Cholinergic neuromodulation of prefrontal attractor dynamics controls performance in spatial working memory.

The behavioral and neural effects of the endogenous release of acetylcholine following stimulation of the Nucleus Basalis of Meynert (NB) have been recently examined in two male monkeys (Qi et al. 2021). Counterintuitively, NB stimulation enhanced behavioral performance while broadening neural tuning in the prefrontal cortex (PFC). The mechanism by which a weaker mnemonic neural code could lead to better performance remains unclear. Here, we show that increased neural excitability in a simple continuous bump attractor model can induce broader neural tuning and decrease bump diffusion, provided neural rates are saturated. Increased memory precision in the model overrides memory accuracy, improving overall task performance. Moreover, we show that bump attractor dynamics can account for the nonuniform impact of neuromodulation on distractibility, depending on distractor distance from the target. Finally, we delve into the conditions under which bump attractor tuning and diffusion balance in biologically plausible heterogeneous network models. In these discrete bump attractor networks, we show that reducing spatial correlations or enhancing excitatory transmission can improve memory precision. Altogether, we provide a mechanistic understanding of how cholinergic neuromodulation controls spatial working memory through perturbed attractor dynamics in PFC.Significance statement Acetylcholine has been thought to improve cognitive performance by sharpening neuronal tuning in prefrontal cortex. Recent work has shown that electrical stimulation of the cholinergic forebrain in awake-behaving monkeys induces a reduction in prefrontal neural tuning under stimulation conditions that improve performance. To reconcile these divergent observations, we provide network simulations showing that these derive consistently from specific conditions in prefrontal attractor dynamics: firing rate saturation leads to increased storage precision and reduced neural tuning upon cholinergic activation via an increase in neural excitability, a reduction in neural correlations, and an increase in excitatory transmission. Our study integrates previously reported data into a consistent mechanistic view of how acetylcholine controls spatial working memory via attractor network dynamics in prefrontal cortex.

Neurological, psychiatric, and sleep investigations after treatment of anti-leucine-rich glioma-inactivated protein 1 (LGI1) encephalitis in Spain: a prospective cohort study.

BACKGROUND: Anti-leucine-rich glioma-inactivated protein 1 (LGI1) encephalitis is an autoimmune disorder that can be treated with immunotherapy, but the symptoms that remain after treatment have not been well described. We aimed to characterise the clinical features of patients with anti-LGI1 encephalitis for 1 year starting within the first year after initial immunotherapy. METHODS: For this prospective cohort study, we recruited patients with anti-LGI1 encephalitis as soon as possible after they had received conventional immunotherapy for initial symptoms; patients were recruited from 21 hospitals in Spain. Patients were excluded if they had an interval of more than 1 year since initial immunotherapy, had pre-existing neurodegenerative or psychiatric disorders, or were unable to travel to Hospital Clínic de Barcelona (Barcelona, Spain). Patients visited Hospital Clínic de Barcelona on three occasions-the first at study entry (visit 1), the second 6 months later (visit 2), and the third 12 months after the initial visit (visit 3). They underwent neuropsychiatric and videopolysomnography assessments at each visit. Healthy participants who were matched for age and sex and recruited from Hospital Clínic de Barcelona underwent the same investigations at study entry and at 12 months. Cross-sectional comparisons of clinical features between groups were done with conditional logistic regression, and binary logistic regression was used to assess associations between cognitive outcomes at 12 months and clinical features before initial immunotherapy and at study entry. FINDINGS: Between May 1, 2019, and Sept 30, 2022, 42 participants agreed to be included in this study. 24 (57%) participants had anti-LGI1 encephalitis (mean age 63 years [SD 12]; 13 [54%] were female and 11 [46%] were male) and 18 (43%) were healthy individuals (mean age 62 years [10]; 11 [61%] were female and seven [39%] were male). At visit 1 (median 88 days [IQR 67-155] from initiation of immunotherapy), all 24 patients had one or more symptoms; 20 (83%) patients had cognitive deficits, 20 (83%) had psychiatric symptoms, 14 (58%) had insomnia, 12 (50%) had rapid eye movement (REM)-sleep behaviour disorder, nine (38%) had faciobrachial dystonic seizures, and seven (29%) had focal onset seizures. Faciobrachial dystonic seizures were unnoticed in four (17%) of 24 patients and focal onset seizures were unnoticed in five (21%) patients. At visit 1, videopolysomnography showed that 19 (79%) patients, but no healthy participants, had disrupted sleep structure (p=0·013); 15 (63%) patients and four (22%) healthy participants had excessive fragmentary myoclonus (p=0·039), and nine (38%) patients, but no healthy participants, had myokymic discharges (p=0·0051). These clinical and videopolysomnographic features led to additional immunotherapy in 15 (63%) of 24 patients, which resulted in improvement of these features in all 15 individuals. However, at visit 3, 13 (65%) of 20 patients continued to have cognitive deficits. Persistent cognitive deficits at visit 3 were associated with no use of rituximab before visit 1 (odds ratio [OR] 4·0, 95% CI 1·5-10·7; p=0·0015), REM sleep without atonia at visit 1 (2·2, 1·2-4·2; p=0·043), and presence of LGI1 antibodies in serum at visit 1 (11·0, 1·1-106·4; p=0·038). INTERPRETATION: Unsuspected but ongoing clinical and videopolysomnography alterations are common in patients with anti-LGI1 encephalitis during the first year or more after initial immunotherapy. Recognising these alterations is important as they are treatable, can be used as outcome measures in clinical trials, and might influence cognitive outcome. FUNDING: Fundació La Caixa.

