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|Year : 2018 | Volume
| Issue : 6 | Page : 299--301
Connectomics: A pharmacologic viewpoint
Dibbanti Harikrishnareddy, Manisha Prajapat, Subodh Kumar, Ajay Prakash, Bikash Medhi
Department of Pharmacology, PGIMER, Chandigarh, India
Dr. Bikash Medhi
Department of Pharmacology, PGIMER, Chandigarh - 160 012
|How to cite this article:|
Harikrishnareddy D, Prajapat M, Kumar S, Prakash A, Medhi B. Connectomics: A pharmacologic viewpoint.Indian J Pharmacol 2018;50:299-301
|How to cite this URL:|
Harikrishnareddy D, Prajapat M, Kumar S, Prakash A, Medhi B. Connectomics: A pharmacologic viewpoint. Indian J Pharmacol [serial online] 2018 [cited 2023 Mar 31 ];50:299-301
Available from: https://www.ijp-online.com/text.asp?2018/50/6/299/250585
Drug discovery process in medicine, biotechnology and pharmacology, takes a huge time and resource. Therefore, nowadays, several “omics” helps the drug discovery process short and specific so that this process gets quicker for the translational value and society may get benefited namely genomics, proteomics, metabolomics, and other advanced techniques. However, neuroscientists are continuous in search of new scope to discover new drugs for neurological disorders. “Connectomics” as a new scope to the neuroscientist gives an option to understand the “Brain Connections,” including branches of the neurons and their beautiful interconnection. Connectomics is the field of neuroscience studying comprehensive mapping of extraordinary complex and highly organized networks of neurons at cellular and synaptic level. This field began in the 1970s with mapping of the entire nervous system of tiny roundworm Caenorhabditis elegans. Using powerful microscopes, scientists created wiring diagram of 302 neurons with 7000 synapses/connections between neurons of C. elegans. In the late 1980s, scientists published the entire connectome diagram of C. elegans.,
Contextual of Neuroscience
If we see history, 1700 BC documents on neuroscience dating stated that Egyptians had knowledge on signs and symptoms of some of the brain disorders. Studies on brain became enlarged in the late 18th century after invention of microscope and development of staining techniques to stain brain cells. During the 19th century, neuroscientists pioneered in conducting live experiments in animals to study the behavior and loss of functionality of particular organ due to localized lesions in certain areas of the brain. The principle of “neuron doctrine” was formed in this period which hypothesized that neuron is the functional unit of the brain. Neuroscience got distinct academic status in the 20th century and recognized as a separate academic specialization. Hodgkin–Huxley model for transmission of electrical signals, generation, and propagation of action potential was also established in this period. The 21st century is the golden era for neuroscience; extensive studies on understanding the brain connections known as connectomics became glorified.
In human body, nervous system is the most complex system with brain, spinal cord, and peripheral nerves. Brain is the most complex organ and is the key to evolutionary success of humans and which makes us distinct from other species. It is made up of around one hundred billion neurons with more than one hundred trillion synapses and a very complex wiring which helps in exchange of information among different brain areas. This remarkable feature is one of the main reasons for difficulty in understanding the structure of nervous system unlike other organ systems., Therefore, the need of Neuroscience originated which deals with scientifically studying and understanding nervous system. Today, neuroscience is a discipline which seems to be focal point, where all disciplines of biological sciences converge in and diverge out with innovations. The current status of neuroscience became broaden by collaborating with other allied fields such as cognitive sciences, computational neuroscience, neuroinformatics, neuro-robotics, developmental neuroscience, neuroanatomy, neuromorphic computing, neuro-imaging, systems neuroscience, and other interdisciplinary fields such as physics, chemistry, engineering, and computer science.
Nervous system occupies the first place, which associated with long list of incurable diseases. Till today, there are many nervous system illnesses without known cause and even know which part of the nervous system got affected? Knowing what can go wrong with different nervous illnesses is primary approach to find the solution for treatment. Neuro-anatomic methods cannot be able to scale up the complex networking and pattern of neural connectivity. Now, neuroscientists are interested in how different parts of the brain are connected and how information gets stored in the brain. Connectomics is such a beautiful platform which can help in better understanding of structural and functional connectivity of the brain.
