Hironori Kumano

Neuronal mechanisms of visual perceptual learning

Numerous psychophysical studies have described perceptual learning as long-lasting improvements in perceptual discrimination and detection capabilities following practice. Where and how long-term plastic changes occur in the brain is central to understanding the neural basis of perceptual learning. Here, neurophysiological research using non-human primates is reviewed to address the neural mechanisms underlying visual perceptual learning. Previous studies have shown that training either has no effect on or only weakly alters the sensitivity of neurons in early visual areas, but more recent evidence indicates that training can cause long-term changes in how sensory signals are read out in the later stages of decision making. These results are discussed in the context of learning specificity, which has been crucial in interpreting the mechanisms underlying perceptual learning. The possible mechanisms that support learning-related plasticity are also discussed.

Change in Choice-Related Response Modulation in Area MT during Learning of a Depth-Discrimination Task is Consistent with Task Learning

What are the neural mechanisms underlying improvement in perceptual performance due to learning? A recent study using motion-direction discrimination suggested that perceptual learning is due to improvements in the “readout” of sensory signals in sensory–motor cortex and not to improvements in neural sensitivity of the sensory cortex. To test the generality of this hypothesis, we examined this in a similar but different task. We recorded from isolated neurons in the middle temporal (MT) area while monkeys were trained in a depth-discrimination task. Consistent with earlier reports using direction discrimination, we found no long-term improvement in MT neuron sensitivity to depth, although monkey performance improved over months with extensive training, even when taking out the effect of behavioral biases. We further addressed improvement in the readout of sensory signals by focusing on choice-related response modulation [choice probability (CP)]. CP increased with training, suggesting an improvement in the readout of sensory signals from MT. CP, however, correlated more strongly with lapse rate than psychophysical threshold, suggesting that changes in readout may be restricted to early phases of learning. To test how behavioral learning, as well as the magnitude of CP, transferred across visual fields, we measured CP variation in one hemifield after training monkeys on the depth-discrimination task in the opposite hemifield. CP was large from the beginning of training in the untrained hemifield, even though a small but significant improvement in sensitivity was observed behaviorally. Overall, our findings are consistent with the idea that increases in CP reflect task learning.

The Spatial Profile of Macaque MT Neurons Is Consistent With Gaussian Sampling of Logarithmically Coordinated Visual Representation

Neurons in extrastriate visual areas have large receptive fields (RFs) compared with those in primary visual cortex (V1), suggesting extensive spatial integration. To examine the spatial integration of neurons in area MT, we modeled the RFs of MT neurons based on a symmetrical (Gaussian) integration of V1 outputs and tested the model using single-unit recording in two fixating macaque monkeys. Because visual representation in V1 is logarithmically compressed along eccentricity, the resulting RF model is log-Gaussian along the radial axis in polar coordinates. To test the log-Gaussian model, the RF of each neuron was mapped on a 5 x 5 grid using a small patch of random dots drifting at the preferred velocity of the neuron. The majority of MT neurons had RFs with a steeper slope near the fovea and a shallower slope away from the fovea. Among various two-dimensional Gaussian models fitted to the RFs, the log-Gaussian model provided the best description. The fitted parameters revealed that the range of sampling by MT neurons has no systematic relationship with eccentricities, consistent with a recent study for V4 neurons. Our results suggest that MT neurons integrate inputs from constant-sized patches of V1 cortex.

Responses to Random Dot Motion Reveal Prevalence of Pattern-Motion Selectivity in Area MT

How the visual system reconstructs global patterns of motion from components is an important issue in vision. Conventional studies using plaids have shown that approximately one-third of neurons in cortical area MT respond to one-dimensional (1D) components of a moving pattern (component cells), whereas another third responds to the global two-dimensional (2D) motion of a pattern (pattern cells). Conversely, studies using spots of light or random dots that contain multiple orientations have seldom reported directional tuning that is consistent with 1D motion preference. To bridge the gap between these studies, we recorded from isolated neurons in macaque area MT and measured tuning for velocity (direction and speed) using random dot stimuli. We used the “intersection of constraints” principle to classify our population into pattern-direction-selective (PDS) neurons and component-direction-selective (CDS) neurons. We found a larger proportion of PDS cells (68%) and a smaller proportion of CDS cells (8%) compared with prior studies using plaids. We further compared velocity tuning, measured using random dot stimuli, with direction tuning, measured using plaids. Although there was a correlation between the degree of preference for 2D over 1D motion of the two measurements, tuning seemed to prefer 2D motion using random dot stimuli. Modeling analyses suggest that integration across orientations contributes to the 2D motion preference of both dots and plaids, but opponent inhibition mainly contributes to the 2D motion preference of plaids. We conclude that MT neurons become more capable of identifying a particular 2D velocity when stimuli contain multiple orientations.

