Items presented in large font are rated with higher judgments of learning (JOLs) than those presented in small font. According to current explanations of this phenomenon in terms of processing fluency or implicit beliefs, this effect should be present no matter the type of material under study. However, we hypothesized that the linguistic cues present in sentences may prevent using font size as a cue for JOLs. Experiment 1, with short sentences, showed the standard font-size effect on JOLs, and Experiment 2, with pairs of longer sentences, showed a reduced effect. These results suggest that linguistic factors do not prevent font size from being used for JOLs. However, Experiment 3, with both short and long sentences, showed an effect of font size only for the former and not the latter condition, suggesting that the greater amount of to-be-remembered information eliminated the font-size effect. In Experiment 4, we tested a mechanism to explain this result and manipulated cognitive load using the dot-memory task. The short sentences from Experiments 1 and 3 were used, and the results replicated the font-size effect only in the low-cognitive load condition. Our results are consistent with the idea that perceptual information is used to make JOLs only with materials such as words, word pairs, or short sentences, and that the increased cognitive load required to process longer sentences prevents using font size as a cue for JOLs.
Calcium plays a role of universal cellular regulator in the living cell and one of the crucial regulators of proper fetal development during gestation. Mitochondria are important for intracellular calcium handling and signaling. Mitochondrial calcium uniporter (mtCU) is a multiprotein complex of the mitochondrial inner membrane responsible for the transport of calcium to the mitochondrial matrix. In the present study, we analyzed the expression level of mtCU components in two parts of the feto-maternal system - placenta and myometrium at full-term delivery and at preterm birth (PTB) on different stages: 22-27, 28-32, 33-36 weeks of gestation (n = 50). A gradual increase of mRNA expression and changes in protein content of MCU and MICU1 subunits were revealed in the placenta during gestation. We also observed slower depolarization rate of isolated placental mitochondria induced by Ca2+ titration at PTB. In myometrium at PTB relative gene expression level of MCU, MCUb and SMDT1 increased as compared to full-term pregnancy, but the tendency to gradual increase of MCU protein simultaneous with MCUb increase and MICU1 decline was shown in gestational dynamics. Changes observed in the present study might be considered both natural dynamics as well as possible pathological mechanisms underlying preterm birth.
As a foraging facilitator, Inhibition of return (IOR) must be coded in spatiotopic coordinates. Early reports confirmed this suggestion but these results have been recently challenged. The present study was designed to examine the reference frame of IOR and to test whether retinotopic IOR might be a part of the spatiotopic IOR gradient. We conducted four experiments with spatiotopically and retinotopically cued coordinates and an intervening saccade between the cue and target presentations. We alternated the response modality (manual and saccadic) and the cue-target spatial distance (fixed and contiguous). Our data showed evidence for an independent source of retinotopic IOR neither at discrete locations nor as a gradient; moreover, we observed the spread of IOR across the whole validly cued hemifield. We propose that these results indicate a strategy to attend and then inhibit the entire cued hemifield.
The Oxford Cognitive Screen (OCS) is a screening tool for the assessment of poststroke deficits in attention, memory, praxis, language, and number processing. The goal of the present study was to develop a Russian version of the OCS (Rus-OCS) via translation of the original battery, its cultural and linguistic adaptations, and reporting preliminary findings on its psychometric properties.
All parts of OCS were translated by native Russian-speaking neuropsychologists. Russian-speaking stroke patients (N = 205) were assessed with the Rus-OCS. Their performance was compared with performance of 60 healthy Russian-speaking adults aged between the ages of 18 and 91 years. The performance of 15 stroke patients and 42 healthy adults were assessed with a parallel version within 7 days of first testing. Convergent validity of the Rus-OCS was established via correlations with comparable tasks. Performance of three stroke groups with different lesion lateralization (right, left, and bilateral) was compared on language and visual attention subtasks. Preliminary normative data based on 5th to 95th percentile were also reported.
