Hiromasa Takemura

A Major Human White Matter Pathway Between Dorsal and Ventral Visual Cortex

Human visual cortex comprises many visual field maps organized into clusters. A standard organization separates visual maps into 2 distinct clusters within ventral and dorsal cortex. We combined fMRI, diffusion MRI, and fiber tractography to identify a major white matter pathway, the vertical occipital fasciculus (VOF), connecting maps within the dorsal and ventral visual cortex. We use a model-based method to assess the statistical evidence supporting several aspects of the VOF wiring pattern. There is strong evidence supporting the hypothesis that dorsal and ventral visual maps communicate through the VOF. The cortical projection zones of the VOF suggest that human ventral (hV4/VO-1) and dorsal (V3A/B) maps exchange substantial information. The VOF appears to be crucial for transmitting signals between regions that encode object properties including form, identity, and color and regions that map spatial information.

White matter consequences of retinal receptor and ganglion cell damage.

PURPOSE Patients with Leber hereditary optic neuropathy (LHON) and cone-rod dystrophy (CRD) have central vision loss; but CRD damages the retinal photoreceptor layer, and LHON damages the retinal ganglion cell (RGC) layer. Using diffusion MRI, we measured how these two types of retinal damage affect the optic tract (ganglion cell axons) and optic radiation (geniculo-striate axons). METHODS Adult onset CRD (n = 5), LHON (n = 6), and healthy controls (n = 14) participated in the study. We used probabilistic fiber tractography to identify the optic tract and the optic radiation. We compared axial and radial diffusivity at many positions along the optic tract and the optic radiation. RESULTS In both types of patients, diffusion measures within the optic tract and the optic radiation differ from controls. The optic tract change is principally a decrease in axial diffusivity; the optic radiation change is principally an increase in radial diffusivity. CONCLUSIONS Both photoreceptor layer (CRD) and retinal ganglion cell (LHON) retinal disease causes substantial change in the visual white matter. These changes can be measured using diffusion MRI. The diffusion changes measured in the optic tract and the optic radiation differ, suggesting that they are caused by different biological mechanisms.

Neural Correlates of Induced Motion Perception in the Human Brain

A physically stationary stimulus surrounded by a moving stimulus appears to move in the opposite direction. There are similarities between the characteristics of this phenomenon of induced motion and surround suppression of directionally selective neurons in the brain. Here, functional magnetic resonance imaging was used to investigate the link between the subjective perception of induced motion and cortical activity. The visual stimuli consisted of a central drifting sinusoid surrounded by a moving random-dot pattern. The change in cortical activity in response to changes in speed and direction of the central stimulus was measured. The human cortical area hMT+ showed the greatest activation when the central stimulus moved at a fast speed in the direction opposite to that of the surround. More importantly, the activity in this area was the lowest when the central stimulus moved in the same direction as the surround and at a speed such that the central stimulus appeared to be stationary. The results indicate that the activity in hMT+ is related to perceived speed modulated by induced motion rather than to physical speed or a kinetic boundary. Early visual areas (V1, V2, V3, and V3A) showed a similar pattern; however, the relationship to perceived speed was not as clear as that in hMT+. These results suggest that hMT+ may be a neural correlate of induced motion perception and play an important role in contrasting motion signals in relation to their surrounding context and adaptively modulating our motion perception depending on the spatial context.

The visual white matter: The application of diffusion MRI and fiber tractography to vision science.

Visual neuroscience has traditionally focused much of its attention on understanding the response properties of neurons along the visual pathways. This review focuses instead on the properties of the white matter connections between these neurons. Specifically, we provide an introduction to methods to study the human visual white matter using diffusion MRI (dMRI). This method allows us to measure the white matter connections in individual visual systems in vivo, allows us to trace long-range connections between different parts of the visual system, and to measure the biophysical properties of these connections. We explain the principles underlying dMRI measurements and the basics of modeling these data. We review a range of findings from recent studies on connections between different visual field maps, on the effects of visual impairment on the white matter, and on the properties underlying networks that process visual information that supports visual face recognition. Finally, we discuss a few promising directions for future studies. These include new methods for analysis of MRI data, open data-sets that are becoming available to study brain connectivity and white matter properties, and open-source software for the analysis of these data.

Visual motion detection sensitivity is enhanced by orthogonal induced motion

Visual motion information passes through several distinct stages including local motion processing in an earlier stage, followed by global motion processing at a later stage. However, the stage at which the perceptual limit of detection arises remains unknown. In order to examine which stage is critical for motion detection, we investigated how vertical illusory motion affected detection performance for physical horizontal motion. We introduced illusory induced motion, such that a central pattern would be perceived as moving in the opposite direction to the surrounding motion, even though the central stimulus was physically stationary. We presented the central Gabor patch, which was barely moving to the left or right, together with a surrounding grating moving vertically. Subjects were asked to judge whether the central stimulus was moving left or right, and thus the illusory vertical motion itself was task-irrelevant. We found that the performance on the horizontal test was enhanced when it was combined with the induced vertical motion, which resulted in the central motion appearing slightly oblique rather than purely horizontal. Our results indicate that the later stage, in which motion integration and center-surround interaction appears, is critical for determining the perceptual limit of motion detection.

Occipital White Matter Tracts in Human and Macaque

We compare several major white-matter tracts in human and macaque occipital lobe using diffusion magnetic resonance imaging. The comparison suggests similarities but also significant differences in the tracts. There are several apparently homologous tracts in the 2 species, including the vertical occipital fasciculus (VOF), optic radiation, forceps major, and inferior longitudinal fasciculus (ILF). There is one large human tract, the inferior fronto-occipital fasciculus, with no corresponding fasciculus in macaque. We could identify the macaque VOF (mVOF), which has been little studied. Its position is consistent with classical invasive anatomical studies by Wernicke. VOF homology is supported by similarity of the endpoints in V3A and ventral V4 across species. The mVOF fibers intertwine with the dorsal segment of the ILF, but the human VOF appears to be lateral to the ILF. These similarities and differences between the occipital lobe tracts will be useful in establishing which circuitry in the macaque can serve as an accurate model for human visual cortex.

