Dynamic and stable population coding of attentional instructions coexist in the prefrontal cortex

Facial gestures are enacted via a cortical hierarchy of dynamic and stable codes

Successful communication requires the generation and perception of a shared set of signals. Facial gestures are one fundamental set of communicative behaviors in primates, generated through the dynamic arrangement of dozens of fine muscles. While much progress has been made uncovering the neural mechanisms of face perception, little is known about those controlling facial gesture production. Commensurate with the importance of facial gestures in daily social life, anatomical work has shown that facial muscles are under direct control from multiple cortical regions, including primary and premotor in lateral frontal cortex, and cingulate in medial frontal cortex. Furthermore, neuropsychological evidence from focal lesion patients has suggested that lateral cortex controls voluntary movements, and medial emotional expressions. Here we show that lateral and medial cortical face motor regions encode both types of gestures. They do so through unique temporal activity patterns, distinguishable well-prior to movement onset. During gesture production, cortical regions encoded facial kinematics in a context-dependent manner. Our results show how cortical regions projecting in parallel downstream, but each situated at a different level of a posterior-anterior hierarchy form a continuum of gesture coding from dynamic to temporally stable, in order to produce context-related, coherent motor outputs during social communication.

Mixed selectivity: Cellular computations for complexity

The property of mixed selectivity has been discussed at a computational level and offers a strategy to maximize computational power by adding versatility to the functional role of each neuron. Here, we offer a biologically grounded implementational-level mechanistic explanation for mixed selectivity in neural circuits. We define pure, linear, and nonlinear mixed selectivity and discuss how these response properties can be obtained in simple neural circuits. Neurons that respond to multiple, statistically independent variables display mixed selectivity. If their activity can be expressed as a weighted sum, then they exhibit linear mixed selectivity; otherwise, they exhibit nonlinear mixed selectivity. Neural representations based on diverse nonlinear mixed selectivity are high dimensional; hence, they confer enormous flexibility to a simple downstream readout neural circuit. However, a simple neural circuit cannot possibly encode all possible mixtures of variables simultaneously, as this would require a combinatorially large number of mixed selectivity neurons. Gating mechanisms like oscillations and neuromodulation can solve this problem by dynamically selecting which variables are mixed and transmitted to the readout.

Cognition is an emergent property

Cognition relies on the flexible organization of neural activity. In this discussion, we explore how many aspects of this organization can be described as emergent properties, not reducible to their constituent parts. We discuss how electrical fields in the brain can serve as a medium for propagating activity nearly instantaneously, and how population-level patterns of neural activity can organize computations through subspace coding.

Static and dynamic coding in distinct cell types during associative learning in the prefrontal cortex

The prefrontal cortex maintains information in memory through static or dynamic population codes depending on task demands, but whether the population coding schemes used are learning-dependent and differ between cell types is currently unknown. We investigate the population coding properties and temporal stability of neurons recorded from male macaques in two mapping tasks during and after stimulus-response associative learning, and then we use a Strategy task with the same stimuli and responses as control. We identify a heterogeneous population coding for stimuli, responses, and novel associations: static for putative pyramidal cells and dynamic for putative interneurons that show the strongest selectivity for all the variables. The population coding of learned associations shows overall the highest stability driven by cell types, with interneurons changing from dynamic to static coding after successful learning. The results support that prefrontal microcircuitry expresses mixed population coding governed by cell types and changes its stability during associative learning.

Early sensory gain control is dominated by obligatory and global feature-based attention in top-down shifts of combined spatial and feature-based attention

What are the dynamics of global feature-based and spatial attention, when deployed together? In an attentional shifting experiment, flanked by three control experiments, we investigated neural temporal dynamics of combined attentional shifts. For this purpose, orange- and blue-frequency-tagged spatially overlapping Random Dot Kinematograms were presented in the left and right visual hemifield to elicit continuous steady-state-visual-evoked-potentials. After being initially engaged in a fixation cross task, participants were at some point in time cued to shift attention to one of the Random Dot Kinematograms, to detect and respond to brief coherent motion events, while ignoring all such events in other Random Dot Kinematograms. The analysis of steady-state visual-evoked potentials allowed us to map time courses and dynamics of early sensory-gain modulations by attention. This revealed a time-invariant amplification of the to-be attended color both at the attended and the unattended side, followed by suppression for the to-be-ignored color at attended and unattended sides. Across all experiments, global and obligatory feature-based selection dominated early sensory gain modulations, whereas spatial attention played a minor modulatory role. However, analyses of behavior and neural markers such as alpha-band activity and event-related potentials to target- and distractor-event processing, revealed clear modulations by spatial attention.