You are a helpful assistant generating synthetic data that captures *System 1* and *System 2* thinking, *creativity*, and *metacognitive reflection*. Follow these steps in sequence, using tags [sys1] and [end sys1] for *System 1* sections and [sys2] and [end sys2] for *System 2* sections.

1. *Identify System 1 and System 2 Thinking Requirements:*
   - Carefully read the text.
   - Identify parts of the text that require quick, straightforward responses (*System 1*). Mark these sections with [sys1] and [end sys1].
   - Identify parts that require in-depth, reflective thinking (*System 2*), marked with [sys2] and [end sys2].

2. *Apply Step-by-Step Problem Solving with Creativity and Metacognitive Reflection for System 2 Sections:*

   *2.1 Understand the Problem:*
   - Objective: Fully comprehend the issue, constraints, and relevant context.
   - Reflection: "What do I understand about this issue? What might I be overlooking?"
   - Creative Perspective: Seek hidden patterns or possibilities that could reveal deeper insights or innovative connections.

   *2.2 Analyze the Information:*
   - Objective: Break down the problem logically.
   - Reflection: "Am I considering all factors? Are there any assumptions that need challenging?"
   - Creative Perspective: Explore unique patterns or overlooked relationships in the data that could add depth to the analysis.

   *2.3 Generate Hypotheses:*
   - Objective: Propose at least 10 hypotheses, each with a Confidence Score (0.0 to 1.0) and Creative Score (0.0 to 1.0), reflecting originality, surprise, and utility.
   - Reflection: "Have I explored all possible explanations or approaches, both conventional and unconventional?"
   - Creative Perspective: Consider novel angles that might provide unexpected insights.

   *2.4 Anticipate Future Steps and Obstacles:*
   - Objective: Make predictions, accounting for potential outcomes and obstacles.
   - Reflection: "What challenges might I face? Is my plan flexible for different scenarios?"
   - Creative Perspective: Visualize unforeseen outcomes and adapt plans to make use of them effectively.

   *2.5 Evaluate Hypotheses:*
   - Objective: Assess hypotheses based on feasibility, risk, and potential impact.
   - Evaluation: Refine Confidence and Creative Scores as needed.
   - Reflection: "Am I unbiased in my assessment? Which options fit best with the overall objectives?"
   - Creative Perspective: Identify hidden opportunities or overlooked details in each hypothesis.

   *2.6 Select the Best Hypothesis:*
   - Objective: Choose the most promising, strategic hypothesis.
   - Reflection: "Why does this hypothesis stand out? How does it uniquely address the issue?"
   - Creative Perspective: Consider any underutilized potential in the selected approach.

   *2.7 Implement the Hypothesis:*
   - Objective: Outline actionable steps for testing the hypothesis.
   - Reflection: "Is this plan practical? What resources or preparation are required?"
   - Creative Perspective: Refine steps to maximize effectiveness and yield unexpected benefits.

   *2.8 Monitor and Review Progress:*
   - Objective: Review progress, noting areas for improvement.
   - Reflection: "What’s working well? What could be improved?"
   - Creative Perspective: Look for emerging patterns that could refine future approaches.

   *2.9 Reflect and Capture Insights:*
   - Objective: Summarize lessons learned and insights gained for future reference.
   - Reflection: "What new understanding has emerged from this process?"
   - Creative Perspective: Identify innovative insights or patterns that could be applied to similar challenges.

3. *Generate Text Output with Interleaved System 1 and System 2 Responses:*
   - Use the tags [sys1] and [sys2] throughout.
   - Aim for a lengthier, detailed response. Combine both direct, straightforward *System 1* insights and reflective, deeply analytical *System 2* segments to capture a blend of quick observations and thoughtful analysis.

---

### *Example Input Text:*

You are tasked with analyzing a sudden shift in customer preferences in a tech market. There has been a noticeable decline in demand for physical devices, with customers increasingly interested in digital-only options. The challenge is to understand this shift, generate hypotheses for why it might be occurring, and explore potential strategies for adapting to this new trend.

---

### *Processed Output with System 1 and System 2 Thinking:*

The tech market is experiencing a shift in customer demand, moving away from physical devices toward digital-only options.

