Nick Steinmetz
Attention: Cortical Microcircuits

Personal Background

I studied Bioengineering at the University of Pennsylvania before coming to Stanford in 2007. I began a collaboration between the Brains In Silicon lab and Dr. Tirin Moore's neurophysiology lab, and have been pursuing experimental and modeling studies since then. My auxilliary research activities have included the Woods Hole "Methods in Computational Neuroscience" course (2009), the FENS-IBRO "Neural Coding in Sensory Systems" course (2012), many neuroscience courses at Stanford, and also assisting the teaching of two neuroscience courses here. For several years I organized Stanford's "Brain Day" program, bringing real brain samples to 7th grade classrooms around Palo Alto.

Research Goals

Selective attention is a key cognitive faculty that allows us to perceive and respond to only the chosen portion of the information that constantly and torrentially impinges on our brain via sensory systems. In the visual domain, this means that though our entire retinae are stimulated continually when our eyes are open, our higher visual centers typically ignore almost all of this information, instead responding to only those select parts that grab our attention. The improvements in our perception and memory of attended stimuli versus ignored stimuli have been examined extensively with psychophysical studies for many years, but the neural mechanisms underlying these perceptual improvements remain mysterious. Over the last twenty five years, neuroscientists have done much to elucidate the physiological correlates of these perceptual changes by recording the neural activity of the visual and frontal cortices, as well as of subcortical structures such as the superior colliculus and thalamus.

In silico model captures attentional modulation of firing rates in cortical area V4. The subject is cued to direct his covert spatial attention to one of two visual targets on a computer screen, either inside (Attend Toward) or outside (Attend Away) the recorded neuron's receptive field (dashed line). Across a range of visual stimulus contrasts, firing rates are higher in the Attend Toward condition (red traces, lower plots) compared to the Attend Away condition (black traces). The in silico model replicates this modulation.

The present challenge, then, is to determine the mechanisms that generate these neural correlates of attention. Earning this understanding would improve our ability to understand what approaches are needed to effectively treat disorders of attention. We hope to make progress toward this goal with a combination of extracellular recordings in awake, behaving animals and computational models of spiking networks to explain the neurophysiological data and make novel predictions. In particular, we are carrying out recordings with linear array electrodes that allow for the simultaneous measurement of neural activity in multiple parts of the visual cortical microcircuit (i.e., in separate cortical layers and neuronal types). Our models will seek to include these layers and the pattern of interactions between them in order to better understand the microcircuit mechanisms underlying visual selective attention.

Project Status

I am currently recording from an animal trained on a selective attention task, analyzing these data, and training another animal to perform the task. Simultaneously, I am developing spiking neuron models to account for the neural data on Neurogrid hardware, as demonstrated below and in the Neurogrid pages.

Selected Publications

ID Article Full Text

 

Steinmetz NA, Moore T (2012) Pattern of attentional and presaccadic modulation of visual responses in macaque V4 measured simultaneously across cortical layers. Poster, Cosyne Conference.


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Steinmetz NA, Moore T (2010) Changes in the Response Rate and Response Variability of Area V4 Neurons During the Preparation of Saccadic Eye Movements. Journal of Neurophysiology 103:1171-1178


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