Cognitive neuroscience

Cognitive neuroscience is an interdisciplinary area of study that has emerged from neuroscience and psychology. There are several stages in these disciplines that have changed the way researchers approached their investigations and that led to the field becoming fully established. Although the task of cognitive neuroscience is to describe the neural mechanisms associated with the mind, historically it has progressed by investigating how a certain area of the brain supports a given mental faculty. However, early efforts to subdivide the brain proved to be problematic. The phrenologist movement failed to supply a scientific basis for its theories and has since been rejected. The aggregate field view, meaning that all areas of the brain participated in all behavior, was also rejected as a result of brain mapping, which began with Hitzig and Fritsch's experiments and eventually developed through methods such as positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). Gestalt theory, neuropsychology, and the cognitive revolution were major turning points in the creation of cognitive neuroscience as a field, bringing together ideas and techniques that enabled researchers to make more links between behavior and its neural substrates. The connection between brain and behavior was first documented in the 16th century BC, in the Edwin Smith Papyrus of Ancient Egypt. While the Ancient Greeks Alcmaeon, Plato, Aristotle in the 5th and 4th centuries BC, and then the Roman physician Galen in the 2nd century AD already argued that the brain is the source of mental activity, scientific research into the connections between brain areas and cognitive functions began in the second half of the 19th century. The founding insights in the Cognitive neuroscience establishment were: • In 1848, Phineas Gage became a classic subject for studying the connection between the prefrontal cortex and behavior, decision-making, and consequences when an explosion accident pierced his brain with an iron rod. • In 1861, French neurologist Paul Broca discovered that a damaged area of the posterior inferior frontal gyrus (pars triangularis, BA45, also known as Broca's area) in patients caused an inability to speak. His work "Localization of Speech in the Third Left Frontal Cultivation" in 1865 inspired others to study brain regions linking them to sensory and motor functions. • In 1870, German physicians Eduard Hitzig and Gustav Fritsch stimulated the cerebral cortex of a dog with electricity, causing different muscles to contract depending on the areas of the brain involved. This led to the suggestion that individual functions are localized to specific areas of the brain. • In 1874, German neurologist and psychiatrist Carl Wernicke hypothesized an association between the left posterior section of the superior temporal gyrus and the reflexive mimicking of words and their syllables. Perhaps this was the first serious attempts to localize mental functions to specific locations in the brain. This was mostly achieved by studying the effects of injuries to different parts of the brain on psychological functions. The cases of Broca and Wernicke, which suggested that lesions caused specific behavioral changes, strongly supported the localizationist view. Additionally, Aphasia is a learning disorder which was also discovered by Paul Broca. According to, Johns Hopkins School of Medicine, Aphasia is a language disorder caused by damage in a specific area of the brain that controls language expression and comprehension. This can often lead to the person speaking words with no sense known as "word salad" • In 1878, Italian professor of pharmacology and physiology Angelo Mosso associated blood flow with brain functions. He invented the first neuroimaging technique, known as 'human circulation balance'. Angelo Mosso is a forerunner of more refined techniques like functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). • In 1887, Spanish neuroanatomist professor Santiago Ramón y Cajal (1852–1934) improved the Golgi's method of visualizing nervous tissue under light microscopy by using a technique he termed "double impregnation". He discovered a number of facts about the organization of the nervous system: the nerve cell as an independent cell, insights into degeneration and regeneration, and ideas on brain plasticity. • In 1894, neurologist and psychiatrist Edward Flatau published a human brain atlas “Atlas of the Human Brain and the Course of the Nerve-Fibres” which consisted of long-exposure photographs of fresh brain sections. It contained an overview of the knowledge of the time on the fibre pathways in the central nervous system. • In 1909, German anatomist Korbinian Brodmann published his original research on brain mapping in the monograph Vergleichende Lokalisationslehre der Großhirnrinde (Localisation in the cerebral cortex), defining 52 distinct regions of the cerebral cortex, known as Brodmann areas now, based on regional variations in structure. These Brodmann areas were associated with diverse functions including sensation, motor control, and cognition. • In 1924, German physiologist and psychiatrist Hans Berger (1873–1941) recorded the first human electroencephalogram EEG, discovering the electrical activity of the brain (called brain waves) and, in particular, the alpha wave rhythm, which is a type of brain wave. • A first clinical positron imaging device, a prototype of a modern Positron Emission Tomography (PET), was invented in 1953 by Dr. Brownell and Dr. Aronow. American scientists specializing in nuclear medicine David Edmund Kuhl, Luke Chapman and Roy Edwards developed this new method of tomographic imaging and constructed several tomographic instruments in the late 1950s. Ph.D. in Chemistry Michael E. Phelps was able to invent their insights into the first PET scanner in 1973. PET became a valuable research tool to study brain functioning. This technique can indirectly measure radioactivity signal that indicates increased blood flow associated with increased brain activity. • In 1971, American chemist and physicist Paul Christian Lauterbur invented the idea of MR imaging (MRI). In 2003, he received the Nobel Prize. MRI is the investigative tool for contrasting grey and white matter, which makes MRI the choice to study many conditions of the central nervous system. This method contributed to the development of Functional Magnetic Resonance Imaging (fMRI), which has been used in many studies in cognitive neuroscience since 1990s. ==Notable perspectives==

