The timing of response onset and offset in macaque visual neurons

Different sensory information is used for state estimation when stationary or moving

The accurate estimation of limb state is necessary for movement planning and execution. While state estimation requires both feedforward and feedback information, we focus here on the latter. Prior literature has shown that integrating visual and proprioceptive feedback improves estimates of static limb position. However, differences in visual and proprioceptive feedback delays suggest that multisensory integration could be disadvantageous when the limb is moving. We formalized this hypothesis by modeling feedback-based state estimation using the longstanding maximum likelihood estimation model of multisensory integration, which we updated to account for sensory delays. Our model predicted that the benefit of multisensory integration was largely lost when the limb was passively moving. We tested this hypothesis in a series of experiments in human subjects that compared the degree of interference created by discrepant visual or proprioceptive feedback when estimating limb position either statically at the end of the movement or dynamically at movement midpoint. In the static case, we observed significant interference: discrepant feedback in one modality systematically biased sensory estimates based on the other modality. However, no interference was seen in the dynamic case: participants could ignore sensory feedback from one modality and accurately reproduce the motion indicated by the other modality. Together, these findings suggest that the sensory feedback used to compute a state estimate differs depending on whether the limb is stationary or moving. While the former may tend toward multimodal integration, the latter is more likely to be based on feedback from a single sensory modality.

Phase of neural oscillations as a reference frame for attention-based routing in visual cortex

Selective attention allows the brain to efficiently process the image projected onto the retina, selectively focusing neural processing resources on behaviorally relevant visual information. While previous studies have documented the crucial role of the action potential rate of single neurons in relaying such information, little is known about how the activity of single neurons relative to their neighboring network contributes to the efficient representation of attended stimuli and transmission of this information to downstream areas. Here, we show in the dorsal visual pathway of monkeys (medial superior temporal area) that neurons fire spikes preferentially at a specific phase of the ongoing population beta (∼20 Hz) oscillations of the surrounding local network. This preferred spiking phase shifts towards a later phase when monkeys selectively attend towards (rather than away from) the receptive field of the neuron. This shift of the locking phase is positively correlated with the speed at which animals report a visual change. Furthermore, our computational modeling suggests that neural networks can manipulate the preferred phase of coupling by imposing differential synaptic delays on postsynaptic potentials. This distinction between the locking phase of neurons activated by the spatially attended stimulus vs. that of neurons activated by the unattended stimulus, may enable the neural system to discriminate relevant from irrelevant sensory inputs and consequently filter out distracting stimuli information by aligning the spikes which convey relevant/irrelevant information to distinct phases linked to periods of better/worse perceptual sensitivity for higher cortices. This strategy may be used to reserve the narrow windows of highest perceptual efficacy to the processing of the most behaviorally relevant information, ensuring highly efficient responses to attended sensory events.

Characterizing Spatiotemporal Population Receptive Fields in Human Visual Cortex with fMRI

The use of fMRI and computational modeling has advanced understanding of spatial characteristics of population receptive fields (pRFs) in human visual cortex. However, we know relatively little about the spatiotemporal characteristics of pRFs because neurons' temporal properties are one to two orders of magnitude faster than fMRI BOLD responses. Here, we developed an image-computable framework to estimate spatiotemporal pRFs from fMRI data. First, we developed a simulation software that predicts fMRI responses to a time-varying visual input given a spatiotemporal pRF model and solves the model parameters. The simulator revealed that ground-truth spatiotemporal parameters can be accurately recovered at the millisecond resolution from synthesized fMRI responses. Then, using fMRI and a novel stimulus paradigm, we mapped spatiotemporal pRFs in individual voxels across human visual cortex in 10 participants (both females and males). We find that a compressive spatiotemporal (CST) pRF model better explains fMRI responses than a conventional spatial pRF model across visual areas spanning the dorsal, lateral, and ventral streams. Further, we find three organizational principles of spatiotemporal pRFs: (1) from early to later areas within a visual stream, spatial and temporal windows of pRFs progressively increase in size and show greater compressive nonlinearities, (2) later visual areas show diverging spatial and temporal windows across streams, and (3) within early visual areas (V1-V3), both spatial and temporal windows systematically increase with eccentricity. Together, this computational framework and empirical results open exciting new possibilities for modeling and measuring fine-grained spatiotemporal dynamics of neural responses using fMRI.

Optogenetic activation of visual thalamus generates artificial visual percepts

The lateral geniculate nucleus (LGN), a retinotopic relay center where visual inputs from the retina are processed and relayed to the visual cortex, has been proposed as a potential target for artificial vision. At present, it is unknown whether optogenetic LGN stimulation is sufficient to elicit behaviorally relevant percepts, and the properties of LGN neural responses relevant for artificial vision have not been thoroughly characterized. Here, we demonstrate that tree shrews pretrained on a visual detection task can detect optogenetic LGN activation using an AAV2-CamKIIα-ChR2 construct and readily generalize from visual to optogenetic detection. Simultaneous recordings of LGN spiking activity and primary visual cortex (V1) local field potentials (LFPs) during optogenetic LGN stimulation show that LGN neurons reliably follow optogenetic stimulation at frequencies up to 60 Hz and uncovered a striking phase locking between the V1 LFP and the evoked spiking activity in LGN. These phase relationships were maintained over a broad range of LGN stimulation frequencies, up to 80 Hz, with spike field coherence values favoring higher frequencies, indicating the ability to relay temporally precise information to V1 using light activation of the LGN. Finally, V1 LFP responses showed sensitivity values to LGN optogenetic activation that were similar to the animal's behavioral performance. Taken together, our findings confirm the LGN as a potential target for visual prosthetics in a highly visual mammal closely related to primates.

Characterizing spatiotemporal population receptive fields in human visual cortex with fMRI

The use of fMRI and computational modeling has advanced understanding of spatial characteristics of population receptive fields (pRFs) in human visual cortex. However, we know relatively little about the spatiotemporal characteristics of pRFs because neurons' temporal properties are one to two orders of magnitude faster than fMRI BOLD responses. Here, we developed an image-computable framework to estimate spatiotemporal pRFs from fMRI data. First, we developed a simulation software that predicts fMRI responses to a time varying visual input given a spatiotemporal pRF model and solves the model parameters. The simulator revealed that ground-truth spatiotemporal parameters can be accurately recovered at the millisecond resolution from synthesized fMRI responses. Then, using fMRI and a novel stimulus paradigm, we mapped spatiotemporal pRFs in individual voxels across human visual cortex in 10 participants. We find that a compressive spatiotemporal (CST) pRF model better explains fMRI responses than a conventional spatial pRF model across visual areas spanning the dorsal, lateral, and ventral streams. Further, we find three organizational principles of spatiotemporal pRFs: (i) from early to later areas within a visual stream, spatial and temporal integration windows of pRFs progressively increase in size and show greater compressive nonlinearities, (ii) later visual areas show diverging spatial and temporal integration windows across streams, and (iii) within early visual areas (V1-V3), both spatial and temporal integration windows systematically increase with eccentricity. Together, this computational framework and empirical results open exciting new possibilities for modeling and measuring fine-grained spatiotemporal dynamics of neural responses in the human brain using fMRI.

