Anxiety and depression: A top-down, bottom-up model of circuit function.

A functional interplay of bottom-up and top-down processing allows an individual to appropriately respond to the dynamic environment around them. These processing modalities can be represented as attractor states using a dynamical systems model of the brain. The transition probability to move from one attractor state to another is dependent on the stability, depth, neuromodulatory tone, and tonic changes in plasticity. However, how does the relationship between these states change in disease states, such as anxiety or depression? We describe bottom-up and top-down processing from Marr's computational-algorithmic-implementation perspective to understand depressive and anxious disease states. We illustrate examples of bottom-up processing as basolateral amygdala signaling and projections and top-down processing as medial prefrontal cortex internal signaling and projections. Understanding these internal processing dynamics can help us better model the multifaceted elements of anxiety and depression.

Cortical ensembles orchestrate social competition through hypothalamic outputs.

Most social species self-organize into dominance hierarchies1,2, which decreases aggression and conserves energy3,4, but it is not clear how individuals know their social rank. We have only begun to learn how the brain represents social rank5-9 and guides behaviour on the basis of this representation. The medial prefrontal cortex (mPFC) is involved in social dominance in rodents7,8 and humans10,11. Yet, precisely how the mPFC encodes relative social rank and which circuits mediate this computation is not known. We developed a social competition assay in which mice compete for rewards, as well as a computer vision tool (AlphaTracker) to track multiple, unmarked animals. A hidden Markov model combined with generalized linear models was able to decode social competition behaviour from mPFC ensemble activity. Population dynamics in the mPFC predicted social rank and competitive success. Finally, we demonstrate that mPFC cells that project to the lateral hypothalamus promote dominance behaviour during reward competition. Thus, we reveal a cortico-hypothalamic circuit by which the mPFC exerts top-down modulation of social dominance.

Relocating cued goals induces population remapping in CA1 related to memory performance in a two-platform water task in rats.

The activity of CA1 neurons in the rodent hippocampus represents multiple aspects of learning episodes, including cue and place information. Previous reports on cue and place representation in CA1 have examined activity in single neurons and population recordings during free exploration of an environment or when actions are directed to either cue or place aspects of memory tasks. To better understand cue and place memory representation in CA1, and how these interact during goal-directed navigation, we investigated population activity in CA1 during memory encoding and retrieval in a novel water task with two visibly distinct platforms, using mRNA for immediate early genes Arc and Homer1a as markers of neural activity. After training, relocating cues to new places induces an extensive, perhaps global, remapping of the memory code that is accompanied by altered navigation and rapid learning of new cue-place information. In addition, we have found a significant relationship between the extent of reactivation and overall cue choice accuracy. These findings demonstrate an important relationship between population remapping in CA1 and memory-guided behavior.