Methods for modular modelling: Additive factors and cognitive neuropsychology

Beyond modular and non-modular states: theoretical considerations, exemplifications, and practical implications

The concept of modularity in neuropsychology remains a topic of significant debate, especially when considering complex, non-innate, hyper-learned, and adaptable modular systems. This paper critically examines the evolution of cognitive modularity, addressing the challenges of integrating foundational theories with recent empirical and theoretical developments. We begin by analyzing the contributions of Sternberg and Fodor, whose foundational work established the concept of specialized, encapsulated modules within cognitive processes, particularly in the domains of perception and language. Building on this, we explore Carruthers' theory of massive modularity, which extends the modular framework to broader cognitive functions, though we reject its application to central amodal systems, which are overarching and resistant to modularization. We also evaluate recent discoveries, such as mirror neurons and the neural reuse hypothesis, and their implications for traditional modularity models. Furthermore, we investigate the dynamic interactions between the Default Mode Network (DMN), Central Executive Network (CEN), and Salience Network (SN), highlighting their roles in shifting between automatic and controlled states. This exploration refines existing theoretical models, distinguishing innate systems, genetically predisposed ones, and those hyper-learned through working memory, as exemplified by the three-level model of Moscovitch and Umiltà. We address the blurred boundary between domain-specific and domain-general systems, proposing modular versus non-modular states-indexed by automaticity and mandatoriness-as key discriminators. This systematization, supported by empirical literature and our own research, provides a more stable framework for understanding modular systems, avoiding interpretive confusion across varying levels of complexity. These insights advance both theoretical understanding and practical applications in cognitive science.

Markov blankets in the brain

Recent characterisations of self-organising systems depend upon the presence of a 'Markov blanket': a statistical boundary that mediates the interactions between the inside and outside of a system. We leverage this idea to provide an analysis of partitions in neuronal systems. This is applicable to brain architectures at multiple scales, enabling partitions into single neurons, brain regions, and brain-wide networks. This treatment is based upon the canonical micro-circuitry used in empirical studies of effective connectivity, so as to speak directly to practical applications. The notion of effective connectivity depends upon the dynamic coupling between functional units, whose form recapitulates that of a Markov blanket at each level of analysis. The nuance afforded by partitioning neural systems in this way highlights certain limitations of 'modular' perspectives of brain function that only consider a single level of description.

The evolution of general intelligence

The presence of general intelligence poses a major evolutionary puzzle, which has led to increased interest in its presence in nonhuman animals. The aim of this review is to critically evaluate this question and to explore the implications for current theories about the evolution of cognition. We first review domain-general and domain-specific accounts of human cognition in order to situate attempts to identify general intelligence in nonhuman animals. Recent studies are consistent with the presence of general intelligence in mammals (rodents and primates). However, the interpretation of a psychometric g factor as general intelligence needs to be validated, in particular in primates, and we propose a range of such tests. We then evaluate the implications of general intelligence in nonhuman animals for current theories about its evolution and find support for the cultural intelligence approach, which stresses the critical importance of social inputs during the ontogenetic construction of survival-relevant skills. The presence of general intelligence in nonhumans implies that modular abilities can arise in two ways, primarily through automatic development with fixed content and secondarily through learning and automatization with more variable content. The currently best-supported model, for humans and nonhuman vertebrates alike, thus construes the mind as a mix of skills based on primary and secondary modules. The relative importance of these two components is expected to vary widely among species, and we formulate tests to quantify their strength.

Recognizing and identifying people: A neuropsychological review

Recognizing people is a classic example of a cognitive function that involves multiple processing stages and parallel routes of information. Neuropsychological data have provided important evidence for models of this process, particularly from case reports; however, the quality and extent of the data varies widely between studies. In this review we first discuss the requirements and logical basis of the types of neuropsychological evidence to support conclusions about the modules in this process. We then survey the adequacy of the current body of reports to address two key issues. First is the question of which cognitive operation generates a sense of familiarity: the current debate revolves around whether familiarity arises in modality-specific recognition units or later amodal processes. Key evidence on this point comes from the search for dissociations between familiarity for faces, voices and names. The second question is whether lesions can differentially affect the abilities to link diverse sources of person information (e.g., face, voice, name, biographic data). Dissociations of these linkages may favor a 'distributed-only' model of the organization of semantic knowledge, whereas a 'person-hub' model would predict uniform impairments of all linkages. While we conclude that there is reasonable evidence for dissociations in name, voice and face familiarity in regards to the first question, the evidence for or against dissociated linkages between information stores in regards to the second question is tenuous at best. We identify deficiencies in the current literature that should motivate and inform the design of future studies.