Recognition of letters displayed as successive contour fragments

Shapes can be displayed as parts but perceived as a whole through feedforward and feedback mechanisms in the visual system, though the exact spatiotemporal relationships for this process are still unclear. Our experiments examined the integration of letter fragments that were displayed as a rapid sequence. We examined the effects of timing and masking on integration, hypothesizing that increasing the timing interval between frames would impair recognition by disrupting contour linkage. We further used different mask types, a full-field pattern mask and a smaller strip mask, to examine the effects of global vs local masking on integration. We found that varying mask types and contrast produced a greater decline in recognition than was found when persistence or mask density was manipulated. The study supports prior work on letter recognition and provides greater insight into the spatiotemporal factors that contribute to the identification of shapes.

More than the end: OFF response plasticity as a mnemonic signature of a sound’s behavioral salience

In studying how neural populations in sensory cortex code dynamically varying stimuli to guide behavior, the role of spiking after stimuli have ended has been underappreciated. This is despite growing evidence that such activity can be tuned, experience-and context-dependent and necessary for sensory decisions that play out on a slower timescale. Here we review recent studies, focusing on the auditory modality, demonstrating that this so-called OFF activity can have a more complex temporal structure than the purely phasic firing that has often been interpreted as just marking the end of stimuli. While diverse and still incompletely understood mechanisms are likely involved in generating phasic and tonic OFF firing, more studies point to the continuing post-stimulus activity serving a short-term, stimulus-specific mnemonic function that is enhanced when the stimuli are particularly salient. We summarize these results with a conceptual model highlighting how more neurons within the auditory cortical population fire for longer duration after a sound’s termination during an active behavior and can continue to do so even while passively listening to behaviorally salient stimuli. Overall, these studies increasingly suggest that tonic auditory cortical OFF activity holds an echoic memory of specific, salient sounds to guide behavioral decisions.

Adaptive erasure of spurious sequences in sensory cortical circuits

Sequential activity reflecting previously experienced temporal sequences is considered a hallmark of learning across cortical areas. However, it is unknown how cortical circuits avoid the converse problem: producing spurious sequences that are not reflecting sequences in their inputs. We develop methods to quantify and study sequentiality in neural responses. We show that recurrent circuit responses generally include spurious sequences, which are specifically prevented in circuits that obey two widely known features of cortical microcircuit organization: Dale’s law and Hebbian connectivity. In particular, spike-timing-dependent plasticity in excitation-inhibition networks leads to an adaptive erasure of spurious sequences. We tested our theory in multielectrode recordings from the visual cortex of awake ferrets. Although responses to natural stimuli were largely non-sequential, responses to artificial stimuli initially included spurious sequences, which diminished over extended exposure. These results reveal an unexpected role for Hebbian experience-dependent plasticity and Dale’s law in sensory cortical circuits.

•

Recurrent circuits generate spurious sequences without sequential inputs

•

A principled measure of total sequentiality in population responses is developed

•

Theory predicts that Hebbian plasticity should abolish spurious sequences

•

Spurious sequences in the visual cortex diminish with experience

Stimulus dependence of directed information exchange between cortical layers in macaque V1

Perception and cognition require the integration of feedforward sensory information with feedback signals. Using different sized stimuli, we isolate spectral signatures of feedforward and feedback signals, and their effect on communication between layers in primary visual cortex of male macaque monkeys. Small stimuli elicited gamma frequency oscillations predominantly in the superficial layers. These Granger-causally originated in upper layer 4 and lower supragranular layers. Unexpectedly, large stimuli generated strong narrow band gamma oscillatory activity across cortical layers. They Granger-causally arose in layer 5, were conveyed through layer six to superficial layers, and violated existing models of feedback spectral signatures. Equally surprising, with large stimuli, alpha band oscillatory activity arose predominantly in granular and supragranular layers and communicated in a feedforward direction. Thus, oscillations in specific frequency bands are dynamically modulated to serve feedback and feedforward communication and are not restricted to specific cortical layers in V1.

A neuronal basis of iconic memory in macaque primary visual cortex

After a briefly presented visual stimulus disappears, observers retain a detailed representation of this stimulus for a short period of time. This sensory storage is called iconic memory. We measured iconic memory in the perception of monkeys and its neuronal correlates in the primary visual cortex (area V1). We determined how many milliseconds extra viewing time iconic memory is worth and how it decays by varying the duration of a brief stimulus and the timing of a mask. The V1 activity that persists after the disappearance of a stimulus predicted accuracy, with a time course resembling the worth and decay of iconic memory. Finally, we examined how iconic memory interacts with attention. A cue presented after the stimulus disappears boosts attentional influences pertaining to a relevant part of the stimulus but only if it appears before iconic memory decayed. Our results relate iconic memory to neuronal activity in early visual cortex.

Dynamic divisive normalization circuits explain and predict change detection in monkey area MT

Sudden changes in visual scenes often indicate important events for behavior. For their quick and reliable detection, the brain must be capable to process these changes as independently as possible from its current activation state. In motion-selective area MT, neurons respond to instantaneous speed changes with pronounced transients, often far exceeding the expected response as derived from their speed tuning profile. We here show that this complex, non-linear behavior emerges from the combined temporal dynamics of excitation and divisive inhibition, and provide a comprehensive mathematical analysis. A central prediction derived from this investigation is that attention increases the steepness of the transient response irrespective of the activation state prior to a stimulus change, and irrespective of the sign of the change (i.e. irrespective of whether the stimulus is accelerating or decelerating). Extracellular recordings of attention-dependent representation of both speed increments and decrements confirmed this prediction and suggest that improved change detection derives from basic computations in a canonical cortical circuitry.

'Fearful-place' coding in the amygdala-hippocampal network

Animals seeking survival needs must be able to assess different locations of threats in their habitat. However, the neural integration of spatial and risk information essential for guiding goal-directed behavior remains poorly understood. Thus, we investigated simultaneous activities of fear-responsive basal amygdala (BA) and place-responsive dorsal hippocampus (dHPC) neurons as rats left the safe nest to search for food in an exposed space and encountered a simulated 'predator.' In this realistic situation, BA cells increased their firing rates and dHPC place cells decreased their spatial stability near the threat. Importantly, only those dHPC cells synchronized with the predator-responsive BA cells remapped significantly as a function of escalating risk location. Moreover, optogenetic stimulation of BA neurons was sufficient to cause spatial avoidance behavior and disrupt place fields. These results suggest a dynamic interaction of BA's fear signalling cells and dHPC's spatial coding cells as animals traverse safe-danger areas of their environment.

Contrasting effects of exogenous and endogenous attention on size perception

Although neuroimaging studies have shown that exogenous and endogenous attention are dissociable, only a few behavioural studies have explored their differential effects on visual sensitivity, and none have directly focused on visual appearance. Here, we show that exogenous and endogenous attention produces contrasting effects on apparent size. Participants performed a spatial pre-cueing comparative judgement task that had been frequently used to test the attentional effects on visual perception. The results showed that a smaller stimulus within the focus of exogenous attention was perceived to be equal in size as a larger unattended stimulus, whereas a larger stimulus within the focus of endogenous attention was perceived to be equal in size as a smaller unattended stimulus. In other words, exogenous attention increased the perceived size while endogenous attention decreased the perceived size. The contrasting effects may be attributed to the mechanism that exogenous attention favours parvocellular processing for which more neurons with smaller receptive fields (RFs) are activated for a given size, whereas endogenous attention favours magnocellular processing for which fewer neurons with larger RFs are activated. This finding shows that exogenous and endogenous attention acts differentially on size perception, and provides supportive evidence for the distinct mechanisms underlying the two types of attentional processing.

