Cognitive Enhancement through Nicotine (12)
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The nicotinic cholinergic receptors (nAChRs) are better understood and more relevant to cognition, compared to the five muscarinic receptors. As with muscarine, the nicotinic cholinergic receptors were named because all seventeen of them respond to both acetylcholine and nicotine, a compound naturally found in the nightshade family of plants.
The understanding of nicotine’s (and thereby, the seventeen nAChRs’) impact on cognition began in the 1960’s and continued in the 1970’s with studies on rodents. By the early 1990’s, it was shown in animal models that nicotine had widespread effects on neurotransmitters. Through its effect on the nAChRs, it increased extracellular dopamine in the hippocampus, frontal cortex, cingulate cortex, and pontine nucleus, serotonin in the cingulate gyrus and frontal cortex, and norepinephrine (which may be more familiar as noradrenaline) in the substantia nigra, cingulate gyrus, and pontine nucleus.
While nicotine’s neuroprotective effect on dopaminergic neurons was first noticed in epidemiological studies from the 1970’s, its ability to improve cognition in Alzheimer’s disease patients was being studied in earnest by the late 1980’s. In humans, nicotine broadly improves attention and memory. It particularly improves cognitive performance in attention-demanding tasks, indicating that the nAChRs play an important role in sustained attention.
Interestingly, its effect on attention-demanding tasks follows a U-shaped curve, where too much and too little nicotine both result in inferior performance. While it was once hypothesized that nicotine only exerted benefits on cognition in an acute form, it was later shown that improvements in cognition for AD patients did not decline with chronic nicotine administration, meaning that a tolerance to nicotine either does not develop or does not impact its profound benefit on cognition.
NICOTINE MODULATES COGNITIVE NETWORKS
The Default Mode Network (DMN), once called the ‘task-negative network,’ is a set of brain loci where activity increases at rest and declines during externally driven tasks. It is the network of cognition that practitioners of mindful meditation seek to tame – the stream of consciousness that we experience throughout our lives. It is also the cognitive network found to have pathological function in sufferers of ADHD. The DMN has two cognitive hubs, namely, the anterior medial prefrontal cortex and the posterior cingulate cortex with the precuneus cortex.
In opposition to the DMN, the Central Executive Network (CEN), also called the cognitive or ‘executive control network,’ is a set of regions that are particularly active during external tasks of cognition. The CEN is believed to be involved in attention, working memory, and decision-making, and it has hubs in the dorsolateral prefrontal cortex (dlPFC) and the posterior parietal cortex. People with ADHD who improve their symptomatic condition are found to exhibit improvements in the integrity of their CENs.
There is an antagonistic relationship between these DMN and CEN. A third brain network, called the Salience Network (SN), monitors and responds to environmental stimuli, switching between the DMN and CEN as needed. It includes the amygdala, frontotemporal areas, and the anterior cingulate cortex (ACC).
Fascinatingly, the nicotinic cholinergic receptors have been shown to play a crucial role in the modulation of these cognitive networks. Studies have shown that nAChR agonists, such as nicotine and acetylcholine, decrease the activity of the DMN and increase activity of the CEN, potentially partially explaining the performance enhancing benefits of the agonists. These findings are particularly relevant for the mentally ill or depressed, who often exhibit an overactivity of the DMN and underactivity of the CEN, producing the ruminating behavior commonly exhibited among depressives.
To return to an overview of the blog series on the cholinergic system, click here.
 Oliverio, A. (1968). Recent Advances in Learning and Retention. Rome: Accademia Nazionale Dei Lincei. 346 pp.  Bovet-Nitti, F. (1969). Facilitation of simultaneous visual discrimination by nicotine in four “inbred” strains of mice. Psychopharmacologia, 14(3), 193-199.  McGaugh, J. L. (1973). Drug facilitation of learning and memory. Annual review of pharmacology, 13(1), 229-241.  Castellano, C. (1976). Effects of nicotine on discrimination learning, consolidation and learned behaviour in two inbred strains of mice. Psychopharmacology, 48(1), 37-43.  Toth, E., Sershen, H., Hashim, A., Vizi, E. S., & Lajtha, A. (1992). Effect of nicotine on extracellular levels of neurotransmitters assessed by microdialysis in various brain regions: role of glutamic acid. Neurochemical research, 17(3), 265-271.  KESSLER, I. I., & DIAMOND, E. L. (1971). Epidemiologic studies of Parkinson's disease: I. Smoking and Parkinson's disease: a survey and explanatory hypothesis. American journal of epidemiology, 94(1), 16-25.  Sahakian, B., Jones, G., Levy, R., Gray, J., & Warburton, D. A. V. I. D. (1989). The effects of nicotine on attention, information processing, and short-term memory in patients with dementia of the Alzheimer type. The British Journal of Psychiatry, 154(6), 797-800.  Heishman, S. J., Kleykamp, B. A., & Singleton, E. G. (2010). Meta-analysis of the acute effects of nicotine and smoking on human performance. Psychopharmacology, 210(4), 453-469.  Gandelman, J. A., Newhouse, P., & Taylor, W. D. (2018). Nicotine and networks: potential for enhancement of mood and cognition in late-life depression. Neuroscience & Biobehavioral Reviews, 84, 289-298.  White, H. K., & Levin, E. D. (2004). Chronic transdermal nicotine patch treatment effects on cognitive performance in age-associated memory impairment. Psychopharmacology, 171(4), 465-471.  Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001). A default mode of brain function. Proceedings of the National Academy of Sciences, 98(2), 676-682.  Kingsland, J. (2016). Siddhartha's brain: the science of meditation, mindfulness and enlightenment. Hachette UK.  Uddin, L. Q., Kelly, A. C., Biswal, B. B., Margulies, D. S., Shehzad, Z., Shaw, D., ... & Milham, M. P. (2008). Network homogeneity reveals decreased integrity of default-mode network in ADHD. Journal of neuroscience methods, 169(1), 249-254.  Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The brain's default network: anatomy, function, and relevance to disease.  Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., ... & Greicius, M. D. (2007). Dissociable intrinsic connectivity networks for salience processing and executive control. Journal of Neuroscience, 27(9), 2349-2356.  Francx, W., Oldehinkel, M., Oosterlaan, J., Heslenfeld, D., Hartman, C. A., Hoekstra, P. J., ... & Mennes, M. (2015). The executive control network and symptomatic improvement in attention-deficit/hyperactivity disorder. Cortex, 73, 62-72.  Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences, 102(27), 9673-9678.  Goulden, N., Khusnulina, A., Davis, N. J., Bracewell, R. M., Bokde, A. L., McNulty, J. P., & Mullins, P. G. (2014). The salience network is responsible for switching between the default mode network and the central executive network: replication from DCM. Neuroimage, 99, 180-190.  Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., ... & Greicius, M. D. (2007). Dissociable intrinsic connectivity networks for salience processing and executive control. Journal of Neuroscience, 27(9), 2349-2356.  Sutherland, M. T., Ray, K. L., Riedel, M. C., Yanes, J. A., Stein, E. A., & Laird, A. R. (2015). Neurobiological impact of nicotinic acetylcholine receptor agonists: an activation likelihood estimation meta-analysis of pharmacologic neuroimaging studies. Biological psychiatry, 78(10), 711-720.  Gandelman, J. A., Newhouse, P., & Taylor, W. D. (2018). Nicotine and networks: potential for enhancement of mood and cognition in late-life depression. Neuroscience & Biobehavioral Reviews, 84, 289-298.