Cognition is the study of the brain, mind, and its process. There are a lot of cognitive skills. Some of them are Attention, perception, memory, decision-making, creativity, problem-solving, reasoning, and the like. This slide show talks about the same.

1. COGNITIVE SKILLS
BY
Dr.S.Jerslin

2. MEANING
• Cognitive skills, also called cognitive functions,
cognitive abilities or cognitive capacities, are brain-
based skills which are needed in acquisition of
knowledge, manipulation of information, and
reasoning. They have more to do with the mechanisms
of how people learn, remember, problem-solve, and
pay attention, rather than with actual knowledge.
Cognitive skills or functions encompass the domains of
perception, attention, memory, learning, decision
making, and language abilities.
• https://artsandculture.google.com/entity/cognitive-
skill/m0kbh_lz?hl=en

3. COGNITIVE SKILLS-IMAGE

4. Auditory Sustained stay on task for sustained
periods of time
Visual Processing Visual Discrimination The ability to recognize the
details of an image and
distinguish differences.
Auditory Processing Auditory Discrimination The ability to recognize the
details of sounds and
distinguish differences
Sensory Integration Oculomotor Skill The ability to use the eyes
efficiently to read and
gather information from
the environment.
Memory Visual Sensory Memory
Auditory Sensory Memory
The ability to screen out
unimportant sensory
information and keep
important information for
further processing
(approximately 1/1000th of
a second).

5. TYPES OF COGNITIVE SKILLS
Abductive Reasoning Abstract Thinking
Analogical Reasoning Analysis
Attentional Control Attribution
Category Formation Cognitive Flexibility
Composition Conjecture
Convergent Thinking Counterfactual Thinking
Creativity Critical Thinking
Crystallized Intelligence Dealing With Ambiguity
Decision Making Deductive Reasoning
Design Thinking Divergent Thinking
Emotional Intelligence Fluid Intelligence
Imagination Improvising

6. Con…
Inference Inhibitory Control
Introspection Intuition
Judgment Kinesthetic Intelligence
Learning Linguistic Intelligence
Logic Memory
Objectivity Pattern Recognition
Perception Planning
Problem Solving Rational Thought
Reasoning Reflective Thinking
Salience Self-Awareness
Situational Awareness Social Cognition
Spatial Reasoning Strategy
Systems Thinking Tactics
Verbal Reasoning Visual Thinking

7. ATTENTION
• https://simplicable.com/en/cognitive-skills
Attention is the ability to choose and concentrate
on relevant stimuli. Attention is the cognitive
process that makes it possible to position ourselves
towards relevant stimuli and consequently
respond to it. This cognitive ability is very
important and is an essential function in our daily
lives. Luckily, attention can be trained and improved
with the appropriate cognitive training.

8. TYPES OF ATTENTION
• Arousal: Refers to our activation level and level of
alertness, whether we are tired or energized.
• Focused Attention: Refers to our ability to focus attention
on a stimulus.
• Sustained Attention: The ability to attend to a stimulus or
activity over a long period of time.
• Selective Attention: The ability to attend to a specific
stimulus or activity in the presence of other distracting
stimuli.
• Alternating Attention: The ability to change focus attention
between two or more stimuli.
• Divided Attention: The ability to attend different stimuli or
attention at the same time.

9. EXAMPLE
• When we drive, we are almost constantly using all of
our attentional sub-processes. We have to be awake
(arousal), we have to be able to focus our attention on
the stimuli on the road (focused attention), pay
attention for long periods of time (sustained attention),
keep ourselves from getting distracted by irrelevant
stimuli (selective attention), be able to change focus
from one lane to another, to the mirror, and back to
your lane (alternating attention), and be able to carry
out all of the actions necessary for driving, like using
the pedals, turning the wheel, and changing gears
(divided attention).

10. MEASURING ATTENTION
• With the help of a complete neuropsychological
assessment, it is possible to easily and effectively
evaluate a number of different cognitive skills, like
focused attention. CogniFit's assessment to evaluate
focused attention was inspired by the Continuous
Performance Test (CPT), the classic Stroop test, the Test
of Variables of Attention (TOVA), and the Hooper Visual
Organization Task (VOT). This test helps to evaluate
other behavioral alterations, response time, visual
perception, shifting, inhibition, updating, spatial
perception, processing speed, visual scanning, and
hand-eye coordination

11. PERCEPTION
• Perception is the ability to capture, process,
and actively make sense of the information
that our senses receive.

