An abstract categorical decision code in dorsal premotor cortex.

The dorsal premotor cortex (DPC) has classically been associated with a role in preparing and executing the physical motor variables during cognitive tasks. While recent work has provided nuanced insights into this role, here we propose that DPC also participates more actively in decision-making. We recorded neuronal activity in DPC while two trained monkeys performed a vibrotactile categorization task, utilizing two partially overlapping ranges of stimulus values that varied on two physical attributes: vibrotactile frequency and amplitude. We observed a broad heterogeneity across DPC neurons, the majority of which maintained the same response patterns across attributes and ranges, coding in the same periods, mixing temporal and categorical dynamics. The predominant categorical signal was maintained throughout the delay, movement periods and notably during the intertrial period. Putting the entire population's data through two dimensionality reduction techniques, we found strong temporal and categorical representations without remnants of the stimuli's physical parameters. Furthermore, projecting the activity of one population over the population axes of the other yielded identical categorical and temporal responses. Finally, we sought to identify functional subpopulations based on the combined activity of all stimuli, neurons, and time points; however, we found that single-unit responses mixed temporal and categorical dynamics and couldn't be clustered. All these point to DPC playing a more decision-related role than previously anticipated.

A Second Introduction to the Neurobiology of Interval Timing.

Time is a critical variable that organisms must be able to measure in order to survive in a constantly changing environment. Initially, this paper describes the myriad of contexts where time is estimated or predicted and suggests that timing is not a single process and probably depends on a set of different neural mechanisms. Consistent with this hypothesis, the explosion of neurophysiological and imaging studies in the last 10 years suggests that different brain circuits and neural mechanisms are involved in the ability to tell and use time to control behavior across contexts. Then, we develop a conceptual framework that defines time as a family of different phenomena and propose a taxonomy with sensory, perceptual, motor, and sensorimotor timing as the pillars of temporal processing in the range of hundreds of milliseconds.

Dopamine reward prediction error signal codes the temporal evaluation of a perceptual decision report.

Learning to associate unambiguous sensory cues with rewarded choices is known to be mediated by dopamine (DA) neurons. However, little is known about how these neurons behave when choices rely on uncertain reward-predicting stimuli. To study this issue we reanalyzed DA recordings from monkeys engaged in the detection of weak tactile stimuli delivered at random times and formulated a reinforcement learning model based on belief states. Specifically, we investigated how the firing activity of DA neurons should behave if they were coding the error in the prediction of the total future reward when animals made decisions relying on uncertain sensory and temporal information. Our results show that the same signal that codes for reward prediction errors also codes the animal's certainty about the presence of the stimulus and the temporal expectation of sensory cues.

Representation of accumulating evidence for a decision in two parietal areas.

Decisions are often made by accumulating evidence for and against the alternatives. The momentary evidence represented by sensory neurons is accumulated by downstream structures to form a decision variable, linking the evolving decision to the formation of a motor plan. When decisions are communicated by eye movements, neurons in the lateral intraparietal area (LIP) represent the accumulation of evidence bearing on the potential targets for saccades. We now show that reach-related neurons from the medial intraparietal area (MIP) exhibit a gradual modulation of their firing rates consistent with the representation of an evolving decision variable. When decisions were communicated by saccades instead of reaches, decision-related activity was attenuated in MIP, whereas LIP neurons were active while monkeys communicated decisions by saccades or reaches. Thus, for decisions communicated by a hand movement, a parallel flow of sensory information is directed to parietal areas MIP and LIP during decision formation.

Internal signal correlates neural populations and biases perceptual decision reports.

In perceptual decision-making tasks the activity of neurons in frontal and posterior parietal cortices covaries more with perceptual reports than with the physical properties of stimuli. This relationship is revealed when subjects have to make behavioral choices about weak or uncertain stimuli. If knowledge about stimulus onset time is available, decision making can be based on accumulation of sensory evidence. However, the time of stimulus onset or even its very presence is often ambiguous. By analyzing firing rates and correlated variability of frontal lobe neurons while monkeys perform a vibrotactile detection task, we show that behavioral outcomes are crucially affected by the state of cortical networks before stimulus onset times. The results suggest that sensory detection is partly due to a purely internal signal whereas the stimulus, if finally applied, adds a contribution to this initial processing later on. The probability to detect or miss the stimulus can thus be explained as the combined effect of this variable internal signal and the sensory evidence.

