Deep neural networks are not a single hypothesis but a language for expressing computational hypotheses.

An ideal vision model accounts for behavior and neurophysiology in both naturalistic conditions and designed lab experiments. Unlike psychological theories, artificial neural networks (ANNs) actually perform visual tasks and generate testable predictions for arbitrary inputs. These advantages enable ANNs to engage the entire spectrum of the evidence. Failures of particular models drive progress in a vibrant ANN research program of human vision.

The neuroconnectionist research programme.

Artificial neural networks (ANNs) inspired by biology are beginning to be widely used to model behavioural and neural data, an approach we call 'neuroconnectionism'. ANNs have been not only lauded as the current best models of information processing in the brain but also criticized for failing to account for basic cognitive functions. In this Perspective article, we propose that arguing about the successes and failures of a restricted set of current ANNs is the wrong approach to assess the promise of neuroconnectionism for brain science. Instead, we take inspiration from the philosophy of science, and in particular from Lakatos, who showed that the core of a scientific research programme is often not directly falsifiable but should be assessed by its capacity to generate novel insights. Following this view, we present neuroconnectionism as a general research programme centred around ANNs as a computational language for expressing falsifiable theories about brain computation. We describe the core of the programme, the underlying computational framework and its tools for testing specific neuroscientific hypotheses and deriving novel understanding. Taking a longitudinal view, we review past and present neuroconnectionist projects and their responses to challenges and argue that the research programme is highly progressive, generating new and otherwise unreachable insights into the workings of the brain.

Distinguishing Old From New Referents During Discourse Comprehension: Evidence From ERPs and Oscillations.

In this EEG study, we used pre-registered and exploratory ERP and time-frequency analyses to investigate the resolution of anaphoric and non-anaphoric noun phrases during discourse comprehension. Participants listened to story contexts that described two antecedents, and subsequently read a target sentence with a critical noun phrase that lexically matched one antecedent ('old'), matched two antecedents ('ambiguous'), partially matched one antecedent in terms of semantic features ('partial-match'), or introduced another referent (non-anaphoric, 'new'). After each target sentence, participants judged whether the noun referred back to an antecedent (i.e., an 'old/new' judgment), which was easiest for ambiguous nouns and hardest for partially matching nouns. The noun-elicited N400 ERP component demonstrated initial sensitivity to repetition and semantic overlap, corresponding to repetition and semantic priming effects, respectively. New and partially matching nouns both elicited a subsequent frontal positivity, which suggested that partially matching anaphors may have been processed as new nouns temporarily. ERPs in an even later time window and ERPs time-locked to sentence-final words suggested that new and partially matching nouns had different effects on comprehension, with partially matching nouns incurring additional processing costs up to the end of the sentence. In contrast to the ERP results, the time-frequency results primarily demonstrated sensitivity to noun repetition, and did not differentiate partially matching anaphors from new nouns. In sum, our results show the ERP and time-frequency effects of referent repetition during discourse comprehension, and demonstrate the potentially demanding nature of establishing the anaphoric meaning of a novel noun.

A Young Scientists' Perspective on DBS: A Plea for an International DBS Organization.

Our think tank tasked by the Dutch Health Council, consisting of Radboud University Nijmegen Honours Academy students with various backgrounds, investigated the implications of Deep Brain Stimulation (DBS) for psychiatric patients. During this investigation, a number of methodological, ethical and societal difficulties were identified. We consider these difficulties to be a reflection of a still fragmented field of research that can be overcome with improved organization and communication. To this effect, we suggest that it would be useful to found a centralized DBS organization. Such an organization makes it possible to 1) set up and maintain a repository, 2) facilitate DBS studies with a larger sample size, 3) improve communication amongst researchers, clinicians and ethical committees, and 4) improve communication between DBS experts and the public at large.