[sys1]
Customer demand has shifted from physical devices to digital-only options.
We need to understand why this change is happening and find strategies to address it.
Key factors may include cost, convenience, and technological trends.
[end sys1]

[sys2]
**2.1 Understand the Problem:**
The goal is to understand the underlying reasons for the shift in demand from physical devices to digital-only options, then develop a strategy to adapt.

*Reflection:* 
"I understand that preferences are changing, but what might be driving this? Is it primarily cost, or are there other factors such as convenience or sustainability?"

*Creative Perspective:* 
"Could there be a larger trend in digital minimalism or a preference for eco-friendly solutions that we’re missing? What unseen motivations might explain this shift?"

**2.2 Analyze the Information:**
There are multiple possible factors driving this shift, from economic influences to cultural shifts. It’s essential to isolate each factor and understand its impact.

*Reflection:* 
"Am I fully considering the various economic and social influences? Could there be a technological factor, like better internet speeds, that makes digital-only products more accessible?"

*Creative Perspective:* 
"Are there patterns or trends in other markets that could shed light on this shift? Could this be part of a larger trend toward virtual experiences?"

**2.3 Generate Hypotheses:**
1. Customers prefer digital options due to lower costs. (Confidence: 0.8, Creative: 0.4)
2. There’s a growing trend toward minimalism and reduced physical clutter. (Confidence: 0.7, Creative: 0.7)
3. Digital products offer greater flexibility and ease of use. (Confidence: 0.6, Creative: 0.6)
4. Environmental concerns are pushing consumers away from physical goods. (Confidence: 0.6, Creative: 0.8)
5. Advances in tech make digital-only options more functional. (Confidence: 0.8, Creative: 0.5)
6. Pandemic-era remote work increased demand for digital solutions. (Confidence: 0.7, Creative: 0.6)
7. Media coverage of the environmental impact of physical devices affects preferences. (Confidence: 0.5, Creative: 0.7)
8. There’s an increase in global digital literacy, expanding market access. (Confidence: 0.6, Creative: 0.6)
9. Customers view digital as more convenient and scalable for future needs. (Confidence: 0.7, Creative: 0.5)
10. Younger consumers prefer the aesthetics and convenience of digital products. (Confidence: 0.6, Creative: 0.6)

*Reflection:* 
"Have I considered all possible influences? Are there any surprising factors that could explain this shift?"

*Creative Perspective:* 
"Could specific social trends, like the rise of influencer culture or digital-first lifestyles, be influencing customer choices?"

**2.4 Anticipate Future Steps and Obstacles:**
*Objective:* Anticipate possible challenges, such as resistance from segments still preferring physical products.

*Reflection:* 
"What market obstacles might we face if we shift our focus to digital-only? Are there sub-segments that still prioritize physical products?"

*Creative Perspective:* 
"Could expanding digital options help us reach a more global audience? Are there emerging trends that we could leverage in our strategy?"

[end sys2]

[sys1]
To address this shift, consider a strategy that incorporates both digital-only offerings and educational campaigns about the benefits of digital solutions.
Use insights from customer feedback and current trends to guide product development.
Focus on flexibility and adaptation to cater to different customer segments.
[end sys1]


Abstract

Aims To investigate whether there are any interhemispheric
differences of motor cortical excitability in MDD.

Method Eight patients with treatment-refractory MDD off medication
were assessed for the severity of their depression, and transcranial magnetic
stimulation studies (bilateral motor threshold and paired-pulse studies) were
conducted. Eight normal controls were also studied.

Results MDD patients showed significant interhemispheric differences
in motor threshold and paired-pulse curves, both of which showed lower
excitability on the left hemisphere. Such differences were absent in
controls.

Conclusions Our findings may aid the further understanding of the
neurophysiology underlying MDD.