Localizationist view The localizationist view was concerned with mental abilities being localized to specific areas of the brain rather than on what the characteristics of the abilities were and how to measure them. Studies performed in Europe, such as those of John Hughlings Jackson, supported this view. Jackson studied patients with brain damage, particularly those with epilepsy. He discovered that the epileptic patients often made the same clonic and tonic movements of muscle during their seizures, leading Jackson to believe that they must be caused by activity in the same place in the brain every time. Jackson proposed that specific functions were localized to specific areas of the brain, which was critical to future understanding of the brain lobes. Aggregate field view According to the aggregate field view, all areas of the brain participate in every mental function. His approach has been criticised on the basis that the tests were not sensitive enough to notice selective deficits had they been present. Mapping the brain In 1870, German physicians Eduard Hitzig and Gustav Fritsch published their findings of the behavior of animals. Hitzig and Fritsch ran an electric current through the cerebral cortex of a dog, causing different muscles to contract depending on which areas of the brain were electrically stimulated. This led to the proposition that individual functions are localized to specific areas of the brain rather than the cerebrum as a whole, as the aggregate field view suggests. The brain is also divided into fissures and sulci. The lateral sulcus called the Sylvian Fissure separates the frontal and temporal lobes. The insula is described as being deep to this lateral fissure. The longitudinal fissure separates the lobes of the brain length-wise. Lobes are considered to be distinct in their distribution of vessels. Neuron doctrine In the early 20th century, Santiago Ramón y Cajal and Camillo Golgi began working on the structure of the neuron. Golgi developed a silver staining method that could entirely stain several cells in a particular area, leading him to believe that neurons were directly connected with each other in one cytoplasm. Cajal challenged this view after staining areas of the brain that had less myelin and discovering that neurons were discrete cells. Cajal also discovered that cells transmit electrical signals down the neuron in one direction only. Both Golgi and Cajal were awarded a Nobel Prize in Physiology or Medicine in 1906 for this work on the neuron doctrine. == Notable experiments ==

Throughout the history of cognitive neuroscience, many notable experiments have been conducted. For example, the mental rotation experiment conducted by Kosslyn et al., 1993, indicated that the time it takes to mentally rotate an object via imagination takes the same amount of time as actually rotating it; they found that mentally rotating an object activates parts of the brain involved in motor functioning, which may explain this similarity. They define bottom-up attention is the brain visually processing salient images first, and then the surrounding information, while top-down attention involves focusing on task-relevant objects first. The researchers found that the ventral stream focuses on visual recognition, the dorsal stream is involved in the spatial information concerning the object. As experiments in cognitive neuroscience, what these have in common is that the researchers are measuring activities or behaviors that we can see, and then determining the neural basis of the function and what part of the brain is involved. ==Emergence of a new discipline==

Birth of cognitive science On September 11, 1956, a large-scale meeting of cognitivists took place at the Massachusetts Institute of Technology. George A. Miller presented his "The Magical Number Seven, Plus or Minus Two" paper while Noam Chomsky and Newell & Simon presented their findings on computer science. Ulric Neisser commented on many of the findings at this meeting in his 1967 book Cognitive Psychology. The term "psychology" had been waning in the 1950s and 1960s, causing the field to be referred to as "cognitive science". Behaviorists such as Miller began to focus on the representation of language rather than general behavior. David Marr concluded that one should understand any cognitive process at three levels of analysis. These levels include computational, algorithmic/representational, and physical levels of analysis. Combining neuroscience and cognitive science Before the 1980s, interaction between neuroscience and cognitive science was scarce. Cognitive neuroscience began to integrate the newly laid theoretical ground in cognitive science, that emerged between the 1950s and 1960s, with approaches in experimental psychology, neuropsychology and neuroscience. (Neuroscience was not established as a unified discipline until 1971). In the late 1970s, neuroscientist Michael S. Gazzaniga and cognitive psychologist George A. Miller were said to have first coined the term "cognitive neuroscience." In the very late 20th century new technologies evolved that are now the mainstay of the methodology of cognitive neuroscience, including TMS (1985) and fMRI (1991). Earlier methods used in cognitive neuroscience include EEG (human EEG 1920) and MEG (1968). Occasionally cognitive neuroscientists utilize other brain imaging methods such as PET and SPECT. An upcoming technique in neuroscience is NIRS which uses light absorption to calculate changes in oxy- and deoxyhemoglobin in cortical areas. In some animals Single-unit recording can be used. Other methods include microneurography, facial EMG, and eye tracking. Integrative neuroscience attempts to consolidate data in databases, and form unified descriptive models from various fields and scales: biology, psychology, anatomy, and clinical practice. Adaptive resonance theory (ART) is a cognitive neuroscience theory developed by Gail Carpenter and Stephen Grossberg in the late 1970s on aspects of how the brain processes information. It describes a number of artificial neural network models which use supervised and unsupervised learning methods, and address problems such as pattern recognition and prediction. In 2014, Stanislas Dehaene, Giacomo Rizzolatti and Trevor Robbins, were awarded the Brain Prize "for their pioneering research on higher brain mechanisms underpinning such complex human functions as literacy, numeracy, motivated behaviour and social cognition, and for their efforts to understand cognitive and behavioural disorders". Brenda Milner, Marcus Raichle and John O'Keefe received the Kavli Prize in Neuroscience "for the discovery of specialized brain networks for memory and cognition" and O'Keefe shared the Nobel Prize in Physiology or Medicine in the same year with May-Britt Moser and Edvard Moser "for their discoveries of cells that constitute a positioning system in the brain". In 2017, Wolfram Schultz, Peter Dayan and Ray Dolan were awarded the Brain Prize "for their multidisciplinary analysis of brain mechanisms that link learning to reward, which has far-reaching implications for the understanding of human behaviour, including disorders of decision-making in conditions such as gambling, drug addiction, compulsive behaviour and schizophrenia"., ==Recent trends==

