Interdigitated Columnar Representation of Personal Space and Visual Space in Human Parietal Cortex.

Personal space (PS) is the space around the body that people prefer to maintain between themselves and unfamiliar others. Intrusion into personal space evokes discomfort and an urge to move away. Physiologic studies in nonhuman primates suggest that defensive responses to intruding stimuli involve the parietal cortex.

Personal space increases during the COVID-19 pandemic in response to real and virtual humans.

Personal space is the distance that people tend to maintain from others during daily life in a largely unconscious manner. For humans, personal space-related behaviors represent one form of non-verbal social communication, similar to facial expressions and eye contact. Given that the changes in social behavior and experiences that occurred during the COVID-19 pandemic, including "social distancing" and widespread social isolation, may have altered personal space preferences, we investigated this possibility in two independent samples.

Psychological and physiological evidence for an initial 'Rough Sketch' calculation of personal space.

Personal space has been defined as "the area individuals maintain around themselves into which others cannot intrude without arousing discomfort". However, the precise relationship between discomfort (or arousal) responses as a function of distance from an observer remains incompletely understood. Also the mechanisms involved in recognizing conspecifics and distinguishing them from other objects within personal space have not been identified.

Management of Neuropsychiatric Symptoms in Neurocognitive Disorders.

Dementias, renamed neurocognitive disorders (NCDs) in the , are defined by acquired decline in cognitive and functional abilities. now also includes mild NCD, which incorporates the previous diagnosis of mild cognitive impairment. recognizes the following etiologies for NCDs: NCD due to Alzheimer's disease, vascular NCD, NCD with Lewy bodies, frontotemporal NCD, substance-/medication-induced NCD, NCD due to traumatic brain injury, NCD due to Huntington's disease, NCD due to HIV infection, NCD due to prion disease, and NCD due to other medical conditions.

Stability and Competition in Multi-spike Models of Spike-Timing Dependent Plasticity.

Spike-timing dependent plasticity (STDP) is a widespread plasticity mechanism in the nervous system. The simplest description of STDP only takes into account pairs of pre- and postsynaptic spikes, with potentiation of the synapse when a presynaptic spike precedes a postsynaptic spike and depression otherwise. In light of experiments that explored a variety of spike patterns, the pair-based STDP model has been augmented to account for multiple pre- and postsynaptic spike interactions.

A neural circuit mechanism for regulating vocal variability during song learning in zebra finches.

Motor skill learning is characterized by improved performance and reduced motor variability. The neural mechanisms that couple skill level and variability, however, are not known. The zebra finch, a songbird, presents a unique opportunity to address this question because production of learned song and induction of vocal variability are instantiated in distinct circuits that converge on a motor cortex analogue controlling vocal output.

Sparseness and expansion in sensory representations.

In several sensory pathways, input stimuli project to sparsely active downstream populations that have more neurons than incoming axons. Here, we address the computational benefits of expansion and sparseness for clustered inputs, where different clusters represent behaviorally distinct stimuli and intracluster variability represents sensory or neuronal noise. Through analytical calculations and numerical simulations, we show that expansion implemented by feed-forward random synaptic weights amplifies variability in the incoming stimuli, and this noise enhancement increases with sparseness of the expanded representation.

Pairwise analysis can account for network structures arising from spike-timing dependent plasticity.

Spike timing-dependent plasticity (STDP) modifies synaptic strengths based on timing information available locally at each synapse. Despite this, it induces global structures within a recurrently connected network. We study such structures both through simulations and by analyzing the effects of STDP on pair-wise interactions of neurons.

Intrinsic stability of temporally shifted spike-timing dependent plasticity.

Spike-timing dependent plasticity (STDP), a widespread synaptic modification mechanism, is sensitive to correlations between presynaptic spike trains and it generates competition among synapses. However, STDP has an inherent instability because strong synapses are more likely to be strengthened than weak ones, causing them to grow in strength until some biophysical limit is reached. Through simulations and analytic calculations, we show that a small temporal shift in the STDP window that causes synchronous, or nearly synchronous, pre- and postsynaptic action potentials to induce long-term depression can stabilize synaptic strengths.

A generalized linear model of the impact of direct and indirect inputs to the lateral geniculate nucleus.

Relay neurons in the lateral geniculate nucleus (LGN) receive direct visual input predominantly from a single retinal ganglion cell (RGC), in addition to indirect input from other sources including interneurons, thalamic reticular nucleus (TRN), and the visual cortex. To address the extent of influence of these indirect sources on the response properties of the LGN neurons, we fit a Generalized Linear Model (GLM) to the spike responses of cat LGN neurons driven by spatially homogeneous spots that were rapidly modulated by a pseudorandom luminance sequence. Several spot sizes were used to probe the spatial extent of the indirect visual effects.

Fast nonnegative deconvolution for spike train inference from population calcium imaging.

Fluorescent calcium indicators are becoming increasingly popular as a means for observing the spiking activity of large neuronal populations. Unfortunately, extracting the spike train of each neuron from a raw fluorescence movie is a nontrivial problem. This work presents a fast nonnegative deconvolution filter to infer the approximately most likely spike train of each neuron, given the fluorescence observations.

Bursting as an effective relay mode in a minimal thalamic model.

In recent years, accumulating evidence indicates that thalamic bursts are present during wakefulness and participate in information transmission as an effective relay mode with distinctive properties from the tonic activity. Thalamic bursts originate from activation of the low threshold calcium cannels via a local feedback inhibition, exerted by the thalamic reticular neurons upon the relay neurons. This article, examines if this simple mechanism is sufficient to explain the distinctive properties of thalamic bursting as an effective relay mode.

Brain complexity increases in mania.

An important challenge in measuring whole brain activation is to develop a measure that could distinguish between normal and abnormal mood states. The application of chaos theory and non-linear dynamics to problems in biological sciences has resulted in a growing body of advancements and the notion of brain as a complex, non-linear system has attracted physicists, mathematicians, biologists and psychologists alike. To search for a correlation between alterations in chaotic brain states and mood disorders, we compared the fractal dimension of the electroencephalographic (EEG) signal in patients going through a manic episode of bipolar mood disorder (BMD) type I to a control group of healthy adults and showed that the EEG fractal dimension is significantly augmented in our patients.

Munker-White-like illusions without T-junctions.

Some interpretations of the Munker-White illusion were evaluated by designing new versions of this illusion devoid of T-junctions (Munker-White-like images). The magnitudes of both Munker-White and Munker-White-like illusions were then quantified by using a brightness-matching technique. The results showed the effect to persist in all proposed versions.

New attractor states for synchronous activity in synfire chains with excitatory and inhibitory coupling.

In a feedforward network of integrate-and-fire neurons, where the firing of each layer is synchronous (synfire chain), the final firing state of the network converges to two attractor states: either a full activation or complete fading of the tailing layers. In this article, we analyze various modes of pattern propagation in a synfire chain with random connection weights and delta-type postsynaptic currents. We predict analytically that when the input is fully synchronized and the network is noise free, varying the characteristics of the weights distribution would result in modes of behavior that are different from those described in the literature.