Neuronal Correlates of Serial Decision-Making in the Supplementary Eye Field.

Human behavior is influenced by serial decision-making: past decisions affect choices that set the context for selecting future options. A primate brain region that may be involved in linking decisions across time is the supplementary eye field (SEF), which, in addition to its well known visual responses and saccade-related activity, also signals the rules that govern flexible decisions and the outcomes of those decisions. Our hypotheses were that SEF neurons encode events during serial decision-making and link the sequential decisions with sustained activity. We recorded from neurons in the SEF of two rhesus monkeys (Macaca mulatta, one male, one female) that performed a serial decision-making task. The monkeys used saccades to select a rule that had to be applied later in the same trial to discriminate between visual stimuli. We found, first, that SEF neurons encoded the spatial parameters of saccades during rule selection but not during visual discrimination, suggesting a malleability to their movement-related tuning. Second, SEF activity linked the sequential decisions of rule selection and visual discrimination, but not continuously. Instead, rule-encoding activity appeared in a "just-in-time" manner before the visual discrimination. Third, SEF neurons encoded trial outcomes both prospectively, before decisions within a trial, and retrospectively, across multiple trials. The results thus identify neuronal correlates of rule selection and application in the SEF, including transient signals that link these sequential decisions. Its activity patterns suggest that the SEF participates in serial decision-making in a contextually dependent manner as part of a broader network.SIGNIFICANCE STATEMENT Much research has gone into studying the neurobiological basis of single, isolated decisions. An important next step is to understand how the brain links multiple decisions to generate a coherent stream of thought and behavior. We studied neural activity related to serial decision-making in an area of frontal cortex known as the supplementary eye field (SEF). Neural recordings were conducted in monkeys that performed a serial decision-making task in which they selected and applied rules. We found that SEF neurons convey signals for serial decision-making, including transient encoding of one decision at the time it is needed for the next one and longer-term representations of trial outcomes, suggesting that the region plays a role in continuity of cognition and behavior.

Visual continuity across saccades is influenced by expectations.

As we make saccades, the image on each retina is displaced, yet our visual perception is uninterrupted. This is commonly referred to as transsaccadic perceptual stability, but such a description is inadequate. Some visual objects are stable (e.g., rocks) and should be perceived as such across saccades, but other objects may move at any time (e.g., birds). Stability is probabilistic in natural scenes. Here we extend the common notion of transsaccadic visual stability to a more general, ecologically based hypothesis of transsaccadic visual continuity in which postsaccadic percepts of objects depend on expectations about their probability of movement. Subjects made a saccade to a target and reported whether it seemed displaced after the saccade. Targets had varying probabilities of movement (ranging from 0.1-0.9) that corresponded to their color (spectrum from blue to red). Performance was compared before and after subjects were told about the color-probability pairings ("uninformed" vs. "informed" conditions). Analyses focused on signal detection and psychometric threshold measures. We found that in the uninformed condition, performance was similar across color-probability pairings, but in the informed condition, response biases varied with probability of movement, and movement-detection sensitivities were higher for rarely moving targets. We conclude that subjects incorporate priors about object movement into their judgments of visual continuity across saccades.

Application of long-interval paired-pulse transcranial magnetic stimulation to motion-sensitive visual cortex does not lead to changes in motion discrimination.

The perception of visual motion is dependent on a set of occipitotemporal regions that are readily accessible to neuromodulation. The current study tested if paired-pulse Transcranial Magnetic Stimulation (ppTMS) could modulate motion perception by stimulating the occipital cortex as participants viewed near-threshold motion dot stimuli. In this sham-controlled study, fifteen subjects completed two sessions. On the first visit, resting motor threshold (RMT) was assessed, and participants performed an adaptive direction discrimination task to determine individual motion sensitivity. During the second visit, subjects performed the task with three difficulty levels as TMS pulses were delivered 150 and 50 ms prior to motion stimulus onset at 120% RMT, under the logic that the cumulative inhibitory effect of these pulses would alter motion sensitivity. ppTMS was delivered at one of two locations: 3 cm dorsal and 5 cm lateral to inion (scalp-based coordinate), or at the site of peak activation for "motion" according to the NeuroSynth fMRI database (meta-analytic coordinate). Sham stimulation was delivered on one-third of trials by tilting the coil 90°. Analyses showed no significant active-versus-sham effects of ppTMS when stimulation was delivered to the meta-analytic (p = 0.15) or scalp-based coordinates (p = 0.17), which were separated by 29 mm on average. Active-versus-sham stimulation differences did not interact with either stimulation location (p = 0.12) or difficulty (p = 0.33). These findings fail to support the hypothesis that long-interval ppTMS recruits inhibitory processes in motion-sensitive cortex but must be considered within the limited parameters used in this design.

Serial decision-making in monkeys during an oculomotor task.

Much of everyday behavior involves serial decision-making, in which the outcome of 1 choice affects another. An example is setting rules for oneself: choosing a behavioral rule guides appropriate choices in the future. How the brain links decisions across time is poorly understood. Neural mechanisms could be studied in monkeys, as it is known that they can select and use behavioral rules, but existing psychophysical paradigms are poorly suited for the constraints of neurophysiology. Therefore, we designed a streamlined task that requires sequential, linked decisions, and trained 2 rhesus monkeys (Macaca mulatta) to perform it. The task features trial-by-trial consistency, visual stimuli, and eye movement responses to optimize it for simultaneous electrophysiological inquiry. In the first stage of each trial, the monkeys selected a rule or a rule was provided to them. In the second stage, they used the rule to discriminate between 2 test stimuli. Our hypotheses were that they could use self-selected rules and could deliberately select rules based on reinforcement history. We found that the monkeys were as proficient at using self-selected rules as instructed rules. Their preferences for selecting rules correlated with their performance in using them, consistent with systematic, rather than random, strategies for accomplishing the task. The results confirm and extend prior findings on rule selection in monkeys and establish a viable, experimentally flexible paradigm for studying the neural basis of serial decision-making. (PsycINFO Database Record

Planar saline bath phantom of the Rush head model.

The Rush head model is an approximation of the volume conducting properties of the human head. A planar saline bath phantom was developed to simulate the key properties of the Rush head model while creating a testing platform for implantable neural devices. The phantom closely mimics electrical properties of human tissue such as increased resistivity through the skull region and current flow that wraps around the head. Preliminary testing shows good agreement of the saline bath phantom to predictions from a computer model.