Causes and consequences of representational drift.

The nervous system learns new associations while maintaining memories over long periods, exhibiting a balance between flexibility and stability. Recent experiments reveal that neuronal representations of learned sensorimotor tasks continually change over days and weeks, even after animals have achieved expert behavioral performance. How is learned information stored to allow consistent behavior despite ongoing changes in neuronal activity? What functions could ongoing reconfiguration serve? We highlight recent experimental evidence for such representational drift in sensorimotor systems, and discuss how this fits into a framework of distributed population codes. We identify recent theoretical work that suggests computational roles for drift and argue that the recurrent and distributed nature of sensorimotor representations permits drift while limiting disruptive effects. We propose that representational drift may create error signals between interconnected brain regions that can be used to keep neural codes consistent in the presence of continual change. These concepts suggest experimental and theoretical approaches to studying both learning and maintenance of distributed and adaptive population codes.This work is supported by the Human Frontier Science Program, ERC grant StG 716643 FLEXNEURO, and NIH grants (NS108410, NS089521, MH107620)

Optimal Encoding in Stochastic Latent-Variable Models.

In this work we explore encoding strategies learned by statistical models of sensory coding in noisy spiking networks. Early stages of sensory communication in neural systems can be viewed as encoding channels in the information-theoretic sense. However, neural populations face constraints not commonly considered in communications theory. Using restricted Boltzmann machines as a model of sensory encoding, we find that networks with sufficient capacity learn to balance precision and noise-robustness in order to adaptively communicate stimuli with varying information content. Mirroring variability suppression observed in sensory systems, informative stimuli are encoded with high precision, at the cost of more variable responses to frequent, hence less informative stimuli. Curiously, we also find that statistical criticality in the neural population code emerges at model sizes where the input statistics are well captured. These phenomena have well-defined thermodynamic interpretations, and we discuss their connection to prevailing theories of coding and statistical criticality in neural populations

The information theory of developmental pruning: Optimizing global network architectures using local synaptic rules.

Funder: Studienstiftung des Deutschen Volkes; funder-id: http://dx.doi.org/10.13039/501100004350Funder: Bundesministerium für Bildung und Forschung; funder-id: http://dx.doi.org/10.13039/501100002347Funder: Max-Planck-Gesellschaft; funder-id: http://dx.doi.org/10.13039/501100004189During development, biological neural networks produce more synapses and neurons than needed. Many of these synapses and neurons are later removed in a process known as neural pruning. Why networks should initially be over-populated, and the processes that determine which synapses and neurons are ultimately pruned, remains unclear. We study the mechanisms and significance of neural pruning in model neural networks. In a deep Boltzmann machine model of sensory encoding, we find that (1) synaptic pruning is necessary to learn efficient network architectures that retain computationally-relevant connections, (2) pruning by synaptic weight alone does not optimize network size and (3) pruning based on a locally-available measure of importance based on Fisher information allows the network to identify structurally important vs. unimportant connections and neurons. This locally-available measure of importance has a biological interpretation in terms of the correlations between presynaptic and postsynaptic neurons, and implies an efficient activity-driven pruning rule. Overall, we show how local activity-dependent synaptic pruning can solve the global problem of optimizing a network architecture. We relate these findings to biology as follows: (I) Synaptic over-production is necessary for activity-dependent connectivity optimization. (II) In networks that have more neurons than needed, cells compete for activity, and only the most important and selective neurons are retained. (III) Cells may also be pruned due to a loss of synapses on their axons. This occurs when the information they convey is not relevant to the target population

Stable task information from an unstable neural population

Over days and weeks, neural activity representing an animal’s position and movement in sensorimotor cortex has been found to continually reconfigure or ‘drift’ during repeated trials of learned tasks, with no obvious change in behavior. This challenges classical theories, which assume stable engrams underlie stable behavior. However, it is not known whether this drift occurs systematically, allowing downstream circuits to extract consistent information. Analyzing long-term calcium imaging recordings from posterior parietal cortex in mice (Mus musculus), we show that drift is systematically constrained far above chance, facilitating a linear weighted readout of behavioral variables. However, a significant component of drift continually degrades a fixed readout, implying that drift is not confined to a null coding space. We calculate the amount of plasticity required to compensate drift independently of any learning rule, and find that this is within physiologically achievable bounds. We demonstrate that a simple, biologically plausible local learning rule can achieve these bounds, accurately decoding behavior over many days

