Task interference as a neuronal basis for the cost of cognitive flexibility

Humans and animals have an impressive ability to juggle multiple tasks in a constantly changing environment. This flexibility, however, leads to decreased performance under uncertain task conditions. Here, we combined monkey electrophysiology, human psychophysics, and artificial neural network modeling to investigate the neuronal mechanisms of this performance cost. We developed a behavioural paradigm to measure and influence participants' decision-making and perception in two distinct perceptual tasks. Our data revealed that both humans and monkeys, unlike an artificial neural network trained for the same tasks, make less accurate perceptual decisions when the task is uncertain. We generated a mechanistic hypothesis by comparing this neural network trained to produce correct choices with another network trained to replicate the participants' choices. We hypothesized, and confirmed with further behavioural, physiological, and causal experiments, that the cost of task flexibility comes from what we term task interference. Under uncertain conditions, interference between different tasks causes errors because it results in a stronger representation of irrelevant task features and entangled neuronal representations of different features. Our results suggest a tantalizing, general hypothesis: that cognitive capacity limitations, both in health and disease, stem from interference between neural representations of different stimuli, tasks, or memories.

Orthogonal neural representations support perceptual judgements of natural stimuli

In natural behavior, observers must separate relevant information from a barrage of irrelevant information. Many studies have investigated the neural underpinnings of this ability using artificial stimuli presented on simple backgrounds. Natural viewing, however, carries a set of challenges that are inaccessible using artificial stimuli, including neural responses to background objects that are task-irrelevant. An emerging body of evidence suggests that the visual abilities of humans and animals can be modeled through the linear decoding of task-relevant information from visual cortex. This idea suggests the hypothesis that irrelevant features of a natural scene should impair performance on a visual task only if their neural representations intrude on the linear readout of the task relevant feature, as would occur if the representations of task-relevant and irrelevant features are not orthogonal in the underlying neural population. We tested this hypothesis using human psychophysics and monkey neurophysiology, in response to parametrically variable naturalistic stimuli. We demonstrate that 1) the neural representation of one feature (the position of a central object) in visual area V4 is orthogonal to those of several background features, 2) the ability of human observers to precisely judge object position was largely unaffected by task-irrelevant variation in those background features, and 3) many features of the object and the background are orthogonally represented by V4 neural responses. Our observations are consistent with the hypothesis that orthogonal neural representations support stable perception of objects and features despite the tremendous richness of natural visual scenes.

Targeted V1 comodulation supports task-adaptive sensory decisions

Sensory-guided behavior requires reliable encoding of stimulus information in neural populations, and flexible, task-specific readout. The former has been studied extensively, but the latter remains poorly understood. We introduce a theory for adaptive sensory processing based on functionally-targeted stochastic modulation. We show that responses of neurons in area V1 of monkeys performing a visual discrimination task exhibit low-dimensional, rapidly fluctuating gain modulation, which is stronger in task-informative neurons and can be used to decode from neural activity after few training trials, consistent with observed behavior. In a simulated hierarchical neural network model, such labels are learned quickly and can be used to adapt downstream readout, even after several intervening processing stages. Consistently, we find the modulatory signal estimated in V1 is also present in the activity of simultaneously recorded MT units, and is again strongest in task-informative neurons. These results support the idea that co-modulation facilitates task-adaptive hierarchical information routing.

Topological insights into the neural basis of flexible behavior

It is widely accepted that there is an inextricable link between neural computations, biological mechanisms, and behavior, but it is challenging to simultaneously relate all three. Here, we show that topological data analysis (TDA) provides an important bridge between these approaches to studying how brains mediate behavior. We demonstrate that cognitive processes change the topological description of the shared activity of populations of visual neurons. These topological changes constrain and distinguish between competing mechanistic models, are connected to subjects' performance on a visual change detection task, and, via a link with network control theory, reveal a tradeoff between improving sensitivity to subtle visual stimulus changes and increasing the chance that the subject will stray off task. These connections provide a blueprint for using TDA to uncover the biological and computational mechanisms by which cognition affects behavior in health and disease.

