Month: February 2016

“The question of why we see things the way we do in large measure still eludes us” (p.341). This article explores the elusive relationship between vision and cognition. Is what we see solely a function of the stimulation we receive on our retina, or is it “cognitively penetrable” and influenced by what we “expect” to see? Furthermore, does what we see change our beliefs and representations of the world? Pylyshyn’s hypothesis is that early vision encompasses the stage of vision in which computational and top-down processing produces a 3D-image, but this stage is impenetrable to cognitive influence. Rather, cognition is constrained to two points: 1) pre-perception allocation of attention and 2) post-perception pattern-recognition decisions.

Questioning the Continuity Thesis

Pylyshyn puts forward four reasons for questioning whether vision is continuous with cognition. First, he argues that perception is resistant to rational influence. To support this claim, he cites optical illusions – even when you “know” two lines are the same length, you perceive them as uneven. Second, he explains that the principles of perception differ from principles of inference, which follow rational rules of reasoning. Principles of perception are responsive only to visually presented information; they do not reflect simplicity. For example, even if parts of an image are blocked, we can picture what is behind the blocked areas quite accurately. Therefore, these principles are “insensitive to knowledge, expectations, and even to the effects of learning” (p.345). Third, Pylyshyn cites clinical evidence from neuroscience that suggests at least partial dissociation of cognitive and visual functions. Finally, Pylyshyn presents methodological arguments that acknowledge the observed effects of expectations, beliefs, and contextual cues, but designates these influences to stages of processing that lie outside of what is called “early vision” (pg. 345).

Arguments For/Against Continuity

Pylyshyn explores three fields which have also explored the continuity thesis. First, he considers progress in artificial intelligence, in which the goal is to design a system that can “see.” The major progress that has come out of this field has been the development of a knowledge-based/model-based systems approach. These systems use stored general knowledge regarding objects to help determine whether said object appears in the field of view. Though this supports the continuity thesis, Pylyshyn argues that in addition to these systems, there needs to be development of systems that contain constraints on interpretation, which are congruent with the impenetrability thesis.

Next, he introduces discoveries in neuroscience indicating that attention can “sensitize or gate the visual field” (p. 347). This research partially favors the continuity theory, as there is evidence for top-down effects that modulate attention. However, there have been no discoveries of cells that influence the interpretation or emotional part of vision. Pylyshyn argues that what they illustrate is a pattern/motion response, not a content (cognitive) response.

Finally, Pylyshyn offers examples from clinical neurology in which pathology, specifically visual agnosia, strongly indicates a dissociation of vision and cognition. Upon impairment of one of the systems, the other continues to function. This view contradicts the continuity theory. Pylyshyn concurs with this evidence, although admits that these observations could certainly be correlational, not causal.

Determining Visual Stages: Methodological Issues

Pylyshyn acknowledges that all evidence provided above has been highly debated due to the complexity of the visual process. He highlights the importance of clarifying the phases of vision to better interpret these and other findings. He reviews methodological problems associated with distinguishing the stages of the visual process. The signal detection theory explores the ways in which humans make decisions about and respond to stimuli. Two phases of vision have been defined: a “perceptual” phase recognizes a stimulus (cognitively impenetrable), and a “decision” phase formulates a response (cognitively penetrable). The former is represented by the sensitivity parameter (d’), which represents the statistical relationship between the presence of the tone and a person experiencing the tone. The latter is represented by the response bias/criterion measure (ẞ), which represents the statistical relationship between the presence of the tone and the formulation of a response. While this interpretation locates such effects in a post-perceptual stage, Pylyshyn argues that this decomposition is generally too coarse to accurately establish when cognitive influences play a role.

