This document discusses key concepts related to learning, brain development, and neuroplasticity. It defines learning as lasting changes in the functional architecture of the brain through modifications to neural connectivity and synaptic strength. Learning is influenced by both evolution and experience-dependent development. There are critical periods early in life when the brain is most plastic and receptive to certain types of learning. However, the brain remains plastic throughout life, with different forms of plasticity like experience-expectant and experience-dependent mechanisms enabling continuous learning from experiences.
1. The document defines learning as the long-lasting modification of the functional architecture of the brain through changes to neuronal connectivity and efficacy.
2. It discusses how evolution, development, and learning all shape the brain's functional architecture. Evolution selects learning mechanisms and stored knowledge. Brain development wires circuits based on experience within critical periods.
3. Adult learning involves modifying the efficacy of existing connections rather than structural changes, as the architecture is largely set after development. Experience and environment influence both development and lifelong learning.
1. The cortex and basal ganglia play important roles in motor learning through changes in their neural networks. The cerebellum, thalamus, and motor cortex are involved in motor learning tasks.
2. The primary motor cortex generates movement signals and also plays a role in higher cognitive processes like attention, motor learning, and movement inhibition as shown through noninvasive brain stimulation techniques.
3. The supplementary motor area, pre-motor cortex, and basal ganglia are also involved in motor control and learning. The basal ganglia help mediate stimulus-response learning through incremental acquisition of associations.
Understanding the encoding of memory and its retrieval is a complex task. The neurobiological correlates of memory have been summarised in this presentation for easy understanding of students.
This document discusses how memories are formed and stored in the brain. It explains that memories are formed through synaptic plasticity, which refers to changes in the strength of connections between neurons. These connections are made stronger or weaker based on past activation patterns. Three key areas involved in memory are the hippocampus, which forms episodic memories; the amygdala, which attaches emotional significance; and the neocortex, where memories may be consolidated over time. Different memory systems rely on different brain regions, such as the basal ganglia and cerebellum for implicit memories, and the prefrontal cortex for working memory. The document also outlines how occupational therapists assess memory through standardized tests and occupation-based evaluations.
This document outlines the agenda and content for a seminar on cognitive neuroscience. It introduces cognitive neuroscience as the study of biological substrates underlying cognition, focusing on the neural substrate of mental processes. It discusses the basic unit of the brain (the neuron), cognition, neurocognition, areas of the brain like the hippocampus and prefrontal cortex. It also outlines methods used to study cognition like psychophysics, EEG, fMRI, and transcranial magnetic stimulation. The seminar aims to provide an understanding of how psychological/cognitive functions are produced by neural circuits in the brain.
This document may help one to understand that how learning and synaptic plasticity are connected in a detailed manner.It may also help to understand HEBBs theory with various animals.In this he has taken rat as his subject.
Marines Longart is a neuroscientist seeking a new position. She has extensive experience researching neuronal differentiation and synaptic plasticity. Her work has identified proteins that regulate neuronal development and signaling pathways modulating differentiation. Longart has also studied how neuregulin proteins differentially target neurons and regulate synaptic plasticity mechanisms like long-term potentiation. She is eager to continue her research career at an institution that prioritizes neuroscience.
This document provides summaries of four keynote presentations and four symposia abstracts from the Australasian Cognitive Neurosciences Conference held in December 2012.
The keynote presentations discuss research on how memory supports future thinking, limits of subliminal processing and signatures of conscious access, temporal processing deficits in neurodevelopmental disorders, and the role of neural oscillations in schizophrenia and brain development.
The symposia abstracts report on research examining individual differences in cognitive flexibility and its neural bases, the neural mechanisms underlying cognitive control over reward in opiate users and healthy controls, behavioral control in adults with schizophrenia and children at elevated risk, and the development of cognitive control networks from childhood to adulthood.
1. The document defines learning as the long-lasting modification of the functional architecture of the brain through changes to neuronal connectivity and efficacy.
2. It discusses how evolution, development, and learning all shape the brain's functional architecture. Evolution selects learning mechanisms and stored knowledge. Brain development wires circuits based on experience within critical periods.
3. Adult learning involves modifying the efficacy of existing connections rather than structural changes, as the architecture is largely set after development. Experience and environment influence both development and lifelong learning.
1. The cortex and basal ganglia play important roles in motor learning through changes in their neural networks. The cerebellum, thalamus, and motor cortex are involved in motor learning tasks.
2. The primary motor cortex generates movement signals and also plays a role in higher cognitive processes like attention, motor learning, and movement inhibition as shown through noninvasive brain stimulation techniques.
3. The supplementary motor area, pre-motor cortex, and basal ganglia are also involved in motor control and learning. The basal ganglia help mediate stimulus-response learning through incremental acquisition of associations.
Understanding the encoding of memory and its retrieval is a complex task. The neurobiological correlates of memory have been summarised in this presentation for easy understanding of students.
This document discusses how memories are formed and stored in the brain. It explains that memories are formed through synaptic plasticity, which refers to changes in the strength of connections between neurons. These connections are made stronger or weaker based on past activation patterns. Three key areas involved in memory are the hippocampus, which forms episodic memories; the amygdala, which attaches emotional significance; and the neocortex, where memories may be consolidated over time. Different memory systems rely on different brain regions, such as the basal ganglia and cerebellum for implicit memories, and the prefrontal cortex for working memory. The document also outlines how occupational therapists assess memory through standardized tests and occupation-based evaluations.
This document outlines the agenda and content for a seminar on cognitive neuroscience. It introduces cognitive neuroscience as the study of biological substrates underlying cognition, focusing on the neural substrate of mental processes. It discusses the basic unit of the brain (the neuron), cognition, neurocognition, areas of the brain like the hippocampus and prefrontal cortex. It also outlines methods used to study cognition like psychophysics, EEG, fMRI, and transcranial magnetic stimulation. The seminar aims to provide an understanding of how psychological/cognitive functions are produced by neural circuits in the brain.
This document may help one to understand that how learning and synaptic plasticity are connected in a detailed manner.It may also help to understand HEBBs theory with various animals.In this he has taken rat as his subject.
Marines Longart is a neuroscientist seeking a new position. She has extensive experience researching neuronal differentiation and synaptic plasticity. Her work has identified proteins that regulate neuronal development and signaling pathways modulating differentiation. Longart has also studied how neuregulin proteins differentially target neurons and regulate synaptic plasticity mechanisms like long-term potentiation. She is eager to continue her research career at an institution that prioritizes neuroscience.
