Toward a molecular profile of self-representation

Feeling embodiment over our body or body part has a major role in the understanding of the self and control of self-actions. Even though it is crucial in our daily life, embodiment is not an homogenous phenotype across population, as quantified by implicit and explicit measures (i.e., neuroimaging or self-reports). Studies have shown differences in neuropathological conditions compared to healthy controls, but also across healthy individuals. We discuss examples of self-perception differences, and the molecular origin of embodiment, focusing on clinical cases, during the first and second section. We then discuss two important questions in this molecular-to-embodiment relationship: (i) which are the molecular levels (and their associated techniques) that can be relevant to embodiment, and (ii) which are the most adequate experiments to correlate molecular profiles and embodiment quantification across individuals. Potential answers for both questions will be outlined during the third and fourth sections, respectively, in order to design a framework to study the molecular profile of body embodiment

Network adaptation improves temporal representation of naturalistic stimuli in drosophila eye: II Mechanisms

Retinal networks must adapt constantly to best present the ever changing visual world to the brain. Here we test the hypothesis that adaptation is a result of different mechanisms at several synaptic connections within the network. In a companion paper (Part I), we showed that adaptation in the photoreceptors (R1-R6) and large monopolar cells (LMC) of the Drosophila eye improves sensitivity to under-represented signals in seconds by enhancing both the amplitude and frequency distribution of LMCs' voltage responses to repeated naturalistic contrast series. In this paper, we show that such adaptation needs both the light-mediated conductance and feedback-mediated synaptic conductance. A faulty feedforward pathway in histamine receptor mutant flies speeds up the LMC output, mimicking extreme light adaptation. A faulty feedback pathway from L2 LMCs to photoreceptors slows down the LMC output, mimicking dark adaptation. These results underline the importance of network adaptation for efficient coding, and as a mechanism for selectively regulating the size and speed of signals in neurons. We suggest that concert action of many different mechanisms and neural connections are responsible for adaptation to visual stimuli. Further, our results demonstrate the need for detailed circuit reconstructions like that of the Drosophila lamina, to understand how networks process information

Multidimensional Recording (MDR) and Data Sharing: An Ecological Open Research and Educational Platform for Neuroscience

Primate neurophysiology has revealed various neural mechanisms at the single-cell level and population level. However, because recording techniques have not been updated for several decades, the types of experimental design that can be applied in the emerging field of social neuroscience are limited, in particular those involving interactions within a realistic social environment. To address these limitations and allow more freedom in experimental design to understand dynamic adaptive neural functions, multidimensional recording (MDR) was developed. MDR obtains behavioral, neural, eye position, and other biological data simultaneously by using integrated multiple recording systems. MDR gives a wide degree of freedom in experimental design because the level of behavioral restraint is adjustable depending on the experimental requirements while still maintaining the signal quality. The biggest advantage of MDR is that it can provide a stable neural signal at higher temporal resolution at the network level from multiple subjects for months, which no other method can provide. Conventional event-related analysis of MDR data shows results consistent with previous findings, whereas new methods of analysis can reveal network mechanisms that could not have been investigated previously. MDR data are now shared in the public server Neurotycho.org. These recording and sharing methods support an ecological system that is open to everyone and will be a valuable and powerful research/educational platform for understanding the dynamic mechanisms of neural networks

Consequences of converting graded to action potentials upon neural information coding and energy efficiency

Information is encoded in neural circuits using both graded and action potentials, converting between them within single neurons and successive processing layers. This conversion is accompanied by information loss and a drop in energy efficiency. We investigate the biophysical causes of this loss of information and efficiency by comparing spiking neuron models, containing stochastic voltage-gated Na+ and K+ channels, with generator potential and graded potential models lacking voltage-gated Na+ channels. We identify three causes of information loss in the generator potential that are the by-product of action potential generation: (1) the voltage-gated Na+ channels necessary for action potential generation increase intrinsic noise and (2) introduce non-linearities, and (3) the finite duration of the action potential creates a ‘footprint’ in the generator potential that obscures incoming signals. These three processes reduce information rates by ~50% in generator potentials, to ~3 times that of spike trains. Both generator potentials and graded potentials consume almost an order of magnitude less energy per second than spike trains. Because of the lower information rates of generator potentials they are substantially less energy efficient than graded potentials. However, both are an order of magnitude more efficient than spike trains due to the higher energy costs and low information content of spikes, emphasizing that there is a two-fold cost of converting analogue to digital; information loss and cost inflation

Working Together May Be Better: Activation of Reward Centers during a Cooperative Maze Task

