Intensity- and timing-dependent modulation of motion perception with transcranial magnetic stimulation of visual cortex☆
Introduction
Transcranial magnetic stimulation (TMS) has become a valuable treatment option for a host of psychiatric and neurological disorders and a useful tool in the study of the psychophysiology of human cognition. The underlying neural mechanisms that lead to these effects, however, are relatively poorly understood. While a rich literature of studies now offer characterization of transient induced, and plastic long-term, effects of TMS in the motor system (Hallett et al., 2017; Pascual-Leone et al., 1995), systematic dose–response characterization in the visual system, including evaluation of the intensity and timing of stimulation effects, is limited.
TMS to the visual system can yield non-retinal perceptions, referred to as “phosphenes” for static flashes or “mophenes” if perceptual motion is induced (Pascual-Leone and Walsh, 2001; Schaeffner and Welchman, 2017), as well as modulation of perception from retinal input (de Graaf et al., 2014). Notably, single-pulse TMS (spTMS) and paired-pulse TMS (ppTMS) of the visual cortex have been widely reported to induce changes in the perception of visual motion (Bosco et al., 2008; Grasso et al., 2018; Laycock et al., 2007; Silvanto et al., 2005; Vetter et al., 2015). Across a number of studies, TMS to motion sensitive cortex has been shown to influence speed perception (Matthews et al., 2001) and direction sensitivity (Campana et al., 2002), as well as perception of biological motion (Mather et al., 2016). Despite this accumulation of literature, the relationship between the reported physiological response and the degree of behavioral engagement across these studies is highly variable, and the links between TMS parameters and their neurophysiological effects have yet to be established.
Studies of motion perception are particularly well-suited for exploring mechanisms of TMS due to the superficial location of motion sensitive cortex and its well-characterized spatiotemporal progression of electroencephalographic (EEG) activation described by the P1/N2/P3 Visual Evoked Potential (VEP) complex. In this progression, it is regarded that the initial P1 component reflects pattern-related activity of the parvo-cellular subsystem, while the subsequent N2 component has been associated with motion perceptual sensitivity (Bach and Ullrich, 1997; Kuba et al., 2007; Martin et al., 2010) and is localized to the direction-selective area V5 of the extra-striate visual cortex (Pazo-Álvarez et al., 2004). In lateralized visual attention tasks, this response has been characterized as pre-attentive in the early (<200 ms) phase, and specific to spatial attention after about 200 ms, as observed in the widely-reported N2pc component (Clark, Appelbaum, van den Berg, Mitroff and Woldorff, 2015; Luck and Hillyard, 1990). Lastly, in tasks where response selection is made on motion stimuli, a central positive P3 component is frequently observed around 300 ms (Kuba et al., 1998; Kubová et al., 2002) that is thought to reflect attentional allocation to the stimuli (Duncan-Johnson and Donchin, 1982). While other thalamo-cortical pathways also contribute to visual motion perception, these VEPs offer specific testable neural markers that can be characterized to infer dose–response properties of TMS.
The present study builds on these two bodies of literature, TMS modulation of motion perception and motion-induced VEPs, to characterize dose–response functions of spTMS in the visual cortex. Our approach was to measure concurrent TMS-EEG during an individually calibrated, dot-motion, direction-discrimination task, previously developed by our group to test ppTMS effects (Gamboa et al., 2020). For this purpose, we used a three-visit study design consisting of an initial dose-finding session to derive individualized motion coherence thresholds and stimulation parameters based on the onset of the N2 VEP component (“N2-Onset”), followed by two dose-testing sessions during which spTMS was delivered according to the spatial, temporal, and intensity parameters derived from the first session. During the dose-testing sessions, spTMS was delivered at one of two different timings, either 30 ms before the onset of motion (“Pre-Onset”, based on the observation that TMS to V5 around this latency can disrupt motion perception (Beckers and Homberg, 1992; Beckers and Zeki, 1995; D'Alfonso et al., 2002; Sack et al., 2006), or at the N2-Onset latency for each participant measured during the first session. During each of these two sessions, participants performed eight blocks of trials with intermixed pulse intensities at 0%, 80%, 100%, and 120% of resting motor threshold (RMT) delivered over the hotspot of the N2-Onset component, as well as two separate blocks of trials at 120% RMT delivered at the vertex of the head, therefore serving as a control location. As such, this study tested the effects of spTMS over intensities that have previously been reported to induce facilitatory and inhibitory perceptual effects (Luber et al., 2020; Silvanto et al., 2017), but at different timings relative to the motion onset and at different cortical targets. In addition, this approach includes use of two reference conditions, no-stimulation trials with 0% RMT intensity and 120% RMT delivered to the vertex, for experimental control.
