Patches Of Cortex Research Articles

Scene Perception and Visuospatial Memory Converge at the Anterior Edge of Visually Responsive Cortex.

To fluidly engage with the world, our brains must simultaneously represent both the scene in front of us and our memory of the immediate surrounding environment (i.e., local visuospatial context). How does the brain's functional architecture enable sensory and mnemonic representations to closely interface while also avoiding sensory-mnemonic interference? Here, we asked this question using first-person, head-mounted virtual reality and fMRI. Using virtual reality, human participants of both sexes learned a set of immersive, real-world visuospatial environments in which we systematically manipulated the extent of visuospatial context associated with a scene image in memory across three learning conditions, spanning from a single FOV to a city street. We used individualized, within-subject fMRI to determine which brain areas support memory of the visuospatial context associated with a scene during recall (Experiment 1) and recognition (Experiment 2). Across the whole brain, activity in three patches of cortex was modulated by the amount of known visuospatial context, each located immediately anterior to one of the three scene perception areas of high-level visual cortex. Individual subject analyses revealed that these anterior patches corresponded to three functionally defined place memory areas, which selectively respond when visually recalling personally familiar places. In addition to showing activity levels that were modulated by the amount of visuospatial context, multivariate analyses showed that these anterior areas represented the identity of the specific environment being recalled. Together, these results suggest a convergence zone for scene perception and memory of the local visuospatial context at the anterior edge of high-level visual cortex.SIGNIFICANCE STATEMENT As we move through the world, the visual scene around us is integrated with our memory of the wider visuospatial context. Here, we sought to understand how the functional architecture of the brain enables coexisting representations of the current visual scene and memory of the surrounding environment. Using a combination of immersive virtual reality and fMRI, we show that memory of visuospatial context outside the current FOV is represented in a distinct set of brain areas immediately anterior and adjacent to the perceptually oriented scene-selective areas of high-level visual cortex. This functional architecture would allow efficient interaction between immediately adjacent mnemonic and perceptual areas while also minimizing interference between mnemonic and perceptual representations.

Linking histology to post‐mortem 7T MRI measures of neurodegeneration

AbstractBackgroundNeurodegenerative disorders are associated with different pathologies that often co‐occur and have differential contribution to the pattern of cognitive impairment. The majority of these pathologies cannot be detected or measured by in‐vivo methods; therefore, recognition of the topographic patterns of them and association with MRI findings may provide probabilistic non‐invasive biomarkers. We investigated the association of cortical and medial temporal lobe subregional thickness measured from postmortem MRI and semi‐quantitative pathologic measures in order to provide a methodological approach for linking pathological and radiological measures.Method22 brain hemispheres from donors with Alzheimer’s disease (AD) spectrum diagnosis were included. T2‐weighted images were obtained on 7 Tesla scanner (0.28 mm isotropic) and patches of cortex around 16 anatomical locations were segmented using semi‐automated active contour segmentation in ITK‐SNAP. Immunohistochemistry evaluation was performed using previously validated antibodies to detect amyloid‐β, phosphorylated tau, phosphorylated TDP‐43 deposits and pathological conformation of α‐synuclein on contralateral hemispheres. Neuronal loss was visually assessed. Thickness measures at each location were associated with pathology measures at corresponding or closest to corresponding anatomical location. Multivariate linear models were used for statistical analyses.ResultThe mean age of donors at death was 80.2±10.7 years (range 63‐99) and 8 (36%) were female. The median Braak stage was 5 (range: 2‐6). Linear models including regional Tau and TDP43 scores and age showed significant relationships between increased regional tau score and reduced thickness in anterior temporal pole, entorhinal, angular and superior parietal cortices. (Table 1, Figure 1) Linear models including Braak stages, TDP43 scores and age showed significant correlation between Braak stage and thickness in anterior temporal pole and entorhinal cortices and BA35 region of medial temporal lobe.ConclusionThe aim of the current study is to validate methods for development of 3D pathology maps which can be directly linked to local neurodegeneration measures. As the primary result of such an effort, the present study demonstrates an association of semi‐quantitative measures of AD pathology and with local tissue loss in several common AD regions despite limited range of pathology in these cases. These promising results provide support for future studies directly linking pathology with post‐mortem measures of structure.

If perception is probabilistic, why does it not seem probabilistic?