Disparity in Context: Understanding how monocular image content interacts with disparity processing in human visual cortex

Horizontal disparities between the two eyes' retinal images are the primary cue for depth. Commonly used random ot tereograms (RDS) intentionally camouflage the disparity cue, breaking the correlations between monocular image structure and the depth map that are present in natural images. Because of the nonlinear nature of visual processing, it is unlikely that simple computational rules derived from RDS will be sufficient to explain binocular vision in natural environments. In order to understand the interplay between natural scene structure and disparity encoding, we used a depth-image-based-rendering technique and a library of natural 3D stereo pairs to synthesize two novel stereogram types in which monocular scene content was manipulated independent of scene depth information. The half-images of the novel stereograms comprised either random-dots or scrambled natural scenes, each with the same depth maps as the corresponding natural scene stereograms. Using these stereograms in a simultaneous Event-Related Potential and behavioral discrimination task, we identified multiple disparity-contingent encoding stages between 100 ~ 500 msec. The first disparity sensitive evoked potential was observed at ~100 msec after an earlier evoked potential (between ~50-100 msec) that was sensitive to the structure of the monocular half-images but blind to disparity. Starting at ~150 msec, disparity responses were stereogram-specific and predictive of perceptual depth. Complex features associated with natural scene content are thus at least partially coded prior to disparity information, but these features and possibly others associated with natural scene content interact with disparity information only after an intermediate, 2D scene-independent disparity processing stage.

Early recurrence enables figure border ownership

Rubin's face-vase illusion demonstrates how one can switch back and forth between two different interpretations depending on how the figure outlines are assigned. In the primate visual system, assigning ownership along figure borders is encoded by neurons called the border ownership (BO) cells. Studies show that the responses of these neurons not only depend on the local features within their receptive fields, but also on contextual information. Despite two decades of studies on BO neurons, the ownership assignment mechanism in the brain is still unknown. Here, we propose a hierarchical recurrent model grounded on the hypothesis that neurons in the dorsal stream provide the context required for ownership assignment. Our proposed model incorporates early recurrence from the dorsal pathway as well as lateral modulations within the ventral stream. While dorsal modulations initiate the response difference to figure on either side of the border, lateral modulations enhance the difference. We found responses of our dorsally-modulated BO cells, similar to their biological counterparts, are invariant to size, position and solid/outlined figures. Moreover, our model BO cells exhibit comparable levels of reliability in the ownership signal to biological BO neurons. We found dorsal modulations result in high levels of accuracy and robustness for BO assignments in complex scenes compared to previous models based on ventral feedback. Finally, our experiments with illusory contours suggest that BO encoding could explain the perception of such contours in higher processing stages in the brain.

Visual responses in the dorsolateral frontal cortex of marmoset monkeys

The marmoset monkey (Callithrix jacchus) has gained attention in neurophysiology research as a new primate model for visual processing and behavior. In particular, marmosets have a lissencephalic cortex, making multielectrode, optogenetic, and calcium-imaging techniques more accessible than other primate models. However, the degree of homology of brain circuits for visual behavior with those identified in macaques and humans is still being ascertained. For example, whereas the location of the frontal eye fields (FEF) within the dorsolateral frontal cortex has been proposed, it remains unclear whether neurons in the corresponding areas show visual responses-an important characteristic of FEF neurons in other species. Here, we provide the first description of receptive field properties and neural response latencies in the marmoset dorsolateral frontal cortex, based on recordings using Utah arrays in anesthetized animals. We find brisk visual responses in specific regions of the dorsolateral prefrontal cortex, particularly in areas 8aV, 8C, and 6DR. As in macaque FEF, the receptive fields were typically large (10°-30° in diameter) and the median responses latency was brisk (60 ms). These results constrain the possible interpretations about the location of the marmoset FEF and suggest that the marmoset model's significant advantages for the use of physiological techniques may be leveraged in the study of visuomotor cognition.NEW & NOTEWORTHY Behavior and cognition in humans and other primates rely on networks of brain areas guided by the frontal cortex. The marmoset offers exciting new opportunities to study links between brain physiology and behavior, but the functions of frontal cortex areas are still being identified in this species. Here, we provide the first evidence of visual receptive fields in the marmoset dorsolateral frontal cortex, an important step toward future studies of visual cognitive behavior.

Origin of the Time Lag Phenomenon and the Global Signal in Resting-State fMRI

The global mean signal of resting-state fMRI (rs-fMRI) shows a characteristic spatiotemporal pattern that is closely related to the pattern of vascular perfusion. Although being increasingly adopted in the mapping of the flow of neural activity, the mechanism that gives rise to the BOLD signal time lag remains controversial. In the present study, we compared the time lag of the global mean signal with those of the local network components obtained by applying temporal independent component analysis to the resting-state fMRI data, as well as by using simultaneous wide-field visual stimulation, and demonstrated that the time lag patterns are highly similar across all types of data. These results suggest that the time lag of the rs-fMRI signal reflects the local variance of the hemodynamic responses rather than the arrival or transit time of the stimulus, whether the trigger is neuronal or non-neuronal in origin as long as it is mediated by local hemodynamic responses. Examinations of the internal carotid artery signal further confirmed that the arterial signal is tightly inversely coupled with the global mean signal in accordance with previous studies, presumably reflecting the blood flow or blood pressure changes that are occurring almost simultaneously in the internal carotid artery and the cerebral pial/capillary arteries, within the low-frequency component in human rs-fMRI.

Stimulus Feature-Specific Information Flow Along the Columnar Cortical Microcircuit Revealed by Multivariate Laminar Spiking Analysis

Most of the mammalian neocortex is comprised of a highly similar anatomical structure, consisting of a granular cell layer between superficial and deep layers. Even so, different cortical areas process different information. Taken together, this suggests that cortex features a canonical functional microcircuit that supports region-specific information processing. For example, the primate primary visual cortex (V1) combines the two eyes' signals, extracts stimulus orientation, and integrates contextual information such as visual stimulation history. These processes co-occur during the same laminar stimulation sequence that is triggered by the onset of visual stimuli. Yet, we still know little regarding the laminar processing differences that are specific to each of these types of stimulus information. Univariate analysis techniques have provided great insight by examining one electrode at a time or by studying average responses across multiple electrodes. Here we focus on multivariate statistics to examine response patterns across electrodes instead. Specifically, we applied multivariate pattern analysis (MVPA) to linear multielectrode array recordings of laminar spiking responses to decode information regarding the eye-of-origin, stimulus orientation, and stimulus repetition. MVPA differs from conventional univariate approaches in that it examines patterns of neural activity across simultaneously recorded electrode sites. We were curious whether this added dimensionality could reveal neural processes on the population level that are challenging to detect when measuring brain activity without the context of neighboring recording sites. We found that eye-of-origin information was decodable for the entire duration of stimulus presentation, but diminished in the deepest layers of V1. Conversely, orientation information was transient and equally pronounced along all layers. More importantly, using time-resolved MVPA, we were able to evaluate laminar response properties beyond those yielded by univariate analyses. Specifically, we performed a time generalization analysis by training a classifier at one point of the neural response and testing its performance throughout the remaining period of stimulation. Using this technique, we demonstrate repeating (reverberating) patterns of neural activity that have not previously been observed using standard univariate approaches.

