Diego Fernández Slezak

University of Buenos Aires | UBA · Department of Computer Sciences (FCEN)

Background The persisting cognitive symptoms observed in individuals after a Covid‐19 infection (long‐Covid) remain an enigmatic aspect of the disease. Clinical descriptions in the literature are dissimilar, suggesting more than one clinical phenotype. Our study aims to explore cognitive performance and brain network of long‐Covid patients, to dete...

Background Early detection of Mild Cognitive Impairment (MCI) is crucial for effective prevention. Traditional methods like expert judgment, clinical evaluations, and manual linguistic analyses are now complemented by Artificial Intelligence (AI). AI offers new avenues for identifying linguistic, facial, and acoustic markers of MCI. The exploration...

Background and purpose Subjective cognitive complaints post‐COVID‐19, known as long‐COVID, have unclear effects on neural activity. This study explores the neural basis of these cognitive impairments by comparing resting‐state functional networks of long‐COVID individuals to a control group. Methods Forty‐two individuals with cognitive complaints...

Mate Marote is an open-access cognitive training software aimed at children between 4 and 8 years old. It consists of a set of computerized games specifically tailored to train and evaluate Executive Functions (EF), a class of processes critical for purposeful, goal-directed behavior, including working memory, planning, flexibility, and inhibitory...

Spatio-temporal patterns of evoked brain activity contain information that can be used to decode and categorize the semantic content of visual stimuli. This procedure can be biased by statistical regularities which can be independent from the concepts that are represented in the stimuli, prompting the need to dissociate between the contributions of...

Objectives: Evaluate the performance of a deep learning (DL)-based model for multiple sclerosis (MS) lesion segmentation and compare it to other DL and non-DL algorithms. Methods: This ambispective, multicenter study assessed the performance of a DL-based model for MS lesion segmentation and compared it to alternative DL- and non-DL-based method...

Executive functions like working memory, inhibitory control, and cognitive flexibility are a set of neurocognitive processes involved in reasoning, planning, and self-regulatory skills that allow goal-oriented behaviors. Mounting evidence supports the importance of these processes for educational success from early on. Executive functions can be im...

Numerous works use word embedding-based metrics to quantify societal biases and stereotypes in texts. Recent studies have found that word embeddings can capture semantic similarity but may be affected by word frequency. In this work we study the effect of frequency when measuring female vs. male gender bias with word embedding-based bias quantifica...

Recent research has shown that static word embeddings can encode word frequency information. However, little has been studied about this phenomenon and its effects on downstream tasks. In the present work, we systematically study the association between frequency and semantic similarity in several static word embeddings. We find that Skip-gram, Glo...

The 'day residue' - the presence of waking memories into dreams - is a century-old concept that remains controversial in neuroscience. Even at the psychological level, it remains unclear how waking imagery cedes into dreams. Are visual and affective residues enhanced, modified, or erased at sleep onset? Are they linked, or dissociated? What are the...

The epileptic network hypothesis and epileptogenic zone hypothesis are two theories of ictogenesis. The network hypothesis posits that coordinated activity among interconnected nodes produces seizures. The epileptogenic zone hypothesis posits that distinct regions are necessary and sufficient for seizure generation. High-frequency oscillations, and...

Executive functions are a class of cognitive processes critical for purposeful goal-directed behavior. Cognitive training is the adequate stimulation of executive functions and has been extensively studied and applied for more than 20 years. However, there is still a lack of solid consensus in the scientific community about its potential to elicit...

The epileptic network hypothesis and epileptogenic zone (EZ) hypothesis are two theories of ictogenesis. The network hypothesis posits that coordinated activity among interconnected nodes produces seizures. The EZ hypothesis posits that distinct regions are necessary and sufficient for seizure generation. High-frequency oscillations (HFOs), and par...

Measuring human capabilities to synchronize in time, adapt to perturbations to timing sequences, or reproduce time intervals often requires experimental setups that allow recording response times with millisecond precision. Most setups present auditory stimuli using either MIDI devices or specialized hardware such as Arduino and are often expensive...

