Editing Cognitive neuroscience (section)

==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.<ref>{{cite web|last=Takeo|first=Watanabe|title=Cognitive neuroscience Editorial overview|url=http://people.bu.edu/takeo/takeo/Editorial%20(Current%20Opinion).pdf|access-date=2011-12-01|archive-url=https://web.archive.org/web/20121224221332/http://people.bu.edu/takeo/takeo/Editorial%20(Current%20Opinion).pdf|archive-date=2012-12-24|url-status=dead}}</ref> 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.<ref>{{cite journal|last=Hasson|first=Uri|title=Intersubject Synchronization of Cortical Activity During Natural Vision |journal=Science|volume=303|issue=5664|pages=1634–1640|display-authors=etal|doi=10.1126/science.1089506|pmid=15016991|year=2004|bibcode=2004Sci...303.1634H }}</ref>

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.<ref>{{cite journal |last1=Dembitskaya |first1=Yulia |last2=Boyce |first2=Andrew K. J. |last3=Idziak |first3=Agata |last4=Pourkhalili Langeroudi |first4=Atefeh |last5=Arizono |first5=Misa |last6=Girard |first6=Jordan |last7=Le Bourdellès |first7=Guillaume |last8=Ducros |first8=Mathieu |last9=Sato-Fitoussi |first9=Marie |last10=Ochoa de Amezaga |first10=Amaia |last11=Oizel |first11=Kristell |last12=Bancelin |first12=Stephane |last13=Mercier |first13=Luc |last14=Pfeiffer |first14=Thomas |last15=Thompson |first15=Roger J. |last16=Kim |first16=Sun Kwang |last17=Bikfalvi |first17=Andreas |last18=Nägerl |first18=U. Valentin |title=Shadow imaging for panoptical visualization of brain tissue in vivo |journal=Nature Communications |date=12 October 2023 |volume=14 |issue=1 |page=6411 |doi=10.1038/s41467-023-42055-2 |pmid=37828018 |pmc=10570379 |bibcode=2023NatCo..14.6411D }}</ref>

Another very recent trend in cognitive neuroscience is the use of [[optogenetics]] to explore circuit function and its behavioral consequences.<ref>{{cite journal |last1=Pama |first1=E. A. Claudia |last2=Colzato |first2=Lorenza S. |last3=Hommel |first3=Bernhard |date=6 September 2013 |title=Optogenetics as a neuromodulation tool in cognitive neuroscience |journal=Frontiers in Psychology |volume=4 |page=610 |doi=10.3389/fpsyg.2013.00610 |pmc=3764402 |pmid=24046763 |doi-access=free}}</ref> 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.<ref>{{cite journal |last1=Deisseroth |first1=Karl |last2=Feng |first2=Guoping |last3=Majewska |first3=Ania K. |last4=Miesenböck |first4=Gero |last5=Ting |first5=Alice |last6=Schnitzer |first6=Mark J. |title=Next-Generation Optical Technologies for Illuminating Genetically Targeted Brain Circuits |journal=The Journal of Neuroscience |date=11 October 2006 |volume=26 |issue=41 |pages=10380–10386 |doi=10.1523/JNEUROSCI.3863-06.2006 |pmid=17035522 |pmc=2820367 }}</ref>

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.<ref>{{cite journal |last1=Prillaman |first1=McKenzie |title=Faster MRI scan captures brain activity in mice |journal=Nature |date=13 October 2022 |doi=10.1038/d41586-022-03276-5 |pmid=36229690 }}</ref>