Measures of internal consistency and test-retest reliability ranged from acceptable to very good and estimates of convergent validity ranged from moderate to high. Sensitivity and specificity was found to range from .56 to 1 and from .73 to 1, respectively. Significant differences in performance between stroke and healthy groups on all subtasks confirmed the discriminative power of the Rus-OCS was good.
Rus-OCS is a promising cognitive screening instrument for Russian-speaking patients. However, further validation is needed. Constraints of socioeconomic differences between Russian speakers in the wider population should be considered. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Transcranial alternating current stimulation (tACS) can be used to modulate brain activity. tACS was shown to induce frequency-, state-, and phase- dependent effects which makes tACS a neurostimulation technique that provides a more valuable predictable outcome. However, the impact of different tACS intensities has not been systematically investigated yet. Here, we proposed to investigate the effects of tACS of the primary motor cortex (M1) delivered at different intensities.
There is a common assumption that application of stimulation for longer duration or for higher intensity leads to more reliable physiological and behavioral effects. However, previous studies performed using different transcranial electrical stimulation methods such as transcranial direct current stimulation (tDCS) and/or at high-frequency such as tACS at ripple range, showed non-monotonic effect of stimulation intensity. Nevertheless, tDCS and high-frequency tACS potentially rely on different mechanisms of neuromodulation with respect to conventional tACS delivered at EEG range (1 – 70 Hz).
In this study we applied 20 Hz tACS to the primary motor cortex (M1) to investigate potential non-monotonic effect of tACS intensities (ranging from 0.25 mA to 2 mA with 0.25 mA interval between conditions) on the M1 excitability measured as the peak-to-peak amplitude of TMS-induced motor evoked potentials (MEPs). As for control, we used 1 mA 10 Hz (alpha) tACS and a no stimulation condition.
Preliminary results (N = 9) showed increase of MEPs for higher intensities (1.5 mA, 2 mA) of stimulation. In addition, an interesting effect emerged for those subjects with a lower motor threshold which showed a higher MEPs modulation effect of beta-tACS
Emotion congruence in emotion perception is manifested in increasing sensitivity to the emotions corresponding to the perceiver’s emotional state. In this study, an experimental procedure that robustly generates emotion congruence during the perception of ambiguous facial expressions has been developed. It was hypothesized that emotion congruence will be stronger in the early stages of perception. In two experiments, happiness and sadness were elicited in 69 (mean age 20.2, 57 females) and 58 (mean age 18.2, 50 females) participants. Then they determined what emotions were present in the ambiguous faces. The duration of stimulus presentation varied for the analysis of earlier and later stages of perception. The effect of emotion congruence was obtained in both experiments: happy participants perceived more happiness and less sadness in ambiguous facial expression compared to sad participants. Stimulus duration did not influence emotion congruence. Further studies should focus on the juxtaposition of the models connecting the emotion congruence mechanisms either with perception or with response generation.
Recent theories of cognitive control put large emphasis on theta oscillations in relation to action monitoring. Multiple EEG studies of cognitive control revealed increased power of theta oscillations restricted to midfrontal areas, while there is a substantial body of functional connectivity data demonstrating that theta oscillations may be a carrier of informational exchange over multiple cortical regions. fMRI studies revealed immense distributed networks involved in cognitive control. Paradoxically, MEG has been considered almost insensitive to theta oscillations in such an experimental context. It also remains debatable what is the functional role of such theta oscillations. An influential line of evidence links feedback-related theta oscillations to two types of prediction errors (unsigned and signed), but this distinction has not been tested during trial-end-error learning with theta activity measured beyond the midfrontal cortex.
We recorded MEG while participants were involved in trial-and-error learning within a novel multiple-choice behavioral task with complex stimulus-to-response mapping. Three conditions were analyzed: correct and erroneous trials during the initial stage of learning acquisition, as well as correct trials during stable performance. Sources of MEG activity were analyzed using minimum-norm estimation method within 4-6 Hz frequency range.