12. Types of Perception and
Neuroanatomy
• Visual or visual perception: The ability to see and interpret light
information within the visible spectrum that arrives to our eyes.
The area of the brain responsible for visual perception is the
occipital lobe (primary visual cortex V1 and secondary visual cortex
V2).
• Hearing or auditory perception: Ability to receive and interpret
information that arrives to our ears by audible frequency waves
through the air or another mean (sound). The brain part in charge
of the basic stage of auditory perception is the temporal lobe
(primary auditory cortex A1 and secondary auditory cortex A2).
• Touch, touch perception, somatosensory or haptic perception :
The capacity to interpret information of pressure and vibration
received on the surface of our skin. The parietal lobe is the part of
the brain responsible for the basic stages in haptic perception
(primary somatosensory cortex S1 and secondary somatosensory
cortex S2).

13. Con…
• Smell or olfactory perception: The ability to interpret
information of chemical substances dissolved in the air
(smell). Basic stages of the olfactory perception are
done by the olfactory bulb (primary olfactory cortex)
and the piriform cortex (secondary olfactory cortex).
• Taste or taste perception: The ability to interpret
information from chemical substances dissolved in
saliva (taste). The main brain areas in control of the
basic stages are the primary taste areas G1 (postcentral
inferior gyrus, parietal ventral lobe, anterior insula,
fronto-parietal medial operculum) and secundary taste
areas G2 (caudolateral frontal orbital cortex and
anterior cingulate cortex).

14. Examples of Perception
• It's important to identify on time any perceptive
problem that the student might have. This will allow us
to apply the means necessary so no auditory
information is lost (what the professor says) or visual
information (the text on the board and books).
• A correct perception helps workers do their job
efficiently. Artists are a clear example of the
importance of perception in the professional world.
However, any job requires, in a greater or lesser
manner, some type of perception: sweepers, taxi
drivers, designers, policemen, cashiers, builders, etc

15. Memory
• Memory is a complex process that allows us to
code, store, and recover information. If the
attention system doesn't work properly, we
won't be as efficient in doing such tasks. If we
don't pay attention to something, we cannot
code, store, or recover this information. In
order to understand memory, we can classify
it according to two criteria

16. MEMORY
Memory
Short
Term
Long
Term
Sensory
Explicit(Con
Implicit(Un
con)
Declarative(Fa
cts, Events)
Procedural(
skills,tasks)
Epidotic(Eve
nts,experien
ces)
Semantic(fa
cts,
concepts)

17. 1-TEMPORAL CRITERION
• Short-term memory:
• -Immediate memory
• -Operative or working memory: Short-term
passive storage system that allows us to work
with information. For example, when we try to
remember a telephone number before writing
it on a piece of paper.

18. LONG TERM MEMORY
• AREAS THAT MEMORY OPERATES
• Declarative (explicit) memory: References memories
that may be consciously evoked.
• -Episodic: the autobiographical memory that allows us
to remember concepts and events from our past. For
example, where did we go on vacation last year? When
did I graduate? When did I get married?
• -Semantic: This memory references what we've
learned and our general knowledge of the world. What
is the capital of France? What is a square root?
• The medial temporal lobe and the diencephalon are
the structures associated with this kind of memory.

19. LANGUAGE
• Language is a symbolic communication system
that is presented through languages. Language
isn't only important for communicating with
others, but also for structuring our internal
thoughts. Language processing uses different
brain areas that act together through different
functional systems that involve the left
hemisphere especially. We could talk about two
cortical areas that are in charge of expression and
reception of language, mainly in the left cerebral
hemisphere:

20. 1.LANGUAGE EXPRESSION AREA
• Includes different areas of the cerebral cortex.
• - Pre-frontal area: Involved in the motivational
processes of language. It is where both verbal
and written communication starts (related to the
executive functions).
• -Broca's area: Located in the left frontal lobe. It is
related to speech production and spoken
language processing.
• -Primary motor cortex: Starts the movements to
start to pronounce words and movements to
guide writing.

21. 2. LANGUAGE RECEPTION AREA
• : Includes:
• -Occipital Lobe: Allows us to identify linguistic images.
• -Parietal lobe: In charge of integrating visual and auditory stimuli.
• - Left temporal lobe: In charge of synthesizing and understanding spoken
sounds. It is integrated by: Helsch's Area (primary auditory area. It
receives the sounds to code them in the multimodal area) and
the Wernicke's Area (related to language comprehension. It gives meaning
to these perceived sounds.)
• Aside from the cortical areas, other areas are also essential for proper
language function. The interconnection between these cortical areas with
other subcortical structures, like the arcuate fasciculus (connects the
Broca's area to the Wernicke's area), the thalamus (important for language
regulation, as it connects sympathetic with expressive areas), the pulvinar
nucleus and geniculate, basal ganglia, and the cerebellum (which
intervenes in language fluency, rhythm, and tone), etc.

