Neuronal correlates of a perceptual decision

The relationship between neuronal activity and psychophysical judgement has long been of interest to students of sensory processing. Previous analyses of this problem have compared the performance of human or animal observers in detection or discrimination tasks with the signals carried by individual neurons, but have been hampered because neuronal and perceptual data were not obtained at the same time and under the same conditions. We have now measured the performance of monkeys and of visual cortical neurons while the animals performed a psychophysical task well matched to the properties of the neurons under study. Here we report that the reliability and sensitivity of most neurons on this task equalled or exceeded that of the monkeys. We therefore suggest that under our conditions, psychophysical judgements could be based on the activity of a relatively small number of neurons.     

A general mechanism for perceptual decision-making in the human brain

Findings from single-cell recording studies suggest that a comparison of the outputs of different pools of selectively tuned lower-level sensory neurons may be a general mechanism by which higher-level brain regions compute perceptual decisions. For example, when monkeys must decide whether a noisy field of dots is moving upward or downward, a decision can be formed by computing the difference in responses between lower-level neurons sensitive to upward motion and those sensitive to downward motion. Here we use functional magnetic resonance imaging and a categorization task in which subjects decide whether an image presented is a face or a house to test whether a similar mechanism is also at work for more complex decisions in the human brain and, if so, where in the brain this computation might be performed. Activity within the left dorsolateral prefrontal cortex is greater during easy decisions than during difficult decisions, covaries with the difference signal between face- and house-selective regions in the ventral temporal cortex, and predicts behavioural performance in the categorization task. These findings show that even for complex object categories, the comparison of the outputs of different pools of selectively tuned neurons could be a general mechanism by which the human brain computes perceptual decisions.     

Representation of a perceptual decision in developing oculomotor commands

Behaviour often depends on the ability to make categorical judgements about sensory information acquired over time. Such judgements require a comparison of the evidence favouring the alternatives, but how the brain forms these comparisons is unknown. Here we show that in a visual discrimination task, the accumulating balance of sensory evidence favouring one interpretation over another is evident in the neural circuits that generate the behavioural response. We trained monkeys to make a direction judgement about dynamic random-dot motions and to indicate their judgement with an eye movement to a visual target. We interrupted motion viewing with electrical microstimulation of the frontal eye field and analysed the resulting, evoked eye movements for evidence of ongoing activity associated with the oculomotor response. Evoked eye movements deviated in the direction of the monkey's judgement. The magnitude of the deviation depended on motion strength and viewing time. The oculomotor signals responsible for these deviations reflected the accumulated motion information that informed the monkey's choices on the discrimination task. Thus, for this task, decision formation and motor preparation appear to share a common level of neural organization.     

Adaptive coding of visual information in neural populations

Our perception of the environment relies on the capacity of neural networks to adapt rapidly to changes in incoming stimuli. It is increasingly being realized that the neural code is adaptive, that is, sensory neurons change their responses and selectivity in a dynamic manner to match the changes in input stimuli. Understanding how rapid exposure, or adaptation, to a stimulus of fixed structure changes information processing by cortical networks is essential for understanding the relationship between sensory coding and behaviour. Physiological investigations of adaptation have contributed greatly to our understanding of how individual sensory neurons change their responses to influence stimulus coding, yet whether and how adaptation affects information coding in neural populations is unknown. Here we examine how brief adaptation (on the timescale of visual fixation) influences the structure of interneuronal correlations and the accuracy of population coding in the macaque (Macaca mulatta) primary visual cortex (V1). We find that brief adaptation to a stimulus of fixed structure reorganizes the distribution of correlations across the entire network by selectively reducing their mean and variability. The post-adaptation changes in neuronal correlations are associated with specific, stimulus-dependent changes in the efficiency of the population code, and are consistent with changes in perceptual performance after adaptation. Our results have implications beyond the predictions of current theories of sensory coding, suggesting that brief adaptation improves the accuracy of population coding to optimize neuronal performance during natural viewing.     

