Jamie D. Roitman

Response of Neurons in the Lateral Intraparietal Area during a Combined Visual Discrimination Reaction Time Task

Decisions about the visual world can take time to form, especially when information is unreliable. We studied the neural correlate of gradual decision formation by recording activity from the lateral intraparietal cortex (area LIP) of rhesus monkeys during a combined motion-discrimination reaction-time task. Monkeys reported the direction of random-dot motion by making an eye movement to one of two peripheral choice targets, one of which was within the response field of the neuron. We varied the difficulty of the task and measured both the accuracy of direction discrimination and the time required to reach a decision. Both the accuracy and speed of decisions increased as a function of motion strength. During the period of decision formation, the epoch between onset of visual motion and the initiation of the eye movement response, LIP neurons underwent ramp-like changes in their discharge rate that predicted the monkeys decision. A steeper rise in spike rate was associated with stronger stimulus motion and shorter reaction times. The observations suggest that neurons in LIP integrate time-varying signals that originate in the extrastriate visual cortex, accumulating evidence for or against a specific behavioral response. A threshold level of LIP activity appears to mark the completion of the decision process and to govern the tradeoff between accuracy and speed of perception.

Probabilistic Population Codes for Bayesian Decision Making

When making a decision, one must first accumulate evidence, often over time, and then select the appropriate action. Here, we present a neural model of decision making that can perform both evidence accumulation and action selection optimally. More specifically, we show that, given a Poisson-like distribution of spike counts, biological neural networks can accumulate evidence without loss of information through linear integration of neural activity and can select the most likely action through attractor dynamics. This holds for arbitrary correlations, any tuning curves, continuous and discrete variables, and sensory evidence whose reliability varies over time. Our model predicts that the neurons in the lateral intraparietal cortex involved in evidence accumulation encode, on every trial, a probability distribution which predicts the animals performance. We present experimental evidence consistent with this prediction and discuss other predictions applicable to more general settings.

Monotonic Coding of Numerosity in Macaque Lateral Intraparietal Area

As any child knows, the first step in counting is summing up individual elements, yet the brain mechanisms responsible for this process remain obscure. Here we show, for the first time, that a population of neurons in the lateral intraparietal area of monkeys encodes the total number of elements within their classical receptive fields in a graded fashion, across a wide range of numerical values (2–32). Moreover, modulation of neuronal activity by visual quantity developed rapidly, within 100 ms of stimulus onset, and was independent of attention, reward expectations, or stimulus attributes such as size, density, or color. The responses of these neurons resemble the outputs of “accumulator neurons” postulated in computational models of number processing. Numerical accumulator neurons may provide inputs to neurons encoding specific cardinal values, such as “4,” that have been described in previous work. Our findings may explain the frequent association of visuospatial and numerical deficits following damage to parietal cortex in humans.

A Physiologically-Inspired Model of Numerical Classification Based on Graded Stimulus Coding

In most natural decision contexts, the process of selecting among competing actions takes place in the presence of informative, but potentially ambiguous, stimuli. Decisions about magnitudes – quantities like time, length, and brightness that are linearly ordered – constitute an important subclass of such decisions. It has long been known that perceptual judgments about such quantities obey Webers Law, wherein the just-noticeable difference in a magnitude is proportional to the magnitude itself. Current physiologically inspired models of numerical classification assume discriminations are made via a labeled line code of neurons selectively tuned for numerosity, a pattern observed in the firing rates of neurons in the ventral intraparietal area (VIP) of the macaque. By contrast, neurons in the contiguous lateral intraparietal area (LIP) signal numerosity in a graded fashion, suggesting the possibility that numerical classification could be achieved in the absence of neurons tuned for number. Here, we consider the performance of a decision model based on this analog coding scheme in a paradigmatic discrimination task – numerosity bisection. We demonstrate that a basic two-neuron classifier model, derived from experimentally measured monotonic responses of LIP neurons, is sufficient to reproduce the numerosity bisection behavior of monkeys, and that the threshold of the classifier can be set by reward maximization via a simple learning rule. In addition, our model predicts deviations from Weber Law scaling of choice behavior at high numerosity. Together, these results suggest both a generic neuronal framework for magnitude-based decisions and a role for reward contingency in the classification of such stimuli.