Contributions of early and mid-level visual cortex to high-level object categorization

The complexity of visual features for which neurons are tuned increases from early to late stages of the ventral visual stream. Thus, the standard hypothesis is that high-level functions like object categorization are primarily mediated by higher visual areas because they require more complex image formats that are not evident in early visual processing stages. However, human observers can categorize images as objects or animals or as big or small even when the images preserve only some low- and mid-level features but are rendered unidentifiable ('texforms', Long et al., 2018). This observation suggests that even the early visual cortex, in which neurons respond to simple stimulus features, may already encode signals about these more abstract high-level categorical distinctions. We tested this hypothesis by recording from populations of neurons in early and mid-level visual cortical areas while rhesus monkeys viewed texforms and their unaltered source stimuli (simultaneous recordings from areas V1 and V4 in one animal and separate recordings from V1 and V4 in two others). Using recordings from a few dozen neurons, we could decode the real-world size and animacy of both unaltered images and texforms. Furthermore, this neural decoding accuracy across stimuli was related to the ability of human observers to categorize texforms by real-world size and animacy. Our results demonstrate that neuronal populations early in the visual hierarchy contain signals useful for higher-level object perception and suggest that the responses of early visual areas to simple stimulus features display preliminary untangling of higher-level distinctions.

Coordinated multiplexing of information about separate objects in visual cortex

Sensory receptive fields are large enough that they can contain more than one perceptible stimulus. How, then, can the brain encode information about each of the stimuli that may be present at a given moment? We recently showed that when more than one stimulus is present, single neurons can fluctuate between coding one vs. the other(s) across some time period, suggesting a form of neural multiplexing of different stimuli (Caruso et al., 2018). Here, we investigate (a) whether such coding fluctuations occur in early visual cortical areas; (b) how coding fluctuations are coordinated across the neural population; and (c) how coordinated coding fluctuations depend on the parsing of stimuli into separate vs. fused objects. We found coding fluctuations do occur in macaque V1 but only when the two stimuli form separate objects. Such separate objects evoked a novel pattern of V1 spike count ('noise') correlations involving distinct distributions of positive and negative values. This bimodal correlation pattern was most pronounced among pairs of neurons showing the strongest evidence for coding fluctuations or multiplexing. Whether a given pair of neurons exhibited positive or negative correlations depended on whether the two neurons both responded better to the same object or had different object preferences. Distinct distributions of spike count correlations based on stimulus preferences were also seen in V4 for separate objects but not when two stimuli fused to form one object. These findings suggest multiple objects evoke different response dynamics than those evoked by single stimuli, lending support to the multiplexing hypothesis and suggesting a means by which information about multiple objects can be preserved despite the apparent coarseness of sensory coding.

Dynamic task-belief is an integral part of decision-making

Natural decisions involve two seemingly separable processes: inferring the relevant task (task-belief) and performing the believed-relevant task. The assumed separability has led to the traditional practice of studying task-switching and perceptual decision-making individually. Here, we used a novel paradigm to manipulate and measure macaque monkeys' task-belief and demonstrated inextricable neuronal links between flexible task-belief and perceptual decision-making. We showed that in animals, but not in artificial networks that performed as well or better than the animals, stronger task-belief is associated with better perception. Correspondingly, recordings from neuronal populations in cortical areas 7a and V1 revealed that stronger task-belief is associated with better discriminability of the believed-relevant, but not the believed-irrelevant, feature. Perception also impacts belief updating; noise fluctuations in V1 help explain how task-belief is updated. Our results demonstrate that complex tasks and multi-area recordings can reveal fundamentally new principles of how biology affects behavior in health and disease.

A general decoding strategy explains the relationship between behavior and correlated variability

Improvements in perception are frequently accompanied by decreases in correlated variability in sensory cortex. This relationship is puzzling because overall changes in correlated variability should minimally affect optimal information coding. We hypothesize that this relationship arises because instead of using optimal strategies for decoding the specific stimuli at hand, observers prioritize generality: a single set of neuronal weights to decode any stimuli. We tested this using a combination of multineuron recordings in the visual cortex of behaving rhesus monkeys and a cortical circuit model. We found that general decoders optimized for broad rather than narrow sets of visual stimuli better matched the animals’ decoding strategy, and that their performance was more related to the magnitude of correlated variability. In conclusion, the inverse relationship between perceptual performance and correlated variability can be explained by observers using a general decoding strategy, capable of decoding neuronal responses to the variety of stimuli encountered in natural vision.

Methylphenidate as a causal test of translational and basic neural coding hypotheses

Most systems neuroscience studies fall into one of two categories: basic science work aimed at understanding the relationship between neurons and behavior, or translational work aimed at developing treatments for neuropsychiatric disorders. Here we use these two approaches to inform and enhance each other. Our study both tests hypotheses about basic science neural coding principles and elucidates the neuronal mechanisms underlying clinically relevant behavioral effects of systemically administered methylphenidate (Ritalin). We discovered that orally administered methylphenidate, used clinically to treat attention deficit hyperactivity disorder (ADHD) and generally to enhance cognition, increases spatially selective visual attention, enhancing visual performance at only the attended location. Further, we found that this causal manipulation enhances vision in rhesus macaques specifically when it decreases the mean correlated variability of neurons in visual area V4. Our findings demonstrate that the visual system is a platform for understanding the neural underpinnings of both complex cognitive processes (basic science) and neuropsychiatric disorders (translation). Addressing basic science hypotheses, our results are consistent with a scenario in which methylphenidate has cognitively specific effects by working through naturally selective cognitive mechanisms. Clinically, our findings suggest that the often staggeringly specific symptoms of neuropsychiatric disorders may be caused and treated by leveraging general mechanisms.

