Miller (1956) summarized evidence that people can remember about seven chunks in short-term memory (STM) tasks. How- ever, that number was meant more as a rough estimate and a rhetorical device than as a real capacity limit. Others have since suggested that there is a more precise capacity limit, but that it is only three to five chunks. The present target article brings together a wide vari- ety of data on capacity limits suggesting that the smaller capacity limit is real. Capacity limits will be useful in analyses of information processing only if the boundary conditions for observing them can be carefully described. Four basic conditions in which chunks can be identified and capacity limits can accordingly be observed are: (1) when information overload limits chunks to individual stimulus items, (2) when other steps are taken specifically to block the recoding of stimulus items into larger chunks, (3) in performance discontinuities caused by the capacity limit, and (4) in various indirect effects of the capacity limit. Under these conditions, rehearsal and long-term memory cannot be used to combine stimulus items into chunks of an unknown size; nor can storage mechanisms that are not capacity- limited, such as sensory memory, allow the capacity-limited storage mechanism to be refilled during recall. A single, central capacity limit averaging about four chunks is implicated along with other, noncapacity-limited sources. The pure STM capacity limit expressed in chunks is distinguished from compound STM limits obtained when the number of separately held chunks is unclear. Reasons why pure capacity estimates fall within a narrow range are discussed and a capacity limit for the focus of attention is proposed.

/pdf/the-magical-number-4-in-short-term-memory-a-reconsideration-3704b9phuz.pdf

The magical number 4 in short-term memory: a reconsideration of mental storage capacity.

Noise — random disturbances of signals — poses a fundamental problem for information processing and affects all aspects of nervous-system function. However, the nature, amount and impact of noise in the nervous system have only recently been addressed in a quantitative manner. Experimental and computational methods have shown that multiple noise sources contribute to cellular and behavioural trial-to-trial variability. We review the sources of noise in the nervous system, from the molecular to the behavioural level, and show how noise contributes to trial-to-trial variability. We highlight how noise affects neuronal networks and the principles the nervous system applies to counter detrimental effects of noise, and briefly discuss noise's potential benefits.

/pdf/noise-in-the-nervous-system-22k10mncs2.pdf

Noise in the nervous system.

Synchronous rhythms represent a core mechanism for sculpting temporal coordination of neural activity in the brain-wide network. This review focuses on oscillations in the cerebral cortex that occur during cognition, in alert behaving conditions. Over the last two decades, experimental and modeling work has made great strides in elucidating the detailed cellular and circuit basis of these rhythms, particularly gamma and theta rhythms. The underlying physiological mechanisms are diverse (ranging from resonance and pacemaker properties of single cells to multiple scenarios for population synchronization and wave propagation), but also exhibit unifying principles. A major conceptual advance was the realization that synaptic inhibition plays a fundamental role in rhythmogenesis, either in an interneuronal network or in a reciprocal excitatory-inhibitory loop. Computational functions of synchronous oscillations in cognition are still a matter of debate among systems neuroscientists, in part because the notion of regular oscillation seems to contradict the common observation that spiking discharges of individual neurons in the cortex are highly stochastic and far from being clocklike. However, recent findings have led to a framework that goes beyond the conventional theory of coupled oscillators and reconciles the apparent dichotomy between irregular single neuron activity and field potential oscillations. From this perspective, a plethora of studies will be reviewed on the involvement of long-distance neuronal coherence in cognitive functions such as multisensory integration, working memory, and selective attention. Finally, implications of abnormal neural synchronization are discussed as they relate to mental disorders like schizophrenia and autism.

/pdf/neurophysiological-and-computational-principles-of-cortical-48xnk4ixsg.pdf

Neurophysiological and Computational Principles of Cortical Rhythms in Cognition

Noise in dynamical systems is usually considered a nuisance. But in certain nonlinear systems, including electronic circuits and biological sensory apparatus, the presence of noise can in fact enhance the detection of weak signals. This phenomenon, called stochastic resonance, may find useful application in physical, technological and biomedical contexts.