The association between benign prostatic hyperplasia and chronic kidney disease in community-dwelling men

The association between benign prostatic hyperplasia and chronic kidney disease in community-dwelling men.BackgroundBenign prostatic hyperplasia (BPH) and chronic kidney disease are important public health problems in older men. Previous referral-based studies disagree on whether BPH is associated with chronic kidney disease. The objective of this study was to determine the community-based association between clinical measures of BPH and chronic kidney disease.MethodsA community-based sample of 2115 white men (ages 40–79 years) was randomly selected from the Olmsted County, Minnesota population (55% participation rate) in 1990. A random subsample (N = 476) had a detailed clinical evaluation. This evaluation included a questionnaire with similar queries to the International Prostate Symptom Score (IPSS), peak urinary flow rates (uroflowmeter), postvoid residual urine volume (ultrasound), prostate volume (ultrasound), serum prostate specific antigen (PSA), and serum creatinine.ResultsAfter adjustment for age, hypertension, diabetes, leukocyte esterase positive (possible urinary tract infection), and smoking, chronic kidney disease [serum creatinine ≥133 μmol/L (1.5 mg/dL)] was associated with diminished peak urinary flow rate (<15 mL/sec) by an odds ratio (OR) = 2.96 (95% CI 1.30–7.01), moderate-severe lower urinary tract symptoms (IPSS >7) by an OR = 2.91 (95% CI 1.32–6.62), and chronic urinary retention (postvoid residual >100 mL) by an OR = 2.28 (95% CI 0.66–6.68). There was no association with a prostate volume >30 mL by an OR = 0.56 (95% CI 0.22–1.37) or PSA >1.4 ng/mL by an OR = 1.17 (95% CI 0.47–2.81).ConclusionThere was a cross-sectional association between signs and symptoms of bladder outlet obstruction and chronic kidney disease in community-dwelling men. Prostatic enlargement was not associated with chronic kidney disease

Dissociation between sustained single-neuron spiking β-rhythmicity and transient β-LFP oscillations in primate motor cortex

Determining the relationship between single-neuron spiking and transient (20 Hz) β-local field potential (β-LFP) oscillations is an important step for understanding the role of these oscillations in motor cortex. We show that whereas motor cortex firing rates and beta spiking rhythmicity remain sustained during steady-state movement preparation periods, β-LFP oscillations emerge, in contrast, as short transient events. Single-neuron mean firing rates within and outside transient β-LFP events showed no differences, and no consistent correlation was found between the beta oscillation amplitude and firing rates, as was the case for movement- and visual cue-related β-LFP suppression. Importantly, well-isolated single units featuring beta-rhythmic spiking (43%, 125/292) showed no apparent or only weak phase coupling with the transient β-LFP oscillations. Similar results were obtained for the population spiking. These findings were common in triple microelectrode array recordings from primary motor (M1), ventral (PMv), and dorsal premotor (PMd) cortices in nonhuman primates during movement preparation. Although beta spiking rhythmicity indicates strong membrane potential fluctuations in the beta band, it does not imply strong phase coupling with β-LFP oscillations. The observed dissociation points to two different sources of variation in motor cortex β-LFPs: one that impacts single-neuron spiking dynamics and another related to the generation of mesoscopic β-LFP signals. Furthermore, our findings indicate that rhythmic spiking and diverse neuronal firing rates, which encode planned actions during movement preparation, may naturally limit the ability of different neuronal populations to strongly phase-couple to a single dominant oscillation frequency, leading to the observed spiking and β-LFP dissociation. NEW & NOTEWORTHY We show that whereas motor cortex spiking rates and beta (~20 Hz) spiking rhythmicity remain sustained during steady-state movement preparation periods, β-local field potential (β-LFP) oscillations emerge, in contrast, as transient events. Furthermore, the β-LFP phase at which neurons spike drifts: phase coupling is typically weak or absent. This dissociation points to two sources of variation in the level of motor cortex beta: one that impacts single-neuron spiking and another related to the generation of measured mesoscopic β-LFPs

