Exam 3 Flashcards

Question

What was the purpose of scrambling images in the control analysis?

Answer 1

To rule out low-level perceptual differences that could drive the observed effects.

Answer 2

It suggests that there are specialized cortical regions for processing faces.

Answer 3

Low-level perceptual differences between the stimuli could account for the effects.

Answer 4

By showing that scrambled versions of faces still elicited strong responses.

Answer 5

Faces may naturally draw our attention due to their social significance.

Answer 6

The fusiform gyrus responds selectively to faces and indicates a specialized processing pathway for them.

Answer 7

There are many alternative explanations for observed responses.

Answer 8

The ability to recognize faces regardless of their orientation or location.

Answer 9

Adaptation, where the neuronal response decreases with repeated exposure.

Answer 10

It processes them more efficiently, reducing energy expenditure.

Answer 11

The response is reduced.

Answer 12

It adapts to stimuli, reducing energy use.

Answer 13

The average activity across cells is reduced.

Answer 14

A decrease in response to the same stimulus over time.

Answer 15

* Viewpoint invariant representation * Viewpoint specific representation

Answer 16

The face is recognized regardless of its orientation in space.

Answer 17

It does not show adaptation.

Answer 18

It leads to a stronger adaptation response.

Answer 19

Fusiform Face Area.

Answer 20

It may be a visual expertise region rather than solely a face region.

Answer 21

Experts show different responses compared to non-experts.

Answer 22

strong adaptation.

Answer 23

It results in higher levels of response compared to identical faces.

Answer 24

Faces as distinct based on their orientation.

Answer 25

If they represent the same identity.

Answer 26

Identity can outweigh perceptual differences in adaptation.

Answer 27

It encodes both identity and spatial orientation.

Answer 28

Experts in other categories showed different adaptation responses.

Answer 29

Different expertise leads to varied responses in the FFA.

Answer 30

Recognition of faces is independent of their spatial orientation.

Answer 31

The FFA is being mischaracterized as the face region; it is actually a visual expertise region.

Answer 32

Attentional manipulations are driving the response of the FFA based on subjects' expertise.

Answer 33

Expertise in recognizing characters from the 'crazy family' of rebels.

Answer 34

Activation occurs in specific brain areas when experts see rebels.

Answer 35

Rebels may look somewhat face-like, potentially influencing perception.

Answer 36

Causal manipulation evidence from patients undergoing brain surgery.

Answer 37

Patients report perceiving faces even when no face is present.

Answer 38

Information about specific facial features like eyes and nose.

Answer 39

Prosopagnosia.

Answer 40

A firefighter who lost the ability to recognize faces after injuries.

Answer 41

They can recognize other details in the world but not faces.

Answer 42

There are specialized regions for face perception that can be damaged in isolation.

Answer 43

visual expertise

Answer 44

It is the representation to respond to certain categories of stimuli.

Answer 45

-Certain stimuli are located in different sections of the brain. I did find it at the early 1800s or the first. I started to go for imaging technology to examine brain activity in healthy individuals is at the center of all types of stimuli. -What was discovered was that there are in regions of high, low visual cortex that respond very strongly to certain types of stimulation, categories of feelings. Ex: Faces, places, What I like places Tv, violence,visual words, bodies and people who are living now. - Clusters of neurons respond to visual stimuli high and low.

Answer 46

It does not know if the brain has specialized for that kind of purpose. But It is specialized for specific high level categories of things.

Answer 47

One idea of the predominant data for these findings for the now, was that there was just a sort of general purpose machinery where you sort of build up as detectors to be one to more complex things like textures and shapes. And then you got to sort of general purpose support, identifying all different types of categories for faces, objects, animals, all different types of things. And it wouldn't necessarily be a cluster of neurons that would look specifically for faces or a cluster. Or specifically for coffee. I didn't know that before they actually did these experiments.

Answer 48

There's not going to be like a specialized module for every single thing that we look at, or why these particular categories have specialized regions. Its a debate.

Answer 49

Face- "Fusiform face area"(FFA) Faces>Scenes 'Parahippocampal place area'(PPA) faces

Answer 50

Regions on the ventral visual stream. They are located in the ventral temporal cortex. Located near the part of the primary care gyrus. Go to the fusiform narrows.

