Search

We investigated whole-brain functional magnetic resonance imaging (fMRI) activation in a group of 21 healthy adult subjects during perception, imagination and remembering of two dynamic visual scenarios. Activation of the posterior parts of the cortex prevailed when watching videos. The cognitive tasks of imagination and remembering were accompanied by a predominant activity in the anterior parts of the cortex. An independent component analysis identified seven large-scale cortical networks with relatively invariant spatial distributions across all experimental conditions. The time course of their activation over experimental sessions was task-dependent. These detected networks can be interpreted as a recombination of resting state networks. Both central and peripheral networks were identified within the primary visual cortex. The central network around the caudal pole of BA17 and centers of other visual areas was activated only by direct visual stimulation, while the peripheral network responded to the presentation of visual information as well as to the cognitive tasks of imagination and remembering. The latter result explains the particular susceptibility of peripheral and twilight vision to cognitive top-down influences that often result in false-alarm detections.

It has been proposed in cognitive neuroscience that the operations of large-scale cortical networks are directly related to various aspects of cognitive function. However, the dynamic neural mechanisms responsible for these network operations are only poorly understood. This paper re-introduces Walter Freeman's idea of the wave packet as both an experimentally and theoretically unifying concept in neural dynamics. We begin by discussing the history of the wave packet as empirically observed in the olfactory local field potential by Freeman and colleagues. Freeman claimed that the wave packet, a mesoscopically self-organized cooperative neuronal activity pattern, is the way in which sensory information is turned into percepts, and ultimately, by which brains create meaning. He surmised that the wave packet is the most fundamental functional unit in the brain that carries meaningful contextdependent information. We extend Freeman's work to all cognitive function, which we propose is subserved by large-scale networks of linked neuronal populations in different neocortical areas, each generating a wave packet. We propose that the neocortical wave packet is comprised of locally-generated gamma oscillatory activity, as it is in paleocortex, and the linking mechanism consists of inter-areal phase coupling of beta oscillatory activity. We argue that neurocognitive function derives from wave packets in multiply linked neocortical areas reaching a functionally consistent consensus, and claim that the wave packet, discovered in the paleocortex, is key to the operation of the neocortex in cognition. [ABSTRACT FROM AUTHOR]

Neural correlations during a cognitive task are central to study brain information processing and computation. However, they have been poorly analyzed due to the difficulty of recording simultaneous single neurons during task performance. In the present work, we quantified neural directional correlations using spike trains that were simultaneously recorded in sensory, premotor, and motor cortical areas of two monkeys during a somatosensory discrimination task. Upon modeling spike trains as binary time series, we used a nonparametric Bayesian method to estimate pairwise directional correlations between many pairs of neurons throughout different stages of the task, namely, perception, working memory, decision making, and motor report. We find that solving the task involves feedforward and feedback correlation paths linking sensory and motor areas during certain task intervals. Specifically, information is communicated by task-driven neural correlations that are significantly delayed across secondary somatosensory cortex, premotor, and motor areas when decision making takes place. Crucially, when sensory comparison is no longer requested for task performance, a major proportion of directional correlations consistently vanish across all cortical areas. [ABSTRACT FROM AUTHOR]

