Search

Neuronal spiking was sampled from the frontal eye field (FEF) and from the rostral part of area 6 that reaches to the superior limb of the arcuate sulcus, dorsal to the arcuate spur when present (F2vr) in macaque monkeys performing memory-guided saccades and visually guided saccades for visual search. Neuronal spiking modulation in F2vr resembled that in FEF in many but not all respects. A new consensus clustering algorithm of neuronal modulation patterns revealed that F2vr and FEF contain a greater variety of modulation patterns than previously reported. The areas differ in the proportions of visuomotor neuron types, the proportions of neurons discriminating a target from distractors during visual search, and the consistency of modulation patterns across tasks. However, between F2vr and FEF we found no difference in the magnitude of delay period activity, the timing of the peak discharge rate relative to saccades, or the time of search target selection. The observed similarities and differences between the 2 cortical regions contribute to other work establishing the organization of eye fields in the frontal lobe and may help explain why FEF in monkeys is identified within granular prefrontal area 8 but in humans is identified within agranular premotor area 6.

We discuss the problem of elucidating mechanisms of visual search. We begin by considering the history, logic, and methods of relating behavioral or cognitive processes with neural processes. We then survey briefly the cognitive neurophysiology of visual search and essential aspects of the neural circuitry supporting this capacity. We introduce conceptually and empirically a powerful but underutilized experimental approach to dissect the cognitive processes supporting performance of a visual search task with factorial manipulations of singleton-distractor identifiability and stimulus-response cue discriminability. We show that systems factorial technology can distinguish processing architectures from the performance of macaque monkeys. This demonstration offers new opportunities to distinguish neural mechanisms through selective manipulation of visual encoding, search selection, rule encoding, and stimulus-response mapping.

Neurons in macaque frontal eye field contribute to spatial but typically not feature selection during visual search. Using an innovative visual search task, we report a serendipitous discovery that some frontal eye field neurons can develop rapid selectivity for stimulus orientation that is used to guide gaze during a visual search task with pro-saccade and anti-saccade responses. This feature selectivity occurs simultaneously at multiple locations for all objects sharing that feature and coincides with when neurons select the singleton of a search array. This feature selectivity also reveals the distinct, subsequent operation of selecting the endpoint of the saccade in pro-saccade as well as anti-saccade trials. These results demonstrate that target selection preceding saccade preparation is composed of multiple operations. We conjecture that singleton selection indexes the allocation of attention, which can be divided, to conspicuous items. Consequently, endpoint selection indexes the focused allocation of attention to the endpoint of the saccade. These results demonstrate that saccade target selection is not a unitary process.SIGNIFICANCE STATEMENTFrontal eye field is well known to contribute to spatial selection for attention and eye movements. We discovered that some frontal eye field neurons can acquire selectivity for stimulus orientation when it guides visual search. The chronometry of neurons with and without feature selectivity reveal distinct operations accomplishing visual search.

Visual Abstract, Frontal eye field (FEF) in macaque monkeys contributes to visual attention, visual–motor transformations and production of eye movements. Traditionally, neurons in FEF have been classified by the magnitude of increased discharge rates following visual stimulus presentation, during a waiting period, and associated with eye movement production. However, considerable heterogeneity remains within the traditional visual, visuomovement, and movement categories. Cluster analysis is a data-driven method of identifying self-segregating groups within a dataset. Because many cluster analysis techniques exist and outcomes vary with analysis assumptions, consensus clustering aggregates over multiple analyses, identifying robust groups. To describe more comprehensively the neuronal composition of FEF, we applied a consensus clustering technique for unsupervised categorization of patterns of spike rate modulation measured during a memory-guided saccade task. We report 10 functional categories, expanding on the traditional 3 categories. Categories were distinguished by latency, magnitude, and sign of visual response; the presence of sustained activity; and the dynamics, magnitude and sign of saccade-related modulation. Consensus clustering can include other metrics and can be applied to datasets from other brain regions to provide better information guiding microcircuit models of cortical function.

Frontal eye field (FEF) in macaque monkeys contributes to visual attention, visual-motor transformations and production of eye movements. Traditionally, neurons in FEF have been classified by the magnitude of increased discharge rates following visual stimulus presentation, during a waiting period, and associated with eye movement production. However, considerable heterogeneity remains within the traditional visual, visuomovement and movement categories. Cluster analysis is a data-driven method of identifying self-segregating groups within a dataset. Because many cluster analysis techniques exist and cluster outcomes vary with analysis assumptions, consensus clustering aggregates over multiple cluster analyses, identifying robust groups. To describe more comprehensively the neuronal composition of FEF, we applied a consensus clustering technique for unsupervised categorization of patterns of spike rate modulation measured during a memory-guided saccade task. We report ten functional categories, expanding on the traditional three. Categories were distinguished by latency, magnitude, and sign of visual response, presence of sustained activity, and dynamics, magnitude and sign of saccade-related modulation. Consensus clustering can include other metrics and can be applied to datasets from other brain regions to provides better information guiding microcircuit models of cortical function.SIGNIFICANCE STATEMENTThe contribution of a brain region cannot be understood without knowing the diversity, arrangement, and circuitry of constituent neurons. Traditional descriptions of frontal eye field include visual, visuo-saccadic, and saccadic categories. Here, we employ a novel consensus clustering method to identify more reliably functional categories in neural data. While confirming the traditional categories, consensus clustering distinguishes additional, previously unappreciated diversity in neural activity patterns. Such information is necessary to formulate correct microcircuit models of cortical function.