5 research outputs found

    Visual salience of the stop signal affects the neuronal dynamics of controlled inhibition

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    The voluntary control of movement is often tested by using the countermanding, or stop-signal task that sporadically requires the suppression of a movement in response to an incoming stop-signal. Neurophysiological recordings in monkeys engaged in the countermanding task have shown that dorsal premotor cortex (PMd) is implicated in movement control. An open question is whether and how the perceptual demands inherent the stop-signal affects inhibitory performance and their underlying neuronal correlates. To this aim we recorded multi-unit activity (MUA) from the PMd of two male monkeys performing a countermanding task in which the salience of the stop-signals was modulated. Consistently to what has been observed in humans, we found that less salient stimuli worsened the inhibitory performance. At the neuronal level, these behavioral results were subtended by the following modulations: when the stop-signal was not noticeable compared to the salient condition the preparatory neuronal activity in PMd started to be affected later and with a less sharp dynamic. This neuronal pattern is probably the consequence of a less efficient inhibitory command useful to interrupt the neural dynamic that supports movement generation in PMd

    The small scale functional topology of movement control: Hierarchical organization of local activity anticipates movement generation in the premotor cortex of primates.

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    How neurons coordinate their collective activity for behavioural control is an open question in neuroscience. Several studies have progressively proven, on various scales, that the patterns of neural synchronization change accordingly with behavioural events. However, the topological features of the neural dynamics that underlie task-based cognitive decisions on the small scale level are not understood. We analysed the multiunit activity (MUA) from a multielectrode (96 channels) array of the dorsal premotor cortex (PMd) in rhesus monkeys during a countermanding reaching task. Within the framework of graph theory, we found that in the local PMd network motor execution is preceded by the emergence of hubs of anti-correlation that are organized in a hierarchical manner. Conversely, this organization is absent when monkeys correctly inhibit programmed movements. Thus, we interpret the presence of hubs as reflecting the readiness of the motor plan and the irrevocable signature of the onset of the incoming movement

    Persistence of cortical neuronal activity in the dying brain

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    We report the presence of cortical electrical activity persisting for about 120 min after cardiac arrest. The general consensus is that interruption of brain blood flow triggers a chain of electrophysiological phenomena: oscillatory activity rises in the first tens of seconds [1], followed by a depression of both oscillatory and spiking activities, and then by a slow spreading depolarization due to the beginning of irreversible degenerative processes at the cellular level [2–4]. The spreading depolarization is characterized by direct current changes that can last up to tens of minutes and it has been described by using coarsegrained electroencephalography and electrocorticography measures. As such, low-amplitude and faster local phenomena might have been missed. To address whether some brain activity at a microscale can persist for longer periods after cardiac arrest, we recorded the intraparenchymal activity in the frontal cortex of an adult male macaque monkey using a multi-electrode miniaturized array to monitor neuronal activities during the standard end of a protocol-established euthanasia procedure. Both local field potentials (LFPs) and multi-unit activities (MUAs) [5] were recorded starting from the deep sedated state (induction by ketamine and medetomidine hydrochloride; mixture isoflurane/oxygen to effect), and well beyond the cardiorespiratory arrest caused by the intravascular bolus injection of pentothal sodium. During the initial deep anaesthesia stage, neuronal activity displayed the typical burst suppression regime with irregular LFP and MUA oscillations (Fig. 1a-b). This activity strongly reduced after cardiac arrest (Fig. 1c). However, after about 20 min, bursts of LFPs re-emerged sparse in time up to about 120 min, each displaying a peak of power at 1–3 Hz in the Fourier spectrograms. Importantly, these bursts were accompanied by a supra- and subthreshold MUA modulations giving rise to a significant time-delayed LFP-MUA coupling (see Fig. 1d). Although confined to a single subject, our results prove that the dying brain at the microscale can show electrophysiological activity for long time after cardiac arrest. Importantly, this activity appears after a period of relative silence and it is characterized by a peculiar temporal relationship between LFP and MUA in several electrodes suggesting a non-local origin. This would require a common synaptic input which in principle could be provided by brainstem structures that are typically more resistant to anoxia [4]. We think that our data contribute in posing fundamental questions about the nature of the transition to the death state. For example, what is the metabolic state associated with this process? Can spontaneous (or artificially induced) enhanced neuromodulation be of help in augmenting the resilience to global ischemia? Our finding outlines the importance of investigating the neurobiology of dying with intraparenchymal high-resolution approaches. This could help in addressing central medical questions like the definition of death, the proper timing and the adequate sedation for organ transplantation, and the development of resuscitation and recovery procedures. Whether this activity is a sign of intact brain processing needs further studies

