What is next in African neuroscience?

Working in Africa provides neuroscientists with opportunities that are not available in other continents. Populations in this region exhibit the greatest genetic diversity; they live in ecosystems with diverse flora and fauna; and they face unique stresses to brain health, including child brain health and development, due to high levels of traumatic brain injury and diseases endemic to the region. However, the neuroscience community in Africa has yet to reach its full potential.

Ultra-High-Field Neuroimaging Reveals Fine-Scale Processing for 3D Perception.

Binocular disparity provides critical information about three-dimensional (3D) structures to support perception and action. In the past decade significant progress has been made in uncovering human brain areas engaged in the processing of binocular disparity signals. Yet, the fine-scale brain processing underlying 3D perception remains unknown.

How multisensory neurons solve causal inference.

Sitting in a static railway carriage can produce illusory self-motion if the train on an adjoining track moves off. While our visual system registers motion, vestibular signals indicate that we are stationary. The brain is faced with a difficult challenge: is there a single cause of sensations (I am moving) or two causes (I am static, another train is moving)? If a single cause, integrating signals produces a more precise estimate of self-motion, but if not, one cue should be ignored.

Exploring and explaining properties of motion processing in biological brains using a neural network.

Visual motion perception underpins behaviors ranging from navigation to depth perception and grasping. Our limited access to biological systems constrains our understanding of how motion is processed within the brain. Here we explore properties of motion perception in biological systems by training a neural network to estimate the velocity of image sequences.

But Still It Moves: Static Image Statistics Underlie How We See Motion.

Seeing movement promotes survival. It results from an uncertain interplay between evolution and experience, making it hard to isolate the drivers of computational architectures found in brains. Here we seek insight into motion perception using a neural network (MotionNet) trained on moving images to classify velocity.

Learning predictive structure without a teacher: decision strategies and brain routes.

Extracting the structure of complex environments is at the core of our ability to interpret the present and predict the future. This skill is important for a range of behaviours from navigating a new city to learning music and language. Classical approaches that investigate our ability to extract the principles of organisation that govern complex environments focus on reward-based learning.

Adaptation to Binocular Anticorrelation Results in Increased Neural Excitability.

Throughout the brain, information from individual sources converges onto higher order neurons. For example, information from the two eyes first converges in binocular neurons in area V1. Some neurons are tuned to similarities between sources of information, which makes intuitive sense in a system striving to match multiple sensory signals to a single external cause-that is, establish causal inference.

Mixed-polarity random-dot stereograms alter GABA and Glx concentration in the early visual cortex.

The offset between images projected onto the left and right retina (binocular disparity) provides a powerful cue to the three-dimensional structure of the environment. It was previously shown that depth judgements are better when images comprise both light and dark features, rather than only light or only dark elements. Since Harris and Parker ( 374: 808-811, 1995) discovered the "mixed-polarity benefit," there has been limited evidence supporting their hypothesis that the benefit is due to separate bright and dark channels.

Contextual effects on binocular matching are evident in primary visual cortex.

Global context can dramatically influence local visual perception. This phenomenon is well-documented for monocular features, e.g.

Areal differences in depth cue integration between monkey and human.

Electrophysiological evidence suggested primarily the involvement of the middle temporal (MT) area in depth cue integration in macaques, as opposed to human imaging data pinpointing area V3B/kinetic occipital area (V3B/KO). To clarify this conundrum, we decoded monkey functional MRI (fMRI) responses evoked by stimuli signaling near or far depths defined by binocular disparity, relative motion, and their combination, and we compared results with those from an identical experiment previously performed in humans. Responses in macaque area MT are more discriminable when two cues concurrently signal depth, and information provided by one cue is diagnostic of depth indicated by the other.

The mixed-polarity benefit of stereopsis arises in early visual cortex.

Depth perception is better when observers view stimuli containing a mixture of bright and dark visual features. It is currently unclear where in the visual system sensory processing benefits from the availability of different contrast polarity. To address this question, we applied transcranial magnetic stimulation to the visual cortex to modulate normal neural activity during processing of single- or mixed-polarity random-dot stereograms.

Shape Perception: Boundary Conditions on a Grey Area.

