Tag Archives: spatial navigation

#PLOS #SfN15 Recap: Hidden variables of behavior

Originally published on the PLOS Neuroscience Community

The Society for Neuroscience meeting is unique in both is breadth and depth. There are sessions on literally everything Neuro, each delving with exquisite detail and nuance into their given topic. While this level of focus is great for those seeking comprehensive coverage of their niche, it can be daunting for those looking for a broader sampling of the field’s cutting edge. The Hidden Variables of Behavior symposium was one of the rare sessions to stray from the single-track convention to elegantly bridge seemingly disparate topics, methodologies and applications, producing a standout session with exceptionally broad appeal. It accomplished this by exploring a theme that is perhaps the unifying motivation underlying nearly all Neuroscience research: how does the brain engender behavior? How does neural activity give rise to the thoughts, interactions with our environment, and engagements with others that define our experiences? In an enthralling series of talks by Loren Frank, Mark Schnitzer, Yang Dan and Catherine Dulac, the symposium covered topics ranging from learning and memory to sleep and social behavior. This session had it all.

Rapidly alternating representations of present and past in hippocampal-cortical networks

frankLoren Frank kicked off the symposium by exploring how the hippocampus supports our ability to remember the past and plan for the future. Hippocampal cells have a remarkable ability to replay past experiences via high-frequency oscillations during sharp waves known as ripples. When an animal traverses a path its hippocampal neurons will fire in a characteristic sequence that codes its trajectory; later, at rest or while sleeping, this spiking sequence will repeat, with the sequence sped up approximately twenty times the original rate! Disrupting hippocampal ripples impairs sequence learning, indicating that they’re critical for acquiring memories. However, the mechanisms, at both regional and whole-brain levels, by which sharp wave ripples (SWRs) help to consolidate memories are unclear.

Place_Cell_Spiking_Activity_Example

Much attention has been paid to neurons in hippocampal subregions CA1 and CA3, which are excitable by high-speed motion and positively modulated by SWRs. However, Frank’s group identified a new group of hippocampal neurons – CA2P and CA2N – that are also positively and negatively modulated by SWRs, respectively. Notably, the CA2N population has an exceptionally high level of baseline activity and preferentially fires during rest or low speed motion. Because of their distinct function, these rebellious cells may be crucial for ongoing processing of the current state while maintaining representations of the past and future.

Although some (including yours truly) may hold a hippocampo-centric view of memory, Frank reminds us that memory is “not just a hippocampal thing.” Looking to the rest of the brain, his group found that SWRs recruit 35% of prelimbic regions, including cells that are both excited and inhibited by SWRs. Similar to the distinct populations of CA2P and CA2N cells, prefrontal cortex neurons may activate during either high-speed motion or immobility. This balance of excitation and inhibition in the hippocampus and surrounding cortex may promote rapid transitions between representations of the past and future, and facilitate their integration for learning and planning.

Large-scale ensemble neural dynamics underlying learning and long-term associative memory

schnitzer_mark_107Mark Schnitzer continued with this theme, presenting intriguing findings regarding the spatiotemporal properties of neural adaptations subserving learning. However, equally impressive are the advanced imaging tools his lab is developing to explore these issues. Their techniques allow neural recordings in behaving animals at unprecedented spatial depths and extents over long time scales. For instance, their current best is recording 1202 hippocampal cells in a freely moving mouse. Someone give this man the “I-recorded-the-most-neurons” award!

Using these tools, Schnitzer has been exploring hippocampal morphological and physiological changes that contribute to learning. CA1 neurons are a likely target for spatial learning, as they show place-cell activity, preferentially responding to particular regions of an animal’s environment. Surprisingly, dendrites in subregion CA1 are remarkably stable, suggesting that dendritic plasticity is unlikely to be the critical factor underlying learning. However, CA1 spine turnover is relatively rapid – on the order of 8-10 days – in comparison to cortical spines, of which 50% are permanent over a month. Schnitzer explained that although these cells are temporally stochastic in that they sometimes take breaks from their place-coding activity, when they return to the neuronal “spatial ensemble” they always return to encode the same place. What’s more, CA1 spatial representations are refined by learning, becoming both more accurate and reliable in their coding. I’ll be eagerly following Schnitzer’s work to see how their ongoing methodological innovations and applications advance our understanding of the hippocampal dynamics supporting long-term memories.

