Use of 31 P magnetisation transfer magnetic resonance spectroscopy to measure ATP changes after 670 nm transcranial photobiomodulation in older adults.

Mitochondrial function declines with age, and many pathological processes in neurodegenerative diseases stem from this dysfunction when mitochondria fail to produce the necessary energy required. Photobiomodulation (PBM), long-wavelength light therapy, has been shown to rescue mitochondrial function in animal models and improve human health, but clinical uptake is limited due to uncertainty around efficacy and the mechanisms responsible. Using 31 P magnetisation transfer magnetic resonance spectroscopy (MT-MRS) we quantify, for the first time, the effects of 670 nm PBM treatment on healthy ageing human brains. We find a significant increase in the rate of ATP synthase flux in the brain after PBM in a cohort of older adults. Our study provides initial evidence of PBM therapeutic efficacy for improving mitochondrial function and restoring ATP flux with age, but recognises that wider studies are now required to confirm any resultant cognitive benefits.

The Emergence of Tuning to Global Shape Properties of Radial Frequency Patterns in the Ventral Visual Pathway.

Radial frequency (RF) patterns, created by sinusoidal modulations of a circle's radius, are processed globally when RF is low. These closed shapes therefore offer a useful way to interrogate the human visual system for global processing of curvature. RF patterns elicit greater responses than those to radial gratings in V4 and more anterior face-selective regions of the ventral visual pathway. This is largely consistent with work on nonhuman primates showing curvature processing emerges in V4, but is evident also higher up the ventral visual stream. Rather than contrasting RF patterns with other stimuli, we presented them at varied frequencies in a regimen that allowed tunings to RF to be derived from 8 human participants (3 female). We found tuning to low RF in lateral occipital areas and to some extent in V4. In a control experiment, we added a high-frequency ripple to the stimuli disrupting the local contour. Low-frequency tuning to these stimuli remained in the ventral visual stream, underscoring its role in global processing of shape curvature. We then used representational similarity analysis to show that, in lateral occipital areas, the neural representation was related to stimulus similarity, when it was computed with a model that captured how stimuli are perceived. We therefore show that global processing of shape curvature emerges in the ventral visual stream as early as V4, but is found more strongly in lateral occipital regions, which exhibit responses and representations that relate well to perception.SIGNIFICANCE STATEMENT We show that tuning to low radial frequencies, known to engage global shape processing mechanisms, was localized to lateral occipital regions. When low-level stimulus properties were accounted for such tuning emerged in V4 and LO2 in addition to the object-selective region LO. We also documented representations of global shape properties in lateral occipital regions, and these representations were predicted well by a proxy of the perceptual difference between the stimuli.

Neurochemical and functional interactions for improved perceptual decisions through training.

Learning and experience are known to improve our ability to make perceptual decisions. Yet, our understanding of the brain mechanisms that support improved perceptual decisions through training remains limited. Here, we test the neurochemical and functional interactions that support learning for perceptual decisions in the context of an orientation identification task. Using magnetic resonance spectroscopy (MRS), we measure neurotransmitters (i.e., glutamate, GABA) that are known to be involved in visual processing and learning in sensory [early visual cortex (EV)] and decision-related [dorsolateral prefrontal cortex (DLPFC)] brain regions. Using resting-state functional magnetic resonance imaging (rs-fMRI), we test for functional interactions between these regions that relate to decision processes. We demonstrate that training improves perceptual judgments (i.e., orientation identification), as indicated by faster rates of evidence accumulation after training. These learning-dependent changes in decision processes relate to lower EV glutamate levels and EV-DLPFC connectivity, suggesting that glutamatergic excitation and functional interactions between visual and dorsolateral prefrontal cortex facilitate perceptual decisions. Further, anodal transcranial direct current stimulation (tDCS) in EV impairs learning, suggesting a direct link between visual cortex excitation and perceptual decisions. Our findings advance our understanding of the role of learning in perceptual decision making, suggesting that glutamatergic excitation for efficient sensory processing and functional interactions between sensory and decision-related regions support improved perceptual decisions.NEW & NOTEWORTHY Combining multimodal brain imaging [magnetic resonance spectroscopy (MRS), functional connectivity] with interventions [transcranial direct current stimulation (tDCS)], we demonstrate that glutamatergic excitation and functional interactions between sensory (visual) and decision-related (dorsolateral prefrontal cortex) areas support our ability to optimize perceptual decisions through training.

