Search

Visual imagery relies on a widespread network of brain regions, partly engaged during the perception of external stimuli. Beyond the recruitment of category-selective areas (FFA, PPA), perception of familiar faces and places has been reported to engage brain areas associated with semantic information, comprising the precuneus, temporo-parietal junction (TPJ), medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC). Here we used multivariate pattern analyzes (MVPA) to examine to which degree areas of the visual imagery network, category-selective and semantic areas contain information regarding the category and familiarity of imagined stimuli. Participants were instructed via auditory cues to imagine personally familiar and unfamiliar stimuli (i.e. faces and places). Using region-of-interest (ROI)-based MVPA, we were able to distinguish between imagined faces and places within nodes of the visual imagery network (V1, SPL, aIPS), within category-selective inferotemporal regions (FFA, PPA) and across all brain regions of the extended semantic network (i.e. precuneus, mPFC, IFG and TPJ). Moreover, we were able to decode familiarity of imagined stimuli in the SPL and aIPS, and in some regions of the extended semantic network (in particular, right precuneus, right TPJ), but not in V1. Our results suggest that posterior visual areas - including V1 - host categorical representations about imagined stimuli, and that stimulus familiarity might be an additional aspect that is shared between perception and visual imagery.

Human brain imaging typically employs structured and controlled tasks to avoid variable and inconsistent activation patterns. Here we expand this assumption by showing that an extremely open-ended, high-level cognitive task of thinking about an abstract content, loosely defined as “abstract thinking” - leads to highly consistent activation maps. Specifically, we show that activation maps generated during such cognitive process were precisely located relative to borders of well-known networks such as internal speech, visual and motor imagery. The activation patterns allowed decoding the thought condition at >95%. Surprisingly, the activated networks remained the same regardless of changes in thought content. Finally, we found remarkably consistent activation maps across individuals engaged in abstract thinking. This activation bordered, but strictly avoided visual and motor networks. On the other hand, it overlapped with left lateralized language networks. Activation of the default mode network (DMN) during abstract thought was similar to DMN activation during rest. These observations were supported by a quantitative neuronal distance metric analysis. Our results reveal that despite its high level, and varied content nature - abstract thinking activates surprisingly precise and consistent networks in participants’ brains.

Visual imagery has been suggested to recruit occipital cortex via feedback projections from fronto-parietal regions, suggesting that these feedback projections might be exploited to boost recruitment of occipital cortex by means of real-time neurofeedback. To test this prediction, we instructed a group of healthy participants to perform peripheral visual imagery while they received real-time auditory feedback based on the BOLD signal from either early visual cortex or the medial superior parietal lobe. We examined the amplitude and temporal aspects of the BOLD response in the two regions. Moreover, we compared the impact of self-rated mental focus and vividness of visual imagery on the BOLD responses in these two areas. We found that both early visual cortex and the medial superior parietal cortex are susceptible to auditory neurofeedback within a single feedback session per region. However, the signal in parietal cortex was sustained for a longer time compared to the signal in occipital cortex. Moreover, the BOLD signal in the medial superior parietal lobe was more affected by focus and vividness of the visual imagery than early visual cortex. Our results thus demonstrate that (a) participants can learn to self-regulate the BOLD signal in early visual and parietal cortex within a single session, (b) that different nodes in the visual imagery network respond differently to neurofeedback, and that (c) responses in parietal, but not in occipital cortex are susceptible to self-rated vividness of mental imagery. Together, these results suggest that medial superior parietal cortex might be a suitable candidate to provide real-time feedback to patients suffering from visual field defects. • Neurofeedback helps control both early visual cortex and parietal cortex via imagery. • Large influence of subjective vividness and focus on brain activity. • Parietal cortex more affected by focus and vividness. [ABSTRACT FROM AUTHOR]

Humans rely on at least two modes of thought: verbal (inner speech) and visual (imagery). Are these modes independent, or does engaging in one entail engaging in the other? To address this question, we performed a behavioral and an fMRI study. In the behavioral experiment, participants received a prompt and were asked to either silently generate a sentence or create a visual image in their mind. They were then asked to judge the vividness of the resulting representation, and of the potentially accompanying representation in the other format. In the fMRI experiment, participants had to recall sentences or images (that they were familiarized with prior to the scanning session) given prompts, or read sentences and view images, in the control, perceptual, condition. An asymmetry was observed between inner speech and visual imagery. In particular, inner speech was engaged to a greater extent during verbal than visual thought, but visual imagery was engaged to a similar extent during both modes of thought. Thus, it appears that people generate more robust verbal representations during deliberate inner speech compared to when their intent is to visualize. However, they generate visual images regardless of whether their intent is to visualize or to think verbally. One possible interpretation of these results is that visual thinking is somehow primary, given the relatively late emergence of verbal abilities during human development and in the evolution of our species. [ABSTRACT FROM AUTHOR]