Measuring human capabilities to synchronize in time, adapt to perturbations to timing sequences or reproduce time intervals often require experimental setups that allow recording response times with millisecond precision. Most setups present auditory stimuli using either MIDI devices or specialized hardware such as Arduino and are often expensive o...

In recent years, the use of word embeddings has become popular to measure the presence of biases in texts. Despite the fact that these measures have been shown to be effective in detecting a wide variety of biases, metrics based on word embeddings lack transparency, explainability and interpretability. In this study, we propose a PMI-based metric t...

While technology has dramatically changed medical practice, various aspects of mental health practice and diagnosis remain almost unchanged across decades. Here we argue that artificial intelligence — with its capacity to learn and infer from data the workings of the human mind — may rapidly change this scenario. However, this process will not happ...

Background Graph analysis detects psychosis and literacy acquisition. Bronze Age literature has been proposed to contain childish or psychotic features, which would only have matured during the Axial Age (∼800-200 BC), a putative boundary for contemporary mentality. Method Graph analysis of literary texts spanning ∼4,500 years shows remarkable asy...

Purpose To investigate the diagnostic performance of an Artificial Intelligence (AI) system for detection of COVID-19 in chest radiographs (CXR), and compare results to those of physicians working alone, or with AI support. Materials and methods An AI system was fine-tuned to discriminate confirmed COVID-19 pneumonia, from other viral and bacteria...

Pulse is the base timing to which western music is commonly notated, generally expressed by a listener by performing periodic taps with their hand or foot. This cognitive construction helps organize the perception of timed events in music and is the most basic expectation in rhythms. The analysis of expectations, and more specifically the strength...

Background and purpose There are instances in which an estimate of the brain volume should be obtained from MRI in clinical practice. Our objective is to calculate cross-sectional robustness of a convolutional neural network (CNN) based software (Entelai Pic) for brain volume estimation and compare it to traditional software such as FreeSurfer, CAT...

Automatic segmentation of white matter hyperintensities in magnetic resonance images is of paramount clinical and research importance. Quantification of these lesions serve as a predictor for risk of stroke, dementia and mortality. During the last years, convolutional neural networks (CNN) specifically tailored for biomedical image segmentation hav...

Ripple oscillations (80–200 Hz) in the normal hippocampus are involved in memory consolidation during rest and sleep. In the epileptic brain, increased ripple and fast ripple (200–600 Hz) rates serve as a biomarker of epileptogenic brain. We report that both ripples and fast ripples exhibit a preferred phase angle of coupling with the trough-peak (...

When we read printed text, we are continuously predicting upcoming words to integrate information and guide future eye movements. Thus, the Predictability of a given word has become one of the most important variables when explaining human behaviour and information processing during reading. In parallel, the Natural Language Processing (NLP) field...

Pathological high frequency oscillations (HFOs) are putative neurophysiological biomarkers of epileptogenic brain tissue. Utilizing HFOs for epilepsy surgery planning offers the promise of improved seizure outcomes for patients with medically refractory epilepsy. This review discusses possible machine learning strategies that can be applied to HFO...

Brain lesion and anatomy segmentation in magnetic resonance images are fundamental tasks in neuroimaging research and clinical practice. Given enough training data, convolutional neuronal networks (CNN) proved to outperform all existent techniques in both tasks independently. However, to date, little work has been done regarding simultaneous learni...

The problem of skill acquisition is ubiquitous and fundamental to life. Most tasks in modern society involve the cooperation with other subjects. Notwithstanding its fundamental importance, teammate selection is commonly overlooked when studying learning. We exploit the virtually infinite repository of human behavior available in Internet to study...

Details about the gameplay: Rules, maps, limits and mechanics. Fig A: The probability of winning as a function of the skill difference between: (a) Case of two individual opponents and two team opponents. (c) Case of three opponents. Fig B: Histogram of skill. Fig C: Learning curve of committed population. Fig D: Learning curve of population of pla...

