Modulation of the visual cortex by non invasive brain stimulation

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The Government of the Russian federation

Federal State Autonomous Educational Institution of Higher Professional Education

National Research University-Higher School of Economics

Faculty of Social Sciences, School of Psychology,

Master's program

“Cognitive sciences and technologies: from neuron to cognition”

Final qualifying work - MASTER THESIS

«Modulation of the visual cortex by Non Invasive brain stimulation»

Nieto Doval



Chapter 1. Introduction

On this research we focus on the investigation of modulation of brain excitability, using the internally generated visual effect, socalled phosphenes as a measure of visual awareness.

For this purpose, we decided to target the primary visual cortex (V1) by using Transcranial Magnetic Stimulation (TMS) and Transcranial Direct Current Stimulation (tDCS) aiming to develop a useful neuromodulatory protocol to disentangle the actual controversies of the current literature and to explore potential effects of the manipulation of the visual cortex for future clinical application. Therefore, we will adopt a new tDCS electrode montage supported by modelling software simulation of the distribution of the electrical field on the scalp in order to target V1 with a specific focus (Thielscher, Antunes, and Saturnino, 2015).

Understanding the mechanisms of action of tDCS in modulation of cortical excitation/inhibition balance, which means manipulation of neuroplasticity of the brain, will help us improve and extend its application for cognitive enhancement and neurorehabilitation in both cognitive and clinical fields.



Chapter 2. Visual Awareness

2.1 Visual Awareness and Confounders

Modulation of visual awareness represents the target of the current project. Here, we address the concept of visual awareness, its relation and entanglement with other similar concepts (visual perception/attention), and their neural correlates. All of this, must be framed on its actual conception, with all its limits and keeping in mind the difficulty to define these concepts that have been source of discussion for long time and through different fields likewise philosophy, psychology and psychophysics.

Awareness and attention have been considered the same process for long time and even nowadays we are still defining their boundaries, differences and similarities.

In the recent decades, several studies have focused on this dichotomy, showing that attending a stimulus do not imply necessarily awareness. Hsieh, Colas & Kanwisher (2011) found that conscious visual awareness of a feature is not necessary to attract attention, pointing that cognitive processes of awareness and attention are, in some way, independent.

As an example of the intricate of these two concepts we can refer to Lamme words "attention does not determine whether stimuli reach a conscious state butdetermines whether a (conscious) report about stimuli is possible" (Lamme, 2003, p.13) and his examples of possible models of awareness-attention interaction (Figure 1).



Figure 1. "Four models of visual awareness and its relation to attention" (Lamme, 2003)

Bibliography regarding this topic is very extensive and with a lot of sources for consulting. But we will focus on the topic that is matter of our concern, visual awareness and its neural correlations.

2.2 Visual Awareness and Neural Correlations

Here we face another time an extensive discussion about the neurophysiological bases of vision involved in awareness.

Some image studies have defended the idea that visual consciousness rely on the activation of visual areas beyond V1, dissociating V1 activation from awareness (Muckli et al., 2002; Moutoussis, Keliris, Kourtzi & Logothetis, 2005). While other studies defend the role of V1 on awareness (Lennie, 1998; Tong & Engle, 2001). On this regarding, other studies argued that the correlations of neural activation of V1 are just a consequence of feedback from activation of higher order areas, even when there is no conscious perception (Moutoussis & Zeki, 2002, 2006).

Due to these different results, actual evidence point to an interaction of several visual areas and parietal and frontal cortex (like V1, V5, V4, Frontal Eye Field and so on) as needed to raise visual awareness. As Rees (2007) wrote on a review, the actual evidence suggests that the conditions necessary and sufficient for awareness, involve the activation, on V1 and ventral visual areas, of a distributed representation of the visual scene and also activity of frontal and parietal areas. Lamme (2000) defended the same idea. While neural activation in specific brain areas is not enough to raise awareness, horizontal and feedback connections, sources of recurrent processing, are necessary to have awareness. Because none of visual areas (V1, extrastriate areas or areas of ventral and dorsal streams) is sufficient by itself to generate visual awareness (Lamme, Supиr, Landman, Roelfsema & Spekreijse, 2000).

These proposals work on the basis of cycles of mutual activation (bottom-up and top-down processes) as sufficient and necessary for consciousness. As shown by Pascual-Leone and Walsh (2001), where they used TMS to probe that the timing and function of the back-projection from MT+/V5 to V1 is critical for awareness of movement.

Despite not being part of visual cortex, frontal and parietal cortex have shown to play a key role in visual awareness. Mostly due to cases of deficiency in visual awareness as consequences of damage on these areas (visual neglect).

Experiments following this idea have shown the importance of the signals from prefrontal and parietal cortex for normal conscious perception (Driver & Mattingley, 1998). Also, direct evidence of it comes from the use of non-Invasive brain stimulation techniques (NIBS), more specifically by using transcranial magnetic stimulation (TMS) to disrupt frontal and parietal cortex, what produces impairment of conscious detection of change (Turatto, Sandrini & Miniussi, 2004; Beck, Muggleton, Walsh & Lavie, 2006).

