Activation of Overlapping but not Identical Frontal and Parietal Regions by Saccadic Eye Movement and Overt Spatial Attention Tasks

1. We studied neuronal activity in the supplementary eye field (SEF) and frontal eye field (FEF) of a monkey during performance of a conditional motor task that required capturing of a target either with a saccadic eye movement (the saccade-only condition) or with an eye-hand reach (the saccade-and-reach condition), according to visual instructions. 2. Among 106 SEF neurons that showed presaccadic activity, more than one-half of them (54%) were active preferentially under the saccade-only condition (n = 12) or under the saccade-and-reach condition (n = 45), while the remaining 49 neurons were equally active in both conditions. 3. By contrast, most (97%) of the 109 neurons in the FEF exhibited approximately equal activity in relation to saccades under the two conditions. 4. The present results suggest the possibility that SEF neurons, at least in part, are involved in signaling whether the motor task is oculomotor or combined eye-arm movements, whereas FEF neurons are mostly related to oculomotor control.

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Does frontal normality exist in schizophrenia? A saccadic eye movement study

Psychiatry Research ◽

10.1016/s0165-1781(01)00275-x ◽

2001 ◽

Vol 103 (2-3) ◽

pp. 167-178 ◽

Cited By ~ 19

Author(s):

Annelies Broerse ◽

Esther A.E Holthausen ◽

Robert J van den Bosch ◽

Johan A den Boer

Keyword(s):

Eye Movement ◽

Saccadic Eye Movement ◽

Movement Study

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A dynamic, imperturbable link between midbrain activity and saccade velocity

Journal of Neurophysiology ◽

10.1152/jn.00328.2019 ◽

2020 ◽

Vol 123 (2) ◽

pp. 451-453

Author(s):

Joshua A. Seideman

Keyword(s):

Eye Movement ◽

Strong Evidence ◽

Neural Control ◽

Oculomotor Control ◽

Saccadic Eye Movement ◽

Saccade Velocity ◽

Midbrain Structure ◽

Instantaneous Control ◽

Dynamic Moment

We make a saccadic eye movement once every few hundred milliseconds; however, the neural control of saccade execution is not fully understood. Dynamic, moment-by-moment variations in saccade velocity are typically thought to be controlled by neurons in the lower, but not the upper regions of the brainstem. In a recent report, Smalianchuk et al. (Smalianchuk I, Jagadisan UK, Gandhi NJ. J Neurosci 38: 10156–10167, 2018) provided strong evidence for a role of the superior colliculus, a midbrain structure, in the instantaneous control of saccade velocity, suggesting the revision of long-standing models of oculomotor control.

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Floating-Gate Circuits for Adaptation of Saccadic Eye Movement Accuracy

The Springer International Series in Engineering and Computer Science - Neuromorphic Systems Engineering ◽

10.1007/978-0-585-28001-1_7 ◽

2007 ◽

pp. 175-189

Author(s):

Timothy K. Horiuchi ◽

Christof Koch

Keyword(s):

Eye Movement ◽

Floating Gate ◽

Saccadic Eye Movement ◽

Movement Accuracy

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Revisiting Persistent Neuronal Activity During Covert Spatial Attention

Frontiers in Neural Circuits ◽

10.3389/fncir.2021.679796 ◽

2021 ◽

Vol 15 ◽

Author(s):

Julian L. Amengual ◽

Suliann Ben Hamed

Keyword(s):

Spatial Attention ◽

Neural Representation ◽

Persistent Activity ◽

Sources Of Information ◽

Multiple Sources ◽

Oscillatory Dynamics ◽

Attention Orienting ◽

Related Information ◽

Attention Tasks ◽

Reduction Methods

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.

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