    Neuronal correlates of motivated inhibition in monkey motor cortices

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    The ability to rapidly inhibit actions is critical to the effective and flexible interactions with the environment, and it has been widely studied by using the countermanding (stop-signal) task. An open question is how this ability can be affected by other cognitive functions, such as motivation, and relatedly, which are the neural correlates of this influence. To address this question we designed a combined countermanding/motivation task intended to modulate the motivation to stop and to move by using the reward prospect, and we recorded the Multi-Unit Activity (MUA) by means of Utah arrays (2x48 channels) from the dorsal premotor cortex (PMd) and the primary motor cortex (M1) of a macaque monkey while engaged in the task. Indeed previous data have shown that motor cortices neuronal activity signals both movement inhibition (Mattia et al., 2013) and reward (Roesch and Olson, 2004), but it is unclear whether and how these phenomena are combined. In the countermanding/motivation task, the monkey was instructed to reach to a target after a go signal (no-stop trials) but to withhold his response when a stop-signal followed after a variable delay (stop trials). In every trial, one out of three possible reward cues (RC) was presented 1 sec before the go signal to inform about the amount of reward that would have been delivered if a correct response had been produced. RC conditions were: Go+Stop- with a higher reward for no-stop trials compared to the stop trials; Go-Stop+, with reversed reward amounts; and Go Stop with equal amounts delivered. We found that the monkey strategically adapted his behavior to the different reward prospects: reaction times (RTs) diminished and the probability of errors in the stop trials increased from Go-Stop+, to Go Stop and then to Go+Stop- conditions. Recorded MUA in both PMd and M1 was modulated by task conditions. In some channels (22/96), MUA was significantly modulated before go signal by the RC value. Of these channels, 41% showed a progressive increase of MUA after the RC presentation until movement onset; this activity was progressively higher for Go-Stop+, Go Stop and Go+Stop-. Fifty-five percent showed a decrease during the RT epoch and a further increase of MUA just before or after movement onset. Others channels (48/96) showed RC related modulations around movement onset and/or after reaching the final target but not before go signal. Interestingly, in correct stop trials, some of the channels showed an early stop-signal response which magnitude was affected by the RC value. These results suggest that motor cortices can signal and integrate motivational aspects into movement control and inhibition

    Effect of Motivation on Movement Control: Neural Correlates in Dorsal Premotor Cortex

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    The dorsal premotor cortex (PMd) is a brain area involved in the control of movement. An open question is how the motivation can modulate this function. We trained a macaque monkey to a modified version of the countermanding task, in which Go trials (~65%) require to make a movement after a go signal, while Stop trials (~35%) require to inhibit the reactive movement after a stop signal. In each trial, an initial cue (1000 msec delay) informed about the potential amount of reward that would have been delivered if a correct response would have been produced. The meaning of the cue for correct responses was different. In the Go+Stop- condition the cue indicated more reward for the Go trials and less reward for the Stop trials. The opposite was in the Go-Stop+ condition. The cue was not informative (neutral) for the GoStop condition. We found that the monkey adapted his behavior to the cue value: faster reaction times in Go trials and higher error rate in Stop trials diminished from Go+Stop-, to GoStop and then to Go-Stop+ conditions. In PMd we found that 43/74 neurons recorded distinguished between conditions: some of them started to differentiate between conditions after 500msec from the cue, others close to the go signal. Seventeen/43 neurons were directly involved in movement control and showed different responses to the stop signal presentation depending on the cue presented. These data suggest that in PMd motivational information is integrated into neural mechanism of movement control by a heterogeneous dynamic
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