The results of these studies indicate a role of the parietal and prefrontal cortex in visual awareness, but are not enough to precise their functional roles or to clarify how these neural processes work.



Chapter 3. Non-Invasive Brain Stimulation (NIBS)

3.1 General Characteristics and Applications

There are several types of brain stimulation techniques: transcranial Electrical Stimulation (tES) and Transcranial Magnetic stimulation (TMS), to most unusual or early developed like Transcranial Focused Ultrasound (FUS) and Transcranial Optogenetic Stimulation (TOS).

During the next paragraphs we will discuss deeper about tES and TMS, since these are the tools that we used for the completion of the current project.

NIBS techniques can be used from clinical to research purposes, allowing us to perform diagnostics; interventions on neurophysiology, modulating cortical and subcortical networks and inducing controlled behavioural manipulations; and focal neuropharmacology, by inducing focal gene expression and releasing of neurotransmitters (Boes et al., 2018; Obeso, Oliviero, & Jahanshahi, 2016; Ridding & Ziemann, 2010; Wagner, Valero-Cabre, & Pascual-Leone, 2007).

NIBS techniques allow us to study cognitive processes by identifying brain regions involved, and how these regions are involved, when we stimulate them. To understand how the brain works, NIBS allow us to transitory modulate neural activity through different kinds of stimulations, what has as consequence facilitatory or inhibitory behavioural effects (Miniussi, Harris & Ruzzoli, 2013).

However, the mechanisms about how these stimulation techniques work to modulate brain activity (physics, action mechanisms, electrophysiological bases,...) are still only known till some extent.

The application of NIBS is present for both research and clinical purpose.

For instance, NIBS is used to treat psychiatric disorders (mood disorders, schizophrenia, anxiety disorders, drug abuse,...), neurologic diseases (epilepsy, some degenerative diseases,...), stroke and aphasia rehabilitation, and pain syndromes (Wagner, Valero-Cabre, & Pascual-Leone, 2007; Rossini et al., 2015; Obeso,Oliviero, & Jahanshahi, 2016; Boes, Kelly, Trapp, Stern, Press, & Pascual-Leone, 2018).

NIBS techniques that are more commonly used, are transcranial direct current stimulation (tDCS) (purely neuromodulatory), and transcranial magnetic stimulation (TMS) (neuromodulation and neurostimulation). In the following paragraphs, we will describe in more details the action mechanisms of these techniques, how do they work and their common applications and effects.

For the study of NIBS and its applications we must consider different parameters that can vary among the different techniques like stimulation time, intensity, frequency, and targeted areas.

A common and highly relevant parameter is the "on-line" and "off-line" application. These, define the time of application of the stimulation, so it is possible to the study the effects of NIBS on tasks and processes of interest when the stimulation is applied during (on-line) or before (off-line) tasks. By using an "on-line" approach we can study the immediate effect of the stimulation during a task, while by the "off-line", approach we can study the lasting effects after the stimulation (Obeso, Oliviero, & Jahanshahi, 2016).

NIBS allow also simultaneous coupling with neuroimaging modalities such as electroencephalography (EEG), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI). This pairing of tools provides us with more information about NIBS effects and mechanisms of action and also help to achieve better evaluations of neurological pathologies and their pathophysiology.

This reversibly interaction with normal learning and behaviour, consequence of induction of lasting changes in cortical excitability, is also known as cortical plasticity. These induced changes last from few minutes to about one hour, but some clinical studies have found some longer lasting effects for certain conditions under some specific application criteria (Vestito, Rosellini, Mantero & Bandini, 2014).

Main evidence explaining the reversible changes points towards mechanisms similar to long-term potentiation (LTP) and long-term depression (LTD) (Thickbroom, 2007; Monte-Silva et al., 2013). This long-term plasticity of cortical synapsis is generally associated to NMDA receptor (NMDAR) functions, with also an important role of GABA on controlling plasticity (Ridding & Ziemann, 2010).

Studies coincide on the evidence that response direction and magnitude to NIBS plasticity protocols is dependent on previous activation and current state of the cortex (Ridding & Ziemann, 2010).

NIBS have shown variability in behavioural and neurophysiological responses by multifactorial cause, still unknown in its whole (Ridding & Ziemann, 2010). Some individual variables have shown their relevance and interaction with cortical plasticity (Figure 2). For example: regular exercise (Kramer & Erickson, 2007), age (Barnes, 2003), attentional focus (Antal, Terney, Poreisz & Paulus 2007), sex (McEwen, 1994; Chaieb, Antal & Paulus, 2008), neuropharmachological drugs (Ziemann, Meintzschel, Korchounov & Ilic, 2006), genetics [genetic polymorphisms of neurotrophins] (Bramham, 2008), time of the day (Sale, Ridding & Nordstrom, 2008), and endogenous brain oscillations (Huerta & Lisman, 1995).