Disentangling the Role of Cortico-Basal Ganglia Loops in Top-Down and Bottom-Up Visual Attention: An Investigation of Attention Deficits in Parkinson Disease

It is solidly established that top-down (goal-driven) and bottom-up (stimulus-driven) attention mechanisms depend on distributed cortical networks, including prefrontal and frontoparietal regions. On the other hand, it is less clear whether the BG also contribute to one or the other of these mechanisms, or to both. The current study was principally undertaken to clarify this issue. Parkinson disease (PD), a neurodegenerative disorder primarily affecting the BG, has proven to be an effective model for investigating the contribution of the BG to different brain functions; therefore, we set out to investigate deficits of top-down and bottom-up attention in a selected cohort of PD patients. With this objective in mind, we compared the performance on three computerized tasks of two groups of 12 parkinsonian patients (assessed without any treatment), one otherwise pharmacologically treated and the other also surgically treated, with that of a group of controls. The main behavioral tool for our study was an attentional capture task, which enabled us to tap the competition between top-down and bottom-up mechanisms of visual attention. This task was suitably combined with a choice RT and a simple RT task to isolate any specific deficit of attention from deficits in motor response selection and initiation. In the two groups of patients, we found an equivalent increase of attentional capture but also comparable delays in target selection in the absence of any salient distractor (reflecting impaired top-down mechanisms) and movement initiation compared with controls. In contrast, motor response selection processes appeared to be prolonged only in the operated patients. Our results confirm that the BG are involved in both motor and cognitive domains. Specifically, damage to the BG, as it occurs in PD, leads to a distinct deficit of top-down control of visual attention, and this can account, albeit indirectly, for the enhancement of attentional capture, reflecting weakened ability of top-down mechanisms to antagonize bottom-up control.

On the definition and interpretation of voice selective activation in the temporal cortex

Regions along the superior temporal sulci and in the anterior temporal lobes have been found to be involved in voice processing. It has even been argued that parts of the temporal cortices serve as voice-selective areas. Yet, evidence for voice-selective activation in the strict sense is still missing. The current fMRI study aimed at assessing the degree of voice-specific processing in different parts of the superior and middle temporal cortices. To this end, voices of famous persons were contrasted with widely different categories, which were sounds of animals and musical instruments. The argumentation was that only brain regions with statistically proven absence of activation by the control stimuli may be considered as candidates for voice-selective areas. Neural activity was found to be stronger in response to human voices in all analyzed parts of the temporal lobes except for the middle and posterior STG. More importantly, the activation differences between voices and the other environmental sounds increased continuously from the mid-posterior STG to the anterior MTG. Here, only voices but not the control stimuli excited an increase of the BOLD response above a resting baseline level. The findings are discussed with reference to the function of the anterior temporal lobes in person recognition and the general question on how to define selectivity of brain regions for a specific class of stimuli or tasks. In addition, our results corroborate recent assumptions about the hierarchical organization of auditory processing building on a processing stream from the primary auditory cortices to anterior portions of the temporal lobes.

How to discover modules in mind and brain: the curse of nonlinearity, and blessing of neuroimaging. A comment on Sternberg (2011)

Sternberg (2011) elegantly formalizes how certain sets of hypotheses, specifically modularity and pure or composite measures, imply certain patterns of behavioural and neuroimaging data. Experimentalists are often interested in the converse, however: whether certain patterns of data distinguish certain hypotheses, specifically whether more than one module is involved. In this case, there is a striking reversal of the relative value of the data patterns that Sternberg considers. Foremost, the example of additive effects of two factors on one composite measure becomes noninformative for this converse question. Indeed, as soon as one allows for nonlinear measurement functions and nonlinear module processes, even a cross-over interaction between two factors is noninformative in this respect. Rather, one requires more than one measure, from which certain data patterns do provide strong evidence for multiple modules, assuming only that the measurement functions are monotonic. If two measures are not monotonically related to each other across the levels of one or more experimental factors, then one has evidence for more than one module (i.e., more than one nonmonotonic transform). Two special cases of this are illustrated here: a “reversed association” between two measures across three levels of a single factor, and Sternberg's example of selective effects of two factors on two measures. Fortunately, functional neuroimaging methods normally do provide multiple measures over space (e.g., functional magnetic resonance imaging, fMRI) and/or time (e.g., electroencephalography, EEG). Thus to the extent that brain modules imply mind modules (i.e., separate processors imply separate processes), the performance data offered by functional neuroimaging are likely to be more powerful in revealing modules than are the single behavioural measures (such as accuracy or reaction time, RT) traditionally considered in psychology.

The specialization of function: cognitive and neural perspectives

A unifying theme that cuts across all research areas and techniques in the cognitive and brain sciences is whether there is specialization of function at levels of processing that are "abstracted away" from sensory inputs and motor outputs. Any theory that articulates claims about specialization of function in the mind/brain confronts the following types of interrelated questions, each of which carries with it certain theoretical commitments. What methods are appropriate for decomposing complex cognitive and neural processes into their constituent parts? How do cognitive processes map onto neural processes, and at what resolution are they related? What types of conclusions can be drawn about the structure of mind from dissociations observed at the neural level, and vice versa? The contributions that form this Special Issue of Cognitive Neuropsychology represent recent reflections on these and other issues from leading researchers in different areas of the cognitive and brain sciences.