2006 Nature Publishing Group http www nature com natureneuroscience ARTICLES Optimal decoding of correlated neural population responses in the primate visual cortex Yuzhi Chen Wilson S Geisler Eyal Seidemann Even the simplest environmental stimuli elicit responses in large populations of neurons in early sensory cortical areas How these distributed responses are read out by subsequent processing stages to mediate behavior remains unknown Here we used voltagesensitive dye imaging to measure directly population responses in the primary visual cortex V1 of monkeys performing a demanding visual detection task We then evaluated the ability of different decoding rules to detect the target from the measured neural responses We found that small visual targets elicit widespread responses in V1 and that response variability at distant sites is highly correlated These correlations render most previously proposed decoding rules inefficient relative to one that uses spatially antagonistic center surround summation This optimal decoder consistently outperformed the monkey in the detection task demonstrating the sensitivity of our techniques Overall our results suggest an unexpected role for inhibitory mechanisms in efficient decoding of neural population responses A fundamental feature of mammalian cerebral cortex is its use of orderly topographic maps to represent sensory and motor information1 3 Because cortical neurons tend to respond to a broad range of stimuli4 or movements5 and because there are generally multiple neurons tuned to the same range of parameters within one cortical column6 7 even the simplest sensory stimulus or motor response elicits activity that is distributed over a substantial population of neurons5 8 9 Electrophysiological studies in behaving primates suggest that perceptual and motor responses are indeed mediated by populations of neurons rather than by single neurons10 13 These observations raise several fundamental questions how are stimuli and movements encoded by neural population responses what are the optimal strategies for decoding pooling the population responses and how efficient are different non optimal pooling strategies Several models of neural pooling in the brain have been proposed11 14 19 These include monitoring only the most sensitive neurons at the extreme a single neuron 16 simple averaging over the active neural population11 and weighted summation where the contribution of each neuron in the pool is proportional to its sensitivity17 or proportional to the parameter value at the peak of its tuning function14 15 18 19 Importantly evaluating these and other decoding rules has been held back because of limited experimental techniques for reliably monitoring neural population responses Optical imaging with voltage sensitive dyes VSD measures neural population responses at high spatial and temporal resolutions20 Only recently however has this technique been applied successfully to behaving animals21 22 In the current study we use for the first time VSD imaging in behaving monkeys to investigate possible decoding rules for population responses in V1 RESULTS Experimental design Two monkeys were trained to detect a small oriented visual target indicating target presence by making a saccadic eye movement to the target location as soon as it was detected Fig 1a While the monkeys performed this task VSD imaging was carried out through a cranial window over V1 Fig 1b Performance in the detection task is likely to depend on neural signals provided by topographic maps in V1 that can be directly identified by optical imaging23 25 Because V1 is retinotopically organized information regarding the presence or absence of the target is confined to several square millimeters of cortex within V1 Optical imaging allows us to localize this cortical region precisely and visualize the pattern of population activity within this entire region in real time as behavior unfolds Furthermore in primates V1 provides the main source of visual information to other cortical areas and thus optical imaging may allow us to visualize most of the information that is potentially available to subsequent processing stages in our task However because VSD signals are likely to be dominated by subthreshold synaptic activity it is possible that some of this information is not transmitted from V1 To evaluate the efficiency of possible decoding mechanisms and to determine the optimal Bayesian decoding strategy we began by analyzing in detail the statistical properties of neural population responses Statistical properties of V1 population responses The major goal in this study was to determine how target related neural population responses in V1 could be pooled by subsequent processing stages in order to mediate visual detection The efficiency of a pooling Department of Psychology and Center for Perceptual Systems 1 University Station A8000 University of Texas at Austin Austin Texas 78712 USA Correspondence should be addressed to E S eyal mail cps utexas edu Received 11 September accepted 26 September published online 22 October 2006 doi 10 1038 nn1792 1412 VOLUME 9 NUMBER 11 NOVEMBER 2006 NATURE NEUROSCIENCE ARTICLES a Offset of Gabor Onset of Gabor Fixation point dims 300 ms b Lunate 300 ms Locate fixation point 300 ms 500 ms 0 1 000 ms Figure 1 Behavioral task and recording chamber a Task and stimulus see Methods b The cranial window over V1 in the left hemisphere in one monkey The cortex is seen through a transparent artificial dura44 A typical imaged area of 10 10 mm is indicated by the black square method depends on three key properties of V1 population responses i the amplitude and spatial spread of the response which determines the size of the neural population that could contribute to detection ii the variability of the population response which influences the quality of the signals provided by neurons at each imaging site a single pixel or a binned group of pixels and iii the magnitude and extent of spatial correlations in response variability which can have a large Spread of V1 population response To quantify the amplitude of the VSD response in single trials the average response was computed for each site in the imaged area over a short interval following the onset of the neural response and prior to the behavioral response see Methods The neural response to the small target increased with contrast and extended over an area of several square millimeters Fig 2c left column indicating
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