TrueSkill, Technical Report. Analytical computation of the posterior distribution. This file includes details about update rules and the derivation of used expressions. (PDF)

Determining the state of consciousness in patients with disorders of consciousness is a challenging practical and theoretical problem. Recent findings suggest that multiple markers of brain activity extracted from the EEG may index the state of consciousness in the human brain. Furthermore, machine learning has been found to optimize their capacity...

Objective: Evaluate accuracy and safety of an artificial intelligent (AI) system for nonacute headache diagnosis. Background: Headache is the main cause of neurologic consultation, entailing high cost in healthcare systems and a great impact in quality of life of patients suffering from it. Moreover, the access to qualified specialists and appropr...

Background Language offers a privileged view into the mind; it is the basis by which we infer others’ thoughts. Subtle language disturbance is evident in schizophrenia prior to psychosis onset, including decreases in coherence and complexity, as measured using clinical ratings in familial and clinical high-risk (CHR) cohorts. Bearden et al previous...

We present a theory of decision-making in the presence of multiple choices that departs from traditional approaches by explicitly incorporating entropic barriers in a stochastic search process. We analyze response time data from an on-line repository of 15 million blitz chess games, and show that our model fits not just the mean and variance, but t...

Supplemental materials. Analytic solutions of First Passage Time distributions. Individual player and automata RT distributions. (PDF)

Language and speech are the primary source of data for psychiatrists to diagnose and treat mental disorders. In psychosis, the very structure of language can be disturbed, including semantic coherence (e.g., derailment and tangentiality) and syntactic complexity (e.g., concreteness). Subtle disturbances in language are evident in schizophrenia even...

Background: Natural speech analytics has seen some improvements over recent years, and this has opened a window for objective and quantitative diagnosis in psychiatry. Here, we used a machine learning algorithm applied to natural speech to ask whether language properties measured before psilocybin for treatment-resistant can predict for which pati...

We present a theory of decision-making in the presence of multiple choices that departs from traditional approaches by explicitly incorporating entropic barriers in a stochastic search process. We analyze response time data from an on-line repository of 15 million blitz chess games, and show that our model fits not just the mean and variance, but t...

Latent Semantic Analysis (LSA) and Word2vec are some of the most widely used word embeddings. Despite the popularity of these techniques, the precise mechanisms by which they acquire new semantic relations between words remain unclear. In the present article we investigate whether LSA and Word2vec capacity to identify relevant semantic dimensions i...

Objective: We here aimed at characterizing heart-brain interactions in patients with disorders of consciousness. We tested how this information impacts data-driven classification between unresponsive and minimally conscious patients. Methods: A cohort of 127 patients in vegetative state/unresponsive wakefulness syndrome (VS/UWS; n = 70) and mini...

Computer-based dreams content analysis relies on word frequencies within predefined categories in order to identify different elements in text. As a complementary approach, we explored the capabilities and limitations of word-embedding techniques to identify word usage patterns among dream reports. These tools allow us to quantify words association...

Human behavior and physiology exhibit diurnal fluctuations. These rhythms are entrained by light and social cues, with vast individual differences in the phase of entrainment - referred as an individual’s chronotype - ranging in a continuum between early larks and late owls. Understanding whether decision-making in real-life situations depends on t...

Discourse varies with age, education, psychiatric state and historical epoch, but the ontogenetic and cultural dynamics of discourse structure remain to be quantitatively characterized. To this end we investigated word graphs obtained from verbal reports of 200 subjects ages 2-58, and 676 literary texts spanning ~5,000 years. In healthy subjects, l...

Word embeddings have been extensively studied in large text datasets. However, only a few studies analyze semantic representations of small corpora, particularly relevant in single-person text production studies. In the present paper, we compare Skip-gram and LSA capabilities in this scenario, and we test both techniques to extract relevant semanti...

