Spikes, BOLD, attention, and awareness: a comparison of electrophysiological and fMRI signals in V1

Disparate nonlinear neural dynamics measured with different techniques in macaque and human V1

Diverse neuro-imaging techniques measure different aspects of neural responses with distinct spatial and temporal resolutions. Relating measured neural responses across different methods has been challenging. Here, we take a step towards overcoming this challenge, by comparing the nonlinearity of neural dynamics measured across methods. We used widefield voltage-sensitive dye imaging (VSDI) to measure neural population responses in macaque V1 to visual stimuli with a wide range of temporal waveforms. We found that stimulus-evoked VSDI responses are surprisingly near-additive in time. These results are qualitatively different from the strong sub-additive dynamics previously measured using fMRI and electrocorticography (ECoG) in human visual cortex with a similar set of stimuli. To test whether this discrepancy is specific to VSDI-a signal dominated by subthreshold neural activity, we repeated our measurements using widefield imaging of a genetically encoded calcium indicator (GcaMP6f)-a signal dominated by spiking activity, and found that GCaMP signals in macaque V1 are also near-additive. Therefore, the discrepancies in the extent of sub-additivity between the macaque and the human measurements are unlikely due to differences between sub- and supra-threshold neural responses. Finally, we use a simple yet flexible delayed normalization model to capture these different dynamics across measurements (with different model parameters). The model can potentially generalize to a broader set of stimuli, which aligns with previous suggestion that dynamic gain-control is a canonical computation contributing to neural processing in the brain.

Optimized microburst VNS elicits fMRI responses beyond thalamic-specific response from standard VNS

OBJECTIVE

In parallel to standard vagus nerve stimulation (VNS), microburst stimulation delivery has been developed. We evaluated the fMRI-related signal changes associated with standard and optimized microburst stimulation in a proof-of-concept study (NCT03446664).

METHODS

Twenty-nine drug-resistant epilepsy patients were prospectively implanted with VNS. Three 3T fMRI scans were collected 2 weeks postimplantation. The maximum tolerated VNS intensity was determined prior to each scan starting at 0.125 mA with 0.125 mA increments. FMRI scans were block-design with alternating 30 sec stimulation [ON] and 30 sec no stimulation [OFF]: Scan 1 utilized standard VNS and Scan 3 optimized microburst parameters to determine target settings. Semi-automated on-site fMRI data processing utilized ON-OFF block modeling to determine VNS-related fMRI activation per stimulation setting. Anatomical thalamic mask was used to derive highest mean thalamic t-value for determination of microburst stimulation parameters. Paired t-tests corrected at P < 0.05 examined differences in fMRI responses to each stimulation type.

RESULTS

Standard and microburst stimulation intensities at Scans 1 and 3 were similar (P = 0.16). Thalamic fMRI responses were obtained in 28 participants (19 with focal; 9 with generalized seizures). Group activation maps showed standard VNS elicited thalamic activation while optimized microburst VNS showed widespread activation patterns including thalamus. Comparison of stimulation types revealed significantly greater cerebellar, midbrain, and parietal fMRI signal changes in microburst compared to standard VNS. These differences were not associated with seizure responses.

INTERPRETATION

While standard and optimized microburst VNS elicited thalamic activation, microburst also engaged other brain regions. Relationship between these fMRI activation patterns and clinical response warrants further investigation.

CLINICAL TRIAL REGISTRATION

The study was registered with clinicaltrials.gov (NCT03446664).

Does V1 response suppression initiate binocular rivalry?

During binocular rivalry (BR) only one eye's view is perceived. Neural underpinnings of BR are debated. Recent studies suggest that primary visual cortex (V1) initiates BR. One trigger might be response suppression across most V1 neurons at the onset of BR. Here, we utilize a variant of BR called binocular rivalry flash suppression (BRFS) to test this hypothesis. BRFS is identical to BR, except stimuli are shown with a ∼1s delay. If V1 response suppression was required to initiate BR, it should occur during BRFS as well. To test this, we compared V1 spiking in two macaques observing BRFS. We found that BRFS resulted in response facilitation rather than response suppression across V1 neurons. However, BRFS still reduces responses in a subset of V1 neurons due to the adaptive effects of asynchronous stimulus presentation. We argue that this selective response suppression could serve as an alternate initiator of BR.

Neurovascular coupling: motive unknown

In the brain, increases in neural activity drive changes in local blood flow via neurovascular coupling. The common explanation for increased blood flow (known as functional hyperemia) is that it supplies the metabolic needs of active neurons. However, there is a large body of evidence that is inconsistent with this idea. Baseline blood flow is adequate to supply oxygen needs even with elevated neural activity. Neurovascular coupling is irregular, absent, or inverted in many brain regions, behavioral states, and conditions. Increases in respiration can increase brain oxygenation without flow changes. Simulations show that given the architecture of the brain vasculature, areas of low blood flow are inescapable and cannot be removed by functional hyperemia. As discussed in this article, potential alternative functions of neurovascular coupling include supplying oxygen for neuromodulator synthesis, brain temperature regulation, signaling to neurons, stabilizing and optimizing the cerebral vascular structure, accommodating the non-Newtonian nature of blood, and driving the production and circulation of cerebrospinal fluid (CSF).

Flexible utilization of spatial- and motor-based codes for the storage of visuo-spatial information

Working memory provides flexible storage of information in service of upcoming behavioral goals. Some models propose specific fixed loci and mechanisms for the storage of visual information in working memory, such as sustained spiking in parietal and prefrontal cortex during working memory maintenance. An alternative view is that information can be remembered in a flexible format that best suits current behavioral goals. For example, remembered visual information might be stored in sensory areas for easier comparison to future sensory inputs, or might be re-coded into a more abstract action-oriented format and stored in motor areas. Here, we tested this hypothesis using a visuo-spatial working memory task where the required behavioral response was either known or unknown during the memory delay period. Using functional magnetic resonance imaging (fMRI) and multivariate decoding, we found that there was less information about remembered spatial position in early visual and parietal regions when the required response was known versus unknown. Furthermore, a representation of the planned motor action emerged in primary somatosensory, primary motor, and premotor cortex during the same task condition where spatial information was reduced in early visual cortex. These results suggest that the neural networks supporting working memory can be strategically reconfigured depending on specific behavioral requirements during a canonical visual working memory paradigm.

Neural Substrates of Visual Perception and Working Memory: Two Sides of the Same Coin or Two Different Coins?

Visual perception occurs when a set of physical signals emanating from the environment enter the visual system and the brain interprets such signals as a percept. Visual working memory occurs when the brain produces and maintains a mental representation of a percept while the physical signals corresponding to that percept are not available. Early studies in humans and non-human primates demonstrated that lesions of the prefrontal cortex impair performance during visual working memory tasks but not during perceptual tasks. These studies attributed a fundamental role in working memory and a lesser role in visual perception to the prefrontal cortex. Indeed, single cell recording studies have found that neurons in the lateral prefrontal cortex of macaques encode working memory representations via persistent firing, validating the results of lesion studies. However, other studies have reported that neurons in some areas of the parietal and temporal lobe-classically associated with visual perception-similarly encode working memory representations via persistent firing. This prompted a line of enquiry about the role of the prefrontal and other associative cortices in working memory and perception. Here, we review evidence from single neuron studies in macaque monkeys examining working memory representations across different areas of the visual hierarchy and link them to studies examining the role of the same areas in visual perception. We conclude that neurons in early visual areas of both ventral (V1-V2-V4) and dorsal (V1-V3-MT) visual pathways of macaques mainly encode perceptual signals. On the other hand, areas downstream from V4 and MT contain subpopulations of neurons that encode both perceptual and/or working memory signals. Differences in cortical architecture (neuronal types, layer composition, and synaptic density and distribution) may be linked to the differential encoding of perceptual and working memory signals between early visual areas and higher association areas.

