Decline of long-range temporal correlations in the human brain during sustained wakefulness

Sleep is crucial for daytime functioning, cognitive performance and general well-being. These aspects of daily life are known to be impaired after extended wake, yet, the underlying neuronal correlates have been difficult to identify. Accumulating evidence suggests that normal functioning of the brain is characterized by long-range temporal correlations (LRTCs) in cortex, which are supportive for decision-making and working memory tasks. Here we assess LRTCs in resting state human EEG data during a 40-hour sleep deprivation experiment by evaluating the decay in autocorrelation and the scaling exponent of the detrended fluctuation analysis from EEG amplitude fluctuations. We find with both measures that LRTCs decline as sleep deprivation progresses. This decline becomes evident when taking changes in signal power into appropriate consideration. Our results demonstrate the importance of sleep to maintain LRTCs in the human brain. In complex networks, LRTCs naturally emerge in the vicinity of a critical state. The observation of declining LRTCs during wake thus provides additional support for our hypothesis that sleep reorganizes cortical networks towards critical dynamics for optimal functioning

Deforestation and Decolonization: Lafcadio Hearn’s French Antillean Writing

Looking outside at my breadfruit tree reminds me how European colonialism shaped Caribbean landscape through the genocide of indigenous peoples and colonization of their lands, followed by the theft, commodification and dispersal of indigenous plants and botanic knowledge. Furthermore, these processes were accompanied by the production and hierarchization of race and the enslavement and exploitation of African and Asian populations. As Elizabeth Deloughrey, Renee Gosson, and George Handley note, ‘there is probably no other region in the world that has been more radically altered in terms of human and botanic migration, transplantation and settlement than the Caribbean’. Yet, our ability to detect ecoimperialist activities by reading Caribbean landscapes is hampered by ‘the ever-expanding and ambitious imaginative symbolism’ through which the colonizers constituted the islands as tropical paradises’. As Deloughrey explains, ‘at the height of the process of altering and damaging island landscapes, tropical islands were interpellated in Edenic terms, removed in space and time’ and segregated from human agency. This interpellation, still active in today’s tourism advertisements, naturalizes the altered landscapes, thereby effacing the violent ecological history of the Caribbean plantation economy

Behavioural simulation of biological neuron systems using VHDL and VHDL-AMS

The investigation of neuron structures is an incredibly difficult and complex task that yields relatively low rewards in terms of information from biological forms (either animals or tissue). The structures and connectivity of even the simplest invertebrates are almost impossible to establish with standard laboratory techniques, and even when this is possible it is generally time consuming, complex and expensive. Recent work has shown how a simplified behavioural approach to modelling neurons can allow “virtual” experiments to be carried out that map the behaviour of a simulated structure onto a hypothetical biological one, with correlation of behaviour rather than underlying connectivity. The problems with such approaches are numerous. The first is the difficulty of simulating realistic aggregates efficiently, the second is making sense of the results and finally, it would be helpful to have an implementation that could be synthesised to hardware for acceleration. In this paper we present a VHDL implementation of Neuron models that allow large aggregates to be simulated. The models are demonstrated using a system level VHDL and VHDL-AMS model of the C. Elegans locomotory system