Jeremiah Y. Cohen

Neuron-type specific signals for reward and punishment in the ventral tegmental area

Dopamine has a central role in motivation and reward. Dopaminergic neurons in the ventral tegmental area (VTA) signal the discrepancy between expected and actual rewards (that is, reward prediction error), but how they compute such signals is unknown. We recorded the activity of VTA neurons while mice associated different odour cues with appetitive and aversive outcomes. We found three types of neuron based on responses to odours and outcomes: approximately half of the neurons (type I, 52%) showed phasic excitation after reward-predicting odours and rewards in a manner consistent with reward prediction error coding; the other half of neurons showed persistent activity during the delay between odour and outcome that was modulated positively (type II, 31%) or negatively (type III, 18%) by the value of outcomes. Whereas the activity of type I neurons was sensitive to actual outcomes (that is, when the reward was delivered as expected compared to when it was unexpectedly omitted), the activity of type II and type III neurons was determined predominantly by reward-predicting odours. We ‘tagged’ dopaminergic and GABAergic neurons with the light-sensitive protein channelrhodopsin-2 and identified them based on their responses to optical stimulation while recording. All identified dopaminergic neurons were of type I and all GABAergic neurons were of type II. These results show that VTA GABAergic neurons signal expected reward, a key variable for dopaminergic neurons to calculate reward prediction error.

Neurally constrained modeling of perceptual decision making.

Stochastic accumulator models account for response time in perceptual decision-making tasks by assuming that perceptual evidence accumulates to a threshold. The present investigation mapped the firing rate of frontal eye field (FEF) visual neurons onto perceptual evidence and the firing rate of FEF movement neurons onto evidence accumulation to test alternative models of how evidence is combined in the accumulation process. The models were evaluated on their ability to predict both response time distributions and movement neuron activity observed in monkeys performing a visual search task. Models that assume gating of perceptual evidence to the accumulating units provide the best account of both behavioral and neural data. These results identify discrete stages of processing with anatomically distinct neural populations and rule out several alternative architectures. The results also illustrate the use of neurophysiological data as a model selection tool and establish a novel framework to bridge computational and neural levels of explanation.

Serotonergic neurons signal reward and punishment on multiple timescales

Serotonins function in the brain is unclear. One challenge in testing the numerous hypotheses about serotonins function has been observing the activity of identified serotonergic neurons in animals engaged in behavioral tasks. We recorded the activity of dorsal raphe neurons while mice experienced a task in which rewards and punishments varied across blocks of trials. We ‘tagged’ serotonergic neurons with the light-sensitive protein channelrhodopsin-2 and identified them based on their responses to light. We found three main features of serotonergic neuron activity: (1) a large fraction of serotonergic neurons modulated their tonic firing rates over the course of minutes during reward vs punishment blocks; (2) most were phasically excited by punishments; and (3) a subset was phasically excited by reward-predicting cues. By contrast, dopaminergic neurons did not show firing rate changes across blocks of trials. These results suggest that serotonergic neurons signal information about reward and punishment on multiple timescales. DOI: http://dx.doi.org/10.7554/eLife.06346.001

Organization of Monosynaptic Inputs to the Serotonin and Dopamine Neuromodulatory Systems

Serotonin and dopamine are major neuromodulators. Here, we used a modified rabies virus to identify monosynaptic inputs to serotonin neurons in the dorsal and median raphe (DR and MR). We found that inputs to DR and MR serotonin neurons are spatially shifted in the forebrain, and MR serotonin neurons receive inputs from more medial structures. Then, we compared these data with inputs to dopamine neurons in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc). We found that DR serotonin neurons receive inputs from a remarkably similar set of areas as VTA dopamine neurons apart from the striatum, which preferentially targets dopamine neurons. Our results suggest three major input streams: a medial stream regulates MR serotonin neurons, an intermediate stream regulates DR serotonin and VTA dopamine neurons, and a lateral stream regulates SNc dopamine neurons. These results provide fundamental organizational principles of afferent control for serotonin and dopamine.

