Cortical Information Flow During Flexible Sensorimotor Decisions

By Markus Siegel, Timothy J. Buschman, Earl K. Miller. 2015

437 citations recorded by the source corpus.

Signal flow during sensorimotor choices Little is known about the flow of task signals across the brain. Siegel et al. simultaneously recorded from multiple units in the sensory, parietal, prefrontal, and motor cortex while monkeys were cued to perform one among two possible simple tasks. The proportion of neurons coding for stimuli, cues, tasks, and choices, and their response latency, varied across regions. Parietal and prefrontal brain regions encoded task information and choices with the same latency. Interestingly, all brain areas encoded all types of information. However, they differed functionally according to the proportions of neurons and their response latency. Science, this issue p. 1352 A dynamic network of cortical areas processing similar information but to different degrees is explored. During flexible behavior, multiple brain regions encode sensory inputs, the current task, and choices. It remains unclear how these signals evolve. We simultaneously recorded neuronal activity from six cortical regions [middle temporal area (MT), visual area four (V4), inferior temporal cortex (IT), lateral intraparietal area (LIP), prefrontal cortex (PFC), and frontal eye fields (FEF)] of monkeys reporting the color or motion of stimuli. After a transient bottom-up sweep, there was a top-down flow of sustained task information from frontoparietal to visual cortex. Sensory information flowed from visual to parietal and prefrontal cortex. Choice signals developed simultaneously in frontoparietal regions and travelled to FEF and sensory cortex. This suggests that flexible sensorimotor choices emerge in a frontoparietal network from the integration of opposite flows of sensory and task information.

Subfields: Cognitive Neuroscience

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Citations in the corpus

Learning Rapid-Temporal Adaptations (2017, background): “Neuroscientific evidence suggests that PFC uses incoming information to support task-specific temporal adaptation and planning [38, 35, 22, 5].”
Working Memory 2.0 (2018, background): “They are also the cortical areas where top-down and bottom-up information reaches apex (Brincat et al., 2018; Siegel et al., 2015) and thus could support domain-general cognitive operations (Haller et al.”
Navigating the Neural Space in Search of the Neural Code. (2017, neutral): “…Laurent et al., 2001; Lo and Wang, 2006; Mante et al., 2013; Ma et al., 2006; Moore and Armstrong, 2003; Raposo et al., 2014; Rigotti et al., 2013; Siegel et al., 2015; Znamenskiy and Zador, 2013), and they are thus difficult to explore by searching through the combinatorial space of possible…”
Dopamine and Cognitive Control in Prefrontal Cortex. (2019, background): “For example, in visual detection tasks that require a monkey to make a binary decision about the absence or presence of a stimulus, PFC neurons signal the stimulus-present or stimulus-absent percept of the subject rather than the properties of the physical stimulus [3,5,64,65].”
Rapid Adaptation with Conditionally Shifted Neurons (2017, background): “Neuroscientific evidence suggests that these areas use incoming information to support task-specific temporal adaptation and planning (Stokes et al., 2013; Siegel et al., 2015; Miller & Buschman, 2015; Brincat & Miller, 2016).”
The representation of abstract goals in working memory is supported by task-congruent neural geometry (2024, unknown): “Neural activity in frontal cortex has also been found to preferentially encode higher-order, abstract representations of task contingencies [13], contexts [14], rules, or goals [15–17], providing top-down control signals that target stimulus representations in downstream brain regions [10,18].”