Modulations in light intensity across a visual image could be caused by a flat object with varying pigmentation, such as wallpaper, or differential light reflection from a three-dimensional shape made of uniform material, such as curtains. A new study identifies key image cues that help the brain work out which interpretation to select.

White-Matter Pathways for Statistical Learning of Temporal Structures.

Extracting the statistics of event streams in natural environments is critical for interpreting current events and predicting future ones. The brain is known to rapidly find structure and meaning in unfamiliar streams of sensory experience, often by mere exposure to the environment (i.e.

Proscription supports robust perceptual integration by suppression in human visual cortex.

Perception relies on integrating information within and between the senses, but how does the brain decide which pieces of information should be integrated and which kept separate? Here we demonstrate how proscription can be used to solve this problem: certain neurons respond best to unrealistic combinations of features to provide 'what not' information that drives suppression of unlikely perceptual interpretations. First, we present a model that captures both improved perception when signals are consistent (and thus should be integrated) and robust estimation when signals are conflicting. Second, we test for signatures of proscription in the human brain.

Learning predictive statistics from temporal sequences: Dynamics and strategies.

Human behavior is guided by our expectations about the future. Often, we make predictions by monitoring how event sequences unfold, even though such sequences may appear incomprehensible. Event structures in the natural environment typically vary in complexity, from simple repetition to complex probabilistic combinations.

Functional brain networks for learning predictive statistics.

Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. This skill relies on extracting regular patterns in space and time by mere exposure to the environment (i.e.

Learning Predictive Statistics: Strategies and Brain Mechanisms.

When immersed in a new environment, we are challenged to decipher initially incomprehensible streams of sensory information. However, quite rapidly, the brain finds structure and meaning in these incoming signals, helping us to predict and prepare ourselves for future actions. This skill relies on extracting the statistics of event streams in the environment that contain regularities of variable complexity from simple repetitive patterns to complex probabilistic combinations.

The Human Brain in Depth: How We See in 3D.

Human perception is remarkably flexible: We experience vivid three-dimensional (3D) structure under diverse conditions, from the seemingly random magic-eye stereograms to the aesthetically beautiful, but obviously flat, canvases of the Old Masters. How does the brain achieve this apparently effortless robustness? Using brain imaging we are beginning to discover how different parts of the visual cortex support 3D perception by tracing different computations in the dorsal and ventral pathways. This review concentrates on studies of binocular disparity and its combination with other depth cues.

"What Not" Detectors Help the Brain See in Depth.

Binocular stereopsis is one of the primary cues for three-dimensional (3D) vision in species ranging from insects to primates. Understanding how the brain extracts depth from two different retinal images represents a tractable challenge in sensory neuroscience that has so far evaded full explanation. Central to current thinking is the idea that the brain needs to identify matching features in the two retinal images (i.

Mapping the visual brain areas susceptible to phosphene induction through brain stimulation.

Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation technique whose effects on neural activity can be uncertain. Within the visual cortex, phosphenes are a useful marker of TMS: They indicate the induction of neural activation that propagates and creates a conscious percept. However, we currently do not know how susceptible different areas of the visual cortex are to TMS-induced phosphenes.

Lesions to right posterior parietal cortex impair visual depth perception from disparity but not motion cues.

The posterior parietal cortex (PPC) is understood to be active when observers perceive three-dimensional (3D) structure. However, it is not clear how central this activity is in the construction of 3D spatial representations. Here, we examine whether PPC is essential for two aspects of visual depth perception by testing patients with lesions affecting this region.

'Proto-rivalry': how the binocular brain identifies gloss.

Visually identifying glossy surfaces can be crucial for survival (e.g. ice patches on a road), yet estimating gloss is computationally challenging for both human and machine vision.

Differential processing of binocular and monocular gloss cues in human visual cortex.

The visual impression of an object's surface reflectance ("gloss") relies on a range of visual cues, both monocular and binocular. Whereas previous imaging work has identified processing within ventral visual areas as important for monocular cues, little is known about cortical areas involved in processing binocular cues. Here, we used human functional MRI (fMRI) to test for brain areas selectively involved in the processing of binocular cues.