Perceptual Learning via Modification of Cortical Top-Down Signals

The primary visual cortex (V1) is pre-wired to facilitate the extraction of behaviorally important visual features. Collinear edge detectors in V1, for instance, mutually enhance each other to improve the perception of lines against a noisy background. The same pre-wiring that facilitates line extraction, however, is detrimental when subjects have to discriminate the brightness of different line segments. How is it possible to improve in one task by unsupervised practicing, without getting worse in the other task? The classical view of perceptual learning is that practicing modulates the feedforward input stream through synaptic modifications onto or within V1. However, any rewiring of V1 would deteriorate other perceptual abilities different from the trained one. We propose a general neuronal model showing that perceptual learning can modulate top-down input to V1 in a task-specific way while feedforward and lateral pathways remain intact. Consistent with biological data, the model explains how context-dependent brightness discrimination is improved by a top-down recruitment of recurrent inhibition and a top-down induced increase of the neuronal gain within V1. Both the top-down modulation of inhibition and of neuronal gain are suggested to be universal features of cortical microcircuits which enable perceptual learning.

Verbal instructions and top-down saccade control.

Few studies have addressed the interaction between instruction content and saccadic eye movement control. To assess the impact of instructions on top-down control, we instructed 20 healthy volunteers to deliberately delay saccade triggering, to make inaccurate saccades or to redirect saccades--i.e. to glimpse towards and then immediately opposite to the target. Regular pro- and antisaccade tasks were used for comparison. Bottom-up visual input remained unchanged and was a gap paradigm for all instructions. In the inaccuracy and delay tasks, both latencies and accuracies were detrimentally impaired by either type of instruction and the variability of latency and accuracy was increased. The intersaccadic interval (ISI) required to correct erroneous antisaccades was shorter than the ISI for instructed direction changes in the redirection task. The word-by-word instruction content interferes with top-down saccade control. Top-down control is a time consuming process, which may override bottom-up processing only during a limited time period. It is questionable whether parallel processing is possible in top-down control, since the long ISI for instructed direction changes suggests sequential planning.

Combining Bottom-up and Top-down Generation of Interactive Knowledge Maps for Enterprise Search

Our research project develops an intranet search engine with concept- browsing functionality, where the user is able to navigate the conceptual level in an interactive, automatically generated knowledge map. This knowledge map visualizes tacit, implicit knowledge, extracted from the intranet, as a network of semantic concepts. Inductive and deductive methods are combined; a text ana- lytics engine extracts knowledge structures from data inductively, and the en- terprise ontology provides a backbone structure to the process deductively. In addition to performing conventional keyword search, the user can browse the semantic network of concepts and associations to find documents and data rec- ords. Also, the user can expand and edit the knowledge network directly. As a vision, we propose a knowledge-management system that provides concept- browsing, based on a knowledge warehouse layer on top of a heterogeneous knowledge base with various systems interfaces. Such a concept browser will empower knowledge workers to interact with knowledge structures.

Impaired top-down modulation of saccadic latencies in patients with schizophrenia but not in first-degree relatives

Impaired eye movements have a long history in schizophrenia research and meet the criteria of a reliable biomarker. However, the effects of cognitive load and task difficulty on saccadic latencies (SL) are less understood. Recent studies showed that SL are strongly task dependent: SL are decreased in tasks with higher cognitive demand, and increased in tasks with lower cognitive demand. The present study investigates SL modulation in patients with schizophrenia and their first-degree relatives. A group of 13 patients suffering from ICD-10 schizophrenia, 10 first-degree relatives, and 24 control subjects performed two different types of visual tasks: a color task and a Landolt ring orientation task. We used video-based oculography to measure SL. We found that patients exhibited a similar unspecific SL pattern in the two different tasks, whereas controls and relatives exhibited 20–26% shorter average latencies in the orientation task (higher cognitive demand) compared to the color task (lower cognitive demand). Also, classification performance using support vector machines suggests that relatives should be assigned to the healthy controls and not to the patient group. Therefore, visual processing of different content does not modulate SL in patients with schizophrenia, but modulates SL in the relatives and healthy controls. The results reflect a specific oculomotor attentional dysfunction in patients with schizophrenia that is a potential state marker, possibly caused by impaired top-down disinhibition of the superior colliculus by frontal/prefrontal areas such as the frontal eye fields.