We revealed a number of bilateral cortical areas that displayed theta oscillations to the feedback signal: in addition to the "classical" medial frontal areas (the anterior part of the medial cingulate cortex and the pre-supplementary motor area), this network included the insula and the auditory cortex, the frontal operculum and posterior inferior frontal gyrus, the premotor cortex, the paracentral lobule, and the posterior part of the medial cingulate cortex. Granger causality analysis revealed overall communication directed from lateral to medial sites. During the initial stage of trial-and-error learning, we observed a strong non-differential response to feedback signal that reflected an unsigned component of the prediction error. The signed component of the prediction error was observed later – with greater theta activations after errors compared with correct responses.
Thus, using MEG, we were able to reveal a distributed network of brain areas in relation to feedback-related processing that included not only medial frontal, but also auditory areas, insula, lateral frontal, and medial parietal areas. The data obtained confirm the existence of two components of the prediction error, and this distinction was evident all over the network revealed.
The study was implemented in the framework of the Basic Research Program at the National Research University Higher School of Economics (HSE) in 2018.
Pharmacoresistant epilepsy is a common neurological disorder in which increased neuronal intrinsic excitability and synaptic excitation lead to pathologically synchronous behavior in the brain. In the majority of experimental and theoretical epilepsy models, epilepsy is associated with reduced inhibition in the pathological neural circuits, yet effects of intrinsic excitability are usually not explicitly analyzed. Here we present a novel neural mass model that includes intrinsic excitability in the form of spike-frequency adaptation in the excitatory population. We validated our model using local field potential data recorded from human hippocampal/subicular slices. We found that synaptic conductances and slow adaptation in the excitatory population both play essential roles for generating seizures and pre-ictal oscillations. Using bifurcation analysis, we found that transitions towards seizure and back to the resting state take place via Andronov-Hopf bifurcations. These simulations therefore suggest that single neuron adaptation as well as synaptic inhibition are responsible for orchestrating seizure dynamics and transition towards the epileptic state.
In the past decade, several studies have examined the effects of transcranial direct current stimulation (tDCS) on long-term episodic memory formation and retrieval. These studies yielded conflicting results, likely due to differences in stimulation parameters, experimental design and outcome measures.
In this work we aimed to assess the robustness of tDCS effects on long-term episodic memory using a meta-analytical approach.
We conducted four meta-analyses to analyse the effects of anodal and cathodal tDCS on memory accuracy and response times. We also used a moderator analysis to examine whether the size of tDCS effects varied as a function of specific stimulation parameters and experimental conditions.
Although all selected studies reported a significant effect of tDCS in at least one condition in the published paper, the results of the four meta-analyses showed only statistically non-significant close-to-zero effects. A moderator analysis suggested that for anodal tDCS, the duration of the stimulation and the task used to probe memory moderated the effectiveness of tDCS. For cathodal tDCS, site of stimulation was a significant moderator, although this result was based on only a few observations.
To warrant theoretical advancement and practical implications, more rigorous research is needed to fully understand whether tDCS reliably modulates episodic memory, and the specific circumstances under which this modulation does, and does not, occur.
The world that we perceive and describe changes constantly. If we believe our descriptions of the world to be accurate and consistent, we must assume that the content and the structure of our individual sentences accurately and consistently reflect the world’s constantly changing nature. If so, a comprehensive production system must model the sentence generation process taking into account this basic assumption: Words, their linear arrangement, and the structures they are inserted in must somehow reflect the corresponding parameters of the observed and described event. This system must include representation of salience as one integral component resulting in interplay that involves constant, regular, and automatic mappings between elements of a visual scene, their varying salience, and the structural arrangement of the sentence constituents and the grammatical relations between them. In this interplay, perceptual input contributes initially to this mapping process by providing information for further conceptual and linguistic encoding. Importantly, this information is not processed in an unconstrained fashion; instead, it is systematically filtered, selected, and relayed based on a regular interface between the aspects of attention and their corresponding counterparts in the conceptual and linguistic structures. Bottom-up and top-down features of this interface include noticeability, importance, or relevance. As a result, linguistic output reflects the event’s conceptual organization including the attentional state of the speaker in a regular way. This mapping between attentional focus and structural choice is a part of a more complex mapping mechanism that we will refer to as Cognition-Language Interface or CLI. Specifically, this Chapter will consider theoretical and empirical knowledge about the complex interplay between the speaker’s attentional state and the structural choices they make during sentence production.
