Dataset Information

Categorization training changes the visual representation of face identity.

ABSTRACT: Previous research suggests that learning to categorize faces along a new dimension changes the perceptual representation of that dimension, but little is known about how the representation of specific face identities changes after such category learning. Here, we trained participants to categorize faces that varied along two morphing dimensions. One dimension was relevant to the categorization task and the other was irrelevant. We used reverse correlation to estimate the internal templates used to identify the two faces at the extremes of the relevant dimension, both before and after training, and at two different levels of the irrelevant dimension. Categorization training changed the internal templates used for face identification, even though identification and categorization tasks impose different demands on the observers. After categorization training, the internal templates became more invariant across changes in the irrelevant dimension. These results suggest that the representation of face identity can be modified by categorization experience.

SUBMITTER: Soto FA

PROVIDER: S-EPMC6703175 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Categorization training changes the visual representation of face identity.

Soto Fabian A FA

Attention, perception & psychophysics 20190701 5

Previous research suggests that learning to categorize faces along a new dimension changes the perceptual representation of that dimension, but little is known about how the representation of specific face identities changes after such category learning. Here, we trained participants to categorize faces that varied along two morphing dimensions. One dimension was relevant to the categorization task and the other was irrelevant. We used reverse correlation to estimate the internal templates used ...[more]

PMID: 31152373

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Project description:Putting a name to a face is a highly common activity in our daily life that greatly enriches social interactions. Although this specific person-identity association becomes automatic with learning, it remains difficult and can easily be disrupted in normal circumstances or neurological conditions. To shed light on the neural basis of this important and yet poorly understood association between different input modalities in the human brain, we designed a crossmodal frequency-tagging paradigm coupled to brain activity recording via scalp and intracerebral electroencephalography. In Experiment 1, 12 participants were presented with variable pictures of faces and written names of a single famous identity at a 4-Hz frequency rate while performing an orthogonal task. Every 7 items, another famous identity appeared, either as a face or a name. Robust electrophysiological responses were found exactly at the frequency of identity change (i.e., 4 Hz / 7 = 0.571 Hz), suggesting a crossmodal neural response to person identity. In Experiment 2 with twenty participants, two control conditions with periodic changes of identity for faces or names only were added to estimate the contribution of unimodal neural activity to the putative crossmodal face-name responses. About 30% of the response occurring at the frequency of crossmodal identity change over the left occipito-temporal cortex could not be accounted for by the linear sum of unimodal responses. Finally, intracerebral recordings in the left ventral anterior temporal lobe (ATL) in 7 epileptic patients tested with this paradigm revealed a small number of "pure" crossmodal responses, i.e., with no response to changes of identity for faces or names only. Altogether, these observations provide evidence for integration of verbal and nonverbal person identity-specific information in the human brain, highlighting the contribution of the left ventral ATL in the automatic retrieval of face-name identity associations.

Project description:Visual categorization is integral for our interaction with the natural environment. In this process, similar selective responses are produced to a class of variable visual inputs. Whether categorization is supported by partial (graded) or absolute (all-or-none) neural responses in high-level human brain regions is largely unknown. We address this issue with a novel frequency-sweep paradigm probing the evolution of face categorization responses between the minimal and optimal stimulus presentation times. In a first experiment, natural images of variable non-face objects were progressively swept from 120 to 3 ?Hz (8.33-333 ?ms duration) in rapid serial visual presentation sequences. Widely variable face exemplars appeared every 1 ?s, enabling an implicit frequency-tagged face-categorization electroencephalographic (EEG) response at 1 ?Hz. Face-categorization activity emerged with stimulus durations as brief as 17 ?ms (17-83 ?ms across individual participants) but was significant with 33 ?ms durations at the group level. The face categorization response amplitude increased until 83 ?ms stimulus duration (12 ?Hz), implying graded categorization responses. In a second EEG experiment, faces appeared non-periodically throughout such sequences at fixed presentation rates, while participants explicitly categorized faces. A strong correlation between response amplitude and behavioral accuracy across frequency rates suggested that dilution from missed categorizations, rather than a decreased response to each face stimulus, accounted for the graded categorization responses as found in Experiment 1. This was supported by (1) the absence of neural responses to faces that participants failed to categorize explicitly in Experiment 2 and (2) equivalent amplitudes and spatio-temporal signatures of neural responses to behaviorally categorized faces across presentation rates. Overall, these observations provide original evidence that high-level visual categorization of faces, starting at about 100 ?ms following stimulus onset in the human brain, is variable across observers tested under tight temporal constraints, but occurs in an all-or-none fashion.

Dataset Information

Categorization training changes the visual representation of face identity.

Publications

Categorization training changes the visual representation of face identity.

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