This document provides summaries of four keynote presentations and four symposia abstracts from the Australasian Cognitive Neurosciences Conference held in December 2012.
The keynote presentations discuss research on how memory supports future thinking, limits of subliminal processing and signatures of conscious access, temporal processing deficits in neurodevelopmental disorders, and the role of neural oscillations in schizophrenia and brain development.
The symposia abstracts report on research examining individual differences in cognitive flexibility and its neural bases, the neural mechanisms underlying cognitive control over reward in opiate users and healthy controls, behavioral control in adults with schizophrenia and children at elevated risk, and the development of cognitive control networks from childhood to adulthood.
Connectomics is a new paradigm for understanding brain diseases using comprehensive maps of neural connections in the brain. Magnetic resonance imaging (MRI) techniques like functional MRI and diffusion MRI allow non-invasive mapping of functional and anatomical connectivity networks in the living human brain. There are three main approaches to analyzing connectome data: candidate circuit analysis of specific hypothesized networks, connectome-wide analysis of effects across the entire connectivity matrix, and topological analysis of network organization. Connectomics research aims to uncover mechanisms of neurological disorders and enable more targeted clinical applications.
This document discusses a hypothesis that molecular dynamics across neural membranes and cytoskeletal structures provide a matrix for self-organized behavior and information processing in the brain. Specifically:
1) Patterns of molecular activity may form stable solitons or "chaotons" capable of storing information over time, providing a basis for learning, memory, and consciousness.
2) These solitons could behave in a self-similar way across complexes of neurons operating within synapto-dendritic field activity.
3) Atomic force microscopy may help experimentally confirm theoretical models of these solitons and emergent structures in subcellular processes.
Neuroscience is the scientific study of the nervous system. It is an interdisciplinary field that collaborates with other sciences. Neuroscience examines the nervous system from molecular to cognitive levels using various techniques. Modern neuroscience can be categorized into major branches that study specific areas and scales of the nervous system, such as behavioral, cellular, clinical, and computational neuroscience. Neuroscientists often work across subfields to answer questions.
This document provides a student research proposal for a project studying adult hippocampal neurogenesis across primate species, including humans. The student aims to quantify and compare the presence of new neurons in the dentate gyrus of various primates to test the hypothesis that humans have greater neurogenesis which could allow for unique episodic memory abilities. The student has experience in neuroanatomy research and aims to continue the project to gain skills relevant to future career goals investigating memory and neurolaw.
Memory involves the storage and retrieval of information acquired through learning. For memories to form, learning causes persistent changes in brain structure and function. The parts of the brain involved in memory include the frontal, parietal, occipital and temporal lobes, limbic system structures like the hippocampus and amygdala, and the diencephalon. Different types of memory include immediate memory for recent experiences, procedural memory for skills, short-term memory for seconds to minutes, and long-term memory stored from days to years. Memory formation results from changes in neurons and synaptic connections in networks across the brain.
Neural oscillations occur throughout the central nervous system and can be measured at different scales: microscopic (single neuron), mesoscopic (local groups of neurons), and macroscopic (between brain regions). At the microscopic level, neurons generate action potentials that form rhythmic spike trains. Groups of synchronized neurons give rise to local field potential oscillations. Interactions between brain areas also produce large-scale oscillations measured by EEG. Different neural oscillations have been linked to cognitive functions like perception and memory.
This document discusses physiology of memory and learning. It defines learning as a relatively permanent change in behavior due to experience, while memory is the ability to recall past events. There are two main types of learning - associative and non-associative. Associative learning involves associating stimuli, like in classical and operant conditioning. Non-associative learning does not require association of stimuli, and includes habituation and sensitization. Memory is classified into sensory, short-term, long-term and permanent memory based on duration. The hippocampus and surrounding areas are involved in consolidating memories by converting them from short-term to long-term storage through long-term potentiation.
This document summarizes key concepts from a psychology unit on memory, including:
1. Long-term memories have an unlimited capacity and are stored across interconnected brain networks rather than single locations. The hippocampus organizes new memories and stores them in various brain centers.
2. The frontal lobes support working memory while the hippocampus processes explicit memories by consolidating short-term memories into long-term storage during sleep. Damage to the hippocampus impairs new explicit memory formation.
3. The cerebellum and basal ganglia support implicit memory and automatic processing through classical conditioning and procedural memory formation. Damage to the cerebellum inhibits new habit formation.
This document discusses the biological basis of memory. It covers topics like the definition of memory, different types of memory (sensory, short-term, long-term, working), memory processes (encoding, storage, retrieval), neuroplasticity mechanisms like long-term potentiation, molecular basis of memory formation, brain structures involved in memory like the hippocampus and amnesia. It provides historical context on pioneering figures who studied memory and describes classical experiments that advanced the understanding of the neurological underpinnings of memory.
This document provides background information on a book titled "Coherent Behavior in Neuronal Networks". It begins with a preface written by the book's four editors - Kresimir Josic, Jonathan Rubin, Manuel A. Matias, and Ranulfo Romo. The preface describes the motivation and goals for the book, which is to provide a sampling of recent research on coherent neuronal network behavior from an interdisciplinary perspective, with contributions from both experimentalists and theorists. It then provides a brief overview of the book's scientific content, which covers topics such as ongoing cortical activity, small neuronal network interactions, spatiotemporal neuronal activity patterns, and coherence in encoding and decoding across different systems.
This document discusses declarative memory, which includes both episodic and semantic memory. It defines declarative memory as factual knowledge and memories of past events that are encoded by the hippocampus, entorhinal cortex, and perirhinal cortex. Episodic memory refers to autobiographical memories of specific events and experiences, while semantic memory involves general factual knowledge. The document also discusses the HM case of a patient with amnesia following removal of parts of the hippocampus, and how this case contributed to understanding the brain regions involved in memory formation.
The document discusses neurobiology of memory, including:
1. It describes the anatomical and functional organization of memory, focusing on the hippocampus formation, its afferents and efferents, and its role in learning and memory.
2. It discusses the different types of memory including explicit and implicit memory, and the cellular and molecular processes underlying short-term and long-term memory formation.
3. It explains mechanisms of memory formation and consolidation at the synaptic level, including the roles of proteins like CaMKII and CREB.