Answer 51

is in recognizing what these thing are and become highly complex after that. You want the back of the brain and who work directly along the ventral steam.

Answer 52

Stronger responses to faces rather than scenes. Did a study of comparison to determine what was the underlying cause. who were the people.

Answer 53

Neurons must be located for places, so researches who applied electric and other visual cortex to different types of stimuli did sometimes. find neurons that would respond strongly to the faces. And having a condition where they are not able to perceive faces.

Answer 54

Where people have difficulty perceiving faces. See everything except faces. Can be a developing thing or just something more like brain trauma.

Answer 55

Run a scan to compare faces and other objects, and see if there any regions of the visual system that respond to more to faces. They were doing a good example of attentiveness. Just. the basic idea watch a video of the object/faces and perceive the reaction it shown.

Answer 56

Methods they use: For FMRI Scale, they used a block scale design, where stimuli is shown on blocks. looking at the idea of some sort of voxels. That is the average FMRI activity. And then labeling the different types in the scanner. Faces were shown for 30 seconds. Nothing shown 20 seconds and later objects was shown 45 seconds. nothing 20 seconds. This case is called a blind neturo, lot of faces, lots of objects, and lots of faces. Dealing with 2 different aspects.

Answer 57

This case is called a blind neturo, lot of faces, lots of objects, and lots of faces. Dealing with 2 different aspects.

Answer 58

It has low temporal dynamics and low temporal resolution. So we can't really see ground operation time with the right data because the low resolution and dynamics of the signal. So anyways you're looking at response. Motion peaks in 46 seconds you know its onset. It takes time to to go back to the baseline. There is ways to do this statically now but its hard. Just instead worry about the FMRI blocks.

Answer 59

Slow general dynamics mean that signals change gradually over time. Low temporal resolution (e.g., in fMRI) prevents capturing precise, fast neural events. The response peaks 4-6 seconds after stimulus onset, making real-time tracking inaccurate. It takes time to return to baseline, affecting event timing interpretation. To compensate, researchers analyze large time blocks and average activity within them.

Answer 60

That Face is stronger spikes and objects is not.

Answer 61

A cluster of voxels is a group of neighboring voxels showing statistically significant activation in brain imaging (e.g., fMRI, PET). Instead of analyzing single voxels, clustering improves statistical power and reduces false positives. Used in thresholding to identify meaningful brain activity. Helps detect functionally relevant brain regions instead of isolated noise.

Answer 62

The subtraction method isolates task-specific brain activity by comparing two conditions. Formula: (Task Condition Activity) - (Control Condition Activity) = True Neural Response. Helps identify which brain areas are activated during a specific task. Reduces background noise by removing baseline activity. Common in fMRI and PET studies (e.g., comparing reading words vs. looking at a blank screen). so find what you are trying to look for example faces: Remove the blue and are set with with face specific area. Since the other don't happen twice.

Answer 63

So another methodological thing to point out. is the idea of looking at regions of interest and specifically functional regions of interest. Can look very specific region for the subtraction method. Instead of looking at anatomy of the brain. Ex: How the fusiform gyrus responds to different types types of stimuli. That is my interest. so I use circle form anatomy to identify the fusiform juror using data from there to analyze the boxes.

Answer 64

ROIs are specific brain regions selected for focused analysis instead of studying the whole brain. They are often chosen based on their response properties rather than just anatomical location. Example: The Fusiform Face Area (FFA) is an ROI for face perception studies. Functional ROIs improve accuracy by identifying task-specific brain activity.

Answer 65

Because once they release the faces, they realized that different cluster in different section contain different slightly points for different faces. Each subject

Answer 66

Traditionally, ROIs were defined using anatomical landmarks (e.g., identifying the fusiform gyrus structurally). Now, ROIs are often defined functionally based on how they respond to stimuli (e.g., face perception). Functional ROIs improve accuracy since activation clusters vary slightly in location across individuals.

