Dr. Lisa Giocomo is an Assistant Professor of Neurobiology at Stanford University. Her lab is primarily interested in understanding how ion channels control neural coding and behavior. The system her lab uses to investigate this question is studying spatial coding by non-sensory medial entorhinal cortex neurons, and the discovery of an ion channel that directly maps to specific features of functionally-defined medial entorhinal neurons. Her previous work demonstrated that spatially selective medial entorhinal neurons use ion channel kinetics for spatial scaling, giving her lab unprecedented access to a system ideal for studying the connections between ion channels, coding and behavior. In particular, the Giocomo lab uses electrophysiology, behavior, imaging, gene manipulations, optogenetics, and computational modeling to study how single-cell biophysics and network dynamics interact to mediate spatial memory and navigation.

In August of this year, her lab published a paper in Nature Neuroscience showing a theoretical framework for understanding how landmark and self-motion cues combine during navigation to create spatial representations and guide behavior. The neurons that contribute to encoding position in space in the medial entorhinal cortex (MEC) include grid cells, head direction cells, border cells, and speed cells. However, the principles by which these MEC cells integrate self-motion versus landmark cues are not well understood. Giocomo examined how mouse behavior and MEC cell classes integrate self-motion with landmark cues by analyzing the neural activity and behavior of mice while they explored virtual reality environments.

Giocomo found principled regimes under which behaviorally measured position estimates and MEC codes differentially weight the influence of visual landmark and self-motion cues. Gain was manipulated by altering the transformation between the rotation of the running ball and translation of the VR track, with gain decreasing or increasing the visual scene translation. These manipulations placed visual and locomotor cues in conflict, depicted in Fig 2. Through structural analysis of gain change responses, she found that conflicts between locomotion and visual cues caused grid cells to remap in an asymmetric manner, with gain increases causing phase shifts and gain decreases causing grid scale changes. This finding that grid cells responded differently to gain increases and decreases, with an occasional loss of fields, and remapping and rescaling in gain decreases, led them to wonder about the mechanism driving this.

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Figure 2

She then developed a coupled-oscillator attractor model that explained how grid responses to gain manipulations could come from competition between conflicting self-motion and landmark cues. The model successfully predicted grid responses to an intermediate gain change. Finally, she used a path integration task to demonstrate behavioral asymmetry in the weighting of visual versus locomotor cues that matched grid and speed responses. These findings provide an important framework for understanding the dynamics of cue combination in MEC neural codes and navigational behavior.

You can read the complete paper here: https://www.nature.com/articles/s41593-018-0189-y

To learn more about Dr. Giocomo’s exciting work, please join us this Tuesday, 12/4/18, at 4pm in the Marilyn G. Farquhar Seminar room in CNCB.

Desi Chu is a first-year Neuroscience PhD student currently working in Dr. Sung Han’s lab.


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