The consideration of these factors (and probably others still to discover), is crucial for a good prediction of individual neuroplasticity response to NIBS, therefore for clinical application.



Figure 2. Determinants of NIBS-induced plasticity (Ridding & Ziemann, 2010)

3.2 Transcranial Electrical Stimulation

Transcranial electrical stimulation (tES) appeared at the end of 19th century as treatment for some psychiatric disorders. During 1930s, electroconvulsive therapy is introduced as treatment, this type of electric stimulation is based on strong electrical currents. During the 20th century the investigation on low-intensity currents were also developed, rising its use on research at the end of the century.

When talking about low-intensity tES we should highlight three main methods: transcranial direct current stimulation (tDCS), transcranial alternating current stimulation (tACS), and transcranial random noise stimulation (tRNS) (Figure 3).



Figure 3. Representation of signals from tDCS, tRNS and tACS

These neuromodulatory interventions are tools that are actually used in the treatment of neurological and psychological conditions. These low-current techniques have shown its utility for neuroplasticity due to their capacity of inducing changes in cortical excitability.

3.2.1 Transcranial Direct Current Stimulation (tDCS)

3.2.1.1 Basic Characteristics. tDCS is a neuromodulatory technique based on constant low-level electric currents, usually between 0.5 and 2.0 milliamps (mA). The main characteristic of this technique is that it uses constant current, with different polarity on each electrode, to modulate cortical excitability; producing neuroplasticity changes.

The parameters we must consider during tDCS application are current intensity (mA), duration (minutes), and current flow; based on the size of the electrodes and electrodes placement (Figure 4).

The position of the electrodes on the scalp will affect the current flow and the brain areas affected by it and if it is in an inhibitory or excitatory way. For it, is usually used as reference the International 10-20 System.



Figure 4. Montage example with marked direction of electric current flow (Moreno-Duarte et al., 2014)

Anodal electrode provides positive current which facilitates depolarization. This is an increase of the neuronal excitability, changing the resting voltage of the neural membrane; what has as consequence a reduction on the neuronal firing threshold.

While the cathodal electrode provides negative current that facilitates hyperpolarization. That induces a reduction on neural excitability, or inhibition, which reflects the opposite effect of the anodal stimulation.

This effect of polarity applies mainly in motor cortex, while in other cognitive domains it can vary. Jacobson, Koslowsky and Lavidor (2011) brought to stage on their review that this dual-polarity effect is not present on all tDCS studies. The anodal-excitation and cathodal-inhibition (AeCi) effect is the common assumption, but the meta-analysis showed that dichotomy of AeCi effect is only homogeneous for motor studies and heterogeneous for cognitive studies.

3.2.1.2 Applications. tDCS is an extensively used technique from research to clinical applications.

We can find one of its utilities in clinical neurorehabilitation, where has been proved to be effective to improve training effects of motor function and learning processes and also to show feasibility as technique to be applied with double-blind and sham-controlled randomized trials (Gandiga, Hummel & Cohen, 2006). These characteristics provide a big value for both clinical and basic research.

Some studies have focused on long lasting effects, with the objective of finding the best therapeutic applications by improving the efficacy on treatments for neuropsychiatric diseases, stroke recovery, depressive symptoms. Monte-Silva et al. (2013) found that it is possible to induce late long-term potentiation (l-LTP)-like effects on human motor cortex by tDCS stimulation. This neural plasticity is dependent on the periodicity of the stimulation, with a critical role of specific time windows to induce this stimulation.

3.2.2 Transcranial Alternate Current Stimulation (tACS)

tACS is a method based on low-level non-constant current. For this stimulation method, the current pulses can be based on rectangular or sinusoidal waves. Allowing brain stimulation at specific frequencies.

Alternate current stimulation modifies the transmembrane potential of neurons. The polarization effect depends on the applied current, being linearly proportional to it and frequency dependent. Inducing bigger polarization at low frequencies (Miniussi, Harris, & Ruzzoli, 2013).

While tACS montage is similar to the tDCS montage, together with current intensity (mA), duration of the stimulation (minutes) and placement of the electrodes, the crucial factor here is the frequency of stimulation (Hz) (Woods et al., 2016). With tACS we can induce entrainment effects and boost performance in a frequency and state dependent fashion (Feurra et al., 2019).

3.2.3 Transcranial Random Noise Stimulation (tRNS) This technique is the more controversial. It is based on the application of a random (stochastic) electrical oscillation spectrum.

It can be applied in three frequency ranges: entire spectrum ( 0.1 to 640 Hz), low band (0.1-100), and high band (101-640). Indeed, only high-frequency stimulation modulates cortical excitability (Paulus, 2011).

It has been shown to be effective in modulating cortical excitability, but its underlying physiological mechanisms are still unknown, like the optimal parameters of application or possible clinical effects (Miniussi, Harris, & Ruzzoli, 2013).