Alpha phase-coding supports feature binding during working memory maintenance.

Working memory (WM) is the ability to retain and manipulate information in mind, which allows mnemonic representations to flexibly guide behavior. Successful WM requires that objects' individual features are bound into cohesive representations, however the mechanisms supporting feature binding remain unclear. Binding errors (or swaps) provide a window into the intrinsic limits in capacity of WM. We tested the hypothesis that binding in WM is accomplished via neural phase synchrony and swaps result from its perturbations. Using magnetoencephalography data collected from human subjects, in a task designed to induce swaps, we showed that swaps are characterized by reduced phase-locked oscillatory activity during memory retention. We found that this reduction arises from increased phase-coding variability in the alpha-band, over a distributed network of sensorimotor areas. Our findings support the notion that feature binding in WM is accomplished through phase-coding dynamics that emerge from the competition between different memories.

Cholinergic neuromodulation of prefrontal attractor dynamics controls performance in spatial working memory.

The behavioral and neural effects of the endogenous release of acetylcholine following stimulation of the Nucleus Basalis of Meynert (NB) have been recently examined (Qi et al. 2021). Counterintuitively, NB stimulation enhanced behavioral performance while broadening neural tuning in the prefrontal cortex (PFC). The mechanism by which a weaker mnemonic neural code could lead to better performance remains unclear. Here, we show that increased neural excitability in a simple continuous bump attractor model can induce broader neural tuning and decrease bump diffusion, provided neural rates are saturated. Increased memory precision in the model overrides memory accuracy, improving overall task performance. Moreover, we show that bump attractor dynamics can account for the nonuniform impact of neuromodulation on distractibility, depending on distractor distance from the target. Finally, we delve into the conditions under which bump attractor tuning and diffusion balance in biologically plausible heterogeneous network models. In these discrete bump attractor networks, we show that reducing spatial correlations or enhancing excitatory transmission can improve memory precision. Altogether, we provide a mechanistic understanding of how cholinergic neuromodulation controls spatial working memory through perturbed attractor dynamics in PFC.

Country-level gender inequality is associated with structural differences in the brains of women and men.

Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women's worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7,876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women's brains and provide initial evidence for neuroscience-informed policies for gender equality.

