Neural Correlates of Correct and Errant Attentional Selection Revealed Through N2pc and Frontal Eye Field Activity

Abstract

Heitz RP, Cohen JY, Woodman GF, Schall JD. Neural correlates of correct and errant attentional selection revealed through N2pc and frontal eye field activity. J Neurophysiol 104: 2433-2441, 2010. First published September 1, 2010 doi:10.1152/jn.00604.2010. The goal of this study was to obtain a better understanding of the physiological basis of errors of visual search. Previous research has shown that search errors occur when visual neurons in the frontal eye field (FEF) treat distractors as if they were targets. We replicated this finding during an inefficient form search and extended it by measuring simultaneously a macaque homologue of an event-related potential indexing the allocation of covert attention known as the m-N2pc. Based on recent work, we expected errors of selection in FEF to propagate to areas of extrastriate cortex responsible for allocating attention and implicated in the generation of the m-N2pc. Consistent with this prediction, we discovered that when FEF neurons selected a distractor instead of the search target, the m-N2pc shifted in the same, incorrect direction prior to the erroneous saccade. This suggests that such errors are due to a systematic misorienting of attention from the initial stages of visual processing. Our analyses also revealed distinct neural correlates of false alarms and guesses. These results demonstrate that errant gaze shifts during visual search arise from errant attentional processing. I N T R O D U C T I O NComprehensive models of cognition must account for patterns of both correct and errant behavior. This has proven difficult because errors can arise in many ways, both through faulty sensory processing and through hasty response preparation. Still, behavioral measures of errant responding have been of interest for many years (Rabbitt 1966), and leading models of perceptual decision making aim to account for errant behavior along with correct responding (Ratcliff and Rouder 1998). Unfortunately, these efforts are limited by a paucity of evidence identifying the neural correlates of errors. Understanding the neural activity associated with errant performance provides a more complete picture of the neurophysiological basis of behavior and offers important constraints on cognitive models (e.g., Purcell et al. 2010).In this study, we obtained new information about how errors of visual search occur by recording the macaque homologue of the human N2pc using electrodes embedded in the macaque skull (Woodman et al. 2007) simultaneously with single units and local field potential (LFP) in macaque frontal eye field (FEF), an area recognized as contributing to attentional selection on the one hand (Cohen et al. 2009a; Sato and Schall 2003;Schall et al. 1995a) and saccade production on the other (Bruce and Goldberg 1985;Hanes and Schall 1996;Ray et al. 2004;Schall 1991).Previous research has demonstrated that the N2pc is a signature of covert attentional selection (Luck and Hillyard 1994;Luck et al. 1993) and can be used to monitor dynamic shifts of attention (Woodman an...

The modulatory impact of reward and attention on global feature selection in human visual cortex

“…Reward value is often linked to orbito-frontal (Hikosaka & Watanabe, 2004;PadoaSchioppa & Assad, 2006;Roesch & Olson, 2007;Schultz, Tremblay, & Hollerman, 2000;Tremblay & Schultz, 1999 and dorso-medial frontal cortex like the anterior cingulate cortex (ACC) (Gehring & Willoughby, 2002;Hayden, Pearson, & Platt, 2009). Visual attention is rather controlled by dorsolateral-prefrontal cortex areas, in particular by the frontal eye field (FEF) (Armstrong, Fitzgerald, & Moore, 2006;Armstrong & Moore, 2007;Heitz, Cohen, Woodman, & Schall, 2010;Moore, Armstrong, & Fallah, 2003;Moore & Fallah, 2004). It is possible that independent modulatory influences of orbitofrontal/dorso-medial and dorsolateral-prefrontal cortex areas converge on feature-selective neurons of the ventral extrastriate cortex thereby adding their bias.…”

From Salience to Saccades: Multiple-Alternative Gated Stochastic Accumulator Model of Visual Search

“…1 A , inset). Basic behavioral and physiological analyses of these data have been published previously (Woodman et al, 2008; Cohen et al, 2009; Heitz et al, 2010). Briefly, after fixating a central stimulus for ~600 ms, a stimulus array appeared containing a target (T or L) among one, three, or seven distractors (random 90° orientations of the other letter).…”

“…Thus, the spike trains that drive the model represent the responses of visually responsive neurons recorded under the exact conditions being simulated. Simulations that used input from trials in which the animal erroneously looked to a distractor most often predicted erroneous responses due to the form of sampled input (Heitz et al, 2010), but this was not always the case. Indeed, we present examples of models that fail to adequately predict error probabilities.…”

Neural dynamics and circuit mechanisms of decision-making

“…Biologically, the notion of decision threshold should be understood as the firing level of decision neurons that is required for triggering a switch-like response in downstream premotor neurons [42]. Consistent with this perspective is the common observation that, in a visual search task, behavioral reaction time co-varies with the time it takes for the firing rates of competing visually responsive neurons to significantly diverge from each other, rather than to reach a fixed threshold level, in FEF [66, 80, 18, 34], SC [52] and LIP [37, 73, 2]. …”