Attention improves information flow between neuronal populations without changing the communication subspace

Visual attention allows observers to change the influence of different parts of a visual scene on their behavior, suggesting that information can be flexibly shared between visual cortex and neurons involved in decision making. We investigated the neural substrate of flexible information routing by analyzing the activity of populations of visual neurons in the medial temporal area (MT) and oculo-motor neurons in the superior colliculus (SC) while rhesus monkeys switched spatial attention. We demonstrated that attention increases the efficacy of visuomotor communication: trial-to-trial variability in SC population activity could be better predicted by the activity of the MT population (and vice versa) when attention was directed toward their joint receptive fields. Surprisingly, this improvement in prediction was not explained by changes in the dimensionality of the shared subspace or in the magnitude of local or shared pairwise noise correlations. These results lay a foundation for future theoretical and experimental studies into how visual attention can flexibly change information flow between sensory and decision neurons.

Low rank mechanisms underlying flexible visual representations

Neuronal population responses to sensory stimuli are remarkably flexible. The responses of neurons in visual cortex have heterogeneous dependence on stimulus properties (e.g., contrast), processes that affect all stages of visual processing (e.g., adaptation), and cognitive processes (e.g., attention or task switching). Understanding whether these processes affect similar neuronal populations and whether they have similar effects on entire populations can provide insight into whether they utilize analogous mechanisms. In particular, it has recently been demonstrated that attention has low rank effects on the covariability of populations of visual neurons, which impacts perception and strongly constrains mechanistic models. We hypothesized that measuring changes in population covariability associated with other sensory and cognitive processes could clarify whether they utilize similar mechanisms or computations. Our experimental design included measurements in multiple visual areas using four distinct sensory and cognitive processes. We found that contrast, adaptation, attention, and task switching affect the variability of responses of populations of neurons in primate visual cortex in a similarly low rank way. These results suggest that a given circuit may use similar mechanisms to perform many forms of modulation and likely reflects a general principle that applies to a wide range of brain areas and sensory, cognitive, and motor processes.

Simultaneous multi-area recordings suggest that attention improves performance by reshaping stimulus representations

Visual attention dramatically improves individuals' ability to see and modulates the responses of neurons in every known visual and oculomotor area, but whether such modulations can account for perceptual improvements is unclear. We measured the relationship between populations of visual neurons, oculomotor neurons and behavior during detection and discrimination tasks. We found that neither of the two prominent hypothesized neuronal mechanisms underlying attention (which concern changes in information coding and the way sensory information is read out) provide a satisfying account of the observed behavioral improvements. Instead, our results are more consistent with the hypothesis that attention reshapes the representation of attended stimuli to more effectively influence behavior. Our results suggest a path toward understanding the neural underpinnings of perception and cognition in health and disease by analyzing neuronal responses in ways that are constrained by behavior and interactions between brain areas.

Cognition as a Window into Neuronal Population Space

Understanding how cognitive processes affect the responses of sensory neurons may clarify the relationship between neuronal population activity and behavior. However, tools for analyzing neuronal activity have not kept up with technological advances in recording from large neuronal populations. Here, we describe prevalent hypotheses of how cognitive processes affect sensory neurons, driven largely by a model based on the activity of single neurons or pools of neurons as the units of computation. We then use simple simulations to expand this model to a new conceptual framework that focuses on subspaces of population activity as the relevant units of computation, uses comparisons between brain areas or to behavior to guide analyses of these subspaces, and suggests that population activity is optimized to decode the large variety of stimuli and tasks that animals encounter in natural behavior. This framework provides new ways of understanding the ever-growing quantity of recorded population activity data.

Circuit Models of Low-Dimensional Shared Variability in Cortical Networks

Trial-to-trial variability is a reflection of the circuitry and cellular physiology that make up a neuronal network. A pervasive yet puzzling feature of cortical circuits is that despite their complex wiring, population-wide shared spiking variability is low dimensional. Previous model cortical networks cannot explain this global variability, and rather assume it is from external sources. We show that if the spatial and temporal scales of inhibitory coupling match known physiology, networks of model spiking neurons internally generate low-dimensional shared variability that captures population activity recorded in vivo. Shifting spatial attention into the receptive field of visual neurons has been shown to differentially modulate shared variability within and between brain areas. A top-down modulation of inhibitory neurons in our network provides a parsimonious mechanism for this attentional modulation. Our work provides a critical link between observed cortical circuit structure and realistic shared neuronal variability and its modulation.