3.3 Transcranial Magnetic Stimulation (TMS)

3.3.1 Brief History. At the beginning of XXth century, D'Arsonval, induced phosphenes and faint flickering by stimulating subjects retina with time-varying magnetic fields that electromagnetically induced currents. Later on, Bickford and Freeming (1965) used these magnetic fields to stimulate nerves and muscles. And more recently, Barker et al. (1985) proved that magnetic impulses can be used to stimulate human brain.

3.3.2 Basic Characteristics. Transcranial magnetic stimulation (TMS) is a both a neuromodulatory and neurostimulatory non-invasive technique. The device sends a current through a coil that induce a local magnetic field which transfers the energy through the skull, inducing a secondary electric current on the brain (Wagner, Valero-Cabre & Pascual-Leone, 2007).

For TMS, a coil delivers a pulse, a strong and transient magnetic field, that induces a transitory electric current in the targeted cortical area. This elicits a fast and over the threshold depolarization of the cell membranes of the stimulated area. After, as consequence, it triggers the transynaptic hyperpolarization and depolarization of the interconnected neurons (Barker, Freestone, Jalinous & Jarrat, 1987).

3.3.3 Applications. TMS application depends on different criteria that have different effects; we must rely on the intensity of the stimulation, number of pulses, duration of stimulation and aimed area.

Single pulse TMS (spTMS) triggers action potentials of the neurons, while repeated TMS (rTMS), pulses applied in rapid succession, creates a sustained alteration on cortex excitability, decreasing or increasing it.

When applied during enough time, TMS can modulate cortical functions for even after the stimulation period (Rossi et al., 2009).

Different combinations of intensity, frequency and duration of TMS can simulate different protocols that target both mechanisms of time- and activity-dependent synaptic plasticity.

TMS interventions have a short after-effect itself to rise a relevant clinical functional improvement, but on interaction with other therapies the results are more significant and long-lasting (Obeso, Oliveiro, & Jahanshahi, 2016).

One way of application for TMS was the "virtual lesion assumption" approach. Based on neuropsychological theories about the location of the areas involved in different functions, some specific areas are targeted during cognitive processes to assess if there is interference due to the stimulation. An experiment based on this idea was performed by Amassian et al. (1989), they found that stimulating occipital cortex with a magnetic coil during a specific time frame of the visual processing, 80-100 ms, can disrupt or completely inhibit the perception of the stimulus.

Virtual lesion approach was followed for other alternative hypothesis with better explanatory power: signal reduction versus noise generation (based on signal-to-noise ratio), state dependency (consider the importance of the stimulated area depending on the functional activation during a specific task), and entrainment (use an external oscillatory force to induce an specific oscillatory frequency on the brain) (Miniussi, Harris, & Ruzzoli, 2013).

These more developed hypothesis together with the use of neuroimaging techniques provide us with more detailed information about the roles and function of the brain area studied and how TMS interact with it.



Chapter 4. Modulation of Visual Awareness by NIBS

On previous chapters we have seen already some evidence about neuromodulation by NIBS of areas related with visual awareness and how these studies help us to understand the inner mechanisms of visual awareness.

Here we will focus on the two main non-invasive neuromodulatory techniques, that happen to be also the cornerstones of this project; transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS).

Visual awareness is a broad concept including various subjective visual experiences. It can refer to awareness of external visual stimuli, as well as visual representations internally generated. That means that the origin of visual awareness don't rely only and necessarily on external visual inputs, but also on internal factors like imagination, dreams or hallucinations.

One way to study VA is using artificial percept such as phosphenes, which can be induced by TMS.

The phosphene threshold (PT), represents an index of visual cortical excitability; it is represented by the minimum intensity needed to induce phosphene perception.

Most of the studies that we will and we have already reviewed are based on the generation or phosphenes or the estimation of PT. Due to the need of a trigger to generate phosphenes perception, we must keep in mind that tDCS fulfils the role of neuromodulatory technique of cortical excitability (with just few exceptions where it proved to be enough to generate phosphenes), while TMS is the neuroexcitatory tool, responsible of the phosphenes generation.

Phosphenes can be defined as brief artificial flash-like visual percept, that last only for few milliseconds (Nicholson, 2002) (Figure 5).



Figure 5. Phosphenes representation (Nicholson, 2002)

4.1 Evidences of Neuromodulation of Visual Awareness

tDCS is a technique both with therapeutic and basic research purposes in a wide variety of domains: memory, perception, decision making, degenerative diseases, mental diseases (Obeso, Oliveiro, & Jahanshahi, 2016).

tDCS has a reduced cost it is easy to apply and is a small portable device. Also, it has advantages for protocols development, thanks to the possibility of doing unipolar or bipolar montage, to stimulate at different intensities and during different periods of time.

As we saw before, the dichotomy of the anodal-excitatory/cathodal-inhibitory effect (AeCi effect) of tDCS is not always consistent out of motor cortex and motor evoked potentials (MEP). This can be related with the incongruences on literature about the effect of electrical stimulation on the visual cortex.