It is important to note that the way we usually determine detection of a signal (sensitivity) is through a response (criterion measure), and therefore, being able to determine the location of cognition fails here as well. However, one way to compensate for this is through measurement of event-related potentials, which allows for measurement of stimulus evaluation uncontaminated by the response decision-making process. Pylyshyn also finds fault with this method because it encompasses everything except the response selection process, including memory retrieval for recognition, decisions, and inferences. He argues that “we need to make further distinctions within the stimulus evaluation stage so as to separate functions such as categorization and identification, which require accessing memory and making judgments, from functions that do not” (p. 351).

He concludes this section by further questioning the relationship between the stages of perception and sensitivity, which seems to be rather inconclusive. It is obvious that we need to determine a sort of mechanism that can lead to specificity in our sensitivity. Therefore, we need some sort of filtering to formulate the hypothesis generation stage of visual perception.

Constraints and Attention

Pylyshyn discusses several examples in which vision “appears on the surface to be remarkably like cases of inference” (p. 354). In these cases the visual system appears to “choose” one interpretation over other possible ones, and the choice appears remarkably “rational” (p. 354). However, Pylyshyn insists the examples do not actually constitute cognitive penetration for two reasons. First, he argues against cognitive penetration of natural constraints, which “are typically stated as if they were assumptions about the physical world” (p. 354). Natural constraints fail to demonstrate inference because the visual system evolved to work as it does, and principles of the visual system are internal to the system. They are neither sensitive to beliefs and knowledge, nor accessible to the cognitive network (p. 355). Next, Pylyshyn argues that cases of so-called perceptual “intelligence” and “problem-solving” also fail, and for the same reasons as natural constraints (also p.355). Specifically, the visual system often fails a simple test of rationality when certain basic facts about the world known to every observer.

How Knowledge Affects Perception

Pylyshyn discusses apparent counterexamples to the discontinuity theory. While he acknowledges the value of these as having an impact on response time, he asserts that the improved response is the result of knowing where to look or what to look for, limiting cognition to the pre-perceptual and post-perceptual stages. Hints of finding meaningful images do not actually help and does not affect the content that is seen (which is required for cognitive penetration). “Expert perceivers” (p. 358) appear to have knowledge that increases their ability to perceive certain patterns and with increased speed, but this seems to result solely from learned classification of visual patterns to enhance recognition and identification. He argues that this is part of the post-perceptual process. Additionally, although findings show that what people see is altered through experience, he argues that cognition plays a role only in pre-early vision by indexing spatially relevant locations. This development of focal attention is an important mechanism by which vision is malleable to the transient external world, and represents the main interface between vision and cognition. Further, he allows that cognition can influence post-perception decision making based on knowledge and experience (although with practice, this can become automated and cognitively impenetrable).

Output of Visual Systems

Pylyshyn makes the case for the visual system being a single system with two outputs, neither of which is knowledge-dependent. 

He defines “early vision” from a functional perspective, as the “attentionally modulated activity of the eyes” (p. 361). In this way, he’s acknowledging that early vision happens after attentional gating, and depends on inputs from other modalities, including non-retinal spatial information. Pylyshyn presents research showing that the output of the visual system in categories, such as shape-classes. Pylyshyn outlines that we form a 3D representation of surfaces (independent of knowledge), encode the layout of a scene (again, without knowledge or reasoning), and perceive a set of surfaces in depth. However, he stresses that “computing what the stimulus before you looks like…does not itself depend upon knowledge” (p.361).  Identifying a shape is not the same as recognizing what it actually is. For that, we need to draw upon other knowledge in memory and perform top-down processing, which can form a bridge between seeing the shape and knowing what it represents.

A second type of visual output is that which affects motor actions. These, too, Pylyshyn argues, happen separately from cognition, and he uses examples from clinical neurology to illustrate the “fractionation of the output of vision” (p.362) that allows patients to act as if they can see even when they don’t “think” that they can.