Signal but not noise changes with perceptual learning

Perceptual discrimination improves with practice. This 'perceptual learning' is often specific to the stimuli presented during training, indicating that practice may alter the response characteristics of cortical sensory neurons. Although much is known about how learning modifies cortical circuits, it remains unclear how these changes relate to behaviour. Different theories assume that practice improves discrimination by enhancing the signal, diminishing internal noise or both. Here, to distinguish among these alternatives, we fashioned sets of faces and textures whose signal strength could be varied, and we trained observers to identify these patterns embedded in noise. Performance increased by up to 400% across several sessions over several days. Comparisons of human performance to that of an ideal discriminator showed that learning increased the efficiency with which observers encoded task-relevant information. Observer response consistency, measured by a double-pass technique in which identical stimuli are shown twice in each experimental session, did not change during training, showing that learning had no effect on internal noise. These results indicate that perceptual learning may enhance signal strength, and provide important constraints for theories of learning.     

A neural representation of depth from motion parallax in macaque visual cortex

Perception of depth is a fundamental challenge for the visual system, particularly for observers moving through their environment. The brain makes use of multiple visual cues to reconstruct the three-dimensional structure of a scene. One potent cue, motion parallax, frequently arises during translation of the observer because the images of objects at different distances move across the retina with different velocities. Human psychophysical studies have demonstrated that motion parallax can be a powerful depth cue, and motion parallax seems to be heavily exploited by animal species that lack highly developed binocular vision. However, little is known about the neural mechanisms that underlie this capacity. Here we show, by using a virtual-reality system to translate macaque monkeys (Macaca mulatta) while they viewed motion parallax displays that simulated objects at different depths, that many neurons in the middle temporal area (area MT) signal the sign of depth (near versus far) from motion parallax in the absence of other depth cues. To achieve this, neurons must combine visual motion with extra-retinal (non-visual) signals related to the animal's movement. Our findings suggest a new neural substrate for depth perception and demonstrate a robust interaction of visual and non-visual cues in area MT. Combined with previous studies that implicate area MT in depth perception based on binocular disparities, our results suggest that area MT contains a more general representation of three-dimensional space that makes use of multiple cues.     

Behavioural report of single neuron stimulation in somatosensory cortex

Understanding how neural activity in sensory cortices relates to perception is a central theme of neuroscience. Action potentials of sensory cortical neurons can be strongly correlated to properties of sensory stimuli and reflect the subjective judgements of an individual about stimuli. Microstimulation experiments have established a direct link from sensory activity to behaviour, suggesting that small neuronal populations can influence sensory decisions. However, microstimulation does not allow identification and quantification of the stimulated cellular elements. The sensory impact of individual cortical neurons therefore remains unknown. Here we show that stimulation of single neurons in somatosensory cortex affects behavioural responses in a detection task. We trained rats to respond to microstimulation of barrel cortex at low current intensities. We then initiated short trains of action potentials in single neurons by juxtacellular stimulation. Animals responded significantly more often in single-cell stimulation trials than in catch trials without stimulation. Stimulation effects varied greatly between cells, and on average in 5% of trials a response was induced. Whereas stimulation of putative excitatory neurons led to weak biases towards responding, stimulation of putative inhibitory neurons led to more variable and stronger sensory effects. Reaction times for single-cell stimulation were long and variable. Our results demonstrate that single neuron activity can cause a change in the animal's detection behaviour, suggesting a much sparser cortical code for sensations than previously anticipated.     