A recurrent circuit implements normalization, simulating the dynamics of V1 activity

The normalization model has been applied to explain neural activity in diverse neural systems including primary visual cortex (V1). The model's defining characteristic is that the response of each neuron is divided by a factor that includes a weighted sum of activity of a pool of neurons. Despite the success of the normalization model, there are three unresolved issues. 1) Experimental evidence supports the hypothesis that normalization in V1 operates via recurrent amplification, i.e., amplifying weak inputs more than strong inputs. It is unknown how normalization arises from recurrent amplification. 2) Experiments have demonstrated that normalization is weighted such that each weight specifies how one neuron contributes to another's normalization pool. It is unknown how weighted normalization arises from a recurrent circuit. 3) Neural activity in V1 exhibits complex dynamics, including gamma oscillations, linked to normalization. It is unknown how these dynamics emerge from normalization. Here, a family of recurrent circuit models is reported, each of which comprises coupled neural integrators to implement normalization via recurrent amplification with arbitrary normalization weights, some of which can recapitulate key experimental observations of the dynamics of neural activity in V1.

Modulation of responses to visual stimulus onset and offset by chronic alcohol consumption and withdrawal in the rat visual cortex and lateral geniculate nucleus

In the visual system, chronic alcohol consumption and subsequent abstinence strongly modulate processing of sensory information, which could interfere with the actions in our daily lives. Although previous studies showed histological and electrophysiological changes in the retina and visual cortex during chronic alcohol consumption and abstinence, there is still a lack of information related to the effect of alcohol on: 1) different stages of visual information processing; and 2) responses of stimulus onset (ON) and offset (OFF). In order to answer these questions, we recorded visual evoked potentials (VEPs), elicited by onset and offset of a 500-ms stimulus, following long-term alcohol consumption (8 weeks) and abstinence (3 weeks) in freely moving Wistar rats. Latency and amplitude of five components in the visual cortex (N1_VC, P2_VC, N2_VC, P3_VC, N3_VC) and three components in the lateral geniculate nucleus (P1_LGN, N1_LGN, P2_LGN) were analyzed. The results showed that long-term chronic alcohol consumption and abstinence have a strong long-term and, in some cases, irreversible impact on visual information processing. Both of these conditions modulate only the last stage of stimulus onset processing at the level of the visual cortex, but not at the level of the lateral geniculate body. Response to the stimulus offset is more susceptible to the effect of alcohol consumption and/or abstinence and is modulated at both the visual cortex and lateral geniculate nucleus levels. This modulation at different stages of the information processing chain can result in inaccurate processing of visual stimuli parameters and can lead to changes in perception of stimulus duration and intensity.

Timing of response onset and offset in macaque V4: stimulus and task dependence

In the primate visual cortex, both the magnitude of the neuronal response and its timing can carry important information about the visual world, but studies typically focus only on response magnitude. Here, we examine the onset and offset latency of the responses of neurons in area V4 of awake, behaving macaques across several experiments in the context of a variety of stimuli and task paradigms. Our results highlight distinct contributions of stimuli and tasks to V4 response latency. We found that response onset latencies are shorter than typically cited (median = 75.5 ms), supporting a role for V4 neurons in rapid object and scene recognition functions. Moreover, onset latencies are longer for smaller stimuli and stimulus outlines, consistent with the hypothesis that longer latencies are associated with higher spatial frequency content. Strikingly, we found that onset latencies showed no significant dependence on stimulus occlusion, unlike in inferotemporal cortex, nor on task demands. Across the V4 population, onset latencies had a broad distribution, reflecting the diversity of feedforward, recurrent, and feedback connections that inform the responses of individual neurons. Response offset latencies, on the other hand, displayed the opposite tendency in their relationship to stimulus and task attributes: they are less influenced by stimulus appearance but are shorter in guided saccade tasks compared with fixation tasks. The observation that response latency is influenced by stimulus- and task-associated factors emphasizes a need to examine response timing alongside firing rate in determining the functional role of area V4.NEW & NOTEWORTHY Onset and offset timing of neuronal responses can provide information about visual environment and neuron's role in visual processing and its anatomical connectivity. In the first comprehensive examination of onset and offset latencies in the intermediate visual cortical area V4, we find neurons respond faster than previously reported, making them ideally suited to contribute to rapid object and scene recognition. While response onset reflects stimulus characteristics, timing of response offset is influenced more by behavioral task.

Alpha oscillations and traveling waves: Signatures of predictive coding?

Predictive coding is a key mechanism to understand the computational processes underlying brain functioning: in a hierarchical network, higher levels predict the activity of lower levels, and the unexplained residuals (i.e., prediction errors) are passed back to higher layers. Because of its recursive nature, we wondered whether predictive coding could be related to brain oscillatory dynamics. First, we show that a simple 2-level predictive coding model of visual cortex, with physiological communication delays between levels, naturally gives rise to alpha-band rhythms, similar to experimental observations. Then, we demonstrate that a multilevel version of the same model can explain the occurrence of oscillatory traveling waves across levels, both forward (during visual stimulation) and backward (during rest). Remarkably, the predictions of our model are matched by the analysis of 2 independent electroencephalography (EEG) datasets, in which we observed oscillatory traveling waves in both directions.

Invariant neural responses for sensory categories revealed by the time-varying information for communication calls

Although information theoretic approaches have been used extensively in the analysis of the neural code, they have yet to be used to describe how information is accumulated in time while sensory systems are categorizing dynamic sensory stimuli such as speech sounds or visual objects. Here, we present a novel method to estimate the cumulative information for stimuli or categories. We further define a time-varying categorical information index that, by comparing the information obtained for stimuli versus categories of these same stimuli, quantifies invariant neural representations. We use these methods to investigate the dynamic properties of avian cortical auditory neurons recorded in zebra finches that were listening to a large set of call stimuli sampled from the complete vocal repertoire of this species. We found that the time-varying rates carry 5 times more information than the mean firing rates even in the first 100 ms. We also found that cumulative information has slow time constants (100–600 ms) relative to the typical integration time of single neurons, reflecting the fact that the behaviorally informative features of auditory objects are time-varying sound patterns. When we correlated firing rates and information values, we found that average information correlates with average firing rate but that higher-rates found at the onset response yielded similar information values as the lower-rates found in the sustained response: the onset and sustained response of avian cortical auditory neurons provide similar levels of independent information about call identity and call-type. Finally, our information measures allowed us to rigorously define categorical neurons; these categorical neurons show a high degree of invariance for vocalizations within a call-type. Peak invariance is found around 150 ms after stimulus onset. Surprisingly, call-type invariant neurons were found in both primary and secondary avian auditory areas.

Just as the recognition of faces requires neural representations that are invariant to scale and rotation, the recognition of behaviorally relevant auditory objects, such as spoken words, requires neural representations that are invariant to the speaker uttering the word and to his or her location. Here, we used information theory to investigate the time course of the neural representation of bird communication calls and of behaviorally relevant categories of these same calls: the call-types of the bird’s repertoire. We found that neurons in both the primary and secondary avian auditory cortex exhibit invariant responses to call renditions within a call-type, suggestive of a potential role for extracting the meaning of these communication calls. We also found that time plays an important role: first, neural responses carry significantly more information when represented by temporal patterns calculated at the small time scale of 10 ms than when measured as average rates and, second, this information accumulates in a non-redundant fashion up to long integration times of 600 ms. This rich temporal neural representation is matched to the temporal richness found in the communication calls of this species.