One-Dimensional Dynamics of Attention and Decision Making in LIP

Where we allocate our visual spatial attention depends upon a continual competition between internally generated goals and external distractions. Recently it was shown that single neurons in the macaque lateral intraparietal area (LIP) can predict the amount of time a distractor can shift the locus of spatial attention away from a goal. We propose that this remarkable dynamical correspondence between single neurons and attention can be explained by a network model in which generically high-dimensional firing-rate vectors rapidly decay to a single mode. We find direct experimental evidence for this model, not only in the original attentional task, but also in a very different task involving perceptual decision making. These results confirm a theoretical prediction that slowly varying activity patterns are proportional to spontaneous activity, pose constraints on models of persistent activity, and suggest a network mechanism for the emergence of robust behavioral timing from heterogeneous neuronal populations.

Linking Neuroscience With Modern Concepts of Impulse Control Disorders in Parkinson's Disease

Patients with Parkinsons disease (PD) may experience impulse control disorders (ICDs) when on dopamine agonist therapy for their motor symptoms. In the last few years, a rapid growth of interest for the recognition of these aberrant behaviors and their neurobiological correlates has occurred. Recent advances in neuroimaging are helping to identify the neuroanatomical networks responsible for these ICDs, and together with psychopharmacological assessments are providing new insights into the brain status of impulsive behavior. The genetic associations that may be unique to ICDs in PD are also being identified. Complementing human studies, electrophysiological and biochemical studies in animal models are providing insights into neuropathological mechanisms associated with these disorders. New animal models of ICDs in PD patients are being implemented that should provide critical means to identify efficacious therapies for PD‐related motor deficits while avoiding ICD side effects. Here, we provide an overview of these recent advances, with a particular emphasis on the neurobiological correlates reported in animal models and patients along with their genetic underpinnings.

Hedonic and nucleus accumbens neural responses to a natural reward are regulated by aversive conditioning

The nucleus accumbens (NAc) plays a role in hedonic reactivity to taste stimuli. Learning can alter the hedonic valence of a given stimulus, and it remains unclear how the NAc encodes this shift. The present study examined whether the population response of NAc neurons to a taste stimulus is plastic using a conditioned taste aversion (CTA) paradigm. Electrophysiological and electromyographic (EMG) responses to intraoral infusions of a sucrose (0.3 M) solution were made in naïve rats (Day 1). Immediately following the session, half of the rats (n = 6; Paired) received an injection of lithium chloride (0.15 M; i.p.) to induce malaise and establish a CTA while the other half (n = 6; Unpaired) received a saline injection. Days later (Day 5), NAc recordings during infusions of sucrose were again made. Electrophysiological and EMG responses to sucrose did not differ between groups on Day 1. For both groups, the majority of sucrose responsive neurons exhibited a decrease in firing rate (77% and 71% for Paired and Unpaired, respectively). Following conditioning, in Paired rats, EMG responses were indicative of aversion. Moreover, the majority of responsive NAc neurons now exhibited an increase in firing rate (69%). Responses in Unpaired rats were unchanged by the experience. Thus, the NAc differentially encodes the hedonic value of the same stimulus based on learned associations.