Some studies have found no results, or at least incongruent with the AeCi effect, when stimulating with tDCS on different regions out of the motor cortex (Brьckner & Kammer, 2016; Antal, Nitsche & Paulus, 2001). Or different results among subjects based, a priori, on other criteria like sex (Chaieb, Antal & Paulus, 2008).

But a mayor part of studies supports the utility of this technique to produce neuromodulation on visual cortex (Antal, Nitsche & Paulus, 2005; Sczesny-Kaiser et al., 2016). Even when results are not identical, these differences can be due to different parameters of the protocol, the experimental design or just inter-individual or inter-population differences.

Some of these studies have also provided us with evidence of the interconnection of areas of the visual cortex which have continuous feed-forward and feedback interaction, a key process for information processing. Antal, Kincses, Nitsche and Paulus (2003) found that excitability changes induced at V1 with tDCS can modulate the perception of moving phosphenes, that are perceived when TMS is applied on V5. In other study, Kar and Krekelberg (2012) evoked phosphenes perception with retinal origin by transcranial electrical stimulation (tES) of the visual cortex.



Chapter 5. Protocol

5.1 Basic Ideas and Concerns

On this chapter we report the experimental design, justifications, tools involved and comments and concerns about previous literature.

The purpose of the study is to investigate the potential neuromodulation of the primary visual cortex (V1) excitability. For this, we use anodal tDCS (a-tDCS) to neuromodulate the visual cortex and TMS as a probe due to its neuroexcitatory capabilities.

To measure the cortical excitability, we use phosphene induction by spTMS on V1. Being our reference the phosphene threshold (PT) and its variability conditioned by a-tDCS stimulation.

Learning how to modulate cortical excitability is crucial to understand and manage neural plasticity. We already discussed in previous chapters the clinical advantages of the use of neuroplasticity for the treatment of neurological damage and diseases.

We discussed on Chapter 3 about the dichotomy of AeCi effect of tDCS on human cortex, present on its ideal state for motor cortex (Nitsche & Paulus, 2000) (Figure 6) but with incongruences when applied on other areas.

Here, again we have an issue with this AeCi effect when applying this current stimulation on visual cortex. Some studies have found results that confirm the effects of this dichotomy model on visual cortex (Antal, Nitsche & Paulus, 2005; Sczesny-Kaiser et al., 2016) but others have failed to find these expected neuromodulatory effects on visual cortex excitability (Brьckner & Kammer, 2016; Antal, Nitsche & Paulus, 2001).



Figure 6. Effects of anodal and cathodal stimulation on motor evoked potentials (MEP) (Nitsche & Paulus, 2000)

For this reason, we try to elucidate the reality here and which factors can be the reason of these inconsistences among studies.

Other factors to have into consideration for the task design, are the dependence of neuroplasticity on cognitive state (Antal, Ambrus & Chaieb, 2014) and sex-specific effects of stimulation (Chaieb, Antal & Paulus, 2008).

5.2 Methods

5.2.1 Participants. According to a priori power analysis using G*Power 3.1.9.7 (Faul et al., 2009) sample size was determined to be not less than 21 (using estimate of =.25 from previous papers, for alpha =.05 and.8 target power). As revealed by post hoc power analysis, achieved statistical power was higher and equal to.9.

Due to the conditions consequence of the pandemic it was not possible to test on the full estimated sample. The final sample was composed by 7 participants (5 females) with an average age of 23.7 (Range: 20-29).

Healthy volunteers with no history of mental pathologies or migraine for them or close relatives. Subjects counted with a previous MR scan to use for reference during neuronavigation. No consume of alcohol or drugs previous to the experiment was indicated. The experiment was approved by the local ethics committee of HSE.

Subjects were asked to seat comfortably in a reclining chair and relax.

5.2.2 TMS. Delivered on the centre of primary visual cortex (V1), the calcarine cortex, through a MagPro X100 (MagVenture) stimulator with MCF-B65 induction focal coil (75-mm wing radius) which was used to produce biphasic TMS pulses.

The MR scans were used for a correct localization by a neuronavigation TMS system (Localite TMS Navigator, Localite GmbH) in an MRI-guided stimulation design which allowed optimization and recording of the identified TMS brain area (hot spot) and ensured consistent cortical target throughout the experiment. This system allows a correct repositioning within and across both experimental sessions.

To define the PT we used the staircase method (Mazzi, Savazzi, Abrahamyan, & Ruzzoli, 2017). The resulting PT measure was used as reference for starting the asses again in the next measure.

During the process of PT estimation the subjects were requested to focus on a fixation cross in the middle of a white screen, with the objective of making phosphenes easier to perceive.

5.2.3 tDCS. Current stimulation was different depending on the session, real and sham. Delivered by a battery-driven current stimulator (BrainSTIM, EMS Medical, Italy) through surface saline-soaked sponge electrodes (size 5x7 cm). Rubber straps around the head were used to provide a stable electrode-scalp contact.

