Large Scale Neurocognitive Networks Underlying Episodic Memory

2000 ◽  
Vol 12 (1) ◽  
pp. 163-173 ◽  
Author(s):  
Lars Nyberg ◽  
Jonas Persson ◽  
Reza Habib ◽  
Endel Tulving ◽  
Anthony R. McIntosh ◽  
...  
Keyword(s):  
Episodic Memory ◽  
Large Scale ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Activity Patterns ◽  
Brain Regions ◽  
Target Density ◽  
Functional Connections ◽  
Positron Emission ◽  
Episodic Encoding

Large-scale networks of brain regions are believed to mediate cognitive processes, including episodic memory. Analyses of regional differences in brain activity, measured by functional neuroimaging, have begun to identify putative components of these networks. To more fully characterize neurocognitive networks, however, it is necessary to use analytical methods that quantify neural network interactions. Here, we used positron emission tomography (PET) to measure brain activity during initial encoding and subsequent recognition of sentences and pictures. For each type of material, three recognition conditions were included which varied with respect to target density (0%, 50%, 100%). Analysis of large-scale activity patterns identified a collection of foci whose activity distinguished the processing of sentences vs. pictures. A second pattern, which showed strong prefrontal cortex involvement, distinguished the type of cognitive process (encoding or retrieval). For both pictures and sentences, the manipulation of target density was associated with minor activation changes. Instead, it was found to relate to systematic changes of functional connections between material-specific regions and several other brain regions, including medial temporal, right prefrontal and parietal regions. These findings provide evidence for large-scale neural interactions between material-specific and process-specific neural substrates of episodic encoding and retrieval.

scholarly journals Functional neuroimaging of psychiatric disorders: exploring hidden behaviour

2004 ◽  
Vol 34 (4) ◽  
pp. 577-581 ◽  
Author(s):  
P. C. FLETCHER
Keyword(s):  
Functional Neuroimaging ◽  
Brain Activity ◽  
Cognitive Strategies ◽  
Healthy Person ◽  
Brain Regions ◽  
Task Demands ◽  
Unrealistic Expectation ◽  
Positron Emission ◽  
The Impact ◽  
Function Mapping

From the outset, people have had high expectations of functional neuroimaging. Many will have been disappointed. After roughly a decade of widespread use, even an enthusiastic advocate must be diffident about the impact of the two most frequently used techniques – positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) – upon clinical psychiatry. Perhaps this disappointment arises from an unrealistic expectation of what these techniques are able to tell us about the workings of the normal and the disordered brain. Anyone who hoped for intricate and unambiguous region-to-function mapping was always going to be disappointed. This expectation presupposes, among other things, a thorough understanding of the cognitive functions that are to be mapped onto the brain regions. This understanding, however, while developing, is still rudimentary. Mapping disorder along comparable lines is even more complex since it demands two levels of understanding. The first is of the healthy region-to-function mapping, the second of the disordered region-to-function mapping, which immediately demands a consideration of the nature of the function in the disordered state. After all, someone with schizophrenia, when confronted with a psychological task, might tackle it in a very different way, in terms of the cognitive strategies used, from a healthy person confronted with the same task. The observation that brain activity differs across the two individuals would only be interpretable insofar as one thoroughly understood the processes that each individual invoked in response to the task demands.

scholarly journals A spatiotemporal complexity architecture of human brain activity

2021 ◽  
Author(s):  
Stephan Krohn ◽  
Nina von Schwanenflug ◽  
Leonhard Waschke ◽  
Amy Romanello ◽  
Martin Gell ◽  
...  
Keyword(s):  
Human Brain ◽  
Neural Activity ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain Organization ◽  
Functional Connections ◽  
Signal Complexity ◽  
The Brain

