Dynamic shifts of visual and saccadic signals in prefrontal cortical regions 8Ar and FEF

Frontal eye fields in macaque monkeys: prefrontal and premotor contributions to visually guided saccades

Neuronal spiking was sampled from the frontal eye field (FEF) and from the rostral part of area 6 that reaches to the superior limb of the arcuate sulcus, dorsal to the arcuate spur when present (F2vr) in macaque monkeys performing memory-guided saccades and visually guided saccades for visual search. Neuronal spiking modulation in F2vr resembled that in FEF in many but not all respects. A new consensus clustering algorithm of neuronal modulation patterns revealed that F2vr and FEF contain a greater variety of modulation patterns than previously reported. The areas differ in the proportions of visuomotor neuron types, the proportions of neurons discriminating a target from distractors during visual search, and the consistency of modulation patterns across tasks. However, between F2vr and FEF we found no difference in the magnitude of delay period activity, the timing of the peak discharge rate relative to saccades, or the time of search target selection. The observed similarities and differences between the 2 cortical regions contribute to other work establishing the organization of eye fields in the frontal lobe and may help explain why FEF in monkeys is identified within granular prefrontal area 8 but in humans is identified within agranular premotor area 6.

Decoding the Time Course of Spatial Information from Spiking and Local Field Potential Activities in the Superior Colliculus

Place code representation is ubiquitous in circuits that encode spatial parameters. For visually guided eye movements, neurons in many brain regions emit spikes when a stimulus is presented in their receptive fields and/or when a movement is directed into their movement fields. Crucially, individual neurons respond for a broad range of directions or eccentricities away from the optimal vector, making it difficult to decode the stimulus location or the saccade vector from each cell's activity. We investigated whether it is possible to decode the spatial parameter with a population-level analysis, even when the optimal vectors are similar across neurons. Spiking activity and local field potentials (LFPs) in the superior colliculus (SC) were recorded with a laminar probe as monkeys performed a delayed saccade task to one of eight targets radially equidistant in direction. A classifier was applied offline to decode the spatial configuration as the trial progresses from sensation to action. For spiking activity, decoding performance across all eight directions was highest during the visual and motor epochs and lower but well above chance during the delay period. Classification performance followed a similar pattern for LFP activity too, except the performance during the delay period was limited mostly to the preferred direction. Increasing the number of neurons in the population consistently increased classifier performance for both modalities. Overall, this study demonstrates the power of population activity for decoding spatial information not possible from individual neurons.

The eyes reflect an internal cognitive state hidden in the population activity of cortical neurons

Decades of research have shown that global brain states such as arousal can be indexed by measuring the properties of the eyes. The spiking responses of neurons throughout the brain have been associated with the pupil, small fixational saccades, and vigor in eye movements, but it has been difficult to isolate how internal states affect the eyes, and vice versa. While recording from populations of neurons in the visual and prefrontal cortex (PFC), we recently identified a latent dimension of neural activity called "slow drift," which appears to reflect a shift in a global brain state. Here, we asked if slow drift is correlated with the action of the eyes in distinct behavioral tasks. We recorded from visual cortex (V4) while monkeys performed a change detection task, and PFC, while they performed a memory-guided saccade task. In both tasks, slow drift was associated with the size of the pupil and the microsaccade rate, two external indicators of the internal state of the animal. These results show that metrics related to the action of the eyes are associated with a dominant and task-independent mode of neural activity that can be accessed in the population activity of neurons across the cortex.

Dynamic encoding of saccade sequences in primate frontal eye field

The frontal eye field (FEF) is a key part of the oculomotor system, with dominant responses to the direction of single saccades. However, whether and how FEF contributes to sequential saccades remain largely unknown. By training rhesus monkeys to perform saccade sequences, we found sequence-related activities in FEF neurons, whose selectivity to saccade direction undergoes dynamic changes during sequential vs. single saccades. These sequence-related activities are context-dependent, exhibiting different firing activities during memory- vs. visually guided sequences. When the monkey was performing the sequential saccade task, the thresholds of microstimulation to evoke saccades in FEF were increased and the percentage of the successfully induced saccades was significantly reduced compared with the fixation condition. Pharmacological inactivation of FEF impaired the monkey's performance of previously learned sequential saccades, with different effects on the same actions depending on its position within the sequence. These results reveal the context-dependent, sequence-specific dynamic encoding of saccades in FEF, and underscore the crucial role of FEF in the planning and execution of sequential saccades. KEY POINTS: FEF neurons respond differently during sequential vs. single saccades Sequence-related FEF activity is context-dependent The microstimulation threshold in FEF was increased during the sequential task but the evoked saccade did not alter the sequence structure FEF inactivation severely impaired the performance of sequential saccades.

Revisiting Persistent Neuronal Activity During Covert Spatial Attention

Persistent activity has been observed in the prefrontal cortex (PFC), in particular during the delay periods of visual attention tasks. Classical approaches based on the average activity over multiple trials have revealed that such an activity encodes the information about the attentional instruction provided in such tasks. However, single-trial approaches have shown that activity in this area is rather sparse than persistent and highly heterogeneous not only within the trials but also between the different trials. Thus, this observation raised the question of how persistent the actually persistent attention-related prefrontal activity is and how it contributes to spatial attention. In this paper, we review recent evidence of precisely deconstructing the persistence of the neural activity in the PFC in the context of attention orienting. The inclusion of machine-learning methods for decoding the information reveals that attention orienting is a highly dynamic process, possessing intrinsic oscillatory dynamics working at multiple timescales spanning from milliseconds to minutes. Dimensionality reduction methods further show that this persistent activity dynamically incorporates multiple sources of information. This novel framework reflects a high complexity in the neural representation of the attention-related information in the PFC, and how its computational organization predicts behavior.

Slow Drift of Neural Activity as a Signature of Impulsivity in Macaque Visual and Prefrontal Cortex

An animal's decision depends not only on incoming sensory evidence but also on its fluctuating internal state. This state embodies multiple cognitive factors, such as arousal and fatigue, but it is unclear how these factors influence the neural processes that encode sensory stimuli and form a decision. We discovered that, unprompted by task conditions, animals slowly shifted their likelihood of detecting stimulus changes over the timescale of tens of minutes. Neural population activity from visual area V4, as well as from prefrontal cortex, slowly drifted together with these behavioral fluctuations. We found that this slow drift, rather than altering the encoding of the sensory stimulus, acted as an impulsivity signal, overriding sensory evidence to dictate the final decision. Overall, this work uncovers an internal state embedded in population activity across multiple brain areas and sheds further light on how internal states contribute to the decision-making process.