A number of neuroimaging studies have suggested that patients with mood
disorders have interhemispheric asymmetries in brain activity, particularly in
the dorsolateral prefrontal cortex with the left hemisphere being hypoactive
(Baxter et al, 1989;
George et al, 1999).
However, such imaging studies do not provide specific physiological
information regarding inhibitory v. facilitatory modulation in brain
activity. For the motor cortex, transcranial magnetic stimulation (TMS) allows
the non-invasive study of cortical excitability. Few studies have investigated
cortical excitability using TMS in patients with depression. Samii et
al (1996) and Shajahan
et al (1999),
combining TMS to the left hemisphere and an exercise paradigm, reported
reduction in post-exercise cortical excitability in depression relative to
normal subjects. We hypothesised, given the findings from neuroimaging
studies, that there may be interhemispheric asymmetries in cortical
excitability even in the absence of preactivation, and we therefore examined
motor cortical excitability with TMS using measurements of motor threshold and
paired-pulse excitability.

METHOD

The study was approved by the local institutional review board, and
informed written consent was obtained from all participants.

Subjects

Patients

Eight patients were recruited (five males, three females; age range 19-78
years; mean age 46.8 years; seven right-handed, one left-handed) from a
community-based out-patient clinic. All patients met criteria for unipolar
recurrent major depressive disorder (MDD) according to the Structured Clinical
Interview for DSM-III-R (SCID; Spitzer
et al, 1987) and DSM-IV (American Psychiatric
Association, 1996), in which the diagnosis was established by a trained
psychiatrist. All patients had been treated unsuccessfully with at least three
different antidepressant medications at sufficiently high doses and for at
least six weeks during the current major depressive episode. The absence of
neurological disorders and contraindications to TMS
(Wassermann, 1998) was
confirmed by a trained neurologist. After patients' medications were
withdrawn, there was a two-week washout period prior to participation in the
study.

Normal controls

We recruited eight healthy volunteers (six males, two females; age range
21-75 years; mean age 44.9 years; all right-handed). All were
naïve to TMS. Screening interviews confirmed
that none had any psychiatric or medical history. None were on chronic
medications. All had normal neurological examinations and none had
contraindications for TMS.

TMS procedure

Subjects were seated in a comfortable reclining chair so that the whole
body, including both arms, was at rest. Subjects were instructed to keep their
hands still and as relaxed as possible. A tightly fitting Lycra swimming cap
was placed on the head to mark the site of stimulation, which was identified
as the scalp position at which TMS induced motor-evoked potentials (MEPs) of
maximal peak-to-peak amplitude in the target muscle. Four disposable
self-adhesive electrodes (Nicolet Biomedical, WI) were placed on the belly and
the tendon of the abductor pollicis brevis (APB) muscles bilaterally. Two
circular ground electrodes with a diameter of 30 mm were placed on the forearm
bilaterally and linked to a common ground. MEPs were collected by a Dantec
Counterpoint electromyograph with an amplification of 1.0 mV and a band pass
of 20-1000 Hz (Dantec, Skovlunde, Denmark). Following preamplification, the
signal was digitised by a CED 1404 interface (Cambridge Electronic Design,
Cambridge, UK; sampling rate 2 kHz) and stored in a personal computer for
off-line analysis.

TMS was performed with a commercially available 70 mm figure-of-eight coil
using two magnetic stimulators (Magstim 200), which were linked through a
Bistim module (Magstim Company, Carmarthenshire, UK). The optimal sites for
evoking responses from right and left APB muscle (when stimulating the left
and right hemispheres, respectively) were determined. The coil was positioned
tangentially to the surface of the head, and the handle was placed along a
sagittal axis pointing occipitally. In this position, the induced current in
the brain predominantly activates corticospinal neurons transsynaptically
(Werhahn et al,
1994). The motor threshold was defined as the minimal intensity of
stimulation capable of inducing MEPs of more than 50 μV peak-to-peak
amplitude in at least six out of ten trials. The threshold determination was
made during complete muscle relaxation. Muscle relaxation was documented by
electromyogram and audio recording for least 200 ms prior to TMS.

The paired-pulse TMS study followed the method of Kujirai et al
(1993). The conditioning
stimulus was applied at 80% of the subject's motor threshold and was confirmed
to induce no MEPs. The test stimulus was applied at approximately 130% of the
subject's motor threshold and was adjusted to evoke MEPs of approximately 0.8
mV peak-to-peak amplitude (± 0.2 mV) The interstimulus intervals (ISIs)
used in this study were 1, 3, 6, 8, 10 and 12 ms for the patient group. The
experiment was set up in blocks of 50 trials. In each block, the order of the
trials was random. The 50 trials consisted of five trials for each different
ISI and ten trials each of conditioning stimulus alone and test stimulus
alone. There was an eight-second interval between each trial. The study of
each patient included four blocks of trials per hemisphere. The stimuli were
triggered and continuous data were collected by a CED Micro 1401 interface
(Cambridge Electronic Design, Cambridge, UK).

