Florian Pieper

Attentional Filtering of Visual Information by Neuronal Ensembles in the Primate Lateral Prefrontal Cortex

The activity of neurons in the primate lateral prefrontal cortex (LPFC) is strongly modulated by visual attention. Such a modulation has mostly been documented by averaging the activity of independently recorded neurons over repeated experimental trials. However, in realistic settings, ensembles of simultaneously active LPFC neurons must generate attentional signals on a single-trial basis, despite the individual and correlated variability of neuronal responses. Whether, under these circumstances, the LPFC can reliably generate attentional signals is unclear. Here, we show that the simultaneous activity of neuronal ensembles in the primate LPFC can be reliably decoded to predict the allocation of attention on a single-trial basis. Decoding was sensitive to the noise correlation structure of the ensembles. Additionally, it was resilient to distractors, predictive of behavior, and stable over weeks. Thus, LPFC neuronal ensemble activity can reliably encode attention within behavioral time frames, despite the noisy and correlated nature of neuronal activity.

Correlated variability modifies working memory fidelity in primate prefrontal neuronal ensembles

Significance The working memory (WM)-related activity in the primate prefrontal cortex (PFC) is hypothesized to arise from the structure of the network in which the neurons are embedded. Recent studies have also shown that it is difficult to predict the properties of neuronal ensembles from the properties of individually examined neurons. By recording the activity of neuronal ensembles in the macaque PFC, we found evidence supporting the network origins of WM activity and discovered features of WM coding in neuronal ensembles that were inaccessible in prior single neuron studies. Most notably, we found that correlated firing rate variability between neurons (i.e., noise correlations) can improve WM coding and that neurons not selective for WM can improve WM coding when part of an ensemble. Neurons in the primate lateral prefrontal cortex (LPFC) encode working memory (WM) representations via sustained firing, a phenomenon hypothesized to arise from recurrent dynamics within ensembles of interconnected neurons. Here, we tested this hypothesis by using microelectrode arrays to examine spike count correlations (rsc) in LPFC neuronal ensembles during a spatial WM task. We found a pattern of pairwise rsc during WM maintenance indicative of stronger coupling between similarly tuned neurons and increased inhibition between dissimilarly tuned neurons. We then used a linear decoder to quantify the effects of the high-dimensional rsc structure on information coding in the neuronal ensembles. We found that the rsc structure could facilitate or impair coding, depending on the size of the ensemble and tuning properties of its constituent neurons. A simple optimization procedure demonstrated that near-maximum decoding performance could be achieved using a relatively small number of neurons. These WM-optimized subensembles were more signal correlation (rsignal)-diverse and anatomically dispersed than predicted by the statistics of the full recorded population of neurons, and they often contained neurons that were poorly WM-selective, yet enhanced coding fidelity by shaping the ensemble’s rsc structure. We observed a pattern of rsc between LPFC neurons indicative of recurrent dynamics as a mechanism for WM-related activity and that the rsc structure can increase the fidelity of WM representations. Thus, WM coding in LPFC neuronal ensembles arises from a complex synergy between single neuron coding properties and multidimensional, ensemble-level phenomena.

Single-Trial Decoding of Visual Attention from Local Field Potentials in the Primate Lateral Prefrontal Cortex Is Frequency-Dependent.

Local field potentials (LFPs) are fluctuations of extracellular voltage that may reflect the physiological phenomena occurring within a volume of neural tissue. It is known that the allocation of spatial attention modulates the amplitude of LFPs in visual areas of primates. An issue that remains poorly investigated is whether and how attention modulates LFPs in executive brain areas, such as the lateral prefrontal cortex (LPFC), thought to be involved in the origins of attention. We addressed this issue by recording LFPs from multielectrode arrays implanted in the LPFC of two macaques. We found that the allocation of attention can be reliably decoded on a single-trial basis from ensembles of LFPs with frequencies >60 Hz. Using LFP frequencies <60 Hz, we could not decode the allocation of attention, but we could decode the location of a visual stimulus as well as the endpoint of saccades toward that stimulus. The information contained in the high-frequency LFPs was fully redundant with the information contained in the spiking activity of single neurons recorded from the same electrodes. Moreover, the decoding of attention using γ frequency LFPs was less accurate than using spikes, but it was twice more stable across time. Finally, decorrelating the LFP signals from the different electrodes increased decoding performance in the high frequencies by up to ∼14%. Our findings suggest that LFPs recorded from chronically implanted multielectrode arrays in the LPFC contain information about sensory, cognitive, and motor components of a task in a frequency-dependent manner.

Crossmodal integration improves sensory detection thresholds in the ferret.

