Behavioral Detection of Electrical Microstimulation in Different Cortical Visual Areas

SummaryThe extent to which areas in the visual cerebral cortex differ in their ability to support perceptions has been the subject of considerable speculation. Experiments examining the activity of individual neurons have suggested that activity in later stages of the visual cortex is more closely linked to perception than that in earlier stages [1–9]. In contrast, results from functional imaging, transcranial magnetic stimulation, and lesion studies have been interpreted as showing that earlier stages are more closely coupled to perception [10–15]. We examined whether neuronal activity in early and later stages differs in its ability to support detectable signals by measuring behavioral thresholds for detecting electrical microstimulation in different cortical areas in two monkeys. By training the animals to perform a two-alternative temporal forced-choice task, we obtained criterion-free thresholds from five visual areas—V1, V2, V3A, MT, and the inferotemporal cortex. Every site tested yielded a reliable threshold. Thresholds varied little within and between visual areas, rising gradually from early to later stages. We similarly found no systematic differences in the slopes of the psychometric detection functions from different areas. These results suggest that neuronal signals of similar magnitude evoked in any part of visual cortex can generate percepts

No binocular rivalry in the LGN of alert macaque monkeys

AbstractOrthogonal drifting gratings were presented binocularly to alert macaque monkeys in an attempt to find neural correlates of binocular rivalry. Gratings were centered over lateral geniculate nucleus (LGN) receptive fields and the corresponding points for the opposite eye. The only task of the monkey was to fixate. We found no difference between the responses of LGN neurons under rivalrous and nonrivalrous conditions, as determined by examining the ratios of their respective power spectra. There was, however, a curious “temporal afterimage” effect in which cell responses continued to be modulated at the drift frequency of the grating for several seconds after the grating disappeared

The Neuroscience Peer Review Consortium

As the Neuroscience Peer Review Consortium (NPRC) ends its first year, it is worth looking back to see how the experiment has worked

Nine Criteria for a Measure of Scientific Output

Scientific research produces new knowledge, technologies, and clinical treatments that can lead to enormous returns. Often, the path from basic research to new paradigms and direct impact on society takes time. Precise quantification of scientific output in the short-term is not an easy task but is critical for evaluating scientists, laboratories, departments, and institutions. While there have been attempts to quantifying scientific output, we argue that current methods are not ideal and suffer from solvable difficulties. Here we propose criteria that a metric should have to be considered a good index of scientific output. Specifically, we argue that such an index should be quantitative, based on robust data, rapidly updated and retrospective, presented with confidence intervals, normalized by number of contributors, career stage and discipline, impractical to manipulate, and focused on quality over quantity. Such an index should be validated through empirical testing. The purpose of quantitatively evaluating scientific output is not to replace careful, rigorous review by experts but rather to complement those efforts. Because it has the potential to greatly influence the efficiency of scientific research, we have a duty to reflect upon and implement novel and rigorous ways of evaluating scientific output. The criteria proposed here provide initial steps toward the systematic development and validation of a metric to evaluate scientific output

Strength of Gamma Rhythm Depends on Normalization

Neuronal assemblies often exhibit stimulus-induced rhythmic activity in the gamma range (30–80 Hz), whose magnitude depends on the attentional load. This has led to the suggestion that gamma rhythms form dynamic communication channels across cortical areas processing the features of behaviorally relevant stimuli. Recently, attention has been linked to a normalization mechanism, in which the response of a neuron is suppressed (normalized) by the overall activity of a large pool of neighboring neurons. In this model, attention increases the excitatory drive received by the neuron, which in turn also increases the strength of normalization, thereby changing the balance of excitation and inhibition. Recent studies have shown that gamma power also depends on such excitatory–inhibitory interactions. Could modulation in gamma power during an attention task be a reflection of the changes in the underlying excitation–inhibition interactions? By manipulating the normalization strength independent of attentional load in macaque monkeys, we show that gamma power increases with increasing normalization, even when the attentional load is fixed. Further, manipulations of attention that increase normalization increase gamma power, even when they decrease the firing rate. Thus, gamma rhythms could be a reflection of changes in the relative strengths of excitation and normalization rather than playing a functional role in communication or control

