DEPRESIVNOSTI VIZUELNO PAMĆENJE SPECIFIČNIH STIMULUSA (EMOTIKONA)

Depression is a state of reduced psychophysical activity that is accompanied by various changes in cognitive, emotional and social functioning. Previous studies have found that depression leads to changes in the recognition of the emotions of others, makes it difficult to direct attention and significantly impairs visual memory. The main goal of this research is to examine the relations between depressive symptoms and visual memory of specific stimuli that show emotions. We also want to examine whether the intensity of depressive symptoms is related to longer reaction time in the experimental task, as well as whether the accuracy of the emoticon’s visual memory depends on the set size. The research was conducted on a sample of 84 participants, students of Faculty of Philosophy in Banja Luka (90% female). The PHQ-9 questionnaire was used to assess depressive symptoms. Visual memory task was created in SuperLab 4.1. for Windows.The results show that there is a partial contribution of moderate depression to the accuracy of emoticon memory with sadness expression. No partial contribution of any category of depression to the memory accuracy of emoticons with the expression of happiness has been determined. A statistically significant negative correlation for the category of “sad” stimuli was obtained between the expression of depressive symptoms and the response time in the experimental task, while no statistically significant correlation was obtained for the second category of stimuli. It was also found that the number of errors increases with the set size. These results can be explained by negative bias and cognitive load in information processing. Key words: visual memory, depression, emoticons, expression of happiness, expression of sadness

Prediction of Visual Memorability with EEG Signals: A Comparative Study

Visual memorability is a method to measure how easily media contents can be memorized. Predicting the visual memorability of media contents has recently become more important because it can affect the design principles of multimedia visualization, advertisement, etc. Previous studies on the prediction of the visual memorability of images generally exploited visual features (e.g., color intensity and contrast) or semantic information (e.g., class labels) that can be extracted from images. Some other works tried to exploit electroencephalography (EEG) signals of human subjects to predict the memorability of text (e.g., word pairs). Compared to previous works, we focus on predicting the visual memorability of images based on human biological feedback (i.e., EEG signals). For this, we design a visual memory task where each subject is asked to answer whether they correctly remember a particular image 30 min after glancing at a set of images sampled from the LaMemdataset. During the visual memory task, EEG signals are recorded from subjects as human biological feedback. The collected EEG signals are then used to train various classification models for prediction of image memorability. Finally, we evaluate and compare the performance of classification models, including deep convolutional neural networks and classical methods, such as support vector machines, decision trees, and k-nearest neighbors. The experimental results validate that the EEG-based prediction of memorability is still challenging, but a promising approach with various opportunities and potentials.

RECURRENCE QUANTIFICATION ANALYSIS OF MCI EEG UNDER RESTING AND VISUAL MEMORY TASK CONDITIONS

The work aims at classifying EEG of mild cognitive impairment (MCI) patients from that of normal control (NC) subjects using recurrence quantification analysis (RQA) and a simple visual memory task, which is commonly used in memory clinics. EEG of MCI and NC groups are recorded under three cognitive conditions, resting eyes closed (EC) and two phases of the task, namely, picture viewing (learning phase, PIC) and picture recollection (immediate free recall phase, PICREC). Complexity analysis of EEG is performed using RQA measures, recurrence rate (RR) and entropy (ENTR). Mean values of these measures over electrodes from four cortical regions are used for statistical analysis of group differences, under the different cognitive conditions. In all the cortical regions, the mean RQA RR and ENTR values of MCI group are observed to be higher compared to NC group under the task conditions. Receiver operating characteristics (ROC) analysis is used for assessing the classification efficiency of the RQA-based method applied to EEG of MCI subjects. A fair classification is obtained in all the four cortical regions during the PIC condition using RR and in all regions except frontal, using ENTR. In the PICREC condition, a good classification is obtained in the temporal, parietal and occipital regions and a fair classification is attained in the frontal region using RR. In this condition, the ENTR values provided a fair classification in all the four cortical regions. These RQA measures are used as feature vectors of SVM classifier to further confirm the classification efficiency of the couplets of RQA RR and ENTR. These results indicate RQA method can efficiently classify MCI EEG based on complexity levels using the simple immediate free recall task.

