Prof. Alan A. Stocker

The position is part of the ongoing NSF-funded project ‘Choice-induced biases in human decision-making’ in collaboration with the laboratory of Tobias Donner at the University Medical Center Hamburg, Germany. The goal of the project is to understand how decisions influence the memory of past (consistency bias) but also the evaluation of future evidence (confirmation bias) in human decision-making. The project employs a highly interdisciplinary approach that combines psychophysical and functional neuroimaging (MEG) experiments with theory and computational modeling.

Vocal emotion perception at millisecond speed

The human voice is possibly the most important sound category in the social landscape. Compared to other non-verbal emotion signals, the voice is particularly effective in communicating emotions: it can carry information over large distances and independent of sight. However, the study of vocal emotion expression and perception is surprisingly far less developed than the study of emotion in faces. Thereby, its neural and functional correlates remain elusive. As the voice represents a dynamically changing auditory stimulus, temporally sensitive techniques such as the EEG are particularly informative. In this talk, the dynamic neurocognitive operations that take place when we listen to vocal emotions will be specified, with a focus on the effects of stimulus type, task demands, and speaker and listener characteristics (e.g., age). These studies suggest that emotional voice perception is not only a matter of how one speaks but also of who speaks and who listens. Implications of these findings for the understanding of psychiatric disorders such as schizophrenia will be discussed.

Neural mechanisms underlying visual and vestibular self-motion perception

Connecting structure and function in early visual circuits

How does the brain interpret signals from the outside world? Walking through a park, you might take for granted the ease with which you can understand what you see. Rather than seeing a series of still snapshots, you are able to see simple, fluid movement — of dogs running, squirrels foraging, or kids playing basketball. You can track their paths and know where they are headed without much thought. “How does this process take place?” asks Rudy Behnia, PhD, a principal investigator at Columbia’s Mortimer B. Zuckerman Mind Brain Behavior Institute. “For most of us, it’s hard to imagine a world where we can’t see motion, shapes, and color; where we can’t have a representation of the physical world in our head.” And yet this representation does not happen automatically — our brain has no direct connection with the outside world. Instead, it interprets information taken in by our senses. Dr. Behnia is studying how the brain builds these representations. As a starting point, she focuses on how we see motion

Looking and listening while moving

In this talk I’ll discuss our recent work on how visual and auditory cues to space are integrated as we move. There are at least 3 reasons why this turns out to be a difficult problem for the brain to solve (and us to understand!). First, vision and hearing start off in different coordinates (eye-centred vs head-centred), so they need a common reference frame in which to communicate. By preventing eye and head movements, this problem has been neatly sidestepped in the literature, yet self-movement is the norm. Second, self-movement creates visual and auditory image motion. Correct interpretation therefore requires some form of compensation. Third, vision and hearing encode motion in very different ways: vision contains dedicated motion detectors sensitive to speed, whereas hearing does not. We propose that some (all?) of these problems could be solved by considering the perception of audiovisual space as the integration of separate body-centred visual and auditory cues, the latter formed by integrating image motion with motor system signals and vestibular information. To test this claim, we use a classic cue integration framework, modified to account for cues that are biased and partially correlated. We find good evidence for the model based on simple judgements of audiovisual motion within a circular array of speakers and LEDs that surround the participant while they execute self-controlled head movement.

The role of motion in localizing objects

Everything we see has a location. We know where things are before we know what they are. But how do we know where things are? Receptive fields in the visual system specify location but neural delays lead to serious errors whenever targets or eyes are moving. Motion may be the problem here but motion can also be the solution, correcting for the effects of delays and eye movements. To demonstrate this, I will present results from three motion illusions where perceived location differs radically from physical location. These help understand how and where position is coded. We first look at the effects of a target’s simple forward motion on its perceived location. Second, we look at perceived location of a target that has internal motion as well as forward motion. The two directions combine to produce an illusory path. This “double-drift” illusion strongly affects perceived position but, surprisingly, not eye movements or attention. Even more surprising, fMRI shows that the shifted percept does not emerge in the visual cortex but is seen instead in the frontal lobes. Finally, we report that a moving frame also shifts the perceived positions of dots flashed within it. Participants report the dot positions relative to the frame, as if the frame were not moving. These frame-induced position effects suggest a link to visual stability where we see a steady world despite massive displacements during saccades. These motion-based effects on perceived location lead to new insights concerning how and where position is coded in the brain.

Causal inference can explain hierarchical motion perception and is reflected in neural responses in MT

COSYNE 2022

Structure in motion: visual motion perception as online hierarchical inference

COSYNE 2022

Structure in motion: visual motion perception as online hierarchical inference

COSYNE 2022

Divisive normalization as a mechanism for hierarchical causal inference in motion perception

COSYNE 2023

Bayesian perceptual adaptation in auditory motion perception: A multimodal approach with EEG and pupillometry

FENS Forum 2024