Clarifying status of DNNs as models of human vision.

On several key issues we agree with the commentators. Perhaps most importantly, everyone seems to agree that psychology has an important role to play in building better models of human vision, and (most) everyone agrees (including us) that deep neural networks (DNNs) will play an important role in modelling human vision going forward. But there are also disagreements about what models are for, how DNN-human correspondences should be evaluated, the value of alternative modelling approaches, and impact of marketing hype in the literature.

Successes and critical failures of neural networks in capturing human-like speech recognition.

Natural and artificial audition can in principle acquire different solutions to a given problem. The constraints of the task, however, can nudge the cognitive science and engineering of audition to qualitatively converge, suggesting that a closer mutual examination would potentially enrich artificial hearing systems and process models of the mind and brain. Speech recognition - an area ripe for such exploration - is inherently robust in humans to a number transformations at various spectrotemporal granularities.

A Computational Complexity Perspective on Segmentation as a Cognitive Subcomputation.

Computational feasibility is a widespread concern that guides the framing and modeling of natural and artificial intelligence. The specification of cognitive system capacities is often shaped by unexamined intuitive assumptions about the search space and complexity of a subcomputation. However, a mistaken intuition might make such initial conceptualizations misleading for what empirical questions appear relevant later on.

Deep problems with neural network models of human vision.

Deep neural networks (DNNs) have had extraordinary successes in classifying photographic images of objects and are often described as the best models of biological vision. This conclusion is largely based on three sets of findings: (1) DNNs are more accurate than any other model in classifying images taken from various datasets, (2) DNNs do the best job in predicting the pattern of human errors in classifying objects taken from various behavioral datasets, and (3) DNNs do the best job in predicting brain signals in response to images taken from various brain datasets (e.g.

Dynamic neurocognitive changes in interoception after heart transplant.

Heart-brain integration dynamics are critical for interoception (i.e. the sensing of body signals).

Against the Epistemological Primacy of the Hardware: The Brain from Inside Out, Turned Upside Down.

Before he wrote the recent book , the neuroscientist György Buzsáki previewed some of the arguments in a paper written 20 years ago ("The brain-cognitive behavior problem: a retrospective"), now finally published. The principal focus of the paper is the relationship between neuroscience and psychology. The direction in which that research had proceeded, and continues now, is, in his view, fundamentally misguided.

Time to Face Language: Embodied Mechanisms Underpin the Inception of Face-Related Meanings in the Human Brain.

In construing meaning, the brain recruits multimodal (conceptual) systems and embodied (modality-specific) mechanisms. Yet, no consensus exists on how crucial the latter are for the inception of semantic distinctions. To address this issue, we combined electroencephalographic (EEG) and intracranial EEG (iEEG) to examine when nouns denoting facial body parts (FBPs) and nonFBPs are discriminated in face-processing and multimodal networks.

Consistent Gradient of Performance and Decoding of Stimulus Type and Valence From Local and Network Activity.

The individual differences approach focuses on the variation of behavioral and neural signatures across subjects. In this context, we searched for intracranial neural markers of performance in three individuals with distinct behavioral patterns (efficient, borderline, and inefficient) in a dual-valence task assessing facial and lexical emotion recognition. First, we performed a preliminary study to replicate well-established evoked responses in relevant brain regions.

Reading Shakespearean tropes in a foreign tongue: Age of L2 acquisition modulates neural responses to functional shifts.

Functional shifts (FSs) - morphosyntactically marked words evoking coherent but novel meanings - are ubiquitous in English and, specially, in Shakespearean literature. While their neural signatures have been explored in native speakers, no study has targeted foreign-language users, let alone comparing early and late bilinguals. Here, we administered a validated FS paradigm to subjects from both populations and evaluated time-frequency modulations evoked by FS and control sentences.

Altered neural signatures of interoception in multiple sclerosis.

Multiple sclerosis (MS) patients present several alterations related to sensing of bodily signals. However, no specific neurocognitive impairment has yet been proposed as a core deficit underlying such symptoms. We aimed to determine whether MS patients present changes in interoception-that is, the monitoring of autonomic bodily information-a process that might be related to various bodily dysfunctions.

Attention, in and Out: Scalp-Level and Intracranial EEG Correlates of Interoception and Exteroception.

Interoception, the monitoring of visceral signals, is often presumed to engage attentional mechanisms specifically devoted to inner bodily sensing. In fact, most standardized interoceptive tasks require directing attention to internal signals. However, most studies in the field have failed to compare attentional modulations between internally- and externally-driven processes, thus probing blind to the specificity of the former.

Enhanced Working Memory Binding by Direct Electrical Stimulation of the Parietal Cortex.

Recent works evince the critical role of visual short-term memory (STM) binding deficits as a clinical and preclinical marker of Alzheimer's disease (AD). These studies suggest a potential role of posterior brain regions in both the neurocognitive deficits of Alzheimer's patients and STM binding in general. Thereupon, we surmised that stimulation of the posterior parietal cortex (PPC) might be a successful approach to tackle working memory deficits in this condition, especially at early stages.

Convergence of interoception, emotion, and social cognition: A twofold fMRI meta-analysis and lesion approach.

Guided by indirect evidence, recent approaches propose a tripartite crosstalk among interoceptive signaling, emotional regulation, and low-level social cognition. Here we examined the neurocognitive convergence of such domains. First, we performed three meta-analyses of functional magnetic resonance imaging studies to identify which areas are consistently coactivated by these three systems.

Social neuroscience: undoing the schism between neurology and psychiatry.

Multiple disorders once jointly conceived as "nervous diseases" became segregated by the distinct institutional traditions forged in neurology and psychiatry. As a result, each field specialized in the study and treatment of a subset of such conditions. Here we propose new avenues for interdisciplinary interaction through a triangulation of both fields with social neuroscience.

How language flows when movements don't: An automated analysis of spontaneous discourse in Parkinson's disease.

To assess the impact of Parkinson's disease (PD) on spontaneous discourse, we conducted computerized analyses of brief monologues produced by 51 patients and 50 controls. We explored differences in semantic fields (via latent semantic analysis), grammatical choices (using part-of-speech tagging), and word-level repetitions (with graph embedding tools). Although overall output was quantitatively similar between groups, patients relied less heavily on action-related concepts and used more subordinate structures.

Predictive coding in autism spectrum disorder and attention deficit hyperactivity disorder.

Predictive coding has been proposed as a framework to understand neural processes in neuropsychiatric disorders. We used this approach to describe mechanisms responsible for attentional abnormalities in autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD). We monitored brain dynamics of 59 children (8-15 yr old) who had ASD or ADHD or who were control participants via high-density electroencephalography.

Heart evoked potential triggers brain responses to natural affective scenes: A preliminary study.

The relationship between ongoing brain interoceptive signals and emotional processes has been addressed only indirectly through external stimulus-locked measures. In this study, an internal body trigger (heart evoked potential, HEP) was used to measure ongoing internally triggered signals during emotional states. We employed high-density electroencephalography (hd-EEG), source reconstruction analysis, and behavioral measures to assess healthy participants watching emotion-inducing video-clips (positive, negative, and neutral emotions).

Disentangling interoception: insights from focal strokes affecting the perception of external and internal milieus.

Interoception is the moment-to-moment sensing of the physiological condition of the body. The multimodal sources of interoception can be classified into two different streams of afferents: an internal pathway of signals arising from core structures (i.e.

Hypnotic suggestion: a test for the voluntary action problem.

To study voluntary action a dissociation must be established between the somatic event (e.g, motor action) and what the agent voluntarily does (e.g, handing a tool to a friend).