Modulation of theta phase sync during a recognition memory taskKyongsik Yun
1) The study examined changes in theta phase synchronization across the brain during a recognition memory task using electroencephalography.
2) They found that theta phase synchronization was stronger between the frontal and left parietal areas during correct recognition of previously viewed objects compared to identifying new objects.
3) Specifically, theta phase synchronization between these regions increased from 400-1100ms after stimulus onset for recognized objects, suggesting recognition memory involves interaction between the frontal and left parietal cortices mediated by theta phase synchronization.
Computational neuropharmacology drug designingRevathi Boyina
This document discusses computational neuropharmacology, which uses computational modeling approaches from neuroscience and dynamical systems theory integrated with traditional neuropharmacological methods to study drug effects on the brain and behavior. It describes how computational models are used in neuroscience to simulate neurons, neural circuits, and brain regions. It suggests computational neuropharmacology could help integrate molecular and systems-level descriptions of the nervous system to analyze drug effects on neural activity patterns and behavioral states. This may provide strategies for molecular screening of drugs and searching for target-specific drugs to shift pathological brain dynamics to normal patterns.
Este artículo expone la idea de que las operaciones neocorticales son multisensoriales, es decir, suponen la integración de información de múltiples fuentes sensitivas
1. Memory involves multiple brain structures working together, including the hippocampus, medial temporal lobe, striatum, thalamus, and neocortex.
2. Visual information is first processed in the visual cortex, then held in short-term memory in the frontal lobes.
3. The hippocampus stores new information from short-term memory for weeks or months before transferring it to the cerebral cortex for long-term storage.
4. Recalling long-term memories routes information from the cerebral cortex back to the frontal lobes for temporary storage in working memory.
Quantum physics in neuroscience and psychology a new theory with respect to m...Elsa von Licy
This document discusses a new model for understanding the relationship between mind and brain based on principles of quantum physics. It proposes that classical physics, which views the brain as entirely material, cannot fully explain phenomena like self-directed neuroplasticity where mental processes like attention and effort are able to systematically alter brain function. Quantum physics provides a framework to causally relate mental and physical properties and allow psychological concepts to be included as causal factors in models of brain function. The authors argue this provides a more coherent understanding of how directed attention and cognitive strategies can produce changes in the brain.
Building Executable Biology Models for Synthetic BiologyNatalio Krasnogor
The leveraging of today's unprecedented capability to manipulate biological systems by state-of-the-art computational, mathematical and engineering techniques , may profoundly affect the way we approach the solution to pressing grand challenges such as the development of sustainable green energy, next generation healthcare, etc. The conceptual cornerstone of Synthetic Biology a field very much on its infancy- is that methodologies commonly used to design and construct non-biological artefacts (e.g. computer programs, airplanes, bridges, etc) might also be mastered to create designer living entities. Computational methods for modeling in Synthetic Biology consist of a list of instructions detailing an algorithm that can be executed and whose computation resembles the behavior of the biological system under study. This computational approach to modelling biological systems has been termed executable biology. In this talk I will describe current approaches for the automated generation and testing of executable biology models for synthetic biology.
This was a colloquioum talk at the Computer Science Department, Ben-Gurion University of the Negev, Israel (30/June/2009)
Neuroplasticity refers to the brain's ability to change and adapt in response to experience. It allows for strengthening and weakening of nerve connections and even the growth of new nerve cells. All areas of the brain show some degree of plasticity, even in adulthood, contrary to previous beliefs. Experiences shape the brain by stimulating synaptogenesis, synaptic pruning, and changes in neuronal connectivity. Neuroplasticity enables learning, recovery from injury, and adaptation to environmental changes throughout life.
این پاورپوینت خلاصه شده فصل شش یکی از کتابهای مربوط به علوم اعصاب است. این پاورپوینت در کارگاه تخصصی توانبخشی دیداری عصبی توسط دکتر علیزاده ارائه شده است.
screening models for Nootropics and models for Alzheimer's diseaseAswin Palanisamy
Preclinical and screening model for Nootropics, and models for Alzheimer's disease, in the detailed view, in vivo and in vitro models with neat pictures for easy understanding. for m.pharm students.
Connectomics is a new paradigm for understanding brain diseases using comprehensive maps of neural connections in the brain. Magnetic resonance imaging (MRI) techniques like functional MRI and diffusion MRI allow non-invasive mapping of functional and anatomical connectivity networks in the living human brain. There are three main approaches to analyzing connectome data: candidate circuit analysis of specific hypothesized networks, connectome-wide analysis of effects across the entire connectivity matrix, and topological analysis of network organization. Connectomics research aims to uncover mechanisms of neurological disorders and enable more targeted clinical applications.
This document discusses a hypothesis that molecular dynamics across neural membranes and cytoskeletal structures provide a matrix for self-organized behavior and information processing in the brain. Specifically:
1) Patterns of molecular activity may form stable solitons or "chaotons" capable of storing information over time, providing a basis for learning, memory, and consciousness.
2) These solitons could behave in a self-similar way across complexes of neurons operating within synapto-dendritic field activity.
3) Atomic force microscopy may help experimentally confirm theoretical models of these solitons and emergent structures in subcellular processes.
Neuroscience is the scientific study of the nervous system. It is an interdisciplinary field that collaborates with other sciences. Neuroscience examines the nervous system from molecular to cognitive levels using various techniques. Modern neuroscience can be categorized into major branches that study specific areas and scales of the nervous system, such as behavioral, cellular, clinical, and computational neuroscience. Neuroscientists often work across subfields to answer questions.
This document provides a student research proposal for a project studying adult hippocampal neurogenesis across primate species, including humans. The student aims to quantify and compare the presence of new neurons in the dentate gyrus of various primates to test the hypothesis that humans have greater neurogenesis which could allow for unique episodic memory abilities. The student has experience in neuroanatomy research and aims to continue the project to gain skills relevant to future career goals investigating memory and neurolaw.
Memory involves the storage and retrieval of information acquired through learning. For memories to form, learning causes persistent changes in brain structure and function. The parts of the brain involved in memory include the frontal, parietal, occipital and temporal lobes, limbic system structures like the hippocampus and amygdala, and the diencephalon. Different types of memory include immediate memory for recent experiences, procedural memory for skills, short-term memory for seconds to minutes, and long-term memory stored from days to years. Memory formation results from changes in neurons and synaptic connections in networks across the brain.