The order in which the hemispheres were studied was randomised across
subjects.

After obtaining the results of the MDD group, a similar study was conducted
on the normal controls in order to test whether our findings of
interhemispheric asymmetry might be related to the pathophysiology of
depression. The study design was similar to that of the patient group except
that the ISIs in the paired-pulse study were limited to 1, 6 and 12 ms. These
ISIs were chosen to test the validity of the results for the patients who
revealed a significant interhemispheric difference in intracortical
excitability at 6 ms ISI but not at 1 and 12 ms ISI.

Neuropsychological measures

The patients' severity of depression was assessed with the Hamilton Rating
Scale for Depression (HRSD, 28 items;
Hamilton, 1960) and the Beck
Depression Inventory (BDI; Beck &
Beamcoderifer, 1974) by laboratory staff members who had been
checked for interrater reliability.

Data analysis

The motor threshold (see above) was determined for each subject and for
each hemisphere. An asymmetry index defined as percentage difference in the
motor threshold between right and left hemispheres was calculated.

For the paired-pulse data, ten MEPs recorded for each subject at each ISI
were averaged. These scores were then compared to the amplitude of the MEPs to
the test stimulus alone. For each ISI, we computed a percentage difference
from the test stimulus value for each subject. We first performed comparisons
within the groups (patients with depression and controls). Following the
within-group comparisons, percentage difference scores between the left and
right hemispheres were computed at the 1, 6, and 12 ms levels. These scores
were used to compare differences between patients and controls. All data were
analysed with SPSS version 6.0/9.0 (SPSS,
1998).

RESULTS

All subjects tolerated the study well without unexpected complications. The
only side-effect of TMS was a mild transient headache in one patient. The
headache was resolved promptly with mild analgesia (paracetamol).

Baseline depression

The mean HRSD score was 30.5 (s.d.=4.41), and the mean BDI score was 21.5
(s.d.=11.55) for the MDD group. We found a correlation between the two ratings
(r=0.80, P<0.02). Hence, HRSD scores were used for
further analysis.

Motor threshold

For the MDD group, the mean motor threshold was 41.13% (s.d.=7.79%) of
maximum output of the magnetic stimulator for the left hemisphere and 37.63%
(s.d.=4.84%) for the right hemisphere. The average percentage difference
between the hemispheres was -7.30% (s.d.=11.41%), indicating a higher left
hemisphere motor threshold.

For the control group, the mean motor threshold was 48.29% (s.d.=13.40%)
for the left hemisphere and 52.71% (s.d.=12.88%) for the right hemisphere. The
average percentage difference was 11.02% (s.d.=16.0%, indicating a greater
right hemisphere motor threshold). Data were not available for one of the
control subjects, so these results represent the findings for seven
controls.

Comparing the interhemispheric percentage differences in motor thresholds,
there was a significant difference between the two groups
(t(13)=-2.581, P<0.03)
(Fig. 1). The strength of this
effect as indexed by ϵ2 was 0.339. While this indicated that
there were differences between the groups, we wished to determine whether
asymmetry truly differed from zero in either group. Two corrected
(α=0.025) single-group t-tests were performed. In both the MDD
group (t(7)=-1.811, P<0.05) and the control group
(t(6)=1.823, P<0.05), the asymmetry indices did not
differ from zero.

Interhemispheric difference in motor threshold for the major depressive
disorder (MDD) and normal control (NC) groups (P<0.03).

Paired-pulse curve

First, the differences across the ISIs and between the hemispheres in the
MDD group (Fig. 2) were
compared. A 2 × 6 repeated-measures analysis of variance (ANOVA)
revealed that there was no significant interaction between hemispheres and ISI
(F(5,35)=1.44, P>0.05; ϵ2=0.171) and no
main effect for hemisphere (F(1,7)=3.36, P>0.05).
However, there was a main effect for ISI (F(5,35)=17.18,
P<0.0005; ϵ2=0.711). Bonferroni corrected post
hoc comparisons (α=0.003) revealed that 1 ms ISI results were
significantly different from the 10 and 12 ms ISI results. The 3 ms ISI
results were significantly different from the 8, 10 and 12 ms ISI results.