Recently the focus of research had expanded from the localization of brain area(s) for specific functions in the adult brain using a single technology. Studies have been diverging in several different directions: exploring the interactions between different brain areas, using multiple technologies and approaches to understand brain functions, and using computational approaches. Advances in non-invasive functional neuroimaging and associated data analysis methods have also made it possible to use highly naturalistic stimuli and tasks such as feature films depicting social interactions in cognitive neuroscience studies. In recent years, there have been a lot of new advancements in the field of Cognitive Neuroscience. One new technique that has emerged is called shadow imaging. This method has combined different aspects of various neuroimaging techniques to create one that is more versatile. It uses standard light microscopy and melds it with fluorescence labeling of the interstitial fluid in the brain's extracellular space. This technique can help researchers get a bigger and more detailed look at brain tissue. This can help researchers understand more on anatomy and viability for their experiments. This technique has helped to see neurons, microglia, tumor cells and blood capillaries more closely. Shadow imaging is a new approach that shows a lot of promise in the field of neuroimaging. Another very recent trend in cognitive neuroscience is the use of optogenetics to explore circuit function and its behavioral consequences. This new technology is a combination of genetic targeting of certain neurons and using the imaging technology to see targets in living neurons. This technique allows scientists to see the neurons while they are still intact in animals and be able to trace the electrical happenings in that cell. This new technology has been used successfully in many experiments and it is helping researchers in observing brain activity and understanding its role in disease, behavior and function. Researchers have also modified a fMRI and made it more efficient, in a technique called direct imaging of neuronal activity or DIANA. This group of researchers changed the software to collect data every 5 milliseconds, which is 8 times faster than what the normal technique captures. After, the software can stitch together all of the images taken during the imaging and create a full slice of the brain. In 2024, Prof. in bioengineering Igor Val Danilov introduced the natural neurostimulation hypothesis that explains the neuromodulation mechanism during pregnancy. Because the natural neurostimulation contributes to developing the healthy nervous system during pregnancy, artificial neurostimulation with the physical characteristics of a mother's care for her fetus scaled to the parameters of the specific patient can treat the injured nervous system. Basing on this insight, the novel APIN neurostimulation technique was introduced. The APIN technique exerts its neurotherapeutic effect by inducing mitochondrial stress and microvascular vasodilation of the specific neuronal circuits during an intensive cognitive load. Deep learning, a subfield of AI, uses neural networks to replicate processes similar to those in the human brain. For instance, convolutional neural networks (CNNs) are modeled after the visual system and have transformed tasks like image recognition and speech analysis. AI also benefits from advancements in brain imaging technologies, such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). These tools provide valuable insights into neural activity, which help improve AI systems designed to mimic human thought processes. Despite the progress, replicating the complexity of human cognition remains a challenge. Researchers are now exploring hybrid models that combine neural networks with symbolic reasoning to better mimic how humans think and solve problems. This approach shows promise for addressing some of the limitations of current AI systems. ==Topics==

• Attention • Cognitive development • Consciousness • Creativity • Decision-making • Emotions • Intelligence • Language • Learning • Memory • Perception • Social cognition • Mind Wandering ==Methods==

Experimental methods include: • Psychophysics • Eye-tracking • Functional magnetic resonance imaging • Electroencephalography • Magnetoencephalography • Electrocorticography • Transcranial Magnetic Stimulation • Computational Modeling ==Notable people==

• Jesper Mogensen, Danish neuroscientist and former university professor • Brenda Milner, Canadian neuropsychologist and pioneer of memory research • May-Britt Moser, Norwegian neuroscientist and Nobel Prize winner • Gail Carpenter, American cognitive neuroscientist and mathematician • Karl Friston, British neuroscientist and Fellow of the Royal Society ==See also==