Recent advances in neurofeedback based on real-time functional magnetic resonance imaging (fMRI) allow for learning to control spatially localized brain activity in the range of millimeters across the entire brain. Real-time fMRI neurofeedback studies have demonstrated the feasibility of self-regulating activation in specific areas that are involved in a variety of functions, such as perception, motor control, language, and emotional processing. In most of these previous studies, participants trained to control activity within one region of interest (ROI). In the present study, we extended the neurofeedback approach by now training healthy participants to control the interhemispheric balance between their left and right visual cortices. This was accomplished by providing feedback based on the difference in activity between a target visual ROI and the corresponding homologue region in the opposite hemisphere. Eight out of 14 participants learned to control the differential feedback signal over the course of 3 neurofeedback training sessions spread over 3 days, i.e., they produced consistent increases in the visual target ROI relative to the opposite visual cortex. Those who learned to control the differential feedback signal were subsequently also able to exert that control in the absence of neurofeedback. Such learning to voluntarily control the balance between cortical areas of the two hemispheres might offer promising rehabilitation approaches for neurological or psychiatric conditions associated with pathological asymmetries in brain activity patterns, such as hemispatial neglect, dyslexia, or mood disorders. [ABSTRACT FROM AUTHOR]

Abstract: In this study, we show that top-down control mechanisms engaged during visual imagery of simple shapes (letters X and O) can selectively activate position-invariant perceptual codes in visual areas specialised for shape processing, including lateral occipital complex (LOC). First, we used multivoxel pattern analysis (MVPA) to identify visual cortical areas that code for shape within a position-invariant reference frame. Next, we examined the similarity between these high-level visual codes and patterns elicited while participants imagined the corresponding stimulus at central fixation. Our results demonstrate that imagery engages object-centred codes in higher-level visual areas. More generally, our results also demonstrate that top-down control mechanisms are able to generate highly specific patterns of visual activity in the absence of corresponding sensory input. We argue that a general model of top-down control must account for dynamic modulation of functional connectivity between high-level control centres and overlapping neural codes in visual cortex. [Copyright &y& Elsevier]

Abstract: In the preceding paper (Lacey, S., Flueckiger, P., Stilla, R., Lava, M., Sathian, K., 2009a. Object familiarity modulates involvement of visual imagery in haptic shape perception), we showed that the activations evoked by visual imagery overlapped more extensively, and their magnitudes were more correlated, with those evoked during haptic shape perception of familiar, compared to unfamiliar, objects. Here we used task-specific analyses of functional and effective connectivity to provide convergent evidence. These analyses showed that the visual imagery and familiar haptic shape tasks activated similar networks, whereas the unfamiliar haptic shape task activated a different network. Multivariate Granger causality analyses of effective connectivity, in both a conventional form and one purged of zero-lag correlations, showed that the visual imagery and familiar haptic shape networks involved top-down paths from prefrontal cortex into the lateral occipital complex (LOC), whereas the unfamiliar haptic shape network was characterized by bottom-up, somatosensory inputs into the LOC. We conclude that shape representations in the LOC are flexibly accessible, either top-down or bottom-up, according to task demands, and that visual imagery is more involved in LOC activation during haptic shape perception when objects are familiar, compared to unfamiliar. [Copyright &y& Elsevier]

Abstract: Subjects deciding whether two objects presented at angular disparity are identical or mirror versions of each other usually show response times that linearly increase with the angle between objects. This phenomenon has been termed mental rotation. While there is widespread agreement that parietal cortex plays a dominant role in mental rotation, reports concerning the involvement of motor areas are less consistent. From a theoretical point of view, activation in motor areas suggests that mental rotation relies upon visuo-motor rather than visuo-spatial processing alone. However, the type of information that is processed by motor areas during mental rotation remains unclear. In this study we used event-related fMRI to assess whether activation in parietal and dorsolateral premotor areas (dPM) during mental rotation is distinctively related to processing spatial orientation information. Using a newly developed task paradigm we explicitly separated the processing steps (encoding, mental rotation proper and object matching) required by mental rotation tasks and additionally modulated the amount of spatial orientation information that had to be processed. Our results show that activation in dPM during mental rotation is not strongly modulated by the processing of spatial orientation information, and that activation in dPM areas is strongest during mental rotation proper. The latter finding suggests that dPM is involved in more generalized processes such as visuo-spatial attention and movement anticipation. We propose that solving mental rotation tasks is heavily dependent upon visuo-motor processes and evokes neural processing that may be considered as an implicit simulation of actual object rotation. [Copyright &y& Elsevier]