The human brain operates in large-scale functional networks, collectively subsumed as the functional connectome1-13. Recent work has begun to unravel the organization of the connectome, including the temporal dynamics of brain states14-20, the trade-off between segregation and integration9,15,21-23, and a functional hierarchy from lower-order unimodal to higher-order transmodal processing systems24-27. However, it remains unknown how these network properties are embedded in the brain and if they emerge from a common neural foundation. Here we apply time-resolved estimation of brain signal complexity to uncover a unifying principle of brain organization, linking the connectome to neural variability6,28-31. Using functional magnetic resonance imaging (fMRI), we show that neural activity is marked by spontaneous "complexity drops" that reflect episodes of increased pattern regularity in the brain, and that functional connections among brain regions are an expression of their simultaneous engagement in such episodes. Moreover, these complexity drops ubiquitously propagate along cortical hierarchies, suggesting that the brain intrinsically reiterates its own functional architecture. Globally, neural activity clusters into temporal complexity states that dynamically shape the coupling strength and configuration of the connectome, implementing a continuous re-negotiation between cost-efficient segregation and communication-enhancing integration9,15,21,23. Furthermore, complexity states resolve the recently discovered association between anatomical and functional network hierarchies comprehensively25-27,32. Finally, brain signal complexity is highly sensitive to age and reflects inter-individual differences in cognition and motor function. In sum, we identify a spatiotemporal complexity architecture of neural activity — a functional "complexome" that gives rise to the network organization of the human brain.

scholarly journals Meta-analytic clustering dissociates brain activity and behavior profiles across reward processing paradigms

2019 ◽  
Author(s):  
Jessica S. Flannery ◽  
Michael C. Riedel ◽  
Katherine L. Bottenhorn ◽  
Ranjita Poudel ◽  
Taylor Salo ◽  
...  
Keyword(s):  
Large Scale ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain Network ◽  
Reward Processing ◽  
Network Activity ◽  
Reward Learning ◽  
Learning Theories ◽  
Behavior Profiles

ABSTRACTReward learning is a ubiquitous cognitive mechanism guiding adaptive choices and behaviors, and when impaired, can lead to considerable mental health consequences. Reward-related functional neuroimaging studies have begun to implicate networks of brain regions essential for processing various peripheral influences (e.g., risk, subjective preference, delay, social context) involved in the multifaceted reward processing construct. To provide a more complete neurocognitive perspective on reward processing that synthesizes findings across the literature while also appreciating these peripheral influences, we utilized emerging meta-analytic techniques to elucidate brain regions, and in turn networks, consistently engaged in distinct aspects of reward processing. Using a data-driven, meta-analytic, k-means clustering approach, we dissociated seven meta-analytic groupings (MAGs) of neuroimaging results (i.e., brain activity maps) from 749 experimental contrasts across 176 reward processing studies involving 13,358 healthy participants. We then performed an exploratory functional decoding approach to gain insight into the putative functions associated with each MAG. We identified a seven-MAG clustering solution which represented dissociable patterns of convergent brain activity across reward processing tasks. Additionally, our functional decoding analyses revealed that each of these MAGs mapped onto discrete behavior profiles that suggested specialized roles in predicting value (MAG-1 & MAG-2) and processing a variety of emotional (MAG-3), external (MAG-4 & MAG-5), and internal (MAG-6 & MAG-7) influences across reward processing paradigms. These findings support and extend aspects of well-accepted reward learning theories and highlight large-scale brain network activity associated with distinct aspects of reward processing.

