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Within the primate visual system, areas at lower levels of the cortical hierarchy process basic visual features, whereas those at higher levels, such as the frontal eye fields (FEF), are thought to modulate sensory processes via feedback connections. Despite these functional exchanges during perception, there is little shared activity between early and late visual regions at rest. How interactions emerge between regions encompassing distinct levels of the visual hierarchy remains unknown. Here we combined neuroimaging, non-invasive cortical stimulation and computational modelling to characterize changes in functional interactions across widespread neural networks before and after local inhibition of primary visual cortex or FEF. We found that stimulation of early visual cortex selectively increased feedforward interactions with FEF and extrastriate visual areas, whereas identical stimulation of the FEF decreased feedback interactions with early visual areas. Computational modelling suggests that these opposing effects reflect a fast-slow timescale hierarchy from sensory to association areas. In humans, the parts of the brain involved in vision are organized into distinct regions that are arranged into a hierarchy. Each of these regions contains neurons that are specialized for a particular role, such as responding to shape, color or motion. To actually ‘see’ an object, these different regions must communicate with each other and exchange information via connections between lower and higher levels of the hierarchy. However, it remains unclear how these connections work. A brain region called the primary visual cortex is the lowest level of the visual cortical hierarchy as it is the first area to receive information from the eye. This region then passes information to higher regions in the hierarchy including the frontal eye fields (FEF), which help to control visual attention and eye movements. In turn, the FEF is thought to provide ‘feedback’ to the primary visual cortex. Cocchi et al. examined how the FEF and primary visual cortex communicate with the rest of the brain by temporarily inhibiting the activity of these regions in human volunteers. The experiments show that inhibiting the primary visual cortex increased communication between this region and higher level visual areas. On the other hand, inhibiting the FEF reduced communication between this region and lower visual areas. Computer simulations revealed that inhibiting particular brain regions alters communication between visual regions by changing the timing of local neural activity. In the simulations, inhibiting the primary visual cortex slows down neural activity in that region, leading to better communication with higher regions, which already operate on slower timescales. By contrast, inhibition of the FEF reduces its influence on lower visual regions by increasing the difference in timescales of neural activity between these regions. The next step is to determine whether similar mechanisms regulate changes in the activity of neural networks outside of the visual system.

Robust evidence suggests that humans explore their environment using a combination of topological landmarks and coarse-grained path integration. This approach relies on identifiable environmental features (topological landmarks) in tandem with estimations of distance and direction (coarse-grained path integration) to construct cognitive maps of the surroundings. This cognitive map is believed to exhibit a hierarchical structure, allowing efficient planning when solving complex navigation tasks. Inspired by human behaviour, this paper presents a scalable hierarchical active inference model for autonomous navigation, exploration, and goal-oriented behaviour. The model uses visual observation and motion perception to combine curiosity-driven exploration with goal-oriented behaviour. Motion is planned using different levels of reasoning, i.e., from context to place to motion. This allows for efficient navigation in new spaces and rapid progress toward a target. By incorporating these human navigational strategies and their hierarchical representation of the environment, this model proposes a new solution for autonomous navigation and exploration. The approach is validated through simulations in a mini-grid environment.

In the context of warming freshwater habitats, protection of Atlantic salmon populations requires an understanding of the effects of temperature on somatic growth during the juvenile life stage. However, quantifying the effect of temperature on growth is challenging given differences among methodologies, metrics of growth, and their underlying assumptions. Using short term studies (2000–2002) in two Canadian populations of wild Atlantic salmon (Margaree and Miramichi rivers), we investigate whether different hierarchical modeling approaches influence the derivation of temperature-growth relationships, by contrasting seasonal growth trajectories (von Bertalanffy; VBGF) to size-at-age data models built with instantaneous growth rates. Size-at-age data analysed seasonally with the VBGF framework failed to detect an effect of temperature, whereas instantaneous growth rates from the same dataset were strongly related to temperature metrics. However, instantaneous growth rates cannot be used to extrapolate predictions into meaningful metrics for fisheries management (e.g., size at the end of the growing season). Nevertheless, we show that size at the end of the growing season can be predicted with VBGF models accounting for site-level variation, which in turn are related to temperature metrics, as observed for instantaneous growth rates. Taken together, these results show that combining these two approaches (size-at-age, growth rates) can circumvent their intrinsic drawbacks and reveal essential ecological patterns that may otherwise remain undetected. In cases where instantaneous growth rates are not available, relating predicted size-at-age from hierarchical VBGF to temperature provides an interesting alternative for detecting subtle environmental effects, even if the VBGF parameters or its residuals are unrelated to temperature metrics.

