Division of labor in frontal eye field neurons during presaccadic remapping of visual receptive fields.

Our percept of visual stability across saccadic eye movements may be mediated by presaccadic remapping. Just before a saccade, neurons that remap become visually responsive at a future field (FF), which anticipates the saccade vector. Hence, the neurons use corollary discharge of saccades. Many of the neurons also decrease their response at the receptive field (RF). Presaccadic remapping occurs in several brain areas including the frontal eye field (FEF), which receives corollary discharge of saccades in its layer IV from a collicular-thalamic pathway. We studied, at two levels, the microcircuitry of remapping in the FEF. At the laminar level, we compared remapping between layers IV and V. At the cellular level, we compared remapping between different neuron types of layer IV. In the FEF in four monkeys (Macaca mulatta), we identified 27 layer IV neurons with orthodromic stimulation and 57 layer V neurons with antidromic stimulation from the superior colliculus. With the use of established criteria, we classified the layer IV neurons as putative excitatory (n = 11), putative inhibitory (n = 12), or ambiguous (n = 4). We found that just before a saccade, putative excitatory neurons increased their visual response at the RF, putative inhibitory neurons showed no change, and ambiguous neurons increased their visual response at the FF. None of the neurons showed presaccadic visual changes at both RF and FF. In contrast, neurons in layer V showed full remapping (at both the RF and FF). Our data suggest that elemental signals for remapping are distributed across neuron types in early cortical processing and combined in later stages of cortical microcircuitry.

Spatial and temporal scales of neuronal correlation in visual area V4.

The spiking activity of nearby cortical neurons is correlated on both short and long time scales. Understanding this shared variability in firing patterns is critical for appreciating the representation of sensory stimuli in ensembles of neurons, the coincident influences of neurons on common targets, and the functional implications of microcircuitry. Our knowledge about neuronal correlations, however, derives largely from experiments that used different recording methods, analysis techniques, and cortical regions. Here we studied the structure of neuronal correlation in area V4 of alert macaques using recording and analysis procedures designed to match those used previously in primary visual cortex (V1), the major input to V4. We found that the spatial and temporal properties of correlations in V4 were remarkably similar to those of V1, with two notable differences: correlated variability in V4 was approximately one-third the magnitude of that in V1 and synchrony in V4 was less temporally precise than in V1. In both areas, spontaneous activity (measured during fixation while viewing a blank screen) was approximately twice as correlated as visual-evoked activity. The results provide a foundation for understanding how the structure of neuronal correlation differs among brain regions and stages in cortical processing and suggest that it is likely governed by features of neuronal circuits that are shared across the visual cortex.

Decision-Making in the Primate Brain

Making decisions is fundamental to everything we do, yet it can be impaired in various disorders and conditions. While research into the neural basis of decision-making has flourished in recent years, many questions remain about how decisions are instantiated in the brain. Here we explored how primates make abstract decisions and decisions in social contexts, as well as one way to non-invasively modulate the brain circuits underlying decision-making. We used rhesus macaques as our model organism. First we probed numerical decision-making, a form of abstract decision-making. We demonstrated that monkeys are able to compare discrete ratios, choosing an array with a greater ratio of positive to negative stimuli, even when this array does not have a greater absolute number of positive stimuli. Monkeys’ performance in this task adhered to Weber’s law, indicating that monkeys—like humans—treat proportions as analog magnitudes. Next we showed that monkeys’ ordinal decisions are influenced by spatial associations; when trained to select the fourth stimulus from the bottom in a vertical array, they subsequently selected the fourth stimulus from the left—and not from the right—in a horizontal array. In other words, they begin enumerating from one side of space and not the other, mirroring the human tendency to associate numbers with space. These and other studies confirmed that monkeys’ numerical decision-making follows similar patterns to that of humans, making them a good model for investigations of the neurobiological basis of numerical decision-making.