Core Differences in Synaptic Signaling Between Primary Visual and Dorsolateral Prefrontal Cortex

Neurons in primary visual cortex (V1) are more resilient than those in dorsolateral prefrontal cortex (dlPFC) in aging, schizophrenia and Alzheimer’s disease. The current study compared glutamate and neuromodulatory actions in macaque V1 to those in dlPFC, and found striking regional differences. V1 neuronal firing to visual stimuli depended on AMPA receptors, with subtle NMDA receptor contributions, while dlPFC depends primarily on NMDA receptors. Neuromodulatory actions also differed between regions. In V1, cAMP signaling increased neuronal firing, and the phosphodiesterase PDE4A was positioned to regulate cAMP effects on glutamate release from axons. HCN channels in V1 were classically located on distal dendrites, and enhanced cell firing. These data contrast with dlPFC, where PDE4A and HCN channels are concentrated in thin spines, and cAMP-HCN signaling gates inputs and weakens firing. These regional differences may explain why V1 neurons are more resilient than dlPFC neurons to the challenges of age and disease.

Coding of self-motion-induced and self-independent visual motion in the rat dorsomedial striatum

Evolutionary development of vision has provided us with the capacity to detect moving objects. Concordant shifts of visual features suggest movements of the observer, whereas discordant changes are more likely to be indicating independently moving objects, such as predators or prey. Such distinction helps us to focus attention, adapt our behavior, and adjust our motor patterns to meet behavioral challenges. However, the neural basis of distinguishing self-induced and self-independent visual motions is not clarified in unrestrained animals yet. In this study, we investigated the presence and origin of motion-related visual information in the striatum of rats, a hub of action selection and procedural memory. We found that while almost half of the neurons in the dorsomedial striatum are sensitive to visual motion congruent with locomotion (and that many of them also code for spatial location), only a small subset of them are composed of fast-firing interneurons that could also perceive self-independent visual stimuli. These latter cells receive their visual input at least partially from the secondary visual cortex (V2). This differential visual sensitivity may be an important support in adjusting behavior to salient environmental events. It emphasizes the importance of investigating visual motion perception in unrestrained animals.

Saccade-synchronized rapid attention shifts in macaque visual cortical area MT

While making saccadic eye-movements to scan a visual scene, humans and monkeys are able to keep track of relevant visual stimuli by maintaining spatial attention on them. This ability requires a shift of attentional modulation from the neuronal population representing the relevant stimulus pre-saccadically to the one representing it post-saccadically. For optimal performance, this trans-saccadic attention shift should be rapid and saccade-synchronized. Whether this is so is not known. We trained two rhesus monkeys to make saccades while maintaining covert attention at a fixed spatial location. We show that the trans-saccadic attention shift in cortical visual medial temporal (MT) area is well synchronized to saccades. Attentional modulation crosses over from the pre-saccadic to the post-saccadic neuronal representation by about 50 ms after a saccade. Taking response latency into account, the trans-saccadic attention shift is well timed to maintain spatial attention on relevant stimuli, so that they can be optimally tracked and processed across saccades.

Saccades result in remapping the neural representation of a target object as well as its attentional modulation. Here the authors show that the trans-saccadic attentional shift is precisely synchronized with the saccade resulting in optimal maintenance of the locus of spatial attention.

Exploring the spatio-temporal neural basis of face learning

Humans are experts at face individuation. Although previous work has identified a network of face-sensitive regions and some of the temporal signatures of face processing, as yet, we do not have a clear understanding of how such face-sensitive regions support learning at different time points. To study the joint spatio-temporal neural basis of face learning, we trained subjects to categorize two groups of novel faces and recorded their neural responses using magnetoencephalography (MEG) throughout learning. A regression analysis of neural responses in face-sensitive regions against behavioral learning curves revealed significant correlations with learning in the majority of the face-sensitive regions in the face network, mostly between 150-250 ms, but also after 300 ms. However, the effect was smaller in nonventral regions (within the superior temporal areas and prefrontal cortex) than that in the ventral regions (within the inferior occipital gyri (IOG), midfusiform gyri (mFUS) and anterior temporal lobes). A multivariate discriminant analysis also revealed that IOG and mFUS, which showed strong correlation effects with learning, exhibited significant discriminability between the two face categories at different time points both between 150-250 ms and after 300 ms. In contrast, the nonventral face-sensitive regions, where correlation effects with learning were smaller, did exhibit some significant discriminability, but mainly after 300 ms. In sum, our findings indicate that early and recurring temporal components arising from ventral face-sensitive regions are critically involved in learning new faces.

Visual attention is available at a task-relevant location rapidly after a saccade

Maintaining attention at a task-relevant spatial location while making eye-movements necessitates a rapid, saccade-synchronized shift of attentional modulation from the neuronal population representing the task-relevant location before the saccade to the one representing it after the saccade. Currently, the precise time at which spatial attention becomes fully allocated to the task-relevant location after the saccade remains unclear. Using a fine-grained temporal analysis of human peri-saccadic detection performance in an attention task, we show that spatial attention is fully available at the task-relevant location within 30 milliseconds after the saccade. Subjects tracked the attentional target veridically throughout our task: i.e. they almost never responded to non-target stimuli. Spatial attention and saccadic processing therefore co-ordinate well to ensure that relevant locations are attentionally enhanced soon after the beginning of each eye fixation.

DOI:http://dx.doi.org/10.7554/eLife.18009.001

When we look at a scene, our gaze does not move continuously across it. Instead, our eyes move discontinuously, shifting gaze rapidly from point to point to focus on different locations in the scene. These eye movements are known as saccades, and during them the brain temporarily and selectively stops processing visual information.

In the brain, a particular area of a scene is represented by different neurons before and after a saccade. Paying attention to a relevant location in a scene across an eye movement therefore requires the brain to shift its attentional effects from the neurons that represented that location in the scene before the saccade to the set of neurons that do so after the saccade. Ideally, this shift should happen rapidly and be synchronized with the eye movement.

Exactly how long it takes for attention to emerge at a relevant location after a saccade was not clear because attention had not been recorded on a fine enough time-scale immediately after an eye movement. Yao et al. have now addressed this issue in a series of experiments that asked volunteers to focus their eyes on a fixed point. The volunteers had to follow the point with their eyes as it jumped to a new location, and at the same time had to look out for a change in the movement of a pattern of random dots.

The results reveal that attention is fully available at the relevant location within 30 milliseconds after the saccade. In fact, the 30-millisecond delay in the emergence of attention matches the period during which vision is suppressed during a saccade. Thus, the change in the brain’s focus of attention coordinates with the saccadic eye movement to ensure that attention can be fixed on a relevant location as soon as possible after the eye movement ends. More studies are now needed to investigate how the brain coordinates its attention and eye-movement processes to synchronize the shift in attention with the eye movement.