Spatio-temporal correlations and visual signalling in a complete neuronal population

Statistical dependencies in the responses of sensory neurons govern both the amount of stimulus information conveyed and the means by which downstream neurons can extract it. Although a variety of measurements indicate the existence of such dependencies, their origin and importance for neural coding are poorly understood. Here we analyse the functional significance of correlated firing in a complete population of macaque parasol retinal ganglion cells using a model of multi-neuron spike responses. The model, with parameters fit directly to physiological data, simultaneously captures both the stimulus dependence and detailed spatio-temporal correlations in population responses, and provides two insights into the structure of the neural code. First, neural encoding at the population level is less noisy than one would expect from the variability of individual neurons: spike times are more precise, and can be predicted more accurately when the spiking of neighbouring neurons is taken into account. Second, correlations provide additional sensory information: optimal, model-based decoding that exploits the response correlation structure extracts 20% more information about the visual scene than decoding under the assumption of independence, and preserves 40% more visual information than optimal linear decoding. This model-based approach reveals the role of correlated activity in the retinal coding of visual stimuli, and provides a general framework for understanding the importance of correlated activity in populations of neurons.     

Modulation of the motion aftereffect by selective attention

The motion aftereffect is a much studied and well documented phenomenon. After viewing a moving visual pattern for a period of time, the same pattern appears to drift in the opposite direction when it is stopped. Psychophysical experiments involving interocular transfer, dichoptic stimulation, and motion aftereffects contingent upon other visual parameters such as colour, orientation and texture, imply that the motion aftereffect is generated at the level of the visual cortex. It has been hypothesized that cortical neurons specialized for the detection of motion along a particular direction become 'fatigued' during the adaptation period so that the resting equilibrium subsequently shifts in the opposite direction to that of the adapting stimulus, giving rise to the sensation of the aftereffect. I have found that if observers are engaged in a separate discrimination task superimposed on a moving textured background, the subsequent motion aftereffect to the background is considerably reduced. It seems that motion aftereffects are susceptible to attentional mechanisms.     

A neuronal mechanism for sensory gating during locomotion in a vertebrate

The response of the foot to touch during walking depends on whether it is in the air or on the ground. In most animals, reflex responses to external stimuli are similarly adapted to their timing in the locomotor cycle, but there is only fragmentary information about the neural mechanisms involved. In arthropods, reflex modulation can occur in the sensory receptors themselves and in neurons that discharge during locomotion. By recording with dye-filled microelectrodes from neurons in the spinal cord of frog embryos, we describe reflex modulation at the level of sensory interneurons. Sensory inputs from skin receptors excite a specific class of spinal sensory interneuron whose activity leads to reflex bending of the body away from the stimulus. During swimming, these inputs are gated by rhythmic postsynaptic inhibition, so that sensory drive reaches motor neurons only at phases in the locomotor cycle when the resulting contraction would likewise turn the embryo away from the stimulated side. Such gating of sensory pathways could be a general feature of all locomotor systems where responses to sensory stimuli need to be adapted to the phase of locomotion.     

Practising orientation identification improves orientation coding in V1 neurons

The adult brain shows remarkable plasticity, as demonstrated by the improvement in fine sensorial discriminations after intensive practice. The behavioural aspects of such perceptual learning are well documented, especially in the visual system. Specificity for stimulus attributes clearly implicates an early cortical site, where receptive fields retain fine selectivity for these attributes; however, the neuronal correlates of a simple visual discrimination task remained unidentified. Here we report electrophysiological correlates in the primary visual cortex (V1) of monkeys for learning orientation identification. We link the behavioural improvement in this type of learning to an improved neuronal performance of trained compared to naive neurons. Improved long-term neuronal performance resulted from changes in the characteristics of orientation tuning of individual neurons. More particularly, the slope of the orientation tuning curve that was measured at the trained orientation increased only for the subgroup of trained neurons most likely to code the orientation identified by the monkey. No modifications of the tuning curve were observed for orientations for which the monkey had not been trained. Thus training induces a specific and efficient increase in neuronal sensitivity in V1.     

Motion speed modulates walking direction discrimination: The role of the feet in biological motion perception

The human visual system is tuned to the motions of biological entities, which provide potentially vital information for survival. The current study examines the interplay between motion speed and motion direction perception. Following a brief presentation of a point-light walker walking straight ahead or slightly leftward or rightward, observers were asked to quickly judge the walking direction (left or right). Participants showed better direction discrimination when the walker walked at a fast pace compared to a natural or slow pace, and this was not simply due to a difference in motion cycles. Moreover, walking direction sensitivity could be enhanced by increasing the feet motion speed alone, so long as the direction of feet movement was consistent with that of the other body parts. These findings demonstrate that our perception of walking direction is influenced by local motion speed, and highlight the role of the feet in biological motion perception.     