Questions

• If vision is not continuous with cognition, does that suggest that perception cannot constitute basic beliefs, thus undermining Foundations Theory?
• Is Pylyshyn’s hypothesis consistent with Traditional Epistemology or Natural Epistemology?
• Given the information put forth in this article, as scientists, do you think that we can accurately “observe” any visual data?
• Do you believe that there are two separate forms of visual output? If so, where do you think the motor-function output is derived from?

Patricia Churchland — Epistemology in the Age of Neuroscience

Churchland presents the idea that the framework in which we consider how humans perceive, learn, and understand must be re-contextualized in the age of neuroscience (Figure 1; Churchland p. 545). This new framework calls for the alteration of the question how is it possible for us to represent reality to how does the brain work, by her assertion, and she details three factors to elucidate why contemplating naturalizing epistemology is relevant now. The author postulates that 1) technological developments within the last twenty years have allowed for an understanding of neural systems to such a degree that theorizing about how macro effects, such as human behavior, stem from our neural underpinnings; 2) inexpensive and accessible computing technology allows for investigation of properties at a circuit level (i.e., neural nets); and 3) clinical neurology, biology and psychology are continuously yielding information about the capacity of neural systems, which allows for a segue into considering contemplation of brain, learning, and consciousness with respect to our understanding of evolution. Evolution, according to the author, is critical to consider for three reasons; 1) as the human brain is similar in structure, organization, and componentry to other primate brains, we must anticipate that how we learn, see, hear, and remember does not fundamentally diverge from these processes in other organisms; 2) cognition cannot be removed and considered separately from an organism’s niche and evolutionary goals, and exists in relation to the organism’s necessity to feed, fight, flee, and mate. It therefore cannot be considered in isolation, as though existing for its own sake, and sensorimotor advancements are in place to enhance an organism’s chance of survival; and finally, 3) as the human brain is a product of evolution, which works by modifying existing structures rather than by rewriting the basics, we cannot expect engineering perfection in its design. Churchland then presents a connectionist model as an alternative to the “grand old paradigm” in order to explain our cognitive processes. Connectionist models are constructed to mimic the biology of neural networks, with processing units (neurons), connections between these units (axons and dendrites), and relative weights (strength of synapses). The complexity and dynamism possible in these models, such as the NETtalk model that converts written text to speech, indicate that it may be possible to one day model exactly how our representations are formed and how we reason on a neurobiological level, namely through distinct patterns of activation. Churchland concludes by indicating that progress in this respect will require the efforts of researchers from a variety of disciplines.

Robert Almeder — On Naturalizing Epistemology

In this paper, Robert Almeder grapples with Quine’s argument for naturalized epistemology and concludes that there is ultimately no sound argument in favor of his position. On a Quinean account, naturalized epistemology is a branch of natural science and the only legitimate questions about human knowledge are those answerable through natural science. This version of naturalized epistemology therefore supplants “first philosophy” traditional epistemology—that we can have a notion of whether or not our scientific knowledge satisfies a philosophical analysis of justification or knowledge. Accordingly, we only have scientific knowledge and knowledge of the mechanisms productive of successful practice of natural science.

 The most interesting question to keep in mind during the article is raised by Almeder in his conclusion: “is there something fundamentally incoherent about arguing philosophically for naturalized epistemology… that denies philosophical arguments will count when it comes to answering questions about the nature of epistemology (278).”

Quine’s Argument 

According to Quine, traditional epistemology is concerned with showing how the foundations of knowledge—natural science or mathematics—reduce to certainty. Quine essentially understands traditional epistemology to be the pursuit of refuting the Cartesian sceptic. However, Quine believes traditional epistemology has failed its fundamental pursuit. As examples he points to the reduction of mathematics to the axioms of set theory which do not show how mathematical certainty is possible. Furthermore, Quine points to the Humean issue of induction which holds that no foundation of certainty can be associated with sense impressions or physical objects (natural science). Therefore traditional epistemology is dead and all questions and doubts are scientific in nature, answered by scientists through the natural sciences.