Effects of sulfamethoxazole exposure on mussels (Mytilus galloprovincialis) metabolome using retrospective non-target high-resolution mass spectrometry and chemometric tools.

In this work, the Regions of Interest-Multivariate Curve Resolution (ROIMCR) method is proposed for the analysis of non-target metabolomics data. Samples from marine mussels (Mytilus galloprovincialis) exposed to a sublethal concentration (10 µg/L) of sulfamethoxazole (SMX) during 4 days in different seasonal conditions (summer and winter) were analyzed by High-Performance Liquid Chromatography - High-Resolution Mass Spectrometry (HPLC-HRMS) to study the effect of their exposure to SMX and the different seasonal conditions. The Regions of Interest (ROI) procedure has been applied for data filtering, compression, preprocessing and storage steps. Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) is then applied to the previously MS ROI preprocessed data sets to resolve the elution profiles and spectral fingerprints of the chemical constituents of the analyzed samples. The peak areas of the elution profiles of the chemical constituents resolved by the combined ROIMCR procedure were analyzed by Principal Component Analysis (PCA) and samples were clustered according to their experimental seasonal and SMX exposure. The effects of the two investigated factors and of their interaction on the concentrations of the metabolites were statistically assessed by ANOVA simultaneous component analysis (ASCA). Both types of analyses, PCA clustering and ASCA, confirmed that the seasonal conditions (summer versus winter) produced larger effects than those produced by the exposure to SMX and by the interaction of these two factors. The concentration changes of 16 identified endogenous metabolites were validated individually using a Wilcoxon statistical test, which confirmed the presence of significant disturbances in the levels of some of these metabolites (free fatty acids, amino acids and nucleic acids), and indicated the possible alteration of six different biological pathways, affected by the investigated seasonal and SMX exposure factors.

Clinical characterisation of patients in the post-acute stage of anti-NMDA receptor encephalitis: a prospective cohort study and comparison with patients with schizophrenia spectrum disorders.

BACKGROUND: Anti-NMDA receptor (NMDAR) encephalitis is associated with a post-acute stage that is not well known. We aimed to describe the clinical features of this stage, similarities with schizophrenia spectrum disorders, and the factors that predict cognitive-psychiatric outcomes and could serve as prognostic biomarkers. METHODS: In this prospective cohort study, participants (aged 12-60 years) with anti-NMDAR encephalitis during the post-acute stage visited Hospital Clínic de Barcelona (Barcelona, Spain) on three occasions (at study entry [V1], at 6 months [V2], and at 12 months [V3]) and underwent comprehensive neuropsychiatric evaluations. Similar evaluations were done in a group of age-matched participants with schizophrenia spectrum disorders and a group of age-matched and sex-matched healthy participants also recruited from Hospital Clínic de Barcelona. We analysed differences between and within groups in the longitudinal follow-up using multilevel linear mixed-effect models, adjusting for group, age, sex, and socioeconomic status to control for possible confounding. FINDINGS: Between Jan 1, 2017, and Sept 30, 2020, 82 participants were recruited, 28 (34%) with anti-NMDAR encephalitis, 27 (33%) with schizophrenia spectrum disorders, and 27 (33%) healthy participants. Although, by V1 (median 4 months [IQR 3-7] from disease onset), many acute-stage symptoms in participants with anti-NMDAR encephalitis had resolved (acute stage median modified Rankin Scale [mRS] score 5 [IQR 4-5] vs V1 mRS score 2 [1-2]; p<0·0001), 25 (89%) participants showed deficits in at least one cognitive domain. In this group, 15 (68%) of 22 cognitive domain variables were impaired at V1, whereas only eight (36%) were altered at V3 (p=0·016). In participants with schizophrenia spectrum disorders, 11 (50%) of 22 variables (all shared with participants with anti-NMDAR encephalitis) were impaired at V1, without changes at V3. Two acute-stage features of anti-NMDAR encephalitis (ie, decreased consciousness and no improvement within the first 4 weeks of treatment) predicted cognitive domain outcomes, and a visuospatial task (ie, serial biases) at V1 showed potential in predicting learning and memory outcomes. At V1, all psychiatric symptom clusters were similarly altered in participants with anti-NMDAR encephalitis and in those with schizophrenia spectrum disorders, but only those in individuals with anti-NMDAR encephalitis subsequently improved (p=0·031). The greatest cognitive-psychiatric improvement in participants with anti-NMDAR encephalitis occurred between V1 and V2. During this interval, four (14%) participants with anti-NMDAR encephalitis would have met the diagnostic criteria of schizophrenia if CSF antibody findings had not been investigated. INTERPRETATION: The cognitive-psychiatric symptoms of anti-NMDAR encephalitis in the post-acute stage resembled those of stabilised schizophrenia, but only those in participants with anti-NMDAR encephalitis progressively improved, predominantly during V1-V2. These findings are important for clinical trials on anti-NMDAR encephalitis and suggest that prompt cognitive-psychosocial rehabilitation might be a valuable intervention. FUNDING: Instituto Salud Carlos III, NEURON Network of European Funding for Neuroscience Research, National Alliance for Research in Schizophrenia and Affective Disorders, and la Caixa Health-Research Foundation.

