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      Robust neuronal dynamics in premotor cortex during motor planning

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          Abstract

          Neural activity maintains representations that bridge past and future events, often over many seconds. Network models can produce persistent and ramping activity, but the positive feedback that is critical for these slow dynamics can cause sensitivity to perturbations. Here we use electrophysiology and optogenetic perturbations in mouse premotor cortex to probe robustness of persistent neural representations during motor planning. Preparatory activity is remarkably robust to large-scale unilateral silencing: detailed neural dynamics that drive specific future movements were quickly and selectively restored by the network. Selectivity did not recover after bilateral silencing of premotor cortex. Perturbations to one hemisphere are thus corrected by information from the other hemisphere. Corpus callosum bisections demonstrated that premotor cortex hemispheres can maintain preparatory activity independently. Redundancy across selectively coupled modules, as we observed in premotor cortex, is a hallmark of robust control systems. Network models incorporating these principles show robustness that is consistent with data.

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          Most cited references46

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          Mnemonic coding of visual space in the monkey's dorsolateral prefrontal cortex.

          1. An oculomotor delayed-response task was used to examine the spatial memory functions of neurons in primate prefrontal cortex. Monkeys were trained to fixate a central spot during a brief presentation (0.5 s) of a peripheral cue and throughout a subsequent delay period (1-6 s), and then, upon the extinction of the fixation target, to make a saccadic eye movement to where the cue had been presented. Cues were usually presented in one of eight different locations separated by 45 degrees. This task thus requires monkeys to direct their gaze to the location of a remembered visual cue, controls the retinal coordinates of the visual cues, controls the monkey's oculomotor behavior during the delay period, and also allows precise measurement of the timing and direction of the relevant behavioral responses. 2. Recordings were obtained from 288 neurons in the prefrontal cortex within and surrounding the principal sulcus (PS) while monkeys performed this task. An additional 31 neurons in the frontal eye fields (FEF) region within and near the anterior bank of the arcuate sulcus were also studied. 3. Of the 288 PS neurons, 170 exhibited task-related activity during at least one phase of this task and, of these, 87 showed significant excitation or inhibition of activity during the delay period relative to activity during the intertrial interval. 4. Delay period activity was classified as directional for 79% of these 87 neurons in that significant responses only occurred following cues located over a certain range of visual field directions and were weak or absent for other cue directions. The remaining 21% were omnidirectional, i.e., showed comparable delay period activity for all visual field locations tested. Directional preferences, or lack thereof, were maintained across different delay intervals (1-6 s). 5. For 50 of the 87 PS neurons, activity during the delay period was significantly elevated above the neuron's spontaneous rate for at least one cue location; for the remaining 37 neurons only inhibitory delay period activity was seen. Nearly all (92%) neurons with excitatory delay period activity were directional and few (8%) were omnidirectional. Most (62%) neurons with purely inhibitory delay period activity were directional, but a substantial minority (38%) was omnidirectional. 6. Fifteen of the neurons with excitatory directional delay period activity also had significant inhibitory delay period activity for other cue directions. These inhibitory responses were usually strongest for, or centered about, cue directions roughly opposite those optimal for excitatory responses.(ABSTRACT TRUNCATED AT 400 WORDS)
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            Generating coherent patterns of activity from chaotic neural networks.

            Neural circuits display complex activity patterns both spontaneously and when responding to a stimulus or generating a motor output. How are these two forms of activity related? We develop a procedure called FORCE learning for modifying synaptic strengths either external to or within a model neural network to change chaotic spontaneous activity into a wide variety of desired activity patterns. FORCE learning works even though the networks we train are spontaneously chaotic and we leave feedback loops intact and unclamped during learning. Using this approach, we construct networks that produce a wide variety of complex output patterns, input-output transformations that require memory, multiple outputs that can be switched by control inputs, and motor patterns matching human motion capture data. Our results reproduce data on premovement activity in motor and premotor cortex, and suggest that synaptic plasticity may be a more rapid and powerful modulator of network activity than generally appreciated.
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              Synaptic reverberation underlying mnemonic persistent activity.

              Stimulus-specific persistent neural activity is the neural process underlying active (working) memory. Since its discovery 30 years ago, mnemonic activity has been hypothesized to be sustained by synaptic reverberation in a recurrent circuit. Recently, experimental and modeling work has begun to test the reverberation hypothesis at the cellular level. Moreover, theory has been developed to describe memory storage of an analog stimulus (such as spatial location or eye position), in terms of continuous 'bump attractors' and 'line attractors'. This review summarizes new studies, and discusses insights and predictions from biophysically based models. The stability of a working memory network is recognized as a serious problem; stability can be achieved if reverberation is largely mediated by NMDA receptors at recurrent synapses.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                13 March 2016
                13 April 2016
                28 April 2016
                27 October 2016
                : 532
                : 7600
                : 459-464
                Affiliations
                Janelia Research Campus, HHMI, Ashburn VA 20147
                Author notes
                [*]

                co-first author

                [# ] corresponding author Karel Svoboda, Janelia Research Campus, HHMI, 19700 Helix Drive, Ashburn, VA 20147, svobodak@ 123456janelia.hhmi.org ., Shaul Druckmann, Janelia Research Campus, HHMI, 19700 Helix Drive, Ashburn, VA 20147, druckmanns@ 123456janelia.hhmi.org .
                Article
                HHMIMS767125
                10.1038/nature17643
                5081260
                27074502
                e3907967-5139-48f3-8753-d0e9668dc353

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