Main Project:

Patients who suffer from Alzheimer’s disease, dementia, and a broad spectrum of psychosis, including schizophrenia, show a range of memory deficits along with damage to the hippocampal-entorhinal cortex (HPC-EC). However, little is known about how specific memories are accessed and formed to accomplish given tasks, especially at the systems level. Malfunctions in memory formation and recall functions have the potential to have a significant impact on a person’s daily life. Our lab focuses on the neural dynamics for successful memory access and retrieval during episodic working memory tasks to elucidate the neural circuit mechanism in the hippocampal-cortical network.

PI's Previous Studies:

  • Discovery of Gamma Synchrony during Successful Memory Retrieval  (Yamamoto et al, Cell, 2014)

Neural Oscillation and Synchronous Activity in HPC-EC Network: Network oscillations are proposed to underlie the temporal binding of spatially distributed neuronal populations to enable information processing for cognition and its ensuing behavior. In addition, certain oscillations are hypothesized to allow conscious perception and awareness of associations between external cues and internal goals encoded in the synchronized brain areas. In particular, gamma oscillations correlate with perception, memory, and attention. Emerging empirical evidence suggests that gamma band oscillation (30-100Hz) power increases during working memory tasks in both humans and rodents, and other mammals as well. We found that increased oscillatory phase coherency and/or synchrony of gamma band oscillations within HPC - EC circuits plays a crucial role in successfully processing the working memory function. We discovered that the gamma phase synchrony at the T-junction of a spatial working memory task is tightly coupled with animal’s successful working memory execution during active running state (Figure 1).

Figure 1: Gamma Phase Synchrony in HPC-EC Network during DNMP T-Maze Task (A) A delayed Non-Match to Place (DNMP) task. (B) Spatial segmentation for detailed analysis. (C) An example of a success case run and gamma phase synchrony between HPC-EC network. Statistically significant gamma phase synchrony indicated by a red arrow.
  • Discovery of Reverberating Cortico - hippocampal Ripple Burst (Yamamoto and Tonegawa, Neuron, 2017)

Another prominent hippocampal neural activity is the sharp-wave ripple associated memory replay of place cells during off-line state. the firing sequences of place cells during running behavior are re-expressed at an accelerated rate during quiet awake pauses in locomotion or during subsequent slow-wave sleep. This “replay” of place cells co-occurs with short-lasting (50~100 ms), high-frequency oscillations (100~200 Hz) called sharp-wave ripples or ripples in the local field potential (LFP). These sharp-wave ripple associated replays have been reported during slow-wave sleep or non-REM sleep, and quiet awake. The replay of hippocampal activity patterns has also been reported in relation to memory tasks. When the linear track explored by an animal is relatively short (around 1 meter), the firing sequence of a set of place cells covering the entire track can be replayed within a single ripple event of 50-100 ms. However, for a longer track, the replay of an extended place cell sequence of the track during the quiet awake state spans multiple ripple events which are called ripple-bursts that span 200~500 ms. We previously discovered that MEC layer III input to CA1 is crucial for concatenating short range SWR associated replay events into long-range SWR burst associated replay episodes (Figure 2).

Research 2
Figure 2: Quiet Awake State Specific Ripple Burst Associated Alternating Burst Activities in MEC-CA1 Network. (A) An example of triplet sharp-wave ripple. Top panel: color-coded ripple band LFPs of superficial MEC and dorsal CA1 cell layer. Middle panel: Associated superficial MEC MUA with elevated burst activities (red downward arrow heads). Green dotted trace is smoothed sum of MEC MUA, Bottom panel: Detected CA1 MUA and its smoothed sum (blue dotted traces) with elevated ripple activities (a red upward arrow head). (B) Cross-correlation between MEC and CA1 using ripple-band LFP peak power times during QAW. Blue trace: 10 ms bin. Red trace: smoothed trend line. (C) An example of triplet SWR associated long-range replay by Bayesian decoding in CA1.
  • Development of Semi-Automatic Motorized Microdeive Array for Freely Behaving Rodent. (Yamamoto and Wilson, J. NeuroPhys, 2008)

Large-scale multiple single-unit recording has been one of the most powerful in vivo electro-physiological techniques for investigating neural circuits. The demand has been increasing for small and lightweight chronic recording devices that allow fine adjustments to be made over large numbers of electrodes across multiple brain regions. To achieve this, we developed precision motorized microdrive arrays that use a novel motor multiplexing headstage to dramatically reduce wiring while preserving precision of the microdrive control. Versions of the microdrive array were chronically implanted on both rats (21 microdrives) and mice (7 microdrives) and relatively long term recordings were taken.

Figure 3: (A) An exploded view of the mouse microdrive array: Basically, the overall structure is identical to the rat version except for the scale and the additional interface board. This way of connection is to reduce overall weight while the animal is in the home cage. (B) An actual view of the mouse microdrive array: The bottom cannula has intentionally made angled tip to the right. In addition, the red-colored tubings are polyimide 30Ga tubes for the testing. The working distance and the relative length of 30Ga tube and polyimide tube are shown in this panel as well. (C) An actual view of the rat microdrive array: A twenty-one microdrive array version.