Saccade Target Selection in the Superior Colliculus: A Signal Detection Theory Approach

Abstract

How the brain selects one action from among multiple options is unknown. A main tenet of signal detection theory (SDT) is that sensory stimuli are represented as noisy information channels. Therefore, the accuracy of selection might be predicted by how well neuronal activity representing alternatives can be distinguished. Here, we apply an SDT framework to a motor system by recording from superior colliculus (SC) neurons during performance of a color, oddball selection task. We recorded from sets of four neurons simultaneously, each of the four representing one of the four possible targets. Because the electrode placement constrained the position of the stimuli in the visual field, the stimulus arrangement varied across experiments. This variability in stimulus arrangement led to variability in choices allowing us to explore the relationship between SC neuronal activity and performance accuracy. SC target neurons had higher levels of discharge than SC distractor neurons in subsets of trials when selection performance was very accurate. In subsets of trials when performance was poor, the discharge level decreased in target neurons and increased in distractor neurons. Accurate performance was associated with larger separations between neuronal activity from targets and distractors as quantified by the receiver operating characteristic (ROC) area and d (an index of discriminability). Poorer performance was associated with less separation of target and distractor neuronal activity. ROC area and d scaled approximately linearly with performance accuracy. Furthermore, ROC area and d increased as saccade onset approached. Together, the results indicate that SC buildup neuronal activity signals the saccadic eye movement decision.

Deficits in reach target selection during inactivation of the midbrain superior colliculus

“…Previous recording studies have identified neural correlates of target selection for saccadic and pursuit eye movements in the SC (7,(11)(12)(13)(14)(15)(16)(17). Furthermore, inactivation and microstimulation studies have demonstrated that manipulations of SC activity can actually change the eye movement choices made by animals, establishing that the SC plays a causal role in target selection for eye movements (45)(46)(47).…”

“…For example, activity related to eye-movement target selection has been identified in the superior colliculus (SC) (7,(11)(12)(13)(14)(15)(16)(17), frontal eye field (18)(19)(20), lateral intraparietal area (10,(21)(22)(23), and supplementary eye fields (24), all areas in which signals related to eye movement execution are seen and in which electrical microstimulation and/or temporary inactivation affects the execution of eye movements (25)(26)(27)(28)(29)(30)(31). For reaching movements, target selection activity has been observed in the dorsal premotor area (32)(33)(34), a region from which reaches can be electrically elicited (35), as well as in the parietal reach region (36,37), which exhibits reach-related planning and execution signals (38,39).…”

Pinna Cues Determine Orienting Response Modes to Synchronous Sounds in Elevation

“…Second, in visuomotor experiments, visual stimuli were well separable, both at the retina, and in early sensory responses of neurons within the visuomotor pathways. This holds also for example for the midbrain superior colliculus (SC), a crucial sensorimotor interface for the programming and generation of eyehead orienting responses (Arai et al, 2004;Kim and Basso, 2008). The actual visual response selection leading to either averaging or bimodal responses is therefore attributable to neural processing, rather than to visual peripheral limitations.…”

“…Competition between different populations, combined with local-excitatory/global-inhibitory interactions, shapes the population that represents the saccade goal. Task constraints and stimulus saliency help favor neurons that represent the target to win this competition, yet also averaging may be the result of this competition (van Opstal and Van Gisbergen, 1990;Glimcher and Sparks, 1993;Arai et al, 2004;Kim and Basso, 2008).…”

“…Varying target features (salience, onset asynchrony, spatial disparity, size), task constraints (instruction), or saccade reaction times systematically affects response endpoint distributions (Findlay, 1982;Ottes et al, 1984Ottes et al, , 1985. This behavior is thought to arise from neural interactions within spatially organized maps, like in midbrain superior colliculus (Ottes et al, 1984;Lee et al, 1988;van Opstal and Van Gisbergen, 1990;Glimcher and Sparks, 1993;Kim and Basso, 2008).…”