The emergence and influence of internal states

Abstract

Animal behavior is shaped by a variety of "internal states"-partially hidden variables that profoundly shape perception, cognition, and action. The neural basis of internal states, such as fear, arousal, hunger, motivation, aggression, and many others, is a prominent focus of research efforts across animal phyla. Internal states can be inferred from changes in behavior, physiology, and neural dynamics and are characterized by properties such as pleiotropy, persistence, scalability, generalizability, and valence. To date, it remains unclear how internal states and their properties are generated by nervous systems. Here, we review recent progress, which has been driven by advances in behavioral quantification, cellular manipulations, and neural population recordings. We synthesize research implicating defined subsets of state-inducing cell types, widespread changes in neural activity, and neuromodulation in the formation and updating of internal states. In addition to highlighting the significance of these findings, our review advocates for new approaches to clarify the underpinnings of internal brain states across the animal kingdom.

Keywords: brain-wide activity; internal states; neural circuits; neuromodulation.

Figure 1.. Features of an example internal state

Using fear in rodents as an example, we show how a central internal state can exhibit multiple features and influence a number of behavioral and physiological processes. Hallmark characteristics of an internal state, including persistence, scalability, and generalizability, are illustrated at left and pleiotropic effects associated with the state of fear are displayed on the right.

Figure 2.. Approaches to infer the presence of internal states from observable behavior

(A) Measuring overt behavior by tracking animal movement (examples: keypoint-based pose tracking in lemurs and nematodes). (B) Inducing need states through environmental control (examples: social or caloric deprivation in rodents). (C) Inferring internal state from transitions in observable movements (example: fly wing extension during courtship). (D) Inferring states from the co-occurrence of multiple behavioral features (example: hunting states of larval zebrafish). (E) Multiple states can interact with one another (example: a hungry rodent may show less fear when foraging under predation). (F) State expression can vary across individuals (example: a rodent’s position in a social hierarchy influences their aggressivity and response to stress).

Figure 3.. Collateralized projections and brain-wide influence of state-inducing neurons

(A) Schematic of projections from AGRP+ hunger-promoting neurons (red) in the arcuate nucleus of the mouse hypothalamus. (B) Schematic of projections from P1 social arousal-promoting neurons (red) in the fly. (C) Schematic of projections from the serotonergic NSM neuron (red) that promotes dwelling states in the nematode. (D) Stimulating thirst-promoting neurons in the lamina terminals recapitulates the effects of natural thirst on behavior (bottom left) and neural populations recorded in multiple brain regions (right; from Allen et al.. 2019).

Figure 4.. Fan-in and fan-out organization of internal states and neuromodulatory neurons

Top: internal states are influenced by the integration of multiple sensory, motor, and internal factors and themselves influence multiple behaviors and physiological processes. Bottom: similarly, many state-inducing neuromodulatory cell types integrate inputs from multiple brain regions and send outputs to multiple downstream regions.

Figure 5.. The broad reach and diverse cellular effects of neuromodulators

(A) Examples of broadly projecting neuromodulatory neurons in larval zebrafish (Herget et al., 2017). adult fly (Deng et al., 2019), and mouse (Li et at., 2018). (B) Neuromodulation can target neurons across the spatial extent of the brain but. within target regions, acts at the scale of intracellular signaling. (C) Schematics of various neuromodulatory signaling mechanisms in neurons, from rapid (top) to persistent (bottom).

Figure 6.. Opposing brain states engage mutually exclusive neural populations

(A) Roaming and dwelling states in C. elegans are supported by opposing sets of neurons that mutually inhibit each other (Ji et al., 2021). (B) Separate brain-wide populations regulate roaming versus dwelling states in hunting larval zebrafish (Marques et al., 2020). (C) Exploration versus anxiety engage different populations of neurons in the mouse amygdala (Gründemann et al., 2019).

Figure 7.. Multiple mechanisms can support the persistence of internal states

(A) Schematics of persistent neural and behavioral responses to transient sensory stimuli. (B) One potential mechanism for generating neuronal persistence is stowty evolving biochemical signaling within neurons, which has been demonstrated to control the persistence of internal states in flies and mammals (Zhang et al. 2019, 2021; Thornquist et al. 2021). (C) Another potential mechanism is recurrent excitation among interconnected neurons, as has been recently demonstrated to maintain persistent defensive behaviors in flies and rodents (Jung et al., 2020; Kennedy et al., 2020).