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Boosting Learning Efficacy with Non-Invasive Brain Stimulation in Intact and Brain-Damaged Humans

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Boosting Learning Efficacy with Non-Invasive Brain Stimulation in Intact and Brain-Damaged Humans This Accepted Manuscript has not been copyedited and formatted. The final version may differ from this version. Research Articles: Behavioral/Cognitive Boosting learning efficacy with non-invasive brain stimulation in intact and brain-damaged humans F. Herpich1,2,3, F. Melnick, M.D.4 , S. Agosta1 , K.R. Huxlin4 , D. Tadin4 and L Battelli1,5,6 1Center for Neuroscience and Cognitive Systems@UniTn, Istituto Italiano di Tecnologia, Corso Bettini 31, 38068 Rovereto (TN), Italy 2Center for Mind/Brain Sciences, University of Trento, 38068 Rovereto, Italy 3kbo Klinikum-Inn-Salzach, Gabersee 7, 83512, Wasserburg am Inn, Germany 4Department of Brain and Cognitive Sciences, Flaum Eye Institute and Center for Visual Science, University of Rochester, Rochester, NY, USA 5Berenson-Allen Center for Noninvasive Brain Stimulation and Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, 02215 Massachusetts, USA 6Cognitive Neuropsychology Laboratory, Harvard University, Cambridge, MA, USA https://doi.org/10.1523/JNEUROSCI.3248-18.2019 Received: 28 December 2018 Revised: 10 April 2019 Accepted: 8 May 2019 Published: 27 May 2019 Author contributions: F.H., M.D.M., K.H., D.T., and L.B. designed research; F.H., M.D.M., and S.A. performed research; F.H., M.D.M., and D.T. analyzed data; F.H., M.D.M., and L.B. wrote the first draft of the paper; M.D.M., S.A., K.H., D.T., and L.B. edited the paper; K.H., D.T., and L.B. wrote the paper. Conflict of Interest: The authors declare no competing financial interests. The present study was funded by the Autonomous Province of Trento, Call “Grandi Progetti 2012”, project “Characterizing and improving brain mechanisms of attention — ATTEND (FH, SA, LB), “Fondazione Caritro — Bando Ricerca e Sviluppo Economico” (FH), NIH (DT, MM and KRH: R01 grants EY027314 and EY021209, CVS training grant T32 EY007125), and by an unrestricted grant from the Research to Prevent Blindness (RPB) Foundation to the Flaum Eye Institute. We thank Valeria Piombino for data collection with neurological patients. Corresponding Author: Lorella Battelli: [email protected] Cite as: J. Neurosci 2019; 10.1523/JNEUROSCI.3248-18.2019 Alerts: Sign up at www.jneurosci.org/alerts to receive customized email alerts when the fully formatted version of this article is published. Accepted manuscripts are peer-reviewed but have not been through the copyediting, formatting, or proofreading process. Copyright © 2019 the authors 1 Boosting learning efficacy with non-invasive brain stimulation in intact and 2 brain-damaged humans 3 4 5 Herpich1,2,3, F., Melnick4, M.D., Agosta1, S., Huxlin4*, K.R., Tadin4*, D. and Battelli1,5,6*, 6 L. 7 8 1Center for Neuroscience and Cognitive Systems@UniTn, Istituto Italiano di Tecnologia, 9 Corso Bettini 31, 38068 Rovereto (TN), Italy 10 2Center for Mind/Brain Sciences, University of Trento, 38068 Rovereto, Italy 11 3kbo Klinikum-Inn-Salzach, Gabersee 7, 83512, Wasserburg am Inn, Germany 12 4Department of Brain and Cognitive Sciences, Flaum Eye Institute and Center for Visual 13 Science, University of Rochester, Rochester, NY, USA 14 5Berenson-Allen Center for Noninvasive Brain Stimulation and Department of 15 Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, 16 02215 Massachusetts, USA 17 6Cognitive Neuropsychology Laboratory, Harvard University, Cambridge, MA, USA 18 19 * equal senior authors 20 21 Corresponding Author: Lorella Battelli: [email protected] 22 23 24 Abstract 25 26 Numerous behavioral studies have shown that visual function can improve with training, 27 although perceptual refinements generally require weeks to months of training to attain. 28 This, along with questions about long-term retention of learning, limits practical and 29 clinical applications of many such paradigms. Here, we show for the first time in female 30 and male human participants that just 10 days of visual training coupled with transcranial 31 random noise stimulation (tRNS) over visual areas causes dramatic improvements in 32 visual motion perception. Relative to control conditions and anodal stimulation, tRNS- 33 enhanced learning was at least twice as fast, and, crucially, it persisted for 6 months 34 after the end of training and stimulation. Notably, tRNS also boosted learning in patients 35 with chronic cortical blindness, leading to recovery of motion processing in the blind field 36 after just 10 days of training, a period too short to elicit enhancements with training 37 alone. In sum, our results reveal a remarkable enhancement of the capacity for long- 38 lasting plastic and restorative changes when a neuromodulatory intervention is coupled 39 with visual training. 