Answer 67

Activation clusters (e.g., for face perception) may appear in slightly different locations in each person. If we just average across all subjects, meaningful activations might cancel out or appear weaker. Solution: Use individualized functional ROIs instead of relying on group-averaged brain maps.

Answer 68

A localizer task identifies specific voxels that respond to a stimulus (e.g., faces) in each subject. It ensures that the correct functional region is analyzed, even if its location varies between people. Used before the main experiment to define subject-specific ROIs.

Answer 69

By comparing face perception vs. object perception in each subject. Localizer data helps identify face-selective voxels in the fusiform gyrus. This allows for more precise ROI selection in follow-up experiments.

Answer 70

Location-Based Averaging ❌ Averages the physical location of activation across subjects. Problem: Individual differences cause misalignment, leading to signal blurring or cancellation. Signal-Based Averaging (Individualized ROIs) ✅ Identifies the strongest activation location per person first. Averages the brain activity strength from the correct region. More accurate since it preserves real functional responses.

Answer 71

Researchers found that activation clusters (e.g., for face perception) appear in every person but in slightly different locations. Traditional averaging methods would have missed this pattern, making the activation seem weaker or nonexistent. This insight led to the discovery of category-selective regions (e.g., Fusiform Face Area for faces). Impact: Changed how we understand visual cortex organization and functional specialization.

Answer 72

A simple observation (e.g., activation clusters don’t always align across individuals) led to new ways of analyzing brain activity. Many breakthroughs come from just looking at the data differently rather than from complex experiments. Neuroscience progresses by challenging old assumptions—this discovery changed how we study functional brain regions.

Answer 73

A difference in brain activation might be due to contrast, brightness, or other visual features, not face perception itself. Researchers controlled for this by scrambling images to remove structured face-like patterns while keeping low-level features (e.g., contrast) the same. This helps confirm that activation in the Fusiform Face Area (FFA) is due to face perception, not just image contrast.

Answer 74

Control analyses ensure that observed brain activity isn’t driven by irrelevant low-level features. In face perception studies, researchers use scrambled images to rule out the effects of brightness, contrast, or spatial frequency. This strengthens the claim that activation differences are truly related to cognitive processes (e.g., face recognition) rather than visual artifacts.

Answer 75

Hight contrast images, thus you do scramble them to make it similar.

Answer 76

-If FFA is. truly selective, it should respond more to faces than scramble with the same low-level visual. features. Which both seem strong response to faces and scramble. is based on the hight level based on the perception. Anti-faces more than faces.

Answer 77

Brain activation differences could be due to contrast, brightness, or spatial frequency, not just face perception. Researchers use control analysis to ensure effects are driven by high-level face processing rather than simple visual features. Example: High contrast vs. low contrast images—without controls, contrast differences might falsely appear as face-specific activation.

Answer 78

Scrambling images removes structured face-like patterns but preserves contrast and other low-level features. If the Fusiform Face Area (FFA) still responds strongly to scrambled faces, then the effect isn’t driven by contrast or brightness alone. This confirms that FFA activation is linked to high-level face processing, not just visual properties.

Answer 79

Researchers first identify face-selective voxels using functional tasks (e.g., Faces vs. Objects). These face-selective voxels become a Region of Interest (ROI) for further analysis. Later, they extract brain activity from those specific voxels to study responses to new stimuli.

Answer 80

Face-processing regions (like FFA) vary slightly in location across individuals. Instead of averaging across a general brain area, researchers extract activity only from functionally relevant voxels. This approach improves accuracy and ensures that measured activation is truly related to face perception.

Answer 81

More contrast can be a play. Response to contrast instead. They scrambled the faces. And preserve all lowlevel. See more to anit-faces more than scramble. So it's simple they found the average or section, go more in. depth to find different section. Then they estimate different wavelengths from it.

Answer 82

Even after controlling for contrast, another confound is that faces belong to the same category, whereas objects may come from multiple categories. This means the brain might be responding not just to faces, but to category consistency in general. To test this, researchers needed a new control condition—objects from a single category (e.g., houses) instead of mixed categories.

Answer 83

Instead of comparing faces vs. a mix of objects, they compared faces vs. a single category of objects (e.g., houses). This ensured that both conditions contained category-consistent stimuli. If the Fusiform Face Area (FFA) still responded more to faces, it confirmed that face perception involves specialized processing beyond general category effects.