Assessing wastewater-based epidemiology for the prediction of SARS-CoV-2 incidence in Catalonia.

While wastewater-based epidemiology has proven a useful tool for epidemiological surveillance during the COVID-19 pandemic, few quantitative models comparing virus concentrations in wastewater samples and cumulative incidence have been established. In this work, a simple mathematical model relating virus concentration and cumulative incidence for full contagion waves was developed. The model was then used for short-term forecasting and compared to a local linear model. Both scenarios were tested using a dataset composed of samples from 32 wastewater treatment plants and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) incidence data covering the corresponding geographical areas during a 7-month period, including two contagion waves. A population-averaged dataset was also developed to model and predict the incidence over the full geography. Overall, the mathematical model based on wastewater data showed a good correlation with cumulative cases and allowed us to anticipate SARS-CoV-2 incidence in one week, which is of special relevance in situations where the epidemiological monitoring system cannot be fully implemented.

Correction: Pinging the brain with visual impulses reveals electrically active, not activity-silent, working memories.

[This corrects the article DOI: 10.1371/journal.pbio.3001436.].

Towards biologically constrained attractor models of schizophrenia.

Alterations in neuromodulation or synaptic transmission in biophysical attractor network models, as proposed by the dominant dopaminergic and glutamatergic theories of schizophrenia, successfully mimic working memory (WM) deficits in people with schizophrenia (PSZ). Yet, multiple, often opposing alterations in memory circuits can lead to the same behavioral patterns in these network models. Here, we critically revise the computational and experimental literature that links NMDAR hypofunction to WM precision loss in PSZ. We show in network simulations that currently available experimental evidence cannot set apart competing biophysical accounts. Critical points to resolve are the effects of increases vs. decreases in E/I ratio (e.g. through NMDAR blockade) on firing rate tuning and shared noise modulations and possible concomitant deficits in short-term plasticity. We argue that these concerted experimental and computational efforts will lead to a better understanding of the neurobiology underlying cognitive deficits in PSZ.

Across-Area Synchronization Supports Feature Integration in a Biophysical Network Model of Working Memory.