The success of the Bayesian perspective in explaining perceptual phenomena has motivated the view that perceptual representation is probabilistic. But if perceptual representation is probabilistic, why does normal conscious perception not reflect the full probability functions that the probabilistic point of view endorses? For example, neurons in cortical area MT that respond to the direction of motion are broadly tuned: a patch of cortex that is tuned to vertical motion also responds to horizontal motion, but when we see vertical motion, foveally, in good conditions, it does not look at all horizontal. The standard solution in terms of sampling runs into the problem that sampling is an account of perceptual decision rather than perception. This paper argues that the best Bayesian approach to this problem does not require probabilistic representation.This article is part of the theme issue 'Perceptual consciousness and cognitive access'.

Layers of Neuroscience

In a patch of cortex, laminae connect to different parts of the brain. Huber etal. (2017) demonstrate the ability of human neuroimaging to derive laminar information flow between brain regions, paving the way for human neuroscience applications.

Spiking network modeling of neuronal dynamics in individual rats

Many researchers base their neuronal models on experimental data, but few systematically calibrate to it, and even fewer use unpooled data from multiple subjects. Some (partial) exceptions are [1], where one model parameter was calibrated to data pooled across four macaques; and [2], where five model parameters were calibrated to unpooled data from 292 humans. To our knowledge, no one has previously calibrated spiking network models to individual subjects - likely because a single model iteration typically takes considerable computational time, compounded by the formidable number of iterations required to perform optimizations on a statistically meaningful number of subjects. In this study, we calibrate and validate a mesoscopic spiking network model against data from individual rats, then use these fits to infer differences in the rats' physiologies. We recorded data from microelectrode arrays implanted in the somatosensory cortices of nine male rats, each of whom received touch stimuli to his left forepaw. The spiking network models consisted of 20,000 Izhikevich neurons, representing a 2x2 mm patch of cortex sampled at approximately 10% true cell density, with cell types (15 across six layers) and connectivities based on empirical data. We calibrated key model parameters (including connection probability and weight, tonic background activity, and the ratio of thalamic to cortical input) to experimental data (including average firing rates and coefficients of variation) using a nonlinear optimization algorithm [3]. The calibrations were validated using the exponents of the local field potential (LFP) power spectra from 5-50 Hz, which were not used for calibration. Changes in the information processing properties of the (simulated) networks were then quantified via interlaminar Granger causality. Experimentally, we found large differences between subjects. Cortical firing rates varied from 3.8 Hz to 19.6 Hz (median 11.9 Hz); coefficients of variation, 0.4 to 1.2 (median 0.9); and peristimulus time histogram peak amplitudes, 48 Hz to 73 Hz (median 62 Hz). Inter-subject differences were significantly greater than intra-subject differences across both sessions and electrodes. The calibrated models reproduced experimental data with an average mismatch of 16%, compared to 30% when uncalibrated. Experimentally, the LFP power spectra exponents varied from -1.4 to -2.7 (median -2.2). While the models had uniformly steeper exponents (range -2.8 to -3.6), calibration reduced mismatch in eight of the nine subjects. Inter-subject differences could be largely accounted for by differences in average synaptic connection probability (which varied by a mean of 24% between subjects, compared to <8% for other fitted parameters). Parameter differences produced changes in how these networks process information - for example, there were significant and complex differences in the patterns of interlaminar information flow between subjects, including reversals in the dominant direction of information flow for some layer pairs. In summary, we found that (1) significant differences exist between individual subjects, (2) these differences can be captured by calibrating spiking network models to data from each individual, and (3) modeling suggests that these differences affect how individuals process information across cortical layers.

Imaging the Dynamics of Neocortical Population Activity in Behaving and Freely Moving Mammals.