The visual white matter: The application of diffusion MRI and fiber tractography to vision science

Visual neuroscience has traditionally focused much of its attention on understanding the response properties of single neurons or neuronal ensembles. The visual white matter and the long-range neuronal connections it supports are fundamental in establishing such neuronal response properties and visual function. This review article provides an introduction to measurements and methods to study the human visual white matter using diffusion MRI. These methods allow us to measure the microstructural and macrostructural properties of the white matter in living human individuals; they allow us to trace long-range connections between neurons in different parts of the visual system and to measure the biophysical properties of these connections. We also review a range of findings from recent studies on connections between different visual field maps, the effects of visual impairment on the white matter, and the properties underlying networks that process visual information supporting visual face recognition. Finally, we discuss a few promising directions for future studies. These include new methods for analysis of MRI data, open datasets that are becoming available to study brain connectivity and white matter properties, and open source software for the analysis of these data.

Stimulus-dependent adjustment of reward prediction error in the midbrain.

Previous reports have described that neural activities in midbrain dopamine areas are sensitive to unexpected reward delivery and omission. These activities are correlated with reward prediction error in reinforcement learning models, the difference between predicted reward values and the obtained reward outcome. These findings suggest that the reward prediction error signal in the brain updates reward prediction through stimulus–reward experiences. It remains unknown, however, how sensory processing of reward-predicting stimuli contributes to the computation of reward prediction error. To elucidate this issue, we examined the relation between stimulus discriminability of the reward-predicting stimuli and the reward prediction error signal in the brain using functional magnetic resonance imaging (fMRI). Before main experiments, subjects learned an association between the orientation of a perceptually salient (high-contrast) Gabor patch and a juice reward. The subjects were then presented with lower-contrast Gabor patch stimuli to predict a reward. We calculated the correlation between fMRI signals and reward prediction error in two reinforcement learning models: a model including the modulation of reward prediction by stimulus discriminability and a model excluding this modulation. Results showed that fMRI signals in the midbrain are more highly correlated with reward prediction error in the model that includes stimulus discriminability than in the model that excludes stimulus discriminability. No regions showed higher correlation with the model that excludes stimulus discriminability. Moreover, results show that the difference in correlation between the two models was significant from the first session of the experiment, suggesting that the reward computation in the midbrain was modulated based on stimulus discriminability before learning a new contingency between perceptually ambiguous stimuli and a reward. These results suggest that the human reward system can incorporate the level of the stimulus discriminability flexibly into reward computations by modulating previously acquired reward values for a typical stimulus.

Computational neuroanatomy of human stratum proprium of interparietal sulcus

Recent advances in diffusion-weighted MRI (dMRI) and tractography have enabled identification of major long-range white matter tracts in the human brain. Yet, our understanding of shorter tracts, such as those within the parietal lobe, remains limited. Over a century ago, a tract connecting the superior and inferior parts of the parietal cortex was identified in a post-mortem study: stratum proprium of interparietal sulcus (SIPS; Sachs, Das hemisphärenmark des menschlichen grosshirns. Verlag von georg thieme, Leipzig, 1892). The tract has since been replicated in another fibre dissection study (Vergani et al., Cortex 56:145–156, 2014), however, it has not been fully investigated in the living human brain and its precise anatomical properties are yet to be described. We used dMRI and tractography to identify and characterise SIPS in vivo, and explored its spatial proximity to the cortical areas associated with optic-flow processing using fMRI. SIPS was identified bilaterally in all subjects, and its anatomical position and trajectory are consistent with previous post-mortem studies. Subsequent evaluation of the tractography results using the linear fascicle evaluation and virtual lesion analysis yielded strong statistical evidence for SIPS. We also found that the SIPS endpoints are adjacent to the optic-flow selective areas. In sum, we show that SIPS is a short-range tract connecting the superior and inferior parts of the parietal cortex, wrapping around the intraparietal sulcus, and that it may be a crucial anatomy underlying optic-flow processing. In vivo identification and characterisation of SIPS will facilitate further research on SIPS in relation to cortical functions, their development, and diseases that affect them.

Neuronal population decoding explains the change in signal detection sensitivity caused by task-irrelevant perceptual bias

Spatiotemporal context in sensory stimulus has profound effects on neural responses and perception, and it sometimes affects task difficulty. Recently reported experimental data suggest that human detection sensitivity to motion in a target stimulus can be enhanced by adding a slow surrounding motion in an orthogonal direction, even though the illusory motion component caused by the surround is not relevant to the task. It is not computationally clear how the task-irrelevant component of motion modulates the subjects sensitivity to motion detection. In this study, we investigated the effects of encoding biases on detection performance by modeling the stochastic neural population activities. We modeled two types of modulation on the population activity profiles caused by a contextual stimulus: one type is identical to the activity evoked by a physical change in the stimulus, and the other is expressed more simply in terms of response gain modulation. For both encoding schemes, the motion detection performance of the ideal observer is enhanced by a task-irrelevant, additive motion component, replicating the properties observed for real subjects. The success of these models suggests that human detection sensitivity can be characterized by a noisy neural encoding that limits the resolution of information transmission in the cortical visual processing pathway. On the other hand, analyses of the neuronal contributions to the task predict that the effective cell populations differ between the two encoding schemes, posing a question concerning the decoding schemes that the nervous system used during illusory states.