The anatomy of human emotion

2012 ◽  
pp. 257-262
Author(s):  
R. J. Dolan
Keyword(s):  
Emotional Processing ◽  
Functional Neuroimaging ◽  
Brain Activity ◽  
Mental States ◽  
Brain Regions ◽  
Emotional States ◽  
Psychological States ◽  
General Utility ◽  
Positron Emission ◽  
Emotional System

Emotions, uniquely among mental states, are characterized by psychological and somatic referents. The former embody the subjectivity of all psychological states. The latter are evident in objectively measurable stereotyped behavioural patterns of facial expression, comportment, and states of autonomic arousal. These include unique patterns of response associated with discrete emotional states, as for example seen in the primary emotions of fear, anger, or disgust often thought of as emotion proper. Emotional states are also unique among psychological states in exerting global effects on virtually all aspects of cognition including attention, perception, and memory. Emotion also exerts biasing influences on high level cognition including the decision-making processes that guide extended behaviour. An informed neurobiological account of emotion needs to incorporate how these wide ranging effects are mediated. Although much of what we can infer about emotional processing in the human brain is derived from clinic-pathological correlations, the advent of high resolution, non-invasive functional neuroimaging techniques such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) has greatly expanded this knowledge base. This is particularly the case for emotion, as opposed to other areas of cognition, where normative studies have provided a much richer account of the underlying neurobiology than that available on the basis of observations from pathology as in classical neuropsychology. Emotion has historically been considered to reflect the product of activity within the limbic system of the brain. The general utility of the concept of a limbic-based emotional system is limited by a lack of a consensus as to its precise anatomical extent and boundaries, coupled with knowledge that emotion-related brain activity is, to a considerable degree, configured by behavioural context. What this means is that brain regions engaged by, for example, an emotion of fear associated with seeing a snake can have both distinct and common features with an emotion of fear associated with a fearful recollection. Consequently, within this framework emotional states are not unique to any single brain region but are expressed in widespread patterns of brain activity, including activity within early sensory cortices, shaped by the emotion eliciting context. This perspective emphasizes a global propagation of emotional signals as opposed to a perspective of circumscribed limbic-mediated emotion-related activity.

scholarly journals Age- and reserve-related increases in fronto-parietal and anterior hippocampal activity during episodic encoding predict subsequent memory

2019 ◽  
Author(s):  
Abdelhalim Elshiekh ◽  
Sivaniya Subramaniapillai ◽  
Sricharana Rajagopal ◽  
Stamatoula Pasvanis ◽  
Elizabeth Ankudowich ◽  
...  
Keyword(s):  
Episodic Memory ◽  
Brain Activity ◽  
Activity Patterns ◽  
Brain Regions ◽  
Task Demands ◽  
Aging Brain ◽  
Older Individuals ◽  
Age Related ◽  
Brain Responses ◽  
Encoding And Retrieval

AbstractRemembering associations between encoded items and their contextual setting is a feature of episodic memory. Although this ability deteriorates with age in general, there is substantial variability in how older individuals perform on episodic memory tasks. This variability may stem from genetic and/or environmental factors related to reserve, allowing some individuals to compensate for age-related decline through differential recruitment of brain regions. In this fMRI study, we tested predictions related to reserve and compensation in a large adult lifespan sample (N=154). We used multivariate Behaviour Partial Least Squares (B-PLS) analysis to examine how age, retrieval accuracy, and a proxy measure of reserve, impacted brain activity patterns during spatial and temporal context encoding and retrieval. Reserve modulated age-related compensatory brain responses in ventral visual, temporal, and fronto-parietal regions during memory encoding as a function of task demands. Activity in inferior parietal, medial temporal, and ventral visual regions were strongly impacted by age at encoding and retrieval, but were also related to individual differences in reserve. Our findings are consistent with the concepts of reserve and compensation and suggest that reserve may mitigate age-related decline by modulating compensatory brain responses in the aging brain.

scholarly journals Reconfiguration of human evolving large-scale epileptic brain networks prior to seizures: an evaluation with node centralities

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Rieke Fruengel ◽  
Timo Bröhl ◽  
Thorsten Rings ◽  
Klaus Lehnertz
Keyword(s):  
Large Scale ◽  
Brain Networks ◽  
Brain Regions ◽  
Brain Network ◽  
Theoretical Concept ◽  
Global Network ◽  
Time Resolved ◽  
Functional Connections ◽  
Node Centrality ◽  
Network Mechanism

