Abstract
Previous research has suggested that the lateral occipital cortex (LOC) is involved with visual decision making, and specifically with the accumulation of information leading to a decision. In humans, this research has been primarily based on imaging and electroencephalography (EEG), and as such only correlational. One line of such research has led to a model of three spatially distributed brain networks that activate in temporal sequence to enable visual decision-making. The model predicted that disturbing neural processing in the LOC at a specific latency would slow object decision-making, increasing reaction time (RT) in a difficult discrimination task. We utilized transcranial magnetic stimulation (TMS) to test this prediction, perturbing LOC beginning at 400 ms post-stimulus onset, a time in the model corresponding to LOC activation at a particular difficulty level, with the expectation of increased RT. Thirteen healthy adults participated in two TMS sessions in which left and right LOC were stimulated separately utilizing neuronavigation and robotic coil guidance. Participants performed a two-alternative forced-choice task selecting whether a car or face was present on each trial amidst visual noise pre-tested to approximate a 75% accuracy level. In an effort to disrupt processing, pairs of TMS pulses separated by 50 ms were presented at one of five stimulus onset asynchronies (SOAs): −200, 200, 400, 450, or 500 ms. Behavioral performance differed systematically across SOAs for RT and accuracy measures. As predicted, TMS at 400 ms resulted in a significant slowing of RT. TMS delivered at −200 ms resulted in faster RT, indicating early stimulation may result in priming and performance enhancement. Use of TMS thus causally demonstrated the involvement of LOC in this task, and more broadly with perceptual decision-making; additionally, it demonstrated the role of TMS in testing well-developed neural models of perceptual processing.
Highlights
The human brain is adept at interpreting visual input with a remarkable ability to process features, objects, and scenes, rapidly performing complex categorizations
A detrimental effect on performance was found when transcranial magnetic stimulation (TMS) was applied at early stimulus onset asynchronies (SOAs) of 0, 50, 150 ms with a slowdown of reaction time (RT) compared to sham. This early effect occurred in a paired-pulse TMS (ppTMS) study by Pitcher et al (2008) and dissociated into two separate processes using finer time resolution in Pitcher et al (2012). These results suggest that lateral occipital cortex (LOC) is involved with the early visual processing associated with the the first network in Philiastades/Sajda’s model, a simpler explanation may be that TMS to LOC at earlier latencies could disrupt processing trans-synaptically via feedback connections with regions of the model’s first network active at this time
While we believe the results of this study demonstrate the usefulness of TMS in validating network models of cortical function, and in particular the Philiastades/Sajda model of visual discrimination, the study did have some limitations that should be mentioned
Summary
The human brain is adept at interpreting visual input with a remarkable ability to process features, objects, and scenes, rapidly performing complex categorizations. Studies by Heekeren et al (2004) presented images of faces and houses masked by varying levels of visual noise to investigate the cortical mechanisms underlying PDM with functional magnetic resonance imaging (fMRI) Their results demonstrated that portions of the dorsal lateral prefrontal cortex activate more in response to easy-than-difficult decisions, and covary with the difference in responses from the face- and house-selective regions of the ventral temporal cortex, while predicting behavioral performance in the categorization task. These and similar findings (Shadlen and Newsome, 2001; Paulus et al, 2002; Grinband et al, 2006; Kahnt et al, 2011) support the notion that spatially-distributed neural networks compare information collected from low-level sensory areas to perform complex PDM
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