Regulation of lifespan by sensory perception in Caenorhabditis elegans

Caenorhabditis elegans senses environmental signals through ciliated sensory neurons located primarily in sensory organs in the head and tail. Cilia function as sensory receptors, and mutants with defective sensory cilia have impaired sensory perception. Cilia are membrane-bound microtubule-based structures and in C. elegans are only found at the dendritic endings of sensory neurons. Here we show that mutations that cause defects in sensory cilia or their support cells, or in sensory signal transduction, extend lifespan. Our findings imply that sensory perception regulates the lifespan of this animal, and suggest that in nature, its lifespan may be regulated by environmental cues.     

Perceptual consequences of centre-surround antagonism in visual motion processing

Centre-surround receptive field organization is a ubiquitous property in mammalian visual systems, presumably tailored for extracting image features that are differentially distributed over space. In visual motion, this is evident as antagonistic interactions between centre and surround regions of the receptive fields of many direction-selective neurons in visual cortex. In a series of psychophysical experiments we make the counterintuitive observation that increasing the size of a high-contrast moving pattern renders its direction of motion more difficult to perceive and reduces its effectiveness as an adaptation stimulus. We propose that this is a perceptual correlate of centre-surround antagonism, possibly within a population of neurons in the middle temporal visual area. The spatial antagonism of motion signals observed at high contrast gives way to spatial summation as contrast decreases. Evidently, integration of motion signals over space depends crucially on the visibility of those signals, thereby allowing the visual system to register motion information efficiently and adaptively.     

Neural networks and perceptual learning

Sensory perception is a learned trait. The brain strategies we use to perceive the world are constantly modified by experience. With practice, we subconsciously become better at identifying familiar objects or distinguishing fine details in our environment. Current theoretical models simulate some properties of perceptual learning, but neglect the underlying cortical circuits. Future neural network models must incorporate the top-down alteration of cortical function by expectation or perceptual tasks. These newly found dynamic processes are challenging earlier views of static and feedforward processing of sensory information.     

Activation of specific interneurons improves V1 feature selectivity and visual perception

Inhibitory interneurons are essential components of the neural circuits underlying various brain functions. In the neocortex, a large diversity of GABA (γ-aminobutyric acid) interneurons has been identified on the basis of their morphology, molecular markers, biophysical properties and innervation pattern. However, how the activity of each subtype of interneurons contributes to sensory processing remains unclear. Here we show that optogenetic activation of parvalbumin-positive (PV+) interneurons in the mouse primary visual cortex (V1) sharpens neuronal feature selectivity and improves perceptual discrimination. Using multichannel recording with silicon probes and channelrhodopsin-2 (ChR2)-mediated optical activation, we found that increased spiking of PV+ interneurons markedly sharpened orientation tuning and enhanced direction selectivity of nearby neurons. These effects were caused by the activation of inhibitory neurons rather than a decreased spiking of excitatory neurons, as archaerhodopsin-3 (Arch)-mediated optical silencing of calcium/calmodulin-dependent protein kinase IIα (CAMKIIα)-positive excitatory neurons caused no significant change in V1 stimulus selectivity. Moreover, the improved selectivity specifically required PV+ neuron activation, as activating somatostatin or vasointestinal peptide interneurons had no significant effect. Notably, PV+ neuron activation in awake mice caused a significant improvement in their orientation discrimination, mirroring the sharpened V1 orientation tuning. Together, these results provide the first demonstration that visual coding and perception can be improved by increased spiking of a specific subtype of cortical inhibitory interneurons.     

Neural correlates of perceptual motion coherence.