We sought to develop a system for exploring the neuronal basis of the cognitive and behavioral effects observed following transcranial magnetic stimulation, a relatively new, non-invasive method of brain stimulation that may be used to treat clinical disorders. We completed a set of pilot studies applying offline low-frequency repetitive transcranial magnetic stimulation to the macaque posterior parietal cortex, which has been implicated in numerical processing, while subjects performed a numerical comparison and control color comparison task, and while electrophysiological activity was recorded from the stimulated region of cortex. We found tentative evidence in one paradigm that stimulation did selectively impair performance in the number task, causally implicating the posterior parietal cortex in numerical decisions. In another paradigm, however, we manipulated the subject’s reaching behavior but not her number or color comparison performance. We also found that stimulation produced variable changes in neuronal firing and local field potentials. Together these findings lay the groundwork for detailed investigations into how different parameters of transcranial magnetic stimulation can interact with cortical architecture to produce various cognitive and behavioral changes.

Finally, we explored how monkeys decide how to behave in competitive social interactions. In a zero-sum computer game in which two monkeys played as a shooter or a goalie during a hockey-like “penalty shot” scenario, we found that shooters developed complex movement trajectories so as to conceal their intentions from the goalies. Additionally, we found that neurons in the dorsolateral and dorsomedial prefrontal cortex played a role in generating this “deceptive” behavior. We conclude that these regions of prefrontal cortex form part of a circuit that guides decisions to make an individual less predictable to an opponent.

Functional neuroimaging of autobiographical memory.

Functional neuroimaging studies of autobiographical memory have grown dramatically in recent years. These studies are important because they can investigate the neural correlates of processes that are difficult to study using laboratory stimuli, including: (i) complex constructive processes, (ii) recollective qualities of emotion and vividness, and (iii) remote memory retrieval. Constructing autobiographical memories involves search, monitoring and self-referential processes that are associated with activity in separable prefrontal regions. The contributions of emotion and vividness have been linked to the amygdala and visual cortex respectively. Finally, there is evidence that recent and remote autobiographical memories might activate the hippocampus equally, which has implications for memory-consolidation theories. The rapid development of innovative methods for eliciting personal memories in the scanner provides the opportunity to delve into the functional neuroanatomy of our personal past.

Imagery and retrieval of auditory and visual information: neural correlates of successful and unsuccessful performance.

Remembering past events - or episodic retrieval - consists of several components. There is evidence that mental imagery plays an important role in retrieval and that the brain regions supporting imagery overlap with those supporting retrieval. An open issue is to what extent these regions support successful vs. unsuccessful imagery and retrieval processes. Previous studies that examined regional overlap between imagery and retrieval used uncontrolled memory conditions, such as autobiographical memory tasks, that cannot distinguish between successful and unsuccessful retrieval. A second issue is that fMRI studies that compared imagery and retrieval have used modality-aspecific cues that are likely to activate auditory and visual processing regions simultaneously. Thus, it is not clear to what extent identified brain regions support modality-specific or modality-independent imagery and retrieval processes. In the current fMRI study, we addressed this issue by comparing imagery to retrieval under controlled memory conditions in both auditory and visual modalities. We also obtained subjective measures of imagery quality allowing us to dissociate regions contributing to successful vs. unsuccessful imagery. Results indicated that auditory and visual regions contribute both to imagery and retrieval in a modality-specific fashion. In addition, we identified four sets of brain regions with distinct patterns of activity that contributed to imagery and retrieval in a modality-independent fashion. The first set of regions, including hippocampus, posterior cingulate cortex, medial prefrontal cortex and angular gyrus, showed a pattern common to imagery/retrieval and consistent with successful performance regardless of task. The second set of regions, including dorsal precuneus, anterior cingulate and dorsolateral prefrontal cortex, also showed a pattern common to imagery and retrieval, but consistent with unsuccessful performance during both tasks. Third, left ventrolateral prefrontal cortex showed an interaction between task and performance and was associated with successful imagery but unsuccessful retrieval. Finally, the fourth set of regions, including ventral precuneus, midcingulate cortex and supramarginal gyrus, showed the opposite interaction, supporting unsuccessful imagery, but successful retrieval performance. Results are discussed in relation to reconstructive, attentional, semantic memory, and working memory processes. This is the first study to separate the neural correlates of successful and unsuccessful performance for both imagery and retrieval and for both auditory and visual modalities.