Ultra-High-Field Neuroimaging Reveals Fine-Scale Processing for 3D Perception.

Binocular disparity provides critical information about three-dimensional (3D) structures to support perception and action. In the past decade significant progress has been made in uncovering human brain areas engaged in the processing of binocular disparity signals. Yet, the fine-scale brain processing underlying 3D perception remains unknown. Here, we use ultra-high-field (7T) functional imaging at submillimeter resolution to examine fine-scale BOLD fMRI signals involved in 3D perception. In particular, we sought to interrogate the local circuitry involved in disparity processing by sampling fMRI responses at different positions relative to the cortical surface (i.e., across cortical depths corresponding to layers). We tested for representations related to 3D perception by presenting participants (male and female, N = 8) with stimuli that enable stable stereoscopic perception [i.e., correlated random dot stereograms (RDS)] versus those that do not (i.e., anticorrelated RDS). Using multivoxel pattern analysis (MVPA), we demonstrate cortical depth-specific representations in areas V3A and V7 as indicated by stronger pattern responses for correlated than for anticorrelated stimuli in upper rather than deeper layers. Examining informational connectivity, we find higher feedforward layer-to-layer connectivity for correlated than anticorrelated stimuli between V3A and V7. Further, we observe disparity-specific feedback from V3A to V1 and from V7 to V3A. Our findings provide evidence for the role of V3A as a key nexus for disparity processing, which is implicated in feedforward and feedback signals related to the perceptual estimation of 3D structures.SIGNIFICANCE STATEMENT Binocular vision plays a significant role in supporting our interactions with the surrounding environment. The fine-scale neural mechanisms that underlie the brain's skill in extracting 3D structures from binocular signals are poorly understood. Here, we capitalize on recent advances in ultra-high-field functional imaging to interrogate human brain circuits involved in 3D perception at submillimeter resolution. We provide evidence for the role of area V3A as a key nexus for disparity processing, which is implicated in feedforward and feedback signals related to the perceptual estimation of 3D structures from binocular signals. These fine-scale measurements help bridge the gap between animal neurophysiology and human fMRI studies investigating cross-scale circuits, from micro circuits to global brain networks for 3D perception.

Functional Interactions between Sensory and Memory Networks for Adaptive Behavior.

The brain's capacity to adapt to sensory inputs is key for processing sensory information efficiently and interacting in new environments. Following repeated exposure to the same sensory input, brain activity in sensory areas is known to decrease as inputs become familiar, a process known as adaptation. Yet, the brain-wide mechanisms that mediate adaptive processing remain largely unknown. Here, we combine multimodal brain imaging (functional magnetic resonance imaging [fMRI], magnetic resonance spectroscopy) with behavioral measures of orientation-specific adaptation (i.e., tilt aftereffect) to investigate the functional and neurochemical mechanisms that support adaptive processing. Our results reveal two functional brain networks: 1) a sensory-adaptation network including occipital and dorsolateral prefrontal cortex regions that show decreased fMRI responses for repeated stimuli and 2) a perceptual-memory network including regions in the parietal memory network (PMN) and dorsomedial prefrontal cortex that relate to perceptual bias (i.e., tilt aftereffect). We demonstrate that adaptation relates to increased occipito-parietal connectivity, while decreased connectivity between sensory-adaptation and perceptual-memory networks relates to GABAergic inhibition in the PMN. Thus, our findings provide evidence that suppressive interactions between sensory-adaptation (i.e., occipito-parietal) and perceptual-memory (i.e., PMN) networks support adaptive processing and behavior, proposing a key role of memory systems in efficient sensory processing.