Population receptive fields in non-human primates from whole-brain fMRI and large-scale neurophysiology in visual cortex

Population receptive field (pRF) modeling is a popular fMRI method to map the retinotopic organization of the human brain. While fMRI-based pRF maps are qualitatively similar to invasively recorded single-cell receptive fields in animals, it remains unclear what neuronal signal they represent. We addressed this question in awake nonhuman primates comparing whole-brain fMRI and large-scale neurophysiological recordings in areas V1 and V4 of the visual cortex. We examined the fits of several pRF models based on the fMRI blood-oxygen-level-dependent (BOLD) signal, multi-unit spiking activity (MUA), and local field potential (LFP) power in different frequency bands. We found that pRFs derived from BOLD-fMRI were most similar to MUA-pRFs in V1 and V4, while pRFs based on LFP gamma power also gave a good approximation. fMRI-based pRFs thus reliably reflect neuronal receptive field properties in the primate brain. In addition to our results in V1 and V4, the whole-brain fMRI measurements revealed retinotopic tuning in many other cortical and subcortical areas with a consistent increase in pRF size with increasing eccentricity, as well as a retinotopically specific deactivation of default mode network nodes similar to previous observations in humans.

Attention differentially modulates multiunit activity in the lateral geniculate nucleus and V1 of macaque monkeys

Attention promotes the selection of behaviorally relevant sensory signals from the barrage of sensory information available. Visual attention modulates the gain of neuronal activity in all visual brain areas examined, although magnitudes of gain modulations vary across areas. For example, attention gain magnitudes in the dorsal lateral geniculate nucleus (LGN) and primary visual cortex (V1) vary tremendously across fMRI measurements in humans and electrophysiological recordings in behaving monkeys. We sought to determine whether these discrepancies are due simply to differences in species or measurement, or more nuanced properties unique to each visual brain area. We also explored whether robust and consistent attention effects, comparable to those measured in humans with fMRI, are observable in the LGN or V1 of monkeys. We measured attentional modulation of multiunit activity in the LGN and V1 of macaque monkeys engaged in a contrast change detection task requiring shifts in covert visual spatial attention. Rigorous analyses of LGN and V1 multiunit activity revealed robust and consistent attentional facilitation throughout V1, with magnitudes comparable to those observed with fMRI. Interestingly, attentional modulation in the LGN was consistently negligible. These findings demonstrate that discrepancies in attention effects are not simply due to species or measurement differences. We also examined whether attention effects correlated with the feature selectivity of recorded multiunits. Distinct relationships suggest that attentional modulation of multiunit activity depends upon the unique structure and function of visual brain areas.

nNOS-expressing interneurons control basal and behaviorally evoked arterial dilation in somatosensory cortex of mice

Cortical neural activity is coupled to local arterial diameter and blood flow. However, which neurons control the dynamics of cerebral arteries is not well understood. We dissected the cellular mechanisms controlling the basal diameter and evoked dilation in cortical arteries in awake, head-fixed mice. Locomotion drove robust arterial dilation, increases in gamma band power in the local field potential (LFP), and increases calcium signals in pyramidal and neuronal nitric oxide synthase (nNOS)-expressing neurons. Chemogenetic or pharmocological modulation of overall neural activity up or down caused corresponding increases or decreases in basal arterial diameter. Modulation of pyramidal neuron activity alone had little effect on basal or evoked arterial dilation, despite pronounced changes in the LFP. Modulation of the activity of nNOS-expressing neurons drove changes in the basal and evoked arterial diameter without corresponding changes in population neural activity.

What do across-subject analyses really tell us about neural coding?

A key challenge in human neuroscience is to gain information about patterns of neural activity using indirect measures. Multivariate pattern analysis methods testing for generalization of information across subjects have been used to support inferences regarding neural coding. One critical assumption of an important class of such methods is that anatomical normalization is suited to align spatially-structured neural patterns across individual brains. We asked whether anatomical normalization is suited for this purpose. If not, what sources of information are such across-subject cross-validated analyses likely to reveal? To investigate these questions, we implemented two-layered feedforward randomly-connected networks. A key feature of these simulations was a gain-field with a spatial structure shared across networks. To investigate whether total-signal imbalances across conditions-e.g. differences in overall activity-affect the observed pattern of results, we manipulated the energy-profile of images conforming to a pre-specified correlation structure. To investigate whether the level of granularity of the data also influences results, we manipulated the density of connections between network layers. Simulations showed that anatomical normalization is unsuited to align neural representations. Pattern similarity-relationships were explained by the observed total-signal imbalances across conditions. Further, we observed that deceptively complex representational structures emerge from arbitrary analysis choices, such as whether the data are mean-subtracted during preprocessing. These simulations also led to testable predictions regarding the distribution of low-level features in images used in recent fMRI studies that relied on leave-one-subject-out pattern analyses. Image analyses broadly confirmed these predictions. Finally, hyperalignment emerged as a principled alternative to test across-subject generalization of spatially-structured information. We illustrate cases in which hyperalignment proved successful, as well as cases in which it only partially recovered the latent correlation structure in the pattern of responses. Our results highlight the need for robust, high-resolution measurements from individual subjects. We also offer a way forward for across-subject analyses. We suggest ways to inform hyperalignment results with estimates of the strength of the signal associated with each condition. Such information can usefully constrain ensuing inferences regarding latent representational structures as well as population tuning dimensions.

Evidence for Hierarchical Cognitive Control in the Human Cerebellum

In non-habitual situations, cognitive control aligns actions with both short- and long-term goals. The capacity for cognitive control is tightly tied to the prefrontal cortex, whose expansion in humans relative to other species is thought to support our superior cognitive control. However, the posterolateral cerebellum has also expanded greatly relative to non-human primates and has an organizational structure that mirrors the prefrontal cortex. Nevertheless, cerebellar contributions to cognitive control are poorly understood. Here, we sought to explore whether a functional hierarchical processing framework, applied to the cerebellum, could elucidate cerebellar contributions to cognitive control. Using functional magnetic resonance imaging, we show that a gradient within the posterolateral cerebellum supports cognitive control with motor-adjacent cerebellar sub-regions supporting control of concrete, proximal actions and motor-distal, cerebellar sub-regions supporting abstract, future processing. This gradient was functionally hierarchical, with regions higher in the hierarchy influencing the relationship between regions lower in the hierarchy. This functional hierarchy provides the infrastructure by which context can inform current actions and prepare for future goals. Crucially, this mirrors the hierarchical organization of cognitive control within the prefrontal cortex. Based on these findings, we propose that the cerebellum contains within itself a parallel but separate hierarchical organization that, along with the prefrontal cortex, supports complex cognition.

