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Impulsivity, Addiction and Brain Circuits of Decision Making
Abstract
Although many studies in neuroscience are based on comparing neuronal responses to single, isolated sensory or motor events, multiple events frequently occur in close temporal proximity in freely moving animals. This often obscures the precise temporal correlation between each event and the relevant brain activity. By simulating neuronal responses in multi-event tasks, we show that perievent time histograms (PETHs) greatly distort the underlying true responses. We propose a multi-event deconvolution method that can separate the contribution of each event to the overall neuronal activity. The improvements over PETH in analyzing real data are demonstrated using simulated data and a sample electrophysiological recording obtained from rats in a task involving responses to a reward predictive cue
Further Information: http://jn.physiology.org/content/104/3/1790.short
http://www.jneurosci.org/content/31/18/6820.abstract
Biography
Dr. Ali Ghazizadeh received his BSc inelectrical engineering with a focus on analogue circuit design from Sharif Universityof Technology in 2002. He then joined the computational motor control lab in JohnsHopkins University under the supervision of Prof. Reza Shadmehr where he received his MSc in Biomedical Sciences. During his Master's degree, he studied the mechanisms of motor memory and skill learning through a combination of psychophysical and modeling methodologies. In 2005, he was admitted to the Joint Bioengineering program in University of California at Berkeley and San Francisco for doctoral studies. There, he studied the brain circuits of impulsivity control using electrophysiological recordings in behaving rodents and computational modeling. He received his PhD from the Bioengineering program under thesupervision of Prof. Howard Fields in 2011
His current research interestinvolves the mesolimbic circuitry of reward and decision making
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