Anodal electrode was positioned over Oz and cathodal electrode on Fpz.

5.2.4 Safety Criteria. At the beginning of the experiment subjects were requested to inform of any kind of pain and discomfort during the intervention to solve the problem or stop the procedure if necessary.

5.3 Experimental Design

The experimental session consisted in two sets of repeated PT measurement, pre- and post-stimulation and one stimulation session between them (Figure 7).

The protocol began at the pre-stimulation stage with five measures of PT, one each five minutes. Calcarine cortex of V1 was targeted and PTs were estimated by staircase method. The participant was asked on each estimation to look at the fixation cross of the white screen.

Once the last PT was measured the stimulation period started. The stimulation part consisted in a 10 minutes session of a-tDCS or sham condition. With a bipolar montage of the anodal or stimulation electrode over Oz and the cathodal or reference electrode over Fpz. Applying a 1.5 mA intensity.

After the stimulation, on the post-stimulation period we repeated the same procedure as before for PT estimation. Aiming the calcarine cortex of V1 and using the staircase method.



Figure 7. Intervention Design

This is a Within Group Design, where we applied both stimuli to each subject, spaced 5-7 days apart to avoid potential carry over effects of stimulation that would interfere and bias the data.

Our aim was to find if the a-tDCS produce a facilitatory effect, raising the excitability of V1. What would have as consequence a reduction of the PTs. And also check if there was variability over time after the stimulation.

For this, post-stimulation repeated measures of PT allowed us to study the effects of a-tDCS on cortical excitability and its decay during the time line.

5.4 Statistical Design

To study the data, first we performed an exploratory analysis of variance with two different Two-Way Repeated Measures ANOVAs.

We studied the differences between pre and post effects for both conditions, a-tDCS and sham. Doing independent Two-Way Repeated Measures ANOVA for each condition. And considering the Pre- and Post-Stimulus stages with their five time windows for the PT measurement.

The second analysis was also performed by a Two-Way Repeated Measures ANOVA, stimulation condition (a-tDCS and sham) and Time (the five time windows). It focused on the effect size of stimulation.

First, we normalized data of the post-stimulation stage to the pre-stimulation for both sessions.

Then we run an analysis of variance for each condition per time window. In order to obtain a reliable time course of the tDCS.



Chapter 6. Results

6.1 Raw Data

Here I will comment the obtained results of our sample.

Due to pandemic it was possible to obtain data from only seven participants. This small sample will limit the possible outcomes from the data and their interpretation.

We measured phosphene thresholds pre- and post-stimulation for both conditions, sham (Table 1) and anodal (Table 2), in all subjects.

Table 1 Phosphene Thresholds for Pre- & Post-Stimulation in Sham Condition

Table 2 Phosphene Thresholds for Pre- & Post-Stimulation in Anodal Condition

After getting the raw data we normalized the results (Table 3) of the participants, Post vs. Pre for each stimulation condition for a later ANOVA analysis. For it, we divided the Post phosphene threshold by the Pre and multiplied the result by 100 for each time measure [Normalization: (Post/Pre)*100].

With this step we adjusted values for a better comparison, obtaining values that reflect the comparison of the two time lines Post and Pre. So later we could compare between conditions the possible effects.

Table 3 Normalized Data of Phosphene Thresholds for Both Stimulation Conditions

6.2 Results from Statistical Analysis (ANOVAs)

In this section I will discuss the results of the ANOVAs ran on the data, previously explained on the Statistical Design section (5.3), using the SPSS Statistics software.

First we performed the exploratory analysis of variance with two different Two-Way Repeated Measures ANOVAs.

Doing independent Two-Way Repeated Measures ANOVA for each condition, anodal and sham. And considering the Pre and Post-Stimulus stages with their five time windows for the PT measurement. The aim of these analysis was to study the differences between pre and post effects for both conditions, a-tDCS and sham.

We ran a Two-Way Repeated Measures ANOVA for Sham condition with factors Pre-Post (two levels: pre-stimulation and post-stimulation) and Time (five levels: phosphene threshold measures 1, 2, 3, 4, & 5) over the raw data of the sham stimulation sessions (Table 4).

Mauchly's sphericity was significant for both factor Time and the interaction Pre-Post*Time (Tale 5). Because sphericity p < 0.05, we use Greenhouse-Geisser correction.