The development of functional imaging techniques applicable to neuroscience and covering a wide range of spatial and temporal scales has greatly facilitated the exploration of the relationships between cognition, behaviour and electrical brain activity. For mammals, the neocortex plays a particularly profound role in generating sensory perception, controlling voluntary movement, higher cognitive functions and planning goal-directed behaviours. Since these remarkable functions of the neocortex cannot be explored in simple model preparations or in anesthetised animals, the neural basis of behaviour must be explored in awake behaving subjects. Because neocortical function is highly distributed across many rapidly interacting regions, it is essential to measure spatiotemporal dynamics of cortical activity in real-time. Extensive work in anesthetised mammals has shown that in vivo Voltage-Sensitive Dye Imaging (VSDI) reveals the neocortical population membrane potential dynamics at millisecond temporal resolution and subcolumnar spatial resolution. Here, we describe recent advances indicating that VSDI is also already well-developed for exploring cortical function in behaving monkeys and mice. The first animal model, the non-human primate, is well-suited for fundamental exploration of higher-level cognitive function and behavior. The second animal model, the mouse, benefits from a rich arsenal of molecular and genetic technologies. In the monkey, imaging from the same patch of cortex, repeatedly, is feasible for a long period of time, up to a year. In the rodent, VSDI is applicable to freely moving and awake head-restrained mice. Interactions between different cortical areas and different cortical columns can therefore now be dynamically mapped through VSDI and related to the corresponding behaviour. Thus by applying VSDI to mice and monkeys one can begin to explore how behaviour emerges from neuronal activity in neuronal networks residing in different cortical areas.

Free concepts association: a neural model

The investigation of complex cognitive functions can not leave aside the study of general collective behaviours generated by the presence of interacting units. In this study we focus on the dynamics underlying a free association between two memories. At the computational level this process can be viewed as a spontaneous jump between attractive configurations of a Potts network, an autoassociative network sketching out the salient features of interacting patches of cortex. In the net each constitutive unit stands for a local patch of cortex. Thus, the connection of these units can be regarded as a global network of local subnetworks. In the system the jump between two memories is elicited by an adaptive process, which weakens the stability of memories representation. The “latching process” so generated results a spontaneous consecutive retrieval of stored memories. Acting on the parameters of the model (such the units connectivity, the number of stored memories, the noise) it is possible to explore a variety of behaviours that goes from a “finite latching” region, in which the system, governed by its relaxation time and the global memories structure, allows only finite sequences of memories retrievals, to an “infinite latching” region, in which this jumping dynamics go on indefinitely.

Multiple scales of organization for object selectivity in ventral visual cortex

Object knowledge is hierarchical. Several hypotheses have proposed that this property might be reflected in the spatial organization of ventral visual cortex. For example, all exemplars of a category might activate the same patches of cortex, but with a slightly different position of the peak of activation in each patch. According to this view, category selectivity would be organized at a larger spatial scale compared to exemplar selectivity. No empirical evidence for such proposals is available from experiments with human subjects. Here, we compare the relative scale of organization for category and exemplar selectivity in two datasets with two methods: (i) by investigating the previously reported beneficial effect of spatial smoothing of the fMRI data on the reliability of multi-voxel selectivity patterns; and (ii) by comparing the relative weight of lower and higher spatial frequencies in the spatial frequency spectrum of these selectivity patterns. The findings are consistent with the proposal that selectivity for stimulus properties that underlie finer distinctions between objects is organized at a finer scale than selectivity for stimulus properties that differentiate categories. This finding confirms the existence of multiple scales of organization in the ventral visual pathway.