Fear learning circuitry is biased toward generalization of fear associations in posttraumatic stress disorder.

Fear conditioning is an established model for investigating posttraumatic stress disorder (PTSD). However, symptom triggers may vaguely resemble the initial traumatic event, differing on a variety of sensory and affective dimensions. We extended the fear-conditioning model to assess generalization of conditioned fear on fear processing neurocircuitry in PTSD. Military veterans (n=67) consisting of PTSD (n=32) and trauma-exposed comparison (n=35) groups underwent functional magnetic resonance imaging during fear conditioning to a low fear-expressing face while a neutral face was explicitly unreinforced. Stimuli that varied along a neutral-to-fearful continuum were presented before conditioning to assess baseline responses, and after conditioning to assess experience-dependent changes in neural activity. Compared with trauma-exposed controls, PTSD patients exhibited greater post-study memory distortion of the fear-conditioned stimulus toward the stimulus expressing the highest fear intensity. PTSD patients exhibited biased neural activation toward high-intensity stimuli in fusiform gyrus (P<0.02), insula (P<0.001), primary visual cortex (P<0.05), locus coeruleus (P<0.04), thalamus (P<0.01), and at the trend level in inferior frontal gyrus (P=0.07). All regions except fusiform were moderated by childhood trauma. Amygdala-calcarine (P=0.01) and amygdala-thalamus (P=0.06) functional connectivity selectively increased in PTSD patients for high-intensity stimuli after conditioning. In contrast, amygdala-ventromedial prefrontal cortex (P=0.04) connectivity selectively increased in trauma-exposed controls compared with PTSD patients for low-intensity stimuli after conditioning, representing safety learning. In summary, fear generalization in PTSD is biased toward stimuli with higher emotional intensity than the original conditioned-fear stimulus. Functional brain differences provide a putative neurobiological model for fear generalization whereby PTSD symptoms are triggered by threat cues that merely resemble the index trauma.

Control of radiative processes using tunable plasmonic nanopatch antennas.

The radiative processes associated with fluorophores and other radiating systems can be profoundly modified by their interaction with nanoplasmonic structures. Extreme electromagnetic environments can be created in plasmonic nanostructures or nanocavities, such as within the nanoscale gap region between two plasmonic nanoparticles, where the illuminating optical fields and the density of radiating modes are dramatically enhanced relative to vacuum. Unraveling the various mechanisms present in such coupled systems, and their impact on spontaneous emission and other radiative phenomena, however, requires a suitably reliable and precise means of tuning the plasmon resonance of the nanostructure while simultaneously preserving the electromagnetic characteristics of the enhancement region. Here, we achieve this control using a plasmonic platform consisting of colloidally synthesized nanocubes electromagnetically coupled to a metallic film. Each nanocube resembles a nanoscale patch antenna (or nanopatch) whose plasmon resonance can be changed independent of its local field enhancement. By varying the size of the nanopatch, we tune the plasmonic resonance by ∼ 200 nm, encompassing the excitation, absorption, and emission spectra corresponding to Cy5 fluorophores embedded within the gap region between nanopatch and film. By sweeping the plasmon resonance but keeping the field enhancements roughly fixed, we demonstrate fluorescence enhancements exceeding a factor of 30,000 with detector-limited enhancements of the spontaneous emission rate by a factor of 74. The experiments are supported by finite-element simulations that reveal design rules for optimized fluorescence enhancement or large Purcell factors.

The spatiotemporal dynamics of autobiographical memory: neural correlates of recall, emotional intensity, and reliving.