Table 4 Data from Sham Condition

Descriptive Statistics
	Mean	Std. Deviation	N
Sham Pre 1	60,00	5,033	7
Sham Pre 2	60,57	5,062	7
Sham Pre 3	60,00	6,831	7
Sham Pre 4	61,86	6,719	7
Sham Pre 5	62,86	4,811	7
Sham Post 1	61,29	4,716	7
Sham Post 2	61,57	5,028	7
Sham Post 3	63,43	6,161	7
Sham Post 4	60,71	8,098	7
Sham Post 5	63,00	5,888	7

Table 5 Mauchly's Test of Sphericity for Sham Condition

Mauchly's Test of Sphericitya
Measure: MEASURE_1
WithinSubjectsEffect	Mauchly's W	Approx. Chi-Square	df	Sig.	Epsilonb
					Greenhouse-Geisser	Huynh-Feldt	Lower-bound
PrePost	1,000	,000	0	.	1,000	1,000	1,000
Time	,003	26,254	9	,003	,323	,375	,250
PrePost * Time	,003	25,330	9	,004	,384	,490	,250

The results of the two-way repeated measures ANOVA on sham condition (Table 6) revealed that there was no significant main effect of any of the factors Pre-Post (F(1,6) =1.451, p =.274, =.175) (Figure 8) or Time (F(1.294,7.762) =1.548, p =.260, =.209) (Figure 9); neither for their interaction Pre-Post*Time (F(1.535,9.212) =1.623, p =.245, =.238) (Figures 10 & 11). The lack of significant results was expected considering we are in sham condition where no variability should be expected between pre and post and along time or in their interactions since we have no stimulation on this condition.

Table 6 Within-Subjects Effects of Sham Condition ANOVA

Tests of Within-Subjects Effects
Measure: MEASURE_1
Source	Type III Sum ofSquares	df	Mean Square	F	Sig.	Noncent. Parameter	ObservedPowera
PrePost	SphericityAssumed	15,557	1	15,557	1,451	,274	1,451	,175
	Greenhouse-Geisser	15,557	1,000	15,557	1,451	,274	1,451	,175
	Huynh-Feldt	15,557	1,000	15,557	1,451	,274	1,451	,175
	Lower-bound	15,557	1,000	15,557	1,451	,274	1,451	,175
Error(PrePost)	SphericityAssumed	64,343	6	10,724
	Greenhouse-Geisser	64,343	6,000	10,724
	Huynh-Feldt	64,343	6,000	10,724
	Lower-bound	64,343	6,000	10,724
Time	SphericityAssumed	42,657	4	10,664	1,548	,220	6,192	,405
	Greenhouse-Geisser	42,657	1,294	32,976	1,548	,260	2,002	,209
	Huynh-Feldt	42,657	1,499	28,456	1,548	,258	2,320	,226
	Lower-bound	42,657	1,000	42,657	1,548	,260	1,548	,184
Error(Time)	SphericityAssumed	165,343	24	6,889
	Greenhouse-Geisser	165,343	7,762	21,303
	Huynh-Feldt	165,343	8,994	18,383
	Lower-bound	165,343	6,000	27,557
PrePost * Time	SphericityAssumed	39,514	4	9,879	1,623	,201	6,492	,423
	Greenhouse-Geisser	39,514	1,535	25,736	1,623	,245	2,492	,238
	Huynh-Feldt	39,514	1,959	20,167	1,623	,238	3,180	,273
	Lower-bound	39,514	1,000	39,514	1,623	,250	1,623	,190
Error(PrePost*Time)	SphericityAssumed	146,086	24	6,087
	Greenhouse-Geisser	146,086	9,212	15,858
	Huynh-Feldt	146,086	11,756	12,426
	Lower-bound	146,086	6,000	24,348

Figure 8. Factor Pre-Post for Sham Condition

Figure 9. Factor Time for Sham Condition



Figure 10. InteractionTime*Pre-post for Sham Condition

Figure 11. Interaction Pre-Post*Time for Sham Condition

On the Pairwise t-Test (Appendix 1) of factor Pre-Post, factor Time and their interactions in both ways Pre-Post*Time and Time*Pre-post we found again the lack of significance more detailed per factor but for few significant interactions on Time and Pre-Post*Time with no important weight as we can see in the general factor significance.

Then we ran again a Two-Way Repeated Measures ANOVA but for Anodal condition with factors Pre-Post (two levels: pre-stimulation and post-stimulation) and Time (five levels: phosphene threshold measures 1, 2, 3, 4, & 5) over the raw data of the sham stimulation sessions (Table 7).

visual awareness neural correlation

Table 7 Data from Anodal Condition

Descriptive Statistics
	Mean	Std. Deviation	N
Real Pre 1	61,29	6,396	7
Real Pre 2	61,00	6,758	7
Real Pre 3	63,14	8,112	7
Real Pre 4	62,43	7,591	7
Real Pre 5	61,43	5,740	7
Real Post 1	63,57	8,364	7
Real Post 2	63,71	7,653	7
Real Post 3	64,00	8,944	7
Real Post 4	64,43	7,678	7
Real Post 5	64,14	7,244	7

Mauchly's sphericity here is no significant for any factor or their interaction (Table 8).