Association of kidney function with inflammatory and procoagulant markers in a diverse cohort: A cross-sectional analysis from the Multi-Ethnic Study of Atherosclerosis (MESA)

Background: Prior studies using creatinine-based estimated glomerular filtration rate (eGFR) have found limited associations between kidney function and markers of inflammation. Using eGFR and cystatin C, a novel marker of kidney function, the authors investigated the association of kidney function with multiple biomarkers in a diverse cohort. Methods: The Multi-Ethnic Study of Atherosclerosis consists of 6,814 participants of white, African-American, Hispanic, and Chinese descent, enrolled from 2000-2002 from six U.S. communities. Measurements at the enrollment visit included serum creatinine, cystatin C, and six inflammatory and procoagulant biomarkers. Creatinine-based eGFR was estimated using the fourvariable Modification of Diet in Renal Disease equation, and chronic kidney disease was defined by an eGFR less than 60 mL/min/1.73 m2. Results: Adjusted partial correlations between cystatin C and all biomarkers were statistically significant: C-reactive protein (r = 0.08), interleukin-6 (r = 0.16), tumor necrosis factor-a soluble receptor 1 (TNF-aR1; r = 0.75), intercellular adhesion molecule-1 (r = 0.21), fibrinogen (r = 0.14), and factor VIII (r = 0.11; two-sided p less than 0.01 for all). In participants without chronic kidney disease, higher creatinine-based eGFR was associated only with higher TNF-aR1 levels. Conclusion: In a cohort characterized by ethnic diversity, cystatin C was directly associated with multiple procoagulant and inflammatory markers. Creatinine-based eGFR had similar associations with these biomarkers among subjects with chronic kidney disease.This research was supported by contracts N01-HC-95159 through N01-HC-95169 from the National Heart, Lung, and Blood Institute (NHLBI)

Dropout in a longitudinal, cohort study of urologic disease in community men

BACKGROUND: Reasons for attrition in studies vary, but may be a major concern in long-term studies if those who drop out differ systematically from those who continue to participate. Factors associated with dropout were evaluated in a twelve-year community-based, prospective cohort study of urologic disease in men. METHODS: During 1989–1991, 2,115 randomly selected Caucasian men, ages 40–79 years from Olmsted County, Minnesota were enrolled and followed with questionnaires biennially; 332 men were added in follow-up. A random subset (~25%) received a urologic examination. Baseline characteristics including age, benign prostatic hyperplasia (BPH) symptoms, comorbidities, and socioeconomic factors were compared between subjects who did and did not participate after the twelfth year of follow-up. RESULTS: Of the 2,447 men, 195 died and were excluded; 682 did not participate in 2002. Compared with men in the 40–49 year age group, men ≥ 70 years of age at baseline had a greater relative odds of dropout, 2.65 (95% CI: 1.93, 3.63). In age-adjusted analyses, relative to men without stroke, men who had suffered a stroke had a higher odds of dropout, age-adjusted OR 3.07 (95% CI: 1.49, 6.33). Presence of at least one BPH symptom was not associated with dropout, (age-adjusted OR 1.12 (95% CI: 0.93, 1.36)). CONCLUSION: These results provide assurance that dropout was not related to primary study outcomes. However, factors associated with dropout should be taken into account in analyses where they may be potential confounders

Right-Wing Politicians Prefer the Emotional Left

Physiological research suggests that social attitudes, such as political beliefs, may be partly hard-wired in the brain. Conservatives have heightened sensitivity for detecting emotional faces and use emotion more effectively when campaigning. As the left face displays emotion more prominently, we examined 1538 official photographs of conservative and liberal politicians from Australia, Canada, the United Kingdom and the United States for an asymmetry in posing. Across nations, conservatives were more likely than liberals to display the left cheek. In contrast, liberals were more likely to face forward than were conservatives. Emotion is important in political campaigning and as portraits influence voting decisions, conservative politicians may intuitively display the left face to convey emotion to voters