Response to Quine’s Argument

In this section Almeder raises objections by Stroud and Sosa and raises three issues with Quine’s argument. First, Quine is accused of incoherency by employing a philosophical argument to argue against the idea of traditional epistemology. Secondly, a further incoherency is found in the fact that the thesis for naturalized epistemology rests on two premises that are only sound if philosophical arguments about human knowledge are sound. These premises are that 1. Hume’s skepticism is established and 2. There is no analytic/synthetic distinction. Finally, Quine’s argument is accused of mischaracterizing traditional epistemology as being primarily concerned with establishing certainty when it is just as concerned with defining concepts of knowledge. i.e. what it means to know.

Philosophy is Science Argument

This section presents Lycan’s defense of Quine’s argument. Lycan, unlike Quine, believes in the analytic (apriori)/synthetic (empirical) distinction—therefore he does not adopt the Humean argument and face the same criticism as Quine. By Lycan’s account, classical philosophy assumes a deductive model in which indisputable truths are arrived at by deductive reasoning. However, he claims the premises for the deductively reached conclusions must be rooted in non-deductively gained, putative knowledge. Therefore premises are evaluated on their plausibility much like scientific theories. According to Lycan this means that 1. philosophy is in fact a high-level science and 2. proper philosophical methods cannot differ from scientific methods.

Ultimately, Almeder argues that Lycan’s position is untenable for a number of reasons.

Most significantly, philosophy is very different from science in that “in science, but not in philosophy, a necessary condition for any explanation being even remotely plausible is that it be in principle empirically testable” (270).

Traditional Epistemology Will Become Irrelevant Argument

Next, Almeder considers arguments in favor of naturalized epistemology from the eliminitivist position which claims that traditional philosophy will be revealed to be “folk psychology” and eliminated in favor of future neuroscientific accounts of cognitive functioning. Such arguments are favored by the Churchlands and Giere. Almeder believes that while the argument is possible there is really no way to justify such optimism a new model of inquiry. Later he offers objections to Giere, but given the weakness of Gyre’s argument, this section is relatively insignificant.

The Argument From Evolutionary Theory

Here, Lycan addresses two arguments that claim the only valid questions about the nature of human knowledge are those that can be answered in biological science by appeal to evolutionary theory. However, only Kornblith’s argument is even evolutionary in nature and her argument is readily dismissed by Lycan for its false premise P2, which claims that humans have a predisposition for believing truths.

The Impossibility of Defining Justification Argument

Lycan considers Richard Ketchum’s argument to be the most interesting argument in favor of naturalized epistemology. Essentially, Ketchum argues that traditional epistemology must include an acceptable definition of the concept of justification. However, given that the question, “are you justified in accepting this definition of justification” can only be answered in terms of the acceptable definition, there is no non-question begging way of defining the concept justification.

The best response Lycan musters is to say that the question “are you justified in accepting this definition of justification,” is in itself meaningless. This is the case because if there is no definition of justification in mind when the question is asked, then it cannot be known what counts as an answer to the question. Given Ketchum’s argument, however, there is no non-question begging way for a definition of justification to be given.

Questions:

As I asked at the beginning of the summary and as Lycan wonders in his conclusion, do we think that it is fundamentally incoherent to give a philosophical argument in favor of naturalized epistemology?

Does Lycan’s final rejection of Ketchum’s argument that I summarized seem strange at all? Is there a way to defend Ketchum’s argument against Lycan’s critique?

This is a 300-level philosophy course. Consequently, active, student-led discussion is expected. I have found the following format works well for achieving this goal: Each student, hereon called a presenter, will be responsible for leading at least one class (Some of you will do this as teams of two). In effect, these will be no different than days in which I’m presenting, save for the addition of 3 distinct stages leading up to the class:

Stage 1: Summary papers: Each presenter should write a 1000-1500 word paper. See below for details.

Stage 2: Pre-class questions for presenters: Approximately five students who are NOT PRESENTING will be “ON CALL.” Being on call means having to post a question on the course blog in response to the Summary Paper and readings. See details below.