A protocol for ultra-high field laminar fMRI in the human brain.

Ultra-high field (UHF) neuroimaging affords the sub-millimeter resolution that allows researchers to interrogate brain computations at a finer scale than that afforded by standard fMRI techniques. Here, we present a step-by-step protocol for using UHF imaging (Siemens Terra 7T scanner) to measure activity in the human brain. We outline how to preprocess the data using a pipeline that combines tools from SPM, FreeSurfer, ITK-SNAP, and BrainVoyager and correct for vasculature-related confounders to improve the spatial accuracy of the fMRI signal. For complete details on the use and execution of this protocol, please refer to Jia et al. (2020) and Zamboni et al. (2020).

Fine-scale computations for adaptive processing in the human brain.

Adapting to the environment statistics by reducing brain responses to repetitive sensory information is key for efficient information processing. Yet, the fine-scale computations that support this adaptive processing in the human brain remain largely unknown. Here, we capitalise on the sub-millimetre resolution of ultra-high field imaging to examine functional magnetic resonance imaging signals across cortical depth and discern competing hypotheses about the brain mechanisms (feedforward vs. feedback) that mediate adaptive processing. We demonstrate layer-specific suppressive processing within visual cortex, as indicated by stronger BOLD decrease in superficial and middle than deeper layers for gratings that were repeatedly presented at the same orientation. Further, we show altered functional connectivity for adaptation: enhanced feedforward connectivity from V1 to higher visual areas, short-range feedback connectivity between V1 and V2, and long-range feedback occipito-parietal connectivity. Our findings provide evidence for a circuit of local recurrent and feedback interactions that mediate rapid brain plasticity for adaptive information processing.

Recurrent Processing Drives Perceptual Plasticity.

Learning and experience are critical for translating ambiguous sensory information from our environments to perceptual decisions. Yet evidence on how training molds the adult human brain remains controversial, as fMRI at standard resolution does not allow us to discern the finer scale mechanisms that underlie sensory plasticity. Here, we combine ultra-high-field (7T) functional imaging at sub-millimeter resolution with orientation discrimination training to interrogate experience-dependent plasticity across cortical depths that are known to support dissociable brain computations. We demonstrate that learning alters orientation-specific representations in superficial rather than middle or deeper V1 layers, consistent with recurrent plasticity mechanisms via horizontal connections. Further, learning increases feedforward rather than feedback layer-to-layer connectivity in occipito-parietal regions, suggesting that sensory plasticity gates perceptual decisions. Our findings reveal finer scale plasticity mechanisms that re-weight sensory signals to inform improved decisions, bridging the gap between micro- and macro-circuits of experience-dependent plasticity.

Do perceptual biases emerge early or late in visual processing? Decision-biases in motion perception.

Visual perception is strongly influenced by contextual information. A good example is reference repulsion, where subjective reports about the direction of motion of a stimulus are significantly biased by the presence of an explicit reference. These perceptual biases could arise early, during sensory encoding, or alternatively, they may reflect decision-related processes occurring relatively late in the task sequence. To separate these two competing possibilities, we asked (human) subjects to perform a fine motion-discrimination task and then estimate the direction of motion in the presence or absence of an oriented reference line. When subjects performed the discrimination task with the reference, but subsequently estimated motion direction in its absence, direction estimates were unbiased. However, when subjects viewed the same stimuli but performed the estimation task only, with the orientation of the reference line jittered on every trial, the directions estimated by subjects were biased and yoked to the orientation of the shifted reference line. These results show that judgements made relative to a reference are subject to late, decision-related biases A model in which information about motion is integrated with that of an explicit reference cue, resulting in a late, decision-related re-weighting of the sensory representation, can account for these results.