Fast and slow errors: logistic regression to identify patterns in accuracy-response time relationships

Understanding error and response time patterns is essential for making inferences in several domains of cognitive psychology. Crucial insights on cognitive performance and typical behavioral patterns are disclosed by using distributional analyses such as conditional accuracy functions (CAFs) instead of mean statistics. Several common behavioral error patterns revealed by CAFs are frequently described in the literature: response capture (associated with relatively fast errors), time pressure or urgency paradigms (slow errors), or cue-induced speed–accuracy trade-off (evenly distributed errors). Unfortunately, the standard way of computing CAFs is problematic, because accuracy is averaged in RT bins. Here we present a novel way of analyzing accuracy–RT relationships on the basis of nonlinear logistic regression, to handle these problematic aspects of RT binning. First we evaluate the parametric robustness of the logistic regression CAF through parameter recovery. Second, we apply the function to three existing data sets showing that specific parametric changes in the logistic regression CAF can consistently describe common behavioral patterns (such as response capture, time pressure, and speed–accuracy trade-off). Finally, we discuss potential modifications for future research

Paired-pulse transcranial magnetic stimulation reveals probability-dependent changes in functional connectivity between right inferior frontal cortex and primary motor cortex during go/no-go performance

The functional role of the right inferior frontal cortex (rIFC) in mediating human behavior is the subject of ongoing debate. Activation of the rIFC has been associated with both response inhibition and with signaling action adaptation demands resulting from unpredicted events. The goal of this study is to investigate the role of rIFC by combining a go/no-go paradigm with paired-pulse transcranial magnetic stimulation (ppTMS) over rIFC and the primary motor cortex (M1) to probe the functional connectivity between these brain areas. Participants performed a go/no-go task with 20% or 80% of the trials requiring response inhibition (no-go trials) in a classic and a reversed version of the task, respectively. Responses were slower to infrequent compared to frequent go trials, while commission errors were more prevalent to infrequent compared to frequent no-go trials. We hypothesized that if rIFC is involved primarily in response inhibition, then rIFC should exert an inhibitory influence over M1 on no-go (inhibition) trials regardless of no-go probability. If, by contrast, rIFC has a role on unexpected trials other than just response inhibition then rIFC should influence M1 on infrequent trials regardless of response demands. We observed that rIFC suppressed M1 excitability during frequent no-go trials, but not during infrequent no-go trials, suggesting that the role of rIFC in response inhibition is context dependent rather than generic. Importantly, rIFC was found to facilitate M1 excitability on all low frequent trials, irrespective of whether the infrequent event involved response inhibition, a finding more in line with a predictive coding framework of cognitive control

Fast and slow errors: logistic regression to identify patterns in accuracy-response time relationships

Understanding error and response time patterns is essential for making inferences in several domains of cognitive psychology. Crucial insights on cognitive performance and typical behavioral patterns are disclosed by using distributional analyses such as conditional accuracy functions (CAFs) instead of mean statistics. Several common behavioral error patterns revealed by CAFs are frequently described in the literature: response capture (associated with relatively fast errors), time pressure or urgency paradigms (slow errors), or cue-induced speed–accuracy trade-off (evenly distributed errors). Unfortunately, the standard way of computing CAFs is problematic, because accuracy is averaged in RT bins. Here we present a novel way of analyzing accuracy–RT relationships on the basis of nonlinear logistic regression, to handle these problematic aspects of RT binning. First we evaluate the parametric robustness of the logistic regression CAF through parameter recovery. Second, we apply the function to three existing data sets showing that specific parametric changes in the logistic regression CAF can consistently describe common behavioral patterns (such as response capture, time pressure, and speed–accuracy trade-off). Finally, we discuss potential modifications for future research

Repetitive transcranial magnetic stimulation for obsessive-compulsive disorder:a systematic review and pairwise/network meta-analysis

BACKGROUND: We evaluated the efficacy and safety of repetitive transcranial magnetic stimulation (rTMS) for obsessive-compulsive disorder (OCD), and ranked the relative efficacy of different stimulation protocols. METHODS: We performed a search for randomised, sham-controlled trials of rTMS for OCD. The primary analysis included both a pairwise meta-analysis and a series of frequentist network meta-analyses (NMA) of OCD symptom severity. Secondary analyses were carried out on relevant clinical factors and safety. RESULTS: 21 studies involving 662 patients were included. The pairwise meta-analysis showed that rTMS for OCD is efficacious across all protocols (Hedges' g=-0.502 [95%CI= -0.708, -0.296]). The first NMA, with stimulation protocols clustered only by anatomical location, showed that both dorsolateral prefrontal cortex (dlPFC) stimulation and medial frontal cortex stimulation were efficacious. In the second NMA, considering each unique combination of frequency and location separately, low frequency (LF) pre-supplementary motor area (preSMA) stimulation, high frequency (HF) bilateral dlPFC stimulation, and LF right dlPFC stimulation were all efficacious . LF right dlPFC was ranked highest in terms of efficacy, although the corresponding confidence intervals overlapped with the other two protocols. LIMITATIONS: Evidence base included mostly small studies, with only a few studies using similar protocols, giving a sparse network. Studies were heterogeneous, and a risk of publication bias was found. CONCLUSIONS: rTMS for OCD was efficacious compared with sham stimulation. LF right dlPFC, HF bilateral dlPFC and LF preSMA stimulation were all efficacious protocols with significant and comparable clinical improvements. Future studies should further investigate the relative merits of these three protocols

Adverse events of repetitive transcranial magnetic stimulation in older adults with depression, a systematic review of the literature

Objective: In the last decade, repetitive transcranial magnetic stimulation (rTMS) has been introduced as a non-invasive neuromodulation therapy for depression. Little is known, however, about (serious) adverse events (AE) of rTMS in older adults with a depression. In this article, we want to study what is known about (serious) AE of rTMS in older adults (>60 years) with late-life depression (LLD). Methods: A systematic search has been performed according to the PRISMA guidelines in PubMed, EMBase and PsycInfo. We have screened 622 articles for eligibility. Eleven studies, evaluating 353 patients in total, were included in this review. Results: AE were reported in 12.4% of the older adults with a LLD treated with rTMS, serious AE in 1.5%. Headache (6.9%) and discomfort at the stimulation site (2.7%) are the most commonly reported AE. Serious AE reported are: psychiatric hospitalization (three times), a combination of posterior vitreous detachment and retinal tear, and increased suicide ideation (both once). Conclusions: rTMS in older adults with LLD was concluded overall to be safe due to the low frequency of AE reported in trials and observational studies. In case-reports, however, more serious AE have been described. To tailor use of rTMS in older adults with LLD, more research is needed in larger samples to optimize tolerance