Optically quantified cerebral blood flow

In vivo imaging allows detailed studies of cerebral blood flow and brain metabolism in both normal and pathological states. Since the 1980s, several methods to measure tissue perfusion in the brain have been introduced. Magnetic resonance imaging (MRI) techniques such as blood oxygen level dependent MRI (BOLD MRI) (Sorensen et al, 1995) and arterial spin labeling (Buxton and Frank 1997) as well as micro-positron emission tomography (Heiss et al, 1994) have enabled noninvasive chronic imaging of both regional blood flow changes and absolute perfusion in both humans and animal models. These methods, however, suffer from poor spatial resolution and are mainly useful when studying regional blood flow in the brain. Intrinsic optical imaging (Ts'o et al, 1990) enables higher spatial resolution mapping of changes in blood volume. Laser Doppler spectroscopy (Eyre et al, 1988) enables measurement of relative changes in blood flow speeds averaged over ∼1-mm2 cortical areas, while laser speckle contrast imaging (Boas and Dunn, 2010) enables these relative blood flow changes to be imaged with a spatial resolution of <100 μm. None of these optical techniques, however, can accurately resolve changes in flow in individual microvessels or determine the absolute perfusion of cortical tissue. When absolute speed measurement of individual vessels is required, two-photon excited fluorescence (2PEF) microscopy has been the tool of choice (Schaffer et al, 2006). It is, however, limited to measurement of flow speed in vessels that are oriented parallel to the imaging plane, and measurements need to be made one vessel at a time, which is a time-consuming process. Currently lacking is an imaging technique that enables absolute blood flow speed measurements in multiple individual vessels at once. In this issue of JCBFM, Srinivasan et al (2011) introduce the use of Doppler optical coherence tomography (DOCT) (Chen et al, 1997) to fill this gap. Srinivasan et al demonstrated DOCT as a viable technique to quantify blood flow across many individual vessels simultaneously in the brain of live, anesthetized rodents. Doppler optical coherence tomography measures the Doppler shift of light scattered off from moving red blood cells to quantify flow speeds, with three-dimensional spatial resolution obtained from the use of coherence tomography to isolate the signal from a single axial location and laser scanning to map the two lateral dimensions. Using this tool, absolute blood flow velocity can be rapidly determined in blood vessels that contain an axial projection. In their article, Srinivasan et al demonstrated that DOCT measurements of flow speed and vessel cross-sectional area showed conservation of volumetric flow along non-branching and branching vascular segments, confirming the quantitative accuracy of the method. They further demonstrated that DOCT enables straightforward measurement of blood flow speed in penetrating arterioles and ascending venules (the vessels most difficult to characterize with 2PEF), with all these vessels being within an ∼1-mm2 field of view measured in an ∼1-min-long scan (as opposed to 2PEF, which allows measurement of only one vessel every few minutes). To obtain a quantitative estimate of tissue perfusion, the authors summed the volumetric flow from all ascending venules in a patch of cortex and estimated the cortical volume that is served by these vessels. They found strong correlation between this DOCT measurement of tissue perfusion and the values obtained from a standard hydrogen clearance method (von Kummer et al, 1986). The DOCT measurements, however, consistently yielded higher values for tissue perfusion, likely reflecting depressed blood flow due to tissue damage from the electrode used for hydrogen clearance measurements. The DOCT technique was best suited to measurements in the top 150 μm of the brain and in larger blood vessels rather than in capillaries, and the technique is optimal for flow speeds between ∼0.5 and 10 mm/s with current DOCT systems. Overall, the approach of summing the volumetric flow measured by DOCT of all the ascending venules in a patch of cortex appears to provide a robust tool for minimally invasive measurements of absolute brain tissue perfusion with a spatial resolution that is not matched by previous methods, opening the door to studies of how blood flow is altered at the microvascular scale by physiological and pathophysiological events in the brain.

Heterogeneous neuronal firing patterns during interictal epileptiform discharges in the human cortex

Epileptic cortex is characterized by paroxysmal electrical discharges. Analysis of these interictal discharges typically manifests as spike-wave complexes on electroencephalography, and plays a critical role in diagnosing and treating epilepsy. Despite their fundamental importance, little is known about the neurophysiological mechanisms generating these events in human focal epilepsy. Using three different systems of microelectrodes, we recorded local field potentials and single-unit action potentials during interictal discharges in patients with medically intractable focal epilepsy undergoing diagnostic workup for localization of seizure foci. We studied 336 single units in 20 patients. Ten different cortical areas and the hippocampus, including regions both inside and outside the seizure focus, were sampled. In three of these patients, high density microelectrode arrays simultaneously recorded between 43 and 166 single units from a small (4 mm x 4 mm) patch of cortex. We examined how the firing rates of individual neurons changed during interictal discharges by determining whether the firing rate during the event was the same, above or below a median baseline firing rate estimated from interictal discharge-free periods (Kruskal-Wallis one-way analysis, P<0.05). Only 48% of the recorded units showed such a modulation in firing rate within 500 ms of the discharge. Units modulated during the discharge exhibited significantly higher baseline firing and bursting rates than unmodulated units. As expected, many units (27% of the modulated population) showed an increase in firing rate during the fast segment of the discharge (+ or - 35 ms from the peak of the discharge), while 50% showed a decrease during the slow wave. Notably, in direct contrast to predictions based on models of a pure paroxysmal depolarizing shift, 7.7% of modulated units recorded in or near the seizure focus showed a decrease in activity well ahead (0-300 ms) of the discharge onset, while 12.2% of units increased in activity in this period. No such pre-discharge changes were seen in regions well outside the seizure focus. In many recordings there was also a decrease in broadband field potential activity during this same pre-discharge period. The different patterns of interictal discharge-modulated firing were classified into more than 15 different categories. This heterogeneity in single unit activity was present within small cortical regions as well as inside and outside the seizure onset zone, suggesting that interictal epileptiform activity in patients with epilepsy is not a simple paroxysm of hypersynchronous excitatory activity, but rather represents an interplay of multiple distinct neuronal types within complex neuronal networks.

