The cortex is a laminated structure that is thought to underlie sequential information processing. Sensory input enters layer 4 (L4) from which activity quickly spreads to superficial layers 2/3 (L2/3) and deep layers 5/6 (L5/6) and other cortical areas eventually leading to appropriate motor responses. Sensory responses themselves depend on ongoing, i.e. spontaneous cortical activity, usually in the form of reverberating activit from within or distant cortical regions, as well as the state and behavioral context of the animal. Receptive field properties of neurons can rapidly and adaptively be reshaped when an animal is engaged in a behavioral task, indicating that encoding of stimuli is dependent on task- or context-dependent state. Responses also depend on ongoing cortical dynamics in a lamina-dependent fashion and differ between the awake and anesthetized state. The intricate neuronal interplay between behavioral context, ongoing activity, and sensory stimulus underlying cortical representations is unknown. Specifically, we do not know how neuronal circuits shape these emergent dynamics within and between laminae, and we do not know which neurons encode which aspect of a sensory stimulus. One shortcoming of all prior studies of sensory processing is that only a few neurons are sampled, and thus information about the interactions between neurons, and between neuron and global brain state is lacking. Here we address these challenges by developing new in vivo 2-photon imaging technology that allows rapid imaging and stimulation in multiple focal planes and new computational and information theoretic techniques to extract network dynamics at the single neuron and population level. These measures go beyond paired measures and take synergistic interactions between neurons into account. We use these new techniques to investigate the 3D single cell and population activity patterns in the auditory cortex in mice. We investigate the influence of single neurons relative to the synergistic influence of specific groups of neurons (the crowd) on network dynamics and ultimately behavior of the animal.

Public Health Relevance

Functioning of the normal, healthy brain, such as in sensory processing and motor actions, depends on the precise interactions of millions of nerve cells. Brain diseases are increasingly linked to changes in these complex interactions between large populations of nerve cells. The current project develops novel imaging tools and analysis concepts to simultaneously study large groups of nerve cells in the awake brain with high temporal and cellular resolution, and will lay the groundwork for deeper insights into how the brain processes information and may provide mechanistic insights into brain disorders such as cerebral palsy, epilepsy, autism, and schizophrenia.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project--Cooperative Agreements (U01)
Project #
3U01NS090569-03S1
Application #
9268816
Study Section
Special Emphasis Panel (ZNS1 (61))
Program Officer
Gnadt, James W
Project Start
2014-09-30
Project End
2017-07-31
Budget Start
2016-08-01
Budget End
2017-07-31
Support Year
3
Fiscal Year
2016
Total Cost
$152,000
Indirect Cost
$52,000
Name
University of Maryland College Park
Department
Biology
Type
Schools of Earth Sciences/Natur
DUNS #
790934285
City
College Park
State
MD
Country
United States
Zip Code
20742
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Francis, Nikolas A; Winkowski, Daniel E; Sheikhattar, Alireza et al. (2018) Small Networks Encode Decision-Making in Primary Auditory Cortex. Neuron 97:885-897.e6
Sheikhattar, Alireza; Miran, Sina; Liu, Ji et al. (2018) Extracting neuronal functional network dynamics via adaptive Granger causality analysis. Proc Natl Acad Sci U S A 115:E3869-E3878
Kazemipour, Abbas; Liu, Ji; Solarana, Krystyna et al. (2018) Fast and Stable Signal Deconvolution via Compressible State-Space Models. IEEE Trans Biomed Eng 65:74-86
Aghayee, Samira; Winkowski, Daniel E; Bowen, Zachary et al. (2017) Particle Tracking Facilitates Real Time Capable Motion Correction in 2D or 3D Two-Photon Imaging of Neuronal Activity. Front Neural Circuits 11:56
Francis, Nikolas A; Kanold, Patrick O (2017) Automated Operant Conditioning in the Mouse Home Cage. Front Neural Circuits 11:10
Meng, Xiangying; Winkowski, Daniel E; Kao, Joseph P Y et al. (2017) Sublaminar Subdivision of Mouse Auditory Cortex Layer 2/3 Based on Functional Translaminar Connections. J Neurosci 37:10200-10214