Answer 84

While testing faces vs. houses, researchers found a brain region that strongly responded to houses but not faces. This led to the discovery of the Parahippocampal Place Area (PPA), which is specialized for processing scenes and places. Just like the Fusiform Face Area (FFA) processes faces, the PPA processes spatial environments.

Answer 85

These findings show that the visual cortex is functionally specialized, with distinct areas processing faces, objects, and places. The Fusiform Face Area (FFA) specializes in face perception. The Parahippocampal Place Area (PPA) specializes in scene/place recognition. This suggests that the brain has dedicated processing systems for different types of visual information.

Answer 86

Researchers initially contrasted faces vs. objects and later controlled for category consistency (e.g., faces vs. houses). However, the distinction was still broad (e.g., face region vs. inanimate object region). They tested places vs. objects to refine their understanding of specialized processing regions. This helped identify distinct visual processing areas beyond just a general “face region” and “object region.”

Answer 87

Faces are naturally attention-grabbing due to their social significance. If face-related brain activity is just due to increased attention, then attention—not face perception—could explain the effect. To test this, researchers designed tasks requiring equal attention to both conditions. If the face-selective region (FFA) still responds more to faces, then the effect is not just due to attention.

Answer 88

Recognizing faces is easy for most people, while recognizing hands is much harder. To rule out task difficulty, researchers tested hand recognition vs. face recognition. If brain activity differences were due to difficulty, then hard hand recognition should activate similar regions. However, face-selective areas still responded strongly to faces, suggesting a true face-processing specialization.

Answer 89

There are many possible alternative explanations for observed activation patterns. Researchers must systematically rule out confounds like contrast, attention, and task difficulty. Even with rigorous controls, it's impossible to exhaustively rule out every possible explanation. The goal is to provide the strongest possible evidence through well-designed experiments.

Answer 90

Yes to determine that maybe hands require more attention which faces do more.

Answer 91

The Fusiform Face Area (FFA), located on or around the fusiform gyrus, responds selectively to faces. Activation occurs whenever subjects view faces, suggesting a specialized face-processing region. This indicates that faces are a unique visual stimulus that requires dedicated neural processing.

Answer 92

No, not every object category has its own dedicated brain region. The Fusiform Face Area (FFA) is selective for faces, but similar specialized areas do not exist for every object type. Some other category-selective regions do exist, like the Parahippocampal Place Area (PPA) for places.

Answer 93

Evolutionary importance: Recognizing faces is critical for social interaction and survival. Expert processing: The brain has a specialized system for identifying faces efficiently. Neuroimaging evidence: The Fusiform Face Area (FFA) consistently activates for face stimuli but not for other objects.

Answer 94

A part of the fusiform gyrus is preferentially active during face viewing and many alternative explanations were rule out Implications that faces are special and not just another of. visual stimulus.

Answer 95

What happens if you change the viewpoint? Does FFA respond of the identify of faces? Are Faces Special?

Answer 96

If you show a stimulus twice in a row, you get a reduced response the second time.

Answer 97

Neural adaptation is when neurons respond less strongly when the same stimulus is shown twice in a row. The brain reduces its response because it has already processed the stimulus and may not need to reprocess it fully. Adaptation is thought to help the brain process information more efficiently by using less energy for repeated stimuli. The effect is strongest when the exact same stimulus is repeated, but it can still occur with slight variations.

Answer 98

Since adaptation leads to a reduced neural response for repeated stimuli, it helps researchers study how the brain represents information. If a brain region shows adaptation to a repeated face, it suggests that region processes facial identity. If the same face at a different angle still causes adaptation, it suggests a viewpoint-invariant face representation. Adaptation effects decrease over time and are weaker if different stimuli are shown in between.

Answer 99

If a brain region represents a face the same way regardless of viewing angle, it is viewpoint-invariant. Researchers show the same face from different angles and measure neural adaptation. If the Fusiform Face Area (FFA) still adapts (reduced response), it suggests that it recognizes the face regardless of angle. If adaptation does not occur, it means the brain treats the rotated face as a new stimulus instead of the same identity.