The overall goal of the study was therefore to map the behavioral and evoked EEG dose–response functions within the constructs of this individualized spatiotemporal targeting. We had two complimentary hypotheses on the capacity of intensity-dependent TMS to affect changes in brain and behavior. Our first hypothesis was that spTMS delivered at the precise onset of the N2 component disrupts motion processes in the brain more than TMS simply delivered at the onset of motion, leading to monotonically increasing effects across different stimulation intensities due to the putative inhibitory effects of spTMS and state-dependency induced by the motion task. Our second hypothesis was that such precisely timed TMS would have significant effects on subsequent VEPs, such that while we did not expect to observe significant changes in the Pre-Onset condition, but we did anticipate reduced amplitude of the P3 component as a manifestation of processing interruptions from stimulation at the onset of the N2 response. We expected that the results of testing these hypotheses would contribute to a coherent neurocognitive framework in which to interpret the intensity-based responses to temporally- and spatially-precise TMS applications.
Section snippets
Participants
Twenty-four healthy volunteers (15 females, Mage = 23, SDage = 2.55) enrolled in this 3-visit study. All participants were self-reported right-handed, had normal or corrected-to-normal vision, and were screened for contraindications to TMS (Rossi et al., 2009). Exclusion criteria included a history of neurological or psychiatric disease and/or use of psychoactive medication, a personal history of head trauma with loss of consciousness or family history of epilepsy or seizures. Informed consent
RMT results
RMT was successfully derived for all participants through convergence of the adaptive Parameter Estimation by Sequential Testing (PEST) procedure (Borckardt et al., 2006). On average 63.6% of Maximum Stimulator Output (MSO) was required to induce the target EMG response at RMT with a range of 44%–83%, as reported in Table 1.
Accuracy and VEP results
As illustrated in Fig. 2A, participants performed the task at chance in trials that had no coherent movement (0%), with a monotonic increase in accuracy for higher coherence
Discussion
The current study investigated task-relevant dose–response functions of single pulse TMS by examining the influence of stimulation timing and intensity on electrophysiological and behavioral responses. Here, single pulse TMS was applied at two latencies relative to the onset of psychometrically calibrated, near-threshold, motion stimuli to assess the behavioral and electrophysiological changes due to TMS. It was hypothesized that stimulation would lead to greater behavioral disruption in motion
Funding
Funding was provided by the National Institute of Mental Health of the National Institutes of Health under BRAIN Initiative Award, RF1MH114253. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
CRediT authorship contribution statement
Olga Lucia Gamboa Arana: Conceptualization, Formal analysis, Investigation, Methodology, Writing - original draft, Writing - review & editing. Hannah Palmer: Data curation, Investigation, Writing - original draft, Writing - review & editing. Moritz Dannhauer: Conceptualization, Formal analysis, Methodology. Connor Hile: Data curation, Investigation. Sicong Liu: Formal analysis, Writing - review & editing. Rena Hamdan: Methodology. Alexandra Brito: Data curation, Investigation, Writing -
Acknowledgments:
The authors would like to thank Zachary Abzug, Lysianne Beynel, Tracy D'Arbeloff, Erik A. Wing, and Rachel Donaldson, who helped develop the behavioral task and Lari Koponen who help with the concurrent TMS-EEG protocols used in this research. The authors would also like to thank all of the individuals who participated in this research.
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2022, HeliyonCitation Excerpt :Stimulation was performed concurrently with EEG using a TMS compatible ActiChamp 64-channel amplifier system, coupled with an ActiCap Slim with active electrodes (BrainProducts, GmbH., Germany). While the use of active electrodes is relatively novel in the context of TMS-EEG, recent research has successfully used them to evaluate TMS evoked brain reactivity (to cite some, Gamboa Arana et al., 2020; Ozdemir et al., 2021b, 2021a, 2020; Redondo-Camós et al., 2022; Rocchi et al., 2021). Moreover, it has been recently shown that the TMS evoked potential waveforms are reliable and comparable to those obtained with passive electrodes (Mancuso et al., 2021), provided that interelectrode impedance is kept low.
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Disclosures: A.V.P. is inventor on patents and patent applications on TMS technology. Related to TMS, in the past 3 years he has received patent royalties from Rogue Research; research and travel support, consulting fees, and equipment donations from Tal Medical/Neurex Therapeutics; patent application and research support from Magstim; equipment loans and hardware donations from MagVenture; as well as consulting fees from Neuronetics.