Takanori Uka

Neural Correlates of Fine Depth Discrimination in Monkey Inferior Temporal Cortex

Binocular disparity is an important visual cue that gives rise to the perception of depth. Disparity signals are widely spread across the visual cortex, but their relative role is poorly understood. Here, we addressed the correlation between the responses of disparity-selective neurons in the occipitotemporal (ventral) visual pathway and the behavioral discrimination of stereoscopic depth. We recorded activity of disparity-selective neurons in the inferior temporal cortex (IT) while monkeys were engaged in a fine stereoscopic depth discrimination (stereoacuity) task. We found that trial-to-trial fluctuations in neuronal responses correlated with the monkeys perceptual choice. We suggest that disparity signals in the IT, located in the ventral visual pathway, are functionally linked to the discrimination of fine-grain depth.

Dynamic readout of behaviorally relevant signals from area MT during task switching.

The processes underlying dynamic changes in human behavior during real situations contain much irrelevant information and represent a key issue facing neuroscientists. Although the roles played by the frontal cortex in this switching behavior have been well documented, little is known regarding how neural pathways governing sensorimotor associations accomplish such a switch. We addressed this question by recording activities of middle temporal (MT) neurons in monkeys switching between direction versus depth discrimination tasks. Although the monkeys successfully switched between the tasks, neural sensitivity did not change as a function of task. More importantly, neurons that signaled the same motor output showed trial-to-trial covariation between neuronal responses and perceptual judgments during both tasks, whereas neurons that signaled the opposite motor output showed no covariation in either task. These results suggest that task switching is accomplished via communication from distinct populations of neurons when sensorimotor associations switch within a short time period.

White Matter Alteration in Metabolic Syndrome Diffusion tensor analysis

OBJECTIVE We explored the regional pattern of white matter alteration in subjects with metabolic syndrome. We also investigated whether white matter alteration was correlated with BMI. RESEARCH DESIGN AND METHODS Seven middle-aged men with metabolic syndrome and seven without metabolic syndrome underwent diffusion tensor imaging with a 3T magnetic resonance imaging imager. We analyzed the fractional anisotropy (FA) values by using a tract-based spatial statistics technique (whole-brain analysis). We subsequently focused on measuring the mean FA values of the right inferior fronto-occipital fasciculus (IFOF) of all subjects by tract-specific analysis (regional brain analysis). We used a Pearson correlation coefficient to evaluate the relationship between BMI and mean FA values of the right IFOF. RESULTS In the whole-brain analysis, subjects with metabolic syndrome had significantly lower FA values than control subjects in part of the right external capsule (part of the right IFOF), the entire corpus callosum, and part of the deep white matter of the right frontal lobe. In the regional brain analysis, the mean FA value of the right IFOF was 0.41 ± 0.03 for subjects with metabolic syndrome and 0.44 ± 0.05 for control subjects. A significant negative correlation was observed between BMI and FA values in the right IFOF (r = −0.56, P < 0.04). CONCLUSIONS Our results show that microstructural white matter changes occur in patients with metabolic syndrome. FA values may be useful indices of white matter alterations in patients with metabolic syndrome.

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.

Architecture of binocular disparity processing in monkey inferior temporal cortex.

Neurons in the inferior temporal (IT) cortex respond not only to the shape, color or texture of objects, but to the horizontal positional disparity of visual features in the right and left retinal images. IT neurons with similar shape selectivity cluster in columns. In this study, we examined how IT neurons are spatially arranged in the IT according to their selectivity for binocular disparity. With a single electrode, we simultaneously recorded extracellular action potentials from a single neuron and those from background multiple neurons at the same sites or recorded multineuronal responses at successive sites along electrode penetrations, while monkeys performed a fixation task. For neurons at each recording site, effective shapes were first determined from a set of 20 shapes presented at the zero-disparity plane. The most effective shape was then presented with varying amounts of disparity. Single neuron responses and background multiunit responses recorded at the same sites showed a similar ability of disparity discrimination and tended to share the preferred disparity, suggesting that neurons with similar disparity selectivity are clustered in the IT. We estimated from sequential recordings along electrode penetrations that the size of the neuronal clusters with similar disparity selectivity was smaller than the size of clusters with similar shape selectivity.

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.

A Leaky-Integrator Model as a Control Mechanism Underlying Flexible Decision Making during Task Switching

The ability to switch between tasks is critical for animals to behave according to context. Although the association between the prefrontal cortex and task switching has been well documented, the ultimate modulation of sensory–motor associations has yet to be determined. Here, we modeled the results of a previous study showing that task switching can be accomplished by communication from distinct populations of sensory neurons. We proposed a leaky-integrator model where relevant and irrelevant information were stored separately in two integrators and task switching was achieved by leaking information from the irrelevant integrator. The model successfully explained both the behavioral and neuronal data. Additionally, the leaky-integrator model showed better performance than an alternative model, where irrelevant information was discarded by decreasing the weight on irrelevant information, when animals initially failed to commit to a task. Overall, we propose that flexible switching is, in part, achieved by actively controlling the amount of leak of relevant and irrelevant information.