A Functional Hierarchy within the Parietofrontal Network in Stimulus Selection and Attention Control

Abstract

Although we are confronted with an ever-changing environment, we do not have the capacity to analyze all incoming sensory information. Perception is selective and is guided both by salient events occurring in our visual field and by cognitive premises about what needs our attention. Although the lateral intraparietal area (LIP) and frontal eye field (FEF) are known to represent the position of visual attention, their respective contributions to its control are still unclear. Here, we report LIP and FEF neuronal activities recorded while monkeys performed a voluntary attention-orientation target-detection task. We show that both encode behaviorally significant events, but that the FEF plays a specific role in mapping abstract cue instructions onto a spatial priority map to voluntarily guide attention. On the basis of a latency analysis, we show that the coding of stimulus identity and position precedes the emergence of an explicit attentional signal within the FEF. We also describe dynamic temporal hierarchies between LIP and FEF: stimuli carrying the highest intrinsic saliency are signaled by LIP before FEF, whereas stimuli carrying the highest extrinsic saliency are signaled in FEF before LIP. This suggests that whereas the parietofrontal attentional network most probably processes visual information in a recurrent way, exogenous processing predominates in the parietal cortex and the endogenous control of attention takes place in the FEF.

The Effect of FEF Microstimulation on the Responses of Neurons in the Lateral Intraparietal Area

“…A more direct demonstration that attentionrelated modulation of the LIP response is evoked by FEF input would require LIP recordings and precisely targeted FEF inactivations, which would by themselves cause deficits in any visual search task (Wardak et al, 2006). Nevertheless, our data provide direct and causal evidence consistent with Ibos et al (2013), implicating FEF as a source of input that enhances the visual responses of LIP neurons to behaviorally relevant events.…”

“…Thus, our results suggest that the effect of FEF-EM on LIP can be observed under conditions of selective spatial attention (toward the LIP RF), but not during divided attention. Ibos et al (2013) compared responses in FEF and LIP neurons during an attention-orientation target detection task, in which monkeys were cued to attend to one hemifield to detect a target embedded in a stream of distractors. On the basis of the analysis of the neuronal latencies and the proportions of cue-and target-selective neurons in FEF and LIP, the authors hypothesized that enhancement of the LIP response to behaviorally relevant stimuli may be the result of top-down influences originating in the FEF.…”

“…The latter study, however, did not investigate the functional significance of FEF-induced spike rate increases in LIP. Hence, it is unclear whether enhanced responses of LIP neurons at attended locations represent the source of endogeneous attentional control (Gottlieb, 2002) or if it arises from the influence of top-down signals originating in frontal areas such as the FEF (Ibos, Duhamel, & Ben Hamed, 2013).…”

The cortex is in overall control of ‘voluntary’ eye movement

“…25 In the parietal lobe, the location and function of subregions involved in eye movements and attention have been studied intensively, but are still not so well known. 26,27 The parietal lobe and more particularly its posterior part, the PPC, are involved in the control of saccades and attention. In humans and nonhuman primates, the PPC includes the intraparietal sulcus (IPS) extending from the post-central sulcus anteriorly to the parieto-occipital sulcus posteriorly (Figure 1).…”

Characterisation of Functional Brain Networks underlying Cognitive Reasoning and Intelligence

“…For example, single cell recordings in the macaque during the execution of complex tasks have revealed that a wide range of task features, including task rules, cues and stimuli features can be coded by the same set of cells (Duncan, 2001;Ibos et al, 2013). Moreover, this coding is dynamic, such that neurons are reallocated to the most important task at hand, at the timescale of single trials (Kadohisa et al, 2013;Stokes et al, 2013).…”