Although we know a great deal about how individual neurons encode information, how networks of cells represent incoming stimuli in population activity has rarely been investigated experimentally. Indeed, although improved multi-electrode techniques and theoretical models are now available to help answer this important question, exactly how cortical networks encode information to influence the accuracy of behavioral responses remains unknown. We will employ state-of-the-art electrophysiological and behavioral techniques to record simultaneously the activity of multiple neurons in multiple visual cortical areas of behaving monkey in combination with computational models of network function to understand how neural circuits produce emergent properties. We plan to examine for the first time how populations of neurons in different cortical areas encode information to influence behavioral decisions. We will perform experiments of a high degree of difficulty to simultaneously record neuronal activity in multiple cortical areas along the same cortical processing stream (e.g., V1, V4, and IT;infero-temporal cortex, or IT, is the terminal processing station of the 'object'pathway) while monkeys will perform an image discrimination task. These experiments will offer us the unique opportunity to examine the coding of visual information at each stage of visual processing and the flow of information between different cortical areas, and thus investigate how the entire network engaged in image processing works to create and update visual representations that are relevant for behavior. The experiments will also allow us to examine for the first time the contribution of different types of cells (e.g., excitatory and inhibitory) to population coding and their impact on behavioral performance. We will examine for the first time the relationship between the properties of the population code in multiple cortical areas and behavioral decisions. We will perform experiments of a high degree of difficulty by simultaneously record neuronal activity in several cortical areas along the same cortical processing stream during an image discrimination task. These studies will offer us the unique opportunity to investigate how interactions between multiple neuronal networks influence behavioral decisions.
We will examine for the first time the relationship between the properties of the population code in multiple cortical areas and behavioral decisions. We will perform experiments of a high degree of difficulty by simultaneously record neuronal activity in several cortical areas along the same cortical processing stream during an image discrimination task. These studies will offer us the unique opportunity to investigate how interactions between multiple neuronal networks influence behavioral decisions.
| Chelaru, Mircea I; Dragoi, Valentin (2016) Negative Correlations in Visual Cortical Networks. Cereb Cortex 26:246-56 |
| Hansen, Bryan J; Chelaru, Mircea I; Dragoi, Valentin (2012) Correlated variability in laminar cortical circuits. Neuron 76:590-602 |
| Wang, Ye; Iliescu, Bogdan F; Ma, Jianfu et al. (2011) Adaptive changes in neuronal synchronization in macaque V4. J Neurosci 31:13204-13 |