Working memory function is severely limited. One key limitation that constrains the ability to maintain multiple items in working memory simultaneously is so-called swap errors. These errors occur when an inaccurate response is in fact accurate relative to a non-target stimulus, reflecting the failure to maintain the appropriate association or "binding" between the features that define one object (e.g., color and location). The mechanisms underlying feature binding in working memory remain unknown. Here, we tested the hypothesis that features are bound in memory through synchrony across feature-specific neural assemblies. We built a biophysical neural network model composed of two one-dimensional attractor networks - one for color and one for location - simulating feature storage in different cortical areas. Within each area, gamma oscillations were induced during bump attractor activity through the interplay of fast recurrent excitation and slower feedback inhibition. As a result, different memorized items were held at different phases of the network's oscillation. These two areas were then reciprocally connected via weak cortico-cortical excitation, accomplishing binding between color and location through the synchronization of pairs of bumps across the two areas. Encoding and decoding of color-location associations was accomplished through rate coding, overcoming a long-standing limitation of binding through synchrony. In some simulations, swap errors arose: "color bumps" abruptly changed their phase relationship with "location bumps." This model, which leverages the explanatory power of similar attractor models, specifies a plausible mechanism for feature binding and makes specific predictions about swap errors that are testable at behavioral and neurophysiological levels.

Pinging the brain with visual impulses reveals electrically active, not activity-silent, working memories.

Persistently active neurons during mnemonic periods have been regarded as the mechanism underlying working memory maintenance. Alternatively, neuronal networks could instead store memories in fast synaptic changes, thus avoiding the biological cost of maintaining an active code through persistent neuronal firing. Such "activity-silent" codes have been proposed for specific conditions in which memories are maintained in a nonprioritized state, as for unattended but still relevant short-term memories. A hallmark of this "activity-silent" code is that these memories can be reactivated from silent, synaptic traces. Evidence for "activity-silent" working memory storage has come from human electroencephalography (EEG), in particular from the emergence of decodability (EEG reactivations) induced by visual impulses (termed pinging) during otherwise "silent" periods. Here, we reanalyze EEG data from such pinging studies. We find that the originally reported absence of memory decoding reflects weak statistical power, as decoding is possible based on more powered analyses or reanalysis using alpha power instead of raw voltage. This reveals that visual pinging EEG "reactivations" occur in the presence of an electrically active, not silent, code for unattended memories in these data. This crucial change in the evidence provided by this dataset prompts a reinterpretation of the mechanisms of EEG reactivations. We provide 2 possible explanations backed by computational models, and we discuss the relationship with TMS-induced EEG reactivations.

Nucleus basalis stimulation enhances working memory by stabilizing stimulus representations in primate prefrontal cortical activity.

Acetylcholine plays a critical role in the neocortex. Cholinergic agonists and acetylcholinesterase inhibitors can enhance cognitive functioning, as does intermittent electrical stimulation of the cortical source of acetylcholine, the nucleus basalis (NB) of Meynert. Here we show in two male monkeys how NB stimulation affects working memory and alters its neural code. NB stimulation increases dorsolateral prefrontal activity during the delay period of spatial working memory tasks and broadens selectivity for stimuli but does not strengthen phasic responses to each neuron's optimal visual stimulus. Paradoxically, despite this decrease in neuronal selectivity, performance improves in many task conditions, likely indicating increased delay period stability. Performance under NB stimulation does decline if distractors similar to the target are presented, consistent with reduced prefrontal selectivity. Our results indicate that stimulation of the cholinergic forebrain increases prefrontal neural activity, and this neuromodulatory tone can improve cognitive performance, subject to a stability-accuracy tradeoff.

Elimination of SARS-CoV-2 along wastewater and sludge treatment processes.