DOI:http://dx.doi.org/10.7554/eLife.18009.002

Information persistence evaluated with low-density dot patterns

After more than a century of study, we do not yet fully understand how shapes and patterns are encoded and identified. Greater progress might result from quantifying stimulus information, thus allowing manipulation of the degree to which a shape or pattern can elicit recognition. The present work used discrete dot patterns that are seen as letters of the alphabet. By adjusting the density of the dots in each pattern, one can determine the probability that it will be recognized. The experiments displayed low-density dot patterns to human respondents, assessing the interval across which non-redundant information provided by two compatible subsets would combine to elicit recognition. This provided a measure of the time required for decay of information persistence. Viewed in the context of prior work, the evidence indicates that the retina mediates initial visibility of the stimulus trace, but the longer-duration persistence required for memory retrieval is mediated by visual cortex.

Masking reduces orientation selectivity in rat visual cortex

In visual masking the perception of a target stimulus is impaired by a preceding (forward) or succeeding (backward) mask stimulus. The illusion is of interest because it allows uncoupling of the physical stimulus, its neuronal representation, and its perception. To understand the neuronal correlates of masking, we examined how masks affected the neuronal responses to oriented target stimuli in the primary visual cortex (V1) of anesthetized rats (n = 37). Target stimuli were circular gratings with 12 orientations; mask stimuli were plaids created as a binarized sum of all possible target orientations. Spatially, masks were presented either overlapping or surrounding the target. Temporally, targets and masks were presented for 33 ms, but the stimulus onset asynchrony (SOA) of their relative appearance was varied. For the first time, we examine how spatially overlapping and center-surround masking affect orientation discriminability (rather than visibility) in V1. Regardless of the spatial or temporal arrangement of stimuli, the greatest reductions in firing rate and orientation selectivity occurred for the shortest SOAs. Interestingly, analyses conducted separately for transient and sustained target response components showed that changes in orientation selectivity do not always coincide with changes in firing rate. Given the near-instantaneous reductions observed in orientation selectivity even when target and mask do not spatially overlap, we suggest that monotonic visual masking is explained by a combination of neural integration and lateral inhibition.

Attentional Gating in Primary Visual Cortex: A Physiological Basis for Dyslexia

The visual magnocellular pathway is known to play a central part in visuospatial attention and in directing attention to specific parts of the visual world in serial search. It is proposed that, in the case of reading, this mechanism is trained to perform a sequential gating of visual information coming into the primary visual cortex to enable further orderly processing by the ventral stream. This scheme, taken together with the potential for plasticity between the different afferent channels in the case of a relative impairment of the magnocellular system, can provide some limited rationale for the beneficial effects that have been claimed for the use of coloured overlays and glasses.

Effects of GABAA kinetics on cortical population activity: computational studies and physiological confirmations

Voltage-sensitive dye (VSD) imaging produces an unprecedented real-time and high-resolution mesoscopic signal to measure the cortical population activity. We have previously shown that the neuronal compartments contributions to the signal are dynamic and stimulus-dependent (Chemla S, Chavane F. Neuroimage 53: 420-438, 2010). Moreover, the VSD signal can also be strongly affected by the network state, such as in anesthetized vs. awake preparations. Here, we investigated the impact of the network state, through GABAA receptors modulation, on the VSD signal using a computational approach. We therefore systematically measured the effect of the GABAA-mediated inhibitory postsynaptic potentials (IPSPs) decay time constant (τG) on our modeled VSD response to an input stimulus of increasing strength. Our simulations suggest that τG strongly modulates the dynamics of the VSD signal, affecting the amplitude, input response function, and the transient balance of excitation and inhibition. We confirmed these predictions experimentally on awake and anesthetized monkeys, comparing VSD responses to drifting gratings stimuli of various contrasts. Lastly, one in vitro study has suggested that GABAA receptors may also be directly affected by the VSDs themselves (Mennerick S, Chisari M, Shu H, Taylor A, Vasek M, Eisenman L, Zorumski C. J Neurosci 30: 2871-2879, 2010). Our modeling approach suggests that the type of modulation described in this study would actually have a negligible influence on the population response. This study highlights that functional results acquired with different techniques and network states must be compared with caution. Biophysical models are proposed here as an adequate tool to delineate the domain of VSD data interpretation.

Covariation between Spike and LFP Modulations Revealed with Focal and Asynchronous Stimulation of Receptive Field Surround in Monkey Primary Visual Cortex

A focal visual stimulus outside the classical receptive field (RF) of a V1 neuron does not evoke a spike response by itself, and yet evokes robust changes in the local field potential (LFP). This subthreshold LFP provides a unique opportunity to investigate how changes induced by surround stimulation leads to modulation of spike activity. In the current study, two identical Gabor stimuli were sequentially presented with a variable stimulus onset asynchrony (SOA) ranging from 0 to 100 ms: the first (S1) outside the RF and the second (S2) over the RF of primary visual cortex neurons, while trained monkeys performed a fixation task. This focal and asynchronous stimulation of the RF surround enabled us to analyze the modulation of S2-evoked spike activity and covariation between spike and LFP modulation across SOA. In this condition, the modulation of S2-evoked spike response was dominantly facilitative and was correlated with the change in LFP amplitude, which was pronounced for the cells recorded in the upper cortical layers. The time course of covariation between the SOA-dependent spike modulation and LFP amplitude suggested that the subthreshold LFP evoked by the S1 can predict the magnitude of upcoming spike modulation.

Dynamics of visual receptive fields in the macaque frontal eye field

Neuronal receptive fields (RFs) provide the foundation for understanding systems-level sensory processing. In early visual areas, investigators have mapped RFs in detail using stochastic stimuli and sophisticated analytical approaches. Much less is known about RFs in prefrontal cortex. Visual stimuli used for mapping RFs in prefrontal cortex tend to cover a small range of spatial and temporal parameters, making it difficult to understand their role in visual processing. To address these shortcomings, we implemented a generalized linear model to measure the RFs of neurons in the macaque frontal eye field (FEF) in response to sparse, full-field stimuli. Our high-resolution, probabilistic approach tracked the evolution of RFs during passive fixation, and we validated our results against conventional measures. We found that FEF neurons exhibited a surprising level of sensitivity to stimuli presented as briefly as 10 ms or to multiple dots presented simultaneously, suggesting that FEF visual responses are more precise than previously appreciated. FEF RF spatial structures were largely maintained over time and between stimulus conditions. Our results demonstrate that the application of probabilistic RF mapping to FEF and similar association areas is an important tool for clarifying the neuronal mechanisms of cognition.

Primary visual cortex represents the difference between past and present

The visual system is confronted with rapidly changing stimuli in everyday life. It is not well understood how information in such a stream of input is updated within the brain. We performed voltage-sensitive dye imaging across the primary visual cortex (V1) to capture responses to sequences of natural scene contours. We presented vertically and horizontally filtered natural images, and their superpositions, at 10 or 33 Hz. At low frequency, the encoding was found to represent not the currently presented images, but differences in orientation between consecutive images. This was in sharp contrast to more rapid sequences for which we found an ongoing representation of current input, consistent with earlier studies. Our finding that for slower image sequences, V1 does no longer report actual features but represents their relative difference in time counteracts the view that the first cortical processing stage must always transfer complete information. Instead, we show its capacities for change detection with a new emphasis on the role of automatic computation evolving in the 100-ms range, inevitably affecting information transmission further downstream.