Answer 100

Exact repetition → Strong adaptation (e.g., same face, same angle). Slight changes → Weaker adaptation (e.g., same face, different angle). Different stimuli → No adaptation (e.g., different faces). Time gap → Reduced adaptation (the longer the delay, the weaker the effect). Intervening stimuli → Less adaptation (if other images are shown between repetitions).

Answer 101

Happens once, then we use less energy to do that. The brain is not just processing. Higther response when different lower response when the same.

Answer 102

activate same neurons become stronger thus it requires less energy to pass information. Show different same adaption wont be as hight do.

Answer 103

Viewpoint-invariant representation means the brain recognizes a face regardless of its angle or orientation. If the same face at different angles still causes adaptation, it suggests the brain processes facial identity independently of viewpoint. This indicates that facial recognition in the brain is not tied to spatial positioning but rather to identity-based processing.

Answer 104

They show the same face twice: Condition 1: Same face, same angle → Strong adaptation. Condition 2: Same face, different angle → If adaptation still occurs, it suggests viewpoint-invariant processing. If no adaptation occurs in Condition 2, it means the brain processes face identity and spatial orientation separately.

Answer 105

The FFA does not store detailed spatial information about where a face is in 3D space. Instead, it seems to process the identity of the face without encoding its specific position or orientation. This supports the idea that face perception is identity-driven rather than space-driven.

Answer 106

Recognizing faces from different angles is crucial for social interaction and survival. The brain generalizes identity across viewpoints, so we can identify people even when they turn their heads. This suggests that face perception is not just about visual features but about higher-level identity processing.

Answer 107

Back: They show the same face from different angles to see if brain activity adapts. If the Fusiform Face Area (FFA) still adapts, it suggests the brain recognizes identity regardless of angle (viewpoint-invariant processing). If no adaptation occurs, it means the brain processes each angle as a new stimulus, indicating viewpoint-dependent representation.

Answer 108

If the brain encodes faces in a binary spatial manner, it would only recognize faces at specific angles rather than generalizing identity across viewpoints. This would mean that face perception is angle-dependent, requiring the brain to process each orientation separately. Researchers test this by measuring if neurons in the Fusiform Face Area (FFA) adapt when a face is shown from different angles.

Answer 109

Dorsal stream → Processes spatial positioning and movement (where an object is). Ventral stream (including FFA) → Processes object identity (what an object is). Face recognition primarily happens in the ventral stream, suggesting faces are encoded for identity rather than exact spatial location. Dorsal located in space.

Answer 110

Viewpoint-Invariant Processing ✅ → The brain recognizes a face regardless of angle. Evidence: Adaptation (weaker response) when the same face is shown from different angles. Example: Fusiform Face Area (FFA) processes face identity independently of viewpoint. Viewpoint-Specific Processing ❌ → The brain treats faces from different angles as different. Evidence: No adaptation (strong response) to the second image. Some dorsal stream regions track faces in spatial position, making them viewpoint-dependent.

Answer 111

Identical faces repeated → Reduced neural response (adaptation) ✅ Different faces shown in sequence → High, sustained neural response ❌ This adaptation effect is seen all over the visual cortex, indicating that the brain processes repeated stimuli more efficiently.

Answer 112

Small changes (e.g., slight rotation, resizing) → Some adaptation occurs. Large changes (e.g., major rotation, viewpoint shift) → Minimal or no adaptation. This suggests that the brain retains some spatial information about faces but is sensitive to viewpoint changes.

Answer 113

Viewpoint Invariant Representation ✅ The brain recognizes the same face across different angles. If this is true, adaptation occurs when the same face is shown at a new angle. Viewpoint Specific Representation ❌ The brain treats the same face from different angles as entirely new stimuli. If this is true, no adaptation occurs—the response remains high for each new viewpoint. 📌 Key Experiment: If a brain area adapts (reduced response) when the face is shown at a different angle → It supports viewpoint invariance. If it does not adapt, it suggests viewpoint-specific encoding.