Abstract The ability to discriminate species and recognize individuals is crucial for reproductive success and/or survival in most animals. However, the temporal order and neural localization of these decision-making processes has remained unclear. In this study, event-related potentials (ERPs) were measured in the telencephalon, diencephalon, and mesencephalon of the music frog Nidirana daunchina. These ERPs were elicited by calls from 1 group of heterospecifics (recorded from a sympatric anuran species) and 2 groups of conspecifics that differed in their fundamental frequencies. In terms of the polarity and position within the ERP waveform, auditory ERPs generally consist of 4 main components that link to selective attention (N1), stimulus evaluation (P2), identification (N2), and classification (P3). These occur around 100, 200, 250, and 300 ms after stimulus onset, respectively. Our results show that the N1 amplitudes differed significantly between the heterospecific and conspecific calls, but not between the 2 groups of conspecific calls that differed in fundamental frequency. On the other hand, the N2 amplitudes were significantly different between the 2 groups of conspecific calls, suggesting that the music frogs discriminated the species first, followed by individual identification, since N1 and N2 relate to selective attention and stimuli identification, respectively. Moreover, the P2 amplitudes evoked in females were significantly greater than those in males, indicating the existence of sexual dimorphism in auditory discrimination. In addition, both the N1 amplitudes in the left diencephalon and the P2 amplitudes in the left telencephalon were greater than in other brain areas, suggesting left hemispheric dominance in auditory perception. Taken together, our results support the hypothesis that species discrimination and identification of individual characteristics are accomplished sequentially, and that auditory perception exhibits differences between sexes and in spatial dominance.

Itinerant dynamics of the brain generates transient and recurrent spatiotemporal patterns in neuroimaging data. Characterizing metastable functional connectivity (FC) - particularly at rest and using functional magnetic resonance imaging (fMRI) - has shaped the field of dynamic functional connectivity (DFC). Mainstream DFC research relies on (sliding window) correlations to identify recurrent FC patterns. Recently, functional relevance of the (IPS) of fMRI signals has been revealed using imaging studies and computational models. In the present paper, we identify the repertoire of whole-brain inter-network IPS states at rest. Moreover, we uncover a hierarchy in the temporal organization of IPS modes. We hypothesize that connectivity disorder in schizophrenia (SZ) is related to the (deep) temporal arrangement of large-scale IPS modes. Hence, we analyze resting-state fMRI data from 68 healthy controls (HC) and 51 SZ patients. Seven resting-state networks (and their sub-components) are identified using spatial independent component analysis. IPS is computed between subject-specific network time courses, using analytic signals. The resultant phase coupling patterns, across time and subjects, are clustered into eight IPS states. Statistical tests show that the relative expression and mean lifetime of certain IPS states have been altered in SZ. Namely, patients spend (45%) less time in a globally coherent state and a subcortical-centered state, and (40%) more time in states reflecting anticoupling within the cognitive control network, compared to the HC. Moreover, the transition profile (between states) reveals a deep temporal structure, shaping two metastates with distinct phase synchrony profiles. A metastate is a collection of states such that within-metastate transitions are more probable than across. Remarkably, metastate occupation balance is altered in SZ, in favor of the less synchronous metastate that promotes disconnection across networks. Furthermore, the trajectory of IPS patterns is less efficient, less smooth, and more restricted in SZ subjects, compared to the HC. Finally, a regression analysis confirms the diagnostic value of the defined IPS measures for SZ identification, highlighting the distinctive role of metastate proportion. Our results suggest that the proposed IPS features may be used for classification studies and for characterizing phase synchrony modes in other (clinical) populations.

Perceptual decisions are made not only during goal-directed behavior such as choice tasks, but also occur spontaneously while multistable stimuli are being viewed. In both contexts, the formation of a perceptual decision is best captured by noisy attractor dynamics. Noise-driven attractor transitions can accommodate a wide range of timescales and a hierarchical arrangement with “nested attractors” harbors even more dynamical possibilities. The attractor framework seems particularly promising for understanding higher-level mental states that combine heterogeneous information from a distributed set of brain areas.

