Michael Campos

A Neural Representation of Sequential States Within an Instructed Task

In the study of the neural basis of sensorimotor transformations, it has become clear that the brain does not always wait to sense external events and afterward select the appropriate responses. If there are predictable regularities in the environment, the brain begins to anticipate the timing of instructional cues and the signals to execute a response, revealing an internal representation of the sequential behavioral states of the task being performed. To investigate neural mechanisms that could represent the sequential states of a task, we recorded neural activity from two oculomotor structures implicated in behavioral timing--the supplementary eye fields (SEF) and the lateral intraparietal area (LIP)--while rhesus monkeys performed a memory-guided saccade task. The neurons of the SEF were found to collectively encode the progression of the task with individual neurons predicting and/or detecting states or transitions between states. LIP neurons, while also encoding information about the current temporal interval, were limited with respect to SEF neurons in two ways. First, LIP neurons tended to be active when the monkey was planning a saccade but not in the precue or intertrial intervals, whereas SEF neurons tended to have activity modulation in all intervals. Second, the LIP neurons were more likely to be spatially tuned than SEF neurons. SEF neurons also show anticipatory activity. The state-selective and anticipatory responses of SEF neurons support two complementary models of behavioral timing, state dependent and accumulator models, and suggest that each model describes a contribution SEF makes to timing at different temporal resolutions.

Separate Representations of Target and Timing Cue Locations in the Supplementary Eye Fields

When different stimuli indicate where and when to make an eye movement, the brain areas involved in oculomotor control must selectively plan an eye movement to the stimulus that encodes the target position and also encode the information available from the timing cue. This could pose a challenge to the oculomotor system since the representation of the timing stimulus location in one brain area might be interpreted by downstream neurons as a competing motor plan. Evidence from diverse sources has suggested that the supplementary eye fields (SEF) play an important role in behavioral timing, so we recorded single-unit activity from SEF to characterize how target and timing cues are encoded in this region. Two monkeys performed a variant of the memory-guided saccade task, in which a timing stimulus was presented at a randomly chosen eccentric location. Many spatially tuned SEF neurons encoded only the location of the target and not the timing stimulus, whereas several other SEF neurons encoded the location of the timing stimulus and not the target. The SEF population therefore encoded the location of each stimulus with largely distinct neuronal subpopulations. For comparison, we recorded a small population of lateral intraparietal (LIP) neurons in the same task. We found that most LIP neurons that encoded the location of the target also encoded the location of the timing stimulus after its presentation, but selectively encoded the intended eye movement plan in advance of saccade initiation. These results suggest that SEF, by conditionally encoding the location of instructional stimuli depending on their meaning, can help identify which movement plan represented in other oculomotor structures, such as LIP, should be selected for the next eye movement.

Signal Multiplexing in Neural Circuits – The Superior Colliculus Deserves a New Look

The primate superior colliculus (SC) is a key component of the system controlling voluntary movements of the eyes and head. A longstanding view is that the SC maintains a retinotopic representation of visual space, and issues commands specifying movements referenced to the fovea. While an accurate representation of target position relative to the fovea is crucial to gaze shifts, information about the position of the eyes in their orbits is important to a number of potential SC functions that include determining the relative contributions of eye and head movements to generate gaze movements, integrating multimodal sensory input, and generating sequences of multiple movements. Nevertheless, the existence and potential role for eye position signals in the SC remains controversial.

Orbitofrontal cortical activity during repeated free choice

Neurons in the orbitofrontal cortex (OFC) have been shown to encode subjective values, suggesting a role in preference-based decision-making, although the precise relation to choice behavior is unclear. In a repeated two-choice task, subjective values of each choice can account for aggregate choice behavior, which is the overall likelihood of choosing one option over the other. Individual choices, however, are impossible to predict with knowledge of relative subjective values alone. In this study we investigated the role of internal factors in choice behavior with a simple but novel free-choice task and simultaneous recording from individual neurons in nonhuman primate OFC. We found that, first, the observed sequences of choice behavior included periods of exceptionally long runs of each of two available options and periods of frequent switching. Neither a satiety-based mechanism nor a random selection process could explain the observed choice behavior. Second, OFC neurons encode important features of the choice behavior. These features include activity selective for exceptionally long runs of a given choice (stay selectivity) as well as activity selective for switches between choices (switch selectivity). These results suggest that OFC neural activity, in addition to encoding subjective values on a long timescale that is sensitive to satiety, also encodes a signal that fluctuates on a shorter timescale and thereby reflects some of the statistically improbable aspects of free-choice behavior.

An improved SpikeTrack: An autonomous multi-electrode control & recording system

This paper summarizes an algorithm to autonomously position an extracellular recording electrode so as to first isolate the action potentials of a single neuron in a multi-unit signal, and then re-position the electrode as necessary to optimize and maintain the recording quality of that neuron over an extended recording interval. We first summarize some of the technical advancements of the current algorithm over earlier versions of the “SpikeTrack” recording system in the area of multi-hypothesis cluster tracking method for spike sorting, and a new technique to optimize the signal recording interval. Novel recording experiments in macaque cortex compare the performance of autonomous extracellular recording with that of an experienced neurophysiologist. We found that the algorithm isolates cells better than a human expert.