• Rano (2012) - A Model and Formal Analysis of Braitenberg Vehicles 2 and 3. Dynamical systems analysis of Braitenberg vehicles.
• Lamb and Calabrese (2012) - Small is beautiful: models of small neuronal networks. A review on modeling small invertebrate networks.
• Kane et al (2013) - Sensorimotor structure of Drosophila larva phototaxis.
• Kidd and Castano (2013) - Reading Literary Fiction Improves Theory of Mind. Why you should read literature.

• Viswanathan et al (2008) - Lévy flights and superdiffusion in the context of biological encounters and random searches. Theory of the optimal distribution of straight run lengths in organisms that move by runs and tumbles and look for food (e.g. Paramecium or E. Coli).
• Bartumeus et al (2003) - Helical Lévy walks- Adjusting searching statistics to resource availability in microzooplankton. Evidence of adaptive change in trajectory statistics in a microorganism.
• Benichou et al (2011) - Intermittent search strategies. A similar problem but when the organism can only look when it stops; applies to molecular transport too.
• Huang et al (2016) - Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding. Some information-theoretic analysis of our adaptive threshold model (Platkiewicz and Brette (2010, 2011) and Fontaine et al. (2014)).
• Clay et al (2008) - A simple modification of the Hodgkin and Huxley equations explains type 3 excitability in squid giant axons. A revision of the HH model with K+ current following GHK.
• Armstrong (2007) - Life among the axons. Pretty cool paper on the history of electrophysiological theory.
• Hille et al (1999) - Ion channels- from idea to reality. The same on channels.

• Rasband and Peles (2015) - The Nodes of Ranvier- Molecular Assembly and Maintenance. I am wondering why Kv channels and Nav channels are spatially segregated.
• Misonou et al (2004) - Regulation of ion channel localization and phosphorylation by neuronal activity. About Kv2.1 but most likely quite general.
• Park et al (2006) - Graded Regulation of the Kv2.1 Potassium Channel by Variable Phosphorylation. More about phosphorylation.
• Wimmer et al (2010) - Axon initial segment dysfunction in epilepsy.
• Bradley and Somjen (1961) - Accommodation in motoneurones of the rat and the cat. One of the first papers about threshold adaptation (in relation with my papers on the subject: Spike-threshold adaptation predicted by membrane potential dynamics in vivo and Impact of Fast Sodium Channel Inactivation on Spike Threshold Dynamics and Synaptic Integration).
• Ahissar and Assa (2016) - Perception as a closed-loop convergence process. Related to subjective physics.
• Zhang et al (2016) - Optical electrophysiology for probing function and pharmacology of voltage-gated ion channels. Sounds cool!
• Hiwatashi et al (1980) - Restoration of membrane excitability in a behavioral mutant of Paramecium caudatum during conjugation and by microinjection of wild-type cytoplasm. Very intriguing!

After a two weeks break:

• Zhang and Rasband (2016) - Cytoskeletal control of axon domain assembly and function. Nice looking review.
• Ko et al (2016) - Serotonin modulates spike probability in the axon initial segment through HCN channels. There was some previous related work by Florence Cotel et al. (2013).
• Bird and Cuntz (2016) - Optimal Current Transfer in Dendrites. The paper includes in the supplementary information a derivation of the extended cable equation with variable diameter. Otherwise I think the approach might be quite interesting for the axon too.
• Srivastava et al (2016) - Motor control by precisely timed spike patterns. The demonstration was made previously by Vladimir Brezina in invertebrate muscles that muscle contraction is highly sensitive to single spikes, but this one is in vertebrates.
• Grunwald and Vitanyi (2010) - Shannon Information and Kolmogorov Complexity. I already knew about Kolmogorov complexity, but I just realized it might be an interesting alternative definition of information to use in neuroscience; in particular you can define the information in a single stimulus (eg image), in contrast with Shannon information (a single stimulus is just one element of a set).
• Jonas and Kording (2016) - Could a neuroscientist understand a microprocessor. None of the epistemological points made here are original, but what I like in this paper is it is a concrete demonstration that the reductionist methods used in systems neuroscience (tuning curves, connectomes etc) are just not going to work. It relates to many texts I have written on this blog, for example: Can we understand the brain by measuring its structure? And the series What is computational neuroscience? It is also related to the point I try to make in my essay Philosophy of the spike, that rate-based descriptions of neural activity are not causal, mechanistic descriptions. Think about having a rate-based view for transistors: you certainly could just as you can with neurons, but that won't get you to any mechanistic level of understanding, just tuning curves and transistor correlates.