Memory Strategies Shift How Information is Represented in Prefrontal Cortex Neurons
Post by Lani Cupo
The takeaway
Brain regions encode information differently depending on the memory strategy used. In the lateral prefrontal cortex of monkeys, neural activity shifts in a strategy-dependent manner between individual neurons and populations of neurons.
What's the science?
Humans and other animals use strategies to organize information in order to counteract the limited capacity of working memory and execute complex cognitive processes, however, how this information is represented in neural mechanisms is still poorly understood. These processes rely on the prefrontal cortex, an area that is flexible enough to adapt to the demands of different tasks. However, information can either be represented at the single-neuron level or at the population level, and it can dynamically respond to employed strategies. This week in Neuron, Chiang and colleagues investigated how working memory strategies employed by monkeys impacted neuronal ensemble coding in the lateral prefrontal cortex (LPFC).
How did they do it?
Previous research established that, like humans, monkeys use strategies to exceed the natural limits to working memory (WM) (usually around 4 items). In the present study, two monkeys were presented with a visual task where six identical, colored circles were presented on a screen and the monkeys had to make a saccade (eye movement) to each one only once, returning their eyes to a central point between each selection, remembering which targets they had already visited. The task forced them to remember up to 6 targets in each trial, exceeding the typical capacity of WM and engaging additional mnemonic strategies. Microelectrodes were implanted in the bilateral LPFC of the monkeys to record neuronal activity from groups of about 40 neurons simultaneously during the task, allowing the authors to link neuronal activity to the task performance. To examine the representation of three variables (location of targets, order of saccades, and color of targets), the authors applied a technique known as linear discriminant analysis (LDA) to the neural activity data, allowing them to separate neuronal representations of each variable. In order to understand how each neuron contributed to the population representation of the overall ensemble code, the authors employed a procedure where they removed each unit from their LDA model in turn to see how the overall pattern changed, identifying that neurons contributed differently to encoding at a population level. To examine the impact of sequencing strategies on task performance and the underlying neuronal activity, the authors examined whether the monkeys were likely to visit targets in a similar order across a block (set of trials). When monkeys were more likely to fixate on circles in a specific pattern, the block was given a high stereotyped index (SI), and when there was more diversity in the pattern it was given a low SI. The categorization allowed them to assess whether monkeys were employing a sequencing strategy (high SI blocks), and how this strategy impacted task performance and neuronal firing.
What did they find?
First, reaction times increased across saccades (on later target selection), and monkeys were more likely to fail (look at a target they had already looked at before), suggesting that selections became more difficult, and working memory was being taxed. However, the monkeys performed better on blocks with a higher SI, implying the mnemonic strategy helped compensate for limits to working memory. One of the main findings was that stereotyped behaviors, representing sequencing strategies, were associated with more distributed neuronal encoding in the LPFC. As behavior became more stereotyped, individual neurons contributed less to the ensemble. Overall, when strategies were used and behavior became more routine (associated with better performance on the task), more neurons were recruited, with smaller individual contributions, whereas when behavior was more flexible, fewer neurons were recruited, each contributing more to the signal.
What's the impact?
This study found that using mnemonic strategies improved task performance and altered the underlying representation of the behavior, shifting towards a more distributed pattern of activity with more neurons contributing less individually. These findings provide a new perspective on how information is represented differently on a neuronal level dependent on cognitive strategies employed. This study represents a step for investigations that seek to further uncover the neural mechanisms underlying higher-order cognitive abilities.
