A test of spatial temporal decoding mechanisms in the superior colliculus

Katnani, Husam A.; Opstal, A. John Van; Gandhi, Neeraj J.

doi:10.1152/jn.00992.2011

Cited by 18 publications

(21 citation statements)

References 48 publications

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“…1990). However, previous studies have demonstrated that suboptimal microstimulation can attenuate both kinematics and metrics (Groh 2011;Katnani et al 2012;Stanford et al 1996;Van Opstal et al 1990); moreover, our current study provides a systematic investigation of the differential effects of current intensity and frequency on movement-evoked properties. In this section, we explain our results by speculating on the spatiotemporal features of the overall activity produced during microstimulation.…”

Section: Neural Mechanisms Of Actionmentioning

confidence: 90%

“…Data of this nature can be beneficial when designing an experiment to test specific properties of a neural system or to test the predictions of a neural model. For example, within the oculomotor field, the input to output relationship characterized in this investigation provides a resource to challenge existing concepts and models that describe spatiotemporal motor decoding in the superior colliculus (Groh 2001;Katnani et al 2012). In addition, a well-developed neural field model of the collicular network trained on these microstimulation results could reveal emerging properties in the SC and provide insightful information on the mechanisms underlying saccade generation.…”

Section: Significance In the Scientific Settingmentioning

confidence: 99%

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The relative impact of microstimulation parameters on movement generation

Katnani

Gandhi

2012

Journal of Neurophysiology

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Microstimulation is widely used in neurophysiology to characterize brain areas with behavior and in clinical therapeutics to treat neurological disorder. Current intensity and frequency, which respectively influence activation patterns in spatial and temporal domains, are typically selected to elicit a desired response, but their effective influence on behavior has not been thoroughly examined. We delivered microstimulation to the primate superior colliculus while systematically varying each parameter to capture effects of a large range of parameter space. We found that frequency was more effective in driving output properties, whereas properties changed gradually with intensity. Interestingly, when different parameter combinations were matched for total charge, effects on behavioral properties became seemingly equivalent. This study provides a first level resource for choosing desired parameter ranges to effectively manipulate behavior. It also provides insights into interchangeability of parameters, which can assist clinical microstimulation that looks to appropriately control behavior within designated constraints, such as power consumption.

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Section: Neural Mechanisms Of Actionmentioning

confidence: 90%

Section: Significance In the Scientific Settingmentioning

confidence: 99%

The relative impact of microstimulation parameters on movement generation

Katnani

Gandhi

2012

Journal of Neurophysiology

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“…The vector summation with saturation (VSS) model proposes that the cumulative sum of the collicular output drives the BG until saturation constrains the sum and terminates the movement [23], [37], [38]. We recently concluded that the saturation function could be implemented in multiple ways, including intracollicular interactions and gating by the OPNs [13]. The blink manipulation in the present study explored this latter potential mechanism.…”

Section: Discussionmentioning

confidence: 88%

“…Behavioral paradigms as well as stimulation and reflex-blink procedures were similar to those described in previous papers [8], [12], [13]. Briefly, all animals were trained to perform the oculomotor gap task.…”

Section: Methodsmentioning

confidence: 99%

Blink Perturbation Effects on Saccades Evoked by Microstimulation of the Superior Colliculus

2012

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Current knowledge of saccade-blink interactions suggests that blinks have paradoxical effects on saccade generation. Blinks suppress saccade generation by attenuating the oculomotor drive command in structures like the superior colliculus (SC), but they also disinhibit the saccadic system by removing the potent inhibition of pontine omnipause neurons (OPNs). To better characterize these effects, we evoked the trigeminal blink reflex by delivering an air puff to one eye as saccades were evoked by sub-optimal stimulation of the SC. For every stimulation site, the peak and average velocities of stimulation with blink movements (SwBMs) were lower than stimulation-only saccades (SoMs), supporting the notion that the oculomotor drive is weakened in the presence of a blink. In contrast, the duration of the SwBMs was longer, consistent with the hypothesis that the blink-induced inhibition of the OPNs could prolong the window of time available for oculomotor commands to drive an eye movement. The amplitude of the SwBM could also be larger than the SoM amplitude obtained from the same site, particularly for cases in which blink-associated eye movements exhibited the slowest kinematics. The results are interpreted in terms of neural signatures of saccade-blink interactions.

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“…particular their adaptive time constants and lateral-interaction weightings specified by Eqns. [16][17]707 caused the peak firing rates of the cells to drop systematically along the rostral-to-caudal axis, while 708 keeping the total number of spikes constant (Fig. 5).…”

Section: Including Lateral Interactions 542 543mentioning

confidence: 99%

Microstimulation in a spiking neural network model of the midbrain superior colliculus

Opstal

Kasap

2018

Preprint

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13The midbrain superior colliculus (SC) generates a rapid saccadic eye movement to a sensory stimulus 14 by recruiting a population of cells in its topographically organized motor map. Supra-threshold 15 electrical microstimulation in the SC reveals that the site of stimulation produces a normometric 16 saccade vector with little effect of the stimulation parameters. Moreover, electrically evoked saccades 17 (E-saccades) have kinematic properties that strongly resemble natural, visual-evoked saccades (V-18 saccades). These findings support models in which the saccade vector is determined by a center-of-19 gravity computation of activated neurons, while its trajectory and kinematics arise from downstream 20 feedback circuits in the brainstem. Recent single-unit recordings, however, have indicated that the SC 21 population also specifies instantaneous kinematics. These results support an alternative model, in 22 which the desired saccade trajectory, including its kinematics, follows from instantaneous summation 23 Kasap and Van Opstal: Microstimulation in a spiking neural network model 2 of movement effects of all SC spike trains. But how to reconcile this model with microstimulation 24 results? Although it is thought that microstimulation activates a large population of SC neurons, the 25 mechanism through which it arises is unknown. We developed a spiking neural network model of the 26 SC, in which microstimulation directly activates a relatively small set of neurons around the electrode 27 tip, which subsequently sets up a large population response through lateral synaptic interactions. We 28 show that through this mechanism the population drives an E-saccade with near-normal kinematics 29 that are largely independent of the stimulation parameters. Only at very low stimulus intensities the 30 network recruits a population with low firing rates, resulting in abnormally slow saccades. 31 32 33 34 35 36 37 Author Summary 38 39 The midbrain Superior Colliculus (SC) contains a topographically organized map for rapid goal-40 directed gaze shifts, in which the location of the active population determines size and direction of the 41 eye-movement vector, and the neural firing rates specify the eye-movement kinematics. Electrical 42 microstimulation in this map produces eye movements that correspond to the site of stimulation with 43 normal kinematics. We here explain how intrinsic lateral interactions within the SC network of spiking 44 neurons sets up the population activity profile in response to local microstimulation to explain these 45 results. 46 47 48

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A test of spatial temporal decoding mechanisms in the superior colliculus

Cited by 18 publications

References 48 publications

The relative impact of microstimulation parameters on movement generation

The relative impact of microstimulation parameters on movement generation

Blink Perturbation Effects on Saccades Evoked by Microstimulation of the Superior Colliculus

Microstimulation in a spiking neural network model of the midbrain superior colliculus

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