The parietal cortices participate in encoding, short-term memory, and decision-making related to tactile shape.

We routinely identify objects with our hands, and the physical attributes of touched objects are often held in short-term memory to aid future decisions. However, the brain structures that selectively process tactile information to encode object shape are not fully identified. In this article we describe the areas within the human cerebral cortex that specialize in encoding, short-term memory, and decision-making related to the shape of objects explored with the hand. We performed event-related functional magnetic resonance imaging in subjects performing a shape discrimination task in which two sequentially presented objects had to be explored to determine whether they had the same shape or not. To control for low-level and nonspecific brain activations, subjects performed a temperature discrimination task in which they compared the temperature of two spheres. Our results show that although a large network of brain structures is engaged in somatosensory processing, it is the areas lining the intraparietal sulcus that selectively participate in encoding, maintaining, and deciding on tactile information related to the shape of objects.

Introduction to the neurobiology of interval timing.

Time is a fundamental variable that organisms must quantify in order to survive. In humans, for example, the gradual development of the sense of duration and rhythm is an essential skill in many facets of social behavior such as speaking, dancing to-, listening to- or playing music, performing a wide variety of sports, and driving a car (Merchant H, Harrington DL, Meck WH. Annu Rev Neurosci. 36:313-36, 2013). During the last 10 years there has been a rapid growth of research on the neural underpinnings of timing in the subsecond and suprasecond scales, using a variety of methodological approaches in the human being, as well as in varied animal and theoretical models. In this introductory chapter we attempt to give a conceptual framework that defines time processing as a family of different phenomena. The brain circuits and neural underpinnings of temporal quantification seem to largely depend on its time scale and the sensorimotor nature of specific behaviors. Therefore, we describe the main time scales and their associated behaviors and show how the perception and execution of timing events in the subsecond and second scales may depend on similar or different neural mechanisms.

Dopamine neurons code subjective sensory experience and uncertainty of perceptual decisions.

Midbrain dopamine (DA) neurons respond to sensory stimuli associated with future rewards. When reward is delivered probabilistically, DA neurons reflect this uncertainty by increasing their firing rates in a period between the sensory cue and reward delivery time. Probability of reward, however, has been externally conveyed by visual cues, and it is not known whether DA neurons would signal uncertainty arising internally. Here we show that DA neurons code the uncertainty associated with a perceptual judgment about the presence or absence of a vibrotactile stimulus. We observed that uncertainty modulates the activity elicited by a go cue instructing monkey subjects to communicate their decisions. That is, the same go cue generates different DA responses depending on the uncertainty level of a judgment made a few seconds before the go instruction. Easily detected suprathreshold stimuli elicit small DA responses, indicating that future reward will not be a surprising event. In contrast, the absence of a sensory stimulus generates large DA responses associated with uncertainty: was the stimulus truly absent, or did a low-amplitude vibration go undetected? In addition, the responses of DA neurons to the stimulus itself increase with vibration amplitude, but only when monkeys correctly detect its presence. This finding suggests that DA activity is not related to actual intensity but rather to perceived intensity. Therefore, in addition to their well-known role in reward prediction, DA neurons code subjective sensory experience and uncertainty arising internally from perceptual decisions.

Keeping time and rhythm by internal simulation of sensory stimuli and behavioral actions.

