Attention; Axons; Brain; Memory; Neurobiology; Neurosciences; Synapses
Our laboratory is investigating the cellular mechanisms of cortical function.
How Does the Brain Work?
How does the brain work? Most neuroscientists, including us, became interested in studying the nervous system because of this question. In our laboratory, we reframe this question as: How does an animal gather and process information, make a decision, and act on that decision? It is on this question that our laboratory is attempting to gain insight by examining how an animal performs a decision making task. One example of such a task is detecting a sound embedded in a complex series of sounds and responding to receive a reward.
Extensive Research Description
Optimal State for Neural and Behavioral Performance
One of the first things we noticed was that the ability of animals to perform the task varied rapidly (seconds) and continuously, even though the animals were clearly awake the entire time. We imagine this is similar to either “seminar behavior” where your attention on the lecture waxes and wanes periodically, or “drowsy driving”, where you periodically lose focus on the task at hand. By measuring brain state electrically, and measuring the diameter of the pupil, we found that there is an optimal state for performance of the task, and that this optimal state occurred when the animal is “in the zone”, meaning exhibiting neither too little nor too much arousal. We are now examining the precise neural circuits (e.g. acetylcholine and norepinephrine) that may be responsible for the determination of this optimal state for performance.
Cortical Coding Efficiency:
Stimulation of the cortex with natural stimuli, particularly in the waking, attentive state, gives rise to highly efficient and reliable neuronal responses. We are examining the mechanisms underlying this efficiency and reliability.
Neural Circuits of Brain Processing:
By examining how neurons operate electically, and how they talk to each other chemically, we are uncovering the neural circuits responsible for behavior. We are particularly interested in the neural circuits that transforms a sensory input into a decision that is then implemented in an action. We find great hope that revealing these neural circuits will increase our understanding of not only the ordered, but also the disordered, human brain.
- Cortical Membrane Potential Signature of Optimal States for Sensory Signal Detection. McGinley MJ, David SV, McCormick DA. Neuron. 2015 Jul 1;87(1):179-92
- Competing Neural Ensembles in Motor Cortex Gate Goal-Directed Motor Output. Zagha E, Ge X, McCormick DA. Neuron. 2015 Nov 4;88(3):565-77.
- Waking State: Rapid Variations Modulate Neural and Behavioral Responses. McGinley MJ, Vinck M, Reimer J, Batista-Brito R, Zagha E, Cadwell CR, Tolias AS, Cardin JA, McCormick DA. Neuron. 2015 Sep 23;87(6):1143-61
- Zagha E, Casale AE, Sachdev RN, McGinley MJ, McCormick DA. (2013) Motor cortex feedback influences sensory processing by modulating network state. Neuron 79(3):567-78.
- Tahvildari B, Wölfel M, Duque A, McCormick DA. Selective functional interactions between excitatory and inhibitory cortical neurons and differential contribution to persistent activity of the slow oscillation. J Neurosci. 2012 Aug 29;32(35):12165-79.
- Frohlich, F., McCormick, D.A. Endogenous electric fields may guide neocortical network activity. Neuron. 2010 Jul 15;67(1):129-43.
- Haider B, Krause MR, Duque A, Yu Y, Touryan J, Mazer JA, McCormick DA. Synaptic and network mechanisms of sparse and reliable visual cortical activity during nonclassical receptive field stimulation. Neuron. 2010 Jan 14;65(1):107-21.
- Haider, B. and McCormick D.A. (2009) Rapid neocortical dynamics: cellular and network mechanisms. Neuron 62: 171-189.
- Yu, Y., Shu, Y., McCormick D.A. (2008) Cortical action potential backpropagation explains spike threshold variability and rapid-onset kinetics. Journal of Neuroscience 28: 7260-7272.
- Hasenstaub, A., Sachdev, R.N.S., McCormick, D.A. (2007) State changes rapidly modulate cortical neuronal responsiveness. J. Neurosci. 27: 9607-9622.