PSYCH 85 - Section 3 (lectures 7+8)

Input analyzers (like perception)

convert sensory input (light, sound waves) into representations of distal stimuli - things in the world (eg color perception, face perception, processing spatial relations, processing speech) 

input analyzers are specialized, modular cognitive subsystems designed to process specific types of incoming sensory information—such as visual patterns, speech sounds, or spatial layouts—before that information is interpreted by higher-level cognitive processes. 

distal stimulus

any physical object or event in the external environment, such as a tree or a ringing phone, that is distant from the observer. It represents the actual, objective reality that exists independent of the viewer, which the sensory systems (like eyes or ears) aim to perceive

what do input analyzers do?

Take what is produced by the transducers and turn it into representation of the object that produced that sensory stimulation

transducers

are mechanisms that convert environmental energy (physical, chemical, or mechanical stimuli) into the "language of the nervous system"—patterns of electrical signals (neural impulses). They function as the bridge between the external world and the internal cognitive system

central systems

high-level, non-modular cognitive processes responsible for reasoning, decision-making, and belief formation. Unlike input systems (modules) that handle specific perceptual data, central systems integrate information from multiple sources. They are characterized as isotropic and Quinean, meaning they are not domain-specific and can utilize data from anywhere in the cognitive system

modularity

the theory that the mind is composed of specialized, independent, and innate subsystems (modules) that handle specific tasks, such as language processing or visual perception

characteristics of modular input analyzers

• informationally encapsulated - not influenced by other mental systems

• domain-specific - processing only a restricted type of inputs

• modular - distinct, specialized, and independent subsystems (modules) that process specific types of info

  • examples: face recognition, lang parsing, visual perception, motion tracking, color perception, fight or flight

• bottom up effects: stimulus driven, no effect of higher-level knowledge.

• automatic and fast

• computationally cheap

• intermediate steps are not accessible to consciousness

• timeline (pace, sequence) of its development is stable across multiple ppl

• hard wired in the brain, structure and function resistent to change

characteristics of nonmodular central systems

• informationally unencapsulated - not influenced by other mental systems

• isotropic: makes use of any relevant information available to the agent, cognitive processes interact with and influence one another, from the beginning of processing

• domain-general - processing is unrestricted in its inputs

• nonmodular - operate as integrated, holistic systems rather than separate, specialized modules

  • exmamples: thinking, reasoning, decision making, prob solving, planning, fixation of belief

• top down effects: stimulus processing is biased by higher level knowledge

why does modularity matter?

debate in cog sci on whether or not it is possible to understand nonmodular cognitive systems/processes. (Fordor, the Modularity of the Mind, reading 4)

examples of top down effect (isotropy)

spatial relations: opening looks narrower when holding a rod horizontally to pass
visual perception: banana looks yellower despite being grey

which cognitive capacities operate on specialized inputs? FFA - example of cog capacity for domain specific

fusiform face area (FFA)

• putative face regions in the brain (believed to be involved based on current evidene, but not completely certain)

• replicate and test the generality of the finding (animals, head, face parts)

from this brain region, we infer that our mental tool box (BRAIN) inlcudes a cognitive capacity that is specialized fro seeing faces

• strong response to pics of faces, human or not

• weaker responses to anything other obj

• not heads, shapes, etc

• not about eyes, mouth, but FACE

tools in cognitive neuroscience

1. fMRI (functional MRI) - recording brain activity

2. neuropsychology: patients with brain damage

3. TMS (transcranial magnetic stimulation) - stimulation/disruption

neuropsychology: brain damage of FFA

prosopagnosia: face blindness

• basic visual perception and mem

• not dientifying familiar faces/celeb

• no recognizing familar face

• no learning new face

object agnosia: object blindness

• recognizing obj from touch

• draw and copy obj

• no visually recognize obj

• recognize faces

• matching and learnign new faces

• detectign faces hidden among obj

double dissociation

a research method in cognitive neuropsychology showing that two cognitive functions (e.g., speech production and comprehension) are independent and localized in different brain areas. It occurs when patient A is impaired on task X but not Y, and patient B is impaired on Y but not X, providing stronger evidence for neural specialization than a single dissociation

a double dissociation btw 2 functions (eg faces vs objs) is the strongest evidence that they rely on 2 distinct mechanisms

reasoning - example of domain general cog capacity ???

• reasoning can be applied to multiple types of content (math, social situations, planning, puzzles)

• brain network (larger than domain specific tools areas) activated whenever you are doing ANYTHING that is difficult (cognitively demanding) - multi-demand network

  • effortful tasks - learn something new, solving a hard exam Q, navigate a new city, figuring out a social sitaution

• diffulty - stronger response (activation of this network)

• deactivated during interally-guided thought, (eg day dreaming, introspection, recall, prospection)

  • activates the DMN, default mode network.

causal role in goal directed beh (this network helps you stay on task and pursue goals.)

• attending to info and manipulating it in WM

• inhibition (avoiding hibitual responses when inappropriate)

  • suppressing automatic responses

    • not blurting out an answer

    • ignoring distractions

    • resisting checking your phone

• biasing the rest of the brain to prioritize what is relevant now

  • MDN works like a control system

    • prioritize relevant informatioon

    • suppress irrelevant info

• the greater the damage to this network, the lower the IQ

  • damage = worse reasoning, problem solving, cognitive control

a system for anything to which we do not have a domain specific solution?????? - we dontknow???

• ex: vision—> visual cortex, language—> lang areas

conclusion from lectures

domain-specificity is a putative input analyzer for faces and domain-generality is a capacity for reasoning within central systems.

putative

supposed, presumed, assumed, gernally considerred or reputed to be