In July, Michele Insanally, PhD, had a paper published in Nature Communications. The significant study is titled “Contributions of cortical neuron firing patterns, synaptic connectivity, and plasticity to task performance.” Dr. Insanally is Assistant Professor in the Departments of Otolaryngology, Neurobiology and Bioengineering.
As Dr. Insanally explained, neurons in the mammalian neocortex have complex and diverse firing patterns ranging from reliable responses to sensory input to those that fire apparently at random. Most contemporary studies of neural coding – using hundreds of neurons or even larger data sets – explicitly select only classically “responsive” neurons for analysis, and implicitly assume that each unit contributes to the overall population code more or less equally. “But is this really true?” she asked. “For example, are auditory cortex neurons with strong frequency tuning important for the perception of sound pitch, and neurons without frequency tuning irrelevant for perception?”
In the study, Dr. Insanally and her colleagues aimed to understand the synaptic origins of diverse neuronal responses in the rodent auditory cortex and relate the specific firing properties of every unit in an unbiased manner to its contribution to behavioral performance and the underlying network architecture. They combined in vivo cell-attached, extracellular, and whole-cell recordings during behavior with analyses of a novel task-performing spiking neural network. Then they determined how synaptic plasticity rules lead to diverse neural responses in a spiking neural network model, ultimately showing how a diversity of response types contributes to network function and task performance.
While classically responsive cells have been extensively studied for decades, the contribution of non-classically responsive cells to behavior have remained underexplored despite their prevalence – until now.
The study is significant for three reasons:
- Diverse firing properties are essential for task performance via distinct connections.
- Neural diversity emerges from excitatory and inhibitory synaptic plasticity.
- We can predict the functional role of a neuron from the pattern of synaptic inputs.
“What’s remarkable about this network is that it can capture the heterogenous neural response profiles that we see in behaving animals,” Dr. Insanally said. “It’s important to remember that we didn’t hand-tune these responses. What’s interesting here is that these response profiles emerge from standard excitatory and inhibitory plasticity – they just fall out of this form of spike-timing-dependent plasticity that the field has been describing for the past several decades. Another surprise is that we were able to use our network model to predict the behavior in neurons recorded in vivo. This powerful approach allows us to understand how individual neurons are wired into the larger network and its function in terms of task performance and stimulus classification.”
Basically, this study provides a more complete understanding of how all neurons recorded from the brain – irrespective of their response profiles – contribute to task performance. “Approaches that are more data inclusive are required for advancing our understanding of how neural activity relates to behavior,” Dr. Insanally said. “Diverse neural responses are likely important for supporting brain dynamics that are related to sensorimotor transformations and may enable decision-making and other flexible computations, so it would be interesting to study them in these contexts.”