Population Encoding by Circadian Clock Neurons Organizes Circadian Behavior

Mammalian circadian rhythms are orchestrated by the suprachiasmatic nuclei (SCN) of the hypothalamus. The SCN are composed of circadian clock neurons, but the mechanisms by which these populations of neuronal oscillators encode rhythmic behavior are incompletely understood. We have used ex vivo real-time gene expression imaging of the neural correlates of circadian behavior, combined with genetic disruption of vasoactive intestinal polypeptide, a key SCN signaling molecule, to examine the neural basis of circadian organization in the SCN. We show that the coherence and timing of clock neuron rhythms are correlated with the coherence and timing of behavioral rhythms within individual mice and that the degree of disruption of SCN neuronal organization correlates with the degree of behavioral disruption within individuals. Our results suggest that the SCN encode circadian phase as a temporal population vector of its constituent neurons; such that as the neuronal population becomes desynchronized, phase information becomes ambiguous.

Neural Basis of the Set-Size Effect in Frontal Eye Field: Timing of Attention During Visual Search

Visual search for a target object among distractors often takes longer when more distractors are present. To understand the neural basis of this capacity limitation, we recorded activity from visually responsive neurons in the frontal eye field (FEF) of macaque monkeys searching for a target among distractors defined by form (randomly oriented T or L). To test the hypothesis that the delay of response time with increasing number of distractors originates in the delay of attention allocation by FEF neurons, we manipulated the number of distractors presented with the search target. When monkeys were presented with more distractors, visual target selection was delayed and neuronal activity was reduced in proportion to longer response time. These findings indicate that the time taken by FEF neurons to select the target contributes to the variation in visual search efficiency.

Biophysical Support for Functionally Distinct Cell Types in the Frontal Eye Field

Numerous studies have described different functional cell types in the frontal eye field (FEF), but the reliability of the distinction between these types has been uncertain. Studies in other brain areas have described specific differences in the width of action potentials recorded from different cell types. To substantiate the functionally defined cell types encountered in FEF, we measured the width of spikes of visual, movement, and visuomovement types of FEF neurons in macaque monkeys. We show that visuomovement neurons had the thinnest spikes, consistent with a role in local processing. Movement neurons had the widest spikes, consistent with their role in sending eye movement commands to subcortical structures such as the superior colliculus. Visual neurons had wider spikes than visuomovement neurons, consistent with their role in receiving projections from occipital and parietal cortex. These results show how structure and function of FEF can be linked to guide inferences about neuronal architecture.

Neural Correlates of Correct and Errant Attentional Selection Revealed Through N2pc and Frontal Eye Field Activity

The goal of this study was to obtain a better understanding of the physiological basis of errors of visual search. Previous research has shown that search errors occur when visual neurons in the frontal eye field (FEF) treat distractors as if they were targets. We replicated this finding during an inefficient form search and extended it by measuring simultaneously a macaque homologue of an event-related potential indexing the allocation of covert attention known as the m-N2pc. Based on recent work, we expected errors of selection in FEF to propagate to areas of extrastriate cortex responsible for allocating attention and implicated in the generation of the m-N2pc. Consistent with this prediction, we discovered that when FEF neurons selected a distractor instead of the search target, the m-N2pc shifted in the same, incorrect direction prior to the erroneous saccade. This suggests that such errors are due to a systematic misorienting of attention from the initial stages of visual processing. Our analyses also revealed distinct neural correlates of false alarms and guesses. These results demonstrate that errant gaze shifts during visual search arise from errant attentional processing.

Response variability of frontal eye field neurons modulates with sensory input and saccade preparation but not visual search salience

Discharge rate modulation of frontal eye field (FEF) neurons has been identified with a representation of visual search salience (physical conspicuity and behavioral relevance) and saccade preparation. We tested whether salience or saccade preparation are evident in the trial-to-trial variability of discharge rate. We quantified response variability via the Fano factor in FEF neurons recorded in monkeys performing efficient and inefficient visual search tasks. Response variability declined following stimulus presentation in most neurons, but despite clear discharge rate modulation, variability did not change with target salience. Instead, we found that response variability was modulated by stimulus luminance and the number of items in the visual field independently of attentional demands. Response variability declined to a minimum before saccade initiation, and presaccadic response variability was directionally tuned. In addition, response variability was correlated with the response time of memory-guided saccades. These results indicate that the trial-by-trial response variability of FEF neurons reflects saccade preparation and the strength of sensory input, but not visual search salience or attentional allocation.

Dopamine and serotonin signals for reward across time scales.

Neurons that release different neurotransmitters transmit different information about rewards Neurons that release different neurotransmitters transmit different information about rewards