Does the information in the phase of low frequency LFP reflect the low frequency envelope of local spike rates?

Recently, it has been shown that when the timing of spikes is measured relative to the phase of the cortical local field potentials (LFP), spikes can carry substantial more information about an external stimulus [1]. Experimental studies in sensory cortices of macaque have shown that the extra information obtained with such phase-of-firing codes above that in the firing rate alone ranges from 55 in primary visual cortex [1] to more than 100 in primary auditory cortex [2]. Here, we use a mathematical model that relates local spike trains and the resulting LFP, to explain the emergence of the phase-of-firing codes in cortex. The model is based on the one proposed in [3] and incorporates two types of integration over the spiking activity: i) a time convolution that results from the filtering properties of neural structures [4], which embeds history effects in LFP from past spiking activity, and ii) an integration step over the activity of neurons in the neighbourhood of the measuring electrode. When the spikes recorded from macaque primary visual cortex were used to synthesize the LFP, the model could reproduce the phase-of-firing information found using the real LFP, as shown in Figure 1. This suggests that an important component of phase-of-firing information originates from the surrounding neural population and past spiking activity. The next question that arises is what is the relative contribution of the neuron population size and the length of the firing rate history embedded in the LFP. We are currently investigating this question by parametrically varying both the population size and time integration ranges in generating the synthetic LFP

Tagging Scientific Publications using Wikipedia and Natural Language Processing Tools. Comparison on the ArXiv Dataset

In this work, we compare two simple methods of tagging scientific publications with labels reflecting their content. As a first source of labels Wikipedia is employed, second label set is constructed from the noun phrases occurring in the analyzed corpus. We examine the statistical properties and the effectiveness of both approaches on the dataset consisting of abstracts from 0.7 million of scientific documents deposited in the ArXiv preprint collection. We believe that obtained tags can be later on applied as useful document features in various machine learning tasks (document similarity, clustering, topic modelling, etc.)

Applications of Information Theory to Analysis of Neural Data

Information theory is a practical and theoretical framework developed for the study of communication over noisy channels. Its probabilistic basis and capacity to relate statistical structure to function make it ideally suited for studying information flow in the nervous system. It has a number of useful properties: it is a general measure sensitive to any relationship, not only linear effects; it has meaningful units which in many cases allow direct comparison between different experiments; and it can be used to study how much information can be gained by observing neural responses in single trials, rather than in averages over multiple trials. A variety of information theoretic quantities are commonly used in neuroscience - (see entry "Definitions of Information-Theoretic Quantities"). In this entry we review some applications of information theory in neuroscience to study encoding of information in both single neurons and neuronal populations.Comment: 8 pages, 2 figure

A modified Trastuzumab antibody for the immunohistochemical detection of HER-2 overexpression in breast cancer

The immunohistochemical determination of HER-2 to identify patients with advanced breast cancer candidates for Trastuzumab treatment proved neither accurate nor fully reliable, possibly because none of the current reagents detects the specific antigenic site target of Trastuzumab. To circumvent this problem, we conjugated the NH2 groups of Trastuzumab with biotin, and the compound obtained, designated BiotHER, was added directly to tissue sections. Biotin-labelling was revealed with horseradish peroxidase-conjugated streptavidin. Specificity and sensitivity of BiotHER immunostaining with respect to HER-2 amplification were tested on 164 breast carcinoma samples. BiotHER staining was detected on the tumour cell membrane of 12% of all specimens and in 49% specimens with gene amplification, while absent in nonamplified tumours. Predictivity of BiotHER status with respect to the clinical outcome was analysed in 54 patients with HER-2 amplified advanced breast cancer treated with Trastuzumab plus chemotherapy. BiotHER staining, detected in 50% of tumours with HER-2 amplification, was an independent predictor of clinical outcome. In fact, BiotHER positivity was independently associated with increased likelihood of tumour response and reduced risk of tumour progression and death. Biotinylated Trastuzumab can thus be used for immunohistochemical detection of HER-2 overexpression in breast cancer, and has the potential to identify patients likely to benefit from Trastuzumab treatment

Local field potential phase and spike timing convey information about different visual features in primary visual cortex