Top-Down Parsing with Parsing Contexts

The domain of context-free languages has been extensively explored and there exist numerous techniques for parsing (all or a subset of) context-free languages. Unfortunately, some programming languages are not context-free. Using standard context-free parsing techniques to parse a context-sensitive programming language poses a considerable challenge. Im- plementors of programming language parsers have adopted various techniques, such as hand-written parsers, special lex- ers, or post-processing of an ambiguous parser output to deal with that challenge. In this paper we suggest a simple extension of a top-down parser with contextual information. Contrary to the tradi- tional approach that uses only the input stream as an input to a parsing function, we use a parsing context that provides ac- cess to a stream and possibly to other context-sensitive infor- mation. At a same time we keep the context-free formalism so a grammar definition stays simple without mind-blowing context-sensitive rules. We show that our approach can be used for various purposes such as indent-sensitive parsing, a high-precision island parsing or XML (with arbitrary el- ement names) parsing. We demonstrate our solution with PetitParser, a parsing-expression grammar based, top-down, parser combinator framework written in Smalltalk.

A systems analysis identifies a feedforward inflammatory circuit leading to lethal influenza infection

For acutely lethal influenza infections, the relative pathogenic contributions of direct viral damage to lung epithelium versus dysregulated immunity remain unresolved. Here, we take a top-down systems approach to this question. Multigene transcriptional signatures from infected lungs suggested that elevated activation of inflammatory signaling networks distinguished lethal from sublethal infections. Flow cytometry and gene expression analysis involving isolated cell subpopulations from infected lungs showed that neutrophil influx largely accounted for the predictive transcriptional signature. Automated imaging analysis, together with these gene expression and flow data, identified a chemokine-driven feedforward circuit involving proinflammatory neutrophils potently driven by poorly contained lethal viruses. Consistent with these data, attenuation, but not ablation, of the neutrophil-driven response increased survival without changing viral spread. These findings establish the primacy of damaging innate inflammation in at least some forms of influenza-induced lethality and provide a roadmap for the systematic dissection of infection-associated pathology.

How involved are they really? A comparative network analysis of the institutional drivers of local actor inclusion

Different socio-economic and environmental drivers lead local communities in mountain regions to adapt land use practices and engage in protection policies. The political system also has to develop new approaches to adapt to those drivers. Local actors are the target group of those policy approaches, and the question arises of if and how much those actors are consulted or even integrated into the design of local land use and protection policies. This article addresses this question by comparing seven different case studies in Swiss mountain regions. Through a formal social network analysis, the inclusion of local actors in collaborative policy networks is investigated and compared to the involvement of other stakeholders representing the next higher sub-national or national decisional levels. Results show that there is a significant difference (1) in how local actors are embedded compared to other stakeholders; and (2) between top-down versus bottom-up designed policy processes.

15 Years of Microstate Research in Schizophrenia - Where Are We? A Meta-Analysis

Schizophrenia patients show abnormalities in a broad range of task demands. Therefore, an explanation common to all these abnormalities has to be sought independently of any particular task, ideally in the brain dynamics before a task takes place or during resting state. For the neurobiological investigation of such baseline states, EEG microstate analysis is particularly well suited, because it identifies subsecond global states of stable connectivity patterns directly related to the recruitment of different types of information processing modes (e.g., integration of top-down and bottom-up information). Meanwhile, there is an accumulation of evidence that particular microstate networks are selectively affected in schizophrenia. To obtain an overall estimate of the effect size of these microstate abnormalities, we present a systematic meta-analysis over all studies available to date relating EEG microstates to schizophrenia. Results showed medium size effects for two classes of microstates, namely, a class labeled C that was found to be more frequent in schizophrenia and a class labeled D that was found to be shortened. These abnormalities may correspond to core symptoms of schizophrenia, e.g., insufficient reality testing and self-monitoring as during auditory verbal hallucinations. As interventional studies have shown that these microstate features may be systematically affected using antipsychotic drugs or neurofeedback interventions, these findings may help introducing novel diagnostic and treatment options.