Effective behavior often requires synchronizing our actions with changes in the environment. Rhythmic changes in the environment are easy to predict, and we can readily time our actions to them. Yet, how the brain encodes and maintains rhythms is not known. Here, we trained primates to internally maintain rhythms of different tempos and performed large-scale recordings of neuronal activity across the sensory-motor hierarchy. Results show that maintaining rhythms engages multiple brain areas, including visual, parietal, premotor, prefrontal, and hippocampal regions. Each recorded area displayed oscillations in firing rates and oscillations in broadband local field potential power that reflected the temporal and spatial characteristics of an internal metronome, which flexibly encoded fast, medium, and slow tempos. The presence of widespread metronome-related activity, in the absence of stimuli and motor activity, suggests that internal simulation of stimuli and actions underlies timekeeping and rhythm maintenance.

Motor cortex projections to red and pontine nuclei have distinct roles during movement in the mouse.

Motor control largely depends on the deep layer 5 (L5) pyramidal neurons that project to subcortical structures. However, it is largely unknown if these neurons are functionally segregated with distinct roles in movement performance. Here, we analyzed mouse motor cortex L5 pyramidal neurons projecting to the red and pontine nuclei during movement preparation and execution. Using photometry to analyze the calcium activity of L5 pyramidal neurons projecting to the red nucleus and pons, we reveal that both types of neurons activate with different temporal dynamics. Optogenetic inhibition of either kind of projection differentially affects forelimb movement onset and execution in a lever press task, but only the activity of corticopontine neurons is significantly correlated with trial-by-trial variations in reaction time. The results indicate that cortical neurons projecting to the red and pontine nuclei contribute differently to sensorimotor integration, suggesting that L5 output neurons are functionally compartmentalized generating, in parallel, different downstream information.

Different subtypes of motor cortex pyramidal tract neurons projects to red and pontine nuclei.

Introduction: Pyramidal tract neurons (PTNs) are fundamental elements for motor control. However, it is largely unknown if PTNs are segregated into different subtypes with distinct characteristics. Methods: Using anatomical and electrophysiological tools, we analyzed in mice motor cortex PTNs projecting to red and pontine midbrain nuclei, which are important hubs connecting cerebral cortex and cerebellum playing a critical role in the regulation of movement. Results: We reveal that the vast majority of M1 neurons projecting to the red and pontine nuclei constitutes different populations. Corticopontine neurons have higher conduction velocities and morphologically, a most homogeneous dendritic and spine distributions along cortical layers. Discussion: The results indicate that cortical neurons projecting to the red and pontine nuclei constitute distinct anatomical and functional pathways which may contribute differently to sensorimotor integration.

Discrimination of Regular and Irregular Rhythms Explained by a Time Difference Accumulation Model.

Perceiving the temporal regularity in a sequence of repetitive sensory events facilitates the preparation and execution of relevant behaviors with tight temporal constraints. How we estimate temporal regularity from repeating patterns of sensory stimuli is not completely understood. We developed a decision-making task in which participants had to decide whether a train of visual, auditory, or tactile pulses, had a regular or an irregular temporal pattern. We tested the hypothesis that subjects categorize stimuli as irregular by accumulating the time differences between the predicted and observed times of sensory pulses defining a temporal rhythm. Results suggest that instead of waiting for a single large temporal deviation, participants accumulate timing-error signals and judge a pattern as irregular when the amount of evidence reaches a decision threshold. Model fits of bounded integration showed that this accumulation occurs with negligible leak of evidence. Consistent with previous findings, we show that participants perform better when evaluating the regularity of auditory pulses, as compared with visual or tactile stimuli. Our results suggest that temporal regularity is estimated by comparing expected and measured pulse onset times, and that each prediction error is accumulated towards a threshold to generate a behavioral choice.

Perceptual detection as a dynamical bistability phenomenon: a neurocomputational correlate of sensation.