AbstractPrevious research has indicated that temporal changes of centrality of specific nodes in human evolving large-scale epileptic brain networks carry information predictive of impending seizures. Centrality is a fundamental network-theoretical concept that allows one to assess the role a node plays in a network. This concept allows for various interpretations, which is reflected in a number of centrality indices. Here we aim to achieve a more general understanding of local and global network reconfigurations during the pre-seizure period as indicated by changes of different node centrality indices. To this end, we investigate—in a time-resolved manner—evolving large-scale epileptic brain networks that we derived from multi-day, multi-electrode intracranial electroencephalograpic recordings from a large but inhomogeneous group of subjects with pharmacoresistant epilepsies with different anatomical origins. We estimate multiple centrality indices to assess the various roles the nodes play while the networks transit from the seizure-free to the pre-seizure period. Our findings allow us to formulate several major scenarios for the reconfiguration of an evolving epileptic brain network prior to seizures, which indicate that there is likely not a single network mechanism underlying seizure generation. Rather, local and global aspects of the pre-seizure network reconfiguration affect virtually all network constituents, from the various brain regions to the functional connections between them.

Neurocognitive Aging and Functional Connectivity Using Functional Magnetic Resonance Imaging

2018 ◽  
Author(s):  
Hana Burianová
Keyword(s):  
Functional Connectivity ◽  
Cognitive Processes ◽  
Large Scale ◽  
Healthy Aging ◽  
Brain Activity ◽  
Brain Regions ◽  
Effective Strategies ◽  
Cognitive Improvement ◽  
Age Related ◽  
Neurocognitive Aging

Determining the mechanisms that underlie neurocognitive aging, such as compensation or dedifferentiation, and facilitating the development of effective strategies for cognitive improvement is essential due to the steadily rising aging population. One approach to study the characteristics of healthy aging comprises the assessment of functional connectivity, delineating markers of age-related neurocognitive plasticity. Functional connectivity paradigms characterize complex one-to-many (or many-to-many) structure–function relations, as higher-level cognitive processes are mediated by the interaction among a number of functionally related neural areas rather than localized to discrete brain regions. Task-related or resting-state interregional correlations of brain activity have been used as reliable indices of functional connectivity, delineating age-related alterations in a number of large-scale brain networks, which subserve attention, working memory, episodic retrieval, and task-switching. Together with behavioral and regional activation studies, connectivity studies and modeling approaches have contributed to our understanding of the mechanisms of age-related reorganization of distributed functional networks; specifically, reduced neural specificity (dedifferentiation) and associated impairment in inhibitory control and compensatory neural recruitment.

scholarly journals Organization of Propagated Intrinsic Brain Activity in Individual Humans

2019 ◽  
Vol 30 (3) ◽  
pp. 1716-1734 ◽  
Author(s):  
Ryan V Raut ◽  
Anish Mitra ◽  
Scott Marek ◽  
Mario Ortega ◽  
Abraham Z Snyder ◽  
...  
Keyword(s):  
Resting State ◽  
Large Scale ◽  
Cortical Excitability ◽  
Brain Activity ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Brain Organization ◽  
Individual Level ◽  
Slow Activity ◽  
Lag Structure

Abstract Spontaneous infra-slow (<0.1 Hz) fluctuations in functional magnetic resonance imaging (fMRI) signals are temporally correlated within large-scale functional brain networks, motivating their use for mapping systems-level brain organization. However, recent electrophysiological and hemodynamic evidence suggest state-dependent propagation of infra-slow fluctuations, implying a functional role for ongoing infra-slow activity. Crucially, the study of infra-slow temporal lag structure has thus far been limited to large groups, as analyzing propagation delays requires extensive data averaging to overcome sampling variability. Here, we use resting-state fMRI data from 11 extensively-sampled individuals to characterize lag structure at the individual level. In addition to stable individual-specific features, we find spatiotemporal topographies in each subject similar to the group average. Notably, we find a set of early regions that are common to all individuals, are preferentially positioned proximal to multiple functional networks, and overlap with brain regions known to respond to diverse behavioral tasks—altogether consistent with a hypothesized ability to broadly influence cortical excitability. Our findings suggest that, like correlation structure, temporal lag structure is a fundamental organizational property of resting-state infra-slow activity.

