Biology subjects

Bastos, A.

Publications and source records attributed to Bastos, A..

4 recordsLinked to original sources

bioRxiv2026

Evidence for predictive computations in a brain hierarchy during a visual search task

Many lines of evidence suggest that the cortex functions fundamentally as a predictive system, compressing high-dimensional sensory inputs into low-dimensional representations that support internal models of the environment. These models generate top-down signals that shape and filter incoming sensory information, prioritizing unpredicted, and thus more informative, inputs for further processing. Multiple, mutually compatible computational frameworks have been proposed to explain these mechanisms, including predictive coding, predictive routing, and autoencoder-based approaches. However, a key challenge remains in empirically disentangling their relative contributions. Here, we directly compared three candidate algorithms, predictive coding, routing and autoencoders using LFP data from a brain hierarchy acquired during a visual search task. Notably, predictive coding differs from alternative models in its capacity to dynamically optimize signal passing across brain hierarchies in an input-specific manner, while the other algorithms do not consider constraints on feedback or feedforward inputs. It also goes beyond pairwise interactions, by predicting information flow in triplets of brain areas; here, V4, 7A and PFC. We considered the characteristic patterns of neural dynamics and within-area coupling that distinct algorithms produce. These were subsequently used to assess the relative evidence of each algorithm in the face of the LFP data. Our results support a hybrid account: hierarchical message passing consistent with predictive coding appears necessary to explain deep-layer activity, while predictive suppression mechanisms, aligned with predictive routing, account for superficial-layer dynamics without requiring explicit error computations.

neuroscience↗

bioRxiv2022

A physical neural mass model framework for the analysis of oscillatory generators from laminar electrophysiological recordings

Cortical function emerges from the interactions of multi-scale networks that may be studied at a high level using neural mass models (NMM), representing the mean activity of large numbers of neurons. In order to properly reproduce experimental data, these models require the addition of further elements. Here we provide a framework integrating conduction physics that can be used to simulate cortical electrophysiology measurements, particularly those obtained from multi-contact laminar electrodes. This is achieved by endowing NMMs with basic physical properties, such as the average laminar location of the apical and basal dendrites of pyramidal cell populations. We call this framework laminar NMM, or LaNMM for short. We then employ this framework to infer the location of oscillatory generators from laminar-resolved data collected from the prefrontal cortex in the macaque monkey. Based on the literature on columnar connectivity, we define a minimal neural mass model capable of generating amplitude and phase coupled slow (alpha/beta, 4-22 Hz) and fast (gamma, 30-250 Hz) oscillations. The synapse layer locations of the two pyramidal cell populations are treated as optimization parameters, together with two more LaNMM-specific parameters, to compare the models with the multi-contact recordings. We rank the candidate models using an optimization function that evaluates the match between the functional connectivity (FC) of the model and data, where the FC is defined by the covariance between bipolar voltage measurements at different cortical depths. The family of best solutions reproduces the FC of the observed electrophysiology while selecting locations of pyramidal cells and their synapses that result in the generation of fast activity at superficial layers and slow activity across most depths, in line with recent literature proposals. HighlightsO_LIWe provide a neural mass modeling formalism that includes a physical layer to simulate electrophysiology measurements. C_LIO_LITo analyze in-vivo data collected in the macaque monkey during a memory task, we propose a specific model with two coupled main circuits that can generate realistic electrophysiological signals in two important oscillatory regimes--the alpha/beta and the gamma bands. C_LIO_LIPhysical elements in the model shed light on the generation of oscillations in the two regimes and on the relative power distribution of fast and slow oscillatory signals across cortical depth, which we show can be altered by the choice of the reference location or method. C_LIO_LIThe model is contrasted with in-vivo data, with parameters adjusted by matching voltage statistics in the alpha/beta and gamma bands, leading to a solution with slow frequency components generated by synapses spanning most cortical layers and fast oscillations in superficial layers. C_LIO_LIThe resulting formalism provides useful tools and concepts to analyze and model data, with implications for understanding altered oscillatory EEG activity in dementia, Alzheimers disease and other disorders with oscillatory features. C_LI