The natural visual environment is characterized by both “what/where” aspects (image features such as contrast or orientation which are defined by the relationship between visual signals simultaneously presented at different points in space) and “when” aspects, describing the temporal variations of the image features. Both “when” and “what/where” information is necessary to describe and understand the natural visual environment, and to take appropriate behavioral decisions. While “where” can be considered embedded as retinotopy, it is likely that localized neural populations in the visual cortex keep a simultaneous representation of both “what” and “when” aspects of the visual stimuli. However, little is yet known about how the spike trains of neurons in primary visual cortex encode both sources of information. The traditional hypothesis in systems neuroscience is that sensory variables are represented by a rate code, i.e. all sensory information is encoded by the number of spikes emitted over relatively long time windows. Although the relevance of rate in encoding static features is well established, this code can be inherently ambiguous in changing environments [1] and it is unlikely that this code is rich enough to represent simultaneously different types of information. Therefore here we explore the hypothesis that the timing of spikes is a crucial variable in representing both “what” and “when” aspects of the natural visual environment. To address these issues, we recorded single unit activity and LFPs in primary visual cortex of opiate anaesthetized macaques during the binocular presentation of naturalistic color movies. By means of computational analysis, we extracted several image features (color, orientation, luminance, space and time contrast, motion) from the receptive fields of each single neuron. We then considered two different spike timing codes previously studied in both the auditory [2] and the visual cortex [3]. In the first code, which we call spike patterns code, sequences of spike times from single neurons are measured (with a resolution of the order of 10 ms) with respect to the time course of the external stimulus. In the second code, which we call phase of firing code, spikes are measured with respect to the phase of the concurrent low frequency LFPs recorded from the same electrode as the spikes. We then used these data to investigate systematically which types of neural codes carry information about the static features of the image and which neural codes carry information about the time course of these features. We found that both “when” and “what” aspects are encoded simultaneously by spike times of visual cortical neurons. However, “what” and “when” are encoded by two different neural information streams; “what” aspects are encoded (on a fine scale of few ms) by spike patterns, and “when” stimulus aspects are encoded by the phase of firing (on a coarse scale of hundreds of ms)

Strategy for investments from Zipf law(s)

We have applied the Zipf method to extract the $\zeta'$ exponent for seven financial indices (DAX, FTSE; DJIA, NASDAQ, S&P500; Hang-Seng and Nikkei 225), after having translated the signals into a text based on two letters. We follow considerations based on the signal Hurst exponent and the notion of a time dependent Zipf law and exponent in order to implement two simple investment strategies for such indices. We show the time dependence of the returns.Comment: submitted to Physica A;Proceedings ICE02, Bali, Aug.28-31, 200

Statistical Laws Governing Fluctuations in Word Use from Word Birth to Word Death

We analyze the dynamic properties of 10^7 words recorded in English, Spanish and Hebrew over the period 1800--2008 in order to gain insight into the coevolution of language and culture. We report language independent patterns useful as benchmarks for theoretical models of language evolution. A significantly decreasing (increasing) trend in the birth (death) rate of words indicates a recent shift in the selection laws governing word use. For new words, we observe a peak in the growth-rate fluctuations around 40 years after introduction, consistent with the typical entry time into standard dictionaries and the human generational timescale. Pronounced changes in the dynamics of language during periods of war shows that word correlations, occurring across time and between words, are largely influenced by coevolutionary social, technological, and political factors. We quantify cultural memory by analyzing the long-term correlations in the use of individual words using detrended fluctuation analysis.Comment: Version 1: 31 pages, 17 figures, 3 tables. Version 2 is streamlined, eliminates substantial material and incorporates referee comments: 19 pages, 14 figures, 3 table

Keywords and Co-Occurrence Patterns in the Voynich Manuscript: An Information-Theoretic Analysis

The Voynich manuscript has remained so far as a mystery for linguists and cryptologists. While the text written on medieval parchment -using an unknown script system- shows basic statistical patterns that bear resemblance to those from real languages, there are features that suggested to some researches that the manuscript was a forgery intended as a hoax. Here we analyse the long-range structure of the manuscript using methods from information theory. We show that the Voynich manuscript presents a complex organization in the distribution of words that is compatible with those found in real language sequences. We are also able to extract some of the most significant semantic word-networks in the text. These results together with some previously known statistical features of the Voynich manuscript, give support to the presence of a genuine message inside the book

Coherent oscillations in word-use data from 1700 to 2008

In written language, the choice of specific words is constrained by both grammatical requirements and the specific semantic context of the message to be transmitted. To a significant degree, the semantic context is in turn affected by a broad cultural and historical environment, which also influences matters of style and manners. Over time, those environmental factors leave an imprint in the statistics of language use, with some words becoming more common and other words being preferred less. Here we characterize the patterns of language use over time based on word statistics extracted from more than 4.5 million books written over a period of 308 years. We find evidence of novel systematic oscillatory patterns in word use with a consistent period narrowly distributed around 14 years. The specific phase relationships between different words show structure at two independent levels: first, there is a weak global phase modulation that is primarily linked to overall shifts in the vocabulary across time; and second, a stronger component dependent on well defined semantic relationships between words. In particular, complex network analysis reveals that semantically related words show strong phase coherence. Ultimately, these previously unknown patterns in the statistics of language may be a consequence of changes in the cultural framework that influences the thematic focus of writers