analysis of network parameters that could contribute to differences in cognitive rule learning. These network parameters include differences in the parameters of synaptic modification and presynaptic inhibition of synaptic transmission that could be regulated by neuromodulatory influences on neural circuits. Neuromodulatory receptors play an important role in cognitive function, as demonstrated by the fact that drugs that block cholinergic muscarinic receptors can cause cognitive impairments. In discussions of the links between neuromodulatory systems and biologically based traits, the issue of mechanisms through which these linkages are realized is often missing. This model demonstrates potential roles of neural circuit parameters regulated by acetylcholine in learning context-dependent rules, and demonstrates the potential contribution of variation in neural circuit properties and neuromodulatory function to individual differences in cognitive function.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'.

Cortical and Subcortical Contributions to Long-Term Memory-Guided Visuospatial Attention.

Long-term memory (LTM) helps to efficiently direct and deploy the scarce resources of the attentional system; however, the neural substrates that support LTM-guidance of visual attention are not well understood. Here, we present results from fMRI experiments that demonstrate that cortical and subcortical regions of a network defined by resting-state functional connectivity are selectively recruited for LTM-guided attention, relative to a similarly demanding stimulus-guided attention paradigm that lacks memory retrieval and relative to a memory retrieval paradigm that lacks covert deployment of attention. Memory-guided visuospatial attention recruited posterior callosal sulcus, posterior precuneus, and lateral intraparietal sulcus bilaterally. Additionally, 3 subcortical regions defined by intrinsic functional connectivity were recruited: the caudate head, mediodorsal thalamus, and cerebellar lobule VI/Crus I. Although the broad resting-state network to which these nodes belong has been referred to as a cognitive control network, the posterior cortical regions activated in the present study are not typically identified with supporting standard cognitive control tasks. We propose that these regions form a Memory-Attention Network that is recruited for processes that integrate mnemonic and stimulus-based representations to guide attention. These findings may have important implications for understanding the mechanisms by which memory retrieval influences attentional deployment.

Models of spatial and temporal dimensions of memory.

Episodic memory involves coding of the spatial location and time of individual events. Coding of space and time is also relevant to working memory, spatial navigation, and the disambiguation of overlapping memory representations. Neurophysiological data demonstrate that neuronal activity codes the current, past and future location of an animal as well as temporal intervals within a task. Models have addressed how neural coding of space and time for memory function could arise, with both dimensions coded by the same neurons. Neural coding could depend upon network oscillatory and attractor dynamics as well as modulation of neuronal intrinsic properties. These models are relevant to the coding of space and time involving structures including the hippocampus, entorhinal cortex, retrosplenial cortex, striatum and parahippocampal gyrus, which have been implicated in both animal and human studies.