Species that use communication sounds to coordinate social and reproductive behavior must be able to distinguish vocalizations from nonvocal sounds as well as to identify individual vocalization types. In this study we sought to identify the neural localization of the processes involved and the temporal order in which they occur in an anuran species, the music frog Babina daunchina. To do this we measured telencephalic and mesencephalic event-related potentials (ERPs) elicited by synthesized white noise (WN), highly sexually attractive (HSA) calls produced by males from inside nests and male calls of low sexual attractiveness (LSA) produced outside of nests. Each stimulus possessed similar temporal structures. The results showed the following: (1) the amplitudes of the first negative ERP component (N1) at ∼100 ms differed significantly between WN and conspecific calls but not between HSA and LSA calls, indicating that discrimination between conspecific calls and nonvocal sounds occurs in ∼100 ms, (2) the amplitudes of the second positive ERP component (P2) at ∼200 ms in the difference waves between HSA calls and WN were significantly higher than between LSA calls and WN in the right telencephalon, implying that call characteristic identification occurs in ∼200 ms and (3) WN evoked a larger third positive ERP component (P3) at ∼300 ms than conspecific calls, suggesting the frogs had classified the conspecific calls into one category and perceived WN as novel. Thus, both the detection of sounds and the identification of call characteristics are accomplished quickly in a specific temporal order, as reflected by ERP components. In addition, the most dynamic ERP patterns appeared in the left mesencephalon and the right telencephalon, indicating the two brain regions might play key roles in anuran vocal communication.

We consider a heteroclinic network in the framework of winnerless competition, realized by generalized Lotka-Volterra equations. By an appropriate choice of predation rates we impose a structural hierarchy so that the network consists of a heteroclinic cycle of three heteroclinic cycles which connect saddles on the basic level. As we have demonstrated in previous work, the structural hierarchy can induce a hierarchy in time scales such that slow oscillations modulate fast oscillations of species concentrations. Here we derive a Poincaré map to determine analytically the number of revolutions of the trajectory within one heteroclinic cycle on the basic level, before it switches to the heteroclinic connection on the second level. This provides an understanding of which parameters control the separation of time scales and determine the decisions of the trajectory at branching points of this network.

Purpose - This paper aims to propose a risk identification method which is a synthesis of existing tools and techniques.Design methodology approach - Risks are viewed as a temporal hierarchy of major decisions or events at the highest level, projects at the middle level, and routine operations at the lowest level. Furthermore, risks emerge as organizational activities progress over time. The organizational activities, called movements in this paper, typically follow the phases of routine (operations) > major decision event > project > adjustment > routine which correspond to the chosen temporal hierarchy. Risks are identified by examining the movements in all applicable phases of their development. The method was applied in a case study of an enterprise in the energy sector.Findings - Focus on movements bridges company silos. Risk logs make sense only when supplied with visualization tools. The future state of the enterprise's routines should be modelled early in the decision-making process. Attention should be paid to changes that major decisions, events, and projects impose on organizational routines.Originality value - The method belongs to the minority of approaches which explore risk evolution, relationships, and hierarchy rather than risk likelihood and impact. Risk evolution is explored by choosing movements as the basic units of risk identification. Risk relationships are detected on the level of routines where risk relationships are the least obvious but most important. The chosen hierarchy serves an enterprise-deep view of risks and makes it possible to be alert for periods when the organization's risks change or new ones emerge.

Understanding of the temporal development of competition symmetry, size hierarchy and the role of episodically supplied resources in forest stands is limited. Because of intrinsic differences in the symmetry of competition for light and below-ground resources, it is hypothesized that the overall expression of competition varies as a consequence of variations in water availability. Historical growth and precipitation data from an unthinned stand of Sitka spruce (Picea sitchensis(Bong.) Carr.) in Denmark are analysed with respect to the effects of precipitation on competition symmetry. The shape and linearity of the size-increment relationship are analysed, and the temporal development of diameter distribution and size hierarchy is modelled. The test value of lack of linear fit through the origin for the diameter/increment relationship plotted against precipitation in the growth period forms a triangular envelope, indicating a more curvilinear relationship for years with high water availability. This indicates that dominant trees apparently benefit more from increased precipitation than suppressed trees—which is also shown in the analysis of the temporal development of the diameter distribution—and as a consequence the size hierarchy increases. Finally, it is proposed that temporal and spatial variations in the availability of water and other below-ground resources may have similar effects on competition symmetry.