22. Dyslexia
• Dyslexia is a learning disorder that affects more than 10% of the
population. It is a neurological impairment that affects the learning
process, making difficult to read, write, and easily decode language
or symbols. Children with dyslexia tend to start speaking later, have
weaker listening comprehension, and have fewer words in their
vocabulary compared to other children their age. Dyslexia is not
related to intelligence, but to the way the brain processes
information. Nowadays people are more aware of this disorder
and children are better diagnosed than they used to be. However,
many adults with reading and writing difficulties throughout their
entire lives still have never heard of dyslexia. The worst-case
scenario are adults with dyslexia that are unaware of their disorder.
If left untreated, dyslexia may lead to a number of problems, such
as low self-esteem, behavior problems, anxiety, aggression, and
withdrawal from friends, parents, and teachers.

23. Con…
• CogniFit Cognitive Assessment Battery for Dyslexia
(CAB-DX) will adapt to the user's age making it
appropriate for kids 7 and older, teens, and adults. This
test consists of two parts, the first part is a
questionnaire based on the relevant dyslexia
symptoms and the second part is aimed at assessing
cognitive tasks in the form of brain games. The CAB-DX
takes approximately 30 to 40 minutes to complete, and
the results are available for download at the end of the
test.
Human Brain Functions and CogniFit
• www.cognifit.com › brain-functions

24. Decision-making
• In psychology, decision-making (also
spelled decision making and decision making)
is regarded as the cognitive process resulting
in the selection of a belief or a course of
action among several alternative possibilities.
Decision-making is the process of identifying
and choosing alternatives based on
the values, preferences and beliefs of the
decision-maker.

25. Neuroscience
• Decision-making is a region of intense study in the
fields of systems neuroscience, and cognitive
neuroscience. Several brain structures, including
the anterior cingulate cortex (ACC), orbitofrontal
cortex and the overlapping ventromedial prefrontal
cortex are believed to be involved in decision-making
processes. A neuroimaging studyfound distinctive
patterns of neural activation in these regions
depending on whether decisions were made on the
basis of perceived personal volition or following
directions from someone else. Patients with damage to
the ventromedial prefrontal cortex have difficulty
making advantageous decisions.

26. Con…
A common laboratory paradigm for studying neural decision-
making is the two-alternative forced choice task (2AFC), in which
a subject has to choose between two alternatives within a
certain time. A study of a two-alternative forced choice task
involving rhesus monkeys found that neurons in the parietal
cortex not only represent the formation of a decision but also
signal the degree of certainty (or "confidence") associated with
the decision. Another recent study found that lesions to the ACC
in the macaque resulted in impaired decision-making in the long
run of reinforcement guided tasks suggesting that the ACC may
be involved in evaluating past reinforcement information and
guiding future action.A 2012 study found that rats and humans
can optimally accumulate incoming sensory evidence, to make
statistically optimal decisions

27. VISUAL AND AUDITORY RECOGNITION
• Short-term memory has been mostly investigated for verbal
stimuli (e.g., words, numbers, syllables) and visual stimuli (e.g.,
figures, spatial positions). The influential memory model of
Baddeley and Hitch (1974) proposed three different components,
with two temporary storages depending on the material type, and a
central executive. The two storages are the phonological loop,
which stores verbal information, and the visuo spatial sketchpad,
which stores visuo spatial information. The central executive is
responsible for controlling and distributing attention resources.
Later on, Baddeley added a further component, the episodic buffer,
which integrates multidimensional information and links working
memory to long-term memory (Baddeley, 2000). The distinction
between verbal storage and visuo spatial storage made by the
model is supported by numerous behavioral and neuroimaging data
(Baldo & Dronkers, 2006; Cocchini et al., 2002; Hirel et al., 2017;
Logie et al., 1990; Rottschy et al., 2012; Smith et al., 1996).