Language processing has been suggested to be partially automatic, with some studies suggesting full automaticity and attention independence of at least early neural stages of language comprehension, in particular, lexical access. Existing neurophysiological evidence has demonstrated early lexically specific brain responses (enhanced activation for real words) to orthographic stimuli presented parafoveally even under the condition of withdrawn attention. These studies, however, did not control participants’ eye movements leaving a possibility that they may have foveated the stimuli, leading to overt processing. To address this caveat, we recorded eye movements to words, pseudowords, and non-words presented parafoveally for a short duration while participants performed a dual non-linguistic feature detection task (color combination) foveally, in the focus of their visual attention. Our results revealed very few saccades to the orthographic stimuli or even to their previous locations. However, analysis of post-experimental recall and recognition performance showed above-chance memory performance for the linguistic stimuli. These results suggest that partial lexical access may indeed take place in the presence of an unrelated demanding task and in the absence of overt attention to the linguistic stimuli. As such, our data further inform automatic and largely attention-independent theories of lexical access.
Nowadays, there is an increasing interest on the acquisition of the reading fluency. This is characterized as an automated reading which leads higher rates of speed and accuracy and allows the reader to carry out higher-level comprehension processes. A key factor for the achievement of a reading fluency is the establishment of word representations in the reader’s lexicon, which allow the direct visual recognition of words. It is widely accepted that to construct these mental representations a repeated visual exposure to novel words is needed. However, the nature of memory traces reached after this training is a question hotly debated in behavioral literature. While some authors argue that a simple visual training enables the formation of lexical traces for novel words, others argue that a training not only in orthographic but also in other word features (as the phonology or meaning) is required for the acquisition of high quality lexical representations. The use of more suitable measures for exploring the brain response during this process could contribute to solve this question. In this sense, the ERP approach emerges as a powerful tool to study the neurophysiological mechanisms underlying the acquisition of the lexical reading, and particularly the training conditions under which the formation of high quality lexical representations is possible. In this paper, the main contributions from the ERP literature to the understanding of the novel word lexicalization are reviewed.
Identifying facial expressions is crucial for social interactions. Functional neuroimaging studies show that a set of brain areas, such as the fusiform gyrus and amygdala, become active when viewing emotional facial expressions. The majority of functional magnetic resonance imaging (fMRI) studies investigating face perception typically employ static images of faces. However, studies that use dynamic facial expressions (e.g., videos) are accumulating and suggest that a dynamic presentation may be more sensitive and ecologically valid for investigating faces. By using quantitative fMRI meta-analysis the present study examined concordance of brain regions associated with viewing dynamic facial expressions. We analyzed data from 216 participants that participated in 14 studies, which reported coordinates for 28 experiments. Our analysis revealed bilateral fusiform and middle temporal gyri, left amygdala, left declive of the cerebellum and the right inferior frontal gyrus. These regions are discussed in terms of their relation to models of face processing.