Answer 114

Back: If a brain region only encodes face identity, it should adapt to the same face even when rotated (viewpoint-invariant). If a brain region encodes viewpoint-specific details, it will treat rotated faces as new stimuli and show no adaptation. This allows researchers to determine whether a brain region tracks identity independently of angle or not.

Answer 115

Small changes (e.g., slight resizing or position shifts) → Some adaptation occurs, meaning the brain still recognizes the face. Large changes (e.g., major rotation, flipped viewpoint) → Minimal or no adaptation, meaning the brain sees it as a new stimulus. Conclusion: The brain retains some viewpoint information but does not fully ignore changes in orientation.

Answer 116

No, face recognition is partially viewpoint-invariant but still sensitive to large viewpoint changes. Some brain regions (e.g., Fusiform Face Area) process face identity, but adaptation decreases when the face rotates significantly. The brain balances identity recognition and spatial encoding, meaning faces are not entirely viewpoint-invariant.

Answer 117

The FFA does not show adaption for rotated views oof the same face which means that is representation are not viewpoint invariant.

Answer 118

The ventral stream is responsible for object and face recognition, not just abstract visual processing. It encodes facial identity, but also retains some information about spatial orientation. This means that face perception is not purely viewpoint-invariant—orientation still matters to some degree.

Answer 119

Face-selective areas encode identity-specific features, but also retain spatial orientation information. Unlike abstract conceptual processing, face perception in the ventral stream still cares about how the face is oriented in space. This means the brain processes both "who" the person is and "how" they appear in space.

Answer 120

Researchers blend two faces (e.g., Margaret Thatcher and another person) in a naturalistic way. This creates faces that look real but contain a mix of two identities. By testing how the brain reacts to different levels of identity mixing, researchers study how facial identity is represented neurally.

Answer 121

Morphing between two identities helps determine how flexibly the brain processes facial identity. If the brain treats a partially morphed face as one person, it suggests identity representation is categorical. If the brain recognizes gradual identity shifts, it suggests continuous facial encoding rather than strict categories.

Answer 122

Face stimuli that transitions from an image of Margaret thatcher to Marylin Monroe. In the "within: and "identical" conditions the indentity stay the same. in the "between" condition, the identity of the person changes from trial 1 to trial 2.

Answer 123

Different faces → High neural response (no adaptation). Same face repeated → Lower neural response (adaptation). This follows the classic definition of adaptation: repeated stimuli cause reduced activity in face-selective brain regions.

Answer 124

Researchers create a gradual transformation between two identities (e.g., 30% of one face mixed into another). This allows them to measure how the brain perceives identity shifts. If adaptation still occurs despite a partial identity change, it suggests identity perception is continuous rather than categorical.

Answer 125

Two faces physically differing by 30% may still be recognized as the same person. But two completely different people (also differing by 30%) are perceived as entirely different. This suggests that facial identity perception is nonlinear—small changes in a known face may not feel as drastic as changes in an unfamiliar face.

Answer 126

Face-selective regions (e.g., Fusiform Face Area, FFA) vary slightly across individuals. Functional localization helps accurately identify where face processing occurs in each person. Once localized, researchers can analyze how these regions respond to identity changes and adaptation effects.

Answer 127

Both of them different by 30 percent but for us it differs a lot.

Answer 128

Same face repeated → Lower neural response due to adaptation. Different faces shown → High neural response (no adaptation). This confirms that brain regions like the Fusiform Face Area (FFA) encode identity recognition through adaptation effects

Answer 129

If two faces differ by 30% but are perceived as the same identity, adaptation still occurs. If two faces differ by 30% and are perceived as different people, no adaptation occurs. This suggests the brain prioritizes identity representation over minor feature differences.

Answer 130

The brain adapts to identity, not just physical features. Even when faces have small feature differences, if they are perceived as the same person, adaptation still happens. This suggests identity representation in the brain is more robust than exact pixel-level differences.

Answer 131

Some physically different faces cause adaptation if they are perceived as the same identity. Some physically similar faces do NOT cause adaptation if they are perceived as different people. This shows that face perception is influenced more by identity recognition than exact feature similarity.