Neural oscillations occur throughout the central nervous system and can be measured at different scales: microscopic (single neuron), mesoscopic (local groups of neurons), and macroscopic (between brain regions). At the microscopic level, neurons generate action potentials that form rhythmic spike trains. Groups of synchronized neurons give rise to local field potential oscillations. Interactions between brain areas also produce large-scale oscillations measured by EEG. Different neural oscillations have been linked to cognitive functions like perception and memory.
This document discusses physiology of memory and learning. It defines learning as a relatively permanent change in behavior due to experience, while memory is the ability to recall past events. There are two main types of learning - associative and non-associative. Associative learning involves associating stimuli, like in classical and operant conditioning. Non-associative learning does not require association of stimuli, and includes habituation and sensitization. Memory is classified into sensory, short-term, long-term and permanent memory based on duration. The hippocampus and surrounding areas are involved in consolidating memories by converting them from short-term to long-term storage through long-term potentiation.
This document summarizes key concepts from a psychology unit on memory, including:
1. Long-term memories have an unlimited capacity and are stored across interconnected brain networks rather than single locations. The hippocampus organizes new memories and stores them in various brain centers.
2. The frontal lobes support working memory while the hippocampus processes explicit memories by consolidating short-term memories into long-term storage during sleep. Damage to the hippocampus impairs new explicit memory formation.
3. The cerebellum and basal ganglia support implicit memory and automatic processing through classical conditioning and procedural memory formation. Damage to the cerebellum inhibits new habit formation.
This document discusses the biological basis of memory. It covers topics like the definition of memory, different types of memory (sensory, short-term, long-term, working), memory processes (encoding, storage, retrieval), neuroplasticity mechanisms like long-term potentiation, molecular basis of memory formation, brain structures involved in memory like the hippocampus and amnesia. It provides historical context on pioneering figures who studied memory and describes classical experiments that advanced the understanding of the neurological underpinnings of memory.
This document provides background information on a book titled "Coherent Behavior in Neuronal Networks". It begins with a preface written by the book's four editors - Kresimir Josic, Jonathan Rubin, Manuel A. Matias, and Ranulfo Romo. The preface describes the motivation and goals for the book, which is to provide a sampling of recent research on coherent neuronal network behavior from an interdisciplinary perspective, with contributions from both experimentalists and theorists. It then provides a brief overview of the book's scientific content, which covers topics such as ongoing cortical activity, small neuronal network interactions, spatiotemporal neuronal activity patterns, and coherence in encoding and decoding across different systems.
This document discusses declarative memory, which includes both episodic and semantic memory. It defines declarative memory as factual knowledge and memories of past events that are encoded by the hippocampus, entorhinal cortex, and perirhinal cortex. Episodic memory refers to autobiographical memories of specific events and experiences, while semantic memory involves general factual knowledge. The document also discusses the HM case of a patient with amnesia following removal of parts of the hippocampus, and how this case contributed to understanding the brain regions involved in memory formation.
The document discusses neurobiology of memory, including:
1. It describes the anatomical and functional organization of memory, focusing on the hippocampus formation, its afferents and efferents, and its role in learning and memory.
2. It discusses the different types of memory including explicit and implicit memory, and the cellular and molecular processes underlying short-term and long-term memory formation.
3. It explains mechanisms of memory formation and consolidation at the synaptic level, including the roles of proteins like CaMKII and CREB.
Modulation of theta phase sync during a recognition memory taskKyongsik Yun
1) The study examined changes in theta phase synchronization across the brain during a recognition memory task using electroencephalography.
2) They found that theta phase synchronization was stronger between the frontal and left parietal areas during correct recognition of previously viewed objects compared to identifying new objects.
3) Specifically, theta phase synchronization between these regions increased from 400-1100ms after stimulus onset for recognized objects, suggesting recognition memory involves interaction between the frontal and left parietal cortices mediated by theta phase synchronization.
Computational neuropharmacology drug designingRevathi Boyina
This document discusses computational neuropharmacology, which uses computational modeling approaches from neuroscience and dynamical systems theory integrated with traditional neuropharmacological methods to study drug effects on the brain and behavior. It describes how computational models are used in neuroscience to simulate neurons, neural circuits, and brain regions. It suggests computational neuropharmacology could help integrate molecular and systems-level descriptions of the nervous system to analyze drug effects on neural activity patterns and behavioral states. This may provide strategies for molecular screening of drugs and searching for target-specific drugs to shift pathological brain dynamics to normal patterns.
Este artículo expone la idea de que las operaciones neocorticales son multisensoriales, es decir, suponen la integración de información de múltiples fuentes sensitivas
1. Memory involves multiple brain structures working together, including the hippocampus, medial temporal lobe, striatum, thalamus, and neocortex.
2. Visual information is first processed in the visual cortex, then held in short-term memory in the frontal lobes.
3. The hippocampus stores new information from short-term memory for weeks or months before transferring it to the cerebral cortex for long-term storage.
4. Recalling long-term memories routes information from the cerebral cortex back to the frontal lobes for temporary storage in working memory.
Quantum physics in neuroscience and psychology a new theory with respect to m...Elsa von Licy
This document discusses a new model for understanding the relationship between mind and brain based on principles of quantum physics. It proposes that classical physics, which views the brain as entirely material, cannot fully explain phenomena like self-directed neuroplasticity where mental processes like attention and effort are able to systematically alter brain function. Quantum physics provides a framework to causally relate mental and physical properties and allow psychological concepts to be included as causal factors in models of brain function. The authors argue this provides a more coherent understanding of how directed attention and cognitive strategies can produce changes in the brain.
Building Executable Biology Models for Synthetic BiologyNatalio Krasnogor
The leveraging of today's unprecedented capability to manipulate biological systems by state-of-the-art computational, mathematical and engineering techniques , may profoundly affect the way we approach the solution to pressing grand challenges such as the development of sustainable green energy, next generation healthcare, etc. The conceptual cornerstone of Synthetic Biology a field very much on its infancy- is that methodologies commonly used to design and construct non-biological artefacts (e.g. computer programs, airplanes, bridges, etc) might also be mastered to create designer living entities. Computational methods for modeling in Synthetic Biology consist of a list of instructions detailing an algorithm that can be executed and whose computation resembles the behavior of the biological system under study. This computational approach to modelling biological systems has been termed executable biology. In this talk I will describe current approaches for the automated generation and testing of executable biology models for synthetic biology.
