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  • Psychology
    Chaz Firestone (Johns Hopkins University)
    Seeing “How”

    MB 7/159 & Zoom Universitätsstr. 150, Bochum, NRW, Germany

    What is perception? The most intuitive and influential answer to this question has long been the one given by David Marr: To see the world is “to know what is where by looking” — to transform light into representations of objects and their features, located somewhere in space. But is this all that perception delivers? Consider the figure to the right; certainly you see some colored shapes, as well as where they are located. Yet, beyond this, you may also see how they relate to one another: The green piece can fit into the others, and even create a new object with a shape of its own.
    In this talk, I present evidence that perception extracts relations between objects in much the same way as it processes the objects themselves, and that these relations are abstract, structured, and surprisingly sophisticated. We’ll explore (and experience) the perception of several sophisticated relations between objects, including combining, supporting, containing, covering, and fastening — as well as relational “illusions” in which objects appear to interact with mysteriously invisible entities. Together, this work suggests that we see not only “what” and “where”, but also “how”.

  • Psychology
    Linda Onnasch (TU Berlin) & Eileen Roesler (George Mason University)
    Trust(worthiness) Issues with Trust in Human-Robot Interaction

    IA 02/461

    Abstract: Trust is one of the most popular concepts in Human–Robot Interaction (HRI)—but also one of the most misunderstood. In this talk, we argue that HRI research has oversimplified trust by treating perceived trustworthiness as a stand-in for trust itself, often ignoring the risk and vulnerability that make trust meaningful in the first place. By revisiting trust theory, measurements, and common research
    paradigms, we uncover key “trust issues” in HRI and propose ways to build more rigorous and insightful future research on trust in HRI.

  • Philosophy
    Alexander Klein (McMaster University & Betrand Russell Research Center)
    Why Can’t You See Your Own Eyes Move in a Mirror? E. B. Holt’s Experimental Psychology as Pre-History of New Realism

    GA1/128 , Germany

    E. B. Holt’s dissertation, The Motor Element in Vision, earned him the PhD in 1901 for empirical
    research he conducted at Harvard’s psychology laboratory under Hugo Münsterberg. Later
    published in polished form as “Eye-Movement and Central Anaesthesia” (Langfeld 1946), the
    work seeks to explain why visual awareness is suppressed during voluntary eye movement (more
    precisely, during what today would be called voluntary saccades; Holt 1903). A pointed
    illustration of this phenomenon had already been documented in the psychological literature by
    the late 19th century: it is difficult, under normal conditions, to see your own eyeball move in a
    mirror. Holt’s dissertation project is to experimentally isolate this phenomenon and then explain
    why it occurs.

    In this talk, I shall examine Holt’s experimental work, which is interesting for several reasons.
    Holt is a founding member of the New Realists, and an important influence (along with James)
    on Russell’s neutral monism. Although philosophers often think of New Realism and Russellian
    monism as quite conceptual, we will find that these movements have at least one important root
    in experimental psychology. In particular, I will show that Holt’s philosophical thinking about
    the relationship between consciousness and the body (as exemplified in later works like Holt
    1912, 1914) took early shape in the context of his experimental work. Second, Holt’s
    interpretation of his own experiments explicitly appealed to Münsterberg’s “action theory” of
    consciousness, which is a step more radical than James’s better-known work. In James’s catch-
    phrase, “consciousness is motor,” the “is” is the is of predication, not identity (Klein 2025); but
    Münsterberg argued that contents become conscious in virtue of stimuli getting connected in the
    right way with motor discharge. Hence Holt’s experimental work can be understood as an
    important step in the radicalization of philosophical and psychological views associated with
    James’s early work on mind, moving such functionalist thinking down the path towards
    behaviorism.

  • Fellow Lecture Neuroscience
    Genela Morris (Tel Aviv)
    Separate neurons for gains and losses: single-neuron recordings in the human brain

    NB 3/57
    Fellow Talk

    Human behavior is shaped by two opposing motivational drives: accumulation of reward and avoidance of harm. It is still unsettled whether, in the human brain, gains and losses are represented separately, enabling independent pursuit of both goals, or conjointly, by a collective pursuit on a common value scale. Human decision making is characterized by fundamental asymmetries between gain and loss processing, hinting at separate representation. Functional imaging studies nevertheless mostly favor a unified scale interpretation. We hypothesized that the poor spatial resolution of fMRI may account for these discrepancies: a voxel averages hundreds of thousands of neurons, so two intermingled populations with opposite preferences are indistinguishable from one bidirectional population. Here, we show that learning signals for gain and loss contexts are encoded by functionally separate neuronal populations that coexist within the same anatomical structures. We analyzed single-unit activity from 370 single neurons in prefrontal cortex, anterior cingulate cortex, temporal cortex, hippocampus and amygdala in 17 patients implanted with intracranial electrodes for epilepsy monitoring, while they performed a probabilistic choice task with separate gain and loss contexts. Trial-by-trial prediction errors were estimated from a reinforcement learning model fit to each participant’s choices. Gain and loss prediction errors were primarily represented by distinct, intermingled neuronal subpopulations, each selectively encoding context-specific prediction errors. A small subset of neurons encoded prediction errors in both contexts, frequently with opposite codes. Participants with greater segregation between the two codes showed a larger asymmetry in learning, with higher error and exploration rates in loss contexts than in gain contexts. Gain and loss errors therefore appear to be implemented through independent but anatomically interleaved neural channels, allowing independent processing pathways. This separation may offer insights into psychopathologies of biased valuation.