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is shed in the feces of infected people. As a consequence, genomic RNA of the virus can be detected in wastewater. Although the presence of viral RNA does not inform on the infectivity of the virus, this presence of genetic material raised the question of the effectiveness of treatment processes in reducing the virus in wastewater and sludge. In this work, treatment lines of 16 wastewater treatment plants were monitored to evaluate the removal of SARS-CoV-2 RNA in raw, processed waters and sludge, from March to May 2020. Viral RNA copies were enumerated using reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) in 5 different laboratories. These laboratories participated in proficiency testing scheme and their results demonstrated the reliability and comparability of the results obtained for each one. SARS-CoV-2 RNA was found in 50.5% of the 101 influent wastewater samples characterized. Positive results were detected more frequently in those regions with a COVID-19 incidence higher than 100 cases per 100,000 inhabitants. Wastewater treatment plants (WWTPs) significantly reduced the occurrence of virus RNA along the water treatment lines. Secondary treatment effluents showed an occurrence of SARS-CoV-2 RNA in 23.3% of the samples and no positive results were found after MBR and chlorination. Non-treated sludge (from primary and secondary treatments) presented a higher occurrence of SARS-CoV-2 RNA than the corresponding water samples, demonstrating the affinity of virus particles for solids. Furthermore, SARS-CoV-2 RNA was detected in treated sludge after thickening and anaerobic digestion, whereas viral RNA was completely eliminated from sludge only when thermal hydrolysis was applied. Finally, co-analysis of SARS-CoV-2 and F-specific RNA bacteriophages was done in the same water and sludge samples in order to investigate the potential use of these bacteriophages as indicators of SARS-CoV-2 fate and reduction along the wastewater treatment.

StimuliApp: Psychophysical tests on mobile devices.

Psychophysical tests are commonly carried out using software applications running on desktop or laptop computers, but running the software on mobile handheld devices such as smartphones or tablets could have advantages in some situations. Here, we present StimuliApp, an open-source application in which the user can create psychophysical tests on the iPad and the iPhone by means of a system of menus. A wide number of templates for creating stimuli are available including patches, gradients, gratings, checkerboards, random-dots, texts, tones or auditory noise. Images, videos and audios stored in files could also be presented. The application was developed natively for iPadOS and iOS using the low-level interface Metal for accessing the graphics processing unit, which results in high timing performance.

Combining an effect-based methodology with chemical analysis for antibiotics determination in wastewater and receiving freshwater and marine environment.

Two different methodologies were combined to evaluate the risks that antibiotics can pose in the environment; i) an effect-based methodology based on microbial growth inhibition and ii) an analytical method based on liquid-chromatography coupled to mass spectrometry (LC-MS). The first approach was adapted and validated for the screening of four antibiotic families, specifically macrolides/ß-lactams, quinolones, sulfonamides and tetracyclines. The LC-MS method was applied for the identification and quantification of target antibiotics; then, the obtained results were combined with ecotoxicological data from literature to determine the environmental risk. The two methodologies were used for the analysis of antibiotics in water samples (wastewater, river water and seawater) and biofluids (fish plasma and mollusk hemolymph) in two monitoring campaigns undertaken in the Ebro Delta and Mar Menor Lagoon (both in the Mediterranean coast of Spain). Both approaches highlighted macrolides (azithromycin) and quinolones (ciprofloxacin and ofloxacin) as the main antibiotics in wastewater treatment plant (WWTP) effluents with potential risk for the environment. However, no risk for the aquatic life was identified in the river, lagoon and seawater as antibiotic levels were much lower than those in WWTP effluents. Fish from Ebro River were the organisms presenting the highest antibiotic concentration when compared with bivalves (mussels) from the Mediterranean Sea and gastropods (marine snails) from the Mar Menor Lagoon. The effect-based methodology successfully determined antibiotic risk in wastewater, but its applicability was less clear in environmental waters such as seawater, due to its high detection limits. Improving sample preconcentration could increase the method sensibility. Overall, combination of both methodologies provides comprehensive insights in antibiotic occurrence and risk associated in areas under study.

Reduced serial dependence suggests deficits in synaptic potentiation in anti-NMDAR encephalitis and schizophrenia.

A mechanistic understanding of core cognitive processes, such as working memory, is crucial to addressing psychiatric symptoms in brain disorders. We propose a combined psychophysical and biophysical account of two symptomatologically related diseases, both linked to hypofunctional NMDARs: schizophrenia and autoimmune anti-NMDAR encephalitis. We first quantified shared working memory alterations in a delayed-response task. In both patient groups, we report a markedly reduced influence of previous stimuli on working memory contents, despite preserved memory precision. We then simulated this finding with NMDAR-dependent synaptic alterations in a microcircuit model of prefrontal cortex. Changes in cortical excitation destabilized within-trial memory maintenance and could not account for disrupted serial dependence in working memory. Rather, a quantitative fit between data and simulations supports alterations of an NMDAR-dependent memory mechanism operating on longer timescales, such as short-term potentiation.

