William T. Newsome

Noise, neural codes and cortical organization

Cortical circuitry must facilitate information transfer in accordance with a neural code. In this article we examine two candidate neural codes: information is represented in the spike rate of neurons, or information is represented in the precise timing of individual spikes. These codes can be distinguished by examining the physiological basis of the highly irregular interspike intervals typically observed in cerebral cortex. Recent advances in our understanding of cortical microcircuitry suggest that the timing of neuronal spikes conveys little, if any, information. The cortex is likely to propagate a noisy rate code through redundant, patchy interconnections.

A relationship between behavioral choice and the visual responses of neurons in macaque MT

We have previously documented the exquisite motion sensitivity of neurons in extrastriate area MT by studying the relationship between their responses and the direction and strength of visual motion signals delivered to their receptive fields. These results suggested that MT neurons might provide the signals supporting behavioral choice in visual discrimination tasks. To approach this question from another direction, we have now studied the relationship between the discharge of MT neurons and behavioral choice, independently of the effects of visual stimulation. We found that trial-to-trial variability in neuronal signals was correlated with the choices the monkey made. Therefore, when a directionally selective neuron in area MT fires more vigorously, the monkey is more likely to make a decision in favor of the preferred direction of the cell. The magnitude of the relationship was modest, on average, but was highly significant across a sample of 299 cells from four monkeys. The relationship was present for all stimuli (including those without a net motion signal), and for all but the weakest responses. The relationship was reduced or eliminated when the demands of the task were changed so that the directional signal carried by the cell was less informative. The relationship was evident within 50 ms of response onset, and persisted throughout the stimulus presentation. On average, neurons that were more sensitive to weak motion signals had a stronger relationship to behavior than those that were less sensitive. These observations are consistent with the idea that neuronal signals in MT are used by the monkey to determine the direction of stimulus motion. The modest relationship between behavioral choice and the discharge of any one neuron, and the prevalence of the relationship across the population, make it likely that signals from many neurons are pooled to form the data on which behavioral choices are based.

Stimulus onset quenches neural variability: a widespread cortical phenomenon

Neural responses are typically characterized by computing the mean firing rate, but response variability can exist across trials. Many studies have examined the effect of a stimulus on the mean response, but few have examined the effect on response variability. We measured neural variability in 13 extracellularly recorded datasets and one intracellularly recorded dataset from seven areas spanning the four cortical lobes in monkeys and cats. In every case, stimulus onset caused a decline in neural variability. This occurred even when the stimulus produced little change in mean firing rate. The variability decline was observed in membrane potential recordings, in the spiking of individual neurons and in correlated spiking variability measured with implanted 96-electrode arrays. The variability decline was observed for all stimuli tested, regardless of whether the animal was awake, behaving or anaesthetized. This widespread variability decline suggests a rather general property of cortex, that its state is stabilized by an input.

Choosing the greater of two goods: neural currencies for valuation and decision making

To make adaptive decisions, animals must evaluate the costs and benefits of available options. The nascent field of neuroeconomics has set itself the ambitious goal of understanding the brain mechanisms that are responsible for these evaluative processes. A series of recent neurophysiological studies in monkeys has begun to address this challenge using novel methods to manipulate and measure an animals internal valuation of competing alternatives. By emphasizing the behavioural mechanisms and neural signals that mediate decision making under conditions of uncertainty, these studies might lay the foundation for an emerging neurobiology of choice behaviour.

Context-dependent computation by recurrent dynamics in prefrontal cortex

Prefrontal cortex is thought to have a fundamental role in flexible, context-dependent behaviour, but the exact nature of the computations underlying this role remains largely unknown. In particular, individual prefrontal neurons often generate remarkably complex responses that defy deep understanding of their contribution to behaviour. Here we study prefrontal cortex activity in macaque monkeys trained to flexibly select and integrate noisy sensory inputs towards a choice. We find that the observed complexity and functional roles of single neurons are readily understood in the framework of a dynamical process unfolding at the level of the population. The population dynamics can be reproduced by a trained recurrent neural network, which suggests a previously unknown mechanism for selection and integration of task-relevant inputs. This mechanism indicates that selection and integration are two aspects of a single dynamical process unfolding within the same prefrontal circuits, and potentially provides a novel, general framework for understanding context-dependent computations.