28. Con…
• Beyond verbal material, auditory short-term memory has
been investigated more recently with tonal material (e.g.,
musical tones) and two separate subsystems have been
proposed: a phonological loop for verbal information and
a tonal loop for music information (Berz, 1995; Schulze et
al., 2011; see also Caclin & Tillmann, 2018 for a discussion.
Furthermore, contour is a privileged feature for processing
and storing auditory information, not only with pitch
variations, but also with loudness and brightness
variations (Graves et al., 2019; McDermott et al., 2008).
Some related observations have been made with visual
stimuli, such as with vertical lines (Balch &
Muscatelli, 1986) and stair plots (Prince et al., 2009).

29. REASONING
• Reasoning is the mental (cognitive) process of looking
for reasons for beliefs, conclusions, actions or feelings.
Humans have the ability to engage in reasoning about
their own reasoning using introspection(observation).
• Different forms of such reflection on reasoning occur in
different fields. In philosophy, the study of reasoning
typically focuses on what makes reasoning efficient or
inefficient, appropriate or inappropriate, good or bad.
• Philosophers do this by either examining the form or
structure of the reasoning within arguments, or by
considering the broader methods used to reach particular
goals of reasoning.

30. Con…
• Psychologists and cognitive scientists, in contrast, tend to study
how people reason, which brain processes are engaged, and how
the reasoning is influenced by the structure of the brain. Specific
forms of reasoning are also studied by mathematicians and lawyers.
• Scientific research into reasoning is carried out within the fields
of psychology and cognitive science.
• Second, psychologists carry out research on reasoning behaviour.
Such research may focus, for example, on how people perform on
tests of reasoning, such as intelligence or I.Q. tests, or on how well
people's reasoning matches ideals set by logic (see, for example,
the Wason test). In addition to carrying out research into
reasoning, some psychologists, for example, clinical
psychologists and psychotherapists work to alter people's reasoning
habits when they are unhelpful.

31. BRAIN PARTS FOR REASONING
• Thinking, reasoning, and impulse control are
part of the cerebral cortex functions. Higher
mental functions like thoughts, memory,
reasoning, and critical thinking are cognitive
aspects that the cerebrum controls.
• https://study.com/academy/answer/what-
part-of-the-brain-is-responsible-for-thinking-
reasoning-and-impulse-control.html

32. TYPES OF REASONING
• The main division between forms of reasoning
that is made in philosophy is
between deductive reasoning and inductive
reasoning.
• Formal logic has been described as 'the
science of deduction'. The study of inductive
reasoning is generally carried out within the
field known as informal logic or critical
thinking.

33. INDUCTIVE REASONING
• Inductive reasoning contrasts strongly with deductive
reasoning. Even in the best, or strongest, cases of inductive
reasoning, the truth of the premises does not guarantee
the truth of the conclusion.
• Instead, the conclusion of an inductive argument follows
with some degree.
• A classical example of inductive reasoning comes from
the empiricist David Hume:
• Premise: The sun has risen in the east every morning up
until now.
• Conclusion: The sun will also rise in the east tomorrow.

34. DEDUCTIVE REASONING
• Deductive arguments are intended to have reasoning
that is valid. Reasoning in an argument is valid if the
argument's conclusion must be true when the
premises (the reasons given to support that
conclusion) are true.
• Premise 1: If green is a colour, then green poisons
cows.
• Premise 2: Green is a colour.
• Conclusion: Grass poisons cows.
• Again, if the premises in this argument were true, the
reasoning is such that the conclusion would also have
to be true.

35. PROBLEM SOLVING
• The counsellors need to assess clients’ knowledge bases,
and particularly clients’ working memory, during the coping
process. Using one’s knowledge bases is a highly complex,
dynamic, and intermittent process that involves encoding,
goal setting, plans, and actions.
• We believe that clients seek counselling, in part, because
they have been unsuccessful in some aspect of these four
problem-solving activities; in our view, effective therapy
removes or reduces cognitive, affective, or behavioural
obstacles that clients en- counter in encoding, goals,
pattern matching, or actions. We will now examine these
four problem-solving activities in greater depth and discuss
specific implications for the counselling process.

36. STEPS
• Using one’s knowledge bases is an exceedingly complex
process and involves what Anderson (1983) labels (1)
encoding, (2) goal setting, (3) developing plans and
pattern matching, and (4) action. These four major
problem-solving activities will be the focus of the next
four sections.
• Briefly, encoding refers to how information is initially
processed and structured as it comes into the human
system. Goals are a means of organizing behavior,
aimed at facilitating the adaptation to internal and
external environmental demands.