During the last two decades ferrets (Mustela putorius) have been established as a highly efficient animal model in different fields in neuroscience. Here we asked whether ferrets integrate sensory information according to the same principles established for other species. Since only few methods and protocols are available for behaving ferrets we developed a head-free, body-restrained approach allowing a standardized stimulation position and the utilization of the ferret’s natural response behavior. We established a behavioral paradigm to test audiovisual integration in the ferret. Animals had to detect a brief auditory and/or visual stimulus presented either left or right from their midline. We first determined detection thresholds for auditory amplitude and visual contrast. In a second step, we combined both modalities and compared psychometric fits and the reaction times between all conditions. We employed Maximum Likelihood Estimation (MLE) to model bimodal psychometric curves and to investigate whether ferrets integrate modalities in an optimal manner. Furthermore, to test for a redundant signal effect we pooled the reaction times of all animals to calculate a race model. We observed that bimodal detection thresholds were reduced and reaction times were faster in the bimodal compared to unimodal conditions. The race model and MLE modeling showed that ferrets integrate modalities in a statistically optimal fashion. Taken together, the data indicate that principles of multisensory integration previously demonstrated in other species also apply to crossmodal processing in the ferret.

Dynamic reconfiguration of cortical functional connectivity across brain states

Throughout each day, the brain displays transient changes in state, as evidenced by shifts in behavior and vigilance. While the electrophysiological correlates of brain states have been studied for some time, it remains unclear how large-scale cortico-cortical functional connectivity systematically reconfigures across states. Here, we investigate state-dependent shifts in cortical functional connectivity by recording local field potentials (LFPs) during spontaneous behavioral transitions in the ferret using chronically implanted micro-electrocorticographic (µECoG) arrays positioned over occipital, parietal, and temporal cortical regions. To objectively classify brain state, we describe a data-driven approach that projects time-varying LFP spectral properties into brain state space. Distinct brain states displayed markedly different patterns of cross-frequency phase-amplitude coupling and inter-electrode phase synchronization across several LFP frequency bands. The largest across-state differences in functional connectivity were observed between periods of presumed slow-wave and rapid-eye-movement-sleep/active-state, which were characterized by the contrasting phenomena of cortical network fragmentation and global synchronization, respectively. Collectively, our data provide strong evidence that large-scale functional interactions in the brain dynamically reconfigure across behavioral states.

Single-trial decoding of intended eye movement goals from lateral prefrontal cortex neural ensembles

Neurons in the lateral prefrontal cortex (LPFC) encode sensory and cognitive signals, as well as commands for goal-directed actions. Therefore, the LPFC might be a good signal source for a goal-selection brain-computer interface (BCI) that decodes the intended goal of a motor action previous to its execution. As a first step in the development of a goal-selection BCI, we set out to determine if we could decode simple behavioral intentions to direct gaze to eight different locations in space from single-trial LPFC neural activity. We recorded neuronal spiking activity from microelectrode arrays implanted in area 8A of the LPFC of two adult macaques while they made visually guided saccades to one of eight targets in a center-out task. Neuronal activity encoded target location immediately after target presentation, during a delay epoch, during the execution of the saccade, and every combination thereof. Many (40%) of the neurons that encoded target location during multiple epochs preferred different locations during different epochs. Despite heterogeneous and dynamic responses, the neuronal feature set that best predicted target location was the averaged firing rates from the entire trial and it was best classified using linear discriminant analysis (63.6-96.9% in 12 sessions, mean 80.3%; information transfer rate: 21-59, mean 32.8 bits/min). Our results demonstrate that it is possible to decode intended saccade target location from single-trial LPFC activity and suggest that the LPFC is a suitable signal source for a goal-selection cognitive BCI.

Intrinsic coupling modes reveal the functional architecture of cortico-tectal networks

Correlation of ongoing neural dynamics reveals the various carrier frequencies of cortico-tectal functional interaction. In the absence of sensory stimulation or motor output, the brain exhibits complex spatiotemporal patterns of intrinsically generated neural activity. Analysis of ongoing brain dynamics has identified the prevailing modes of cortico-cortical interaction; however, little is known about how such patterns of intrinsically generated activity are correlated between cortical and subcortical brain areas. We investigate the correlation structure of ongoing cortical and superior colliculus (SC) activity across multiple spatial and temporal scales. Ongoing cortico-tectal interaction was characterized by correlated fluctuations in the amplitude of delta, spindle, low gamma, and high-frequency oscillations (>100 Hz). Of these identified coupling modes, topographical patterns of high-frequency coupling were the most consistent with patterns of anatomical connectivity, reflecting synchronized spiking within cortico-tectal networks. Cortico-tectal coupling at high frequencies was temporally parcellated by the phase of slow cortical oscillations and was strongest for SC-cortex channel pairs that displayed overlapping visual spatial receptive fields. Despite displaying a high degree of spatial specificity, cortico-tectal coupling in lower-frequency bands did not match patterns of cortex-to-SC anatomical connectivity. Collectively, our findings demonstrate that neural activity is spontaneously coupled between cortex and SC, with high- and low-frequency modes of coupling reflecting direct and indirect cortico-tectal interactions, respectively.