Neuronal population mechanisms of lightness perception

The way that humans and animals perceive the lightness of an object depends on its physical luminance as well as its surrounding context. While neuronal responses throughout the visual pathway are modulated by context, the relationship between neuronal responses and lightness perception is poorly understood. We searched for a neuronal mechanism of lightness by recording responses of neuronal populations in monkey primary visual cortex (V1) and area V4 to stimuli that produce a lightness illusion in humans, in which the lightness of a disk depends on the context in which it is embedded. We found that the way individual units encode the luminance (or equivalently for our stimuli, contrast) of the disk and its context is extremely heterogeneous. This motivated us to ask whether the population representation in either V1 or V4 satisfies three criteria: 1) disk luminance is represented with high fidelity, 2) the context surrounding the disk is also represented, and 3) the representations of disk luminance and context interact to create a representation of lightness that depends on these factors in a manner consistent with human psychophysical judgments of disk lightness. We found that populations of units in both V1 and V4 fulfill the first two criteria but that we cannot conclude that the two types of information in either area interact in a manner that clearly predicts human psychophysical measurements: the interpretation of our population measurements depends on how subsequent areas read out lightness from the population responses. NEW & NOTEWORTHY A core question in visual neuroscience is how the brain extracts stable representations of object properties from the retinal image. We searched for a neuronal mechanism of lightness perception by determining whether the responses of neuronal populations in primary visual cortex and area V4 could account for a lightness illusion measured using human psychophysics. Our results suggest that comparing psychophysics with population recordings will yield insight into neuronal mechanisms underlying a variety of perceptual phenomena.

Learning and attention reveal a general relationship between population activity and behavior

Prior studies have demonstrated that correlated variability changes with cognitive processes that improve perceptual performance. We tested whether correlated variability covaries with subjects' performance-whether performance improves quickly with attention or slowly with perceptual learning. We found a single, consistent relationship between correlated variability and behavioral performance, regardless of the time frame of correlated variability change. This correlated variability was oriented along the dimensions in population space used by the animal on a trial-by-trial basis to make decisions. That subjects' choices were predicted by specific dimensions that were aligned with the correlated variability axis clarifies long-standing paradoxes about the relationship between shared variability and behavior.

Attentional modulation of neuronal variability in circuit models of cortex

The circuit mechanisms behind shared neural variability (noise correlation) and its dependence on neural state are poorly understood. Visual attention is well-suited to constrain cortical models of response variability because attention both increases firing rates and their stimulus sensitivity, as well as decreases noise correlations. We provide a novel analysis of population recordings in rhesus primate visual area V4 showing that a single biophysical mechanism may underlie these diverse neural correlates of attention. We explore model cortical networks where top-down mediated increases in excitability, distributed across excitatory and inhibitory targets, capture the key neuronal correlates of attention. Our models predict that top-down signals primarily affect inhibitory neurons, whereas excitatory neurons are more sensitive to stimulus specific bottom-up inputs. Accounting for trial variability in models of state dependent modulation of neuronal activity is a critical step in building a mechanistic theory of neuronal cognition.

DOI:http://dx.doi.org/10.7554/eLife.23978.001

The world around us is complex and our brains need to navigate this complexity. We must focus on relevant inputs from our senses – such as the bus we need to catch – while ignoring distractions – such as the eye-catching displays in the shop windows we pass on the same street. Selective attention is a tool that enables us to filter complex sensory scenes and focus on whatever is most important at the time. But how does selective attention work?

Our sense of vision results from the activity of cells in a region of the brain called visual cortex. Paying attention to an object affects the activity of visual cortex in two ways. First, it causes the average activity of the brain cells in the visual cortex that respond to that object to increase. Second, it reduces spontaneous moment-to-moment fluctuations in the activity of those brain cells, known as noise. Both of these effects make it easier for the brain to process the object in question.

Kanashiro et al. set out to build a mathematical model of visual cortex that captures these two components of selective attention. The cortex contains two types of brain cells: excitatory neurons, which activate other cells, and inhibitory neurons, which suppress other cells. Experiments suggest that excitatory neurons contribute to the flow of activity within the cortex, whereas inhibitory neurons help cancel out noise. The new mathematical model predicts that paying attention affects inhibitory neurons far more than excitatory ones. According to the model, selective attention works mainly by reducing the noise that would otherwise distort the activity of visual cortex.