Functional MRI and EEG Index Complementary Attentional Modulations

Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are two noninvasive methods commonly used to study neural mechanisms supporting visual attention in humans. Studies using these tools, which have complementary spatial and temporal resolutions, implicitly assume they index similar underlying neural modulations related to external stimulus and internal attentional manipulations. Accordingly, they are often used interchangeably for constraining understanding about the impact of bottom-up and top-down factors on neural modulations. To test this core assumption, we simultaneously manipulated bottom-up sensory inputs by varying stimulus contrast and top-down cognitive modulations by changing the focus of spatial attention. Each of the male and female subjects participated in both fMRI and EEG sessions performing the same experimental paradigm. We found categorically different patterns of attentional modulation on fMRI activity in early visual cortex and early stimulus-evoked potentials measured via EEG (e.g., the P1 component and steady-state visually-evoked potentials): fMRI activation scaled additively with attention, whereas evoked EEG components scaled multiplicatively with attention. However, across longer time scales, a contralateral negative-going potential and oscillatory EEG signals in the alpha band revealed additive attentional modulation patterns like those observed with fMRI. These results challenge prior assumptions that fMRI and early stimulus-evoked potentials measured with EEG can be interchangeably used to index the same neural mechanisms of attentional modulations at different spatiotemporal scales. Instead, fMRI measures of attentional modulations are more closely linked with later EEG components and alpha-band oscillations. Considered together, hemodynamic and electrophysiological signals can jointly constrain understanding of the neural mechanisms supporting cognition.SIGNIFICANCE STATEMENT fMRI and EEG have been used as tools to measure the location and timing of attentional modulations in visual cortex and are often used interchangeably for constraining computational models under the assumption that they index similar underlying neural processes. However, by varying attentional and stimulus parameters, we found differential patterns of attentional modulations of fMRI activity in early visual cortex and commonly used stimulus-evoked potentials measured via EEG. Instead, across longer time scales, a contralateral negative-going potential and EEG oscillations in the alpha band exhibited attentional modulations similar to those observed with fMRI. Together, these results suggest that different physiological processes assayed by these complementary techniques must be jointly considered when making inferences about the neural underpinnings of cognitive operations.

Functional Source Separation for EEG-fMRI Fusion: Application to Steady-State Visual Evoked Potentials

Neurorobotics is one of the most ambitious fields in robotics, driving integration of interdisciplinary data and knowledge. One of the most productive areas of interdisciplinary research in this area has been the implementation of biologically-inspired mechanisms in the development of autonomous systems. Specifically, enabling such systems to display adaptive behavior such as learning from good and bad outcomes, has been achieved by quantifying and understanding the neural mechanisms of the brain networks mediating adaptive behaviors in humans and animals. For example, associative learning from aversive or dangerous outcomes is crucial for an autonomous system, to avoid dangerous situations in the future. A body of neuroscience research has suggested that the neurocomputations in the human brain during associative learning involve re-shaping of sensory responses. The nature of these adaptive changes in sensory processing during learning however are not yet well enough understood to be readily implemented into on-board algorithms for robotics application. Toward this overall goal, we record the simultaneous electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI), characterizing one candidate mechanism, i.e., large-scale brain oscillations. The present report examines the use of Functional Source Separation (FSS) as an optimization step in EEG-fMRI fusion that harnesses timing information to constrain the solutions that satisfy physiological assumptions. We applied this approach to the voxel-wise correlation of steady-state visual evoked potential (ssVEP) amplitude and blood oxygen level-dependent imaging (BOLD), across both time series. The results showed the benefit of FSS for the extraction of robust ssVEP signals during simultaneous EEG-fMRI recordings. Applied to data from a 3-phase aversive conditioning paradigm, the correlation maps across the three phases (habituation, acquisition, extinction) show converging results, notably major overlapping areas in both primary and extended visual cortical regions, including calcarine sulcus, lingual cortex, and cuneus. In addition, during the acquisition phase when aversive learning occurs, we observed additional correlations between ssVEP and BOLD in the anterior cingulate cortex (ACC) as well as the precuneus and superior temporal gyrus.

Neural mechanisms of auditory species recognition in birds

Auditory communication in humans and other animals frequently takes place in noisy environments with many co-occurring signallers. Receivers are thus challenged to rapidly recognize salient auditory signals and filter out irrelevant sounds. Most bird species produce a variety of complex vocalizations that function to communicate with other members of their own species and behavioural evidence broadly supports preferences for conspecific over heterospecific sounds (auditory species recognition). However, it remains unclear whether such auditory signals are categorically recognized by the sensory and central nervous system. Here, we review 53 published studies that compare avian neural responses between conspecific versus heterospecific vocalizations. Irrespective of the techniques used to characterize neural activity, distinct nuclei of the auditory forebrain are consistently shown to be repeatedly conspecific selective across taxa, even in response to unfamiliar individuals with distinct acoustic properties. Yet, species-specific neural discrimination is not a stereotyped auditory response, but is modulated according to its salience depending, for example, on ontogenetic exposure to conspecific versus heterospecific stimuli. Neuromodulators, in particular norepinephrine, may mediate species recognition by regulating the accuracy of neuronal coding for salient conspecific stimuli. Our review lends strong support for neural structures that categorically recognize conspecific signals despite the highly variable physical properties of the stimulus. The available data are in support of a 'perceptual filter'-based mechanism to determine the saliency of the signal, in that species identity and social experience combine to influence the neural processing of species-specific auditory stimuli. Finally, we present hypotheses and their testable predictions, to propose next steps in species-recognition research into the emerging model of the neural conceptual construct in avian auditory recognition.

Two distinct profiles of fMRI and neurophysiological activity elicited by acetylcholine in visual cortex

fMRI changes are typically assumed to be due to changes in neural activity, although whether this remains valid under the influence of neuromodulators is relatively unknown. Here, we found evidence that intracortical acetylcholine elicits distinct profiles of fMRI and electrophysiological activity in visual cortex. Two patterns of cholinergic activity were observed, depending on the distance to the injection site, although neurovascular coupling was preserved. Our results illustrate the effects of neuromodulators on fMRI and electrophysiological responses and show that these depend on neuromodulator concentration and kinetics.

Cholinergic neuromodulation is involved in all aspects of sensory processing and is crucial for processes such as attention, learning and memory, etc. However, despite the known roles of acetylcholine (ACh), we still do not how to disentangle ACh contributions from sensory or task-evoked changes in functional magnetic resonance imaging (fMRI). Here, we investigated the effects of local injection of ACh on fMRI and neural signals in the primary visual cortex (V1) of anesthetized macaques by combining pharmaco-based MRI (phMRI) with electrophysiological recordings, using single electrodes and electrode arrays. We found that local injection of ACh elicited two distinct profiles of fMRI and neurophysiological activity, depending on the distance from the injector. Near the injection site, we observed an increase in the baseline blood oxygen-level-dependent (BOLD) and cerebral blood flow (CBF) responses, while their visual modulation decreased. In contrast, further from the injection site, we observed an increase in the visually induced BOLD and CBF modulation without changes in baseline. Neurophysiological recordings suggest that the spatial correspondence between fMRI responses and neural activity does not change in the gamma, high-gamma, and multiunit activity (MUA) bands. The results near the injection site suggest increased inhibitory drive and decreased metabolism, contrasting to the far region. These changes are thought to reflect the kinetics of ACh and its metabolism to choline.