Auditory and visual interactions between the superior and inferior colliculi in the ferret

The integration of visual and auditory spatial information is important for building an accurate perception of the external world, but the fundamental mechanisms governing such audiovisual interaction have only partially been resolved. The earliest interface between auditory and visual processing pathways is in the midbrain, where the superior (SC) and inferior colliculi (IC) are reciprocally connected in an audiovisual loop. Here, we investigate the mechanisms of audiovisual interaction in the midbrain by recording neural signals from the SC and IC simultaneously in anesthetized ferrets. Visual stimuli reliably produced band‐limited phase locking of IC local field potentials (LFPs) in two distinct frequency bands: 6–10 and 15–30 Hz. These visual LFP responses co‐localized with robust auditory responses that were characteristic of the IC. Imaginary coherence analysis confirmed that visual responses in the IC were not volume‐conducted signals from the neighboring SC. Visual responses in the IC occurred later than retinally driven superficial SC layers and earlier than deep SC layers that receive indirect visual inputs, suggesting that retinal inputs do not drive visually evoked responses in the IC. In addition, SC and IC recording sites with overlapping visual spatial receptive fields displayed stronger functional connectivity than sites with separate receptive fields, indicating that visual spatial maps are aligned across both midbrain structures. Reciprocal coupling between the IC and SC therefore probably serves the dynamic integration of visual and auditory representations of space.

Laminar profile of visual response properties in ferret superior colliculus

In the superior colliculus (SC), visual afferent inputs from various sources converge in a highly organized way such that all layers form topographically aligned representations of contralateral external space. Despite this anatomical organization, it remains unclear how the layer-specific termination of different visual input pathways is reflected in the nature of visual response properties and their distribution across layers. To uncover the physiological correlates underlying the laminar organization of the SC, we recorded multiunit and local field potential activity simultaneously from all layers with dual-shank multichannel linear probes. We found that the location of spatial receptive fields was strongly conserved across all visual responsive layers. There was a tendency for receptive field size to increase with depth in the SC, with superficial receptive fields significantly smaller than deep receptive fields. Additionally, superficial layers responded significantly faster than deeper layers to flash stimulation. In some recordings, flash-evoked responses were characterized by the presence of gamma oscillatory activity (40-60 Hz) in multiunit and field potential signals, which was strongest in retinorecipient layers. While SC neurons tended to respond only weakly to full-field drifting gratings, we observed very similar oscillatory responses to the offset of grating stimuli, suggesting gamma oscillations are produced following light offset. Oscillatory spiking activity was highly correlated between horizontally distributed neurons within these layers, with oscillations temporally locked to the stimulus. Together, visual response properties provide physiological evidence reflecting the laminar-specific termination of visual afferent pathways in the SC, most notably characterized by the oscillatory entrainment of superficial neurons.

A Quadrantic Bias in Prefrontal Representation of Visual-Mnemonic Space

Single neurons in primate dorsolateral prefrontal cortex (dLPFC) are known to encode working memory (WM) representations of visual space. Psychophysical studies have shown that the horizontal and vertical meridians of the visual field can bias spatial information maintained in WM. However, most studies and models have tacitly assumed that dLPFC neurons represent mnemonic space homogenously. The anatomical organization of these representations has also eluded clear parametric description. We investigated these issues by recording from neuronal ensembles in macaque dLPFC with microelectrode arrays while subjects performed an oculomotor delayed-response task. We found that spatial WM representations in macaque dLPFC are biased by the vertical and horizontal meridians of the visual field, dividing mnemonic space into quadrants. This bias is reflected in single neuron firing rates, neuronal ensemble representations, the spike count correlation structure, and eye movement patterns. We also found that dLPFC representations of mnemonic space cluster anatomically in a nonretinotopic manner that partially reflects the organization of visual space. These results provide an explanation for known WM biases, and reveal novel principles of WM representation in prefrontal neuronal ensembles and across the cortical surface, as well as the need to reconceptualize models of WM to accommodate the observed representational biases.