Humans use theory of mind when predicting the thoughts and feelings and actions of others. There is accumulating evidence that cooperation with a computerized game correlates with a unique pattern of brain activation. To investigate the neural correlates of cooperation in real-time we conducted an fMRI hyperscanning study. We hypothesized that real-time cooperation to complete a maze task, using a blind-driving paradigm, would activate substrates implicated in theory of mind. We also hypothesized that cooperation would activate neural reward centers more than when participants completed the maze themselves. Of interest and in support of our hypothesis we found left caudate and putamen activation when participants worked together to complete the maze. This suggests that cooperation during task completion is inherently rewarding. This finding represents one of the first discoveries of a proximate neural mechanism for group based interactions in real-time, which indirectly supports the social brain hypothesis

Power-Law Inter-Spike Interval Distributions Infer a Conditional Maximization of Entropy in Cortical Neurons

The brain is considered to use a relatively small amount of energy for its efficient information processing. Under a severe restriction on the energy consumption, the maximization of mutual information (MMI), which is adequate for designing artificial processing machines, may not suit for the brain. The MMI attempts to send information as accurate as possible and this usually requires a sufficient energy supply for establishing clearly discretized communication bands. Here, we derive an alternative hypothesis for neural code from the neuronal activities recorded juxtacellularly in the sensorimotor cortex of behaving rats. Our hypothesis states that in vivo cortical neurons maximize the entropy of neuronal firing under two constraints, one limiting the energy consumption (as assumed previously) and one restricting the uncertainty in output spike sequences at given firing rate. Thus, the conditional maximization of firing-rate entropy (CMFE) solves a tradeoff between the energy cost and noise in neuronal response. In short, the CMFE sends a rich variety of information through broader communication bands (i.e., widely distributed firing rates) at the cost of accuracy. We demonstrate that the CMFE is reflected in the long-tailed, typically power law, distributions of inter-spike intervals obtained for the majority of recorded neurons. In other words, the power-law tails are more consistent with the CMFE rather than the MMI. Thus, we propose the mathematical principle by which cortical neurons may represent information about synaptic input into their output spike trains

Visual Coding in Locust Photoreceptors

Information capture by photoreceptors ultimately limits the quality of visual processing in the brain. Using conventional sharp microelectrodes, we studied how locust photoreceptors encode random (white-noise, WN) and naturalistic (1/f stimuli, NS) light patterns in vivo and how this coding changes with mean illumination and ambient temperature. We also examined the role of their plasma membrane in shaping voltage responses. We found that brightening or warming increase and accelerate voltage responses, but reduce noise, enabling photoreceptors to encode more information. For WN stimuli, this was accompanied by broadening of the linear frequency range. On the contrary, with NS the signaling took place within a constant bandwidth, possibly revealing a ‘preference’ for inputs with 1/f statistics. The faster signaling was caused by acceleration of the elementary phototransduction current - leading to bumps - and their distribution. The membrane linearly translated phototransduction currents into voltage responses without limiting the throughput of these messages. As the bumps reflected fast changes in membrane resistance, the data suggest that their shape is predominantly driven by fast changes in the light-gated conductance. On the other hand, the slower bump latency distribution is likely to represent slower enzymatic intracellular reactions. Furthermore, the Q10s of bump duration and latency distribution depended on light intensity. Altogether, this study suggests that biochemical constraints imposed upon signaling change continuously as locust photoreceptors adapt to environmental light and temperature conditions

Overlapping signals for translational regulation and packaging of influenza A virus segment 2

Influenza A virus segment 2 mRNA expresses three polypeptides: PB1, PB1-F2 and PB1-N40, from AUGs 1, 4 and 5 respectively. Two short open reading frames (sORFs) initiated by AUGs 2 and 3 are also present. To understand translational regulation in this system, we systematically mutated AUGs 1–4 and monitored polypeptide synthesis from plasmids and recombinant viruses. This identified sORF2 as a key regulatory element with opposing effects on PB1-F2 and PB1-N40 expression. We propose a model in which AUGs 1–4 are accessed by leaky ribosomal scanning, with sORF2 repressing synthesis of downstream PB1-F2. However, sORF2 also up-regulates PB1-N40 expression, most likely by a reinitiation mechanism that permits skipping of AUG4. Surprisingly, we also found that in contrast to plasmid-driven expression, viruses with improved AUG1 initiation contexts produced less PB1 in infected cells and replicated poorly, producing virions with elevated particle:PFU ratios. Analysis of the genome content of virus particles showed reduced packaging of the mutant segment 2 vRNAs. Overall, we conclude that segment 2 mRNA translation is regulated by a combination of leaky ribosomal scanning and reinitiation, and that the sequences surrounding the PB1 AUG codon are multifunctional, containing overlapping signals for translation initiation and for segmentspecific packaging