Contextual-Dependent Attention Effect on Crowded Orientation Signals in Human Visual Cortex

A target becomes hard to identify with nearby visual stimuli. This phenomenon, known as crowding, places a fundamental limit on conscious perception and object recognition. To understand the neural representation of crowded stimuli, we used fMRI and a forward encoding model to reconstruct the target-specific feature from multivoxel activation patterns evoked by orientation patches. Orientation-selective response profiles were constructed in V1-V4 for a target embedded in different contexts. Subjects of both sexes either directed their attention over all the orientation patches or selectively to the target. In the context with a weak crowding effect, attending to the target enhanced the orientation selectivity of the response profile; such effect increased along the visual pathway. In the context with a strong crowding effect, attending to the target enhanced the orientation selectivity of the response profile in the earlier visual area, but not in V4. The increase and decrease of orientation selectivity along the visual hierarchy demonstrate a contextual-dependent attention effect on crowded orientation signals: in the context with a weak crowding effect, selective attention gradually resolves the target from nearby distractors along the hierarchy; in the context with a strong crowding effect, while selective attention maintains the target feature in the earlier visual area, its effect decreases in the downstream area. Our findings reveal how the human visual system represents the target-specific feature at multiple stages under the limit of attention selection in a cluttered scene.SIGNIFICANCE STATEMENT Using fMRI and a forward encoding model, we reconstructed orientation-selective response profiles for a target embedded in crowded contexts. In the context with a weak crowding effect, attention gradually resolves the target from nearby distractors along the visual hierarchy. In the context with a strong crowding effect, while the feature of the target is preserved in the early visual cortex, it degrades in the later visual processing stage. The increase and decrease of orientation selectivity along the visual hierarchy reveal how the human visual system strikes to present the target-specific feature under the limit of attention selection in a cluttered scene.

Human single neuron activity precedes emergence of conscious perception

Identifying the neuronal basis of spontaneous changes in conscious experience in the absence of changes in the external environment is a major challenge. Binocular rivalry, in which two stationary monocular images lead to continuously changing perception, provides a unique opportunity to address this issue. We studied the activity of human single neurons in the medial temporal and frontal lobes while patients were engaged in binocular rivalry. Here we report that internal changes in the content of perception are signaled by very early (~-2000 ms) nonselective medial frontal activity, followed by selective activity of medial temporal lobe neurons that precedes the perceptual change by ~1000 ms. Such early activations are not found for externally driven perceptual changes. These results suggest that a medial fronto-temporal network may be involved in the preconscious internal generation of perceptual transitions.

Binocular response modulation in the lateral geniculate nucleus

The dorsal lateral geniculate nucleus of the thalamus (LGN) receives the main outputs of both eyes and relays those signals to the visual cortex. Each retina projects to separate layers of the LGN so that each LGN neuron is innervated by a single eye. In line with this anatomical separation, visual responses of almost all of LGN neurons are driven by one eye only. Nonetheless, many LGN neurons are sensitive to what is shown to the other eye as their visual responses differ when both eyes are stimulated compared to when the driving eye is stimulated in isolation. This, predominantly suppressive, binocular modulation of LGN responses might suggest that the LGN is the first location in the primary visual pathway where the outputs from the two eyes interact. Indeed, the LGN features several anatomical structures that would allow for LGN neurons responding to one eye to modulate neurons that respond to the other eye. However, it is also possible that binocular response modulation in the LGN arises indirectly as the LGN also receives input from binocular visual structures. Here we review the extant literature on the effects of binocular stimulation on LGN spiking responses, highlighting findings from cats and primates, and evaluate the neural circuits that might mediate binocular response modulation in the LGN.

Building on a Solid Baseline: Anticipatory Biases in Attention

A brain-imaging paper by Kastner and colleagues in 1999 was the first to demonstrate that merely focusing attention at a spatial location changed the baseline activity level in various regions of human visual cortex even before any stimuli appeared. The study provided a touchstone for investigating cognitive–sensory interactions and understanding the proactive endogenous signals that shape perception.

Determining Excitatory and Inhibitory Neuronal Activity from Multimodal fMRI Data Using a Generative Hemodynamic Model

Hemodynamic responses, in general, and the blood oxygenation level-dependent (BOLD) fMRI signal, in particular, provide an indirect measure of neuronal activity. There is strong evidence that the BOLD response correlates well with post-synaptic changes, induced by changes in the excitatory and inhibitory (E-I) balance between active neuronal populations. Typical BOLD responses exhibit transients, such as the early-overshoot and post-stimulus undershoot, that can be linked to transients in neuronal activity, but they can also result from vascular uncoupling between cerebral blood flow (CBF) and venous cerebral blood volume (venous CBV). Recently, we have proposed a novel generative hemodynamic model of the BOLD signal within the dynamic causal modeling framework, inspired by physiological observations, called P-DCM (Havlicek et al., 2015). We demonstrated the generative model's ability to more accurately model commonly observed neuronal and vascular transients in single regions but also effective connectivity between multiple brain areas (Havlicek et al., 2017b). In this paper, we additionally demonstrate the versatility of the generative model to jointly explain dynamic relationships between neuronal and hemodynamic physiological variables underlying the BOLD signal using multi-modal data. For this purpose, we utilized three distinct data-sets of experimentally induced responses in the primary visual areas measured in human, cat, and monkey brain, respectively: (1) CBF and BOLD responses; (2) CBF, total CBV, and BOLD responses (Jin and Kim, 2008); and (3) positive and negative neuronal and BOLD responses (Shmuel et al., 2006). By fitting the generative model to the three multi-modal experimental data-sets, we showed that the presence or absence of dynamic features in the BOLD signal is not an unambiguous indication of presence or absence of those features on the neuronal level. Nevertheless, the generative model that takes into account the dynamics of the physiological mechanisms underlying the BOLD response allowed dissociating neuronal from vascular transients and deducing excitatory and inhibitory neuronal activity time-courses from BOLD data alone and from multi-modal data.

A lateralized top-down network for visuospatial attention and neglect

The lateralization of visuospatial attention has been well investigated and demonstrated to be primarily resulting from unbalanced interaction between interhemispheric fronto-parietal networks in previous studies. Many recent studies of top-down attention have reported the neural signatures of its effects within visual cortex and identified its causal basis. However, the relationship between top-down networks and asymmetric visuospatial attention has not been well studied. In the current study, we aimed to explore the relationship between top-down connectivity and asymmetric visuospatial ability by using repetitive transcranial magnetic stimulation (rTMS) and resting-state functional connectivity (RSFC) analyses. We used rTMS and RSFC to model the virtual lesion to assess the behavioral performances in visuospatial attention shifting and to identify the behavior-related top-down functional connectivities, respectively. Furthermore, we also investigated the top-down connectivity in neglect patients to validate the RSFC findings. RSFC analyses in healthy subjects and neglect patients consistently revealed that asymmetric visuospatial ability and visuospatial neglect were closely related to the bias of top-down functional connectivity between posterior superior parietal lobule (SPL) and V1. Our findings indicate that stronger top-down connectivity has stronger dominance on its corresponding visual field. We argue that an asymmetric top-down network may represent a possible neurophysiological substrate for the ongoing functional asymmetry of visuospatial attention, and its interhemispheric unbalanced interaction could contribute to the clinical manifestations of visuospatial neglect.