The next step is to test this prediction directly. This will require measuring the activity of the inhibitory neurons in an animal performing a selective attention task. Such experiments, which should be achievable using existing technologies, will allow scientists to confirm or disprove the current model, and to dissect the mechanisms that underlie visual attention.

DOI:http://dx.doi.org/10.7554/eLife.23978.002

Relating normalization to neuronal populations across cortical areas

Normalization, which divisively scales neuronal responses to multiple stimuli, is thought to underlie many sensory, motor, and cognitive processes. In every study where it has been investigated, neurons measured in the same brain area under identical conditions exhibit a range of normalization, ranging from suppression by nonpreferred stimuli (strong normalization) to additive responses to combinations of stimuli (no normalization). Normalization has been hypothesized to arise from interactions between neuronal populations, either in the same or different brain areas, but current models of normalization are not mechanistic and focus on trial-averaged responses. To gain insight into the mechanisms underlying normalization, we examined interactions between neurons that exhibit different degrees of normalization. We recorded from multiple neurons in three cortical areas while rhesus monkeys viewed superimposed drifting gratings. We found that neurons showing strong normalization shared less trial-to-trial variability with other neurons in the same cortical area and more variability with neurons in other cortical areas than did units with weak normalization. Furthermore, the cortical organization of normalization was not random: neurons recorded on nearby electrodes tended to exhibit similar amounts of normalization. Together, our results suggest that normalization reflects a neuron's role in its local network and that modulatory factors like normalization share the topographic organization typical of sensory tuning properties.

Extracellular voltage threshold settings can be tuned for optimal encoding of movement and stimulus parameters

OBJECTIVE

A traditional goal of neural recording with extracellular electrodes is to isolate action potential waveforms of an individual neuron. Recently, in brain-computer interfaces (BCIs), it has been recognized that threshold crossing events of the voltage waveform also convey rich information. To date, the threshold for detecting threshold crossings has been selected to preserve single-neuron isolation. However, the optimal threshold for single-neuron identification is not necessarily the optimal threshold for information extraction. Here we introduce a procedure to determine the best threshold for extracting information from extracellular recordings. We apply this procedure in two distinct contexts: the encoding of kinematic parameters from neural activity in primary motor cortex (M1), and visual stimulus parameters from neural activity in primary visual cortex (V1).

APPROACH

We record extracellularly from multi-electrode arrays implanted in M1 or V1 in monkeys. Then, we systematically sweep the voltage detection threshold and quantify the information conveyed by the corresponding threshold crossings.

MAIN RESULTS

The optimal threshold depends on the desired information. In M1, velocity is optimally encoded at higher thresholds than speed; in both cases the optimal thresholds are lower than are typically used in BCI applications. In V1, information about the orientation of a visual stimulus is optimally encoded at higher thresholds than is visual contrast. A conceptual model explains these results as a consequence of cortical topography.

SIGNIFICANCE

How neural signals are processed impacts the information that can be extracted from them. Both the type and quality of information contained in threshold crossings depend on the threshold setting. There is more information available in these signals than is typically extracted. Adjusting the detection threshold to the parameter of interest in a BCI context should improve our ability to decode motor intent, and thus enhance BCI control. Further, by sweeping the detection threshold, one can gain insights into the topographic organization of the nearby neural tissue.

Attention can either increase or decrease spike count correlations in visual cortex

Visual attention enhances the responses of visual neurons that encode the attended location. Several recent studies showed that attention also decreases correlations between fluctuations in the responses of pairs of neurons (termed spike count correlation or r_SC). The previous results are consistent with two hypotheses. Attention–related changes in rate and r_SC might be linked (perhaps through a common mechanism), so that attention always decreases r_SC. Alternately, attention might either increase or decrease r_SC, possibly depending on the role the neurons play in the behavioral task. We recorded simultaneously from dozens of neurons in area V4 while monkeys performed a discrimination task. We found strong evidence in favor of the second hypothesis, showing that attention can flexibly increase or decrease correlations, depending on whether the neurons provide evidence for the same or opposite perceptual decisions. These results place important constraints on models of the neuronal mechanisms underlying cognitive factors.

Expression of anxiety and depression in a case of subcortical motor aphasia

A decision tree and decimal rating scales were used for psychotherapy with a patient with post-stroke subcortical motor aphasia. These two methods used in combination were highly efficient in obtaining information about the patient's mood and issues of concern. The patient was able to report on changing levels of anxiety and depression. He was able to relate his emotional state to environmental or personal factors. Values as low as 1 and as high as 10 for anxiety and depression were reported by the patient during the course of 25 psychotherapy sessions. A Pearson correlation indicated that anxiety and depression varied independently.