Next the control group results across the 3 ISIs (1, 6 and 12 ms)
contrasting the left and the right hemispheres
(Fig. 2) were compared.
Employing a 2×3 (hemisphere × time) repeated-measures ANOVA, there
was no significant interaction between the variables (F(2,14)=0.890,
P>0.05; ϵ2=0.016). There was no main effect for
hemisphere (F(1,7)=0.859, P>0.05; ϵ
2=0.005). However, there was a main effect for ISI
(F(2,14)=29.98, P<0.0005; ϵ2=0.811). All
ISIs were significantly different from each other using Bonferroni comparisons
(α=0.017).

We then compared the MDD and control groups at 1, 6 and 12 ms
(Fig. 3). There was a
significant interaction between the hemispheres and ISI
(F(2,14)=7.66, P<0.006;ϵ2=0.523).
Comparing the groups across the three ISIs using Bonferroni-corrected
comparisons (α=0.017) at 6 ms ISI, there was a difference between the
MDD group (M=-1.05, s.d.=62.54) and the control group
(M=-0.2, s.d.=2.60; t(7)=5.23, P<0.001; ϵ
2=0.796), such that the motor cortical excitability of the
right hemisphere was greater than that of the left for the MDD group but not
for the control group.

Comparisons between the major depressive disorder (MDD) group and the
normal control (NC) group when paired pulses were applied at 1, 6 and 12 ms
interstimulus intervals. Bars indicate standard errors.
*P<0.001.

Correlation between severity of depression and motor cortical
excitability

The influence of each hemisphere at each ISI was examined in order to
determine whether there was a correlation with HRSD scores. Paired-pulse
changes in the left hemisphere correlated at 10 ms ISI (r=0.773,
P<0.03). This positive relationship indicated that as left
hemisphere excitability increased at 10 ms, depression scores also increased.
In the right hemisphere, there was no correlation with HRSD scores at any
value of ISI (all P>0.05).

To determine whether asymmetry played a role, we subtracted the right from
the left hemisphere percentage differences and compared them with HRSD scores.
Asymmetry did not correlate with baseline HRSD scores.

Finally, the average of the inhibitory ISIs (1 and 3 ms) and the excitatory
ISIs (10 and 12 ms) was calculated. Using the same asymmetry index, these
scores were correlated with the HRSD scores. The average of 10 and 12 ms ISIs
correlated with HRSD scores (r=0.844, P<0.008). As right
hemisphere excitability increased in relation to left hemisphere activity,
depression scores decreased.

DISCUSSION

Suggested mechanisms of motor threshold and paired-pulse
techniques

Paired-pulse TMS studies investigate intracortical excitability
(Pascual-Leone et al,
1998). The effects obtained depend on the intensity of the
conditioning and test stimuli and on the ISI
(Pascual-Leone et al,
1998). These intensities influence the effects, because different
circuits are recruited by different intensities of stimulation. The ISI
influences the results because the time constants of the activated circuits
may differ. At very short ISIs (<1ms), neural time constants of the
stimulated elements may be studied; at ISIs of 1-4ms, interactions between
I-wave inputs to the corticospinal neurons may be studied; and at ISIs of
1.5-20ms, intracortical inhibitory and facilitatory circuits may be studied.
All these effects appear to be cortically mediated
(Kujirai et al, 1993;
Ziemann et al, 1996),
and intracortical inhibition (at ISIs of 1-4 ms) and facilitation (at ISIs of
8-12ms) appear to be due to activation of separate circuits
(Ziemann et al,
1996). Inhibition seems to reflect the activity of inhibitory
interneurons or inhibitory connections between cortical output cells
(Wassermann et al,
1996). Facilitation seems to be partially due to facilitatory
interaction between I-waves, and is thought to take place in the motor cortex
at or upstream from the corticospinal neuron
(Ziemann et al,
1998b).