This was a colloquioum talk at the Computer Science Department, Ben-Gurion University of the Negev, Israel (30/June/2009)
Neuroplasticity refers to the brain's ability to change and adapt in response to experience. It allows for strengthening and weakening of nerve connections and even the growth of new nerve cells. All areas of the brain show some degree of plasticity, even in adulthood, contrary to previous beliefs. Experiences shape the brain by stimulating synaptogenesis, synaptic pruning, and changes in neuronal connectivity. Neuroplasticity enables learning, recovery from injury, and adaptation to environmental changes throughout life.
این پاورپوینت خلاصه شده فصل شش یکی از کتابهای مربوط به علوم اعصاب است. این پاورپوینت در کارگاه تخصصی توانبخشی دیداری عصبی توسط دکتر علیزاده ارائه شده است.
screening models for Nootropics and models for Alzheimer's diseaseAswin Palanisamy
Preclinical and screening model for Nootropics, and models for Alzheimer's disease, in the detailed view, in vivo and in vitro models with neat pictures for easy understanding. for m.pharm students.
The nervous system: an evolutionary approachCaio Maximino
The document summarizes a lecture on the evolutionary approach to understanding the nervous system. It discusses common misconceptions about brain evolution, focusing on the oversimplified view that brain evolution was a linear progression from simple to complex. It also outlines the key topics covered in the lecture, including the bauplan of the vertebrate brain, conservation of molecular and developmental mechanisms across species, changes in brain size and region sizes over evolution, and how these changes impacted connectivity and functions. Finally, it notes that climate change can impact brain development and evolution by influencing neurogenesis and the adaptiveness of neural systems to the sensory environment.
Neuroplasticity refers to the brain's ability to change and adapt in structure and function in response to learning and experience. It occurs throughout life as new neural pathways are strengthened through learning and experience, while unused pathways weaken and die. Theories of neuroplasticity were first proposed in the late 19th century, and it is now understood that the brain can rearrange its structure and functions through various mechanisms like functional and structural plasticity. Physiotherapy techniques can enhance neuroplasticity and aid recovery after brain damage.
Plasticity of the brain - VCE U4 PsychologyAndrew Scott
This file covers Developmental Plasticity including Synaptogenesis, Pruning, Migration and Myelination & Adaptive Plasticity including Rerouting & Sprouting. This file accompanies a Youtube clip made on this topic see my channel - Psyccounting
Neuroplasticity refers to the brain's ability to change and adapt throughout life in response to experiences. There are two main types of neuroplasticity - structural, involving physical changes to neurons and synapses, and functional, involving changes in neural pathways and connections that underlie learning and memory. Structural neuroplastic changes include synaptic plasticity, synaptogenesis, neurogenesis, and neural cell death. Functional changes are mediated by synaptic plasticity mechanisms like long-term potentiation and long-term depression. Neuroplasticity allows the brain to form new memories and skills, but can also contribute to cognitive decline or altered motor control depending on the circumstances.
The document is a travel grant application by Christian Jaques Hissom to present research conducted over the summer investigating the functional significance of neurons in the thalamus and motor cortex related to motor learning. It provides details of the research conducted, including training rats in a motor task, selectively ablating neuron populations, analyzing behavioral changes, and proposed future research. The application requests funding to present this research at the Emerging Researchers National Conference in STEM in Washington D.C. in February 2014.
The document provides an overview of the biological aspects of psychology, including:
- The nervous system and endocrine system direct activities in the body. The nervous system is composed of the central and peripheral nervous systems.
- Neurons are the basic unit of the nervous system and communicate via electrical and chemical signals. The peripheral nervous system connects the central nervous system to senses and organs.
- The central nervous system includes the brain and spinal cord. Techniques like EEG, PET, SPECT, fMRI, TMS provide views of brain structure and function. Key brain regions support functions like movement, memory, and emotion.
A history of optogenetics the development of tools for controlling brain circ...merzak emerzak
Optogenetics allows specific control of neural activity with light by expressing light-sensitive microbial opsins in neurons. The development of optogenetics involved adapting opsins like channelrhodopsin and halorhodopsin that transport ions in response to light. Channelrhodopsin was identified as enabling fast activation of neurons with light, and was expressed in neurons to control their activity, demonstrating the potential of optogenetics to causally study neural circuits.
We have identified goals of education by viewing them from the point of neuroscience; through education, we have to produce individuals who are better problem solvers and decision. To achieve this goal, learners will have to transform what they have learned explicitly into implicit memories and vice versa. Further, through education, we enhance learner consciousness and wisdom. A number of pedagogical practices that are useful in achieving the above goals are presented. When new contents are presented in a teaching-learning environment, high-level concepts need to be highlighted; the concepts are likely to penetrate through multiple domain areas thus helping learners to form better neural networks of knowledge. In order to reach out to multiple brain regions, we need to get the frontal lobe involved essentially and hence the pace of presentation has to be controlled appropriately; as the frontal lobe connects to many brain regions, the processing occurs relatively slowly. The important task of motivating learners can be done by presenting learners with neuroscience-based facts about learning; even difficult content can be mastered by simply paying attention elaborately; human brains have the feature of plasticity and through learning, neural networks can grow throughout the lifespan. Taking into consideration the phenomenon of binocular rivalry - human brains can concentrate only on one thing at a time fully- we should encourage learners to engage in the discussion in a teaching-learning session fully. When setting assessment, we should focus on open-ended, novel conceptual questions so that learners use their frontal lobes connecting many other regions as well.
The document discusses physiological mechanisms and behavior from the perspective of the nervous system and hormones. It provides details on the evolution of the nervous system across organisms from unicellular to multicellular to vertebrates. Key points made include the increasing differentiation and centralization of the nervous system correlating with increased behavioral complexity. Examples are given comparing nervous system anatomy and organization between invertebrate and vertebrate species in relation to different lifestyles and behaviors.
Session 1 Presentation: Attachment, Emotional Well-being and the Developing B...AndriaCampbell
This document provides information about a course on attachment, emotional well-being and the developing brain. It includes an introduction that discusses brain development, trauma, and factors influencing attachment. It outlines the session aims and provides various activities and resources for students. It also covers topics like the physiology of the brain, social constructivism, research informing government policy on early years, and approaches to mental health and well-being. Finally, it discusses key aspects of brain development in early childhood windows of opportunity from birth to 24 months.