Social norms have a critical role in everyday decision-making, as frequent interaction with others regulates our behavior. Neuroimaging studies show that social-based and fairness-related decision-making activates an inconsistent set of areas, which sometimes includes the anterior insula, anterior cingulate cortex, and others lateral prefrontal cortices. Social-based decision-making is complex and variability in findings may be driven by socio-cognitive activities related to social norms. To distinguish among social-cognitive activities related to social norms we identified thirty six eligible articles in the functional magnetic resonance imaging (fMRI) literature, which we separate into two categories (a) social norm representation, and (b) norm violations. The majority of original articles (> 60%) used tasks related with fairness norms and decision-making, such as ultimatum game, dictator game or prisoner’s dilemma; the rest used tasks related to violation of moral norms, such as scenarios and sentences of moral depravity ratings etc. Using quantitative meta-analyses we report brain common and distinct brain areas that show concordance as a function of category. Specifically, concordance in ventromedial prefrontal regions is distinct to social norm representation processing, whereas concordance in right insula, dorsolateral prefrontal and dorsal cingulate cortices is distinct to norm violation processing. We propose a neurocognitive model of social norms for healthy adults, which could help guide future research in social norm compliance and mechanisms of its enforcement.
The contribution of two different training contexts to online, gradual lexical acquisition was investigated by event-related potentials (ERPs) elicited by new, word-like stimuli. Pseudowords were repeatedly preceded by a picture representing a well-known object (semantic-associative training context) or by a hash mark (non-associative training context). The two training styles revealed differential effects of repetition in both behavioral and ERPs data. Repetition of pseudowords not associated with any stimulus gradually enhanced the late positive component (LPC) as well as speeded lexical categorization of these stimuli, suggesting the formation of episodic memory traces. However, repetition under the semantic-associative context caused higher reduction in N400 component and categorization latencies. This result suggests the facilitation in the lexico-semantic processing of pseudowords as a consequence of their progressive associations to picture-concepts, going beyond the visual memory trace that is generated under the non-associative context.
A classification of spectral patterns of EEG underlies several cognitive neurotechnologies including passive and active brain-computer interfaces. Despite arithmetic tasks often being used in studies of cognitive workload, there is a lack of findings describing a possibility to recognize EEG patterns related to different types of math operations. In the present work, we have shown that the power spectral density of EEG can be used to classify types of mental operations including a classification of verbal and different mathematical tasks for simple arithmetic operations or logical tasks with arithmetic progressions. The verbal tasks were separated from arithmetic ones significantly better than arithmetic from logical tasks, and verbal from logical tasks. Better discrimination of verbal tasks from arithmetic but not from logical tasks supports the hypothesis of unique EEG patterns associated with verbal activity that apparently differ from mental operations in arithmetic. Additionally, we compared the behavioral performance in problem solving and accuracy of EEG classification in two groups of subjects with education in math or humanities (N=8+8). We obtained the predicted differences related to better performance of the math group in solving math tasks than the humanitarian group. However, the classification accuracy of tasks based on EEG did not differ significantly between groups and was essentially higher than random. Considered together, our results support the hypothesis that EEG patterns reflect individual cognitive states corresponding to mental operations and can be used in classification of different cognitive activity.
Here we call attention to a scholarly paper of particular note, where Mazurek and Schieber (Mazurek and Schieber, 2017) reported for the first time that arm reaching tasks performed by rhesus monkeys can be instructed by intracortical stimulation (ICMS) applied to dorsal premotor cortex (PMd). Monkeys started each trial by grasping with the hand a home handle that was surrounded by four target handles. Next, reach direction was instructed by turning on a display composed of light emitting diodes (LEDs) at the base of the target handle and/or applying ICMS to different sites in PMd. ICMS of the primary somatosensory cortex (S1) was also tested in the same context. Monkeys responded to the instruction by releasing the home handle and grasping the target handle. They learned to respond correctly to both LED and ICMS instructions, with very high success rate (96–99%).
The discovery of place-representing neurons in the hippocampal formation has been recognized by the Nobel Committee as a paradigm shift in Neuroscience (Burgess, 2014). Here we call attention to an innovative paper of particular note (Zhang and Manahan-Vaughan, 2015) that added important findings to this field of study.