The motions of overlapping contours in a visual scene may arise from the physical motion(s) of either a single or multiple surface(s). A central problem facing the visual motion system is that of assigning the most likely interpretation. The rules underlying this perceptual decision can be explored using a visual stimulus formed by superimposing two moving gratings. The resultant percept is either that of a single coherently moving 'plaid pattern' (coherent motion) or of the two component gratings sliding noncoherently across one another (noncoherent motion). When plaid patterns are configured to mimic one transparent grating overlying another, the percept of noncoherent motion dominates. We now report that neurons in the visual cortex of rhesus monkeys exhibit changes in direction tuning that parallel this perceptual phenomenon: sensitivity to the motions of the component gratings is enhanced under conditions that favour the perception of noncoherent motion. These results challenge models of cortical visual processing that fail to take into account the contribution of figural image segmentation cues to the analysis of visual motion.     

Lateral habenula as a source of negative reward signals in dopamine neurons

Midbrain dopamine neurons are key components of the brain's reward system, which is thought to guide reward-seeking behaviours. Although recent studies have shown how dopamine neurons respond to rewards and sensory stimuli predicting reward, it is unclear which parts of the brain provide dopamine neurons with signals necessary for these actions. Here we show that the primate lateral habenula, part of the structure called the epithalamus, is a major candidate for a source of negative reward-related signals in dopamine neurons. We recorded the activity of habenula neurons and dopamine neurons while rhesus monkeys were performing a visually guided saccade task with positionally biased reward outcomes. Many habenula neurons were excited by a no-reward-predicting target and inhibited by a reward-predicting target. In contrast, dopamine neurons were excited and inhibited by reward-predicting and no-reward-predicting targets, respectively. Each time the rewarded and unrewarded positions were reversed, both habenula and dopamine neurons reversed their responses as the bias in saccade latency reversed. In unrewarded trials, the excitation of habenula neurons started earlier than the inhibition of dopamine neurons. Furthermore, weak electrical stimulation of the lateral habenula elicited strong inhibitions in dopamine neurons. These results suggest that the inhibitory input from the lateral habenula plays an important role in determining the reward-related activity of dopamine neurons.     

Neurons compute internal models of the physical laws of motion

A critical step in self-motion perception and spatial awareness is the integration of motion cues from multiple sensory organs that individually do not provide an accurate representation of the physical world. One of the best-studied sensory ambiguities is found in visual processing, and arises because of the inherent uncertainty in detecting the motion direction of an untextured contour moving within a small aperture. A similar sensory ambiguity arises in identifying the actual motion associated with linear accelerations sensed by the otolith organs in the inner ear. These internal linear accelerometers respond identically during translational motion (for example, running forward) and gravitational accelerations experienced as we reorient the head relative to gravity (that is, head tilt). Using new stimulus combinations, we identify here cerebellar and brainstem motion-sensitive neurons that compute a solution to the inertial motion detection problem. We show that the firing rates of these populations of neurons reflect the computations necessary to construct an internal model representation of the physical equations of motion.     

Imaging cortical correlates of illusion in early visual cortex

Exploring visual illusions reveals fundamental principles of cortical processing. Illusory motion perception of non-moving stimuli was described almost a century ago by Gestalt psychologists. However, the underlying neuronal mechanisms remain unknown. To explore cortical mechanisms underlying the 'line-motion' illusion, we used real-time optical imaging, which is highly sensitive to subthreshold activity. We examined, in the visual cortex of the anaesthetized cat, responses to five stimuli: a stationary small square and a long bar; a moving square; a drawn-out bar; and the well-known line-motion illusion, a stationary square briefly preceding a long stationary bar presentation. Whereas flashing the bar alone evoked the expected localized, short latency and high amplitude activity patterns, presenting a square 60-100 ms before a bar induced the dynamic activity patterns resembling that of fast movement. The preceding square, even though physically non-moving, created gradually propagating subthreshold cortical activity that must contribute to illusory motion, because it was indistinguishable from cortical representations of real motion in this area. These findings demonstrate the effect of spatio-temporal patterns of subthreshold synaptic potentials on cortical processing and the shaping of perception.