Smell-based memory training: Evidence of olfactory learning and transfer to a visual task

Human and non-human animal research converge to suggest that the sense of smell, olfaction, has a high level of plasticity and is intimately associated with visual-spatial orientation and memory encoding networks. We investigated whether olfactory memory training would lead to transfer to an untrained visual memory task, as well as untrained olfactory tasks. We devised a memory intervention to compare transfer effects generated by olfactory and non-olfactory (visual) memory training. Adult participants were randomly assigned to daily memory training for about 40 days with either olfactory or visual tasks, that had a similar difficulty level. Results showed that while visual training did not produce transfer to the olfactory memory task, olfactory training produced transfer to the untrained visual memory task. Olfactory training also improved participants’ performance on odor discrimination and naming tasks, such that they reached the same performance level as a high-performing group of wine professionals. Our results indicate that the olfactory system is highly responsive to training, and we speculate that the sense of smell may facilitate transfer of learning to other sensory domains. Further research is however needed in order to replicate and extend our findings.

Single-exposure visual memory judgments are reflected in inferotemporal cortex

Our visual memory percepts of whether we have encountered specific objects or scenes before are hypothesized to manifest as decrements in neural responses in inferotemporal cortex (IT) with stimulus repetition. To evaluate this proposal, we recorded IT neural responses as two monkeys performed a single-exposure visual memory task designed to measure the rates of forgetting with time. We found that a weighted linear read-out of IT was a better predictor of the monkeys’ forgetting rates and reaction time patterns than a strict instantiation of the repetition suppression hypothesis, expressed as a total spike count scheme. Behavioral predictions could be attributed to visual memory signals that were reflected as repetition suppression and were intermingled with visual selectivity, but only when combined across the most sensitive neurons.

Single-exposure visual memory judgments are reflected in IT cortex

Our visual memory percepts of whether we have encountered specific objects or scenes before are hypothesized to manifest as decrements in neural responses in inferotemporal cortex (IT) with stimulus repetition. To evaluate this proposal, we recorded IT neural responses as two monkeys performed a single-exposure visual memory task designed to measure the rates of forgetting with time. We found that a weighted linear read-out of IT was a better predictor of the monkeys’ forgetting rates and reaction time patterns than a strict instantiation of the repetition suppression hypothesis, expressed as a total spike count scheme. Behavioral predictions could be attributed to visual memory signals that were reflected as repetition suppression and were intermingled with visual selectivity, but only when combined across the most sensitive neurons.

Muscarinic mechanisms in psychosis: A multimodal imaging study

BackgroundThe majority of people with psychosis suffer from cognitive problems. These cognitive problems are among the most disabling features of the illness and have a negative effect on clinical outcome. Research has demonstrated that acetylcholine including muscarinic receptors play an important role in cognitive function. A post-mortem study in chronic patients with schizophrenia demonstrated a decrease of 75% of muscarinic M1 receptors.AimThe aim of this study was to investigate the role of M1 receptors in-vivo in brain and cognitive function in psychosis.MethodsThirty medication free patients with psychosis and 30 healthy controls matched for age, gender and IQ were included for 1) 1x IDEX Spect scan to determine M1 binding potential; 2) 2x fMRI scan using a visual memory task; 3) 2x MRS to determine choline concentrations; 2x CANTAB cognitive battery. Except for SPECT all subjects were tested twice, once with placebo and once with biperiden M1 antagonist.ResultatenPatients demonstrated a significant negative correlation between M1 binding potential and cognitive impairments and negative symptom scores on PANSS. Following biperiden challenge, performance on verbal learning and memory was worse. Hippocampal activity was larger during a visual memory task in patients.ConclusieThese results support a role for the M1 receptor in cognitive function in psychosis.Disclosure of interestThe author has not supplied his/her declaration of competing interest.