Table 8 Mauchly's Test of Sphericity for Anodal Condition

Mauchly's Test of Sphericitya
Measure: MEASURE_1
WithinSubjectsEffect	Mauchly's W	Approx. Chi-Square	df	Sig.	Epsilonb
					Greenhouse-Geisser	Huynh-Feldt	Lower-bound
PrePost	1,000	,000	0	.	1,000	1,000	1,000
Time	,101	10,106	9	,375	,462	,660	,250
PrePost * Time	,066	12,028	9	,242	,584	,978	,250



The results of the two-way repeated measures ANOVA on anodal condition (Table 9) revealed that there is only significant main effect of the factor Pre-Post (F(1,6) =16.661, p =.006, =.922) (Figure 12). But not significant effect for factor Time (F(4,24) =4.407, p =.388, =.288) (Figure 13); neither for their interaction Pre-Post*Time (F(4,24) =2.050, p =.495, =.236) (Figures 14 & 15).

Table 9 Within-Subjects Effect for Real Condition

Tests of Within-Subjects Effects
Measure: MEASURE_1
Source	Type III Sum ofSquares	df	Mean Square	F	Sig.	Noncent. Parameter	ObservedPowera
PrePost	SphericityAssumed	78,229	1	78,229	16,661	,006	16,661	,922
	Greenhouse-Geisser	78,229	1,000	78,229	16,661	,006	16,661	,922
	Huynh-Feldt	78,229	1,000	78,229	16,661	,006	16,661	,922
	Lower-bound	78,229	1,000	78,229	16,661	,006	16,661	,922
Error(PrePost)	SphericityAssumed	28,171	6	4,695
	Greenhouse-Geisser	28,171	6,000	4,695
	Huynh-Feldt	28,171	6,000	4,695
	Lower-bound	28,171	6,000	4,695
Time	SphericityAssumed	17,629	4	4,407	1,082	,388	4,327	,288
	Greenhouse-Geisser	17,629	1,850	9,530	1,082	,367	2,001	,189
	Huynh-Feldt	17,629	2,638	6,682	1,082	,379	2,854	,227
	Lower-bound	17,629	1,000	17,629	1,082	,338	1,082	,143
Error(Time)	SphericityAssumed	97,771	24	4,074
	Greenhouse-Geisser	97,771	11,099	8,809
	Huynh-Feldt	97,771	15,830	6,176
	Lower-bound	97,771	6,000	16,295
PrePost * Time	SphericityAssumed	8,200	4	2,050	,872	,495	3,489	,236
	Greenhouse-Geisser	8,200	2,335	3,512	,872	,455	2,037	,178
	Huynh-Feldt	8,200	3,914	2,095	,872	,493	3,414	,233
	Lower-bound	8,200	1,000	8,200	,872	,386	,872	,124
Error(PrePost*Time)	SphericityAssumed	56,400	24	2,350
	Greenhouse-Geisser	56,400	14,010	4,026
	Huynh-Feldt	56,400	23,483	2,402
	Lower-bound	56,400	6,000	9,400

Figure 12.Factor Pre-Post for Anodal Condition



Figure 13. Factor Time for Anodal Condition

Figure 14. InteractionTime*Pre-post for Anodal Condition



Figure 15. Interaction Pre-Post*Timefor Anodal Condition

On the Pairwise t-Test (Appendix 2) of factor Time and the interaction Pre-Post*Time we found again the lack of significance in more detailed statistics; in the later case this means no modulation in time. But for the interaction Time*Pre-Post, we found a significative difference between pre and post stages for time 2 (p=.018) and time 4 (p=.044) and close to be significant for time 1 (p=.061) and time 5 (p=.059) (Table 10). This shows that by increasing sample size it is likely to get an interaction effect.

Table 10 Interaction Time*Pre-Post for Anodal Condition

Pairwise Comparisons
Measure: MEASURE_1
Time	(I) PrePost	(J) PrePost	Mean Difference (I-J)	Std. Error	Sig.b	95% Confidence Interval forDifferenceb
						LowerBound	UpperBound
1	1	2	-2,286	,993	,061	-4,716	,144
	2	1	2,286	,993	,061	-,144	4,716
2	1	2	-2,714*	,837	,018	-4,763	-,666
	2	1	2,714*	,837	,018	,666	4,763
3	1	2	-,857	,595	,200	-2,312	,598
	2	1	,857	,595	,200	-,598	2,312
4	1	2	-2,000*	,787	,044	-3,925	-,075
	2	1	2,000*	,787	,044	,075	3,925
5	1	2	-2,714	1,169	,059	-5,576	,147
	2	1	2,714	1,169	,059	-,147	5,576

After these we ran the second analysis to be performed, also a Two-Way Repeated Measures ANOVA regarding the stimulation condition (a-tDCS and sham) and the five time windows. It will be focused on the effect size of stimulation.

First we normalized data of the post-stimulation stage to the pre-stimulation for both sessions (Table 11).

Then we ran an analysis of variance for each condition per time window. In order to obtain a reliable time course of the tDCS.

Table 11 Data from Normalized Measures

Descriptive Statistics
	Mean	Std. Deviation	N
PT1 sham	...

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