Answer 132

Even if two images look slightly different, if they are perceived as the same person, adaptation still occurs. This suggests that identity perception overrides physical differences in face processing. The brain encodes identity holistically, rather than focusing solely on individual facial features.

Answer 133

The FFA primarily encodes facial identity, but it also retains some information about viewpoint. If the same face at a different orientation causes less adaptation, it suggests partial viewpoint dependence. This means the FFA stores identity but does not fully ignore spatial orientation.

Answer 134

The brain simultaneously encodes both identity and spatial orientation of faces. This means face perception is not purely invariant to changes in viewpoint. Face recognition involves a complex network beyond just the FFA, including areas that process pose, lighting, and perspective

Answer 135

Humans are face experts—we can quickly recognize subtle differences between faces. Faces are more visually similar to each other than many other objects, making recognition harder. This expertise allows us to make fine distinctions, similar to how bird experts or car experts can differentiate subtle variations in their specialized domains.

Answer 136

They compare face recognition to recognition of objects within an expert’s category (e.g., birdwatchers recognizing birds, car experts identifying cars). If face perception activates the same brain areas as object expertise, it supports the visual expertise hypothesis. However, if the FFA is uniquely selective for faces, it suggests a face-specific processing mechanism, separate from general expertise.

Answer 137

Yes it does. They may be different still does adaptation.

Answer 138

Ventral Stream (Identity Recognition) The FFA is part of the ventral stream, specializing in face identity processing (the "what" pathway). It helps recognize the same person even with small changes in lighting, pose, or expression. ❌✅ Some Dorsal-Like Features (Viewpoint Sensitivity) While mostly viewpoint-invariant, the FFA does not fully ignore spatial orientation. If a face is rotated significantly, the FFA may treat it as a new stimulus, showing less adaptation. This suggests it tracks both identity and some spatial properties. 📌 Conclusion: The FFA is primarily ventral (identity-based) but retains some viewpoint-specific encoding, making it a hybrid processor.

Answer 139

The brain encodes both identity and spatial orientation for faces. The Fusiform Face Area (FFA) is not purely viewpoint-invariant; it retains some viewpoint-specific information. This dual function makes face processing more complex than a simple identity recognition system.

Answer 140

Humans are "face experts"—we recognize subtle differences between faces with extreme precision. Faces are more visually similar to each other than many other objects, requiring specialized processing. This expertise may explain why the FFA is highly selective for faces—because we have developed fine-tuned visual discrimination for them.

Answer 141

Faces share similar structures (two eyes, a nose, a mouth), making them harder to distinguish compared to vastly different objects (e.g., cars vs. trees). The brain relies on subtle variations to differentiate individuals. This requires specialized neural mechanisms that go beyond general object recognition.

Answer 142

Researchers study non-face experts (e.g., birdwatchers, car experts, astronauts). If their expertise in identifying birds or cars activates the same brain regions as face recognition, it supports the visual expertise hypothesis. If the FFA remains face-selective, it suggests face perception is uniquely specialized and not just a product of expertise.

Answer 143

aces are structurally similar, making them difficult to distinguish compared to objects with more obvious differences (e.g., a car vs. a tree). The brain must rely on fine details (e.g., subtle differences in eyes, nose, and mouth) to differentiate individuals. This specialized processing may explain why the Fusiform Face Area (FFA) exists—to optimize face recognition.

Answer 144

They studied non-face experts, such as birdwatchers and car experts. If expertise alone activates the FFA, then car experts should show FFA activation for cars, and bird experts for birds. Findings: Bird experts showed activation in the FFA for birds but NOT cars. Car experts showed activation for cars but NOT birds. This suggests a dissociation, meaning FFA activity is not solely due to general expertise.

Answer 145

Some researchers argue that the FFA is mischaracterized as a "face region" and is actually a visual expertise region. Others argue that faces are unique, and the FFA evolved specifically for face recognition. Ongoing Debate: Pro-Expertise View: The FFA responds to any category requiring fine discrimination, such as birds for birdwatchers. Pro-Face Hypothesis: The FFA shows stronger, more automatic activation for faces than for any other category, even in non-expe

Answer 146

Car experts showed stronger FFA responses to cars. Bird experts showed stronger FFA responses to birds. But neither group showed strong FFA activation for the other category (e.g., bird experts didn’t activate FFA for cars). This suggests that expertise can modulate FFA activity, but it does not fully explain face specialization.