Psychosis is a mental syndrome associated to loss of contact with reality which may arise in patients with different diseases, such as schizophrenia or bipolar disorder. Symptoms include hallucinations, confused and disturbed thoughts or lack of self-awareness. Recent studies have found that psychotic patients can be objectively screened using grap...

To assess the impact of Parkinson’s disease (PD) on spontaneous discourse, we conducted computerized analyses of brief monologues produced by 51 patients and 50 controls. We explored differences in semantic fields (via latent semantic analysis), grammatical choices (using part-of-speech tagging), and word-level repetitions (with graph embedding too...

The massive availability of digital repositories of human thought opens radical novel way of studying the human mind. Natural language processing tools and computational models have evolved such that many mental conditions are predicted by analysing speech. Transcription of interviews and discourses are analyzed using syntactic, grammatical or sent...

La humanidad atraviesa uno de los cambios tecnológicos más importantes de su historia, a partir de la introducción progresiva en la vida cotidiana, educativa y laboral de las tecnologías de la comunicación y de la información (TIC). En la actualidad, si bien persisten brechas tecnológicas entre los países del mundo, debido a las diferencias en el d...

Objectives: To estimate trends of undernutrition (stunting and underweight) among children younger than 5 years covered by the universal health coverage programs Plan Nacer and Programa Sumar. Methods: From 2005 to 2013, Plan Nacer and Programa Sumar collected high-quality information on birth and visit dates, age (in days), gender, weight (in k...

Inner concepts are much richer than the words that describe them. Our general objective is to inquire what are the best procedures to communicate conceptual knowledge. We construct a simplified and controlled setup emulating important variables of pedagogy amenable to quantitative analysis. To this aim, we designed a game inspired in Chinese Whispe...

Background/objectives: Psychiatry lacks the objective clinical tests routinely used in other specializations. Novel computerized methods to characterize complex behaviors such as speech could be used to identify and predict psychiatric illness in individuals. Aims: In this proof-of-principle study, our aim was to test automated speech analyses c...

There is a prevailing belief that interruptions using cellular phones during face to face interactions may affect severely how people relate and perceive each other. We set out to determine this cost quantitatively through an experiment performed in dyads, in a large audience in a TEDx event. One of the two participants (the speaker) narrates a sto...

We investigate the dynamics of semantic organization using social media, a collective expression of human thought. We propose a novel, time-dependent semantic similarity measure (TSS), based on the social network Twitter. We show that TSS is consistent with static measures of similarity but provides high temporal resolution for the identification o...

Supplemental material compares TSS measure to Joint Frequency. JF showed a strong correlation with TSS, but TSS showed higher performance in the evaluation datasets.

Significance Executive functions (EF) imply processes critical for purposeful, goal-directed behavior. In children, evidence derived from laboratory measures indicates that training can improve EF. However, this hypothesis has never been explicitly examined based on real-world measures, especially of educational achievement. Here, we investigate wh...

Abused drugs can profoundly alter mental states in ways that may motivate drug use. These effects are usually assessed with self-report, an approach that is vulnerable to biases. Analyzing speech during intoxication may present a more direct, objective measure, offering a unique 'window' into the mind. Here, we employed computational analyses of sp...

Theories of expertise based on the acquisition of chunk and templates suggest a differential geometric organization of perception between experts and novices. It is implied that expert representation is less anchored by spatial (Euclidean) proximity and may instead be dictated by the intrinsic relation in the structure and grammar of the specific d...

Background / Purpose: Abused drugs can produce profound mental state alterations. Measuring these effects by self-report relies on the capacity to accurately report introspective experiences. Analyzing content of speech during intoxication may present a more direct “window” into these effects. We employed computational analysis of speech semantic...

Grid computing refers to the federation of geographically distributed and heterogeneous computer resources. These resources may belong to different administrative domains, but are shared among users. Every grid presents a key component responsible for obtaining, distributing, indexing and archiving information about the configuration and state of s...