Article 'Neocortex saves energy by reducing coding precision during food scarcity' published in Neuron
Well done to all from the lab of @RochefortLab with @KatsanevakiD and Nathalie Dupuy, for this article which is now published in Neuron, looking at how the metabolically-expensive, mammalian brain adapts to food scarcity.
I am very excited to share my work from the lab of @RochefortLab with @KatsanevakiD and Nathalie Dupuy, now published in Neuron, looking at how the metabolically-expensive, mammalian brain adapts to food scarcity.
1/ TLDR; We find that coding precision in neocortex is reduced with reduced caloric intake, independent of hunger, in order to save energy. This process just requires a few tweaks in cell-intrinsic electrophysiology, and is mediated by the fat mass-regulated hormone leptin.
Very grateful to Simon Laughlin (@neuralesyne) and David Attwell for characterizing the brain energy budget - turned out to be a big help in this project!
2/ The brain is an energy-hungry machine, demanding about a quarter of our caloric intake. So what happens when food is scarce? Does the brain reduce costly information processing to save energy? We explored this question by food restricting mice and looking at what happened to neuronal activity and energy use in vivo in the visual cortex.
3/ We first imaged ATP in a transgenic mouse line and found that food restriction reduced the rate of energy consumption during visual processing.
4/ How are neurons saving energy? Excitatory synaptic activity consumes the majority of ATP used by the cortex (57% of the brain signalling budget). We found that excitatory currents in vivo were reduced by 29%, leading to a 29% savings in ATP consumption.
5/ What was intriguing was that spiking activity was unchanged. (Spikes are metabolically expensive, but consume about half as much energy as synaptic signalling).
6/ How could excitatory currents be reduced with no change in spike rate? We found that food restricted neurons also had a compensatory increase in input resistance and a depolarization of their resting membrane potential. What was really cool is that these changes enabled neurons from food-restricted animals to spike at a similar rate as controls, but to use less energy on the underlying excitatory currents!
7/ On the flip side, these compensatory changes were associated with an increase in the trial-to-trial fluctuations of visually-evoked responses in vivo, which broadened orientation tuning. This meant that visual neurons were no longer as selective to stimulus orientations. Not a good thing for the precise encoding of visual information!
8/And indeed, we found that information encoding was degraded on a population-level, resulting in a loss of fine visual detail. It was also associated with behavioral impairments in fine visual discrimination.
9/ We could capture the data using a simple Hodgkin-Huxley model neuron with stochastic channels. Decreasing the synaptic conductance (gAMPAR), whilst increasing the input resistance (R) and depolarizing the resting membrane potential (VRest), as observed with food-restriction, amplified channel noise and led to a broadened orientation tuning and loss of coding precision, similar to what we saw in vivo.
10/ How might peripheral caloric intake led to a loss of cortical coding precision? We next looked at the hormone leptin, which is secreted by adipose tissue in proportion to fat mass. Leptin levels were reduced with food-restriction. Supplementing this lost leptin exogenously restored coding precision in the cortex, even though animals still were food-restricted!
11/ Overall our study shows that neurons can dynamically adjust how much energy they spend on encoding information, and that this process is controlled by metabolic state.
The article can be found here: Neocortex saves energy by reducing coding precision during food scarcity: Neuron (cell.com)