Answer 147

Researchers created fictional creatures ("Greebles") with subtle differences and trained participants to become experts in distinguishing them. After training, participants showed activation in the Fusiform Face Area (FFA) when recognizing Greebles. Takeaway: This supports the visual expertise hypothesis, suggesting the FFA may not be exclusive to faces but also processes highly familiar, visually complex categories.

Answer 148

Greebles have face-like structures, meaning participants may have perceived them as face-like objects rather than completely novel stimuli. This makes it unclear whether FFA activation was due to expertise training or because Greebles resembled faces. Critics argue that this weakens the claim that the FFA is purely a visual expertise region.

Answer 149

Researchers stimulated the FFA in epilepsy patients undergoing brain surgery. Patients reported distortions of faces but not of other objects, suggesting the FFA plays a causal role in face perception. This provides direct evidence that the FFA is more than just a general expertise region—it is functionally linked to face recognition.

Answer 150

Patients perceived distortions in faces but not in non-face objects. This suggests the FFA is directly responsible for face perception, not just a general expertise area. Causal Evidence: Unlike fMRI studies, electrical stimulation shows direct functional involvement in face recognition.

Answer 151

Visual Expertise Hypothesis: The FFA responds to expert-level object recognition (e.g., bird and car experts activating FFA). Face-Specific Hypothesis: The FFA is innately specialized for face recognition, not just expertise. Recent Evidence (e.g., electrical stimulation studies) strongly supports the face-specific hypothesis, but the debate continues.

Answer 152

In epilepsy patients, electrodes were implanted over the FFA as part of their treatment. When the FFA was electrically stimulated, patients reported distorted face perceptions—even when no face was present. This directly links the FFA to face perception, suggesting it is not just an expertise region but a face-specific area.

Answer 153

Patients report seeing distortions in faces, even if they are looking at non-face objects. If the patient is already looking at a face, the stimulation causes the face to warp or change appearance. This suggests that the FFA is actively involved in face perception, not just passive recognition.

Answer 154

fMRI only shows correlations—it tells us where brain activity happens, but not whether it causes perception. Electrical stimulation is causal—it directly manipulates brain activity and shows immediate perceptual effects. Since stimulating the FFA changes face perception, this proves it plays a functional role in face processing.

Answer 155

The brain does not just passively receive visual input; it actively constructs our perception. The fact that stimulating the FFA can make people "see" faces (even when no face is there) suggests face perception is a top-down process. This supports the idea that the brain has a specialized system for detecting and processing faces.

Answer 156

Neurons in the FFA respond specifically to facial features, such as eyes, noses, and mouths. This suggests that face perception is not just about holistic recognition but also feature-specific processing. Damage to these neurons can result in face-processing deficits, reinforcing the idea of a specialized system for face perception.

Answer 157

Prosopagnosia ("face blindness") is a condition where a person has normal vision but cannot recognize faces. This occurs due to damage to face-selective brain regions, like the Fusiform Face Area (FFA). People with prosopagnosia can recognize objects, voices, and other visual details, proving that face perception is a specialized function.

Answer 158

Patients with prosopagnosia can identify objects normally but fail to recognize faces. This selective impairment suggests that face recognition relies on distinct neural pathways separate from general object recognition. If face recognition were just another form of object recognition, damage to the FFA should affect all visual perception, but it does not.

Answer 159

Electrical stimulation of the FFA causes face distortions but does not affect non-face objects. Damage to the FFA causes face-recognition deficits (prosopagnosia) without impairing general vision. This proves that the FFA is functionally necessary for face perception, not just involved in visual expertise.

Answer 160

Face-Specific Hypothesis: The FFA evolved specifically for face perception, independent of expertise. Expertise Hypothesis: The FFA processes faces because we are experts at recognizing them, similar to how birdwatchers recognize birds. Prosopagnosia & electrical stimulation studies strongly support the idea that faces are processed in a unique, specialized way.

Exam 3 Flashcards

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