Decision-related activity in sensory neurons: correlations among neurons and with behavior

Neurons in early sensory cortex show weak but systematic correlations with perceptual decisions when trained animals perform at psychophysical threshold. These correlations are observed across repeated presentations of identical stimuli and cannot be explained by variation in external factors. The relationship between the activity of individual sensory neurons and the animal's behavioral choice means that even neurons in early sensory cortex carry information about an upcoming decision. This relationship, termed choice probability, may reflect the effect of fluctuations in neuronal firing rate on the animal's decision, but it can also reflect modulation of sensory responses by cognitive factors, or network properties such as variability that is shared among populations of neurons. Here, we review recent work clarifying the relationship among fluctuations in the responses of individual neurons, correlated variability, and behavior in a variety of tasks and cortical areas. We also discuss the possibility that choice probability may in part reflect the influence of cognitive factors on sensory neurons and explore the situations in which choice probability can be used to make inferences about the role of particular sensory neurons in the decision-making process.

Using neuronal populations to study the mechanisms underlying spatial and feature attention

Visual attention affects both perception and neuronal responses. Whether the same neuronal mechanisms mediate spatial attention, which improves perception of attended locations, and nonspatial forms of attention has been a subject of considerable debate. Spatial and feature attention have similar effects on individual neurons. Because visual cortex is retinotopically organized, however, spatial attention can comodulate local neuronal populations, whereas feature attention generally requires more selective modulation. We compared the effects of feature and spatial attention on local and spatially separated populations by recording simultaneously from dozens of neurons in both hemispheres of V4. Feature and spatial attention affect the activity of local populations similarly, modulating both firing rates and correlations between pairs of nearby neurons. However, whereas spatial attention appears to act on local populations, feature attention is coordinated across hemispheres. Our results are consistent with a unified attentional mechanism that can modulate the responses of arbitrary subgroups of neurons.

Measuring and interpreting neuronal correlations

Mounting evidence suggests that understanding how the brain encodes information and performs computations will require studying the correlations between neurons. The recent advent of recording techniques such as multielectrode arrays and two-photon imaging has made it easier to measure correlations, opening the door for detailed exploration of their properties and contributions to cortical processing. However, studies have reported discrepant findings, providing a confusing picture. Here we briefly review these studies and conduct simulations to explore the influence of several experimental and physiological factors on correlation measurements. Differences in response strength, the time window over which spikes are counted, spike sorting conventions and internal states can all markedly affect measured correlations and systematically bias estimates. Given these complicating factors, we offer guidelines for interpreting correlation data and a discussion of how best to evaluate the effect of correlations on cortical processing.

Attention improves performance primarily by reducing interneuronal correlations

Visual attention can dramatically improve behavioural performance by allowing observers to focus on the important information in a complex scene. Attention also typically increases the firing rates of cortical sensory neurons. Rate increases improve the signal-to-noise ratio of individual neurons, and this improvement has been assumed to underlie attention-related improvements in behaviour. We recorded dozens of neurons simultaneously in visual area V4 and found that changes in single neurons accounted for only a small fraction of the improvement in the sensitivity of the population. Instead, over 80% of the attentional improvement in the population signal was caused by decreases in the correlations between the trial-to-trial fluctuations in the responses of pairs of neurons. These results suggest that the representation of sensory information in populations of neurons and the way attention affects the sensitivity of the population may only be understood by considering the interactions between neurons.

Fluorescamine as a terminating agent in solid phase peptide synthesis

Fluorescamine was shown to be an excellent terminating agent for blocking unreacted amino groups during solid phase peptide synthesis. A comparison of the termination efficiency of fluorescamine versus that of acetylation revealed that the former method gave superior products as assessed by peptide analysis, dansyl-amino end group determination and biological assay. In addition, fluorescamine terminated fragments were converted to non-fluorescent spirolactones during the deprotection stage. These spirolactones were stable to subsequent solid phase reaction conditions and were readily removed from the target peptide.