Zhang and Manahan-Vaughan investigated the contribution of olfactory cues to the formation of place fields in hippocampal neurons. For this purpose, they put male Wistar rats in the darkness into a 80 × 80 cm square box. Four odors (orange, vanilla, almond, and lemon) were placed into the quadrants of the arena. Chocolate crumbs were scattered across the arena to encourage exploratory behavior. The researchers observed the formation of stable place fields in the hippocampal neurons, even though visual cues were unavailable to the rats. The place fields rotated when the odor placements were rotated, and remapped when the odors were shuffled. The authors concluded that “despite the less precise nature of olfactory stimuli compared with visual stimuli, these can substitute for visual inputs to enable the acquisition of metric information about space.”
Neuroimaging studies are accumulating fast. A significant number of these studies use functional magnetic resonance imaging (fMRI) and report stereotactic brain coordinates. In the last 15 years meta-analytic software tools have been developed to identify over-arching data agreement across studies (e.g., http://www.brainmap.org/). Meta-analytic studies help establish statistical concordance and quantitatively summarize large amounts of evidence. To date there are 944 papers on fMRI meta-analyses, as indexed by Web of Science (WOS; 28/04/18). Before analyzing coordinates researchers have to compile, systematically review relevant literature and extract stereotaxic coordinates. One process of pooling information from the articles requires manual search of the articles and manual extraction the relevant data, such as coordinates (i.e., foci), contrasts (i.e., experiments) and types of analyses (whole-brain or region of interest). Another available approach is offered by software with pre-extracted information, such as Sleuth (http://brainmap.org/sleuth/), Neurosynth (http://neurosynth.org/) and other open-source programs. Critically, these methods do not have up to date datasets covering only a limited number of studies (e.g., 11406 papers in the Neurosynth and 3294 papers in the Sleuth 2.4 at the 28/04/2018), whereas, a WOS search for the keyword (“fMRI”) yields 61976 papers. To improve the quality of the manual search for area-based meta-analyses and increase the speed of the identification of the foci of interest, we developed CoordsFinder - standalone graphical interface software for addressing the challenge of processing multiple fMRI articles reporting data in coordinate space. The software is written using WPF (C# and XAML), based on .NET Framework 4.5.2, and it supports Microsoft Windows 7 operating system or higher. The CoordsFinder estimates the foci uploaded in the software manually and searches for it inside the specified folder, which contains the pdf files of the papers, as this is the most common file format for articles. Foci coordinates can be found both in tables and in a plain text of the articles. The foci file uploaded could contain MNI or TAL space coordinates, and the software can indicate each type. In the current version, CoordsFinder can explore only files stored at the user’s computer, and process 274 papers per minute for a typical computer. Practically this software provides a solution for automatically extracting coordinates from multiple articles for effectively organizing and further analyzing data already available in the literature.
Concurrent EEG and fMRI acquisitions in resting state showed a correlation between EEG power in various bands and spontaneous BOLD fluctuations. However, there is a lack of data on how changes in the complexity of brain dynamics derived fromEEG reflect variations in the BOLD signal. The purpose of our study was to correlate both spectral patterns, as linear features of EEG rhythms, and nonlinear EEG dynamic complexity with neuronal activity obtained by fMRI. We examined the relationships between EEG patterns and brain activation obtained by simultaneous EEG-fMRI during the resting state condition in 25 healthy right-handed adult volunteers. Using EEG-derived regressors, we demonstrated a substantial correlation of BOLD signal changes with linear and nonlinear features of EEG. We found the most significant positive correlation of fMRI signal with delta spectral power. Beta and alpha spectral features had no reliable effect on BOLD fluctuation. However, dynamic changes of alpha peak frequency exhibited a significant association with BOLD signal increase in right-hemisphere areas. Additionally, EEG dynamic complexity as measured by the HFD of the 2–20Hz EEG frequency range significantly correlated with the activation of cortical and subcortical limbic system areas. Our results indicate that both spectral features of EEG frequency bands and nonlinear dynamic properties of spontaneous EEG are strongly associated with fluctuations of the BOLD signal during the resting state condition.