37. 1. Encoding
• Encoding is the processing and structuring of information as it
comes into the human system. Exactly how information is
represented internally is unclear (see Hebb, 1949; Hollon & Garber,
in press; McCulloch, 1965). At this point, suffice it simply to note
that knowledge is organized and structured in some way. In
addition, the way information is organized affects how new
information is then processed and encoded (see Balota, 1983).
• Thus encoding does not happen in a vacuum but rather occurs in
conjunction with the knowledge that one already possesses.
• We conceptualize encoding in terms of two major categories:
• (1) encoding of the problem cues or stressful event per se and
• (2) an appraisal of the meaning or significance of the problem

38. 2. Goal Setting
• Goal setting is the process of establishing, with varying
degrees of specificity, a possible solution that is aimed at
responding to one’s internal and external environmental
demands.
• Problem solving is a goal-directed process, although for any
one problem a person may have several goals
simultaneously, some incompatible with the others. Goals
serve as sources of high and constant activation (Anderson,
1983) and, ultimately, as a way of organizing behavior.
• This seems to be the case even when the goal is unclear if
the problem is important in some way. In short, a goal is a
pivotal aspect of the problem-solving process because it
stimilarities and directs the testing of possible solutions.

39. 3. Plan/Pattern Matching
• When faced with a problem or goal, people then
begin searching their memory for ways to apply
what they know to the situation at hand.
• More specifically, an individual goes through a
process of examining the conditions and actions
required of the goal (or problem) and developing
plans based on information stored in long-term
memory to solve the problem (Anderson, 1983).
This can be a very quick process or it can be.

40. 4. Actions
• Problem-solving actions are the diverse range of
cognitive, affective, and behavioral activities associated
with the performance of problem- solving responses. T
• The performance of problem-solving actions is a
complex and intermittent process. Actions are not
emitted randomly, but rather are cued by previous
problem-solving processes, such as encoded elements
of the problem (e.g., immediate versus long-term
demands, perceived threat), goals (e.g., specific
versus vague goals), and pattern matching (e.g.,
identification of steps to solve a problem).

41. CONCLUSION
• The problem-solving outcomes may lead to decisions to recycle the earlier
problem-solving activities. For example, the problem solver, upon
recognizing that a particular action was not effective or only partially
effective, may recycle to problem-definition activities or action planning.
Or conversely, the problem solver might find the problem- solving
activities so aversive, he or she attempts to escape from the problem in
some way (e.g., denial, rationalization, procrastination, change of
environments). It is essential to recognize that this process is highly
interactive.
• Typically within the personal problem-solving process, the problem solver
does not reach a perfect or total resolution of the problem. Following a
partial solution, a number of variables, such as personal characteristics,
environmental contingencies related to the problem, and competing
demands, probably interact to cue or extinguish additional problem-
solving activities. The adage, “The squeaky wheel gets oiled first,” may
accurately reflect this intermittent problem-solving process.

42. COMPUTATIONAL MODELLING
• As it contributes more to the understanding of human
cognition than artificial intelligence, computational cognitive
modeling emerged from the need to define various cognition
functionalities (like motivation, emotion, or perception) by
representing them in computational models of mechanisms
and processes. Computational models study complex
systems through the use of algorithms (processes) of many
variables and extensive computational resources to
produce computer simulation(imitation).Simulation is
achieved by adjusting the variables, changing one alone or
even combining them together, to observe the effect on the
outcomes. The results help experimenters make predictions
about what would happen in the real system if those similar
changes were to occur.

43. Con…
• When computational models attempt to mimic human
cognitive functioning, all the details of the function must
be known for them to transfer and display properly
through the models, allowing researchers to thoroughly
understand and test an existing theory because no
variables are vague and all variables are modifiable.
Consider a model of memory built by Atkinson and Shiffrin
in 1968, it showed how rehearsal leads to long-term
memory, where the information being rehearsed would be
stored. Despite the advancement it made in revealing the
function of memory, this model fails to provide answers to
crucial questions like: how much information can be
rehearsed at a time? How long does it take for information
to transfer from rehearsal to long-term memory?

44. USES
• Similarly, other computational models raise more questions about
cognition than they answer, making their contributions much less
significant for the understanding of human cognition than other
cognitive approaches. An additional shortcoming of computational
modeling is its reported lack of objectivity.
• John Anderson in his Adaptive Control of Thought-Rational (ACT-R)
model uses the functions of computational models and the findings
of cognitive science. The ACT-R model is based on the theory that
the brain consists of several modules which perform specialized
functions separate of each other. The ACT-R model is classified as
a symbolic approach to cognitive science.
• https://en.wikipedia.org/wiki/Computational_cognition#:~:text=Co
mputational%20cognition%20(sometimes%20referred%20to,comp
uter%20simulation%2C%20and%20behavioral%20experiments.