We sought to map the time course of autobiographical memory retrieval, including brain regions that mediate phenomenological experiences of reliving and emotional intensity. Participants recalled personal memories to auditory word cues during event-related functional magnetic resonance imaging (fMRI). Participants pressed a button when a memory was accessed, maintained and elaborated the memory, and then gave subjective ratings of emotion and reliving. A novel fMRI approach based on timing differences capitalized on the protracted reconstructive process of autobiographical memory to segregate brain areas contributing to initial access and later elaboration and maintenance of episodic memories. The initial period engaged hippocampal, retrosplenial, and medial and right prefrontal activity, whereas the later period recruited visual, precuneus, and left prefrontal activity. Emotional intensity ratings were correlated with activity in several regions, including the amygdala and the hippocampus during the initial period. Reliving ratings were correlated with activity in visual cortex and ventromedial and inferior prefrontal regions during the later period. Frontopolar cortex was the only brain region sensitive to emotional intensity across both periods. Results were confirmed by time-locked averages of the fMRI signal. The findings indicate dynamic recruitment of emotion-, memory-, and sensory-related brain regions during remembering and their dissociable contributions to phenomenological features of the memories.

The neuropsychology of autobiographical memory.

This special issue of Cortex focuses on the relative contribution of different neural networks to memory and the interaction of 'core' memory processes with other cognitive processes. In this article, we examine both. Specifically, we identify cognitive processes other than encoding and retrieval that are thought to be involved in memory; we then examine the consequences of damage to brain regions that support these processes. This approach forces a consideration of the roles of brain regions outside of the frontal, medial-temporal, and diencephalic regions that form a central part of neurobiological theories of memory. Certain kinds of damage to visual cortex or lateral temporal cortex produced impairments of visual imagery or semantic memory; these patterns of impairment are associated with a unique pattern of amnesia that was distinctly different from the pattern associated with medial-temporal trauma. On the other hand, damage to language regions, auditory cortex, or parietal cortex produced impairments of language, auditory imagery, or spatial imagery; however, these impairments were not associated with amnesia. Therefore, a full model of autobiographical memory must consider cognitive processes that are not generally considered 'core processes,' as well as the brain regions upon which these processes depend.

Changes in Brain Resting-state Functional Connectivity Associated with Peripheral Nerve Block: A Pilot Study.

BACKGROUND: Limited information exists on the effects of temporary functional deafferentation (TFD) on brain activity after peripheral nerve block (PNB) in healthy humans. Increasingly, resting-state functional connectivity (RSFC) is being used to study brain activity and organization. The purpose of this study was to test the hypothesis that TFD through PNB will influence changes in RSFC plasticity in central sensorimotor functional brain networks in healthy human participants. METHODS: The authors achieved TFD using a supraclavicular PNB model with 10 healthy human participants undergoing functional connectivity magnetic resonance imaging before PNB, during active PNB, and during PNB recovery. RSFC differences among study conditions were determined by multiple-comparison-corrected (false discovery rate-corrected P value less than 0.05) random-effects, between-condition, and seed-to-voxel analyses using the left and right manual motor regions. RESULTS: The results of this pilot study demonstrated disruption of interhemispheric left-to-right manual motor region RSFC (e.g., mean Fisher-transformed z [effect size] at pre-PNB 1.05 vs. 0.55 during PNB) but preservation of intrahemispheric RSFC of these regions during PNB. Additionally, there was increased RSFC between the left motor region of interest (PNB-affected area) and bilateral higher order visual cortex regions after clinical PNB resolution (e.g., Fisher z between left motor region of interest and right and left lingual gyrus regions during PNB, -0.1 and -0.6 vs. 0.22 and 0.18 after PNB resolution, respectively). CONCLUSIONS: This pilot study provides evidence that PNB has features consistent with other models of deafferentation, making it a potentially useful approach to investigate brain plasticity. The findings provide insight into RSFC of sensorimotor functional brain networks during PNB and PNB recovery and support modulation of the sensory-motor integration feedback loop as a mechanism for explaining the behavioral correlates of peripherally induced TFD through PNB.