How our brain functions when we are aged? In the fast changing world, many a times we heard people saying i am 60 years old and i cannot learn new skills. Is there any truth in the statement. Who is the best consultant for 'downsizing' if we do not use our resouces-It is brain by process.
Learning involves lasting changes in the functional architecture of the brain through experience. It occurs through different mechanisms at various stages of life. Early learning mechanisms in infants and young children include statistical learning, causal learning, imitation, and learning through social interactions. Babies are born with core knowledge and learning mechanisms that allow them to acquire cultural skills and knowledge from a very early age through observation, experimentation, and implicit learning processes. Learning is both an individual and social process supported by evolved capacities for language, cooperation, and culture that enabled the human capacity for cumulative cultural evolution.
The document discusses several cognitive and psychological principles related to learning, including how expert systems attempt to simulate human problem solving, the role of prior knowledge in learning new information, analogical reasoning and transfer of learning. It also addresses the biological basis of learning in the human brain and how neural connections and chemical transmitters support the learning process.
Regeneration of Brain with new understanding gives us good ground to be optimistic in matters of research and also day to day clinics. This presentation at the most introduces you to the potential stride of the field.
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Digital technologies are increasingly used in education both formally and informally. While technologies may engage students as "digital natives," simply using technologies does not guarantee effective learning. Meaningful learning requires understanding principles rather than just practicing skills. Studies show skills can transfer between similar tasks, but not always to novel tasks without principles. Technologies offer potential to simulate real-world problem solving, but more research is needed to identify how and why specific technologies may improve learning outcomes.
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4
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2. Fair testing requires considering alternative explanations, ensuring experimental and control groups are equivalent, using active controls, and not overinterpreting results. Transfer of skills from one context to another is difficult to achieve.
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1. EP1.
Learning
Elena Pasquinelli
Educa3on, cogni3on, cerveau
Cogmaster 2010‐2011
2. Op3miza3on of educa3on
• “Considera3ons on the op3miza3on of
educa3onal strategies should take into
account knowledge on brain development and
learning mechanisms that has been
accumulated by neurobiological research over
the past decades.” (Singer, in BaKro, Fischer &
Léna, 2008, p. 97)
3. • Pre‐programming and experience: rela2onship
between learning, development, evolu2on
• Learning all life‐long?
• Learning everything?
• Prac2cal issues related to plas2city and learning
5. Defini3on of learning
• Learning = modifica3on of stored • “any learning, i.e. the
knowledge and of computa3onal
programs
modifica2on of
computa2onal
• Which takes place through the programs and of stored
modifica3on of the brain knowledge, must occur
func3onal architecture through las$ng
changes in their
• Learning = long‐las3ng change in func$onal
the func3onal architecture of the
brain
architecture.” (Singer,
2008, p. 98)
6. Defini3on of knowledge
• Knowledge is the product • « there is no dichotomy between
of biological processes, hard‐ and soXware in the brain. The
which determine or way in which brains operate is fully
modify the func3onal determined by the integra3ve
architecture of the brain proper3es of the individual nerve
• Learning is one of these cells and the way in which they are
processes interconnected. It is the func3onal
architecture, the blueprint of
connec3ons and their respec3ve
weight, that determines how brains
perceive, decide, and act.
• … all the knowledge that a brain
possesses reside in its func3onal
architecture. » (Singer, 2008, p. 98)
7. Modifica3on of the brain’s func3onal
architecture: 3 processes
• 3 different “altering the integra2ve proper2es of
processes are individual neurons…
responsible of changing the anatomical connec2vity
the paRerns, …
specifica3on/ modifying the efficacy of excitatory
modifica3on of and/or inhibitory connec2ons.
the brain’s
…”(Singer, 2008, p. 98)
func3onal
architecture
(and thus, of
knowledge “Evolu3on,
acquisi3on): Ontogene3c development,
And learning.” (Singer, 2008, p. 98)
8. a. Learning and evolu3on
• Evolu3on has selected both learning mechanisms
and knowledge contents:
– E.g. : “Fire together, wire together”
– E. g. : How to evaluate regulari3es, extract rules,
associate signals, iden3fy causal rela3ons,
reason, associate emo3ons to sensory s3muli
– E. g. How to interpret sensory signals
• The brain stores knowledge even before making
experiences: it’s not a tabula rasa.
– Educa2on cannot be considered as the task of
filling a hollow box
9. b. Learning and development
• The brain at birth is s3ll immature: neurons are in place, basic
distant connec3ons between neurons are formed, but not the most
part of the neurons of the cortex
• From birth to the end of puberty, neural circuits are formed and
selected
– Development includes 3me window, or expects certain s3muli at specific
periods of the life of the animal in order to implement certain func3ons
• During development connec3ons are formed and tested (“fire
together‐wire together”): those connec3ons, which have a high
probability of being ac3vated simultaneously are consolidated,
those which have a low probability are discarded.