Comprehensive chronic laminar single-unit, multi-unit, and local field potential recording performance with planar single shank electrode arrays

BACKGROUND

Intracortical electrode arrays that can record extracellular action potentials from small, targeted groups of neurons are critical for basic neuroscience research and emerging clinical applications. In general, these electrode devices suffer from reliability and variability issues, which have led to comparative studies of existing and emerging electrode designs to optimize performance. Comparisons of different chronic recording devices have been limited to single-unit (SU) activity and employed a bulk averaging approach treating brain architecture as homogeneous with respect to electrode distribution.

NEW METHOD

In this study, we optimize the methods and parameters to quantify evoked multi-unit (MU) and local field potential (LFP) recordings in eight mice visual cortices.

RESULTS

These findings quantify the large recording differences stemming from anatomical differences in depth and the layer dependent relative changes to SU and MU recording performance over 6-months. For example, performance metrics in Layer V and stratum pyramidale were initially higher than Layer II/III, but decrease more rapidly. On the other hand, Layer II/III maintained recording metrics longer. In addition, chronic changes at the level of layer IV are evaluated using visually evoked current source density.

COMPARISON WITH EXISTING METHOD(S)

The use of MU and LFP activity for evaluation and tracking biological depth provides a more comprehensive characterization of the electrophysiological performance landscape of microelectrodes.

CONCLUSIONS

A more extensive spatial and temporal insight into the chronic electrophysiological performance over time will help uncover the biological and mechanical failure mechanisms of the neural electrodes and direct future research toward the elucidation of design optimization for specific applications.

Duration estimation entails predicting when

The estimation of duration can be affected by context and surprise. Using MagnetoEncephaloGraphy (MEG), we tested whether increased neural activity during surprise and following neural suppression in two different contexts supported subjective time dilation (Eagleman and Pariyadath, 2009; Pariyadath and Eagleman, 2012). Sequences of three 300 ms frequency-modulated (FM, control) or pure tones (test) were presented and followed by a fourth FM varying in duration. In test, the last FM was perceived as significantly longer than veridical duration (Tse et al., 2004) but did not differ from the perceived duration in control. Several novel and distinct neural signatures were observed in duration estimation: first, neural suppression of standard stimuli was observed for the onset but not for the offset auditory evoked responses. Second, ramping activity increased with veridical duration in control whereas at the same latency in test, the amplitude of the midlatency response increased with the distance of deviant durations. Third, in both conditions, the amplitude of the offset auditory evoked responses accounted well for participants' performance: the longer the perceived duration, the larger the offset response. Fourth, neural duration demarcated by the peak latencies of the onset and ramping evoked activities indexed a systematic time compression that reliably predicted subjective time perception. Our findings suggest that interval timing undergoes time compression by capitalizing on the predicted offset of an auditory event.

ROC-based estimates of neural-behavioral covariations using matched filters

Correlations between responses in visual cortex and perceptual performance help draw a functional link between neural activity and visually guided behavior. These correlations are commonly derived with ROC-based neural-behavioral covariances (referred to as choice or detect probability) using boxcar analysis windows. Although boxcar windows capture the covariation between neural activity and behavior during steady-state stimulus presentations, they are not optimized to capture these correlations during short time-varying visual inputs. In this study, we implemented a matched-filter technique, combined with cross-validation, to improve the estimation of ROC-based neural-behavioral covariance under short and dynamic stimulus conditions. We show that this approach maximizes the area under the ROC curve and converges to the true neural-behavioral covariance using a Poisson spiking model. We also demonstrate that the matched filter, combined with cross-validation, reveals the dynamics of the neural-behavioral covariations of individual MT neurons during the detection of a brief motion stimulus.

The processing of coherent global form and motion patterns without visual awareness

In the present study we addressed whether the processing of global form and motion was dependent on visual awareness. Continuous flash suppression (CFS) was used to suppress from awareness global dot motion (GDM) and Glass pattern stimuli. We quantified the minimum time taken for both pattern types to break suppression with the signal coherence of the pattern (0, 25, 50, and 100% signal) and the type of global structure (rotational, and radial) as independent variables. For both form and motion patterns increasing signal coherence decreased the time required to break suppression. This was the same for both rotational and radial global patterns. However, GDM patterns broke suppression faster than Glass patterns. In a supplementary experiment, we confirmed that this difference in break times is not because of the temporal nature of GDM patterns in attracting attention. In Experiment 2, we examined whether the processing of dynamic Glass patterns were similarly dependent on visual awareness. The processing of dynamic Glass patterns is involves both motion and form systems, and we questioned whether the interaction of these two systems was dependent on visual awareness. The suppression of dynamic Glass patterns was also dependent on signal coherence and the time course of suppression break resembled the detection of global motion and not global form. In Experiment 3 we ruled out the possibility that faster suppression break times was because the visual system is more sensitive to highly coherent form and motion patterns. Here contrast changing GDM and Glass patterns were superimposed on the dynamic CFS mask, and the minimum time required for them to be detected was measured. We showed that there was no difference in detection times for patterns of 0 and 100% coherence. The advantage of highly coherent global motion and form patterns in breaking suppression indicated that the processing and interaction of global motion and form systems occur without visual awareness.

Analog and digital codes in the brain

It has long been debated whether information in the brain is coded at the rate of neuronal spiking or at the precise timing of single spikes. Although this issue is essential to the understanding of neural signal processing, it is not easily resolved because the two mechanisms are not mutually exclusive. We suggest revising this coding issue so that one hypothesis is uniquely selected for a given spike train. To this end, we decide whether the spike train is likely to transmit a continuously varying analog signal or switching between active and inactive states. The coding hypothesis is selected by comparing the likelihood estimates yielded by empirical Bayes and hidden Markov models on individual data. The analysis method is applicable to generic event sequences, such as earthquakes, machine noises, and human communications, and enhances the gain in decoding signals and infers underlying activities.

Mapping the primate lateral geniculate nucleus: a review of experiments and methods

Mapping neuronal responses in the lateral geniculate nucleus (LGN) is key to understanding how visual information is processed in the brain. This paper focuses on our current knowledge of the dynamics the receptive field (RF) as broken down into the classical receptive field (CRF) and the extra-classical receptive field (ECRF) in primate LGN. CRFs in the LGN are known to be similar to those in the retinal ganglion cell layer in terms of both spatial and temporal characteristics, leading to the standard interpretation of the LGN as a relay center from retina to primary visual cortex. ECRFs have generally been found to be large and inhibitory, with some differences in magnitude between the magno-, parvo-, and koniocellular pathways. The specific contributions of the retina, thalamus, and visual cortex to LGN ECRF properties are presently unknown. Some reports suggest a retinal origin for extra-classical suppression based on latency arguments and other reports have suggested a thalamic origin for extra-classical suppression. This issue is complicated by the use of anesthetized animals, where cortical activity is likely to be altered. Thus further study of LGN ECRFs is warranted to reconcile these discrepancies. Producing descriptions of RF properties of LGN neurons could be enhanced by employing preferred naturalistic stimuli. Although there has been significant work in cats with natural scene stimuli and noise that statistically imitates natural scenes, we highlight a need for similar data from primates. Obtaining these data may be aided by recent advancements in experimental and analytical techniques that permit the efficient study of nonlinear RF characteristics in addition to traditional linear factors. In light of the reviewed topics, we conclude by suggesting experiments to more clearly elucidate the spatial and temporal structure of ECRFs of primate LGN neurons.

