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Related Concept Videos

Higher Mental Functions of Brain: Learning and Memory01:26

Higher Mental Functions of Brain: Learning and Memory

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Memory is one of the most vital higher mental functions of the brain. Memory is closely related to learning because it enables us to retain information and experiences from our past to use them in our present life. It also helps us to remember facts, events, and skills, such as riding a bike or swimming. There are two types of memory — declarative memory, which involves memorizing facts or events, and procedural memory, which enables us to remember how to do something like writing or...
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Working memory refers to a combination of components, including short-term memory and attention, that allow an individual to hold information temporarily as we perform cognitive tasks. It is an essential cognitive function that enables the execution of complex tasks such as problem-solving, comprehension, and reasoning. Unlike short-term memory, which simply involves the storage of information for a brief period, working memory involves the active manipulation and processing of this...
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Storage01:23

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A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
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Understanding Memory01:19

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Memory is the retention of information or experiences over time, facilitated through three main processes: encoding, storage, and retrieval. Encoding is the process of inputting information into the memory system. For instance, when listening to a lecture, watching a play, reading a book, or having a conversation, the brain is actively encoding information. This initial stage involves transforming sensory input into a form that can be processed and stored by the brain. Various factors, such as...
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Implicit Memories01:24

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Implicit memories, also known as non-declarative memories, are long-term memories that function outside of conscious awareness. These memories influence behavior and skills without explicit knowledge. This type of memory is evident in tasks like playing tennis, snowboarding, and texting. Implicit memory has three subsystems: procedural memory, conditioning, and priming. This type of memory is essential in various activities, from everyday tasks to specialized skills.
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Role of Cerebellum and Prefrontal Cortex in Memory01:14

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The cerebellum, while traditionally associated with motor control, also plays a crucial role in memory, particularly in procedural memory, which involves learning motor tasks that become automatic through repetition. For example, studies have shown that when the cerebellum is damaged, individuals or animals lose the ability to learn conditioned motor responses, such as the conditioned eye-blink response in classical conditioning experiments with rabbits. This study demonstrates the...
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Related Experiment Video

Updated: Jun 27, 2025

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes
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A Survey of Emerging Memory in a Microcontroller Unit.

Longning Qi1, Jinqi Fan1, Hao Cai1

  • 1School of Integrated Circuits, Southeast University, Nanjing 210096, China.

Micromachines
|April 27, 2024
PubMed
Summary
This summary is machine-generated.

Emerging nonvolatile memories (NVMs) in microcontroller units (MCUs) prevent data loss during power outages. These NVMs enable energy-autonomous systems and pave the way for advanced Internet of Things and neural network applications.

Keywords:
FRAMMRAMPCMRRAMembedded NVMemerging memories

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Area of Science:

  • Electronics and Computer Engineering
  • Materials Science
  • Embedded Systems

Background:

  • Edge computing and battery-powered devices require robust energy conservation, but power shutdowns risk data loss in volatile memory.
  • Energy autonomous systems face operational instability due to inevitable power losses.
  • Emerging nonvolatile memories (NVMs) present a solution to maintain system progress during power interruptions.

Purpose of the Study:

  • To review the integration of emerging NVMs (FRAM, RRAM, MRAM, PCM) within microcontroller units (MCUs).
  • To compare the attributes, benefits, and applications of various NVM technologies for MCUs.
  • To explore NVM circuit design and compute-in-memory (CIM) architectures.

Main Methods:

  • Comprehensive literature review of emerging NVM technologies and their application in MCUs.
  • Comparative analysis of key NVM attributes, focusing on energy efficiency and data retention.
  • Discussion of circuit design considerations and compute-in-memory paradigms enabled by NVMs.

Main Results:

  • Emerging NVMs like FRAM, RRAM, MRAM, and PCM offer viable solutions for data persistence in MCUs during power outages.
  • These NVMs provide minimal energy overhead for sustaining work progress, crucial for energy-constrained systems.
  • NVM integration facilitates advanced functionalities including NVM-driven CIM architectures.

Conclusions:

  • Integrating emerging NVMs into MCUs is a promising strategy for next-generation edge computing applications.
  • NVMs enhance the reliability and efficiency of battery-powered and energy-autonomous devices.
  • The study highlights the potential of NVMs for the Internet of Things (IoT) and neural network hardware.