November 14, 2018
Pattern recognition is often overlooked when it comes to brainpower, but it is one of the most important cognitive functions for overall intelligence. And it may be a crucial factor in humanity’s ability to keep up with self-learning artificial intelligence.
We see and use patterns all the time. From our daily commute to the natural world, we rely on pattern recognition in order to navigate, communicate, recognize places, people, and objects, make decisions, and learn or improve skills.
Nootropics for pattern recognition could enhance our ability to process information, accelerate learning, and increase intelligence.
What is Pattern Recognition?
Psychology cognitive neuroscience describes pattern recognition as a cognitive process that pairs information from stimuli with information stored in memory.
Pattern recognition occurs when short-term memory receives and processes information from the environment and triggers activation of specific content stored in long-term memory.
A pattern can be either an abstract notion or a physical object, but it’s basically a sequence that repeats. Animal classifications or types of vehicles are examples of object-based pattern recognition.
Common abstract patterns include types of music, facial features, language components, and symbols.
Connecting memories with present stimuli is a step of pattern recognition called identification.
Semantic memory, which we access subconsciously and implicitly, is the main type of memory engaged with identification.
Pattern Recognition and the Brain
Pattern recognition is a crucial skill for human survival and perception. But other animals rely on it as well, like koalas, who use pattern recognition to find their favorite food source – eucalyptus leaves.
The human brain is more developed than most others in the animal kingdom, but it shares similarities with many of them.
Neural networks in the outer layer of the human brain allow for superior processing of visual and auditory patterns. However, both humans and animals use spatial recognition, memory, and identification for pattern recognition related to resources and danger.
Theories of Pattern Recognition
There are six main theories of pattern recognition:
- Template matching
- Feature analysis
- Bottom-up and top-down processing
- Fourier analysis
These theories are not mutually exclusive, and we use many of them in everyday life. Each of these theories applies to different activities and domains of pattern recognition related to things like language comprehension, facial recognition, music appreciation, and seriation.
Pattern recognition allows us to predict what comes next.
Learning the alphabet in order relies on a type of pattern recognition called seriation. When a teacher repeats ‘A, B, C’ multiple times to a learner, the learner’s brain uses pattern recognition to say ‘C’ after they hear ‘A, B’ in sequence.
Pattern recognition is automatic and subconscious and includes:
- Recognition of familiar patterns
- Recognition and classification of unfamiliar objects
- Recognition of shapes and objects when viewed from different angles
- Recognition of partially hidden patterns and objects
False Pattern Recognition
Pareidolia is the human tendency to see patterns that do not actually exist, like figures in clouds, the Man in the Moon, religious figures in food, and faces or figures in shadows, wood, stone, etc.
Pareidolia influences superstitions, conspiracy theories, misinterpretation of statistics and scientific data, gambling, and some paranormal and religious experiences.
Music and language recognition rely on the encoding of auditory patterns, while facial recognition and seriation use encoding of visual patterns.
Facial Pattern Recognition
Recognizing faces is one of the most common types of pattern recognition. Most people are highly skilled at recognizing faces, but this automatic programming hides a cognitive challenge – all faces share similar physical features.
Normal faces have two eyes, one mouth, and one nose – all of them in predictable locations, yet humans can recognize a familiar face from various angles and in different lighting conditions.
But there’s an interesting twist. While humans can easily recognize faces from various normal viewing angles, we have tremendous difficulty recognizing upside-down faces. This illustrates the inherent challenges of facial recognition and shows how human brains use specialized procedures for recognizing upright faces.
Neuroscientists think facial recognition occurs in three phases.
- The first phase encodes visual information, focusing on physical features.
- Secondly, the brain taps into long-term memory to identity the person behind the face if we know them, or stores the facial features in memory for future use.
- Finally, if the pattern recognition system is fully functioning, recognizing the face triggers a memory of the person’s name.
The fusiform gyrus is specifically dedicated to processing facial features. A Stanford University study illustrated how the fusiform gyrus influences facial recognition.
- When researchers used electrical impulses to directly stimulate a patient’s fusiform gyrus, the patient reported that the faces of the researchers appeared to change and morphed in front of him. This demonstrates a causal link between the fusiform gyrus and the human ability to recognize faces.
Musical Pattern Recognition
The brain arranges and stores information in neuronal networks and retrieves that information when activated by stimuli in the environment.
For music, this constant referencing of information and environmental stimulus from the environment allows the brain to reconstruct individual musical features into a perceptual whole.
Retrieving the memory of a song expresses general recognition of musical pattern, but pattern recognition also occurs when we hear a song for the first time. Rhythm allows the listener to follow a tempo, recognize the pattern, and expect its recurrence.
When the pattern changes abruptly, the brain’s neural networks get excited and go to work trying to fit the new elements in with the expected. This creates a problem-solving opportunity for the brain that solidifies the experience in memory.
Music activates the medial prefrontal cortex (mPFC), which is usually one of the last areas affected by neurological issues. In turn, the mPFC relies on the hippocampus for learning and memory consolidation.
Music elicits deep emotional experiences from the listener. And potent emotional imprints are stored in long-term memory. So, when we hear the particular song that aroused the initial emotional reaction, that memory is turned on, automatically triggering pattern recognition.