Correlated Disruption of Resting-State fMRI, LFP, and Spike Connectivity between Area 3b and S2 following Spinal Cord Injury in Monkeys

This study aims to understand how functional connectivity (FC) between areas 3b and S2 alters following input deprivation and the neuronal basis of disrupted FC of resting-state fMRI signals. We combined submillimeter fMRI with microelectrode recordings to localize the deafferented digit regions in areas 3b and S2 by mapping tactile stimulus-evoked fMRI activations before and after cervical dorsal column lesion in each male monkey. An average afferent disruption of 97% significantly reduced fMRI, local field potential (LFP), and spike responses to stimuli in both areas. Analysis of resting-state fMRI signal correlation, LFP coherence, and spike cross-correlation revealed significantly reduced functional connectivity between deafferented areas 3b and S2. The degrees of reductions in stimulus responsiveness and FC after deafferentation differed across fMRI, LFP, and spiking signals. The reduction of FC was much weaker than that of stimulus-evoked responses. Whereas the largest stimulus-evoked signal drop (∼80%) was observed in LFP signals, the greatest FC reduction was detected in the spiking activity (∼30%). fMRI signals showed mild reductions in stimulus responsiveness (∼25%) and FC (∼20%). The overall deafferentation-induced changes were quite similar in areas 3b and S2 across signals. Here we demonstrated that FC strength between areas 3b and S2 was much weakened by dorsal column lesion, and stimulus response reduction and FC disruption in fMRI covary with those of LFP and spiking signals in deafferented areas 3b and S2. These findings have important implications for fMRI studies aiming to probe FC alterations in pathological conditions involving deafferentation in humans.SIGNIFICANCE STATEMENT By directly comparing fMRI, local field potential, and spike signals in both tactile stimulation and resting states before and after severe disruption of dorsal column afferent, we demonstrated that reduction in fMRI responses to stimuli is accompanied by weakened resting-state fMRI functional connectivity (FC) in input-deprived and reorganized digit regions in area 3b of the S1 and S2. Concurrent reductions in local field potential and spike FC validated the use of resting-state fMRI signals for probing neural intrinsic FC alterations in pathological deafferented cortex, and indicated that disrupted FC between mesoscale functionally highly related regions may contribute to the behavioral impairments.

Studying brain-regulation of immunity with optogenetics and chemogenetics; A new experimental platform

The interactions between the brain and the immune system are bidirectional. Nevertheless, we have far greater understanding of how the immune system affects the brain than how the brain affects immunity. New technological developments such as optogenetics and chemogenetics (using DREADDs; Designer Receptors Exclusively Activated by Designer Drugs) can bridge this gap in our understanding, as they enable an unprecedented mechanistic and systemic analysis of the communication between the brain and the immune system. In this review, we discuss new experimental approaches for revealing neuronal circuits that can participate in regulation of immunity. In addition, we discuss methods, specifically optogenetics and chemogenetics, that enable targeted neuronal manipulation to reveal how different brain regions affect immunity. We describe how these techniques can be used as an experimental platform to address fundamental questions in psychoneuroimmunology and to understand how neuronal circuits associate with different psychological states can affect physiology.

Single neuron recordings of bilinguals performing in a continuous recognition memory task

We report the results of a bilingual continuous recognition memory task during which single- and multi-neuron activity was recorded in human subjects with intracranial microwire implants. Subjects (n = 5) were right-handed Spanish-English bilinguals who were undergoing evaluation prior to surgery for severe epilepsy. Subjects were presented with Spanish and English words and the task was to determine whether any given word had been seen earlier in the testing session, irrespective of the language in which it had appeared. Recordings in the left and right hippocampus revealed notable laterality, whereby both Spanish and English items that had been seen previously in the other language (switch trials) triggered increased neural firing in the left hippocampus. Items that had been seen previously in the same language (repeat trials) triggered increased neural firings in the right hippocampus. These results are consistent with theories that propose roles of both the left- and right-hemisphere in real-time linguistic processing. Importantly, this experiment presents the first instance of intracranial recordings in bilinguals performing a task with switching demands.

Adjudicating between face-coding models with individual-face fMRI responses

The perceptual representation of individual faces is often explained with reference to a norm-based face space. In such spaces, individuals are encoded as vectors where identity is primarily conveyed by direction and distinctiveness by eccentricity. Here we measured human fMRI responses and psychophysical similarity judgments of individual face exemplars, which were generated as realistic 3D animations using a computer-graphics model. We developed and evaluated multiple neurobiologically plausible computational models, each of which predicts a representational distance matrix and a regional-mean activation profile for 24 face stimuli. In the fusiform face area, a face-space coding model with sigmoidal ramp tuning provided a better account of the data than one based on exemplar tuning. However, an image-processing model with weighted banks of Gabor filters performed similarly. Accounting for the data required the inclusion of a measurement-level population averaging mechanism that approximates how fMRI voxels locally average distinct neuronal tunings. Our study demonstrates the importance of comparing multiple models and of modeling the measurement process in computational neuroimaging.

Simultaneously estimating the task-related and stimulus-evoked components of hemodynamic imaging measurements

Task-related hemodynamic responses contribute prominently to functional magnetic resonance imaging (fMRI) recordings. They reflect behaviorally important brain states, such as arousal and attention, and can dominate stimulus-evoked responses, yet they remain poorly understood. To help characterize these responses, we present a method for parametrically estimating both stimulus-evoked and task-related components of hemodynamic responses from subjects engaged in temporally predictable tasks. The stimulus-evoked component is modeled by convolving a hemodynamic response function (HRF) kernel with spiking. The task-related component is modeled by convolving a Fourier-series task-related function (TRF) kernel with task timing. We fit this model with simultaneous electrode recordings and intrinsic-signal optical imaging from the primary visual cortex of alert, task-engaged monkeys. With high [Formula: see text], the model returns HRFs that are consistent across experiments and recording sites for a given animal and TRFs that entrain to task timing independent of stimulation or local spiking. When the task schedule conflicts with that of stimulation, the TRF remains locked to the task emphasizing its behavioral origins. The current approach is strikingly more robust to fluctuations than earlier ones and gives consistently, if modestly, better fits. This approach could help parse the distinct components of fMRI recordings made in the context of a task.

Cortical Representation of Pain and Touch: Evidence from Combined Functional Neuroimaging and Electrophysiology in Non-human Primates

Human functional MRI studies in acute and various chronic pain conditions have revolutionized how we view pain, and have led to a new theory that complex multi-dimensional pain experience (sensory-discriminative, affective/motivational, and cognitive) is represented by concurrent activity in widely-distributed brain regions (termed a network or pain matrix). Despite these breakthrough discoveries, the specific functions proposed for these regions remain elusive, because detailed electrophysiological characterizations of these regions in the primate brain are lacking. To fill in this knowledge gap, we have studied the cortical areas around the central and lateral sulci of the non-human primate brain with combined submillimeter resolution functional imaging (optical imaging and fMRI) and intracranial electrophysiological recording. In this mini-review, I summarize and present data showing that the cortical circuitry engaged in nociceptive processing is much more complex than previously recognized. Electrophysiological evidence supports the engagement of a distinct nociceptive-processing network within SI (i.e., areas 3a, 3b, 1 and 2), SII, and other areas along the lateral sulcus. Deafferentation caused by spinal cord injury profoundly alters the relationships between fMRI and electrophysiological signals. This finding has significant implications for using fMRI to study chronic pain conditions involving deafferentation in humans.

BOLD neurovascular coupling does not change significantly with normal aging

Studies of cognitive function that compare the blood oxygenation level dependent (BOLD) signal across age groups often require the assumption that neurovascular coupling does not change with age. Tests of this assumption have produced mixed results regarding the strength of the coupling and its relative time course. Using deconvolution, we found that age does not have a significant effect on the time course of the hemodynamic impulse response function or on the slope of the BOLD versus stimulus duration relationship. These results suggest that in cognitive studies of healthy aging, group differences in BOLD activation are likely due to age-related changes in cognitive-neural interactions and information processing rather than to impairments in neurovascular coupling. Hum Brain Mapp 38:3538-3551, 2017. © 2017 Wiley Periodicals, Inc.

