Designing spontaneous behavioral switching via chaotic itinerancy

Chaotic itinerancy is a frequently observed phenomenon in high-dimensional nonlinear dynamical systems and is characterized by itinerant transitions among multiple quasi-attractors. Several studies have pointed out that high-dimensional activity in animal brains can be observed to exhibit chaotic itinerancy, which is considered to play a critical role in the spontaneous behavior generation of animals. Thus, how to design desired chaotic itinerancy is a topic of great interest, particularly for neurorobotics researchers who wish to understand and implement autonomous behavioral controls. However, it is generally difficult to gain control over high-dimensional nonlinear dynamical systems. In this study, we propose a method for implementing chaotic itinerancy reproducibly in a high-dimensional chaotic neural network. We demonstrate that our method enables us to easily design both the trajectories of quasi-attractors and the transition rules among them simply by adjusting the limited number of system parameters and by using the intrinsic high-dimensional chaos.

Gastropod Feeding Systems: Evolution of Neural Circuits that Generate Diverse Behaviors

It is conceptually reasonable to explore how the evolution of behavior involves changes in neural circuitry. Progress in determining this evolutionary relationship has been limited in neuroscience because of difficulties in identifying individual neurons that contribute to the evolutionary development of behaviors across species. However, the results from the feeding systems of gastropod mollusks provide evidence for this concept of co-evolution because the evolution of different types of feeding behaviors in this diverse group of mollusks is mirrored by species-specific changes in neural circuitry. The evolution of feeding behaviors involves changes in the motor actions that allow diverse food items to be acquired and ingested. The evolution in neural control accompanies this variation in food and the associated changes in flexibility of feeding behaviors. This is present in components of the feeding network that are involved in decision making, rhythm generation, and behavioral switching but is absent in background mechanisms that are conserved across species, such as those controlling arousal state. These findings show how evolutionary changes, even at the single neuron level, closely reflect the details of behavioral evolution.

Monitoring in emotion regulation: behavioral decisions and neural consequences

Monitoring and deciding how to adjust an active regulatory strategy in order to maximize adaptive outcomes is an integral element of emotion regulation, yet existing evidence remains scarce. Filling this gap, the present study examined core factors that determine behavioral regulatory monitoring decisions and the neuro-affective consequences of these decisions. Using a novel paradigm, the initial implementation of central downregulation strategies (distraction, reappraisal) and the emotional intensity (high, low) were manipulated, prior to making a behavioral decision to maintain the initial implemented strategy or switch from it. Neuro-affective consequences of these behavioral decisions were evaluated using the Late Positive Potential (LPP), an electro-cortical measure of regulatory success. Confirming predictions, initial implementation of reappraisal in high intensity and distraction in low intensity (Strategy × Intensity combinations that were established in prior studies as non-preferred by individuals), resulted in increased behavioral switching frequency. Neurally, we expected and found that in high (but not low) emotional intensity, where distraction was more effective than reappraisal, maintaining distraction (relative to switching to reappraisal) and switching to distraction (relative to maintaining reappraisal) resulted in larger LPP modulation. These findings suggest that monitoring decisions are consistent with previously established regulatory preferences and are associated with adaptive short-term neural consequences.

Behavioral diversity is maintained by a conditional strategy in a freshwater zooplankton

Many populations have intraspecific diversity in phenotype and ecological strategy, but the mechanisms maintaining such diversity are not fully understood. Multiple behaviors can be maintained either as a conditional strategy, where fitness depends on an individual’s phenotype, or as a mixed strategy, where alternative behaviors have similar fitness independent of phenotype. Using high-resolution depth and time sampling, we characterize 2 distinct diel vertical migration behaviors in a population of freshwater zooplankton (Daphnia pulicaria). Individuals in this population differ in their color phenotype and migratory behavior with red morphs upregulating hemoglobin and undergoing a deep migration and pale morphs not producing hemoglobin and undergoing a shallow migration. We experimentally manipulated the behavior of each phenotype in the field and measured population growth in their natural migration behavior as well as population growth in their alternative behaviors. Experimental populations of pale and red morphs under their natural migrations had roughly equal fitness, despite vast differences in environmental conditions. When forced to switch behaviors, pale morphs suffered reduced fitness, whereas red morphs had similar fitness compared with their natural migration. Our results suggest that although behavioral diversity may be promoted by the opportunity for alternative behaviors of equal fitness, the distinct physiological conditions required for survival in alternative behaviors limit the capacity for individual behavioral switching and likely maintain behavioral diversity as a conditional strategy.