The understanding of neural activity patterns is fundamentally linked to an understanding of how the brain's network architecture shapes dynamical processes. Established approaches rely mostly on deviations of a given network from certain classes of random graphs. Hypotheses about the supposed role of prominent topological features (for instance, the roles of modularity, network motifs or hierarchical network organization) are derived from these deviations. An alternative strategy could be to study deviations of network architectures from regular graphs (rings and lattices) and consider the implications of such deviations for self-organized dynamic patterns on the network. Following this strategy, we draw on the theory of spatio-temporal pattern formation and propose a novel perspective for analysing dynamics on networks, by evaluating how the self-organized dynamics are confined by network architecture to a small set of permissible collective states. In particular, we discuss the role of prominent topological features of brain connectivity, such as hubs, modules and hierarchy, in shaping activity patterns. We illustrate the notion of network-guided pattern formation with numerical simulations and outline how it can facilitate the understanding of neural dynamics.
The voluntary, top-down allocation of visual spatial attention has been linked to changes in the alpha-band of the electroencephalogram (EEG) signal measured over occipital and parietal lobes. In the present study, we investigated how occipitoparietal alpha-band activity changes when people allocate their attentional resources in a graded fashion across the visual field. We asked participants to either completely shift their attention into one hemifield, to balance their attention equally across the entire visual field, or to attribute more attention to one-half of the visual field than to the other. As expected, we found that alpha-band amplitudes decreased stronger contralaterally than ipsilaterally to the attended side when attention was shifted completely. Alpha-band amplitudes decreased bilaterally when attention was balanced equally across the visual field. However, when participants allocated more attentional resources to one-half of the visual field, this was not reflected in the alpha-band amplitudes, which just decreased bilaterally. We found that the performance of the participants was more strongly reflected in the coherence between frontal and occipitoparietal brain regions. We conclude that low alpha-band amplitudes seem to be necessary for stimulus detection. Furthermore, complete shifts of attention are directly reflected in the lateralization of alpha-band amplitudes. In the present study, a gradual allocation of visual attention across the visual field was only indirectly reflected in the alpha-band activity over occipital and parietal cortexes.
In the early days after ischemic stroke, information on structural brain damage from MRI supports prognosis of functional outcome. It is rated widely by the modified Rankin Scale that correlates only moderately with lesion volume. We therefore aimed to elucidate the influence of lesion location from early MRI (days 2-3) on functional outcome after 1 month using voxel-based lesion symptom mapping.
Information processing in the brain is strongly constrained by anatomical connectivity. However, the principles governing the organization of corticocortical connections remain elusive. Here, we tested three models of relationships between the organization of cortical structure and features of connections linking 49 areas of the cat cerebral cortex. Factors taken into account were relative cytoarchitectonic differentiation ('structural model'), relative spatial position ('distance model'), or relative hierarchical position ('hierarchical model') of the areas. Cytoarchitectonic differentiation and spatial distance (themselves uncorrelated) correlated strongly with the existence of inter-areal connections, whereas no correlation was found with relative hierarchical position. Moreover, a strong correlation was observed between patterns of laminar projection origin or termination and cytoarchitectonic differentiation. Additionally, cytoarchitectonic differentiation correlated with the absolute number of corticocortical connections formed by areas, and varied characteristically between different cortical subnetworks, including a 'rich-club' module of hub areas. Thus, connections between areas of the cat cerebral cortex can, to a large part, be explained by the two independent factors of relative cytoarchitectonic differentiation and spatial distance of brain regions. As both the structural and distance model were originally formulated in the macaque monkey, their applicability in another mammalian species suggests a general principle of global cortical organization.