Cortical area MT and the perception of stereoscopic depth

Stereopsis is the perception of depth based on small positional differences between images formed on the two retinae (known as binocular disparity). Neurons that respond selectively to binocular disparity were first described three decades ago,, and have since been observed in many visual areas of the primate brain, including V1, V2, V3, MT and MST. Although disparity-selective neurons are thought to form the neural substrate for stereopsis, the mere existence of disparity-selective neurons does not guarantee that they contribute to stereoscopic depth perception. Some disparity-selective neurons may play other roles, such as guiding vergence eye movements,. Thus, the roles of different visual areas in stereopsis remain poorly defined. Here we show that visual area MT is important in stereoscopic vision: electrical stimulation of clusters of disparity-selective MT neurons can bias perceptual judgements of depth, and the bias is predictable from the disparity preference of neurons at the stimulation site. These results show that behaviourally relevant signals concerning stereoscopic depth are present in MT.

Local Field Potential in Cortical Area MT: Stimulus Tuning and Behavioral Correlations

Low-frequency electrical signals like those that compose the local field potential (LFP) can be detected at substantial distances from their point of origin within the brain. It is thus unclear how useful the LFP might be for assessing local function, for example, on the spatial scale of cortical columns. We addressed this problem by comparing speed and direction tuning of LFPs obtained from middle temporal area MT with the tuning of multiunit (MU) activity recorded simultaneously. We found that the LFP can be well tuned for speed and direction and is highly correlated with that of MU activity, particularly for frequencies at and above the gamma band. LFP tuning is substantially poorer for lower frequencies, although tuning for direction extends to lower frequencies than does tuning for speed. Our data suggest that LFP signals at and above the gamma band reflect neural processing on the spatial scale of cortical columns, within a few hundred micrometers of the electrode tip. Consistent with this notion, we also found that frequencies at and above the gamma band measured during a speed discrimination task exhibit an effect known as “choice probability,” which reveals a particularly close relationship between neural activity and behavioral choices. In the LFP, this signature of the perceptual choice comprises a shift in relative power from low-frequency bands (α and β) to the gamma band. It remains to be determined how LFP choice probability, which is a temporal signature, is related to conventional choice probability effects observed in spike rates.

Anatomical and physiological asymmetries related to visual areas V3 and VP in macaque extrastriate cortex

This report provides an overview of the functional organization of cortex immediately anterior to area V2 in extrastriate visual cortex of the macaque monkey. Contrary to previous suggestions that a single area, V3, lies anterior to V2, we have obtained evidence that this strip of cortex includes two separate areas, V3 and the ventral posterior area, VP. The evidence supporting this conclusion is based on dorso-ventral asymmetries in cortico-cortical connections, myeloarchitecture, and single-unit physiological properties relating to the processing of information about color and motion.

The temporal precision of reward prediction in dopamine neurons

Midbrain dopamine neurons are activated when reward is greater than predicted, and this error signal could teach target neurons both the value of reward and when it will occur. We used the dopamine error signal to measure how the expectation of reward was distributed over time. Animals were trained with fixed-duration intervals of 1–16 s between conditioned stimulus onset and reward. In contrast to the weak responses that have been observed after short intervals (1–2 s), activations to reward increased steeply and linearly with the logarithm of the interval. Results with varied stimulus-reward intervals suggest that the neural expectation was substantial after just half an interval had elapsed. Thus, the neural expectation of reward in these experiments was not highly precise and the precision declined sharply with interval duration. The neural precision of expectation appeared to be at least qualitatively similar to the precision of anticipatory licking behavior.

Estimates of the contribution of single neurons to perception depend on timescale and noise correlation.

The sensitivity of a population of neurons, and therefore the amount of sensory information available to an animal, is limited by the sensitivity of single neurons in the population and by noise correlation between neurons. For decades, therefore, neurophysiologists have devised increasingly clever and rigorous ways to measure these critical variables (Parker and Newsome, 1998). Previous studies examining the relationship between the responses of single middle temporal (MT) neurons and direction-discrimination performance uncovered an apparent paradox. Sensitivity measurements from single neurons suggested that small numbers of neurons may account for a monkeys psychophysical performance (Britten et al., 1992), but trial-to-trial variability in activity of single MT neurons are only weakly correlated with the monkeys behavior, suggesting that the monkeys decision must be based on the responses of many neurons (Britten et al., 1996). We suggest that the resolution to this paradox lies (1) in the long stimulus duration used in the original studies, which led to an overestimate of neural sensitivity relative to psychophysical sensitivity, and (2) mistaken assumptions (because no data were available) about the level of noise correlation in MT columns with opposite preferred directions. We therefore made new physiological and psychophysical measurements in a reaction time version of the direction-discrimination task that matches neural measurements to the actual decision time of the animals. These new data, considered together with our recent data on noise correlation in MT (Cohen and Newsome, 2008), provide a substantially improved account of psychometric performance in the direction-discrimination task.