Drugs in theory, there are a lot of drug classes that are easy to make: To this end, more research could be done on any chemical that can either make or break the action of a target protein. The difficult part is finding a chemical that is receptor-specific (safe to consume or dirty drug). In the Physicians' desk reference, the number of prescription drugs listed in 2005 is twice as high as it was in the 1990 edition. "Selective serotonin reuptake inhibitors," or SSRIs, are examples of modern pharmaceuticals, and many people are already familiar with them. Antidepressants like Paxil and Prozac, which are examples of SSRIs, prolong synapse activity by primarily and selectively inhibiting serotonin transport. One of many categories of selective drugs is transport blockage's mode of action. The FDA has granted approval to medications like antidepressants with NE reuptake inhibitors, antipsychotics with DA blockers, and GABA agonist tranquilizers (benzodiazepines) that selectively affect all of the major neurotransmitters. New endogenous chemicals are discovered each day both the drugs THC (cannabis) and GHB, as well as the endogenous transmitters anandamide and GHB have been found to have specific receptors. The next step is the development of drugs and other specific agents that are specific to receptor subtypes. Major pharmaceutical companies are currently putting a lot of effort into developing these drugs and agents. A model is the push for improved anti-anxiety medications (anxiolytics) in light of CRF1 antagonists. Another is the idea of starting new research into antipsychotics like glycine reuptake inhibitors. Despite the fact that medications that are receptor-explicit can be used, medication treatment lacks the ability to provide physical specificity. Strange behavior can be triggered in various parts of the mind as a result of the same kind of receptor changes in one part of the brain by changing how receptors work in that part of the brain. Examples include D2 altering drugs (neuroleptics), which act on motor cortex to help schizophrenia but also cause a variety of dyskinesias.

The population model of neural networks is the result of the ability of mean-field theory to sometimes simplify the intricate interactions that take place between excitatory and inhibitory neurons. Some neurotheorists argue that in order to discover structural-functional relationships, it is necessary to include as much neuronal and network structure as possible, whereas others favor models with less complexity. Typically, large simulation platforms like GENESIS or NEURON are used to create this type of model. Identification, categorization, and visual attention Visual attention is a collection of mechanisms that restrict some processing to a small number of incoming stimuli. What we see and what we can do is shaped by our attentional mechanisms. There have been some attempts to provide unified approaches that integrate and bridge these complexity levels. They make it possible to select some (preferably relevant) information while simultaneously inhibiting other information. In order to have a more concrete description of the mechanism underlying visual attention and the binding of features, a number of computational models that aim to explain psychophysical findings have been proposed. An example of a theory that is being extensively tested on a behavioral and physiological level is the V1 saliency hypothesis, which asserts that a bottom-up saliency map is created in the primary visual cortex to direct attention from an external source. Computational neuroscience makes it possible to fully simulate and predict neuropsychological syndromes and provides a mathematical framework for studying the mechanisms underlying brain function. In general, all models assume that a saliency or priority map exists for registering the retinal input's potentially interesting areas. Computational modeling of higher cognitive processes, including learning, cognition, and discrimination, has only recently begun. The single-unit recording of primates serves as the primary source of experimental data. The frontal and parietal lobes are responsible for integrating information from various sensory modalities. There are some tentative ideas regarding how straightforward mutually inhibitory functional circuits in these areas may carry out computation that is relevant to biology because the brain appears to be particularly adept at discrimination and adaptation in certain contexts. People appear to have a remarkable capacity for recalling and recognizing faces, for instance. One of the primary goals of computational neuroscience is to examine how biological systems effectively perform these complex computations and possibly replicate these processes for the construction of intelligent machines. Numerous disciplines, including clinical practice, psychology, and biology, shed light on the brain's fundamental organizational principles on a grand scale. Integrative neuroscience aims to consolidate these observations by means of unified descriptive models and behavioral measure and recording database databases. Another attempt to model human cognition is the Computational Representational Understanding of Mind (CRUM), which simulates processes like the use of acquired rule-based systems in decision making and visual representations in decision making. Some quantitative models of brain activity on a large scale are based on these. One of psychology and neuroscience's ultimate goals is to comprehend conscious life's everyday experience. Experts in neuroscience, neurology, psychiatry, decision sciences, and computational modeling work together in the field of computational clinical neuroscience to quantitatively define and investigate issues in neurological and psychiatric diseases, as well as to train scientists and clinicians who want to use these models in diagnosis and treatment. Experts in machine learning, neuroscience, neurology, psychiatry, and psychology collaborate in the new emerging field of computational psychiatry to better comprehend psychiatric disorders.

With Regards,
Joseph Kent
Journal Manager
Journal of Brain, Behaviour & Cognitive Sciences