Summary: Each decision begins subtly, since the brain weighs options long before the action. Researchers have now shown that, despite individual differences in neurons, a shared underlying structure guides the brain towards unified decisions.
When training macaques in a color choice task and registering neuronal activity, scientists discovered that neurons are formed by a common “potential landscape” that varies with the difficulty of the task. This study offers a new model on how the brain organizes complex decisions and can inform the future understanding of psychiatric conditions that interrupt decision making.
Key facts:
Shared structure: various neurons follow a common potential landscape that shapes their collective decision making. Modulation of life: the easiest decisions show “more pronounced” pending “, promoting rapid options; The toughest flatten the landscape. Clinical implications: Understanding this coordination can shed light on disorders such as schizophrenia and bipolar disorder.
Source: Princeton University
Each decision begins invisibly.
Long before someone acts, the brain is already working hard to gather evidence, weigh options and gradually compromise an choice. But even when they face the same evidence, people can reach different results, especially when the decision is difficult.
Two different drivers in peak time traffic, for example, see the same congested road, but one could accelerate to merge while another brake cautiously.
However, the way in which the brain, composed of billions of specialized cells, makes these decisions of the second division has been largely a mystery.
Now, the new findings of Princeton University, in collaboration with researchers from the Harbor Laboratory of Cold Spring, Stanford University and Boston University, shed light on how various brain cells join to guide a unified decision.
The researchers found that while individual neurons have disconcertingly complex responses, their activity is formed by a shared structure that finally guides the brain towards a unified choice.
The findings were published in Nature magazine on June 25.
Classic neuroscience experiments have shown that the brain maps the simple sensory information, such as basic forms or sounds, predictably. A black rectangle rotated at an angle of 45 degrees will activate a specific group of cells in the visual cortex.
However, change the angle slightly, and a different group illuminates. But decisions, especially when linked to action, are more complicated than distinguishing slightly different tones or forms, which makes researchers difficult to identify the neuronal code that guides decision -making.
To overcome this challenge, the research team trained Rhesus macaques to determine which color (red or green) was more dominant on a pictures. The easy trials were clear, but the ambiguous required careful deliberation.
As the monkeys considered their choice, the researchers registered the activity of nerve cells in the dorsal pre -coat cortex, a brain region involved in the translation of actions into actions.
They discovered that neurons responded very differently, even within the same essay, which suggests a high degree of “heterogeneity” or variability, in the neural code for decisions.
“The generalized assumption is that this heterogeneity reflects the complex dynamic involved in cognition,” said Tatiana Engel, Ph.D., an associated professor at the Princeton Neuroscience Institute and the main author of the study.
“But surprisingly, we find that this apparent complexity arises from a very different neural coding principle.”
To explain this diversity, the team developed a flexible computational model that revealed two critical characteristics that drive the behavior of each neuron: 1) Adjustment: When and what type of decision tends to respond; and 2) Neuronal dynamics: represented by a “potential landscape” that guides the activity.
In this model, the valleys in the landscape represent a stable decision that has been taken. As neuronal activity is developed, it is like a ball that surrounds the land: the most pronounced slopes push the activity more decisively towards an choice.
When adjusted to real data, the model showed that tuning remained consisting of easy and hard tests, but the form of the potential landscape changed. In easier tasks, the landscape was steep, which led to faster and more safe decisions. In more difficult tasks, the terrain was flatter and more susceptible to noise, increasing the possibilities of errors.
Although each neuron had a different individual response, everyone seemed to share the same underlying potential landscape.
“Think about it as a group of skiers who descend a mountain,” said Engel.
“Each one prefers a slightly different path, but all are formed by the same slope under them. Similarly, each neuron has its own preference and activity, but the group of cells collectively in the pre -agent cortex takes a coordinated trip and gradually accommodates in a stable state that represents the decision.”
Understanding how neurons collaborate to make decisions could offer a deeper vision of the function of the fundamental brain, and how it goes out in disorders such as schizophrenia or bipolar disorder, where decision -making processes are altered.
With a new model in his hand, Engel and his colleagues now plan to explore how the different types of neurons and the ways in which they connect, contribute to the various affinations and different phases of decision -making they observed.
“Every decision is unique,” said Engel. “But when digging to the level of individual essays and individual neurons, we can begin to make sense.”
About this decision making and neuroscience research news
Author: Daniel was going
Source: Princeton University
Contact: Daniel Vahaba – Princeton University
Image: The image is accredited to Neuroscience News
Original research: open access.
“The dynamics and geometry of choice in the pre -agent cortex” by Tatiana Engel et al. Nature
Abstract
The dynamics and geometry of choice in the pre -agent cortex
The brain represents sensory variables in the coordinated activity of neuronal populations, in which the adjustment curves of individual neurons define the geometry of the population code.
If the same coding principle is valid for dynamic cognitive variables, it is still unknown because internal cognitive processes develop with a unique time course in individual trials observed only in the irregular increase in heterogeneous neuronal populations.
Here we show the existence of this Population Code for the formation of the dynamics of choice in the Premotora Primates cortex.
We develop an approach to simultaneously infer the dynamics of the population and the adjustment functions of individual neurons to the state of the population.
Applied to Spike data registered during decision -making, our model revealed that neurons populations encoded the same prediction of dynamic variables, and heterogeneous shooting rates resulted from the diverse adjustment of individual neurons to this decision variable.
The inferred dynamics indicated a mechanism of attraction for the calculation of the decision.
Our results reveal a unifying geometric principle for the neural coding of sensory and dynamic cognitive variables.