Contextual modulation of primary visual cortex by auditory signals

Early visual cortex receives non-feedforward input from lateral and top-down connections (Muckli & Petro 2013 Curr. Opin. Neurobiol.23, 195–201. (doi:10.1016/j.conb.2013.01.020)), including long-range projections from auditory areas. Early visual cortex can code for high-level auditory information, with neural patterns representing natural sound stimulation (Vetter et al. 2014 Curr. Biol.24, 1256–1262. (doi:10.1016/j.cub.2014.04.020)). We discuss a number of questions arising from these findings. What is the adaptive function of bimodal representations in visual cortex? What type of information projects from auditory to visual cortex? What are the anatomical constraints of auditory information in V1, for example, periphery versus fovea, superficial versus deep cortical layers? Is there a putative neural mechanism we can infer from human neuroimaging data and recent theoretical accounts of cortex? We also present data showing we can read out high-level auditory information from the activation patterns of early visual cortex even when visual cortex receives simple visual stimulation, suggesting independent channels for visual and auditory signals in V1. We speculate which cellular mechanisms allow V1 to be contextually modulated by auditory input to facilitate perception, cognition and behaviour. Beyond cortical feedback that facilitates perception, we argue that there is also feedback serving counterfactual processing during imagery, dreaming and mind wandering, which is not relevant for immediate perception but for behaviour and cognition over a longer time frame.

This article is part of the themed issue ‘Auditory and visual scene analysis’.

Patterns of Activity in the Human Frontal and Parietal Cortex Differentiate Large and Small Saccades

A vast literature indicates that small and large saccades, respectively, subserve different perceptual and cognitive strategies and may rely on different programming modes. While it is well-established that in monkeys’ main oculomotor brain regions small and large eye movements are controlled by segregated neuronal populations, the representation of saccade amplitude in the human brain remains unclear. To address this question we used functional magnetic resonance imaging to scan participants while they performed saccades toward targets at either short (4°) or large (30°) eccentricity. A regional multivoxel pattern analysis reveals that patterns of activity in the frontal eye-field and parietal eye fields discriminate between the execution of large or small saccades. This was not the case in the supplementary eye-fields nor in the inferior precentral cortex. These findings provide the first evidence of a representation of saccadic eye movement size in the fronto-parietal occulomotor circuit. They shed light on the respective roles of the different cortical oculomotor regions with respect to space perception and exploration, as well as on the homology of eye movement control between human and non-human primates.

Rivalry-Like Neural Activity in Primary Visual Cortex in Anesthetized Monkeys

Two incongruent images viewed by the two eyes cause binocular rivalry, during which observers perceive continuous alternations between these two visual images. Previous studies in both humans and monkeys have shown that the primary visual cortex (V1) plays a critical role in the rivalry perception. However, it is unclear whether the rivalry activity observed in V1 relies on conscious influences. Here, we examine the responses of V1 in monkeys under general anesthesia. With intrinsic signal optical imaging and single-trial analysis, alternating activation of ocular dominance columns in V1 was observed during binocularly incongruent stimulation. Left- and right-eye columns exhibited counterphase activation, which were modulated by stimulus features in ways similar to those found in conscious human observers. These observations indicated that binocular rivalry occurs in V1 without consciousness, suggesting that the low-level automatic mechanisms play a more important role than previously believed in handling visual ambiguities.

SIGNIFICANCE STATEMENT

When visual input is ambiguous, for example, in viewing bistable images, human subjects normally perceive one of the interpretations at a particular moment. Previous studies have shown that both low-level visual processing and high-level attention contribute to the establishment of the final visual perception. However, it is not clear whether attention is indispensable in such a process. Here we show that rivalry-like neural activity persisted in monkey V1 when the monkeys were anesthetized and viewed binocularly incongruent stimuli. Such activity has many key features similar to those observed in conscious human subjects. These findings indicate that low-level visual processes play a critical role in solving visual ambiguity such as binocular rivalry.

Non-human Primates in Neuroscience Research: The Case against its Scientific Necessity

Public opposition to non-human primate (NHP) experiments is significant, yet those who defend them cite minimal harm to NHPs and substantial human benefit. Here we review these claims of benefit, specifically in neuroscience, and show that: a) there is a default assumption of their human relevance and benefit, rather than robust evidence; b) their human relevance and essential contribution and necessity are wholly overstated; c) the contribution and capacity of non-animal investigative methods are greatly understated; and d) confounding issues, such as species differences and the effects of stress and anaesthesia, are usually overlooked. This is the case in NHP research generally, but here we specifically focus on the development and interpretation of functional magnetic resonance imaging (fMRI), deep brain stimulation (DBS), the understanding of neural oscillations and memory, and investigation of the neural control of movement and of vision/binocular rivalry. The increasing power of human-specific methods, including advances in fMRI and invasive techniques such as electrocorticography and single-unit recordings, is discussed. These methods serve to render NHP approaches redundant. We conclude that the defence of NHP use is groundless, and that neuroscience would be more relevant and successful for humans, if it were conducted with a direct human focus. We have confidence in opposing NHP neuroscience, both on scientific as well as on ethical grounds.

Gender differences in human single neuron responses to male emotional faces

Well-documented differences in the psychology and behavior of men and women have spurred extensive exploration of gender's role within the brain, particularly regarding emotional processing. While neuroanatomical studies clearly show differences between the sexes, the functional effects of these differences are less understood. Neuroimaging studies have shown inconsistent locations and magnitudes of gender differences in brain hemodynamic responses to emotion. To better understand the neurophysiology of these gender differences, we analyzed recordings of single neuron activity in the human brain as subjects of both genders viewed emotional expressions. This study included recordings of single-neuron activity of 14 (6 male) epileptic patients in four brain areas: amygdala (236 neurons), hippocampus (n = 270), anterior cingulate cortex (n = 256), and ventromedial prefrontal cortex (n = 174). Neural activity was recorded while participants viewed a series of avatar male faces portraying positive, negative or neutral expressions. Significant gender differences were found in the left amygdala, where 23% (n = 15∕66) of neurons in men were significantly affected by facial emotion, vs. 8% (n = 6∕76) of neurons in women. A Fisher's exact test comparing the two ratios found a highly significant difference between the two (p < 0.01). These results show specific differences between genders at the single-neuron level in the human amygdala. These differences may reflect gender-based distinctions in evolved capacities for emotional processing and also demonstrate the importance of including subject gender as an independent factor in future studies of emotional processing by single neurons in the human amygdala.

Implications of cortical balanced excitation and inhibition, functional heterogeneity, and sparseness of neuronal activity in fMRI

Blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies often report inconsistent findings, probably due to brain properties such as balanced excitation and inhibition and functional heterogeneity. These properties indicate that different neurons in the same voxels may show variable activities including concurrent activation and deactivation, that the relationships between BOLD signal and neural activity (i.e., neurovascular coupling) are complex, and that increased BOLD signal may reflect reduced deactivation, increased activation, or both. The traditional general-linear-model-based-analysis (GLM-BA) is a univariate approach, cannot separate different components of BOLD signal mixtures from the same voxels, and may contribute to inconsistent findings of fMRI. Spatial independent component analysis (sICA) is a multivariate approach, can separate the BOLD signal mixture from each voxel into different source signals and measure each separately, and thus may reconcile previous conflicting findings generated by GLM-BA. We propose that methods capable of separating mixed signals such as sICA should be regularly used for more accurately and completely extracting information embedded in fMRI datasets.