Understanding how the mammalian neocortex creates cognition largely depends on knowledge about large-scale cortical organization. Accumulated evidence has illuminated cortical substrates of cognition across the lifespan, but how topological properties of cortical networks support structure-function relationships in normal aging remains an open question. Here we investigate the role of connections (i.e., short/long and direct/indirect) and node properties (i.e., centrality and modularity) in predicting functional-structural connectivity coupling in healthy elderly subjects. Connectivity networks were derived from correlations of cortical thickness and cortical glucose consumption in resting state. Local-direct connections (i.e., nodes separated by less than 30 mm) and node modularity (i.e., a set of nodes highly interconnected within a topological community and sparsely interconnected with nodes from other modules) in the functional network were identified as the main determinants of coupling between cortical networks, suggesting that the structural network in aging is mainly constrained by functional topological properties involved in the segregation of information, likely due to aging-related deficits in functional integration. This hypothesis is supported by an enhanced connectivity between cortical regions of different resting-state networks involved in sensorimotor and memory functions in detrimental to associations between fronto-parietal regions supporting executive processes. Taken collectively, these findings open new avenues to identify aging-related failures in the anatomo-functional organization of the neocortical mantle, and might contribute to early detection of prevalent neurodegenerative conditions occurring in the late life. Hum Brain Mapp 35:2724-2740, 2014. © 2013 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Cognitive functions are subserved by rhythmic neuronal synchronization across widely distributed brain areas. In 105 area pairs, we investigated functional connectivity (FC) through coherence, power correlation, and Granger causality (GC) in the theta, beta, high-beta, and gamma rhythms. Between rhythms, spatial FC patterns were largely independent. Thus, the rhythms defined distinct interaction networks. Importantly, networks of coherence and GC were not explained by the spatial distributions of the strengths of the rhythms. Those networks, particularly the GC networks, contained clear modules, with typically one dominant rhythm per module. To understand how this distinctiveness and modularity arises on a common anatomical backbone, we correlated, across 91 area pairs, the metrics of functional interaction with those of anatomical projection strength. Anatomy was primarily related to coherence and GC, with the largest effect sizes for GC. The correlation differed markedly between rhythms, being less pronounced for the beta and strongest for the gamma rhythm. • Coherence, power correlation, and Granger causality among >200 sites across 15 areas • These interaction metrics peak at the theta, beta, high-beta, and gamma rhythms • The 4 rhythms define distinct interaction networks, largely independent of power • The networks differentially depend on anatomy, strongly for gamma, weakly for beta The brain is much more than the sum of its parts because those parts interact in complex networks. Vezoli et al. show that at least 4 distinct interaction networks coexist, mediated by the neuronal synchronization of 4 brain rhythms. These rhythm-defined networks are differentially dependent on the strengths of anatomical projections. [ABSTRACT FROM AUTHOR]

Background: There is increasing interest in applying neuroscience findings to topics in education. Purpose: This application requires a proper conceptualisation of the relation between cognition and brain function. This paper considers two such conceptualisations. The area focus understands each cognitive competency as the product of one (and only one) brain area. The network focus explains each cognitive competency as the product of collaborative processing among multiple brain areas. Sources of evidence: We first review neuroscience studies of mathematical reasoning-specifically arithmetic problem-solving and magnitude comparison-that exemplify the area focus and network focus. We then review neuroscience findings that illustrate the potential of the network focus for informing three topics in mathematics education: the development of mathematical reasoning, the effects of practice and instruction, and the derailment of mathematical reasoning in dyscalculia. Main argument: Although the area focus has historically dominated discussions in educational neuroscience, we argue that the network focus offers a complementary perspective on brain function that should not be ignored. Conclusions: We conclude by describing the current limitations of network-focus theorising and emerging neuroscience methods that promise to make such theorising more tractable in the future. [ABSTRACT FROM AUTHOR]

The brain's default mode network (DMN) has attracted tremendous attention, but its topology still lacks a substantial and operative definition. At the same time, recent efforts based on coactivation analysis suggest significant involvement of concomitant activation as an origin of synchronous activity, which is the basis of the network detection. Therefore, to establish the biological significance of the intrinsic remote connectivity, understanding such co-occurrence networks may be crucial. This study shows the results of monitoring the network's signal variation during random transitions among two divergent tasks and rest epochs. The subset of the DMN nodes showed three distinct activity levels; it was simultaneously characterized by the lack of a transition response between blocks. Additional connectivity analysis revealed components covering the other DMN nodes showing overshooting in response to a transition that were still connected to the posterior cingulate cortices (PCC), but by different signal components. The overall finding of multiple connectivity modes in the DMN provides a relevant explanation about the two seemingly contradictory characteristics of the network, robustness and variation.

Neural correlations during a cognitive task are central to study brain information processing and computation. However, they have been poorly analyzed due to the difficulty of recording simultaneous single neurons during task performance. In the present work, we quantified neural directional correlations using spike trains that were simultaneously recorded in sensory, premotor, and motor cortical areas of two monkeys during a somatosensory discrimination task. Upon modeling spike trains as binary time series, we used a nonparametric Bayesian method to estimate pairwise directional correlations between many pairs of neurons throughout different stages of the task, namely, perception, working memory, decision making, and motor report. We find that solving the task involves feedforward and feedback correlation paths linking sensory and motor areas during certain task intervals. Specifically, information is communicated by task-driven neural correlations that are significantly delayed across secondary somatosensory cortex, premotor, and motor areas when decision making takes place. Crucially, when sensory comparison is no longer requested for task performance, a major proportion of directional correlations consistently vanish across all cortical areas.