Recent studies that combined psychophysical/neurophysiological experiments [de Lafuente V, Romo R (2005) Nat Neurosci 8:1698-1703] analyzed the responses from single neurons, recorded in several cortical areas of parietal and frontal lobes, while trained monkeys reported the presence or absence of a mechanical vibration of varying amplitude applied to skin of one fingertip. The analysis showed that the activity of primary somatosensory cortex neurons covaried with the stimulus strength but did not covary with the animal's perceptual reports. In contrast, the activity of medial premotor cortex (MPC) neurons did not covary with the stimulus strength but did covary with the animal's perceptual reports. Here, we address the question of how perceptual detection is computed in MPC. In particular, we regard perceptual detection as a bistable neurodynamical phenomenon reflected in the activity of MPC. We show that the activity of MPC is consistent with a decision-making-like scenario of fluctuation-driven computation that causes a probabilistic transition between two bistable states, one corresponding to the case in which the monkey detects the sensory input, the other corresponding to the case in which the monkey does not. Moreover, the high variability activity of MPC neurons both within and between trials reflects stochastic fluctuations that may play a crucial role in the monkey's probabilistic perceptual reports.

Integrating Somatosensory Information Over Time.

Our choices are often informed by temporally integrating streams of sensory information. This has been well demonstrated in the visual and auditory domains, but the integration of tactile information over time has been less studied. We designed an active touch task in which participants explored a spheroid-shaped object to determine its inclination with respect to the horizontal plane (inclined to the left or the right). In agreement with previous findings, our results show that more errors, and longer decision times, accompany difficult decisions (small inclination angles). To gain insight into the decision-making process, we used a time-controlled task in which the experimenter manipulated the time available for tactile exploration on a trial-by-trial basis. The behavioral results were fit with a bounded accumulation model and an independent sampling model that assumes no sensory accumulation. The results of model fits favor an accumulation-to-bound mechanism and suggest that participants integrate the first 600 ms of 1800 ms-long stimuli. This means that the somatosensory system benefits from longer streams of information, although it does not make use of all available evidence.

Neuronal correlates of subjective sensory experience.

When a near-threshold stimulus is presented, a sensory percept may or may not be produced. The unpredictable outcome of such perceptual judgment is believed to be determined by the activity of neurons in early sensory cortex. We analyzed the responses of neurons in primary somatosensory cortex, recorded while monkeys judged the presence or absence of threshold stimuli. We found that these responses did not covary with the monkeys' perceptual reports. In contrast, the activity of frontal lobe neurons did covary with trial-by-trial judgments. Further control and microstimulation experiments indicated that frontal lobe neurons are closely related to the monkeys' subjective experiences during sensory detection.

Language abilities of motor cortex.

A new exploration of the cortical network underlying our language abilities by Hauk et al., in this issue of Neuron, shows that the process of giving meaning to words differentially activates the motor cortex according to the semantic category of the word.

A hidden sensory function for motor cortex.

Sensory perception has traditionally been attributed to the activation of sensory cortices. However, by inducing an illusory perception of movement, Naito and colleagues show in this issue of Neuron that the illusory perception of movement is related to activation of primary motor cortex.

Biomimetic brain machine interfaces for the control of movement.

Quite recently, it has become possible to use signals recorded simultaneously from large numbers of cortical neurons for real-time control. Such brain machine interfaces (BMIs) have allowed animal subjects and human patients to control the position of a computer cursor or robotic limb under the guidance of visual feedback. Although impressive, such approaches essentially ignore the dynamics of the musculoskeletal system, and they lack potentially critical somatosensory feedback. In this mini-symposium, we will initiate a discussion of systems that more nearly mimic the control of natural limb movement. The work that we will describe is based on fundamental observations of sensorimotor physiology that have inspired novel BMI approaches. We will focus on what we consider to be three of the most important new directions for BMI development related to the control of movement. (1) We will present alternative methods for building decoders, including structured, nonlinear models, the explicit incorporation of limb state information, and novel approaches to the development of decoders for paralyzed subjects unable to generate an output signal. (2) We will describe the real-time prediction of dynamical signals, including joint torque, force, and EMG, and the real-time control of physical plants with dynamics like that of the real limb. (3) We will discuss critical factors that must be considered to incorporate somatosensory feedback to the BMI user, including its potential benefits, the differing representations of sensation and perception across cortical areas, and the changes in the cortical representation of tactile events after spinal injury.

Regaining the senses of touch and movement.

Artificially activating neurons in the cortex can make a tetraplegic patient feel naturalistic sensations of skin pressure and arm movement.