New Types of Experiments Reveal that a Neuron Functions as Multiple Independent Threshold Units

Abstract

Neurons are the computational elements that compose the brain and their fundamental principles of activity are known for decades. According to the long-lasting computational scheme, each neuron sums the incoming electrical signals via its dendrites and when the membrane potential reaches a certain threshold the neuron typically generates a spike to its axon. Here we present three types of experiments, using neuronal cultures, indicating that each neuron functions as a collection of independent threshold units. The neuron is anisotropically activated following the origin of the arriving signals to the membrane, via its dendritic trees. The first type of experiments demonstrates that a single neuron’s spike waveform typically varies as a function of the stimulation location. The second type reveals that spatial summation is absent for extracellular stimulations from different directions. The third type indicates that spatial summation and subtraction are not achieved when combining intra- and extra- cellular stimulations, as well as for nonlocal time interference, where the precise timings of the stimulations are irrelevant. Results call to re-examine neuronal functionalities beyond the traditional framework, and the advanced computational capabilities and dynamical properties of such complex systems.

Spatially resolved dendritic integration: Towards a functional classification of neurons

“…Hence, neuronal integration of input from various synaptic sources depends on these non-linear (non-additive) dynamics taking place at dendrites with complex topology. Much work has been done to investigate how topology determines the capability of single neurons to detect intensity of stimulus [14], to reliably detect dendritic spikes [15], to discriminate input patterns [16], and to perform other forms of dendritic computation [17,18]. There has been some attempts to study this problem analytically [19,20].…”

Brain experiments imply adaptation mechanisms which outperform common AI learning algorithms

“…In-Vitro experiments. The experimental methods are similar to our previous studies 6,7 and only the modifications are presented. All procedures were in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals and Bar-Ilan University Guidelines for the Use and Care of Laboratory Animals in Research and were approved and supervised by the Bar-Ilan University Animal Care and Use Committee.…”

Creative destruction: Sparse activity emerges on the mammal connectome under a simulated communication strategy with collisions and redundancy

“…The brain may in fact use a less punitive strategy than this but neurophysiological evidence increasingly supports the notion that signals in the brain regularly collide and are destroyed. For example, Sardi et al (2017) demonstrated the failure of coincident signals above threshold to elicit spikes. They also showed that excitatory signals can cancel each other when they collide "head on" (Sardi et al, 2017; this is in fact predicted by the Hodgkin-Huxley model: Scott, 1977).…”

“…For example, Sardi et al (2017) demonstrated the failure of coincident signals above threshold to elicit spikes. They also showed that excitatory signals can cancel each other when they collide "head on" (Sardi et al, 2017; this is in fact predicted by the Hodgkin-Huxley model: Scott, 1977). Gidon et al (2020) have shown exclusive-OR activity in single ex vivo human pyramidal cortical neurons, a behavior that effectively destroys some colliding signals.…”