Neural circuits for sleep control

YIR_RH_DanYang Dan turned from this fast-paced discussion of rapid neural plasticity, spatial navigation and learning to examine neural regulation of sleep. Historically, neurons that trigger alertness and waking have been easy to identify, but researchers have struggled to track down those “sleep neurons.” Past lesion and c-fos studies have shown that hypothalamic – particularly preoptic – neurons are important for inducing sleep.

Combining optogenetics with electrophysiology, Dan’s lab has expanded upon these findings to pinpoint both the responsible cell types and their specific sleep-inducing effects. In particular, activating GABAergic preoptic cells projecting to the tuberomammillary nucleus (also of the hypothalamus) promotes non-REM sleep initially, and REM sleep later. The midbrain’s ventrolateral periaqueductal gray also promotes sleep, but only the non-REM type. Dan’s findings together suggest that mutual inhibition across these key hypothalamic and brainstem regions regulates transitions across three general brain states of waking, REM sleep and non-REM sleep.

Long-term changes in the representation of social information in the mouse medial amygdala

DulacAfter all this talk about sleep, my hypothalamic sleep neurons had begun batting the morning’s adenosine antagonists. Fortunately, Catherine Dulac’s captivating talk exploring the bases of social interactions and sex-specific behavior kept me alert and engaged. Two key circuits working in concert to process social information, she explained, are the olfactory and vomeronasal systems. This latter system in particular may act as a switch to promote appropriate (and suppress inappropriate) sex-specific behavior.

Dulac’s research, fusing molecular, genetic and electrophysiological techniques, has identified the medial amygdala as a critical stop along the vomeronasal circuit for mediating sex-specific social signaling in mice. Medial amygdalar encoding of social cues is not only sexually dimorphic, but is also regulated by salient social experiences including mating and co-housing. Furthermore, the efficiency of medial amygdalar signaling also changes after mating in a sex-specific manner, increasing in males but decreasing in females. Together, Dulac’s work has pinpointed the medial amygdala as an indispensible hub within an extensive neural circuit that regulates social behavior and in turn, is modulated by sexual and social experience.

Every SfN has at least one session that reminds me why I love the brain and re-ignites my passion for Neuroscience. This year, the Hidden Variables of Behavior symposium was it! It may be a year away, but I’m eagerly awaiting #SfN16 for similarly inspiring talks.

For an abbreviated play-by-play, visit my Storified live-tweeting of the symposium’s highlights.

References

Anderson EB, Grossrubatscher I, Frank L (2015). Dynamic Hippocampal Circuits Support Learning- and Memory-Guided Behaviors. Cold Spring Harb Symp Quant Biol. 79:51–58. doi: 10.1101/sqb.2014.79.024760

Attardo A, Fitzgerald JE, Schnitzer MJ (2015). Impermanence of dendritic spines in live adult CA1 hippocampus. Nature. 523:592–596. doi: 10.1038/nature14467

Bergan JF, Ben-Shaul Y, Dulac C (2014). Sex-specific processing of social cues in the medial amygdala. eLife. 3:e02743. doi: http://dx.doi.org/10.7554/eLife.02743

Brennan PA (2001). The vomeronasal system. Cell Mol Life Sci. 58(4):546–555.

Ego-Stengel V, Wilson MA (2010). Disruption of ripple-associated hippocampal activity during rest impairs spatial learning in the rat. Hippocampus. 20(1):1–10. doi: 10.1002/hipo.20707

Weber F, Chung S, Beier KT, Xu M, Luo L, Dan Y (2015). Control of REM sleep by ventral medulla GABAergic neurons. Nature. 526:435–438. doi: 10.1038/nature14979


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