1. Rats learn rules and apply them to novel situations
The ability to generalize rules learned from specific experiences intuitively appears to be an advanced cognitive function. Language provides examples of such rule learning. The order of words in a sentence is important in most languages, and the rule is generalized according to categories (verb, noun, adjective). A recent study by Murphy et al [2] demonstrates a fundamentally similar ability in rats. The animals were trained to respond to a 3-element sequence of stimuli (ABA, BAB, etc). Only one sequence was associated with getting food. Rats that anticipated food put their heads in the tray where the food was delivered. The first experiment used visual stimuli—bright light and darkness episodes on the background of dim light. Only one pattern (light-dark-light) resulted in a reward. The rats learned the sequence and had an anticipatory response to it. For example, 2 periods of light and then darkness would not elicit anticipatory behavior. In the second experiment, the authors applied an auditory stimulus, consisting of pure tones of different frequencies. The tones were applied either using the same or a different sequence as in the visual experiment. The rats demonstrated significantly more anticipatory behavior when the auditory stimuli were in the same sequence as the light stimuli on which they were trained previously. The study shows that rats can learn simple rules and apply them to novel stimuli. Instead of just learning a simple association like “food comes after a bright light” or even learning the rule “food comes after the sequence of light-dark-light,” they seemed to generalize the rule “food comes after the sequence XYX, regardless of the type of specific stimulus chosen.” It seems to me that, as we study animal cognition, it is increasingly apparent that advanced cognitive functions are not unique to humans. We can also hope that animal models can be further developed to study human cognition and advance the understanding of human brain function.
2. Lower survival after cardiac arrest during nights and weekends
The following will come as no surprise to anyone who has ever worked at a hospital, especially a smaller community hospital: the chance of survival in a patient from a cardiac arrest is significantly lower on nights and weekends. This must be so intuitively, as staffing is less, nights are not a period of optimal performance for most humans, and patient-related factors may be different, too. Peberdy et al, from the National Registry of Cardiopulmonary Resuscitation Investigators, examined the problem quantitatively [3]. They reviewed 86748 consecutive cases of in-hospital cardiac arrest that were recorded from 507 participating hospitals from January 2000 to February 2007. The results were quite striking. The rate of survival to discharge was less than 15% at nights compared with around 20% for the day/evening shifts. Survival rates during the day/evening shifts were higher on weekdays (20.6%) than on weekends (17.4%). This represents a 30% higher chance of survival to discharge after cardiac arrest during weekdays compared with nights. The huge number of patients also resulted in a high level of statistical significance (all P values were less than .01). What do the results mean? Looking at some subsets of data gives a clue regarding possible solutions. The emergency department and trauma services were the only locations where survival was not any worse at night compared with day/evening. The patients may be different, yet the staffing pattern is different too because it stays the same at all times. The authors suggest putting a greater emphasis on a hospital-wide “code team” with routine training in cardiac resuscitation, including “mock codes.” The study and database are a strong basis for future research and follow-up of outcomes. Hospitals that participated in the database tend to be larger than average [3] and possibly have greater resources. The implications for smaller hospitals are not difficult to see. I see reasons for deep concern here. In the study, at night, the starting rhythm at resuscitation was more often asystole. I suspect it indicates a longer time until the code team was called. Having a better code team will not change this parameter. Increasing night nurse staffing levels to daytime levels may be one solution; but it is not easy, given a nurse shortage. Technological solutions such as better monitoring systems are also possible. I do not expect to find anyone opposed to getting better resuscitation outcomes for patients at all times of day or night. But who will pay for the additional resources?
3. Sleep regulation in fruit flies
Here is yet another piece of evidence pointing to extensive similarities between apparently very different animals. A team from Brandeis University demonstrated that flies with a mutant form of one of the receptors for the neurotransmitter γ-aminobutyric acid (GABA) fell asleep faster than normal flies [1]. The antiepileptic drug carbamazepine (CBZ) typically has the opposite effect—it keeps normal fruit flies awake. A common adverse effect of CBZ is insomnia. The mutant flies were resistant to the effect of CBZ on sleep latency. The study suggests that GABA receptor is involved in sleep onset latency. Beyond the technical part, I am again impressed by the similarity of the neural mechanisms in flies and humans. It is also fascinating to find sleep preserved over hundreds of millions of years since the last common ancestors of flies and humans. It must be very important at a basic level, yet we still do not understand its function.
References
[1]. [1]Agosto J, Choi JC, Parisky KM, Stilwell G, Rosbash M, Griffith LC. Modulation of GABA(A) receptor desensitization uncouples sleep onset and maintenance in Drosophila. Nat Neurosci. 2008;11(3):354–359.
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[2]. [2]Murphy RA, Mondragón E, Murphy VA. Rule learning by rats. Science. 2008;319(5871):1849–1851.
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[3]. [3]Peberdy MA, Ornato JP, Larkin GL, Braithwaite RS, Kashner TM, Carey SM, et al. Survival from in-hospital cardiac arrest during nights and weekends. JAMA. 2008;299(7):785–792.
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Department of Neurosurgery, University of Illinois at Chicago, Chicago, IL 60612, USA
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