• AXer birth, this networking ac3vity is influenced by individual
experience of the environment and sensory signals
10. c. Learning (adult) = func3onal modifica3ons of
brain’s func3onal architecture
• Development and learning cross their paths, but aXer puberty neural
circuits and the structural architecture of the brain are (apparently)
mostly stabilized
• Adult learning: Func3onal modifica3ons
– strength of the connec3ons,
– efficacy of the connec3ons
• are the main mechanisms for the modifica3on of the func3onal
architecture of the brain
• Learning does not modify the architecture of the brain at a structural
level (mostly):
• it produces func3onal modifica3ons that affect the strength of the
connec3ons between neurons (synapses) = Func2onal plas2city
11. The role of experience
• In addic3on to gene3c mechanisms, the brain is
modified by experience
• Both
– At the level of epigenesis and development (see
effects of depriva3on)
– At the level of learning
• But with
– constraints to what can be learnt:
• certain mechanisms protect the brain from
adap3ng to any new informa3on coming from
the environment
13. Cri3cal (sensi3ve) periods for learning
• Cri3cal periods = 3me‐
window opportuni3es
• Development of vision
– Hubel & Wiesel, 1970:
monocular depriva3on
reduces the number of cells
responding to the ac3vity of
the deprived eye
– monocular depriva3on has
different effects at different
ages
• Development of language
14. The myth of the first three years
• The no3on of cri3cal periods has been
domina3ng the world of educa3on and has
given birth to myth of the first three years
• Bruer, 1997 describes this myth as a typical
case of bad transla3on from
neuroscien3fic data to educa3onal
applica3ons
• Bruer, 1997 cri3cizes the iden3fica3on of
learning with synaptogenesis:
– Different systems have different sensi3ve
periods, in the sense that they do not develop
at the same rate (including within the visual
system)
– Human cri3cal periods are not necessarily the
same as animals
– The brain is more plas2c than accorded
before
– Learning cannot be reduced to
synaptogenesis
15. general rule for neuroeduca3on
• Bruer has used the myth of the first
three years for showing that
neuroscience is s3ll a bridge too far
from educa3on, and can give rise to
neuromyths and misapplica3ons. So
pay aKen3on to:
• generaliza3on of considera3ons that
are extracted from
– Animal experiments
– Data on specific func3ons
• erroneous iden3fica3on of brain
mechanism and behavioral
phenomenon
– E.g., Iden3fica3on of learning with
synaptogenesis
16. From cri3cal periods to different forms
of plas3city
• (Greenough, Black & Wallace, 1987) have introduced the dis3nc3on between
two ways in which experience modifies the brain:
• Experience‐expectant plas2city:
– Selected by evolu3on
– Concerns sensory motor func3ons
– Allows to fine‐tune the sensory motor systems in rela3onship to the environment
– Through the selec2on of synapses that have been generated in excess
– Defines the s3muli that should be found in the environment for the func3on to develop in a
certain way
– Experiences are very general and concern s3muli, which are normally present in the
environment
• Experience‐dependent plas2city:
– Does not depend on mechanisms that have been selected by evolu3on according to a precise
3ming
– Evolu3on has selected a capacity to learn from experience in general
– Through the genera2on of synapses, and the modifica2on of the strength of the synapses
17. 3 mechanisms for func3onal and
structural plas3city
• Plas3city is the basis of learning from • « The most fascina3ng and important
experience property of mammalian brain is its
• 3 mechanisms: remarkable plas3city, which can be
– Synap3c plas3city = change in strength thought of as the ability of
or efficacy of synap3c transmission experience to modify neural circuitry
– Synaptogenesis & synap3c pruning and thereby to modify future
– Excitability proper3es of single neurons thought, behavior,
feeling.» (Malenka, 2002, p. 147)
• Synap3c plas3city can be transient
(short term phenomena such as
short‐term adapta3on to sensory
inputs) – depends on modula3on of
transmiKer release
• Or long las3ng: long‐term form of
memory
– LTP/LTD (long‐term poten3a3on/long‐
term depression) mechanisms
18. LTP
• LTP: repe33ve ac3va3on of excitatory synapses in the hyppocampus
causes an increase in synap3c strength that can last for hours
• LTP is hypothesized to be involved in the forma3on of memories and
more generally in informa3on storing, hence in learning in general,
because LTP and learning considered at the behavioral level share
some proper3es:
– LTP can be generated rapidly and is prolonged and strengthened by
repe33on
– It is input specific (it is elicited at the ac3vated synapses and not at adjacent
synapses of the same neuron)
– It’s long‐las3ng
• How? Modifica3on of dendri3c spines? Growth of spines? Genera3on of new
synapses as a consequence of the splinng or duplica3on of exis3ng spines?
• Incorpora3ng structural changes into the mechanisms of long‐term synap3c plas3city
provides means by which the ac3vity generated by experience can cause long‐las3ng
modifica3ons of neural circuitry
19. More “structural” plas3city
• “ Un3l rela3vely recently, it was widely assumed that, except for certain cases of response to brain
damage, the brain acquired all of the synapses it was going to have during development, and that
further plas3c change was probably accomplished through modifica3ons of the strength of
preexis3ng connec3ons.
• … it has now become quite clear that new connec3ons may arise as a result of differen3al housing
condi3ons and other manipula3ons throughout much, if not all, the life of the rat…
• There has not yet been a specific demonstra3on of what might be represented by the changes in
synap3c connec3ons brought about by differen3al environmental complexity, nor are the details
of the rela3onship between brain structure and behavioral performance.” (Greenough, Black &
Wallace, 1987, p. 547‐548)
• “However, there are a few excep3ons. Over the past years, evidence has become available that in
a few dis3nct brain region, parts of the hippocampus and the olfactory bulb neurons con3nue to
be generated throughout life, and these neurons form new connec3ons and become integrated in
exis3ng circuitry.”
• “Thus in these dis3nct areas of the brain, developmental processes persist throughout
life…” (Singer, 2008, p. 108)
20. Structural plas3city in the adult brain
• MRI of licensed London taxi drivers were analyzed and
compared with those of control subjects who did not drive
taxis.
• The posterior hippocampi of taxi drivers were significantly
larger rela3ve to those of control subjects.
• Hippocampal volume correlated with the amount of 3me
spent as a taxi driver (posi3vely in the posterior and
nega3vely in the anterior hippocampus).
• These data are in accordance with the idea that the posterior
hippocampus stores a spa3al representa3on of the
environment and can expand regionally to accommodate
elabora3on of this representa3on in people with a high
dependence on naviga3onal skills.
• It seems that there is a capacity for local plas3c change in
the structure of the healthy adult human brain in response
to environmental demands. (Maguire, et al.,2000)
22. The role of educa3on
• 3 possible views:
– One can learn everything, and learns it from scratch
– What we learn depends on past experiences and is
constructed star3ng from these experiences, but one can
learn everything
– The way brain has been shaped by selec3on strongly
constrains what can be learnt
• (Posner & Rothbart, 2007)
23. Can we learn anything? Constraints and biases
• Learning experiences sculpt the brain
and cons3tute a framework for future
learning
• E. g. According to Kuhl (2004) mother
language learning builds a mental filter
that limits second language learning
• the “cri3cal period” depends on
experience as much as 3me, and is a
process rather than a strictly 3med
window of opportunity that is opened
and closed by matura3on.
– (Bransford, et al, in Sawyer, 2009)
24. Can we learn anything? Evolu3on and selec3on
• «… I have oXen observed that educators hold an implicit model of brain as a
tabula rasa or blank slate (Pinker, 2002), ready to be filled through educa3on and
classroom prac3ce. In this view, the capacity of the human brain to be educated,
unique in the human kingdom, relies upon an extended range of cor3cal plas3city
unique to humans. The human brain would be special in its capacity to
accommodate an almost infinite range of new func3ons through learning.