Gaussian Process Kernels for Cross-Spectrum Analysis in Electrophysiological Time Series

Multi-output Gaussian processes provide a convenient framework for multi-task problems. An illustrative and motivating example of a multi-task problem is multi-region electrophysiological time-series data, where experimentalists are interested in both power and phase coherence between channels. Recently, the spectral mixture (SM) kernel was proposed to model the spectral density of a single task in a Gaussian process framework. This work develops a novel covariance kernel for multiple outputs, called the cross-spectral mixture (CSM) kernel. This new, flexible kernel represents both the power and phase relationship between multiple observation channels. The expressive capabilities of the CSM kernel are demonstrated through implementation of 1) a Bayesian hidden Markov model, where the emission distribution is a multi-output Gaussian process with a CSM covariance kernel, and 2) a Gaussian process factor analysis model, where factor scores represent the utilization of cross-spectral neural circuits. Results are presented for measured multi-region electrophysiological data.

Dynamics of visual receptive fields in the macaque frontal eye field.

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

Different stimuli, different spatial codes: a visual map and an auditory rate code for oculomotor space in the primate superior colliculus.

Maps are a mainstay of visual, somatosensory, and motor coding in many species. However, auditory maps of space have not been reported in the primate brain. Instead, recent studies have suggested that sound location may be encoded via broadly responsive neurons whose firing rates vary roughly proportionately with sound azimuth. Within frontal space, maps and such rate codes involve different response patterns at the level of individual neurons. Maps consist of neurons exhibiting circumscribed receptive fields, whereas rate codes involve open-ended response patterns that peak in the periphery. This coding format discrepancy therefore poses a potential problem for brain regions responsible for representing both visual and auditory information. Here, we investigated the coding of auditory space in the primate superior colliculus(SC), a structure known to contain visual and oculomotor maps for guiding saccades. We report that, for visual stimuli, neurons showed circumscribed receptive fields consistent with a map, but for auditory stimuli, they had open-ended response patterns consistent with a rate or level-of-activity code for location. The discrepant response patterns were not segregated into different neural populations but occurred in the same neurons. We show that a read-out algorithm in which the site and level of SC activity both contribute to the computation of stimulus location is successful at evaluating the discrepant visual and auditory codes, and can account for subtle but systematic differences in the accuracy of auditory compared to visual saccades. This suggests that a given population of neurons can use different codes to support appropriate multimodal behavior.

Frontal eye field neurons assess visual stability across saccades.

The image on the retina may move because the eyes move, or because something in the visual scene moves. The brain is not fooled by this ambiguity. Even as we make saccades, we are able to detect whether visual objects remain stable or move. Here we test whether this ability to assess visual stability across saccades is present at the single-neuron level in the frontal eye field (FEF), an area that receives both visual input and information about imminent saccades. Our hypothesis was that neurons in the FEF report whether a visual stimulus remains stable or moves as a saccade is made. Monkeys made saccades in the presence of a visual stimulus outside of the receptive field. In some trials, the stimulus remained stable, but in other trials, it moved during the saccade. In every trial, the stimulus occupied the center of the receptive field after the saccade, thus evoking a reafferent visual response. We found that many FEF neurons signaled, in the strength and timing of their reafferent response, whether the stimulus had remained stable or moved. Reafferent responses were tuned for the amount of stimulus translation, and, in accordance with human psychophysics, tuning was better (more prevalent, stronger, and quicker) for stimuli that moved perpendicular, rather than parallel, to the saccade. Tuning was sometimes present as well for nonspatial transaccadic changes (in color, size, or both). Our results indicate that FEF neurons evaluate visual stability during saccades and may be general purpose detectors of transaccadic visual change.

The steady-state visual evoked potential in vision research: A review.

Periodic visual stimulation and analysis of the resulting steady-state visual evoked potentials were first introduced over 80 years ago as a means to study visual sensation and perception. From the first single-channel recording of responses to modulated light to the present use of sophisticated digital displays composed of complex visual stimuli and high-density recording arrays, steady-state methods have been applied in a broad range of scientific and applied settings.The purpose of this article is to describe the fundamental stimulation paradigms for steady-state visual evoked potentials and to illustrate these principles through research findings across a range of applications in vision science.