Stage 3: Discussion: Each class will begin with the presenter providing a brief (5-minute) synopsis of the reading. (Everybody will have already read the primary material and the summary paper.) The presentation must conclude with a summary of the main questions that people asked (presenters should group questions according to similar concerns). Students who are neither presenters nor on-call are expected to be the first people to answer these questions. This way, everybody has an opportunity to be involved in each discussion in each class.

Presenters and on-call members who submit everything on time and exhibit an honest effort get at least a 92.5 on these assigments. Those who do exceptional work earn 100. Those who fail to be timely or who fail to exhibit of an honest effort (as judged by me) will earn lower grades.

Stage 1: Summary Paper

As noted above (Stage 1), presenters must write a paper in which:

• The presenter summarizes the texts to be discussed for the class.
• The presenter critically engages the texts he/she summarizes so as to stimulate discussion by, e.g., raising potential objections, exploring potential answers to those objections, etc.

This paper should be posted to the blog no later than 11:59pm on two days BEFORE the presentations (i.e. either Sunday or Tuesday, depending on when you’re presenting). The blog address is:

https://sites.middlebury.edu/ratcog/

Please enter this as a new post. Since there are two sections of this course, this will be a cooperative project with your counterpart in the other section.

Stage 2: On-Call Responsibilities

For any given class, approximately 4-5 students who are not presenting will be on-call. Possible questions might be about:

• Passages (in either the text or the presenter’s paper) that were not clear to you. Cite page numbers and use direct quotations
• Passages (in either the text or the presenter’s paper) that you strongly disagree with. Cite page numbers and use direct quotations.
• For those of you who post a bit later than your peers, you’re encouraged to use other on-call group members’ questions and ideas as the basis of your own question. If you do so, try to tie it back to the readings.

You should post these questions to our blog:

https://sites.middlebury.edu/ratcog/

These should posted as replies to the summary paper. You should post these questions by 2pm on the day before the presentation (so either Monday or Wednesday, depending on when you’re on call.) Please post these as replies to the presenter’s blog entry. This blog is not publicly accessible (i.e. people can’t find it if they Google), so don’t be shy about asking a question that you think is “dumb.” (Chances are, it’s not.)

EVERY student has the following responsibilities for EVERY class:

• To read EVERY question on the blog.
• To think about potential responses to 3-4 questions, and be willing to share your ideas in class.

Stage 3: Presentation/Discussion

On the day of the class in which you are scheduled to present, you will lead discussion. The major questions we will answer are those asked by the On-Call group. Wherever possible, students who are neither presenting nor on call should make the first attempt to answer these questions. (This way, everyone’s involved.) Having said this, it’s sometimes easier to start conversations by asking on-call members to motivate/clarify their questions. Presenters should keep the following in mind:

1. All presenters must use PowerPoint, Beamer, or Keynote.
2. Slideshows must be less than 10 slides long.
3. The presenter should begin by situating the reading within the broader themes of the course, especially with respect to earlier readings.
4. The chief criterion by which presenters will be assessed is how well they stimulate discussion. (This is not as easy as it looks!) Consider how different questions on the blog hang together; find interesting points of disagreement.

The slideshow should not be overflowing with information, yet must be sufficiently clear that other members of the class find the ideas easy to follow. Consequently, presenters must be especially reflective about how the accompanying commentary will supplement what the slides say. You are encouraged to look for additional materials about how to use PowerPoint effectively in academic presentations.

Philosophers (and others) study how we ought to reason. By contrast, psychologists (and others) study how actually do reason. Often, their findings conflict. How should these conflicts be reconciled? Potential topics include different kinds of reasoning (deductive, probabilistic, explanatory, analogical, practical, etc.), naturalized epistemology, theories of justification, and heuristics and biases. Prerequisites: either PHIL0180 or PSYC0105.