We describe a comprehensive framework for performing rapid and automatic nonlabel-based nonlinear spatial normalizations. The approach adopted minimizes the residual squared difference between an image and a template of the same modality. In order to reduce the number of parameters to be fitted, the nonlinear warps are described by a linear combination of low spatial frequency basis functions. The objective is to determine the optimum coefficients for each of the bases by minimizing the sum of squared differences between the image and template, while simultaneously maximizing the smoothness of the transformation using a maximum a posteriori (MAP) approach. Most MAP approaches assume that the variance associated with each voxel is already known and that there is no covariance between neighboring voxels. The approach described here attempts to estimate this variance from the data, and also corrects for the correlations between neighboring voxels. This makes the same approach suitable for the spatial normalization of both high-quality magnetic resonance images, and low-resolution noisy positron emission tomography images. A fast algorithm has been developed that utilizes Taylor's theorem and the separable nature of the basis functions, meaning that most of the nonlinear spatial variability between images can be automatically corrected within a few minutes. Hum. Brain Mapping 7:254–266, 1999. © 1999 Wiley-Liss, Inc.
Abstract Applications of fMRI in functional brain imaging are mainly confined to single subject designs, prohibiting the assessment of subject or group by condition interactions (i.e., differential activations) or areas of conjoint activation. In this paper a framework for fMRI group designs, using statistical parametric mapping, is introduced. It is generally believed that intersubject averaging, which requires spatial normalization and smoothing, will decrease the effective spatial resolution of fMRI or its sensitivity. A subcortical activation of the lateral geniculate nucleus (LGN) was therefore chosen to demonstrate the feasibility and power of intersubject averaging in the context of fMRI. Seven volunteers were studied, while looking at a blank screen or radially moving dots. LGN activation was demonstrated in all single subject analyses and in the group analysis.
Abstract. The Rorschach offers a unique and interesting paradigm from the perspective of the (Bayesian) brain. This contribution to the cross-disciplinary special issue considers the Rorschach from the perspective of perceptual inference in the brain and how it might inform subject-specific differences in perceptual synthesis. Before doing so, we provide a broad overview of active inference in its various manifestations. In brief, active inference supposes that our perceptions are the best hypothesis to explain sensory impressions. On a Bayesian account, the requisite belief updating rests sensitively upon the precision or confidence ascribed to sensory input, relative to prior beliefs about the causes of sensations. This focus – on the balance between sensory and prior precision – has been a useful construct in both cognitive science (e.g., as a formal explanation for attention) and neuropsychology (e.g., as a formal explanation for aberrant or false inference in hallucinations). In this setting, false inference is generally understood as abnormally high precision afforded to high-level hypotheses or explanations for visual input, which may compensate for a failure to attenuate sensory precision. On this view, the Rorschach offers an interesting paradigm because the amount of precise information about the causes of visual input is deliberately minimized – and rendered ambiguous – thereby placing greater emphasis on prior beliefs entertained by the respondent. We close by exploring this issue and several other areas of intersection between Rorschach responding and active inference.
Is it possible to understand the intentions of other people by simply observing their movements? Many neuroscientists believe that this ability depends on the brain's mirror-neuron system, which provides a direct link between action and observation. Precisely how intentions can be inferred through movement-observation, however, has provoked much debate. One problem in inferring the cause of an observed action, is that the problem is ill-posed because identical movements can be made when performing different actions with different goals. Here we suggest that this problem is solved by the mirror-neuron system using predictive coding on the basis of a statistical approach known as empirical Bayesian inference. This means that the most likely cause of an observed movement can be inferred by minimizing the prediction error at all cortical levels that are engaged during movement observation. This account identifies a precise role for the mirror-neuron system in our ability to infer intentions from observed movement and outlines possible computational mechanisms.
