Summary: Researchers challenge a 75-year-old neuroscience hypothesis, suggesting dendrites play a crucial role in brain computation, not just the neuronal soma.
Experiments conducted under non-physiological conditions revealed that neuron features like firing frequency and stimulation threshold are controlled by dendrites.
This groundbreaking discovery implies that dendrites could be pivotal in learning processes and may even influence our understanding of brain states and degenerative diseases.
Key Facts:
- The study presents a paradigm shift, indicating dendrites are active computational elements, rather than just passive signal collectors.
- Experimental results showed neuron characteristics are maintained even under conditions that differ from the awake brain state, suggesting a dendritic origin of these features.
- This new perspective could reshape our approach to understanding degenerative diseases and the fundamental mechanisms of the brain’s awake and sleep states.
Source: Bar Ilan University
The brain is a complex network containing billions of neurons. The soma of each of these neurons communicates simultaneously with thousands of others via their synapses (links), and collects incoming signals through several extremely long, branched “arms”, called dendritic trees.
For the last 75 years a core hypothesis of neuroscience has been that the basic computational element of the brain is the neuronal soma, where the long and ramified dendritic trees are only cables that enable them to collect incoming signals from its thousands of connecting neurons. This long-lasting hypothesis has now been called into question.
In an article just published in Physica A, researchers from Bar-Ilan University in Israel reveal that many dynamical features which are commonly attributed to the soma may stem from dendritic mechanisms.
“Typically, in-vitro experiments examine neurons using a fixed holding membrane potential, imitating the physiological conditions of intact brains in an awake state,” said Prof. Ido Kanter, of Bar-Ilan’s Department of Physics and Gonda (Goldschmied) Multidisciplinary Brain Research Center, who led the research.
“We went against conventional wisdom and performed new types of experiments, violating the physiological conditions of the brain. Results showed that neuronal features are independent of these physiological conditions, a finding which strongly pinpoints dendrites as the segments which control neuronal plasticity features, such as the neuronal firing frequency and the stimulation threshold of the neuron.”
Presented experimental evidence supports previous research by Kanter and his experimental research team — conducted by Dr. Roni Vardi — indicating efficient dendritic tree learning evidence for sub-dendritic adaptation using neuronal cultures, together with other anisotropic properties of neurons, like different spike waveforms, refractory periods and maximal transmission rates.
The new results call for a re-examination of the origin of degenerative diseases, since the origin of many neuronal functionalities are beyond the traditional framework and must be attributed to the dendrites instead of the soma. In addition, results question the origin of awake and sleep states of our brain which are commonly attributed to the level of the somatic membrane potential.
About this neuroscience research news
Author: Elana Oberlander
Source: Bar-Ilan University
Contact: Elana Oberlander – Bar-Ilan University
Image: The image is credited to Neuroscience News
Original Research: Open access.
“Neuronal plasticity features are independent of neuronal holding membrane potential” by Ido Kanter et al. Physica A Statistical Mechanics and its Applications
Abstract
Neuronal plasticity features are independent of neuronal holding membrane potential
Dynamical reversible neuronal features in vitro are typically examined using a fixed holding membrane potential, imitating the physiological conditions of intact brains in an awake state.
Here, a set of neuronal plasticity features in synaptic blocked cultures are found to be independent of the holding membrane potential in the range [−95, −50] mV. Specifically, dendritic maximal firing frequency and its absolute refractory period are independent of the holding membrane potential.
In addition, the stimulation threshold is also independent of the holding membrane potential in neurons that do not show membrane depolarization in response to sub-threshold stimulations.
These robust dendritic plasticity features are a prerequisite for neuronal modeling and for their utilization in interconnected neural networks to realize higher-order functionalities.
