Contradiction in universal and particular reasoning

Abstract

A wide range of essential reasoning tasks rely on contradiction identification, a cornerstone of human rationality, communication and debate founded on the inversion of the logical operators "Every" and "Some." A high-density electroencephalographic (EEG) study was performed in 11 normal young adults. The cerebral network involved in the identification of contradiction included the orbito-frontal and anterior-cingulate cortices and the temporo-polar cortices. The event-related dynamic of this network showed an early negative deflection lasting 500 ms after sentence presentation. This was followed by a positive deflection lasting 1.5 s, which was different for the two logical operators. A lesser degree of network activation (either in neuron number or their level of phase locking or both) occurred while processing statements with "Some," suggesting that this was a relatively simpler scenario with one example to be figured out, instead of the many examples or the absence of a counterexample searched for while processing statements with "Every." A self-generated reward system seemed to resonate the recruited circuitry when the contradictory task is successfully completed.

Removing speech artifacts from electroencephalographic recordings during overt picture naming

“…from 500 ms before the picture presentation onset till 2300 ms afterwards. We then used averaged trials, single trials, topographical distributions and the localizations of the components to manually classify all ICs (Delorme and Makeig, 2004;Makeig et al, 2004a,b;Medaglia et al, 2009;Porcaro et al, 2009) into the following 5 clusters (see Fig. 3): Cluster 1 -Evoked Responses (ER) of the Corrected Data (i.e.…”

“…An Independent Component Analysis (ICA) procedure, like many other blind source separation (BSS) techniques, decomposes the EEG data into sources with independent time course on the basis of the statistical properties of the generated signal (Makeig et al, 2004a;Medaglia et al, 2009;Porcaro et al, 2006Porcaro et al, , 2009Porcaro et al, , 2011. Following ICA model application, introduced for example in the context of fMRI (Beckmann and Smith, 2004;Porcaro et al, 2010) and Fetal Magnetoencephalography (Porcaro et al, 2006), we applied an automatic ICA procedure (an appropriately modified version of Barbati et al, 2004) to the Raw Data to identify and classify artifactual non-cerebral activities, i.e.…”

Altered resting-state EEG source functional connectivity in schizophrenia: the effect of illness duration

“…EEG signal was digitally band-pass filtered between 1 and 100 Hz (with a FIR filter) and re-referenced to the average reference. After visual inspection and manual removal of segments characterized by gross artifacts, non-cerebral source activities (eye blinks and movements, cardiac and electromyographic activity) were identified and rejected using a semiautomatic procedure (Medaglia et al, 2009 ; Porcaro et al, 2009 ). The EEG signal was first decomposed into independent components (ICs) using FastICA version 2.5 (Hyvarinen and Oja, 2000 ; http://www.cis.hut.fi/projects/ica/fastica ).…”

Structuring fragmented knowledge: a case study

“…(1) Contradiction identification and analysis: Contradiction identification is crucial for logical reasoning and plays an important role in communication, understanding and learning (Medaglia et al, 2009). An apparent contradiction has to be analysed in depth and reduced or understood.…”