More Like this

1. Leptin resistance and hippocampal behavioral deficits

   https://doi.org/10.1016/j.physbeh.2017.03.002  

   Van Doorn, Catherine ; Macht, Victoria A. ; Grillo, Claudia A. ; Reagan, Lawrence P. ( July 2017 , Physiology & Behavior)
2. Rapid Spectral Dynamics in Hippocampal Oscillons

   https://doi.org/10.3389/fncom.2022.880742  

   Zobaer, M S ; Domenico, Carli M ; Perotti, Luca ; Ji, Daoyun ; Dabaghian, Yuri ( June 2022 , Frontiers in Computational Neuroscience)

   Gupta, D_S (Ed.)

   Neurons in the brain are submerged into oscillating extracellular potential produced by synchronized synaptic currents. The dynamics of these oscillations is one of the principal characteristics of neurophysiological activity, broadly studied in basic neuroscience and used in applications. However, our interpretation of the brain waves' structure and hence our understanding of their functions depend on the mathematical and computational approaches used for data analysis. The oscillatory nature of the wave dynamics favors Fourier methods, which have dominated the field for several decades and currently constitute the only systematic approach to brain rhythms. In the following study, we outline an alternative framework for analyzing waves of local field potentials (LFPs) and discuss a set of new structures that it uncovers: a discrete set of frequency-modulated oscillatory processes—the brain wave oscillons and their transient spectral dynamics 

   more » « less
3. Anxiety Cells in a Hippocampal-Hypothalamic Circuit

   https://doi.org/10.1016/j.neuron.2018.01.016  

   Jimenez, Jessica C. ; Su, Katy ; Goldberg, Alexander R. ; Luna, Victor M. ; Biane, Jeremy S. ; Ordek, Gokhan ; Zhou, Pengcheng ; Ong, Samantha K. ; Wright, Matthew A. ; Zweifel, Larry ; et al ( February 2018 , Neuron)
4. Prefetching Using Principles of Hippocampal-Neocortical Interaction

   https://doi.org/10.1145/3593856.3595901  

   Wu, Michael ; Joshi, Ketaki ; Sheinberg, Andrew ; Cox, Guilherme ; Khandelwal, Anurag ; Pothukuchi, Raghavendra Pradyumna ; Bhattacharjee, Abhishek ( June 2023 , ACM)
5. Bidirectional synaptic plasticity rapidly modifies hippocampal representations

   https://doi.org/10.7554/eLife.73046  

   Milstein, Aaron D ; Li, Yiding ; Bittner, Katie C ; Grienberger, Christine ; Soltesz, Ivan ; Magee, Jeffrey C ; Romani, Sandro ( December 2021 , eLife)

   A new housing development in a familiar neighborhood, a wrong turn that ends up lengthening a Sunday stroll: our internal representation of the world requires constant updating, and we need to be able to associate events separated by long intervals of time to finetune future outcome. This often requires neural connections to be altered. A brain region known as the hippocampus is involved in building and maintaining a map of our environment. However, signals from other brain areas can activate silent neurons in the hippocampus when the body is in a specific location by triggering cellular events called dendritic calcium spikes. Milstein et al. explored whether dendritic calcium spikes in the hippocampus could also help the brain to update its map of the world by enabling neurons to stop being active at one location and to start responding at a new position. Experiments in mice showed that calcium spikes could change which features of the environment individual neurons respond to by strengthening or weaking connections between specific cells. Crucially, this mechanism allowed neurons to associate event sequences that unfold over a longer timescale that was more relevant to the ones encountered in day-to-day life. A computational model was then put together, and it demonstrated that dendritic calcium spikes in the hippocampus could enable the brain to make better spatial decisions in future. Indeed, these spikes are driven by inputs from brain regions involved in complex cognitive processes, potentially enabling the delayed outcomes of navigational choices to guide changes in the activity and wiring of neurons. Overall, the work by Milstein et al. advances the understanding of learning and memory in the brain and may inform the design of better systems for artificial learning. 

   more » « less