• In this view, then, knowledge of the brain is of no help in designing educa3onal
policies.
• …. Much of current classroom content, so the reasoning goes, consists in recent
cultural inven3ons, such as the symbols we use in wri3ng or mathema3cs. Those
cultural tools are far too recent to have exerted any evolu3onary pressure on brain
evolu3on. … Thus, it is logically impossible that there exist dedicated brain
mechanisms evolved for reading or symbolic arithme3c. They have to be learned,
just like myriads of other facts and skills in geography, history, grammar,
philosophy … The fact that our children can learn those materials implies that the
brain is nothing but a powerful universal learning machine. » (Dehaene, in BaKro,
Fischer, & Léna, 2008, p. 233).
25. Biology and culture
• Implica3on of
the idea of
tabula rasa: each
learner is
radically
different from
other learners,
and the same
cerebral areas
can be affected
to different
func3ons
26. Neural recycling hypothesis
• “… Close examina3on of the func3ons of those brain areas in
evolu3on suggests a possible resolu3on of this paradox. It is not
the case that those areas acquire an en3rely dis3nct, culturally
arbitrary new func3on. Rather, they appear to possess, in other
primates, a prior func3on closely related to the one that they will
eventually have in humans. … rela3vely small changes may suffice
to adapt them to their new cultural domain.
• « neural recycling hypothesis », according to which the human
capacity for cultural learning relies on a process of pre‐emp3ng or
recycling pre‐exis3ng brain circuitry.
• In my opinion, this view implies that an understanding of the
child’s brain organiza3on is essen3al to educa3on.
27. Neural recycling & mathema3cs
• Arabic digits and verbal
numerals are culturally
arbitrary and specific to
humans
• the sense of numerical
quan3ty is not: it is
present in infants and
animals
• We learn to give meaning
to our symbols and
calcula3on by connec3ng
them to this pre‐exis3ng
quan3ty representa3on
28. Neural recycling & reading
• Visual cortex presents mechanisms for invariant shape recogni3on
• Visual cortex is connected with auditory and seman3c areas
• Visual cortex responds to T shapes, circles, superposed circles..
• Many of these shapes resemble to our leKers
• We do not need to create a reading area ex novo, but can preempt
other visual and auditory mechanisms
30. From theory to prac3ce
• How can we generate successful interven3ons for
promo3ng relevant learning ?
– How do we pass from theory to prac3ce?
– Which kind of theory and evidence do we need?
– What is relevant learning?
– Learning that is long‐las3ng and transferable
– How do we promote learning that is long‐las2ng and
transferable?
31. Plas3city in prac3ce
• “Learning and brain plas3city are fundamental
proper3es of the nervous system, and they hold
considerable promise when it comes to learning a
second language faster, maintaining our perceptual
and cogni3ve skills as we age, or recovering lost
func3ons aXer brain injury.
• Learning is cri3cally dependent on experience and the
environment that the learner has to face.
• … we are s2ll missing the recipe for successful brain
plas2city interven2on at the prac2cal
level.” (Bavelier, et al., in Gazzaniga, 2009, p. 153)
32. Training & Relevant learning
• In many cases, training produces
effects that cannot be considered
as relevant learning, because
(Bavelier, et al., in Gazzaniga, 2009,
p. 153):
– They are not long‐las2ng : an effect
on learning is not proved by
experiments that evaluate short‐
term effects (e.g.: violent effects of
violent video games)
– They are not sufficiently
generalized: an effect on learning
that is bound to the trained task is
barely interes3ng
– Other variables than the learning
experience produce an effect, but
are not controlled for and evaluated
34. Learning as reusable
• “Learning involves acquiring new informa3on • Learning is supposed to be re‐usable
and u2lizing it later when necessary. Thus, – An example: Imagine a motor therapy which
any kind of learning implies generaliza2on of induces the learning of new movements, but
the originally acquired informa3on: to new these movements can only be accomplished
occasions, new loca3ons, new objects, new in the therapy room
contexts, etc. However, any piece of new
informa3on that an organism perceives is
episodic and par3cular: it involves a single
3me, a specific loca3on and context, and
par3cular objects).” (Gergely & Csibra, 2009,
p. 3)
• “The ques3on of how one can learn (i.e.,
acquire general knowledge) from bits of
episodic informa3on is known as the
induc2on problem and has been tackled by
various theories of learning. These usually
rely on sta3s3cal procedures that involve
sampling mul3ple episodes of experience to
form the basis of generaliza3on to novel
instances.” (Gergely & Csibra, p. 3)
35. The neuromyth of the Mozart effect
• The Mozart effect
(Rauscher, Shaw, Ky, 1993)
– Effects of listening music on
spa3al reasoning (Stanford‐
Binet IQ test)
– Enhancement
– For 15 minutes
• a classic case of
performance enhancement
that is NOT a form of
learning, because it does
not last
• … and a classic neuromyth
– listening to Mozart increases
the IQ
37. Aggression and violent video games
• Violent video games
seem to produce
effects on
physiological
arousal, verbal
violence, but these
effects are only
tested few minutes
aXer the exposi3on
(Bavelier, et al., in
Gazzaniga, 2009, p.
154)
38. Transfer
• “In the field of learning, transfer of
learning from the trained task to even
other very similar task is generally the
excep3on rather than the rule.
• For instance, Pashler and Baylis (1991)
trained subjects to associate one of
three keys with visually presented
symbols (leX key = P or 2, middle key =
V or 8, right key = K or 7). Over the
course of mul3ple training blocks,
par3cipants reac3on 3me decreased
significantly. However, when new
symbols were added that needed to be
mapped to the same keys in addic3on
to the learned symbols … no evidence
of transfer was evident.” (Bavelier, et al.,
in Gazzaniga, 2009, p. 153‐154)
39. Methodological issues
• Studies on the effects of training on
learning should prove that the effects are
long‐las3ng and that there is a causal
rela3onship between the kind of training
and the learning effect (Bavelier, et al., in
Gazzaniga, 2009, p. 154‐155)
– The Hawthorne effect of learning:
mo3va3onal factors influence
performance, but they are not part of
the learning experience being
evaluated
– The popula3on effect: causal links are
not the same than correla3ons, since
correla3on could depend from
external factors