1. Slow wave sleep oscillations coordinate neural ensembles
during memory consolidation
Sara Aton
University of Michigan
Department of Molecular,
Cellular, and Developmental Biology

2. Sleep states affect multiple facets of brain function
What is the role of state-specific brain activity in a basic brain function – forming new memories?
Sleep states affect multiple facets of brain function
Wake Slow wave sleep (SWS) / NREM REM
cortical neuron:
scalp voltage trace (EEG):
1 sec

3. (requires CA1 neuronal activity)
Consolidation of contextual fear memory (CFM)
CFC
CFM
contextual fear conditioning
contextual fear memory !
consolidation
(requires CA1 neuronal activity)
Novel context
Foot shock
Retrieval
Why is sleep necessary?
- “reactivation” of wake experience?
- rhythmic firing patterns?
- pattern causes synaptic depression (“synaptic homeostasis hypothesis”)

4. Our ability to record neural codes is steadily increasing… our ability to decipher those codes is not
Duration of stable recordings is also steadily increasing…
More neurons over behaviorally-relevant timescales = more data to store and manipulate, more parameters to test
Figure from:
Stevenson & Kording, 2011

5. Assessing memory-associated network activity patterns
Sham conditioning
CFC
~10 Gb/hr/recording
× 3 recording systems
× 24h/day, 365d/year
single-neuron
activity:
local field
potentials (LFPs):
Ognjanovski et al., 2014
Ognjanovski et al., 2017
Mandle et al., In Review

6. Augmented rhythmic firing during CFM consolidation
Sham conditioning
CFC
CFC:
Principal neurons Fast-spiking interneurons
NREM REM wake NREM REM wake
baseline
post-CFC
Coherence
Ognjanovski et al., 2014
Ognjanovski et al., 2017
Mandle et al., In Review

7. Consolidation is associated with firing pattern stabilization
total NREM wake
Ognjanovski et al., 2014
Ognjanovski et al., 2017
Mandle et al., In Review

8. Model: CA1 FS interneurons  network oscillations  stability  consolidation!
consolidation
Novel context
Foot shock
Retrieval
FS (PV+)
network oscillations
+ stable firing patterns
synaptic plasticity and memory storage

9. Are PV+ FS interneuron-driven oscillations needed for memory formation?
CA1
hM4Di expressed in CA1 PV+ interneurons in Parv-IRES-CRE transgenic mice  pharmacogenetic silencing following CNO administration
Ognjanovski et al. 2017

10. PV+ interneuron activity is required for CFM consolidation
Ognjanovski et al. 2017

11. CFC-induced oscillations are mediated by PV+ interneurons
local field
potentials (LFPs):
REM NREM
Ognjanovski et al. 2017

12. CFC-induced oscillations are mediated by PV+ interneurons
local field
potentials (LFPs):
REM NREM
Ognjanovski et al. 2017

13. CFC-induced increases in stability are mediated by PV+ interneurons
Ognjanovski et al. 2017

14. PV+ interneurons mediate consistent reactivation of NREM network patterns
Ognjanovski et al. 2017

15. PV+ interneurons mediate consistent reactivation of NREM network patterns
20 min
20 min
Ognjanovski et al. 2017

16. PV+ interneurons mediate consistent reactivation of NREM network patterns
20 min
20 min
Ognjanovski et al. 2017

17. Can PV+ interneurons drive post-CFC network changes?
ChR2
ChR2 expressed in CA1 PV+ interneurons in Parv-IRES-CRE transgenic mice  rhythmic optogenetic activation by blue light

18. PV+ interneurons can amplify CA1 oscillations
Neuronal firing: LFP activity:
Ognjanovski et al. 2017

19. Coherence induced by oscillations increases stability in the network
Ognjanovski et al. 2017

20. Long-term effects of rhythmic inhibition
measure stability and connection strength
measure stability and connection strength
Ognjanovski et al. 2017

21. How do memory traces go from local, small and sparse to broadly-distributed and widely accessible?

22. Thank you! Members of the Aton lab: With support from:
CFM:
Nicollette Ognjanovski
Samantha Schaeffer
Nora Lashner
Hari Thiruchelvam
James Delorme
Varna Kodoth
Sha Jiang
OSRP:
Jaclyn Durkin
Brittany Clawson
Carlos Puentes Mestril
Aneesha Suresh
Julie Colbath
Amanda Morrison
Aditi Rao
Emily Pickup
U of M Physics Department
Stability and network analysis:
Michal Zochowski
Dan Maruyama
Sima Mofakham
Quinton Skilling
Jiaxing Wu
Questions? me!