In principle, cortico-cortical communication dynamics is simple: neurons in one cortical area communicate by sending action potentials that release glutamate and excite their target neurons in other cortical areas. In practice, knowledge about cortico-cortical communication dynamics is minute. One reason is that no current technique can capture the fast spatio-temporal cortico-cortical evolution of action potential transmission and membrane conductances with sufficient spatial resolution. A combination of optogenetics and monosynaptic tracing with virus can reveal the spatio-temporal cortico-cortical dynamics of specific neurons and their targets, but does not reveal how the dynamics evolves under natural conditions. Spontaneous ongoing action potentials also spread across cortical areas and are difficult to separate from structured evoked and intrinsic brain activity such as thinking. At a certain state of evolution, the dynamics may engage larger populations of neurons to drive the brain to decisions, percepts and behaviors. For example, successfully evolving dynamics to sensory transients can appear at the mesoscopic scale revealing how the transient is perceived. As a consequence of these methodological and conceptual difficulties, studies in this field comprise a wide range of computational models, large-scale measurements (e.g., by MEG, EEG), and a combination of invasive measurements in animal experiments. Further obstacles and challenges of studying cortico-cortical communication dynamics are outlined in this critical review.
A new paper shows that a characteristic feature of the arrangement of brain networks, their modular organization across several scales, is responsible for an expanded range of critical neural dynamics. This finding solves several puzzles in computational neuroscience and links fundamental aspects of neural network organization and brain dynamics.
Intrinsic coupling constitutes a key feature of ongoing brain activity, which exhibits rich spatiotemporal patterning and contains information that influences cognitive processing. We discuss evidence for two distinct types of intrinsic coupling modes which seem to reflect the operation of different coupling mechanisms. One type arises from phase coupling of band-limited oscillatory signals, whereas the other results from coupled aperiodic fluctuations of signal envelopes. The two coupling modes differ in their dynamics, their origins, and their putative functions and with respect to their alteration in neuropsychiatric disorders. We propose that the concept of intrinsic coupling modes can provide a unifying framework for capturing the dynamics of intrinsically generated neuronal interactions at multiple spatial and temporal scales.
Using the flanker paradigm in a task requiring eye movement responses, we examined how stimulus type (arrows vs. letters) modulated effects of flanker and flanker position. Further, we examined trial sequence effects and the impact of stimulus type on these effects. Participants responded to a central target with a left- or rightward saccade. We reasoned that arrows, being overlearned symbols of direction, are processed with less effort and are therefore linked more easily to a direction and a required response than are letters. The main findings demonstrate that (a) flanker effects were stronger for arrows than for letters, (b) flanker position more strongly modulated the flanker effect for letters than for arrows, and (c) trial sequence effects partly differed between the two stimulus types. We discuss these findings in the context of a more automatic and effortless processing of arrow relative to letter stimuli.
The formation of the complex network architecture of neural systems is subject to multiple structural and functional constraints. Two obvious but apparently contradictory constraints are low wiring cost and high processing efficiency, characterized by short overall wiring length and a small average number of processing steps, respectively. Growing evidence shows that neural networks are results from a trade-off between physical cost and functional value of the topology. However, the relationship between these competing constraints and complex topology is not well understood quantitatively. We explored this relationship systematically by reconstructing two known neural networks, Macaque cortical connectivity and C. elegans neuronal connections, from combinatory optimization of wiring cost and processing efficiency constraints, using a control parameter ?, and comparing the reconstructed networks to the real networks. We found that in both neural systems, the reconstructed networks derived from the two constraints can reveal some important relations between the spatial layout of nodes and the topological connectivity, and match several properties of the real networks. The reconstructed and real networks had a similar modular organization in a broad range of ?, resulting from spatial clustering of network nodes. Hubs emerged due to the competition of the two constraints, and their positions were close to, and partly coincided, with the real hubs in a range of ? values. The degree of nodes was correlated with the density of nodes in their spatial neighborhood in both reconstructed and real networks. Generally, the rebuilt network matched a significant portion of real links, especially short-distant ones. These findings provide clear evidence to support the hypothesis of trade-off between multiple constraints on brain networks. The two constraints of wiring cost and processing efficiency, however, cannot explain all salient features in the real networks. The discrepancy suggests that there are further relevant factors that are not yet captured here.
In post-unification Germany, lingering conflicts between East and West Germans have found some unusual outlets, including a debate of the relative superiority of East and West German Ampelmännchen pedestrian traffic signs. In our study, we probed the visual efficacy of East and West German Ampelmännchen signs with a Stroop-like conflict task. We found that the distinctive East German man-with-hat figures were more resistant to conflicting information, and in turn produced greater interference when used as distractors. These findings demonstrate Stroop-like effects for real-life objects, such as traffic signs, and underline the practical utility of an East German icon.