CORTICAL PHASE TRANSITIONS: PROPERTIES DEMONSTRATED IN CONTINUUM SIMULATIONS AT MESOSCOPIC AND MACROSCOPIC SCALES

Continuum simulations of cortical dynamics permit consistent simulations to be performed at different spatial scales, using scale-adjusted parameter values. Properties of the simulations described here accord with Freeman's experimental and theoretical findings on gamma synchrony, phase transition, phase cones, and null spikes. State equations include effects of retrograde action potential propagation into dendritic trees, and kinetics of AMPA, GABA, and NMDA receptors. Realistic field potentials and pulse rates, gamma resonance and oscillation, and 1/f2 background activity are obtained. Zero-lag synchrony and traveling waves occur as complementary aspects of cortical transmission, and lead/lag relations between excitatory and inhibitory cell populations vary systematically around transition to autonomous gamma oscillation. Autonomous gamma is initiated by focal excitation of excitatory cells and suppressed by laterally spreading trans-cortical excitation. By implication, patches of cortex excited to gamma oscillation can mutually synchronize into larger fields, self-organized into sequences by mutual negative feedback relations, while the sequence of synchronous fields is regulated both by cortical/subcortical interactions and by traveling waves in the cortex — the latter observable as phase cones. At a critical level of cortical excitation, just before transition to autonomous gamma, patches of cortex exhibit selective sensitivity to action potential pulse trains modulated in the gamma band, while autonomous gamma releases pulse trains modulated in the same band, implying coupling of input and output modes. Transition between input and output modes may be heralded by phase slips and null spikes. Synaptic segregation by retrograde action potential propagation implies state-specific synaptic information storage.

Patches with links: a unified system for processing faces in the macaque temporal lobe.

The brain processes objects through a series of regions along the ventral visual pathway, but the circuitry subserving the analysis of specific complex forms remains unknown. One complex form category, faces, selectively activates six patches of cortex in the macaque ventral pathway. To identify the connectivity of these face patches, we used electrical microstimulation combined with simultaneous functional magnetic resonance imaging. Stimulation of each of four targeted face patches produced strong activation, specifically within a subset of the other face patches. Stimulation outside the face patches produced an activation pattern that spared the face patches. These results suggest that the face patches form a strongly and specifically interconnected hierarchical network.

Maps of Visual Space in Human Occipital Cortex Are Retinotopic, Not Spatiotopic

We experience the visual world as phenomenally invariant to eye position, but almost all cortical maps of visual space in monkeys use a retinotopic reference frame, that is, the cortical representation of a point in the visual world is different across eye positions. It was recently reported that human cortical area MT (unlike monkey MT) represents stimuli in a reference frame linked to the position of stimuli in space, a "spatiotopic" reference frame. We used visuotopic mapping with blood oxygen level-dependent functional magnetic resonance imaging signals to define 12 human visual cortical areas, and then determined whether the reference frame in each area was spatiotopic or retinotopic. We found that all 12 areas, including MT, represented stimuli in a retinotopic reference frame. Although there were patches of cortex in and around these visual areas that were ostensibly spatiotopic, none of these patches exhibited reliable stimulus-evoked responses. We conclude that the early, visuotopically organized visual cortical areas in the human brain (like their counterparts in the monkey brain) represent stimuli in a retinotopic reference frame.

Is There a Common Origin to Surround-Inhibition as Seen Through Electrical Activity Versus Hemodynamic Changes? Focus on “Duration-Dependent Response in SI to Vibrotactile Stimulation in Squirrel Monkey”

A common aspect of neocortical electrophysiology is that even a brief and spatially localized stimulus leads to activation that both outlives the stimulus and spreads well beyond the patch of cortex that receives direct afferent input. In this issue of the Journal of Neurophysiology , Simons et al