Connectomics, the Connections of the Brain
Development of new technology brings novel and big connectome data into neuroscience which provides us clear picture of structural organization of the nervous system and its functions. It also wipes off the poorly understood aspects of connections of the neurons. Neuroscientists are showing keen interest in how memories are physically stored in brain? How brain connectivity will change with age? How behavior and cognition vary from person to person? How the connectivity of psychiatric patients differs from normal? How healthy brain works and how to fix when it can go wrong? Connectomics is such an interesting area which helps in resolving this long list of questions. Collection of big data of brain connectome is easy, but analyzing the data to answer specific question is challenging. There are still many other challenges in neuronal mapping and analysis of brain connectivity. Some of the potential challenges that may encounter in connectome data acquisition and processing are:
Connectomics is a nascent field; the central aim and collection of which data will be most beneficial were still uncertainAlignment of sections of brain images in sequential order is difficultNeurons and their processes (axons and dendrites) are intertwined in three dimensions, so reconstruction of cellular processes of one section to other is challengingDetection of cellular structure such as mitochondria and synaptic specializations is toughReconstruction of neuronal networks into the graphical representation (wiring diagram) is puzzlingThe rate of data generation (speed of image acquisition) is very slowAnalysis of digital information and computation is complexStorage of such a big data is challenging.
Even though there are many limitations, mapping of brain has commercial value such as it will help as biological basis of identity of individual, differentiation of male and female brain, prediction of the clinical expression of disease (diagnosis), and treating brain disorders. Till today, there are many diseases associated with nervous system such as psychiatric disorders, autistic spectrum disorders, migraine, learning-associated disorders, eating disorders, and addiction, which do not have even proper diagnostic tests and even do not know what can go wrong in this disorders. Scientists argue that even though there are restrictions, connectome data will help in revealing many essential characteristics of neural circuits which helps in diagnosis and treatment of such a long list of nervous system illnesses. Imminent motto of connectomics research is to understand how brain connectivity differs in different neurological disorders and how brain operates in diseased patients and healthy individuals. Farfetched technologies are advancing day by day which make studying connectome easy and sort it as future of neuroscience. Blooming connectomics will help in understanding whom we are and what deviations are found in different neurological disorders.
Connectomics in Pharmacology
Connectomics can be utilized to analyze functional magnetic resonance imaging (fMRI), diffusion tensor imaging, magnetoencephalography (MEG), and electroencephalography (EEG) data. Therefore, brain connectomics, which based on the remarkable research progress of these imaging technologies, would show broad prospects.
fMRI is a widely used technique in connectomics analysis. In a study by Dandash et al., 2018, disturbance in functional connectomics is evident in mood disturbance associated with mania. Compared to healthy controls, patients with the first episode of mania showed reduced connectivity in corticostriatal systems in fMRI and increased connectivity in a circuit linking the ventral striatal system, cerebellum, and thalamus. Lithium and quetiapine normalized these abnormal increased connectivities at 3 and 12 months of follow-up. Action of lithium was noted to be more rapid compared to quetiapine. Dopamine is widely implicated in molecular pathways affecting cognition, but the mechanism of this large-scale modulation of cognition by dopamine is still unknown. Using a connectomics-based approach, Alavash et al., 2018 found that enhanced dopaminergic signaling modulates the two potentially interrelated aspects of large-scale cortical dynamics during cognitive performance and the degree of these modulations is able to explain inter-individual differences in l-dopa-induced behavioral benefits and thus established the dynamic role of dopamine in maintaining communication between cortical systems at connectomics level and the degree of these inter-individual differences could explain the inter-individual difference in response to levodopa. Liu et al., 2017 evaluated the effects of propofol on brain connectomes.
Another widely used technique is EEG connectomics. EEG connectomics is also widely used in the evaluation of different neuropharmacological agents. EEG parameters such as oscillation and amplitude are used as potential biomarkers for drug response. Researcher gets out that in the resting stage (persons do not do any brain-related task) of EEG, when increased, the percentage of theta power is correlated with depressive symptom of person. EEG checks the neuronal activity of brain; therefore, EEG and clinical symptom make relationship to predict the drug effect.
EEG and MEG give good temporal resolution as compared to fMRI. Quantitative techniques based on EEG measures can be used as biomarkers. EEG biomarkers are comparable to Alzheimer's disease (AD) severity. Theta power exhibits a correlation with AD. Further study says that QEED is a clinical method which is used to convert the electrical signals of brain into digital form. The delta bend power percentage of QEED is also used as an indicator because EEG pattern can be influenced by ketamine which acts as a biomarker to help in the treatment of refractory status epilepticus patients. Levetiracetam shows the cognitive effect in epilepsy patients which is evaluated by EEG frequency and observe the depth of anesthesia.
Consequently, connectomics-based approach is being widely incorporated in both basic research as well as evaluation of efficacy and safety of drugs.
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