Reward modulates the effect of visual cortical microstimulation on perceptual decisions

Effective perceptual decisions rely upon combining sensory information with knowledge of the rewards available for different choices. However, it is not known where reward signals interact with the multiple stages of the perceptual decision-making pathway and by what mechanisms this may occur. We combined electrical microstimulation of functionally specific groups of neurons in visual area V5/MT with performance-contingent reward manipulation, while monkeys performed a visual discrimination task. Microstimulation was less effective in shifting perceptual choices towards the stimulus preferences of the stimulated neurons when available reward was larger. Psychophysical control experiments showed this result was not explained by a selective change in response strategy on microstimulated trials. A bounded accumulation decision model, applied to analyse behavioural performance, revealed that the interaction of expected reward with microstimulation can be explained if expected reward modulates a sensory representation stage of perceptual decision-making, in addition to the better-known effects at the integration stage.

DOI:http://dx.doi.org/10.7554/eLife.07832.001

Identifying how an object is moving in three-dimensional (3D) space depends upon a brain region known as V5/MT. The neurons that make up area V5/MT form groups that each have a ‘preference’ for a particular direction of movement and a particular 3D depth. If a group of neurons detects its preferred direction of movement and 3D depth, it will become highly active. The brain can assess which groups of neurons are active, in a process known as integration. This information can then be used to work out the object's movement in space.

The process of integration can be influenced by whether a rewarding outcome is expected to result from identifying the 3D movement correctly. This allows the brain to increase its likelihood of success in situations where a large reward is on offer. Until now, it was thought that the activity in area V5/MT, which takes place before integration, was not affected by the likelihood of receiving a reward.

As well as being ‘naturally’ stimulated by moving objects, the V5/MT neurons can also be ‘artificially’ activated by a technique called microstimulation, which uses a tiny electrode to electrically stimulate groups of neurons. Microstimulation can bias visual perception towards the movement and 3D depth ‘preference’ of the artificially activated neurons. If the V5/MT neurons do receive information about potential rewards from other areas of the brain, we would expect rewards to affect naturally and artificially stimulated neural activity in different ways. On the other hand, if the V5/MT neurons do not receive any information about reward, then it will not matter whether their activity is natural or artificial; the signal that they produce will be the same.

Cicmil et al. gave two monkeys a task in which they could receive rewards for correctly identifying a three-dimensional cylinder's direction of rotation, and applied microstimulation to specific groups of V5/MT neurons on some of the trials. When a larger reward was available, microstimulation was less able to bias the monkeys' choices about the rotation direction of the 3D cylinders.

Overall, Cicmil et al.'s results suggest that the V5/MT neurons are able to incorporate information about reward, before integration occurs. The next step will be to record the activity of area V5/MT to investigate exactly how this happens.

DOI:http://dx.doi.org/10.7554/eLife.07832.002

Parietal and Frontal Cortex Encode Stimulus-Specific Mnemonic Representations during Visual Working Memory

Working memory (WM) enables the storage and manipulation of information in an active state. WM storage has long been associated with sustained increases in activation across a network of frontal and parietal cortical regions. However, recent evidence suggests that these regions primarily encode information related to general task goals rather than feature-selective representations of specific memoranda. These goal-related representations are thought to provide top-down feedback that coordinates the representation of fine-grained details in early sensory areas. Here, we test this model using fMRI-based reconstructions of remembered visual details from region-level activation patterns. We could reconstruct high-fidelity representations of a remembered orientation based on activation patterns in occipital visual cortex and in several sub-regions of frontal and parietal cortex, independent of sustained increases in mean activation. These results challenge models of WM that postulate disjoint frontoparietal "top-down control" and posterior sensory "feature storage" networks.

Corresponding ECoG and fMRI category-selective signals in human ventral temporal cortex

Functional magnetic resonance imaging (fMRI) and electrocorticography (ECoG) research have been influential in revealing the functional characteristics of category-selective responses in human ventral temporal cortex (VTC). One important, but unanswered, question is how these two types of measurements might be related with respect to the VTC. Here we examined which components of the ECoG signal correspond to the fMRI response by using a rare opportunity to measure both fMRI and ECoG responses from the same individuals to images of exemplars of various categories including faces, limbs, cars and houses. Our data reveal three key findings. First, we discovered that the coupling between fMRI and ECoG responses is frequency and time dependent. The strongest and most sustained correlation is observed between fMRI and high frequency broadband (HFB) ECoG responses (30-160 hz). In contrast, the correlation between fMRI and ECoG signals in lower frequency bands is temporally transient, where the correlation is initially positive, but then tapers off or becomes negative. Second, we find that the strong and positive correlation between fMRI and ECoG signals in all frequency bands emerges rapidly around 100 ms after stimulus onset, together with the onset of the first stimulus-driven neural signals in VTC. Third, we find that the spatial topology and representational structure of category-selectivity in VTC reflected in ECoG HFB responses mirrors the topology and structure observed with fMRI. These findings of a strong and rapid coupling between fMRI and HFB responses validate fMRI measurements of functional selectivity with recordings of direct neural activity and suggest that fMRI category-selective signals in VTC are associated with feed-forward neural processing.

A case for human systems neuroscience

Can the human brain itself serve as a model for a systems neuroscience approach to understanding the human brain? After all, how the brain is able to create the richness and complexity of human behavior is still largely mysterious. What better choice to study that complexity than to study it in humans? However, measurements of brain activity typically need to be made non-invasively which puts severe constraints on what can be learned about the internal workings of the brain. Our approach has been to use a combination of psychophysics in which we can use human behavioral flexibility to make quantitative measurements of behavior and link those through computational models to measurements of cortical activity through magnetic resonance imaging. In particular, we have tested various computational hypotheses about what neural mechanisms could account for behavioral enhancement with spatial attention (Pestilli et al., 2011). Resting both on quantitative measurements and considerations of what is known through animal models, we concluded that weighting of sensory signals by the magnitude of their response is a neural mechanism for efficient selection of sensory signals and consequent improvements in behavioral performance with attention. While animal models have many technical advantages over studying the brain in humans, we believe that human systems neuroscience should endeavor to validate, replicate and extend basic knowledge learned from animal model systems and thus form a bridge to understanding how the brain creates the complex and rich cognitive capacities of humans.

Modeling fMRI signals can provide insights into neural processing in the cerebral cortex

Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals.

Feedback to distal dendrites links fMRI signals to neural receptive fields in a spiking network model of the visual cortex

The blood oxygenation level-dependent (BOLD) response has been strongly associated with neuronal activity in the brain. However, some neuronal tuning properties are consistently different from the BOLD response. We studied the spatial extent of neural and hemodynamic responses in the primary visual cortex, where the BOLD responses spread and interact over much longer distances than the small receptive fields of individual neurons would predict. Our model shows that a feedforward-feedback loop between V1 and a higher visual area can account for the observed spread of the BOLD response. In particular, anisotropic landing of inputs to compartmental neurons were necessary to account for the BOLD signal spread, while retaining realistic spiking responses. Our work shows that simple dendrites can separate tuning at the synapses and at the action potential output, thus bridging the BOLD signal to the neural receptive fields with high fidelity.