neuroscience↗

bioRxiv2020

Layer and rhythm specificity for predictive routing

In predictive coding, experience generates predictions that attenuate the feeding forward of predicted stimuli while passing forward unpredicted "errors". Different models have different neural implementations of predictive coding. We recorded spikes and local field potentials from laminar electrodes in five cortical areas (V4, LIP, area 7A, FEF, and PFC) while monkeys performed a task that modulated visual stimulus predictability. Pre-stimulus predictions were associated with increased alpha/beta (8-30 Hz) power/coherence that fed back the cortical hierarchy primarily via deep-layer cortex. Unpredictable stimuli were associated with increases in spiking and in gamma-band (40-90 Hz) power/coherence that fed forward up the cortical hierarchy via superficial-layer cortex. Area 7A uniquely showed increases in high-beta (~22-28 Hz) power/coherence to unpredicted stimuli. These results suggest that predictive coding may be implemented via lower-frequency alpha/beta rhythms that "prepare" pathways processing predicted inputs by inhibiting feedforward gamma rhythms and associated spiking.

neuroscience↗

bioRxiv2019

Natural infection and vertical transmission of two flaviviruses (Yellow fever and Zika) in mosquitoes in primary forests in the Brazilian state of Rio de Janeiro (Diptera: Culicidae)

BackgroundZika virus (ZIKV) was recently introduced in the American continent, probably transmitted by Aedes aegypti and possibly by Ae. albopictus and Culex quinquefasciatus in urban environments. ZIKV represents a known public health problem as it has been involved in newborn cases of congenital microcephaly in South America since 2005. The transmission of this virus in forested areas of other countries and its relative ubiquity in relation to its vectors and reservoirs raises suspicions of its adaptation to non-human modified environments (i.e., natural forests reserve) or on this continent, similar to those seen for Yellow fever virus (YFV). The objective of this work was to have an epidemiological monitoring tool mapping insects as well as circulating arboviruses in wild areas with low human interference. This study was based on the history of the insect flavivirus spreading cycle.\n\nMethods/Principal FindingsUsing a previously described sensitive PCR-based assay to assess the conserved NS5 region of the Flavivirus genus, both YFV partial genome and ZIKV were found in pools of Aedes albopictus, a sylvatic mosquito adapted to human-modified environments, and in Haemagogus leucocelaenus, a sylvatic mosquito.\n\nConclusionsThis is the first report of natural infection by ZIKV in mosquitoes in a sylvatic environment on the American continent. The wide distribution of these mosquitoes is probably important in the transmission of ZIKV. Vertical transmission indicates a higher efficiency for the maintenance and transmission of the virus in nature as well as the presence of the ZIKV in permanent character in the forest areas as it occurs with the YFV thus making more difficult the prevention of new cases of Zika in humans.\n\nAuthor SummaryArboviruses are diseases transmitted by arthropod vectors, hence the origin of the term ARthropod BOrne VIRUS, which is adopted since 1942. This work had as objective to survey the circulating insects as well as to detect the presence of viruses in them. Arboviruses circulate between insects and vertebrate hosts, having importance for promoting diseases in humans and animals. The diseases most known at the time, due to the recent cases reported by South America, are Dengue, Zika, Yellow Fever and Chikungunya. For this study, we used appropriate traps to collect the insects and their eggs in wild areas where there is little human interference. After collection, mosquitoes and / or eggs were identified and separated as to the source and species. The eggs were kept in laboratory conditions for the hatching of new insects. All the insects obtained were separated into pools to be macerated and thus extract the RNA from the viruses to be studied. Using molecular biology techniques, in our case the RT-PCR (Reverse Transcriptase Polymerase Chain Reaction), we amplified the RNA and in sequentially, we performed the sequencing reaction. With sequencing, it is possible to identify which virus material is present since each virus has a characteristic arrangement. For the identification of the sequences, we need to use some computational programs that guarantee us the correct result.

molecular biology↗