40 41 2 42 Significance Statement 43 Our work demonstrates that visual training coupled with brain stimulation can 44 dramatically reduce the training period from months to weeks, and lead to fast 45 improvement in neurotypicals and chronic cortically blind patients, indicating the 46 potential of our procedure to help restore damaged visual abilities for currently 47 untreatable visual dysfunctions. Together, these results indicate the critical role of early 48 visual areas in perceptual learning and reveal its capacity for long lasting plastic 49 changes promoted by neuromodulatory intervention. 50 3 51 Introduction 52 The human brain changes throughout life (Gilbert & Li, 2012; Liat al., 2004). Visual 53 training is a well-known tool for inducing such changes, improving sensory performance 54 in healthy adults (Dosher & Lu, 2017; Li, 2016; Sagi, 2011; Wang et al., 2016); and in 55 various clinical populations (Deveau et al., 2013; Melnick et al., 2016; Nyquist et al., 56 2016), a phenomenon referred to as visual perceptual learning (VPL). The specific role 57 of different cortical visual areas during VPL is still openly debated, with several 58 mechanisms likely contributing to learning. For instance, neurophysiological studies 59 have shown that perceptual learning selectively modifies the signal strength of neurons 60 responding to relevant stimulus features, while concurrently suppressing the activity of 61 task irrelevant information (Yan et al., 2014). Other studies suggest that learning stems 62 from better read-out mechanisms in higher-level visual areas (Law & Gold, 2009). 63 Psychophysical studies have suggested that boosting sub-threshold, stimulus-related 64 cortical activity can promote perceptual learning (Seitz & Dinse, 2007), with attention and 65 reinforcement (provided by reward) increasing stimulus-related neuronal activity and 66 facilitating learning (Ahissar, 2001; Pascucci et al., 2015; Seitz & Watanabe, 2005). 67 In parallel, increasing effort is being directed at applying visual perceptual 68 training approaches to rehabilitate patients with various types of vision loss, including 69 cortical blindness (CB), amblyopia (Huang et al., 2008; Levi & Li, 2009; Li et al., 2013; Li 70 et al., 2011; Polat et al., 2004), macular degeneration (Baker et al., 2008; Kwon et al., 71 2012; Liu et al., 2007), myopia (Camilleri et al., 2014; Tan & Fong, 2008) and even 72 keratoconus (Sabesan et al., 2017). Two critical factors that limit practical applications of 73 VPL are: 1) the long duration of training usually required for adequate performance 74 enhancement (e.g. in chronic CB patients, Huxlin et al., 2009), and 2) persistence of 75 visual learning and/or recovered abilities after training ends. Non-invasive brain 76 stimulation coupled with perceptual training has emerged as a potentially promising 77 solution for both of these limitations in healthy adults (Cappelletti et al., 2013; Chesters 78 et al., 2017; Falcone et al., 2012; Fertonani et al., 2011; Sehm et al., 2013; Snowball et 4 79 al., 2013; Zoefel & Davis, 2017). 80 In CB, a form of vision loss caused by primary visual cortex (V1) damage, one 81 approach shown to recover vision involves training on motion integration tasks in the 82 blind field (Figure 1; Cavanaugh & Huxlin, 2017; Das et al., 2014; Huxlin et al., 2009; 83 Vaina et al., 2014). However, the training required to restore normal performance on this 84 task in the blind field of CB patients typically involves months of daily practice, and is 85 thus difficult to attain and sustain. As such, this represents an ideal task with which to 86 ask whether non-invasive brain stimulation of early visual cortex during training can 87 enhance and speed up the resultant perceptual learning. 88 We used two forms of direct current stimulation to modulate cortical functioning 89 and boost performance during learning: transcranial random noise (tRNS) and anodal 90 direct current stimulation (a-tDCS). 91 tRNS was first shown to enhance cortical excitability in the motor cortex (Terney 92 et al., 2008) and subsequent studies reported that it can improve perceptual functions 93 when delivered over the visual cortex (Campana et al., 2014; Pirulli et al., 2013; Tyler et 94 al., 2018; van der Groen et al., 2018), while the effect of a-tDCS is less clear (Miniussi & 95 Ruzzoli, 2013; Ding et al., 2013). 96 The present experiments asked if brain stimulation could improve visual learning 97 when administered during training in visually-intact humans and whether these 98 improvements persist. We then examined the translational potential of this approach to 99 promote visual recovery in chronic CB patients. Early visual areas of the brain were 100 targeted for stimulation because of their apparent role in mediating training-induced 101 visual plasticity in physiological, imaging and brain stimulation studies (Barbot et al., 102 2018; Camilleri et al., 2016; Gratton et al., 2017; Kang et al., 2014; Rokem & Silver, 103 2010; Schwartz et al., 2002; Yang & Maunsell, 2003). 104 105 5 106 Materials and Methods 107 Experiment 1: tRNS-mediated learning in healthy participants 108 Regulatory approval 109 The study was approved by the ethical committee of the University of Trento. 110 111 Subjects 112 A total of 45 subjects participated in the experiment (mean age: 19.9 years old; range: 113 19-36; 32 females and 13 males).
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