Cone signal interactions in direction-selective neurons in the middle temporal visual area (MT)

Many experimental measurements support the hypothesis that the middle temporal visual area (MT) of the rhesus monkey has a central role in processing visual motion. Most of these studies were performed using luminance stimuli, leaving open the question of how color information is used during motion processing. We investigated the specific question of how S-cone signals, an important source of color information, interact with L,M-cone signals, the dominant source of luminance information. In MT, S-cone-initiated signals combine synergistically with L,M-cone (luminance) signals over most of the stimulus range, regardless of whether the stimuli are added or subtracted. A quantitative analysis of the responses to the combination of S- and L,M-cone signals shows that for a significant minority of cells, these S-cone signals are carried to MT by a color-opponent ("blue-yellow") pathway, such that in certain limited contrast ranges, a small amount of S- and L,M-cone cancellation is observed. Both S- and L,M-cone responses are direction-selective, suggesting that MT processes a wide range of motion signals, including those carried by luminance and color. To investigate this possibility further, we measured MT responses while monkeys discriminated the direction of motion of luminance and S-cone-initiated gratings. The sensitivity of single MT neurons and the correlation between trial-to-trial variations in single neuron firing and perception are similar for S- and L,M-cone stimuli, further supporting a role for MT in processing chromatic motion.

Reversal of motor learning in the vestibulo-ocular reflex in the absence of visual input

Motor learning in the vestibulo-ocular reflex (VOR) and eyeblink conditioning use similar neural circuitry, and they may use similar cellular plasticity mechanisms. Classically conditioned eyeblink responses undergo extinction after prolonged exposure to the conditioned stimulus in the absence of the unconditioned stimulus. We investigated the possibility that a process similar to extinction may reverse learned changes in the VOR. We induced a learned alteration of the VOR response in rhesus monkeys using magnifying or miniaturizing goggles, which caused head movements to be accompanied by visual image motion. After learning, head movements in the absence of visual stimulation caused a loss of the learned eye movement response. When the learned gain was low, this reversal of learning occurred only when head movements were delivered, and not when the head was held stationary in the absence of visual input, suggesting that this reversal is mediated by an active, extinction-like process.

What electrical microstimulation has revealed about the neural basis of cognition

Neurophysiologists have shown repeatedly that neural activity in different brain structures can be correlated with specific perceptual and cognitive functions, but the causal efficacy of the observed activity has generally been a matter of conjecture. By contrast, electrical microstimulation, which allows the experimenter to manipulate the activity of small groups of neurons with spatial and temporal precision, can now be used to demonstrate causal links between neural activity and specific cognitive functions. Here, we review this growing literature, including applications to the study of attention, visual and somatosensory perception, 'read-out' mechanisms for interpreting sensory maps, and contextual effects on perception. We also discuss potential applications of microstimulation to studies of higher cognitive functions such as decision-making and subjective experience.

Complete remodelling of displaced fractures of the neck of the phalanx

Fractures of the neck of the phalanx of the finger are uncommon, but problematic, injuries in children. Displaced fractures may heal with malunion leading to loss of movement or angular deformity. Remodelling of the phalangeal neck is reported to be minimal because of the distance of the fracture from the physis. We report three displaced fractures in two children who presented late. The fractures were treated conservatively and remodelled completely. Both patients regained full movement of the fingers.

Herbal and complementary and alternative medicine therapies for liver disease. A focus on Chinese traditional medicine in hepatitis C virus

This article presents herbal and alternative therapies used in the treatment of liver disease, both as adjunctive or complementary treatment to Western pharmaceutical strategies, and as an alternative treatment in liver disease, particularly for Hepatitis C Virus. There is a special emphasis on traditional Chinese herbal medicine.

Use of a chinese herbal medicine for treatment of hiv-associated pathogen-negative diarrhea

Background: Diarrhea is a frequent problem among persons with advanced HIV disease. In the absence of treatable pathogens, symptomatic relief is all that is available for current therapy. As a result, many patients with HIV and chronic diarrhea have turned to herbal formulas for treatment. We assessed the effectiveness and safety of a Chinese herbal formulation (Source Qi) in reducing the number of stools per day related to HIV-associated, pathogen-negative diarrhea. Methods: Sixteen male patients received treatment with Source Qi in an 8-week, open-label study. Patients tested negative for cryptosporidium and other gastrointestinal pathogens, and had chronic diarrhea, defined as having three or more loose stools/day for >/=14 days (and no other treatable causes for diarrhea). Measurements of diarrhea included numbers of bowel movements/day, abnormal bowel movements/day, and liquid bowel movements/day. Subjects completed daily stool diaries an average of 2 weeks before and up to 8 weeks after starting Source Qi. Paired Wilcoxon tests compared the last week before treatment with each week of treatment. Results: There was a reduction in average number of stools/day in each week of treatment (-0.2 to -0.8), except week 1 (+0.1), with improvements in weeks 2-6 approaching or reaching statistical significance. Conclusions: A modest but sustained decrease in average number of stools/day was observed in patients with HIV-associated, pathogen-negative diarrhea. The entry criteria, 2-week run-in period, lack of benefit in week 1, and sustained benefit thereafter all suggest that the improvement was not due to bias.