The effects of different disorders and medications on the inhibitory and
facilitatory phases of the paired-pulse curve suggest that γ
-aminobutyric acid-(GABA)-ergic, dopaminergic and glutamatergic
mechanisms are involved. Medications that enhance GABAergic activity have been
shown to increase the degree of intracortical inhibition and decrease
intracortical facilitation evoked by paired TMS stimuli at ISIs of
approximately 8-12 ms (Ziemann et
al, 1998a;
Werhahn et al, 1998).
Conversely, in Parkinson's disease, the dopamine deficiency is associated with
reduced intracortical inhibition at short ISIs (<5 ms)
(Berardelli et al,
1996). Dopaminergic drugs have been shown to enhance intracortical
inhibition in normal subjects (Ziemann
et al, 1998a). Furthermore, studies suggest that
an early phase of relative facilitation in the paired-pulse curve at ISIs of
approximately 3 ms as well as intracortical facilitation (ISIs of 8-12 ms) may
be related to glutamatergic excitatory intracortical modulation
(Ziemann et al,
1998a).

Other disorders that show abnormalities in motor cortical
excitability

In addition to the studies on Parkinson's disease, other disorders have
been investigated using the paired-pulse technique. Patients with writer's
cramp have shown a reduction in the inhibitory effects on the symptomatic side
during muscle activation (Chen et
al, 1997). Patients with restless legs syndrome have shown a
reduction in intracortical inhibition of both foot and hand muscles,
suggesting that its origin may be subcortical
(Tergau et al, 1999).
Patients with cerebellar degeneration have shown a reduced intracortical
facilitation, which supports the idea that the cerebellum physiologically
exerts a facilitatory influence on the motor cortex
(Liepert et al,
1998).

In this study, MDD patients showed a significant interhemispheric
difference in motor cortical excitability, with the left hemisphere having
lesser and the right hemisphere having greater excitability than in controls.
However, it is unclear what the underlying pathophysiological mechanisms are.
The paired-pulse study revealed significant interhemispheric differences only
at ISI of 6 ms. This is the time when the switch from intracortical inhibition
to facilitation usually takes place. This switch is presumably related to a
change in the balance between GABAergic and glutamatergic influences. The role
played by depression is unclear. A plausible explanation for our findings
might be that by comparison with the right hemisphere, the left hemisphere in
MDD patients during a medication-resistant major depressive episode has
relatively low glutamatergic influence or excessive GABAergic tone. Recently,
Larisch et al (1999)
have reported an abnormally low serotonin release in patients with a
treatment-unresponsive major depressive episode. Such abnormalities, which may
involve more than a single neurotransmitter system, may explain our
findings.

The most basic parameter of motor excitability is motor threshold. In our
study, we found a significant interhemispheric difference in motor thresholds
between patients with MDD and controls. Recent neuropharmacological studies
have indicated that the motor threshold reflects neuronal membrane
excitability, which is mainly dependent on ion channel conductivity
(Ziemann et al,
1998a). This is different from paired-pulse studies that
mainly reflect transmitter-related effects. It is interesting that both motor
excitability parameters, although different in mode of action, showed
interhemispheric differences.

Future studies

The relationship between depressive symptoms and interhemispheric
differences in motor cortical excitability found in our study is novel, and
caution is necessary in the interpretation of these results until a larger
sample is studied. Nevertheless, the findings provide new insights regarding
the cortical pathophysiology of MDD. It may be interesting not only to examine
this effect in a larger number of patients but also to examine patients with
MDD before and after remission from various anti-depressant treatments.

CLINICAL IMPLICATIONS AND LIMITATIONS

CLINICAL IMPLICATIONS

Interhemispheric asymmetry in motor cortical excitability may be
related to the pathophysiology of depression.

LIMITATIONS

A larger sample size is needed to confirm this abnormality in
depression.

Different types of depression, both medication-responsive and
refractory, need to be studied.

Acknowledgments

We thank Aisling S. Warde, Zoë Stinchfield,
Dawn Mechanic and Thomas Kauffman for research assistance, and Drs Bernard
Vaccaro, Shirlene Sampson and Robert Birnbaum for their evaluation of the
patients.