The Neuroscience Peer Review Consortium

The Neuroscience Peer Review Consortium (NPRC) was conceived in the summer of 2007 at a meeting of editors and publishers of neuroscience journals. One of the working groups addressed whether it was possible to construct a system for permitting authors whose manuscript received supportive reviews at one journal but was not accepted to send a revised manuscript together with its first round of reviews to a new journal for the second round. This would speed up the review process and reduce the work for reviewers and editors. The working group not only designed a framework for transferring reviews among journals, but also implemented it as the NPRC. By the fall of 2007, more than a dozen major journals had signed onto the NPRC, sufficient to launch the experiment in January, 2008. We invite authors who have not yet used the NPRC to try this method for appropriate manuscripts

Functional Organization and Connections of the Middle Temporal Visual Area in the Macaque Monkey

A variety of anatomical and physiological criteria have shown that the extrastriate visual cortex of the macaque monkey is subdivided into many distinct areas. There is evidence to suggest that there is functional specialization among these areas. Previous studies have shown that the middle temporal visual area (MT) contains a high proportion of cells which are selective for the direction of movement of visual stimuli, and yet relatively non-selective for stimulus color or form. The experiments reported here examined the response properties in MT in greater detail, and demonstrated the inputs and outputs of the area by means of anatomical tracers. A computer-driven stimulator was used to examine quantitatively the responses of 163 single units from five anesthetized and paralyzed Macaca fascicularis. The experiments included tests of selectivity for stimulus direction, speed, orientation and disparity. Cells were also tested with stimuli which simulated trajectories with components of motion toward or away from the animal. The results show that in addition to direction selectivity, many cells in MT are sharply tuned for stimulus speed and disparity. This suggests that neurons in MT are well adapted for the analysis of motion in three-dimensional space. Horseradish peroxidase and 3H-proline were injected into MT in three animals to demonstrate its anatomical inputs and outputs. Connections were seen with a large number of subcortical and cortical areas. In addition, connections with MT provide evidence contributing to the identification of two previously unrecognized cortical areas, which we have designated the medial superior temporal area (MST) and the ventral intraparietal area (VIP). The cortical layers in which projections originate and terminate are shown to provide objective anatomical criteria for assigning most cortical visual areas to a hierarchical order.</p

Nine Criteria for a Measure of Scientific Output

Scientific research produces new knowledge, technologies, and clinical treatments that can lead to enormous returns. Often, the path from basic research to new paradigms and direct impact on society takes time. Precise quantification of scientific output in the short-term is not an easy task but is critical for evaluating scientists, laboratories, departments, and institutions.While there have been attempts to quantifying scientific output, we argue that current methods are not ideal and suffer from solvable difficulties. Here we propose criteria that a metric should have to be considered a good index of scientific output. Specifically, we argue that such an index should be quantitative, based on robust data, rapidly updated and retrospective, presented with confidence intervals, normalized by number of contributors, career stage and discipline, impractical to manipulate, and focused on quality over quantity. Such an index should be validated through empirical testing.The purpose of quantitatively evaluating scientific output is not to replace careful, rigorous review by experts but rather to complement those efforts. Because it has the potential to greatly influence the efficiency of scientific research, we have a duty to reflect upon and implement novel and rigorous ways of evaluating scientific output. The criteria proposed here provide initial steps toward the systematic development and validation of a metric to evaluate scientific output

A Refined Neuronal Population Measure of Visual Attention

Neurophysiological studies of cognitive mechanisms such as visual attention typically ignore trial-by-trial variability and instead report mean differences averaged across many trials. Advances in electrophysiology allow for the simultaneous recording of small populations of neurons, which may obviate the need for averaging activity over trials. We recently introduced a method called the attention axis that uses multi-electrode recordings to provide estimates of attentional state of behaving monkeys on individual trials. Here, we refine this method to eliminate problems that can cause bias in estimates of attentional state in certain scenarios. We demonstrate the sources of these problems using simulations and propose an amendment to the previous formulation that provides superior performance in trial-by-trial assessments of attentional state