Ghrelin regulates phasic dopamine and nucleus accumbens signaling evoked by food-predictive stimuli

Environmental stimuli that signal food availability hold powerful sway over motivated behavior and promote feeding, in part, by activating the mesolimbic system. These food‐predictive cues evoke brief (phasic) changes in nucleus accumbens (NAc) dopamine concentration and in the activity of individual NAc neurons. Phasic fluctuations in mesolimbic signaling have been directly linked to goal‐directed behaviors, including behaviors elicited by food‐predictive cues. Food‐seeking behavior is also strongly influenced by physiological state (i.e., hunger vs. satiety). Ghrelin, a stomach hormone that crosses the blood‐brain barrier, is linked to the perception of hunger and drives food intake, including intake potentiated by environmental cues. Notwithstanding, whether ghrelin regulates phasic mesolimbic signaling evoked by food‐predictive stimuli is unknown. Here, rats underwent Pavlovian conditioning in which one cue predicted the delivery of rewarding food (CS+) and a second cue predicted nothing (CS−). After training, we measured the effect of ghrelin infused into the lateral ventricle (LV) on sub‐second fluctuations in NAc dopamine using fast‐scan cyclic voltammetry and individual NAc neuron activity using in vivo electrophysiology in separate groups of rats. LV ghrelin augmented both phasic dopamine and phasic increases in the activity of NAc neurons evoked by the CS+. Importantly, ghrelin did not affect the dopamine nor NAc neuron response to the CS−, suggesting that ghrelin selectively modulated mesolimbic signaling evoked by motivationally significant stimuli. These data demonstrate that ghrelin, a hunger signal linked to physiological state, can regulate cue‐evoked mesolimbic signals that underlie food‐directed behaviors. Cues that predict food availability powerfully regulate food‐seeking behavior. Here we show that cue‐evoked changes in both nucleus accumbens (NAc) dopamine (DA) and NAc cell activity are modulated by intra‐cranial infusions of the stomach hormone ghrelin ‐ a hormone known to act centrally to promote food intake. These data demonstrate that hormones associated with physiological state (i.e., hunger) can affect encoding of food‐predictive cues in brain regions that drive food‐motivated behavior.

Risk-preference differentiates orbitofrontal cortex responses to freely chosen reward outcomes.

To successfully evaluate potential courses of action and choose the most favorable, we must consider the outcomes that may result. Many choices involve risk, our assessment of which may lead us to success or failure in matters financial, legal or health‐related. The orbitofrontal cortex (OFC) has been implicated as critical for evaluating choices based on risk. To measure how outcomes of risky decisions are represented in the OFC, we recorded the electrophysiological activity of single neurons while rats made behavioral responses to obtain rewards under conditions of either certainty or risk. Rats exhibited different risk‐preferences when given the opportunity to choose. In risk‐preferring rats, OFC responses were enhanced following the delivery of large rewards obtained under risk compared with smaller, certain rewards and reward omission. However, in risk‐neutral rats, neurons showed similarly enhanced responses to both large rewards obtained under risk and smaller, certain rewards compared with reward omission. Thus, the responses of OFC neurons reflected the subjective evaluation of outcomes in individuals with different risk‐preferences. Such enhanced neural responding to risky rewards may serve to bias individuals towards risk‐preference in decision‐making.

Nucleus accumbens shell, but not core, tracks motivational value of salt

To appropriately respond to an affective stimulus, we must be able to track its value across changes in both the external and internal environment. The nucleus accumbens (NAc) is a critical component of reward circuitry, but recent work suggests that the NAc encodes aversion as well as reward. It remains unknown whether differential NAc activity reflects flexible changes in stimulus value when it is altered due to a change in physiological state. We measured the activity of individual NAc neurons when rats were given intraoral infusions of a hypertonic salt solution (0.45 M NaCl) across multiple sessions in which motivational state was manipulated. This normally nonpreferred taste was made rewarding via sodium depletion, which resulted in a strong motivation to seek out and consume salt. Recordings were made in three conditions: while sodium replete (REP), during acute sodium depletion (DEP), and following replenishment of salt to normal sodium balance (POST). We found that NAc neurons in the shell and core subregions responded differently across the three conditions. In the shell, we observed overall increases in NAc activity when the salt solution was nonpreferred (REP) but decreases when the salt solution was preferred (DEP). In the core, overall activity was significantly altered only after sodium balance was restored (POST). The results lend further support to the selective encoding of affective stimuli by the NAc and suggest that NAc shell is particularly involved in flexibly encoding stimulus value based on motivational state.