Context-Dependent Accumulation of Sensory Evidence in the Parietal Cortex Underlies Flexible Task Switching

Switching behavior based on multiple rules is a fundamental ability of flexible behavior. Although interactions among the frontal, parietal, and sensory cortices are necessary for such flexibility, little is known about the neural computations concerning context-dependent information readouts. Here, we provide evidence that neurons in the lateral intraparietal area (LIP) accumulate relevant information preferentially depending on context. We trained monkeys to switch between direction and depth discrimination tasks and analyzed the buildup activity in the LIP depending on task context. In accordance with behavior, the rate of buildup to identical visual stimuli differed between tasks and buildup was prominent only for the stimulus dimension relevant to the task. These results indicate that LIP neurons accumulate relevant information depending on context to decide flexibly where to move the eye, suggesting that flexibility is, at least partly, implemented in the form of temporal integration gain control. SIGNIFICANCE STATEMENT Flexible behavior depending on context is a hallmark of human cognition. During flexible behavior, the frontal and parietal cortices have complex representations that hinder efforts to conceptualize their underlying computations. We now provide evidence that neurons in the lateral intraparietal area accumulate relevant information preferentially depending on context. We suggest that behavioral flexibility is implemented in the form of temporal integration gain control in the parietal cortex.

Reduction in receptive field size of macaque MT neurons in the presence of visual noise

The visual system faces a trade-off between increased spatial integration of disparate local signals and improved spatial resolution to filter out irrelevant noise. Increased spatial integration is beneficial when signals are weak, whereas increased spatial resolution is particularly beneficial when focusing on a small object in a cluttered natural scene. The receptive field (RF) size of visual cortical neurons can be modulated depending on various factors such as sensory context, allowing adaptive integration of sensory signals. In this study, we explored the spatial integration properties of neurons in macaque middle temporal visual area (MT). We hypothesized that spatial resolution would increase when high-contrast noise was presented simultaneously with a visual stimulus, enabling focus on a small object in a cluttered scene. To test this hypothesis, we mapped the RFs of MT neurons of two fixating monkeys in a 5 × 5 grid manner using a small patch of random-dot motion. To examine the effects of noise on RF profile, a dynamic noise (0% coherence dots) of varying diameter was concurrently presented at the RF center. We found that RF size decreased when noise diameter increased. Analyses based on the response normalization model and area summation provided evidence for the potential contribution of spatial summation properties within the RF and surround suppression to the apparent contraction of RF size. Our results suggest that MT neurons integrate smaller regions of motion signals when signals are embedded in noise, an efficient strategy to filter out surrounding noise.

Visual impairment by surrounding noise is due to interactions among stimuli in the higher-order visual cortex

Observers have difficulty identifying a target in their peripheral vision in the presence of surrounding stimuli. Although hypotheses addressing this phenomenon have been proposed, such as the integration of stimuli and surround suppression in the higher-order visual cortex, no direct comparisons of the psychophysical and neuronal sensitivities have been performed. Here we measured the performance of monkeys with a variant of the direction discrimination task using a center/surround bipartite random-dot stimulus while simultaneously recording from isolated neurons from the middle temporal visual area (MT). The psychophysical threshold increased with the addition of a task-irrelevant noise annulus that surrounded the task-relevant motion stimuli. The neuronal threshold of MT neurons also increased at a spatial scale similar to the psychophysical threshold. This suggests that the impaired ability in our task resulted from impairment in the MT area. Importantly, reduced neuronal performance was due to both a reduced response to preferred motion and an enhanced response to nonpreferred motion. These observations suggest that impairment caused by surrounding noise results from interactions between stimuli and noise and not from a reduction in the response of visual neurons.

Quantification of direction-speed tuning and its relationship with pattern motion selectivity in macaque area MT

Faces play an important role in our social contexts as they convey essential information regarding identity, emotional expressions, or intent. In ERP studies, the components such as N170, VPP (vertex positive potential) are known to be the face-selective components. N170 is negative ERP component between 140 and 200 ms from stimulus onset peaks around 170 ms at the posterior temporal sites, which clearly distinguishes faces from non-face visual stimuli. This component is thought to reflect the structural encoding stage of faces, and a number of studies regarding the face configuration have been reported. Facial color as well as the face configuration, is an important factor for face information. However there are few studies investigating effect of facial color on N170. This study aims to reveal the relationships among hue change in facial color, the N170 component and behavioral evaluation of unnaturalness. We recorded ERPs while subjects viewed face stimulus with facial color of eight hue angles, which were created for each human face images by 45 rotating the original facial color distribution around the white point. A one-way repeated measure ANOVA was performed with facial color (0, 45, 90, 135, 180, −45, −90, −135◦) to the peak amplitude. For N170 amplitude, the main effect of facial color was found in the left hemisphere [F(7,91) = 2.86, p < 0.01], but it was non-significant in the right hemisphere. Our results showed that N170 peak amplitude in left hemisphere tended to increase as the hue angle from the original image color was bigger.

Spatial resolution of direction discrimination: comparison of MT neurons and behavior

Ocular following responses (OFRs) are elicited with ultra-short latencies (∼60 ms) by sudden motion of a visual scene. It is known that the OFRs are largely influenced by luminance signals which are mediated by the magno system. However, little is known whether the OFRs are influenced by color signals which are processed by the parvo system. First, we made vertical isoluminant color sinusoidal gratings with minimum motion technique and recorded the OFRs to horizontal motion of the gratings in monkeys. We found that the isoluminant color gratings did elicit the OFRs. Then, we recorded the OFRs to moving color-gratings and luminance-gratings at 6 spatial (0.07–2.3 cpd) and 5 temporal frequencies (1.56–25 Hz). We found that the high spatial and low temporal frequencies were more suitable for the color-gratings to elicit the OFRs than for the luminance-gratings. These results suggest that the OFRs can also be driven by the signals mediated by the parvo system whose visual responses show high spatial and low temporal resolution.