In 2024, Prof. in bioengineering at RTU Liepaja Academy Igor Val Danilov introduced the natural neurostimulation hypothesis that explains the neuromodulation mechanism during pregnancy.<ref name="Val Danilov Origin Neurostimulation_2024">{{cite journal |last1=Val Danilov |first1=Igor |title=The Origin of Natural Neurostimulation: A Narrative Review of Noninvasive Brain Stimulation Techniques |journal=OBM Neurobiology |date=29 November 2024 |volume=08 |issue=4 |pages=1–23 |doi=10.21926/obm.neurobiol.2404260 |doi-access=free }}</ref> 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.<ref name="Val Danilov Origin Neurostimulation_2024" /><ref name="Val et al 2025">{{cite journal |last1=Val Danilov |first1=Igor |last2=Medne |first2=Dace |last3=Mihailova |first3=Sandra |title=Modulating neuroplasticity with acoustic photonic intellectual neurostimulation (APIN): a case study on neurodegenerative disorder |journal=Brain Stimulation |date=January 2025 |volume=18 |issue=1 |pages=561 |doi=10.1016/j.brs.2024.12.1005 |doi-access=free }}</ref><ref name="Mihailova et al 2025">{{cite journal |last1=Mihailova |first1=Sandra |last2=Medne |first2=Dace |last3=Val Danilov |first3=Igor |title=Acoustic photonic intellectual neurostimulation (APIN) in dysmenorrhea management: a case study on an adolescent |journal=Brain Stimulation |date=January 2025 |volume=18 |issue=1 |pages=510 |doi=10.1016/j.brs.2024.12.860 |doi-access=free }}</ref><ref name="Medne et al 2025">{{cite journal |last1=Medne |first1=Dace |last2=Val Danilov |first2=Igor |last3=Mihailova |first3=Sandra |title=The effect of acoustic and photonic intervention combined with mental load on chronic headaches: a case study |journal=Brain Stimulation |date=January 2025 |volume=18 |issue=1 |pages=542–543 |doi=10.1016/j.brs.2024.12.955 |doi-access=free }}</ref> The APIN technique exerts its neurotherapeutic effect by inducing mitochondrial stress and microvascular vasodilation of the specific neuronal circuits during an intensive cognitive load.<ref name="Val et al 2025" /><ref name="Mihailova et al 2025" /><ref name="Medne et al 2025" />

=== Cognitive Neuroscience and Artificial Intelligence ===
{{Main|Artificial Intelligence}}
Cognitive neuroscience has played a major role in shaping [[Artificial intelligence in healthcare|artificial intelligence]] (AI). By studying how the human brain processes information, researchers have developed AI systems that simulate cognitive functions like learning, pattern recognition, and decision-making. A good example of this is neural networks, which are inspired by the connections between neurons in the brain. These networks form the foundation of many AI applications.<ref>{{cite journal |last1=LeCun |first1=Yann |last2=Bengio |first2=Yoshua |last3=Hinton |first3=Geoffrey |title=Deep learning |journal=Nature |date=28 May 2015 |volume=521 |issue=7553 |pages=436–444 |doi=10.1038/nature14539 |pmid=26017442 |bibcode=2015Natur.521..436L }}</ref>

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.<ref>{{Cite journal |last1=Lake |first1=Brenden M. |last2=Ullman |first2=Tomer D. |last3=Tenenbaum |first3=Joshua B. |last4=Gershman |first4=Samuel J. |date=2017 |title=Building machines that learn and think like people |journal=Behavioral and Brain Sciences |language=en |volume=40 |pages=e253 |doi=10.1017/S0140525X16001837 |pmid=27881212 |arxiv=1604.00289 }}</ref>

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.<ref>{{cite journal |last1=Langley |first1=Christelle |last2=Cirstea |first2=Bogdan Ionut |last3=Cuzzolin |first3=Fabio |last4=Sahakian |first4=Barbara J. |title=Theory of Mind and Preference Learning at the Interface of Cognitive Science, Neuroscience, and AI: A Review |journal=Frontiers in Artificial Intelligence |date=5 April 2022 |volume=5 |doi=10.3389/frai.2022.778852 |doi-access=free |pmc=9038841 |pmid=35493614 }}</ref>

=== Cognitive Neuroscience and Neurotherapy ===
{{Main|Neurotherapy}}
Cognitive neuroscience contributed to development of novel [[Non-invasive procedure|noninvasive]] [[neurostimulation]] methods and developed in parallel with [[Neurotherapy]] aimed to address symptom control and cure several conditions in medical treatment.<ref name="Chapin, Russell-Chapin_2013">Chapin, T.J.; Russell-Chapin, L.A. (2013). "Neurotherapy and: Brain-based treatment for psychological and behavioral problems". ''Routledge''; 2013 Dec 4. </ref> Noninvasive neurotherapy have attracted significant attention from the scientific community since, these methods can be personalized and used in treatment independent of underlying conditions.<ref name="Val Danilov Origin Neurostimulation_2024" /> Based on research in cognitive neuroscience, Neurostimulation techniques apply different innovations to exert an energy-based impact on the nervous system by using [[Electrical energy|electrical]], [[Magnetic energy|magnetic]], and/or [[electromagnetic energy]] to treat mental and physical health disorders in patients.<ref name="Chapin, Russell-Chapin_2013" /><ref name="Val Danilov Origin Neurostimulation_2024" /> Since Neurotherapy aims to heal without harm and implements systemic targeted delivery of an [[Energy|energy stimulus]] to a specific neurological zone in the body to alter neuronal activity and stimulate [[neuroplasticity]], the recent trend in the Cognitive neuroscience is the research of natural neurostimulation.<ref name="Val Danilov Origin Neurostimulation_2024" />