The aim of this work was to study the relevance of the primary motor cortex (M1) for motor functions different to the simple execution of motor orders. The M1 activity during the performance with individual fingers of a simple motor task (tonic flexion), a motor task that includes a complex motor computation but not motor execution (motor imagery), and a motor task that involves both the computation and execution of movements (phasic movement) was evaluated by functional magnetic resonance imaging (fMRI). The possible influence of other cortical tasks on the M1 activation induced by finger movements was assessed by evaluating the effect of a distracting concurrent task (numeric calculation). Data show that both the dimension of the area activated and the intensity of response were higher during motor planning than during motor execution. There is a mosaic-like distribution for motor-planning M1 functions, with the movement of individual fingers being controlled from several M1 loci. The concurrent mental-task induces a rapid functional reconfiguration of M1, adding M1 subsets to motor programming but excluding others. Present data support the involvement of the M1 in more than just simple motor execution, showing broader and more intense modifications during motor tasks not accompanied by movements (motor imagery) than during the execution of simple motor acts (tonic flexion). [Copyright &y& Elsevier]

Complex pictorial information can be represented and retrieved from memory as mental visual images. Functional brain imaging studies have shown that visual perception and visual imagery share common neural substrates. The type of memory (short- or long-term) that mediates the generation of mental images, however, has not been addressed previously. The purpose of this study was to investigate the neural correlates underlying imagery generated from short- and long-term memory (STM and LTM). We used famous faces to localize the visual response during perception and to compare the responses during visual imagery generated from STM (subjects memorized specific pictures of celebrities before the imagery task) and imagery from LTM (subjects imagined famous faces without seeing specific pictures during the experimental session). We found that visual perception of famous faces activated the inferior occipital gyri, lateral fusiform gyri, the superior temporal sulcus, and the amygdala. Small subsets of these face-selective regions were activated during imagery. Additionally, visual imagery of famous faces activated a network of regions composed of bilateral calcarine, hippocampus, precuneus, intraparietal sulcus (IPS), and the inferior frontal gyrus (IFG). In all these regions, imagery generated from STM evoked more activation than imagery from LTM. Regardless of memory type, focusing attention on features of the imagined faces (e.g., eyes, lips, or nose) resulted in increased activation in the right IPS and right IFG. Our results suggest differential effects of memory and attention during the generation and maintenance of mental images of faces. [Copyright &y& Elsevier]

• We investigated the encoding of category and familiarity of imagined stimuli. • MVPA revealed a widespread representation of imagined stimulus category. • Familiarity information was represented in a subset of these regions. • Familiarity might be an additional feature shared between perception and imagery. Visual imagery relies on a widespread network of brain regions, partly engaged during the perception of external stimuli. Beyond the recruitment of category-selective areas (FFA, PPA), perception of familiar faces and places has been reported to engage brain areas associated with semantic information, comprising the precuneus, temporo-parietal junction (TPJ), medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC). Here we used multivariate pattern analyzes (MVPA) to examine to which degree areas of the visual imagery network, category-selective and semantic areas contain information regarding the category and familiarity of imagined stimuli. Participants were instructed via auditory cues to imagine personally familiar and unfamiliar stimuli (i.e. faces and places). Using region-of-interest (ROI)-based MVPA, we were able to distinguish between imagined faces and places within nodes of the visual imagery network (V1, SPL, aIPS), within category-selective inferotemporal regions (FFA, PPA) and across all brain regions of the extended semantic network (i.e. precuneus, mPFC, IFG and TPJ). Moreover, we were able to decode familiarity of imagined stimuli in the SPL and aIPS, and in some regions of the extended semantic network (in particular, right precuneus, right TPJ), but not in V1. Our results suggest that posterior visual areas - including V1 - host categorical representations about imagined stimuli, and that stimulus familiarity might be an additional aspect that is shared between perception and visual imagery. [ABSTRACT FROM AUTHOR]

Human brain imaging typically employs structured and controlled tasks to avoid variable and inconsistent activation patterns. Here we expand this assumption by showing that an extremely open-ended, high-level cognitive task of thinking about an abstract content, loosely defined as "abstract thinking" - leads to highly consistent activation maps. Specifically, we show that activation maps generated during such cognitive process were precisely located relative to borders of well-known networks such as internal speech, visual and motor imagery. The activation patterns allowed decoding the thought condition at >95%. Surprisingly, the activated networks remained the same regardless of changes in thought content. Finally, we found remarkably consistent activation maps across individuals engaged in abstract thinking. This activation bordered, but strictly avoided visual and motor networks. On the other hand, it overlapped with left lateralized language networks. Activation of the default mode network (DMN) during abstract thought was similar to DMN activation during rest. These observations were supported by a quantitative neuronal distance metric analysis. Our results reveal that despite its high level, and varied content nature - abstract thinking activates surprisingly precise and consistent networks in participants' brains. [ABSTRACT FROM AUTHOR]