Cortical patch basis model for spatially extended neural activity

A new source model for representing spatially distributed neural activity is presented. The signal of interest is modeled as originating from a patch of cortex and is represented using a set of basis functions. Each cortical patch has its own set of bases, which allows representation of arbitrary source activity within the patch. This is in contrast to previously proposed cortical patch models which assume a specific distribution of activity within the patch. We present a procedure for designing bases that minimize the normalized mean squared representation error, averaged over different activity distributions within the patch. Extension of existing algorithms to the basis function framework is straightforward and is illustrated using linearly constrained minimum variance (LCMV) spatial filtering and maximum-likelihood signal estimation/generalized likelihood ratio test (ML/GLRT). The number of bases chosen for each patch determines a tradeoff between representation accuracy and the ability to differentiate between distinct patches. We propose choosing the minimum number of bases that satisfy a constraint on the normalized mean squared representation accuracy. A mismatch analysis for LCMV and ML/GLRT is presented to show that this is an appropriate strategy for choosing the number of bases. The effectiveness of the patch basis model is demonstrated using real and simulated evoked response data. We show that significant changes in performance occur as the number of basis functions varies, and that very good results are obtained by allowing modest representation error.

Properties of Correlated Neural Activity Clusters in Cat Auditory Cortex Resemble Those of Neural Assemblies

Spiking activity was recorded from cat auditory cortex using multi-electrode arrays. Cross-correlograms were calculated for spikes recorded on separate microelectrodes. The pair-wise cross-correlation matrix was constructed for the peak values of the correlograms. Hierarchical clustering was performed on the cross-correlation matrix for six stimulus conditions. These were silence, three multi-tone stimulus ensembles with different spectral densities, low-pass amplitude-modulated noise, and Poisson-distributed click trains that each lasted 15 min. The resulting neuron clusters reflect patches in cortex of up to several mm(2) in size that expand and contract in response to different stimuli. Cluster positions and size were very similar for spontaneous activity and multi-tone stimulus-evoked activity but differed between those conditions and the noise and click stimuli. Cluster size was significantly larger in posterior auditory field (PAF) compared with primary auditory cortex (AI), whereas the fraction of common spikes (within a 10-ms window) across all electrode activity participating in a cluster was significantly higher in AI compared with PAF. Clusters crossed area boundaries in <5% of the cases were simultaneous recording were made in AI and PAF. Clusters are therefore similar to but not synonymous with the traditional view of neural assemblies. Common-spike spectrotemporal receptive fields (STRFs) were obtained for common-spike activity and all-spike activity within a cluster. Common-spike STRFs had higher signal-to-noise ratio than all-spike STRFs and showed generally spectral and temporal sharpening. The coincident and noncoincident output of the clusters could potentially act in parallel and may serve different modes of stimulus coding.

Immunocytochemical analysis of D‐serine distribution in the mammalian brain reveals novel anatomical compartmentalizations in glia and neurons

D-Serine is a co-agonist at the NMDA receptor glycine-binding site. Early studies have emphasized a glial localization for D-serine. However the nature of the glial cells has not been fully resolved, because previous D-serine antibodies needed glutaraldehyde-fixation, precluding co-localization with fixation-sensitive antigens. We have raised a new D-serine antibody optimized for formaldehyde-fixation. Light and electron microscopic observations indicated that D-serine was concentrated into vesicle-like compartments in astrocytes and radial glial cells, rather than being distributed uniformly in the cytoplasm. In aged animals, patches of cortex and hippocampus were devoid of immunolabeling for D-serine, suggesting that impaired glial modulation of forebrain glutamatergic signaling might occur. Dual immunofluorescence labeling for glutamate and D-serine revealed D-serine in a subset of glutamatergic neurons, particularly in brainstem regions and in the olfactory bulbs. Microglia also contain D-serine. We suggest that some D-serine may be derived from the periphery. Collectively, our data suggest that the cellular compartmentation and distribution of D-serine may be more complex and extensive than previously thought and may have significant implications for our understanding of the role of D-serine in disease states including hypoxia and schizophrenia.

Long-term voltage-sensitive dye imaging reveals cortical dynamics in behaving monkeys.