scholarly journals How Multiple Retrievals Affect Neural Reactivation in Young and Older Adults

2019 ◽  
Vol 74 (7) ◽  
pp. 1086-1100 ◽  
Author(s):  
Marie St-Laurent ◽  
Bradley R Buchsbaum
Keyword(s):  
Older Adults ◽  
Episodic Memory ◽  
Brain Activity ◽  
Activity Patterns ◽  
Age Groups ◽  
Memory Representation ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Transformative Process ◽  
Repeated Retrieval

Abstract Objectives Aging can reduce the specificity with which memory episodes are represented as distributed patterns of brain activity. It remains unclear, however, whether repeated encoding and retrieval of stimuli modulate this decline. Memory repetition is thought to promote semanticization, a transformative process during which episodic memory becomes gradually decontextualized and abstracted. Because semantic memory is considered more resilient to aging than context-rich episodic memory, we hypothesized that repeated retrieval would affect cortical reinstatement differently in young versus older adults. Methods We reanalyzed data from young and older adults undergoing functional magnetic resonance imaging while repeatedly viewing and recalling short videos. We derived trial-unique multivariate measures of similarity between video-specific brain activity patterns elicited at perception and at recall, which we compared between age groups at each repetition. Results With repetition, memory representation became gradually more distinct from perception in young adults, as reinstatement specificity converged downward toward levels observed in the older group. In older adults, alternative representations that were item-specific but orthogonal to patterns elicited at perception became more salient with repetition. Discussion Repetition transformed dominant patterns of memory representation away and orthogonally from perception in young and older adults, respectively. Although distinct, both changes are consistent with repetition-induced semanticization.

scholarly journals Visual Number Beats Abstract Numerical Magnitude: Format-dependent Representation of Arabic Digits and Dot Patterns in Human Parietal Cortex

2015 ◽  
Vol 27 (7) ◽  
pp. 1376-1387 ◽  
Author(s):  
Jessica Bulthé ◽  
Bert De Smedt ◽  
Hans P. Op de Beeck
Keyword(s):  
Activity Pattern ◽  
Numerical Cognition ◽  
Brain Activity ◽  
Activity Patterns ◽  
Brain Regions ◽  
Numerical Magnitude ◽  
Visual Objects ◽  
Arabic Digits ◽  
The One ◽  
Object Cognition

In numerical cognition, there is a well-known but contested hypothesis that proposes an abstract representation of numerical magnitude in human intraparietal sulcus (IPS). On the other hand, researchers of object cognition have suggested another hypothesis for brain activity in IPS during the processing of number, namely that this activity simply correlates with the number of visual objects or units that are perceived. We contrasted these two accounts by analyzing multivoxel activity patterns elicited by dot patterns and Arabic digits of different magnitudes while participants were explicitly processing the represented numerical magnitude. The activity pattern elicited by the digit “8” was more similar to the activity pattern elicited by one dot (with which the digit shares the number of visual units but not the magnitude) compared to the activity pattern elicited by eight dots, with which the digit shares the represented abstract numerical magnitude. A multivoxel pattern classifier trained to differentiate one dot from eight dots classified all Arabic digits in the one-dot pattern category, irrespective of the numerical magnitude symbolized by the digit. These results were consistently obtained for different digits in IPS, its subregions, and many other brain regions. As predicted from object cognition theories, the number of presented visual units forms the link between the parietal activation elicited by symbolic and nonsymbolic numbers. The current study is difficult to reconcile with the hypothesis that parietal activation elicited by numbers would reflect a format-independent representation of number.

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