Phosphenes are commonly evoked by transcranial magnetic stimulation (TMS) to study the functional organization, connectivity, and excitability of the human visual brain. For years, phosphenes have been documented only from stimulating early visual areas (V1-V3) and a handful of specialized visual regions (V4, V5/MT+) in occipital cortex. Recently, phosphenes were reported after applying TMS to a region of posterior parietal cortex involved in the top-down modulation of visuo-spatial processing. In the present study, we systematically characterized parietal phosphenes to determine if they are generated directly by local mechanisms or emerge through indirect activation of other visual areas. Using technology developed in-house to record the subjective features of phosphenes, we found no systematic differences in the size, shape, location, or frame-of-reference of parietal phosphenes when compared to their occipital counterparts. In a second experiment, discrete deactivation by 1 Hz repetitive TMS yielded a double dissociation: phosphene thresholds increased at the deactivated site without producing a corresponding change at the non-deactivated location. Overall, the commonalities of parietal and occipital phosphenes, and our ability to independently modulate their excitability thresholds, lead us to conclude that they share a common neural basis that is separate from either of the stimulated regions.
Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information processing.
There is emerging evidence for a connection between the surface morphology of the brain and its underlying connectivity. The foundation for this relationship is thought to be established during brain development through the shaping influences of tension exerted by viscoelastic nerve fibers. The tension-based morphogenesis results in compact wiring that enhances efficient neural processing. Individuals with schizophrenia present with multiple symptoms that can include impaired thought, action, perception, and cognition. The global nature of these symptoms has led researchers to explore a more global disruption of neuronal connectivity as a theory to explain the vast array of clinical and cognitive symptoms in schizophrenia. If cerebral function and form are linked through the organization of neural connectivity, then a disruption in neural connectivity may also alter the surface morphology of the brain. This paper reviews developmental theories of gyrification and the potential interaction between gyrification and neuronal connectivity. Studies of gyrification abnormalities in children, adolescents, and adults with schizophrenia demonstrate a relationship between disrupted function and altered morphology in the surface patterns of the cerebral cortex. This altered form may provide helpful clues in understanding the neurobiological abnormalities associated with schizophrenia.
Various brain regions contribute to aspects of attentional control in conflict resolution. Here, we used transcranial magnetic stimulation (TMS) to examine the functions of posterior parietal cortex (PPC) and dorsal medial frontal cortex (dMFC) in a visual flanker task. Participants responded to a central target that was flanked by congruent, neutral or incongruent stimuli on the left or right. Offline low-frequency repetitive TMS (1 Hz, 110% motor threshold, 20 min) was applied to right PPC or dMFC. Performance, as measured by reaction times and accuracy, was established at baseline, after rTMS, and sham stimulation before or after active rTMS. After rTMS to right PPC, the interference of flankers presented in the left visual hemispace diminished selectively. By contrast, after rTMS over the right dMFC, flanker effects in both visual fields remained. Our results suggest that right PPC specifically contributes to the assignment of spatial attention during stimulus encoding.
An essential requirement for the representation of functional patterns in complex neural networks, such as the mammalian cerebral cortex, is the existence of stable regimes of network activation, typically arising from a limited parameter range. In this range of limited sustained activity (LSA), the activity of neural populations in the network persists between the extremes of either quickly dying out or activating the whole network. Hierarchical modular networks were previously found to show a wider parameter range for LSA than random or small-world networks not possessing hierarchical organization or multiple modules. Here we explored how variation in the number of hierarchical levels and modules per level influenced network dynamics and occurrence of LSA. We tested hierarchical configurations of different network sizes, approximating the large-scale networks linking cortical columns in one hemisphere of the rat, cat, or macaque monkey brain. Scaling of the network size affected the number of hierarchical levels and modules in the optimal networks, also depending on whether global edge density or the numbers of connections per node were kept constant. For constant edge density, only few network configurations, possessing an intermediate number of levels and a large number of modules, led to a large range of LSA independent of brain size. For a constant number of node connections, there was a trend for optimal configurations in larger-size networks to possess a larger number of hierarchical levels or more modules. These results may help to explain the trend to greater network complexity apparent in larger brains and may indicate that this complexity is required for maintaining stable levels of neural activation.