Build-up of serial dependence in color working memory.

Serial dependence, how immediately preceding experiences bias our current estimations, has been described experimentally during delayed-estimation of many different visual features, with subjects tending to make estimates biased towards previous ones. It has been proposed that these attractive biases help perception stabilization in the face of correlated natural scene statistics, although this remains mostly theoretical. Color, which is strongly correlated in natural scenes, has never been studied with regard to its serial dependencies. Here, we found significant serial dependence in 7 out of 8 datasets with behavioral data of humans (total n = 760) performing delayed-estimation of color with uncorrelated sequential stimuli. Moreover, serial dependence strength built up through the experimental session, suggesting metaplastic mechanisms operating at a slower time scale than previously proposed (e.g. short-term synaptic facilitation). Because, in contrast with natural scenes, stimuli were temporally uncorrelated, this build-up casts doubt on serial dependencies being an ongoing adaptation to the stable statistics of the environment.

Interplay between persistent activity and activity-silent dynamics in the prefrontal cortex underlies serial biases in working memory.

Persistent neuronal spiking has long been considered the mechanism underlying working memory, but recent proposals argue for alternative 'activity-silent' substrates. Using monkey and human electrophysiology data, we show here that attractor dynamics that control neural spiking during mnemonic periods interact with activity-silent mechanisms in the prefrontal cortex (PFC). This interaction allows memory reactivations, which enhance serial biases in spatial working memory. Stimulus information was not decodable between trials, but remained present in activity-silent traces inferred from spiking synchrony in the PFC. Just before the new stimulus, this latent trace was reignited into activity that recapitulated the previous stimulus representation. Importantly, the reactivation strength correlated with the strength of serial biases in both monkeys and humans, as predicted by a computational model that integrates activity-based and activity-silent mechanisms. Finally, single-pulse transcranial magnetic stimulation applied to the human PFC between successive trials enhanced serial biases, thus demonstrating the causal role of prefrontal reactivations in determining working-memory behavior.

Effect-Based Identification of Hazardous Antibiotic Transformation Products after Water Chlorination.

Antibiotic transformation products (TPs) generated during water treatment can be considered as an environmental concern, since they can retain part of the bioactivity of the parent compound. Effect-directed analysis (EDA) was applied for the identification of bioactive intermediates of azithromycin (AZI) and ciprofloxacin (CFC) after water chlorination. Fractionation of samples allowed the identification of bioactive intermediates by measuring the antibiotic activity and acute toxicity, combined with an automated suspect screening approach for chemical analysis. While the removal of AZI was in line with the decrease of bioactivity in chlorinated samples, an increase of bioactivity after complete removal of CFC was observed (at >0.5 mgCl2/L). Principal component analysis (PCA) revealed that some of the CFC intermediates could contribute to the overall toxicity of the chlorinated samples. Fractionation of bioactive samples identified that the chlorinated TP296 (generated from the destruction of the CFC piperazine ring) maintained 41%, 44%, and 30% of the antibiotic activity of the parent compound in chlorinated samples at 2.0, 3.0, and 4.0 mgCl2/L, respectively. These results indicate the spectrum of antibacterial activity can be altered by controlling the chemical substituents and configuration of the CFC structure with chlorine. On the other hand, the potential presence of volatile DBPs and fractionation losses do not allow for tentative confirmation of the main intermediates contributing to the acute toxic effects measured in chlorinated samples. Our results encourage further development of new and advanced methodologies to study the bioactivity of isolated unknown TPs to understand their hazardous effects in treated effluents.