Different computations over the same inputs produce selective behavior in algorithmic brain networks.

A key challenge in neuroimaging remains to understand where, when, and now particularly human brain networks compute over sensory inputs to achieve behavior. To study such dynamic algorithms from mass neural signals, we recorded the magnetoencephalographic (MEG) activity of participants who resolved the classic XOR, OR, and AND functions as overt behavioral tasks (N = 10 participants/task, N-of-1 replications). Each function requires a different computation over the same inputs to produce the task-specific behavioral outputs.

Healthy aging delays the neural processing of face features relevant for behavior by 40 ms.

Fast and accurate face processing is critical for everyday social interactions, but it declines and becomes delayed with age, as measured by both neural and behavioral responses. Here, we addressed the critical challenge of understanding how aging changes neural information processing mechanisms to delay behavior. Young (20-36 years) and older (60-86 years) adults performed the basic social interaction task of detecting a face versus noise while we recorded their electroencephalogram (EEG).

The Deceptively Simple N170 Reflects Network Information Processing Mechanisms Involving Visual Feature Coding and Transfer Across Hemispheres.

A key to understanding visual cognition is to determine "where", "when", and "how" brain responses reflect the processing of the specific visual features that modulate categorization behavior-the "what". The N170 is the earliest Event-Related Potential (ERP) that preferentially responds to faces. Here, we demonstrate that a paradigmatic shift is necessary to interpret the N170 as the product of an information processing network that dynamically codes and transfers face features across hemispheres, rather than as a local stimulus-driven event.

Tracing the Flow of Perceptual Features in an Algorithmic Brain Network.

The model of the brain as an information processing machine is a profound hypothesis in which neuroscience, psychology and theory of computation are now deeply rooted. Modern neuroscience aims to model the brain as a network of densely interconnected functional nodes. However, to model the dynamic information processing mechanisms of perception and cognition, it is imperative to understand brain networks at an algorithmic level--i.

Eye coding mechanisms in early human face event-related potentials.

In humans, the N170 event-related potential (ERP) is an integrated measure of cortical activity that varies in amplitude and latency across trials. Researchers often conjecture that N170 variations reflect cortical mechanisms of stimulus coding for recognition. Here, to settle the conjecture and understand cortical information processing mechanisms, we unraveled the coding function of N170 latency and amplitude variations in possibly the simplest socially important natural visual task: face detection.

How recent experience affects the perception of ambiguous objects.

Sensory information from the external world is inherently ambiguous, necessitating prior experience as a constraint on perception. Recent experience with clear, prototypical stimuli may, however, induce complex effects on the subsequent perception of ambiguous ones, ranging from attraction (priming) to repulsion (adaptation aftereffects). In the present study, we ask what determines the direction and magnitude of the effects in the case of images of naturalistic (complex) objects, which are putatively analyzed in advanced visual cortices and under the influence of multimodal semantic memories.

Dynamics of trimming the content of face representations for categorization in the brain.

To understand visual cognition, it is imperative to determine when, how and with what information the human brain categorizes the visual input. Visual categorization consistently involves at least an early and a late stage: the occipito-temporal N170 event related potential related to stimulus encoding and the parietal P300 involved in perceptual decisions. Here we sought to understand how the brain globally transforms its representations of face categories from their early encoding to the later decision stage over the 400 ms time window encompassing the N170 and P300 brain events.

Experience-dependent coding of facial expression in superior temporal sulcus.

Sensory information from the external world is inherently ambiguous, necessitating prior experience as a constraint on perception. Prolonged experience (adaptation) induces perception of ambiguous morph faces as a category different from the adapted category, suggesting sensitivity in underlying neural codes to differences between input and recent experience. Using magnetoencephalography, we investigated the neural dynamics of such experience-dependent visual coding by focusing on the timing of responses to morphs after facial expression adaptation.