Regularity of laminar origin and termination of projections appears to be a common feature of corticocortical connections. We tested three models of this regularity, originally formulated for primate cerebral cortex, using quantitative data on the relative supragranular layer origins (SGN%) of 151 projections from 19 areas ( approximately 145,000 neurons) to four areas of cat extrastriate cortex. Predictive variables in the models were: hierarchical level differences (Barone et al., 2000), structural type differences (Barbas, 1986), and distances (Salin and Bullier, 1995) between areas. Global and local hierarchies of cat visual cortex were used to evaluate the hierarchical model. Ranking of areas by their cytoarchitectural differentiation (e.g., relative prominence of layer IV) allowed testing of the structural model, while the distance model was tested for the number of borders separating areas. Laminar projection origins correlated moderately with hierarchical differences, and poorly with border distances, but were strongly and consistently correlated with area differences in cytoarchitectural rank. Moreover, projection densities were moderately and negatively correlated with area distances and structural differences. Our findings suggest that the relative cytoarchitectural differentiation of cortical areas is the main determinant of laminar projection origins in cat visual cortex, and may underlie a general laminar regularity of mammalian cortical connections.
Neural connectivity at the cellular and mesoscopic level appears very specific and is presumed to arise from highly specific developmental mechanisms. However, there are general shared features of connectivity in systems as different as the networks formed by individual neurons in Caenorhabditis elegans or in rat visual cortex and the mesoscopic circuitry of cortical areas in the mouse, macaque, and human brain. In all these systems, connection length distributions have very similar shapes, with an initial large peak and a long flat tail representing the admixture of long-distance connections to mostly short-distance connections. Furthermore, not all potentially possible synapses are formed, and only a fraction of axons (called filling fraction) establish synapses with spatially neighboring neurons. We explored what aspects of these connectivity patterns can be explained simply by random axonal outgrowth. We found that random axonal growth away from the soma can already reproduce the known distance distribution of connections. We also observed that experimentally observed filling fractions can be generated by competition for available space at the target neurons--a model markedly different from previous explanations. These findings may serve as a baseline model for the development of connectivity that can be further refined by more specific mechanisms.
In this era of complete genomes, our knowledge of neuroanatomical circuitry remains surprisingly sparse. Such knowledge is critical, however, for both basic and clinical research into brain function. Here we advocate for a concerted effort to fill this gap, through systematic, experimental mapping of neural circuits at a mesoscopic scale of resolution suitable for comprehensive, brainwide coverage, using injections of tracers or viral vectors. We detail the scientific and medical rationale and briefly review existing knowledge and experimental techniques. We define a set of desiderata, including brainwide coverage; validated and extensible experimental techniques suitable for standardization and automation; centralized, open-access data repository; compatibility with existing resources; and tractability with current informatics technology. We discuss a hypothetical but tractable plan for mouse, additional efforts for the macaque, and technique development for human. We estimate that the mouse connectivity project could be completed within five years with a comparatively modest budget.
Understanding the interplay of topology and dynamics of excitable neural networks is one of the major challenges in computational neuroscience. Here we employ a simple deterministic excitable model to explore how network-wide activation patterns are shaped by network architecture. Our observables are co-activation patterns, together with the average activity of the network and the periodicities in the excitation density. Our main results are: (1) the dependence of the correlation between the adjacency matrix and the instantaneous (zero time delay) co-activation matrix on global network features (clustering, modularity, scale-free degree distribution), (2) a correlation between the average activity and the amount of small cycles in the graph, and (3) a microscopic understanding of the contributions by 3-node and 4-node cycles to sustained activity.
Related JoVE Video
Journal of Visualized Experiments
What is Visualize?
JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.
How does it work?
We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.
Video X seems to be unrelated to Abstract Y...
In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.