45. NEURAL NETWORKS
• Another approach which deals more with the semantic content of
cognitive science is connectionism or neural network modeling.
Connectionism relies on the idea that the brain consists of simple
units or nodes and the behavioral response comes primarily from
the layers of connections between the nodes and not from the
environmental stimulus itself.
• Connectionist network differs from computational modeling
specifically because of two functions: neural back-
propagation and parallel-processing. Neural back-propagation is a
method utilized by connectionist networks to show evidence of
learning. After a connectionist network produces a response, the
simulated results are compared to real-life situational results. The
feedback provided by the backward propagation of errors would
be used to improve accuracy for the network's subsequent
responses.[14]

46. Con…
• The second function, parallel-processing, stemmed
from the belief that knowledge and perception are
not limited to specific modules but rather are
distributed throughout the cognitive networks. The
present of parallel distributed processing has been
shown in psychological demonstrations like the Stroop
effect, where the brain seems to be analyzing the
perception of color and meaning of language at the
same time.[15] However, this theoretical approach has
been continually disproved because the two cognitive
functions for color-perception and word-forming are
operating separately and simultaneously, not parallel
of each other.[16]

47. Con…
The field of cognition may have benefitted from the use of
connectionist networks, but setting up the neural network
models can be quite a tedious task and the results may be less
interpretable than the system they are trying to model.
Therefore, the results may be used as evidence for a broad
theory of cognition without explaining the particular process
happening within the cognitive function. Other disadvantages of
connectionism lie in the research methods it employs or
hypothesis it tests as they have been proven inaccurate or
ineffective often, taking connectionist models away from an
accurate representation of how the brain functions. These
issues cause neural network models to be ineffective on studying
higher forms of information-processing, and hinder
connectionism from advancing the general understanding of
human cognition.[

48. COGNITIVE ARCHITECTURE
• A cognitive architecture refers to both a theory about the structure
of the human mind and to a computational instantiation of such a
theory used in the fields of artificial intelligence (AI)
and computational cognitive science.[1] The formalized models can
be used to further refine a comprehensive theory of cognition and
as a useful artificial intelligence program. Successful cognitive
architectures include ACT-R (Adaptive Control of Thought -
Rational) and SOAR. The research on cognitive architectures as
software instantiation of cognitive theories was initiated by Allen
Newell in 1990.[2]
• The Institute for Creative Technologies defines cognitive
architecture as: "hypothesis about the fixed structures that provide
a mind, whether in natural or artificial systems, and how they work
together – in conjunction with knowledge and skills embodied
within the architecture – to yield intelligent behavior in a diversity of
complex environments."[3]

49. Con…
• Cognitive architectures can be symbolic, connectionist,
or hybrid.[7] Some cognitive architectures or models are based on a
set of generic rules, as, e.g., the Information Processing
Language (e.g., Soar based on the unified theory of cognition, or
similarly ACT-R). Many of these architectures are based on the-
mind-is-like-a-computer analogy. In contrast subsymbolic
processing specifies no such rules a priori and relies on emergent
properties of processing units (e.g. nodes). Hybrid architectures
combine both types of processing (such as CLARION). A further
distinction is whether the architecture is centralized with a neural
correlate of a processor at its core, or decentralized (distributed).
The decentralized flavor, has become popular under the name
of parallel distributed processing in mid-1980s and connectionism,
a prime example being neural networks. A further design issue is
additionally a decision between holistic and atomistic, or (more
concrete) modular structure.

50. Con…
• In traditional AI, intelligence is often programmed from above: the
programmer is the creator, and makes something and imbues it
with its intelligence, though many traditional AI systems were also
designed to learn (e.g. improving their game-playing or problem-
solving competence). Biologically inspired computing, on the other
hand, takes sometimes a more bottom-up, decentralised approach;
bio-inspired techniques often involve the method of specifying a set
of simple generic rules or a set of simple nodes, from the
interaction of which emerges the overall behavior. It is hoped to
build up complexity until the end result is something markedly
complex (see complex systems). However, it is also arguable that
systems designed top-down on the basis of observations of what
humans and other animals can do rather than on observations of
brain mechanisms, are also biologically inspired, though in a
different way.
• https://en.wikipedia.org/wiki/Cognitive_architecture