Pattern Recognition and Cognitive Function
Working memory, sometimes called short-term memory, is essential for pattern recognition. Pattern recognition is a subliminal, automatic response to environmental stimuli. So, without working memory, the brain cannot retrieve or process information in the moment.
For instance, working memory helps accelerate pattern recognition during gameplay. A good working memory amps up the speed of information processing, a huge part of pattern recognition processing.
And quick, accurate pattern recognition gives players a cognitive edge – a cognitive two for one.
Learning is important for pattern recognition because it is the brain’s preferred means of training itself. Through training over time, learning allows the brain to adapt to varying environments so it can accurately process patterns.
The more patterns the brain learns, the better it gets at pattern recognition overall. For example, language is a type of pattern. People who understand multiple languages find it easier to learn a new language than those who comprehend one.
Learning to recognize various language patterns makes it easier for the brain to recognize other, unfamiliar language patterns.
But the link between language learning and pattern recognition goes both ways. Research suggests that language acquisition in infants is linked to accurate pattern recognition.
Studies at Hebrew University and the University of Sydney both reveal a strong correlation between the ability to learn a new language and to identify visual patterns.
- These studies conclude that children with high shape recognition displayed better grammar, even when controlling for intelligence and memory variables.
Fluid intelligence lubricates various cognitive mechanisms, including learning and memory, so they can work together to store and retrieve relevant information.
Learning and memory help store and identify patterns and relationships between different objects or sets of information. In turn, pattern recognition helps improve reasoning and problem solving.
No cognitive function, including pattern recognition, operates from one brain area or mechanism alone, and fluid intelligence makes it easier for complementary cognitive functions to interact seamlessly.
Good chess players are able to recognize and respond to complex patterns. In fact, you could say that chess is a game built upon pattern recognition.
Though other cognitive functions definitely factor in, fast, flexible pattern recognition skills are paramount for the win.
Pattern Recognition in Artificial Intelligence
The human brain is amazing at pattern recognition. Humans can recognize countless types of patterns and transform them into tangible, practical information. And we learn to recognize patterns and differentiate between objects at a very young age.
IQ is measured largely upon the ability to store the greatest amount of patterns. Defeating a human in the game Go has long been considered the gold standard for AI. When Google’s DeepMind AI beat Lee Sedol, one of the top-ranked human Go players, for the third time in 2016, machines gained enough pattern-recognition skill to compete with humans.
In the context of AI, pattern recognition is a sub-set of machine learning that greatly expands its application potential, including:
- Speech recognition
- Speaker identification
- Multimedia document recognition (MDR)
- Automatic medical diagnosis.
Now, IBM’s Watson is diagnosing medical conditions, and future AI will do it even better. The same applies to just about any expert field.
As machines gain more processing power they develop the ability to recognize patterns more accurately and faster than anyone else, making them the doctors, engineers, and scientists of the future.
Pattern recognition is one of the main factors that gives humans an evolutionary advantage over animals. The ability to expand and refine our ability to recognize patterns is a crucial part of the solution to keeping our edge over AI.
Honing selective attention skills can improve pattern recognition skills by automatically dumping the least relevant possibilities in favor of fewer, more viable choices.
Mind Lab Pro® Nootropics for Pattern Recognition
Upgrading the human brain’s ability to recognize patterns swiftly and accurately is more important than ever. If we expect to compete with machines for superior functioning in areas once considered solely the domain of humankind, we must speed up information processing and decision-making skills.
Nootropics for pattern recognition can enhance cognitive functions like memory and learning that directly influence the brain’s ability to process, recognize and identify patterns.
Bacopa monnieri is an adaptogen herb valued in ancient and modern Ayurvedic traditions for its calming properties.
But it also supports learning, boosts working memory, and assists with long-term memory retention, so you can identify new patterns and recognize learned ones faster.
Bacopa may even accelerate visual information processing, helping you recognize visual patterns more quickly.
B. monnieri stimulates the dopaminergic system in the frontal lobes, and studies show that dopamine, norepinephrine, and GABA help enhance information processing speed and amplify pattern recognition.
- More importantly, Bacopa speeds up pattern recognition by expediting neural communication and accelerating the growth rate of nerve endings called dendrites in the nervous system.
L-tyrosine is a naturally occurring amino acid that regulates dopamine and other neurotransmitters that influence memory, spatial perception, and pattern recognition.
N-acetyl-L-tyrosine (NALT) is a more absorbable and bioavailable form of L-tyrosine, making it even more effective.
High-pressure fields like engineering, mathematics, science, physics, medicine, and computer programming require fast and precise pattern recognition skills.
But stress can deplete tyrosine levels in the brain, affecting memory and decision making – cognitive functions directly involved with pattern recognition.
- Supplementing with NALT can protect the brain from the effects of stress and protect pattern recognition speed and accuracy.
Mind Lab Pro® nootropics for pattern recognition improve memory and learning for better pattern recognition speed and accuracy.
Optimal mental performance enhances collective cognitive functioning so your brain fires on all cylinders, giving you access to 100% Brainpower™.
- Mind Lab Pro® is the world’s first Universal Nootropic™ , an all-natural whole-brain optimizer that targets all facets of human cognition, including pattern recognition.
In order to compete with future AI, we must increase our brain’s intelligence and processing speed.
Mind Lab Pro® nootropics can supplement a healthy lifestyle to support overall brain health and protect cognitive functioning, helping human intelligence advance alongside the machines we create.
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