Randomized, placebo-controlled trial of Chinese herb therapy for HIV-1-infected individuals

CONTEXT

Alternative medicine or complementary remedies that have not been scientifically tested are nonetheless widely used to treat chronic illnesses, particularly if curative options are limited.

OBJECTIVES

To assess the effectiveness of Chinese medicinal herbs in reducing symptoms and improving the quality of life of HIV-infected persons.

DESIGN

Prospective, placebo-controlled double-blind study.

SETTING

University-based HIV outpatient clinic.

PATIENTS

68 HIV-infected adults with CD4 cell counts <0.5 x 10(9)/L.

INTERVENTION

Participants were randomized to receive four daily doses of seven pills containing a standardized preparation of 35 Chinese herbs or placebo for 6 months.

MAIN OUTCOME MEASURES

Symptoms, HIV disease progression, HIV-1 RNA plasma viral loads, CD4 and CD8 cell counts, and scores on standard questionnaires for quality of life, depression, anxiety, and coping.

RESULTS

Intervention and placebo groups were equivalent at baseline regarding, respectively, previous antiretroviral therapy (74% versus 79%), median CD4 cell counts (0.20 x 10(9)/L versus 0.25 x 10(9)/L), and median HIV-1 plasma viral loads (35,612 copies/ml versus 52,027 copies/ml). At enrollment, none of the study subjects was seriously ill or depressed, and average coping and quality of life scores were in the normal range. In all, 53 (78%) participants completed the study. Patients taking Chinese herbs reported significantly more gastrointestinal disturbances (79% versus 38%; p = .003) than those receiving placebo. No therapy-related toxicities were observed. At completion of the study, no significant differences between the intervention and placebo groups were found regarding plasma viral loads, CD4 cell counts, symptoms, and psychometric parameters. HIV-1 RNA level was unchanged at study end. Among participants who were not on concomitant antiretroviral therapy, median CD4 cell counts declined by 0.05 x 10(9)/L in both the intervention and placebo groups.

CONCLUSIONS

This standardized formulation of Chinese herbs for HIV-infected individuals did not improve quality of life, clinical manifestations, plasma virus loads, or CD4 cell counts. The data suggest that this formulation of Chinese herbs is not effective when administered in a Western medicine setting.

Baseline relationships between psoriasis and psoriatic arthritis: analysis of 221 patients with active psoriatic arthritis. Department of Veterans Affairs Cooperative Study Group on Seronegative Spondyloarthropathies

OBJECTIVE

To determine differences in disease onset, extent, and manifestations of psoriasis among patients with active, inflammatory psoriatic arthritis (PsA), and to examine relationships that may exist between psoriasis and PsA.

METHODS

Baseline demographic, clinical, and laboratory data were analyzed from 221 patients enrolled in a multicenter cooperative study, and relationships between measures of psoriasis and PsA were determined.

RESULTS

Mean percentage of body surface area (BSA) affected by psoriasis was modest (12+/-17), and mean severity of erythema, induration, and scaling was moderate (4.9+/-2.1 on a 0-9 scale). Spanish Americans tended to have a higher mean percentage of BSA (18.5%) than Caucasians (11%; p = 0.067), as well as higher target lesion severity (5.55 vs. 4.84; p = 0.077). Patients with psoriatic nail disease (180/221, 81%) had significantly greater number of involved distal interphalangeal (DIP) joints (p = 0.004). There were no other significant associations of skin pattern or regional involvement with PsA.

CONCLUSION

Patients with active PsA have generally mild skin disease, and baseline relationships between psoriasis and PsA tend to be weak except for nail involvement and DIP joint activity.

Effectiveness of technical assistance in the development of psychiatric rehabilitation programs

Most mental health programs need technical assistance to develop effective psychiatric rehabilitation programs. This article discusses how psychiatric rehabilitation was introduced into three community mental health programs and describes the elements of a psychiatric rehabilitation program and the phases of a technical assistance process. A case study illustrates how technical assistance consultants can be trained to develop psychiatric rehabilitation programs. Barriers and facilitators to the technical assistance are discussed in the context of several other technical assistance studies.

Survey of hospital systems and common serious medication errors

The Institute for Safe Medication Practices and the University of Illinois at Chicago, College of Pharmacy, undertook a hospital survey of medical-surgical hospitals to determine systems-oriented factors that allow the highest level of medication safety. The study incorporated a peer-reviewed and pretested questionnaire, which focused on critical information necessary to yield quality data for comparison. Through analysis, it was shown that over one third of all medication errors reported in the survey involve just six categories--allergies, insulin, heparin, opiates, PCA devices, and potassium concentrates.