A novel method of chronic optical imaging based on new voltage-sensitive dyes (VSDs) was developed to facilitate the explorations of the spatial and temporal patterns underlying higher cognitive functions in the neocortex of behaving monkeys. Using this system, we were able to explore cortical dynamics, with high spatial and temporal resolution, over period of <or=1 yr from the same patch of cortex. The visual cortices of trained macaques were stained one to three times a week, and immediately after each staining session, the monkey started to perform the behavioral task, while the primary and secondary visual areas (V1 and V2) were imaged with a fast optical imaging system. Long-term repeated VSD imaging (VSDI) from the same cortical area did not disrupt the normal cortical architecture as confirmed repeatedly by optical imaging based on intrinsic signals. The spatial patterns of functional maps obtained by VSDI were essentially identical to those obtained from the same patch of cortex by imaging based on intrinsic signals. On comparing the relative amplitudes of the evoked signals and differential map obtained using these two different imaging methodologies, we found that VSDI emphasizes subthreshold activity more than imaging based on intrinsic signals, that emphasized more spiking activity. The latency of the VSD-evoked response in V1 ranged from 46 to 68 ms in the different monkeys. The amplitude of the V2 response was only 20-60% of that in V1. As expected from the anatomy, the retinotopic responses to local visual stimuli spread laterally across the cortical surface at a spreading velocity of 0.15-0.19 m/s over a larger area than that expected by the classical magnification factor, reaching its maximal anisotropic spatial extent within approximately 40 ms. We correlated the observed dynamics of cortical activation patterns with the monkey's saccadic eye movements and found that due to the slow offset of the cortical response relative to its onset, there was a short period of simultaneous activation of two distinct patches of cortex following a saccade to the visual stimulus. We also found that a saccade to a small stimulus was followed by direct transient activation of a cortical region in areas of V1 and V2, located retinotopically within the saccadic trajectory.

Long-Term Optical Imaging and Spectroscopy Reveal Mechanisms Underlying the Intrinsic Signal and Stability of Cortical Maps in V1 of Behaving Monkeys

Explorations of learning and memory, other long-term plastic changes, and additional cognitive functions in the behaving primate brain would greatly benefit from the ability to image the functional architecture within the same patch of cortex, at the columnar level, for a long period of time. We developed methods for long-term optical imaging based on intrinsic signals and repeatedly visualized the same functional domains in behaving macaque cortex for a period extending over 1 year. Using optical imaging and imaging spectroscopy, we first explored the relationship between electrical activity and hemodynamic events in the awake behaving primate and compared it with anesthetized preparations. We found that, whereas the amplitude of the intrinsic signal was much larger in the awake animal, its temporal pattern was similar to that observed in the anesthetized animals. In both groups, deoxyhemoglobin concentration reached a peak 2-3 sec after stimulus onset. Furthermore, the early activity-dependent increase in deoxyhemoglobin concentration (the "initial dip") was far more tightly colocalized with electrical activity than the delayed increase in oxyhemoglobin concentration, known to be associated with an increase in blood flow. The implications of these results for improvement of the spatial resolution of blood oxygenation level-dependent functional magnetic resonance imaging are discussed. After the characterization of the intrinsic signal in the behaving primate, we used this new imaging method to explore the stability of cortical maps in the macaque primary visual cortex. Functional maps of orientation and ocular dominance columns were found to be stable for a period longer than 1 year.

Faces, faces everywhere

The importance of faces in social interactions between humans, together with the general physical homogeneity of faces has led to the proposal that face-specific processes may have evolved in the human brain. However, the nature of this specificity is debated: are faces special per se, or does the specificity result from the special requirements of individual face recognition that are needed among social primates? Are ‘face-neurones’ grouped into a defined area of the brain, or are they distributed as discrete patches throughout the visual object-processing pathway? The organization of the ventral temporal cortex with regard to face and object processing has been the subject of recent debate in the literature1,2. With respect to face processing in particular, Allison, McCarthy, Puce and colleagues had previously reported a face-specific N200 component in the evoked potential recorded at the ventral surface of the occipito-temporal cortex. Now, in three recent papers, they investigate further face-specific cortical evoked potentials3–5. Face-specific N200 potentials are found laterally as well as ventrally in the occipito-temporal cortex. Another negative face-specific component is evoked around 700 ms (N700) at sites partially overlapping these ventral and lateral areas. A positive component (P350) is also observed in these areas bilaterally, as well as in the right anterior ventral temporal lobe. The responsiveness of these components to numerous stimuli such as face-parts, animal faces, objects, body-parts, different head views and gaze direction, and to manipulations of face familiarity and semantic priming, suggests that face processing and recognition involves a complex mosaic of anatomically and temporally distributed, and functionally discrete, patches of cortex. As such, face processing appears to be organized only partially according to a posterior-to-anterior sequence of processing stages, and is more distributed in humans than suggested by previous work.