Parallelism in the brain's visual form system

We used magnetoencephalography (MEG) to determine whether increasingly complex forms constituted from the same elements (lines) activate visual cortex with the same or different latencies. Twenty right-handed healthy adult volunteers viewed two different forms, lines and rhomboids, representing two levels of complexity. Our results showed that the earliest responses produced by lines and rhomboids in both striate and prestriate cortex had similar peak latencies (40 ms) although lines produced stronger responses than rhomboids. Dynamic causal modeling (DCM) showed that a parallel multiple input model to striate and prestriate cortex accounts best for the MEG response data. These results lead us to conclude that the perceptual hierarchy between lines and rhomboids is not mirrored by a temporal hierarchy in latency of activation and thus that a strategy of parallel processing appears to be used to construct forms, without implying that a hierarchical strategy may not be used in separate visual areas, in parallel.

Visual evoked cortical potential (VECP) elicited by sinusoidal gratings controlled by pseudo-random stimulation

The contributions of contrast detection mechanisms to the visual cortical evoked potential (VECP) have been investigated studying the contrast-response and spatial frequency-response functions. Previously, the use of m-sequences for stimulus control has been almost restricted to multifocal electrophysiology stimulation and, in some aspects, it substantially differs from conventional VECPs. Single stimulation with spatial contrast temporally controlled by m-sequences has not been extensively tested or compared to multifocal techniques. Our purpose was to evaluate the influence of spatial frequency and contrast of sinusoidal gratings on the VECP elicited by pseudo-random stimulation. Nine normal subjects were stimulated by achromatic sinusoidal gratings driven by pseudo random binary m-sequence at seven spatial frequencies (0.4–10 cpd) and three stimulus sizes (4°, 8°, and 16° of visual angle). At 8° subtence, six contrast levels were used (3.12–99%). The first order kernel (K1) did not provide a consistent measurable signal across spatial frequencies and contrasts that were tested–signal was very small or absent–while the second order kernel first (K2.1) and second (K2.2) slices exhibited reliable responses for the stimulus range. The main differences between results obtained with the K2.1 and K2.2 were in the contrast gain as measured in the amplitude versus contrast and amplitude versus spatial frequency functions. The results indicated that K2.1 was dominated by M-pathway, but for some stimulus condition some P-pathway contribution could be found, while the second slice reflected the P-pathway contribution. The present work extended previous findings of the visual pathways contribution to VECP elicited by pseudorandom stimulation for a wider range of spatial frequencies.

Estimation of neural firing rate: the wavelet density estimation approach

The computation of neural firing rates based on spike sequences has been introduced as a useful tool for extraction of an animal's behavior. Different estimating methods of such neural firing rates have been developed by neuroscientists, and among these methods, time histogram and kernel estimators have been used more than other approaches. In this paper, the problem in the estimation of firing rates using wavelet density estimators has been considered. The results of simulation study in estimation of underlying rates based on spike sequences sampled from two different variable firing rates show that the proposed wavelet density method provides better and more accurate estimation of firing rates with smooth results compared to two other classical approaches. Furthermore, the performance of a different family of wavelet density estimators in the estimation of the underlying firing rate of biological data have been compared with results of both time histogram and kernel estimators. All in all, the results show that the proposed method can be useful in the estimation of firing rate of neural spike trains.

Mechanism for synchronized motion between two humans in mutual tapping experiments: transition from alternative mode to synchronization mode

We performed mutual tapping experiments between two humans to investigate the conditions required for synchronized motion. A transition from an alternative mode to a synchronization mode was discovered under the same conditions as when a subject changed from a reactive mode to an anticipation mode in single tapping experiments. The experimental results suggest that the cycle time for each tapping motion is tuned by a proportional control that is based on synchronization errors and cycle time errors. As the tapping frequency increases, a mathematical model based on feedback control in the sensory-motor closed loop predicts a discrete transition of the mode as the gain factors of the proportional control decrease. The conditions for synchronization are shown as a consequence of the coupled dynamics based on the next feedback loop in the sensory-motor system.

Estimating nonstationary input signals from a single neuronal spike train

Neurons temporally integrate input signals, translating them into timed output spikes. Because neurons nonperiodically emit spikes, examining spike timing can reveal information about input signals, which are determined by activities in the populations of excitatory and inhibitory presynaptic neurons. Although a number of mathematical methods have been developed to estimate such input parameters as the mean and fluctuation of the input current, these techniques are based on the unrealistic assumption that presynaptic activity is constant over time. Here, we propose tracking temporal variations in input parameters with a two-step analysis method. First, nonstationary firing characteristics comprising the firing rate and non-Poisson irregularity are estimated from a spike train using a computationally feasible state-space algorithm. Then, information about the firing characteristics is converted into likely input parameters over time using a transformation formula, which was constructed by inverting the neuronal forward transformation of the input current to output spikes. By analyzing spike trains recorded in vivo, we found that neuronal input parameters are similar in the primary visual cortex V1 and middle temporal area, whereas parameters in the lateral geniculate nucleus of the thalamus were markedly different.

Representation of motion onset and offset in an augmented Barlow-Levick model of motion detection

Kinetic occlusion produces discontinuities in the optic flow field, whose perception requires the detection of an unexpected onset or offset of otherwise predictably moving or stationary contrast patches. Many cells in primate visual cortex are directionally selective for moving contrasts, and recent reports suggest that this selectivity arises through the inhibition of contrast signals moving in the cells' null direction, as in the rabbit retina. This nulling inhibition circuit (Barlow-Levick) is here extended to also detect motion onsets and offsets. The selectivity of extended circuit units, measured as a peak evidence accumulation response to motion onset/offset compared to the peak response to constant motion, is analyzed as a function of stimulus speed. Model onset cells are quiet during constant motion, but model offset cells activate during constant motion at slow speeds. Consequently, model offset cell speed tuning is biased towards higher speeds than onset cell tuning, similarly to the speed tuning of cells in the middle temporal area when exposed to speed ramps. Given a population of neurons with different preferred speeds, this asymmetry addresses a behavioral paradox-why human subjects in a simple reaction time task respond more slowly to motion offsets than onsets for low speeds, even though monkey neuron firing rates react more quickly to the offset of a preferred stimulus than to its onset.

Diffusive feedback influences on hierarchical information processing

In visual information processing, feedforward projection from primary to secondary visual cortex (V1-to-V2) is essential for integrating combinations of oriented bars in order to extract angular information embedded within contours that represent the shape of objects. For feedback (V2-to-V1) projection, two distinct types of pathways have been observed: clustered projection and diffused projection. The former innervates V1 domains with a preferred orientation similar to that of V2 cells of origin. In contrast, the latter innervates without such orientation specificity. V2 cells send their axons to V1 domains with both similar and dissimilar orientation preferences. It is speculated that the clustered feedback projection has a role in contour integration. The role of the diffused feedback projection, however, remains to be seen. We simulated a minimal, functional V1-V2 neural network model. The diffused feedback projection contributed to achieving ongoing-spontaneous subthreshold membrane oscillations in V1 cells, thereby reducing the reaction time of V1 cells to a pair of bars that represents specific angular information. Interestingly, the feedback influence took place even before V2 responses, which might stem largely from ongoing-spontaneous signaling from V2. We suggest that the diffusive feedback influence from V2 could act early in V1 responses and accelerate their reaction speed to sensory stimulation in order to rapidly extract angular information.