Attention reduces spatial uncertainty in human ventral temporal cortex

Ventral temporal cortex (VTC) is the latest stage of the ventral "what" visual pathway, which is thought to code the identity of a stimulus regardless of its position or size [1, 2]. Surprisingly, recent studies show that position information can be decoded from VTC [3-5]. However, the computational mechanisms by which spatial information is encoded in VTC are unknown. Furthermore, how attention influences spatial representations in human VTC is also unknown because the effect of attention on spatial representations has only been examined in the dorsal "where" visual pathway [6-10]. Here, we fill these significant gaps in knowledge using an approach that combines functional magnetic resonance imaging and sophisticated computational methods. We first develop a population receptive field (pRF) model [11, 12] of spatial responses in human VTC. Consisting of spatial summation followed by a compressive nonlinearity, this model accurately predicts responses of individual voxels to stimuli at any position and size, explains how spatial information is encoded, and reveals a functional hierarchy in VTC. We then manipulate attention and use our model to decipher the effects of attention. We find that attention to the stimulus systematically and selectively modulates responses in VTC, but not early visual areas. Locally, attention increases eccentricity, size, and gain of individual pRFs, thereby increasing position tolerance. However, globally, these effects reduce uncertainty regarding stimulus location and actually increase position sensitivity of distributed responses across VTC. These results demonstrate that attention actively shapes and enhances spatial representations in the ventral visual pathway.

To see or not to see--thalamo-cortical networks during blindsight and perceptual suppression

Even during moments when we fail to be fully aware of our environment, our brains never go silent. Instead, it appears that the brain can also operate in an alternate, unconscious mode. Delineating unconscious from conscious neural processes is a promising first step toward investigating how awareness emerges from brain activity. Here we focus on recent insights into the neuronal processes that contribute to visual function in the absence of a conscious visual percept. Drawing on insights from findings on the phenomenon of blindsight that results from injury to primary visual cortex and the results of experimentally induced perceptual suppression, we describe what kind of visual information the visual system analyzes unconsciously and we discuss the neuronal routing and responses that accompany this process. We conclude that unconscious processing of certain visual stimulus attributes, such as the presence of visual motion or the emotional expression of a face can occur in a geniculo-cortical circuit that runs independent from and in parallel to the predominant route through primary visual cortex. We speculate that in contrast, bidirectional neuronal interactions between cortex and the thalamic pulvinar nucleus that support large-scale neuronal integration and visual awareness are impeded during blindsight and perceptual suppression.

Stimulus-related neuroimaging in task-engaged subjects is best predicted by concurrent spiking

The implicit goal of functional magnetic resonance imaging is to infer local neural activity. There is considerable debate, however, as to whether imaging correlates most linearly with local spiking or some local field potential (LFP) measurement. Through simultaneous neuroimaging (intrinsic-signal optical imaging) and electrode recordings from alert, task-engaged macaque monkeys, we showed previously that local electrophysiology correlates with only a specific stimulus-related imaging component. Here we show that this stimulus-related component--obtained by subtracting a substantial task-related component--is particularly linear with local spiking over a comprehensive range of response strengths. Matches to concurrent LFP measurements are, to varying degrees, poorer. As a control, we also tried matching the full imaging signal to local electrophysiology without subtracting task-related components. These control matches were consistently worse; they were, however, slightly better for gamma LFP than spiking, potentially resolving discrepancies between our findings and earlier reports favoring LFP.

Featural and temporal attention selectively enhance task-appropriate representations in human primary visual cortex

Our perceptions are often shaped by focusing our attention towards specific features or periods of time irrespective of location. Here we explore the physiological bases of these non-spatial forms of attention by imaging brain activity while subjects perform a challenging change-detection task. The task employs a continuously varying visual stimulus that, for any moment in time, selectively activates functionally distinct subpopulations of primary visual cortex (V1) neurons. When subjects are cued to the timing and nature of the change, the mapping of orientation preference across V1 systematically shifts towards the cued stimulus just prior to its appearance. A simple linear model can explain this shift: attentional changes are selectively targeted towards neural subpopulations, representing the attended feature at the times the feature was anticipated. Our results suggest that featural attention is mediated by a linear change in the responses of task-appropriate neurons across cortex during appropriate periods of time.

On the role of suppression in spatial attention: evidence from negative BOLD in human subcortical and cortical structures

There is clear evidence that spatial attention increases neural responses to attended stimuli in extrastriate visual areas and, to a lesser degree, in earlier visual areas. Other evidence shows that neurons representing unattended locations can also be suppressed. However, the extent to which enhancement and suppression is observed, their stimulus dependence, and the stages of the visual system at which they are expressed remains poorly understood. Using fMRI we set out to characterize both the task and stimulus dependence of neural responses in the lateral geniculate nucleus (LGN), primary visual cortex (V1), and visual motion area (V5) in humans to determine where suppressive and facilitatory effects of spatial attention are expressed. Subjects viewed a lateralized drifting grating stimulus, presented at multiple stimulus contrasts, and performed one of three tasks designed to alter the spatial location of their attention. In retinotopic representations of the stimulus location, we observed increasing attention-dependent facilitation and decreasing dependence on stimulus contrast moving up the visual hierarchy from the LGN to V5. However, in the representations of unattended locations of the LGN and V1, we observed suppression, which was not significantly dependent on the attended stimulus contrast. These suppressive effects were also found in the pulvinar, which has been frequently associated with attention. We provide evidence, therefore, for a spatially selective suppressive mechanism that acts at a subcortical level.

Encoding of graded changes in spatial specificity of prior cues in human visual cortex

Prior information about the relevance of spatial locations can vary in specificity; a single location, a subset of locations, or all locations may be of potential importance. Using a contrast-discrimination task with four possible targets, we asked whether performance benefits are graded with the spatial specificity of a prior cue and whether we could quantitatively account for behavioral performance with cortical activity changes measured by blood oxygenation level-dependent (BOLD) imaging. Thus we changed the prior probability that each location contained the target from 100 to 50 to 25% by cueing in advance 1, 2, or 4 of the possible locations. We found that behavioral performance (discrimination thresholds) improved in a graded fashion with spatial specificity. However, concurrently measured cortical responses from retinotopically defined visual areas were not strictly graded; response magnitude decreased when all 4 locations were cued (25% prior probability) relative to the 100 and 50% prior probability conditions, but no significant difference in response magnitude was found between the 100 and 50% prior probability conditions for either cued or uncued locations. Also, although cueing locations increased responses relative to noncueing, this cue sensitivity was not graded with prior probability. Furthermore, contrast sensitivity of cortical responses, which could improve contrast discrimination performance, was not graded. Instead, an efficient-selection model showed that even if sensory responses do not strictly scale with prior probability, selection of sensory responses by weighting larger responses more can result in graded behavioral performance benefits with increasing spatial specificity of prior information.

Microcircuitry of agranular frontal cortex: testing the generality of the canonical cortical microcircuit

We investigated whether a frontal area that lacks granular layer IV, supplementary eye field, exhibits features of laminar circuitry similar to those observed in primary sensory areas. We report, for the first time, visually evoked local field potentials (LFPs) and spiking activity recorded simultaneously across all layers of agranular frontal cortex using linear electrode arrays. We calculated current source density from the LFPs and compared the laminar organization of evolving sinks to those reported in sensory areas. Simultaneous, transient synaptic current sinks appeared first in layers III and V followed by more prolonged current sinks in layers I/II and VI. We also found no variation of single- or multi-unit visual response latency across layers, and putative pyramidal neurons and interneurons displayed similar response latencies. Many units exhibited pronounced discharge suppression that was strongest in superficial relative to deep layers. Maximum discharge suppression also occurred later in superficial than in deep layers. These results are discussed in the context of the canonical cortical microcircuit model originally formulated to describe early sensory cortex. The data indicate that agranular cortex resembles sensory areas in certain respects, but the cortical microcircuit is modified in nontrivial ways.