Stochastic resonance and the benefits of noise: from ice ages to crayfish and SQUIDs

http://people.physik.hu-berlin.de/~lindner/PDF/physreport.pdf

Effects of noise in excitable systems

OSCILLATING membrane potentials that generate rhythmic impulse patterns are considered to be of particular significance for neuronal information processing1–4. In contrast, noise is usually seen as a disturbance which limits the accuracy of information transfer5–8. We show here, however, that noise in combination with intrinsic oscillations can provide neurons with particular encoding properties, a discovery we made when recording from single electrosensory afferent of a fish. The temporal sequence of the impulse trains indicates oscillations that operate near the spike-triggering threshold. The oscillation frequency determines the basic rhythm of impulse generation, but whether or not an impulse is actually triggered essentially depends on superimposed noise. The probability of impulse generation can be altered considerably by minor modifications of oscillation baseline and amplitude, which may underlie the exquisite sensitivity of these receptors to thermal and electrical stimuli. Additionally, thermal, but not electrical, stimuli alter the oscillation frequency, allowing dual sensory messages to be conveyed in a single spike train. These findings demonstrate novel properties of sensory transduction which may be relevant for neuronal signalling in general.

Oscillation and noise determine signal transduction in shark multimodal sensory cells

The dynamics of neurons is characterized by a variety of different spiking patterns in response to external stimuli. One of the most important transitions in neuronal response patterns is the transition from tonic firing to burst discharges, i.e., when the neuronal activity changes from single spikes to the grouping of spikes. An increased number of interspike-interval sequences of specific temporal correlations was detected in anticipation of temperature induced tonic-to-bursting transitions in both, experimental impulse recordings from hypothalamic brain slices and numerical simulations of a stochastic model. Analysis of the modelling data elucidates that the appearance of such patterns can be related to particular system dynamics in the vicinity of the period-doubling bifurcation. It leads to a nonlinear response on de- and hyperpolarizing perturbations introduced by noise. This explains why such particular patterns can be found as reliable precursors of the neurons’ transition to burst discharges.

Noise-induced precursors of tonic-to-bursting transitions in hypothalamic neurons and in a conductance-based model.

Pandemic scenarios like SARS-Cov-2 require rapid information aggregation. In the age of eHealth and data-driven medicine, publicly available symptom tracking tools offer efficient and scalable means of collecting and analyzing large amounts of data. As a result, information gains can be communicated to front-line providers. We have developed such an application in less than a month and reached more than 500 thousand users within 48 hours. The dataset contains information on basic epidemiological parameters, symptoms, risk factors and details on previous exposure to a COVID-19 patient. Exploratory Data Analysis revealed different symptoms reported by users with confirmed contacts vs. no confirmed contacts. The symptom combination of anosmia, cough and fatigue was the most important feature to differentiate the groups, while single symptoms such as anosmia, cough or fatigue alone were not sufficient. A linear regression model from the literature using the same symptom combination as features was applied on all data. Predictions matched the regional distribution of confirmed cases closely across Germany, while also indicating that the number of cases in northern federal states might be higher than officially reported. In conclusion, we report that symptom combinations anosmia, fatigue and cough are most likely to indicate an acute SARS-CoV-2 infection.

Towards a COVID-19 symptom triad: The importance of symptom constellations in the SARS-CoV-2 pandemic.

/pdf/towards-a-covid-19-symptom-triad-the-importance-of-symptom-4uv4u8zqje.pdf

Martin Hirsch

Papers

Oscillation and noise determine signal transduction in shark multimodal sensory cells

Noise-induced precursors of tonic-to-bursting transitions in hypothalamic neurons and in a conductance-based model.

Towards a COVID-19 symptom triad: The importance of symptom constellations in the SARS-CoV-2 pandemic.

Towards a COVID-19 symptom triad: The importance of symptom constellations in the SARS-CoV-2 pandemic