We review the evidence of pathophysiological changes in the prefrontal and temporal cortices of schizophrenic subjects and of abnormal integration of the physiological dynamics in these two regions. The argument we develop is that some schizophrenic phenomena are best understood in terms of abnormal interactions between different areas, not only at the levels of physiology and functional anatomy, but at the level of cognitive and sensorimotor functioning. We discuss recent functional imaging evidence suggesting abnormal prefronto-temporal interactions in relation to a psychological analysis of experiential symptoms in schizophrenia. Cortico-cortical interactions have been assessed in terms of functional connectivity and eigenimages, using time series of neurophysiological data obtained with positron emission tomography. The results of these analyses suggest that there is a profound disruption of large-scale prefronto-temporal interactions in schizophrenia. These disruptions are particularly relevant if one considers that many positive symptoms of schizophrenia reflect a failure to integrate intrinsically generated behaviour and concurrent perception.
The aim of this note is to revisit the analysis of conjunctions in imaging data. We review some conceptual issues that have emerged from recent discussion (Nichols, T., Brett, M., Andersson, J., Wager, T., Poline, J.-B., this issue. Valid Conjunction Inference with the Minimum Statistic.) and reformulate the conjunction of null hypotheses as a conjunction of k or more effects. Analyses based on minimum statistics have typically used the null hypothesis that k = 0. This enables inferences about one or more effects (k N 0). However, this does not provide control over false-positive rates (FPR) for inferences about a conjunction of k = n effects, over n tests. This is the key point made by Nichols et al., who suggest a procedure based on supremum P values that provides an upper bound on FPR for k = n. Although valid, this is a very conservative procedure, particularly in the context of multiple comparisons. We suggest that an inference on a conjunction of k = n effects is generally unnecessary and distinguish between congruent contrasts that test for the same treatment and incongruent contrasts of the sort used in cognitive conjunctions. For congruent contrasts, the usual inference, k N 0, is sufficient. With incongruent contrasts it is sufficient to infer a conjunction of k N u effects, where u is the number of contrasts that share some uninteresting effect. The issues highlighted by Nichols et al., have important implications for the design and analysis of cognitive conjunction studies and have motivated a change to the SPM software, that affords a test for the more general hypothesis k N u. This more general conjunction test is described.
Abstract Bistable perception follows from observing a static, ambiguous, (visual) stimulus with two possible interpretations. Here, we present an active (Bayesian) inference account of bistable perception and posit that perceptual transitions between different interpretations (i.e. inferences) of the same stimulus ensue from specific eye movements that shift the focus to a different visual feature. Formally, these inferences are a consequence of precision control that determines how confident beliefs are and change the frequency with which one can perceive—and alternate between—two distinct percepts. We hypothesized that there are multiple, but distinct, ways in which precision modulation can interact to give rise to a similar frequency of bistable perception. We validated this using numerical simulations of the Necker cube paradigm and demonstrate the multiple routes that underwrite the frequency of perceptual alternation. Our results provide an (enactive) computational account of the intricate precision balance underwriting bistable perception. Importantly, these precision parameters can be considered the computational homologs of particular neurotransmitters—i.e. acetylcholine, noradrenaline, dopamine—that have been previously implicated in controlling bistable perception, providing a computational link between the neurochemistry and perception.
This paper offers an active inference narrative that considers deeply-held social attitudes and beliefs in relation to the cognitive concept of zones of bounded surprisal (ZBS) proposed by Manrique and Walker (2023). It is argued that narrow ZBS band-widths characterise the discriminatory minds of people who see themselves as an in-group. They tend not to be indignant or outspoken, but, instead, acquiescent and silent, when they witness poor behaviour of those whom otherwise they regard as members of their in-group. Plausibly, when such behaviour harms other people, as, for instance, in racist or gender-based violence, its perpetrators have a very narrow ZBS band-width: one that likely is a characteristic of dehumanising minds. Because such perpetrators see themselves as members of an in-group with entitlement to control aspects of society, they humiliate or abuse out-groups to which they assign others, and have no compunction about violating their dignity or human rights. We briefly consider policies that could lessen the unwelcome social repercussions of the behaviour of people with discriminatory and dehumanising minds.
